database_dump.txt

--
-- PostgreSQL database dump
--

-- Dumped from database version 14.2
-- Dumped by pg_dump version 14.2

SET statement_timeout = 0;
SET lock_timeout = 0;
SET idle_in_transaction_session_timeout = 0;
SET client_encoding = 'UTF8';
SET standard_conforming_strings = on;
SELECT pg_catalog.set_config('search_path', '', false);
SET check_function_bodies = false;
SET xmloption = content;
SET client_min_messages = warning;
SET row_security = off;

SET default_tablespace = '';

SET default_table_access_method = heap;

--
-- Name: country; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.country (
    country_key integer NOT NULL,
    name character varying(255),
    region character varying(255),
    continent character varying(255),
    currency character varying(255),
    capital character varying(255),
    total_population integer,
    birth_rate double precision,
    gross_national_income double precision,
    life_expectancy_at_birth double precision,
    labor_force_total integer,
    human_capital_index integer,
    population_grown_annual double precision
);


ALTER TABLE public.country OWNER TO postgres;

--
-- Name: education; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.education (
    education_key integer NOT NULL,
    total_literacy_rate double precision,
    male_literacy_rate double precision,
    female_literacy_rate double precision,
    primary_school_enrollment double precision,
    secondary_school_enrollment double precision,
    post_secondary_school_enrollment double precision,
    public_education_spending double precision,
    pop_compuslory_school_age_total integer,
    pop_offical_entrance_age_primary_total integer,
    pop_offical_entrance_age_secondary_total integer,
    teachers_primary_total integer,
    teachers_secondary_total integer
);


ALTER TABLE public.education OWNER TO postgres;

--
-- Name: event; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.event (
    event_key integer NOT NULL,
    name character varying(255),
    disaster_type character varying(255),
    start_day integer,
    end_day integer,
    start_month integer,
    end_month integer,
    start_year integer,
    end_year integer,
    disaster_subgroup character varying(255),
    total_deaths integer,
    no_injured integer,
    no_affected integer
);


ALTER TABLE public.event OWNER TO postgres;

--
-- Name: fact_table; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.fact_table (
    month_key integer,
    country_key integer,
    education_key integer,
    population_key integer,
    quality_of_life_key integer,
    health_key integer,
    event_key integer,
    quality_of_life integer,
    development_index integer,
    human_development_index integer
);


ALTER TABLE public.fact_table OWNER TO postgres;

--
-- Name: health; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.health (
    health_key integer NOT NULL,
    domestic_general_government_health_expenditure double precision,
    hospital_beds double precision,
    immunization_hepb3 double precision,
    immunization_dpt double precision,
    immunization_measles double precision,
    immunization_pol3 double precision,
    number_of_surgical_procedures double precision,
    number_of_infant_deaths double precision,
    number_of_stillbirths double precision,
    number_of_deaths_ages_20_24 double precision,
    physicians_per_1000 double precision,
    prevalence_of_overweight double precision,
    diabetes_prevalence double precision,
    prevalence_of_hiv_total double precision,
    adults_living_with_hiv double precision,
    adults_newly_infected_with_hiv double precision,
    children_living_with_hiv double precision,
    children_newly_infected_with_hiv double precision
);


ALTER TABLE public.health OWNER TO postgres;

--
-- Name: month; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.month (
    month_key integer NOT NULL,
    name character varying(255),
    month integer,
    quarter integer,
    year integer,
    decade integer
);


ALTER TABLE public.month OWNER TO postgres;

--
-- Name: population; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.population (
    population_key integer NOT NULL,
    life_expectancy_at_birth_f double precision,
    life_expectancy_at_birth_m double precision,
    life_expectancy_at_birth_t double precision,
    net_migration integer,
    population_ages_0_14 integer,
    population_ages_15_19 integer,
    population_ages_20_24 integer,
    population_ages_24_29 integer,
    population_ages_30_34 integer,
    population_ages_35_39 integer,
    population_ages_40_44 integer,
    population_ages_45_49 integer,
    population_ages_50_54 integer,
    population_ages_55_59 integer,
    population_ages_60_64 integer,
    population_ages_65_up integer,
    rural_population double precision,
    rural_population_growth_rate double precision,
    rural_poverty_rate double precision,
    urban_population double precision,
    urban_population_growth_rate double precision,
    urban_poverty_rate double precision
);


ALTER TABLE public.population OWNER TO postgres;

--
-- Name: quality_of_life; Type: TABLE; Schema: public; Owner: postgres
--

CREATE TABLE public.quality_of_life (
    quality_of_life_key integer NOT NULL,
    access_to_drinking_water double precision,
    access_to_sanitation double precision,
    access_to_basic_handwashing_facilities double precision,
    unemployment_rate_f double precision,
    unemployment_rate_m double precision,
    unemployment_rate_t double precision,
    maternal_leave_benefits double precision,
    access_to_electricity_total double precision,
    access_to_electricity_urban double precision,
    access_to_electricity_rural double precision,
    part_time_employment_t double precision,
    part_time_employment_f double precision,
    part_time_employment_m double precision
);


ALTER TABLE public.quality_of_life OWNER TO postgres;

--
-- Data for Name: country; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.country (country_key, name, region, continent, currency, capital, total_population, birth_rate, gross_national_income, life_expectancy_at_birth, labor_force_total, human_capital_index, population_grown_annual) FROM stdin;
0	Canada	North America	North America	Canadian Dollar	Ottawa	32243753	10.6	34810	80.1926829268293	20788261	\N	0.944466927450734
1	Canada	North America	North America	Canadian Dollar	Ottawa	32571174	10.9	38510	80.3439024390244	20492683	\N	1.01033450270045
2	Canada	North America	North America	Canadian Dollar	Ottawa	32889025	11.2	43090	80.5439024390244	20396697	\N	0.971135141368055
3	Canada	North America	North America	Canadian Dollar	Ottawa	33247118	11.3	45650	80.6951219512195	20218270	\N	1.08290711607014
4	Canada	North America	North America	Canadian Dollar	Ottawa	33628895	11.3	43230	80.9951219512195	19955331	\N	1.14175809912162
5	Canada	North America	North America	Canadian Dollar	Ottawa	34004889	11.1	44490	81.2463414634146	19747709	1	1.11186407517168
6	Canada	North America	North America	Canadian Dollar	Ottawa	34339328	11	47190	81.4487804878049	19629145	\N	0.978697786570341
7	Canada	North America	North America	Canadian Dollar	Ottawa	34714222	11	51080	81.6487804878049	19546552	\N	1.08581726304756
8	Canada	North America	North America	Canadian Dollar	Ottawa	35082954	10.8	52800	81.7487804878049	17821886	\N	1.05659125917789
9	Canada	North America	North America	Canadian Dollar	Ottawa	35437435	10.8	52200	81.8	19322866	\N	1.00533757867378
10	Canada	North America	North America	Canadian Dollar	Ottawa	35702908	10.7	47590	81.9	19147395	\N	0.746339477969813
11	Canada	North America	North America	Canadian Dollar	Ottawa	36109487	10.6	43890	81.9	19001081	\N	1.13234865466606
12	Canada	North America	North America	Canadian Dollar	Ottawa	36545295	10.3	42900	81.9	18799155	1	1.19968215419992
13	Canada	North America	North America	Canadian Dollar	Ottawa	37065178	10.1	45080	82.0487804878049	18667574	1	1.412548033188
14	Canada	North America	North America	Canadian Dollar	Ottawa	37593384	9.9	46550	82.0487804878049	18379605	\N	1.41501469953534
15	Canada	North America	North America	Canadian Dollar	Ottawa	\N	\N	43580	\N	18030705	1	1.08959148655862
16	United States	North America	North America	U.S. Dollar	Washington D.C	295516599	14	46180	77.4878048780488	166355636	\N	0.921713167161207
17	United States	North America	North America	U.S. Dollar	Washington D.C	298379912	14.3	47850	77.6878048780488	163738061	\N	0.964253917136075
18	United States	North America	North America	U.S. Dollar	Washington D.C	301231207	14.3	48520	77.9878048780488	164634753	\N	0.951055242772428
19	United States	North America	North America	U.S. Dollar	Washington D.C	304093966	14	49090	78.0390243902439	163395307	\N	0.945865287282592
20	United States	North America	North America	U.S. Dollar	Washington D.C	306771529	13.5	47830	78.390243902439	161836238	\N	0.876651298802912
21	United States	North America	North America	U.S. Dollar	Washington D.C	309327143	13	49140	78.5414634146342	159912569	1	0.829616674709795
22	United States	North America	North America	U.S. Dollar	Washington D.C	311583481	12.7	50630	78.6414634146341	158910317	\N	0.726786704810745
23	United States	North America	North America	U.S. Dollar	Washington D.C	313877662	12.6	52780	78.7414634146342	158252925	\N	0.733599941250847
24	United States	North America	North America	U.S. Dollar	Washington D.C	316059947	12.4	53980	78.7414634146342	151976098	\N	0.692860276624581
25	United States	North America	North America	U.S. Dollar	Washington D.C	318386329	12.5	55800	78.8414634146341	157841889	\N	0.733361519937424
26	United States	North America	North America	U.S. Dollar	Washington D.C	320738994	12.4	56640	78.690243902439	157163170	\N	0.73621730882542
27	United States	North America	North America	U.S. Dollar	Washington D.C	323071755	12.2	57130	78.5390243902439	157111093	\N	0.724676067451429
28	United States	North America	North America	U.S. Dollar	Washington D.C	325122128	11.8	59240	78.5390243902439	157079943	1	0.63264399508256
29	United States	North America	North America	U.S. Dollar	Washington D.C	326838199	11.6	63490	78.6390243902439	156907793	1	0.526435395564053
30	United States	North America	North America	U.S. Dollar	Washington D.C	328329953	11.4	65970	78.7878048780488	155224880	\N	0.455381285963537
31	United States	North America	North America	U.S. Dollar	Washington D.C	\N	\N	64530	\N	153855509	1	0.350911063312921
32	Mexico	North America	North America	Mexican Peso	Mexico City	106005199	21.741	8050	75.3	56596004	\N	1.4158169793862
33	Mexico	North America	North America	Mexican Peso	Mexico City	107560155	21.343	8690	75.296	53080123	\N	1.4562132376675
34	Mexico	North America	North America	Mexican Peso	Mexico City	109170503	20.973	9250	75.255	55190039	\N	1.48606353186843
35	Mexico	North America	North America	Mexican Peso	Mexico City	110815272	20.635	9780	75.194	54096291	\N	1.49536909755127
36	Mexico	North America	North America	Mexican Peso	Mexico City	112463886	20.327	8820	75.128	53507498	\N	1.47675580253545
37	Mexico	North America	North America	Mexican Peso	Mexico City	114092961	20.042	9040	75.065	52732562	1	1.43814066910139
38	Mexico	North America	North America	Mexican Peso	Mexico City	115695468	19.766	9310	75.011	51780845	\N	1.39478996981758
39	Mexico	North America	North America	Mexican Peso	Mexico City	117274156	19.488	10050	74.966	51318641	\N	1.35529442643505
40	Mexico	North America	North America	Mexican Peso	Mexico City	118827158	19.198	10270	74.93	42869547	\N	1.31555760676608
41	Mexico	North America	North America	Mexican Peso	Mexico City	120355137	18.892	10500	74.908	50512846	\N	1.27768636604222
42	Mexico	North America	North America	Mexican Peso	Mexico City	121858251	18.573	10160	74.904	49035908	\N	1.24116450246976
43	Mexico	North America	North America	Mexican Peso	Mexico City	123333379	18.245	9390	74.917	47982609	\N	1.20325950587092
44	Mexico	North America	North America	Mexican Peso	Mexico City	124777326	17.918	8920	74.947	47176107	1	1.16396694963579
45	Mexico	North America	North America	Mexican Peso	Mexico City	126190782	17.602	9180	74.992	46199021	1	1.12641479134149
46	Mexico	North America	North America	Mexican Peso	Mexico City	127575529	17.297	9470	75.054	45304973	\N	1.09136688717461
47	Mexico	North America	North America	Mexican Peso	Mexico City	\N	\N	8480	\N	44352857	1	1.05824003448927
48	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	226289468	21.765	1220	67.334	136202238	\N	1.33630464499704
49	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	229318262	21.624	1380	67.717	136459585	\N	1.32958175171436
50	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	232374239	21.448	1600	68.105	133000453	\N	1.32383420748243
51	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	235469755	21.251	1940	68.485	129127477	\N	1.32333051767653
52	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	238620554	21.034	2150	68.853	126206202	\N	1.32921737939261
53	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	241834226	20.795	2530	69.205	124807236	0	1.3377824768766
54	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	245115988	20.526	3010	69.542	122770335	\N	1.34790440280692
55	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	248451714	20.225	3580	69.866	120972115	\N	1.35169978721169
56	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	251805314	19.893	3730	70.179	102184327	\N	1.34077086414715
57	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	255128076	19.537	3620	70.481	120144188	\N	1.31094524538172
58	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	258383257	19.165	3430	70.768	117225410	\N	1.26782970253157
59	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	261556386	18.79	3400	71.035	114596174	\N	1.22059105826764
60	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	264650969	18.422	3530	71.282	112039660	1	1.17619742367279
61	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	267670549	18.072	3840	71.509	110890081	1	1.13450697951891
62	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	270625567	17.746	4050	71.716	108893086	\N	1.09792643725552
63	Indonesia	South East Asia	Asia	Indonesian Rupiah	Jakarta	\N	\N	3870	\N	103776784	1	1.06517898587775
64	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	19433604	47.453	1370	50.165	13116712	\N	3.53760476294198
65	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	20149905	47.215	1810	51.143	13415460	\N	3.61958411912021
66	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	20905360	46.92	2460	52.177	12659938	\N	3.68060116794567
67	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	21695636	46.563	3030	53.243	12223456	\N	3.71055489102729
68	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	22514275	46.143	3170	54.311	11804734	\N	3.70384181489182
69	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	23356247	45.656	3230	55.35	11402381	\N	3.67149333263444
70	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	24220660	45.102	3410	56.33	11004723	\N	3.63415021537353
71	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	25107925	44.493	4170	57.236	10621492	\N	3.59775453949706
72	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	26015786	43.847	4780	58.054	7971743	\N	3.55199742692341
73	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	26941773	43.182	5010	58.776	10252532	\N	3.49744741099259
74	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	27884380	42.52	4520	59.398	9898462	\N	3.43886936840162
75	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	28842482	41.882	3770	59.925	9556361	\N	3.37826943218091
76	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	29816769	41.281	3450	60.379	9211974	0	3.32215836256296
77	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	30809787	40.729	3210	60.782	8879695	0	3.2761445879162
78	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	31825299	40.232	2970	61.147	8560730	\N	3.24291402840967
79	Angola	Southern Africa	Africa	Angolan Kwanza	Luanda	\N	\N	2140	\N	8257189	0	3.21853035205175
80	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	13273355	26.147	460	63.088	9221528	\N	1.57088526587846
81	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	13477705	26.101	520	63.927	9185555	\N	1.52781964519231
82	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	13679953	26.05	590	64.697	9088032	\N	1.48946377519015
83	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	13883835	25.947	670	65.394	8957446	\N	1.4793737229702
84	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	14093605	25.767	700	66.014	8841029	\N	1.49959346560005
85	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	14312205	25.502	750	66.56	8450593	\N	1.53915213466393
86	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	14541421	25.166	810	67.043	8362550	\N	1.58885279806388
87	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	14780454	24.797	880	67.48	8183449	\N	1.63044345047096
88	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	15026330	24.422	970	67.888	6740643	\N	1.6498363404781
89	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	15274506	24.048	1020	68.273	8280172	\N	1.6381168470705
90	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	15521435	23.674	1060	68.637	8334043	\N	1.60368077118284
91	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	15766290	23.291	1140	68.977	8087213	\N	1.56521446599878
92	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	16009413	22.889	1230	69.289	7639032	0	1.53027452708458
93	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	16249795	22.464	1380	69.57	7408126	0	1.49034315597302
94	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	16486542	22.02	1530	69.823	7175247	\N	1.44641184190217
95	Cambodia	South East Asia	Asia	Cambodian Riel	Phnom Penh	\N	\N	1500	\N	6957261	0	1.39996509699246
96	Thailand	South East Asia	Asia	Thai Baht	Bangkok	65416189	12.87	2790	72.099	38777939	\N	0.645476031073619
97	Thailand	South East Asia	Asia	Thai Baht	Bangkok	65812540	12.632	3100	72.499	39036695	\N	0.604063162436286
98	Thailand	South East Asia	Asia	Thai Baht	Bangkok	66182064	12.407	3530	72.916	39029222	\N	0.559909199584795
99	Thailand	South East Asia	Asia	Thai Baht	Bangkok	66530980	12.188	3970	73.341	38609507	\N	0.525821416507964
100	Thailand	South East Asia	Asia	Thai Baht	Bangkok	66866834	11.971	4140	73.766	38766594	\N	0.503538550690529
101	Thailand	South East Asia	Asia	Thai Baht	Bangkok	67195032	11.757	4580	74.184	39026171	1	0.489622687570703
102	Thailand	South East Asia	Asia	Thai Baht	Bangkok	67518379	11.548	4950	74.593	39079265	\N	0.480052607326658
103	Thailand	South East Asia	Asia	Thai Baht	Bangkok	67835969	11.351	5520	74.992	39030418	\N	0.469272819846721
104	Thailand	South East Asia	Asia	Thai Baht	Bangkok	68144519	11.169	5720	75.378	37939157	\N	0.453815887976248
105	Thailand	South East Asia	Asia	Thai Baht	Bangkok	68438748	10.999	5760	75.747	40234291	\N	0.430842608467137
106	Thailand	South East Asia	Asia	Thai Baht	Bangkok	68714519	10.836	5710	76.091	40083149	\N	0.402136059408841
107	Thailand	South East Asia	Asia	Thai Baht	Bangkok	68971313	10.676	5700	76.403	38876587	\N	0.373014846949147
108	Thailand	South East Asia	Asia	Thai Baht	Bangkok	69209817	10.513	5970	76.683	39127730	1	0.345205219913361
109	Thailand	South East Asia	Asia	Thai Baht	Bangkok	69428454	10.344	6610	76.931	39082810	1	0.315406676202042
110	Thailand	South East Asia	Asia	Thai Baht	Bangkok	69625581	10.168	7260	77.15	38769324	\N	0.283525943067606
111	Thailand	South East Asia	Asia	Thai Baht	Bangkok	\N	\N	7040	\N	38013146	1	0.250165166562935
112	South Africa	Southern Africa	Africa	South African Rand	Cape Town	47880595	23.073	5610	53.447	22989511	\N	1.23774061841899
113	South Africa	Southern Africa	Africa	South African Rand	Cape Town	48489464	23.238	6310	53.795	21345809	\N	1.26362297174921
114	South Africa	Southern Africa	Africa	South African Rand	Cape Town	49119766	23.367	6630	54.452	22608291	\N	1.29149827532559
115	South Africa	Southern Africa	Africa	South African Rand	Cape Town	49779472	23.433	6660	55.36	22360602	\N	1.3341170229958
116	South Africa	Southern Africa	Africa	South African Rand	Cape Town	50477013	23.417	6510	56.46	21767744	\N	1.39153543190923
117	South Africa	Southern Africa	Africa	South African Rand	Cape Town	51216967	23.305	6880	57.669	21379123	0	1.45528193348191
118	South Africa	Southern Africa	Africa	South African Rand	Cape Town	52003759	23.097	7760	58.895	20542666	\N	1.52451405625199
119	South Africa	Southern Africa	Africa	South African Rand	Cape Town	52832659	22.815	8370	60.06	20110076	\N	1.58135367305518
120	South Africa	Southern Africa	Africa	South African Rand	Cape Town	53687125	22.483	8070	61.099	18550441	\N	1.60436736931238
121	South Africa	Southern Africa	Africa	South African Rand	Cape Town	54544184	22.113	7370	61.968	19550791	\N	1.58378739591921
122	South Africa	Southern Africa	Africa	South African Rand	Cape Town	55386369	21.719	6610	62.649	19095444	\N	1.53224277341692
123	South Africa	Southern Africa	Africa	South African Rand	Cape Town	56207649	21.314	5990	63.153	18827666	\N	1.47193342939738
124	South Africa	Southern Africa	Africa	South African Rand	Cape Town	57009751	20.908	5910	63.538	19114540	0	1.41694725378631
125	South Africa	Southern Africa	Africa	South African Rand	Cape Town	57792520	20.51	6340	63.857	19441243	0	1.36370321600461
126	South Africa	Southern Africa	Africa	South African Rand	Cape Town	58558267	20.129	6670	64.131	19146437	\N	1.31629200967216
127	South Africa	Southern Africa	Africa	South African Rand	Cape Town	\N	\N	6010	\N	18850913	0	1.27335626330668
128	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12076697	33.764	460	43.241	7156060	\N	0.471320321280555
129	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12155496	34.384	440	43.853	7204228	\N	0.650368522177336
130	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12255920	35.021	420	44.947	7028775	\N	0.822767237368314
131	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12379553	35.624	330	46.504	6909356	\N	1.00370744192155
132	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12526964	36.134	480	48.449	6802164	\N	1.18372810843137
133	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12697728	36.464	700	50.64	6709332	0	1.35396387573417
134	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	12894323	36.526	1060	52.896	6611175	\N	1.53640571630567
135	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	13115149	36.292	1260	55.032	6465320	\N	1.69808373055654
136	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	13350378	35.768	1320	56.897	5852903	\N	1.77767247608678
137	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	13586710	34.978	1370	58.41	6322675	\N	1.7547410030553
138	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	13814642	33.981	1390	59.534	6184085	\N	1.66369350951633
139	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	14030338	32.864	1390	60.294	6110955	\N	1.54929408793871
140	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	14236599	31.732	1350	60.812	6052658	0	1.45940581314681
141	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	14438812	30.676	1350	61.195	5999036	0	1.41038154233327
142	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	14645473	29.747	1210	61.49	5949276	\N	1.42114188586135
143	Zimbabwe	Southern Africa	Africa	Real Time Gross Settlement Dollar	Harare	\N	\N	1140	\N	5901376	0	1.47387141587655
\.


--
-- Data for Name: education; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.education (education_key, total_literacy_rate, male_literacy_rate, female_literacy_rate, primary_school_enrollment, secondary_school_enrollment, post_secondary_school_enrollment, public_education_spending, pop_compuslory_school_age_total, pop_offical_entrance_age_primary_total, pop_offical_entrance_age_secondary_total, teachers_primary_total, teachers_secondary_total) FROM stdin;
0	\N	\N	\N	97.3645706176758	101.391189575195	\N	4.76588010787964	4092573	368975	426980	\N	\N
1	\N	\N	\N	98.8806304931641	101.728248596191	\N	\N	4054588	361128	427609	\N	\N
2	\N	\N	\N	98.9664764404297	101.90348815918	63.6000595092773	4.7664098739624	4012842	356032	421977	\N	\N
3	\N	\N	\N	98.013313293457	102.344436645508	63.7673988342285	4.62612009048462	3961374	353599	412521	\N	\N
4	\N	\N	\N	99.0087966918945	102.734443664551	63.0657691955566	4.84057998657227	3905068	353547	403277	\N	\N
5	\N	\N	\N	98.6416015625	102.398483276367	61.6558494567871	5.356369972229	3851269	355584	393451	\N	\N
6	\N	\N	\N	98.1893692016602	103.348960876465	63.4673194885254	5.26205015182495	3807165	359040	384607	\N	\N
7	\N	\N	\N	99.5182800292969	109.987487792969	63.980770111084	\N	3794610	362975	383046	\N	\N
8	\N	\N	\N	100.340713500977	109.485992431641	65.3322982788086	\N	3785262	370329	381453	\N	\N
9	\N	\N	\N	101.536659240723	109.333099365234	65.612907409668	\N	3783967	379571	377140	\N	\N
10	\N	\N	\N	102.485076904297	110.35652923584	64.7869567871094	\N	3792501	389428	369202	\N	\N
11	\N	\N	\N	101.023872375488	112.514282226563	66.4391784667969	\N	3809992	397794	363467	\N	\N
12	\N	\N	\N	100.94367980957	113.76286315918	68.9225082397461	\N	3850892	400896	370148	\N	\N
13	\N	\N	\N	101.501091003418	114.123512268066	70.1130218505859	\N	3884643	400334	380333	\N	\N
14	\N	\N	\N	100.989753723145	114.333267211914	75.6988220214844	\N	3913933	397848	387874	\N	\N
15	\N	\N	\N	\N	\N	\N	\N	\N	395376	394591	\N	\N
16	\N	\N	\N	101.8740234375	95.0524826049805	80.6348266601563	\N	49682243	3822089	4293550	\N	\N
17	\N	\N	\N	\N	\N	\N	\N	49713141	3828153	4251162	\N	\N
18	\N	\N	\N	\N	\N	\N	\N	49768249	3891329	4196880	\N	\N
19	\N	\N	\N	\N	\N	\N	\N	49899954	4046402	4192002	\N	\N
20	\N	\N	\N	\N	\N	\N	\N	49809178	3988117	4159477	\N	\N
21	\N	\N	\N	\N	\N	\N	\N	49819384	4018200	4110576	\N	\N
22	\N	\N	\N	\N	\N	\N	\N	49806498	4062428	4125653	\N	\N
23	\N	\N	\N	\N	\N	\N	\N	49648974	4081627	4135866	\N	\N
24	\N	\N	\N	99.455436706543	96.1864929199219	88.7264175415039	\N	49602123	4106467	4206506	\N	\N
25	\N	\N	\N	99.6733779907227	96.9245376586914	88.6268692016602	\N	49617380	4146714	4136933	1687937	1638606
26	\N	\N	\N	100.299911499023	97.6525497436523	88.8894119262695	\N	49715732	4114053	4094386	1714415	1661375
27	\N	\N	\N	101.362861633301	98.7699279785156	88.8350524902344	\N	49698279	4000424	4104538	\N	\N
28	\N	\N	\N	101.821441650391	98.9523391723633	88.1673889160156	\N	49724657	4045867	4131553	1769451	1694959
29	\N	\N	\N	101.256561279297	99.2755813598633	88.2991790771484	\N	49701081	4052748	4150564	\N	\N
30	\N	\N	\N	100.981300354004	100.063430786133	87.8887100219727	\N	\N	\N	\N	\N	\N
31	\N	\N	\N	\N	\N	\N	\N	\N	\N	\N	\N	\N
32	91.6302719116211	93.1904067993164	90.2104110717773	108.60083770752	82.3040771484375	24.2164001464844	4.84568977355957	24608995	2251858	2228239	519112	593451
33	91.7345199584961	93.9011993408203	89.8345108032227	108.174766540527	84.0856018066406	24.7904300689697	4.69992017745972	24627787	2242275	2248436	521183	610387
34	92.7951736450195	94.4415130615234	91.3555526733398	108.799713134766	84.9070510864258	25.4210605621338	4.69050979614258	24654878	2239799	2252781	522733	620808
35	92.9255981445313	94.5921630859375	91.45361328125	109.424423217773	86.4275283813477	26.1120300292969	4.82006978988647	24686831	2245319	2245920	524517	635518
36	93.4418792724609	94.9165725708008	92.1162490844727	110.545280456543	85.9380111694336	26.5867290496826	5.18794012069702	24715370	2254432	2240778	528555	650513
37	93.0689392089844	94.3839416503906	91.8534164428711	110.633491516113	87.0699234008789	27.5634708404541	5.15922021865845	24732518	2262628	2231609	529599	652140
38	93.5199813842773	94.7827682495117	92.3382797241211	110.540756225586	88.1901779174805	28.3414993286133	5.10564994812012	24724507	2264212	2223740	531256	669583
39	94.228401184082	95.3916320800781	93.1792373657227	110.413452148438	90.6671981811523	29.4718399047852	5.10309982299805	31447472	2263229	2228149	533866	684249
40	93.9628524780273	95.1121063232422	92.903938293457	109.441482543945	93.3275527954102	30.3000392913818	4.69605016708374	31407043	2256134	2239593	575337	683411
41	94.5558776855469	95.6204681396484	93.5913391113281	108.005752563477	97.3433837890625	31.0941390991211	5.25747013092041	31358984	2245666	2248138	573238	782545
42	94.472282409668	95.5493316650391	93.4854965209961	106.606109619141	100.832740783691	31.8190402984619	5.22942018508911	31318900	2234718	2257952	574276	813747
43	94.859619140625	95.8448181152344	93.9685211181641	106.277732849121	102.40406036377	38.4333801269531	4.90681982040405	31306937	2227103	2264619	574210	830578
44	94.9727783203125	95.8723678588867	94.1657562255859	105.770011901855	104.385032653809	40.2289581298828	4.51821994781494	31315892	2226776	2258855	573284	827017
45	95.3799133300781	96.2329025268555	94.6080474853516	105.02806854248	105.103363037109	41.5228004455566	4.25442981719971	31340326	2231977	2247894	571520	833944
46	\N	\N	\N	104.655822753906	104.647239685059	42.8306999206543	\N	31362235	2239200	2238965	\N	\N
47	95.2478485107422	96.0587463378906	94.4951324462891	\N	\N	\N	\N	\N	2244671	2228497	\N	\N
48	\N	\N	\N	107.955436706543	60.1542892456055	17.2262992858887	2.8728199005127	40397965	4503257	4478233	1427974	1281677
49	91.9822692871094	95.1585388183594	88.786979675293	106.268379211426	62.6410293579102	17.280179977417	\N	40781235	4548490	4517417	1525400	1369424
50	\N	\N	\N	109.305770874023	70.5409164428711	17.7949295043945	3.04425001144409	40633092	4566992	4479279	1583589	1434874
51	92.1922988891602	95.383186340332	89.1013870239258	107.822540283203	69.6562271118164	20.6682090759277	2.90190005302429	40645415	4592159	4462549	1425828	1531383
52	92.5817031860352	95.6470108032227	89.677116394043	108.549240112305	74.6276473999023	22.9891204833984	3.52513003349304	40812931	4625583	4469530	1511977	1550054
53	\N	\N	\N	109.150337219238	76.4262466430664	24.0762596130371	2.81227993965149	41118609	4666449	4501293	1595955	1640533
54	92.8119125366211	95.5910873413086	90.0687026977539	109.179832458496	79.1144790649414	26.3031997680664	3.18944001197815	41541270	4712482	4563250	1615479	1407035
55	\N	\N	\N	109.273422241211	80.4523315429688	30.4290008544922	3.40748000144959	41835466	4709390	4623136	1655764	1290585
56	\N	\N	\N	106.841590881348	82.6376419067383	31.0637092590332	3.35904002189636	42005790	4684236	4654753	1870834	1451842
57	95.1162185668945	96.7910079956055	93.4508972167969	106.073402404785	82.6823806762695	30.8957595825195	3.28800988197327	42054324	4649152	4667376	1801909	1459756
58	95.2179336547852	97.1065216064453	93.3357086181641	105.960243225098	86.1227493286133	33.2507209777832	3.58360004425049	42017587	4616348	4683986	\N	\N
59	95.3769683837891	97.1744384765625	93.5869216918945	105.609878540039	84.9521179199219	35.4373588562012	3.5	41935960	4595834	4708485	2106887	1674317
60	\N	\N	\N	105.911430358887	87.0592193603516	36.4444389343262	2.6699800491333	41788284	4596194	4705051	1827213	1586484
61	95.658561706543	97.3313369750977	93.9921798706055	106.410820007324	88.9101715087891	36.3110389709473	3	41727304	4647805	4680038	1727377	1636970
62	\N	\N	\N	\N	\N	\N	2.84185004234314	41760251	4727440	4642754	1771614	\N
63	95.9990081787109	97.4493103027344	94.5523529052734	\N	\N	\N	\N	\N	4810671	4605890	\N	\N
64	\N	\N	\N	\N	\N	2.43892002105713	2.12011003494263	2306240	609090	529100	\N	\N
65	\N	\N	\N	\N	\N	2.3798201084137	2.28146004676819	2391150	633521	545733	\N	\N
66	\N	\N	\N	98.9735794067383	\N	\N	\N	3595510	660238	528706	86769	\N
67	\N	\N	\N	105.180206298828	21.2894592285156	\N	\N	3736493	688394	546105	\N	\N
68	\N	\N	\N	104.130569458008	22.6925506591797	\N	\N	3885762	717087	564807	\N	\N
69	\N	\N	\N	105.781036376953	26.259220123291	\N	3.42131996154785	4039482	745239	584993	93734	\N
70	\N	\N	\N	119.530143737793	26.4825401306152	6.13030004501343	3.2437698841095	4205469	777542	606439	118158	32279
71	\N	\N	\N	\N	\N	\N	3.27847003936768	4383296	811625	630476	\N	\N
72	\N	\N	\N	\N	\N	8.83833026885986	3.8720600605011	4570069	846117	655900	\N	\N
73	66.0301132202148	79.9741516113281	53.4072113037109	\N	\N	\N	2.93055009841919	4761994	879590	682061	\N	\N
74	\N	\N	\N	113.477958679199	\N	8.40093994140625	3.48690009117126	4953310	910404	709888	112352	72859
75	\N	\N	\N	\N	50.6714782714844	9.33625984191895	2.75494003295898	5149203	941905	740259	95827	75997
76	\N	\N	\N	\N	\N	\N	2.46688008308411	5340692	971420	772730	\N	\N
77	\N	\N	\N	\N	\N	\N	2.04469990730286	5524854	999138	805604	\N	\N
78	\N	\N	\N	\N	\N	\N	1.82117998600006	5698765	1025194	839167	\N	\N
79	\N	\N	\N	\N	\N	\N	\N	\N	1050022	871796	\N	\N
80	\N	\N	\N	130.898712158203	\N	3.3885600566864	\N	\N	317733	361721	50654	\N
81	\N	\N	\N	128.833190917969	39.738410949707	5.67854976654053	\N	\N	308238	369665	51212	27070
82	\N	\N	\N	127.848602294922	42.6907386779785	7.31445980072021	1.59930002689362	\N	302389	360458	48736	30258
83	76.8712921142578	84.9874572753906	69.5864105224609	123.756790161133	45.2158813476563	9.12242984771729	\N	\N	299305	344993	48223	\N
84	76.1379623413086	83.9326782226563	69.109016418457	123.281227111816	\N	11.7689504623413	1.66568005084991	\N	298296	333732	46658	\N
85	\N	\N	\N	123.834930419922	\N	13.9649896621704	1.53378999233246	\N	298501	325253	46905	\N
86	\N	\N	\N	122.141471862793	\N	14.8900699615479	1.51068997383118	\N	298617	318415	47033	\N
87	\N	\N	\N	121.787933349609	\N	\N	1.56089997291565	\N	301828	311070	48002	\N
88	\N	\N	\N	123.448059082031	\N	\N	2.05053997039795	\N	309787	305566	47413	\N
89	78.0550918579102	84.8141479492188	71.7817993164063	116.808219909668	\N	\N	1.90938997268677	\N	320285	300299	47691	\N
90	80.5264892578125	86.5324401855469	75.0338668823242	117.078483581543	\N	13.1356296539307	\N	\N	331089	294235	47866	\N
91	\N	\N	\N	110.187652587891	\N	\N	\N	\N	339214	291380	49511	\N
92	\N	\N	\N	107.813056945801	\N	13.1342802047729	\N	\N	345120	295972	50684	\N
93	\N	\N	\N	107.414848327637	\N	13.6877603530884	2.16285991668701	\N	348782	304832	51490	\N
94	\N	\N	\N	106.474739074707	\N	14.7389602661133	\N	\N	350857	313149	51578	\N
95	\N	\N	\N	105.351997375488	54.8304100036621	\N	\N	\N	352084	322127	\N	\N
96	93.5064697265625	95.6002426147461	91.5295715332031	101.92333984375	73.6311569213867	44.5769500732422	3.93859004974365	8933953	932667	1022869	\N	\N
97	\N	\N	\N	101.81307220459	74.1841506958008	44.8578300476074	4.05038022994995	8793035	911044	1014884	319916	208812
98	\N	\N	\N	101.379493713379	79.3435363769531	49.0348014831543	3.60314989089966	8645097	893444	997781	321930	227929
99	\N	\N	\N	100.828437805176	79.2197723388672	48.6715698242188	3.50850009918213	8492383	876171	976935	347959	222799
100	\N	\N	\N	99.1733322143555	80.8186874389648	49.4026985168457	3.86193990707397	8336247	859556	959067	\N	\N
101	96.430908203125	96.4350204467773	96.4270477294922	96.8581390380859	82.4288482666016	50.3747406005859	3.5084400177002	8183489	843823	943751	316552	\N
102	\N	\N	\N	96.7558822631836	85.0075988769531	52.2556991577148	4.80555009841919	8038740	829237	928541	319568	\N
103	\N	\N	\N	97.0294494628906	83.7614593505859	50.6790084838867	4.53670978546143	7965633	824199	920553	307446	\N
104	93.7020721435547	95.2512588500977	92.2491607666016	96.9178466796875	81.999153137207	49.8533706665039	4.12402009963989	7897749	822309	910375	\N	\N
105	\N	\N	\N	102.110877990723	120.332298278809	50.180061340332	3.72356009483337	7831867	821422	899035	336676	229937
106	92.8683090209961	94.6591186523438	91.1919326782227	100.650863647461	120.651168823242	\N	3.75967001914978	7766912	819620	884644	300968	240005
107	\N	\N	\N	100.757530212402	118.625907897949	49.2868118286133	3.63752007484436	7701605	814196	871387	303969	246711
108	\N	\N	\N	99.6250305175781	116.733940124512	\N	3.3557300567627	7592844	804082	859397	293265	240251
109	93.7677612304688	95.202392578125	92.4285583496094	99.7743606567383	117.738807678223	\N	3.05677008628845	7494139	792856	851885	\N	241484
110	\N	\N	\N	101.052673339844	115.152656555176	\N	2.96898007392883	7401193	781034	842800	378131	229313
111	\N	\N	\N	102.225120544434	113.794387817383	\N	\N	\N	769176	833611	\N	\N
112	\N	\N	\N	105.948272705078	87.3967132568359	\N	5.06319999694824	9004960	955310	1042773	232999	141562
113	\N	\N	\N	106.250091552734	90.6488265991211	\N	5.07256984710693	8899564	951051	1026393	219582	158544
114	88.7172470092773	90.7175903320313	87.043098449707	108.024749755859	92.3353729248047	\N	4.97414016723633	8805852	950598	1010026	220308	164990
115	\N	\N	\N	107.526397705078	90.8973999023438	\N	4.86600017547607	8731949	953913	996120	221065	168556
116	92.8948593139648	94.1214599609375	91.7681579589844	106.341697692871	92.5119018554688	\N	5.24869012832642	8685285	961151	984918	212296	187162
117	92.8773193359375	94.1438522338867	91.7139892578125	104.729377746582	93.7371978759766	18.3626308441162	5.72173976898193	8668045	972205	974326	238032	\N
118	93.1021423339844	94.2450866699219	92.0478897094727	103.418388366699	96.1824569702148	19.6080207824707	5.88102006912231	8667892	986256	964327	213440	\N
119	93.7294692993164	94.9637222290039	92.5862503051758	103.229202270508	98.8268585205078	19.1436595916748	6.07742023468018	8710990	1010687	958339	212657	\N
120	\N	\N	\N	102.670402526855	\N	19.9304904937744	5.86465978622437	8798269	1041124	956523	220544	\N
121	94.1399002075195	95.2868499755859	93.0730590820313	102.704963684082	107.804122924805	19.8092403411865	5.99946022033691	8922501	1073099	957609	219579	\N
122	94.367919921875	95.3965301513672	93.4080276489258	105.570388793945	109.444076538086	22.260929107666	5.95619010925293	9074756	1102645	958332	249103	190022
123	\N	\N	\N	103.184959411621	107.176948547363	20.9184494018555	5.94285011291504	9256748	1127593	959561	\N	192359
124	87.0466690063477	87.6777496337891	86.4586334228516	100.864730834961	104.697982788086	22.3660297393799	6.11305999755859	9447226	1144807	968956	\N	182937
125	\N	\N	\N	98.5389022827148	100.511169433594	23.8019599914551	6.15898990631104	9641171	1155954	990907	\N	182982
126	95.0229721069336	95.5453720092773	94.5331726074219	98.3744735717773	102.556663513184	23.8665599822998	6.50505018234253	9827385	1162848	1020897	\N	\N
127	\N	\N	\N	\N	\N	\N	6.83613014221191	\N	1167175	1049733	\N	\N
128	\N	\N	\N	\N	\N	\N	\N	2251272	326138	320119	\N	\N
129	\N	\N	\N	\N	\N	\N	\N	2242521	327946	314779	\N	\N
130	\N	\N	\N	\N	\N	\N	\N	2245701	330994	311711	\N	\N
131	\N	\N	\N	\N	\N	\N	\N	2258837	335191	310788	\N	\N
132	\N	\N	\N	\N	\N	\N	\N	2279942	340313	311594	\N	\N
133	\N	\N	\N	\N	\N	6.69837999343872	1.54405999183655	2306084	346119	314280	\N	\N
134	83.5827102661133	87.7648086547852	80.0656585693359	\N	\N	6.70255994796753	\N	2330166	354445	314332	\N	\N
135	\N	\N	\N	112.516792297363	51.5509910583496	6.85413980484009	6.07020998001099	2369825	365217	315421	74355	41759
136	\N	\N	\N	109.892791748047	52.4056701660156	6.93525981903076	5.99597978591919	2423441	377304	317450	73148	42585
137	88.6934204101563	89.1853713989258	88.2838287353516	\N	\N	\N	6.13835000991821	2488048	389639	321155	\N	\N
138	\N	\N	\N	103.833992004395	\N	10.0065498352051	5.81278991699219	2560255	400870	325775	\N	\N
139	\N	\N	\N	101.309677124023	\N	8.17144012451172	5.47262001037598	2627597	412180	330955	\N	\N
140	\N	\N	\N	98.9331893920898	\N	8.87594985961914	5.3810601234436	2705346	424853	339846	\N	\N
141	\N	\N	\N	97.7508087158203	\N	\N	3.58728003501892	2788693	436916	350684	\N	\N
142	\N	\N	\N	97.1402130126953	\N	\N	\N	2871820	446279	361149	\N	\N
143	\N	\N	\N	97.3049087524414	\N	\N	\N	\N	450565	370097	\N	\N
\.


--
-- Data for Name: event; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.event (event_key, name, disaster_type, start_day, end_day, start_month, end_month, start_year, end_year, disaster_subgroup, total_deaths, no_injured, no_affected) FROM stdin;
0	Null	Flood	27	28	1	3	2005	2005	Hydrological	\N	\N	\N
1	Null	Transport accident	8	8	2	2	2005	2005	Technological	20	70	\N
2	Null	Earthquake	28	28	3	3	2005	2005	Geophysical	915	1146	104167
3	Null	Earthquake	23	23	1	1	2005	2005	Geophysical	1	4	680
4	Null	Landslide	21	21	2	2	2005	2005	Hydrological	143	\N	\N
5	Casa 212	Transport accident	22	22	3	3	2005	2005	Technological	15	3	\N
6	Null	Transport accident	13	13	3	3	2005	2005	Technological	33	\N	\N
7	Null	Flood	17	23	2	2	2005	2005	Hydrological	9	\N	150
8	Null	Flood	7	11	1	1	2005	2005	Hydrological	28	8	500
9	Null	Storm	22	24	1	1	2005	2005	Meteorological	20	\N	\N
10	Null	Transport accident	7	7	1	1	2005	2005	Technological	9	200	750
11	Null	Transport accident	5	5	1	1	2005	2005	Technological	12	13	\N
12	Sea Breeze	Transport accident	25	25	1	1	2005	2005	Technological	17	\N	\N
13	Null	Transport accident	17	17	1	1	2005	2005	Technological	\N	200	\N
14	Null	Transport accident	26	26	1	1	2005	2005	Technological	11	180	\N
15	Raffinerie BP	Industrial accident	23	23	3	3	2005	2005	Technological	15	170	\N
16	Null	Earthquake	9	9	3	3	2005	2005	Geophysical	2	58	\N
17	Null	Transport accident	25	25	3	3	2005	2005	Technological	10	69	\N
18	Null	Flood	26	27	4	4	2005	2005	Hydrological	47	18	750
19	Null	Flood	18	19	10	10	2005	2005	Hydrological	28	211	12000
20	Null	Flood	31	3	12	1	2005	2006	Hydrological	79	30	7781
21	Null	Flood	27	29	9	9	2005	2005	Hydrological	\N	\N	600
22	Null	Flood	7	1	6	7	2005	2005	Hydrological	4	\N	5000
23	Null	Wildfire	\N	\N	7	7	2005	2005	Climatological	\N	\N	\N
24	Null	Wildfire	\N	\N	8	8	2005	2005	Climatological	\N	\N	\N
25	Food poisoning	Miscellaneous accident	30	1	11	12	2005	2005	Technological	\N	506	\N
26	Poisoning	Miscellaneous accident	8	8	5	5	2005	2005	Technological	\N	155	\N
27	Null	Storm	26	29	9	9	2005	2005	Meteorological	\N	\N	300
28	Mt. Talang	Volcanic activity	12	12	4	4	2005	2005	Geophysical	\N	\N	26000
29	Null	Landslide	2	2	9	9	2005	2005	Hydrological	25	10	\N
30	Null	Wildfire	9	9	8	8	2005	2005	Climatological	\N	\N	\N
31	Poliomyelitis	Epidemic	\N	31	6	1	2005	2006	Biological	\N	\N	329
32	Boeing 737-200	Transport accident	5	5	9	9	2005	2005	Technological	150	\N	14
33	Ferry "Digul"	Transport accident	7	7	7	7	2005	2005	Technological	200	\N	\N
34	Null	Transport accident	24	24	9	9	2005	2005	Technological	18	\N	34
35	Null	Transport accident	30	30	6	6	2005	2005	Technological	2	125	\N
36	Null	Flood	22	4	12	1	2006	2007	Hydrological	236	\N	618486
37	Null	Earthquake	17	17	12	12	2006	2006	Geophysical	8	200	1000
38	Null	Flood	13	23	2	2	2006	2006	Hydrological	39	39	17500
39	Null	Flood	19	23	6	6	2006	2006	Hydrological	236	56	28505
40	Null	Flood	25	29	6	6	2006	2006	Hydrological	52	\N	18250
41	Null	Flood	26	14	1	2	2006	2006	Hydrological	19	\N	10000
42	Null	Flood	19	23	4	4	2006	2006	Hydrological	22	2	400
43	Null	Flood	24	26	6	6	2006	2006	Hydrological	41	\N	\N
44	Null	Earthquake	14	14	3	3	2006	2006	Geophysical	3	2	1200
45	Null	Flood	22	31	4	5	2006	2006	Hydrological	\N	\N	2000
46	Null	Flood	\N	\N	1	1	2006	2006	Hydrological	\N	\N	\N
47	Cholera	Epidemic	13	8	2	2	2006	2007	Biological	2354	\N	57570
48	Cholera	Epidemic	24	\N	10	11	2006	2006	Biological	68	\N	\N
49	Helicopter MI-17	Transport accident	25	25	2	2	2006	2006	Technological	18	12	\N
50	Null	Flood	18	24	4	4	2006	2006	Hydrological	\N	\N	200
51	Null	Flood	12	20	4	4	2006	2006	Hydrological	\N	\N	1000
52	Null	Flood	26	2	5	6	2006	2006	Hydrological	\N	\N	300
53	Null	Flood	20	28	5	5	2006	2006	Hydrological	1	\N	400
54	Null	Earthquake	26	26	5	5	2006	2006	Geophysical	5778	137883	2340745
55	Null	Earthquake	1	1	12	12	2006	2006	Geophysical	1	14	\N
56	Null	Earthquake	17	17	7	7	2006	2006	Geophysical	802	543	35000
57	Mt. Merapi	Volcanic activity	18	15	4	5	2006	2006	Geophysical	\N	\N	11000
58	Null	Flood	23	27	6	6	2006	2006	Hydrological	\N	\N	5000
59	Null	Landslide	1	4	1	1	2006	2006	Hydrological	156	13	\N
60	Null	Landslide	22	27	1	1	2006	2006	Hydrological	11	\N	3000
61	Null	Landslide	15	15	12	12	2006	2006	Hydrological	17	\N	\N
62	Null	Wildfire	\N	\N	8	8	2006	2006	Climatological	\N	200	\N
63	Null	Transport accident	17	17	11	11	2006	2006	Technological	12	\N	\N
64	Null	Transport accident	1	1	1	1	2006	2006	Technological	11	14	\N
65	Ferry	Transport accident	31	31	1	1	2006	2006	Technological	117	\N	71
66	Inter-island ferry "Citra Mandala Bakti"	Transport accident	31	31	1	1	2006	2006	Technological	45	\N	114
67	Cargo	Transport accident	6	6	4	4	2006	2006	Technological	29	\N	\N
68	Ferry	Transport accident	18	18	4	4	2006	2006	Technological	10	\N	50
69	Ferry	Transport accident	21	22	6	6	2006	2006	Technological	35	\N	\N
70	Ferry "Trista I"	Transport accident	29	29	12	12	2006	2006	Technological	50	\N	\N
71	Ferry "Senopati Nusantara"	Transport accident	30	31	12	12	2006	2006	Technological	400	\N	250
72	Null	Transport accident	15	15	4	4	2006	2006	Technological	13	26	\N
73	Null	Industrial accident	22	22	11	11	2006	2006	Technological	12	11	\N
74	Null	Industrial accident	29	29	5	5	2006	2006	Technological	13	\N	\N
152	Null	Flood	27	7	7	8	2006	2006	Hydrological	\N	\N	\N
75	Gold mine	Industrial accident	6	6	5	5	2006	2006	Technological	11	\N	\N
76	Null	Miscellaneous accident	8	8	9	9	2006	2006	Technological	23	\N	\N
77	Null	Storm	14	15	2	2	2007	2007	Meteorological	2	\N	\N
78	Null	Landslide	12	14	1	1	2007	2007	Hydrological	32	\N	3990
79	Null	Flood	10	10	1	5	2007	2007	Hydrological	\N	\N	\N
80	Null	Flood	17	25	1	1	2007	2007	Hydrological	105	\N	40000
81	Cholera	Epidemic	1	31	1	12	2007	2007	Biological	515	\N	17875
82	Null	Flood	31	22	1	2	2007	2007	Hydrological	68	1	217086
83	Null	Landslide	9	9	1	1	2007	2007	Hydrological	11	\N	\N
84	Boeing	Transport accident	1	1	1	1	2007	2007	Technological	102	\N	\N
85	Null	Transport accident	1	1	1	1	2007	2007	Technological	15	\N	10
86	Null	Transport accident	16	16	1	1	2007	2007	Technological	5	100	\N
87	Null	Epidemic	\N	\N	2	2	2007	2007	Biological	22	\N	357
88	Katrina	Storm	29	19	8	9	2005	2005	Meteorological	1833	\N	500000
89	Null	Flood	31	18	12	1	2005	2006	Hydrological	3	\N	3600
90	Null	Drought	\N	\N	4	4	2005	2005	Climatological	\N	\N	600000
91	Hurricane "Wilma"	Storm	24	24	10	10	2005	2005	Meteorological	4	\N	30000
92	Null	Flood	21	30	8	8	2005	2005	Hydrological	30	\N	10000
93	Null	Flood	23	12	11	1	2005	2006	Hydrological	55	\N	700000
94	Damrey	Storm	26	30	9	9	2005	2005	Meteorological	10	\N	2000
95	Null	Wildfire	\N	\N	8	8	2005	2005	Climatological	\N	\N	\N
96	Null	Storm	21	21	5	5	2005	2005	Meteorological	\N	\N	1500
97	Stan	Storm	1	13	10	10	2005	2005	Meteorological	36	\N	1954571
98	Hurricane "Wilma"	Storm	19	24	10	10	2005	2005	Meteorological	7	\N	700000
99	Null	Flood	5	5	5	5	2005	2005	Hydrological	8	\N	1000
100	Null	Flood	6	8	5	5	2005	2005	Hydrological	\N	\N	\N
101	Null	Flood	8	16	10	10	2005	2005	Hydrological	11	\N	3000
102	Bret	Storm	29	30	6	6	2005	2005	Meteorological	2	\N	15000
103	Null	Storm	6	8	4	4	2005	2005	Meteorological	\N	8	45
104	Rita	Storm	23	1	9	10	2005	2005	Meteorological	10	\N	300000
105	Null	Flood	8	29	9	9	2005	2005	Hydrological	16	\N	\N
106	Landmine	Miscellaneous accident	13	13	11	11	2005	2005	Technological	13	\N	\N
107	Null	Flood	26	29	9	9	2005	2005	Hydrological	3	\N	3000
108	Emily	Storm	18	18	7	7	2005	2005	Meteorological	2	\N	\N
109	Null	Transport accident	6	6	4	4	2005	2005	Technological	20	15	\N
110	Fireworks market	Miscellaneous accident	15	15	9	9	2005	2005	Technological	\N	104	\N
111	Null	Flood	13	31	8	8	2005	2005	Hydrological	21	40	119270
112	Boat "Runj Roj"	Transport accident	5	5	3	3	2005	2005	Technological	10	65	\N
113	Null	Drought	\N	\N	1	3	2005	2005	Climatological	\N	\N	\N
114	Null	Storm	18	18	8	8	2005	2005	Meteorological	\N	\N	120
115	Null	Storm	8	9	12	12	2005	2005	Meteorological	10	\N	\N
116	Null	Flood	1	6	4	4	2005	2005	Hydrological	2	\N	11000
117	Hurricane "Dennis"	Storm	10	10	7	7	2005	2005	Meteorological	5	\N	\N
118	Null	Extreme temperature	4	30	7	7	2005	2005	Meteorological	33	31	\N
119	Null	Wildfire	27	4	12	1	2005	2006	Climatological	5	\N	\N
120	Bimoteur Grumman G-73T	Transport accident	19	19	12	12	2005	2005	Technological	19	\N	\N
121	Null	Transport accident	23	23	9	9	2005	2005	Technological	24	17	\N
122	Null	Transport accident	2	2	10	10	2005	2005	Technological	21	\N	28
123	Null	Transport accident	15	15	7	7	2005	2005	Technological	23	\N	\N
124	Null	Transport accident	19	19	8	8	2005	2005	Technological	13	8	\N
125	Null	Transport accident	2	2	9	9	2005	2005	Technological	19	\N	\N
126	Null	Transport accident	16	17	12	12	2005	2005	Technological	20	77	\N
127	Porte conteneur "Euro da Brasil" et chalutier "Lindsay"	Transport accident	8	8	5	5	2005	2005	Technological	14	\N	2
128	Null	Transport accident	13	13	7	7	2005	2005	Technological	\N	162	\N
129	Null	Transport accident	25	25	4	4	2005	2005	Technological	11	53	\N
130	Null	Flood	4	17	4	4	2006	2006	Hydrological	1	\N	600
131	Null	Flood	14	23	3	3	2006	2006	Hydrological	7	\N	\N
132	John	Storm	2	4	9	9	2006	2006	Meteorological	7	\N	10000
133	Lane	Storm	16	18	9	9	2006	2006	Meteorological	4	\N	240700
134	Null	Earthquake	15	15	10	10	2006	2006	Geophysical	\N	10	3519
135	Null	Flood	22	11	5	6	2006	2006	Hydrological	116	\N	342895
136	Null	Flood	20	13	8	12	2006	2006	Hydrological	164	\N	2212413
137	Null	Flood	25	1	6	7	2006	2006	Hydrological	11	\N	65000
138	Null	Storm	2	3	4	4	2006	2006	Meteorological	28	36	3600
139	Null	Storm	6	8	4	4	2006	2006	Meteorological	12	160	465
140	Null	Storm	1	7	5	5	2006	2006	Meteorological	1	\N	600
141	Null	Flood	10	1	8	11	2006	2006	Hydrological	5	\N	33000
142	Null	Flood	11	22	5	5	2006	2006	Hydrological	2	\N	2500
143	Null	Flood	22	26	9	9	2006	2006	Hydrological	14	10	1200
144	Null	Storm	30	3	11	12	2006	2006	Meteorological	11	\N	\N
145	Paul	Storm	25	28	10	10	2006	2006	Meteorological	4	\N	20000
146	Null	Storm	11	13	3	3	2006	2006	Meteorological	10	42	\N
147	Null	Storm	15	16	11	11	2006	2006	Meteorological	12	20	\N
148	Null	Storm	12	14	10	10	2006	2006	Meteorological	3	\N	\N
149	Ernesto	Storm	2	7	8	9	2006	2006	Meteorological	6	\N	140
150	Null	Flood	6	7	7	7	2006	2006	Hydrological	\N	\N	5000
151	Dengue	Epidemic	\N	\N	\N	\N	2006	2006	Biological	\N	\N	4368
153	Null	Landslide	2	2	8	8	2006	2006	Hydrological	11	\N	\N
154	Null	Landslide	6	6	9	9	2006	2006	Hydrological	10	\N	\N
155	Null	Extreme temperature	\N	\N	11	11	2006	2006	Meteorological	5	\N	\N
156	Null	Transport accident	17	17	4	4	2006	2006	Technological	57	3	\N
157	Null	Transport accident	16	16	10	10	2006	2006	Technological	14	\N	\N
158	Null	Transport accident	28	28	12	12	2006	2006	Technological	22	9	\N
159	Mine	Industrial accident	19	19	2	2	2006	2006	Technological	65	8	\N
160	Null	Flood	10	18	2	2	2006	2006	Hydrological	\N	\N	2000
161	Null	Storm	25	25	12	12	2006	2006	Meteorological	\N	\N	600
162	Null	Storm	21	21	12	12	2006	2006	Meteorological	\N	\N	\N
163	Null	Storm	27	31	12	12	2006	2006	Meteorological	\N	\N	\N
164	Null	Flood	22	25	6	6	2006	2006	Hydrological	2	\N	2400
165	Null	Flood	27	7	7	8	2006	2006	Hydrological	\N	\N	\N
166	Null	Flood	27	30	7	7	2006	2006	Hydrological	1	\N	600
167	Null	Flood	19	24	8	8	2006	2006	Hydrological	\N	\N	150
168	Null	Flood	9	14	10	10	2006	2006	Hydrological	\N	\N	100
169	Null	Flood	5	10	11	11	2006	2006	Hydrological	2	\N	1500
170	Null	Extreme temperature	14	15	7	8	2006	2006	Meteorological	164	\N	\N
171	Null	Extreme temperature	30	6	7	8	2006	2006	Meteorological	24	\N	\N
172	Null	Wildfire	26	27	10	10	2006	2006	Climatological	4	1	\N
173	Null	Wildfire	3	6	12	12	2006	2006	Climatological	\N	\N	\N
174	Null	Transport accident	27	27	8	8	2006	2006	Technological	49	\N	1
175	"Paquebot "Crown princess"	Transport accident	18	18	7	7	2006	2006	Technological	\N	100	\N
176	Mine	Industrial accident	2	2	1	1	2006	2006	Technological	13	1	6
177	Hall for mentally handicapped people	Miscellaneous accident	26	27	11	11	2006	2006	Technological	10	19	\N
178	Null	Wildfire	9	14	7	7	2006	2006	Climatological	1	17	\N
179	Null	Storm	14	15	12	12	2006	2006	Meteorological	10	\N	\N
180	Null	Flood	26	30	3	3	2006	2006	Hydrological	6	\N	4160
181	Null	Flood	2	4	8	8	2006	2006	Hydrological	6	\N	3000
182	Null	Transport accident	7	7	2	2	2006	2006	Technological	11	35	\N
183	Null	Transport accident	18	18	6	6	2006	2006	Technological	12	\N	\N
184	Null	Transport accident	18	18	6	6	2006	2006	Technological	11	\N	\N
185	Null	Transport accident	24	24	6	6	2006	2006	Technological	14	4	\N
186	Null	Transport accident	8	8	7	7	2006	2006	Technological	10	\N	\N
187	Null	Transport accident	24	24	12	12	2006	2006	Technological	12	34	\N
188	Cargo "Alexandros T"	Transport accident	4	4	5	5	2006	2006	Technological	26	\N	7
189	Null	Transport accident	13	13	11	11	2006	2006	Technological	20	6	\N
190	Null	Miscellaneous accident	29	29	3	3	2006	2006	Technological	12	33	\N
191	Null	Storm	12	17	1	1	2007	2007	Meteorological	65	220	\N
192	Null	Storm	14	15	2	2	2007	2007	Meteorological	16	\N	\N
193	Null	Transport accident	24	24	1	1	2007	2007	Technological	29	25	\N
194	Null	Transport accident	19	19	1	1	2007	2007	Technological	16	30	\N
195	Null	Transport accident	14	14	1	1	2007	2007	Technological	3	100	\N
196	Null	Storm	2	2	2	2	2007	2007	Meteorological	20	\N	6600
197	Null	Flood	15	25	1	1	2007	2007	Hydrological	24	\N	\N
198	Null	Transport accident	1	1	2	2	2007	2007	Technological	20	\N	\N
199	Cholera	Epidemic	\N	\N	5	6	2005	2005	Biological	14	\N	203
200	Cholera	Epidemic	10	18	12	5	2005	2006	Biological	73	\N	980
201	Null	Transport accident	25	25	8	8	2005	2005	Technological	18	62	\N
202	Food poisoning	Miscellaneous accident	13	13	11	11	2005	2005	Technological	14	200	\N
203	Null	Transport accident	6	6	6	6	2006	2006	Technological	18	43	\N
204	Null	Transport accident	7	7	8	8	2006	2006	Technological	33	20	\N
205	Null	Flood	1	10	3	3	2007	2007	Hydrological	74	26	11530
206	Null	Flood	\N	\N	7	7	2007	2007	Hydrological	58	\N	5000
207	Null	Flood	22	7	7	8	2007	2007	Hydrological	88	12	3377
208	Null	Flood	25	\N	12	12	2007	2007	Hydrological	127	95	259545
209	Null	Flood	2	4	9	9	2007	2007	Hydrological	4	\N	1000
210	Null	Earthquake	12	12	9	9	2007	2007	Geophysical	25	82	422685
211	Null	Industrial accident	3	3	11	11	2007	2007	Technological	5	100	\N
212	Unknown	Epidemic	2	29	10	11	2007	2007	Biological	\N	\N	468
213	Null	Flood	6	11	6	6	2007	2007	Hydrological	\N	\N	500
214	Null	Storm	23	26	12	12	2007	2007	Meteorological	4	\N	\N
215	Null	Earthquake	6	6	3	3	2007	2007	Geophysical	67	826	136834
216	Null	Earthquake	9	9	9	9	2007	2007	Geophysical	\N	19	450
217	Null	Earthquake	25	25	11	11	2007	2007	Geophysical	3	1800	20000
218	Mt. Gamkonora	Volcanic activity	9	9	7	7	2007	2007	Geophysical	\N	\N	9758
219	Mt. Kelud	Volcanic activity	16	18	10	10	2007	2007	Geophysical	\N	\N	22154
220	Null	Flood	15	5	5	6	2007	2007	Hydrological	4	\N	60000
221	Null	Flood	25	2	7	8	2007	2007	Hydrological	15	\N	2000
222	Dengue	Epidemic	\N	\N	7	7	2007	2007	Biological	365	\N	34542
223	Dengue	Epidemic	\N	\N	2	3	2007	2007	Biological	16	\N	312
224	Null	Transport accident	7	7	3	3	2007	2007	Technological	22	50	\N
225	Ferry Levina I	Transport accident	22	22	2	2	2007	2007	Technological	77	\N	\N
226	Passenger ship "Wahai Star"	Transport accident	11	11	7	7	2007	2007	Technological	47	\N	\N
227	Ferry "Acita"	Transport accident	18	18	10	10	2007	2007	Technological	60	20	\N
228	Null	Transport accident	25	25	10	10	2007	2007	Technological	30	\N	\N
229	Bridge	Miscellaneous accident	26	26	12	12	2007	2007	Technological	50	\N	\N
230	Null	Flood	11	27	2	2	2008	2008	Hydrological	11	\N	3500
231	Null	Flood	15	16	11	11	2008	2008	Hydrological	33	\N	83000
232	Null	Flood	1	14	3	3	2008	2008	Hydrological	3	\N	12000
233	Null	Flood	26	1	4	5	2008	2008	Hydrological	\N	\N	2000
234	Null	Flood	31	3	1	3	2008	2008	Hydrological	7	\N	81400
235	Cholera	Epidemic	1	30	1	11	2008	2008	Biological	229	\N	9942
236	Cholera	Epidemic	1	17	1	5	2008	2009	Biological	134	\N	7495
237	King Air B200	Transport accident	19	19	1	1	2008	2008	Technological	25	\N	\N
238	Null	Transport accident	15	15	2	2	2008	2008	Technological	15	\N	\N
239	Building	Miscellaneous accident	13	13	3	3	2008	2008	Technological	11	\N	\N
240	Null	Flood	10	24	4	4	2008	2008	Hydrological	\N	\N	400
241	Propone gaz facility	Industrial accident	10	10	8	8	2008	2008	Technological	2	18	12500
242	Null	Earthquake	20	20	2	2	2008	2008	Geophysical	3	25	\N
243	Null	Earthquake	9	9	9	9	2008	2008	Geophysical	2	60	565
244	Null	Earthquake	16	16	11	11	2008	2008	Geophysical	6	77	10000
245	Mt. Egon	Volcanic activity	15	15	4	4	2008	2008	Geophysical	\N	\N	600
246	Null	Flood	8	12	2	2	2008	2008	Hydrological	14	\N	7000
247	Null	Flood	23	27	4	4	2008	2008	Hydrological	\N	\N	34514
248	Null	Flood	2	6	1	1	2008	2008	Hydrological	\N	\N	1000
249	Null	Flood	1	6	2	2	2008	2008	Hydrological	3	\N	88261
250	Null	Flood	30	31	1	1	2008	2008	Hydrological	3	\N	40000
251	Null	Flood	10	3	3	4	2008	2008	Hydrological	\N	\N	60000
252	Null	Flood	6	8	9	9	2008	2008	Hydrological	16	\N	118000
253	Null	Flood	\N	\N	10	10	2008	2008	Hydrological	5	\N	11000
254	Null	Flood	26	12	12	1	2008	2009	Hydrological	24	\N	15000
255	Null	Landslide	5	5	5	5	2008	2008	Hydrological	21	\N	\N
256	Sand mine	Industrial accident	29	29	10	10	2008	2008	Technological	25	\N	\N
257	Null	Miscellaneous accident	29	29	7	7	2008	2008	Technological	16	\N	\N
258	Stampede	Miscellaneous accident	15	15	9	9	2008	2008	Technological	21	11	\N
259	Null	Flood	27	2	1	2	2009	2009	Hydrological	18	\N	12000
260	Null	Flood	26	27	3	3	2009	2009	Hydrological	64	\N	1600
261	Null	Flood	14	16	2	2	2009	2009	Hydrological	2	\N	\N
262	Null	Flood	1	16	3	4	2009	2009	Hydrological	60	\N	220000
263	Cholera	Epidemic	\N	\N	3	3	2009	2009	Biological	9	\N	143
264	Helicopter	Transport accident	12	12	3	3	2009	2009	Technological	16	\N	1
265	Null	Earthquake	3	3	1	1	2009	2009	Geophysical	5	250	4000
266	Null	Earthquake	11	11	2	2	2009	2009	Geophysical	\N	64	2985
267	Null	Landslide	18	18	1	1	2009	2009	Hydrological	15	\N	5
268	Fokker 27	Transport accident	6	6	4	4	2009	2009	Technological	24	\N	\N
269	Null	Transport accident	17	17	4	4	2009	2009	Technological	11	\N	\N
270	Ferry "Teratai Prima"	Transport accident	10	11	1	1	2009	2009	Technological	247	\N	34
271	Null	Transport accident	13	14	1	1	2009	2009	Technological	28	\N	\N
272	Null	Flood	28	16	10	11	2007	2007	Hydrological	22	\N	1600000
273	Null	Flood	16	27	8	8	2007	2007	Hydrological	26	40	2800
274	Lorenzo	Storm	28	1	9	10	2007	2007	Meteorological	5	\N	33000
275	Null	Storm	3	7	12	12	2007	2007	Meteorological	17	28	1100
276	Null	Storm	4	8	5	5	2007	2007	Meteorological	12	40	\N
277	Null	Storm	13	17	4	4	2007	2007	Meteorological	23	\N	\N
278	Null	Flood	26	6	6	7	2007	2007	Hydrological	8	\N	5000
279	Null	Flood	14	15	4	4	2007	2007	Hydrological	38	\N	\N
280	Null	Landslide	6	6	11	11	2007	2007	Hydrological	16	\N	\N
281	Null	Flood	7	21	12	12	2007	2007	Hydrological	3	\N	65000
282	Null	Storm	21	25	5	5	2007	2007	Meteorological	5	\N	\N
283	Null	Flood	19	20	6	6	2007	2007	Hydrological	4	\N	120
284	Null	Wildfire	21	24	10	10	2007	2007	Climatological	8	64	640000
285	Null	Storm	23	25	2	2	2007	2007	Meteorological	4	27	\N
286	Dean	Storm	21	24	8	8	2007	2007	Meteorological	9	\N	140000
287	Felix	Storm	4	6	9	9	2007	2007	Meteorological	\N	\N	\N
288	Null	Storm	24	26	4	4	2007	2007	Meteorological	10	80	\N
289	Erin	Storm	16	19	8	8	2007	2007	Meteorological	7	\N	\N
290	Null	Storm	23	26	12	12	2007	2007	Meteorological	22	\N	\N
291	Null	Storm	9	11	12	12	2007	2007	Meteorological	24	2	\N
292	Null	Flood	10	24	8	8	2007	2007	Hydrological	2	\N	19000
293	Dengue	Epidemic	\N	\N	7	7	2007	2007	Biological	182	\N	17000
294	Antonov AN-24 XU-UA4	Transport accident	25	25	6	6	2007	2007	Technological	22	\N	\N
295	Null	Flood	4	12	9	9	2007	2007	Hydrological	\N	\N	55000
296	Henriette	Storm	1	1	9	9	2007	2007	Meteorological	6	\N	\N
297	Null	Transport accident	4	4	7	7	2007	2007	Technological	32	\N	\N
298	Null	Transport accident	9	9	9	9	2007	2007	Technological	29	120	\N
299	Null	Transport accident	15	15	9	9	2007	2007	Technological	15	12	\N
300	Null	Transport accident	19	19	10	10	2007	2007	Technological	24	\N	\N
301	Oil plateform	Industrial accident	23	24	10	10	2007	2007	Technological	23	\N	63
302	Null	Flood	11	21	5	5	2007	2007	Hydrological	\N	\N	1000
303	Monsoonal rain	Flood	5	10	9	11	2007	2007	Hydrological	10	\N	17000
304	Null	Flood	22	29	10	10	2007	2007	Hydrological	2	\N	100000
305	MD-82	Transport accident	16	16	9	9	2007	2007	Technological	90	40	\N
306	Null	Transport accident	20	20	3	3	2007	2007	Technological	29	37	\N
307	Null	Transport accident	23	23	12	12	2007	2007	Technological	22	\N	\N
308	Null	Storm	1	2	3	3	2007	2007	Meteorological	20	20	\N
309	Null	Flood	24	29	5	5	2007	2007	Hydrological	8	\N	100
310	Null	Flood	17	22	6	6	2007	2007	Hydrological	10	\N	750
311	Null	Wildfire	24	2	6	7	2007	2007	Climatological	\N	\N	\N
312	Null	Wildfire	24	27	11	11	2007	2007	Climatological	\N	\N	10000
313	Cessna 208B	Transport accident	7	7	10	10	2007	2007	Technological	10	\N	\N
314	Bridge	Miscellaneous accident	2	2	8	8	2007	2007	Technological	29	60	\N
315	Null	Drought	\N	\N	10	6	2007	2009	Climatological	\N	\N	\N
316	Home	Miscellaneous accident	7	8	3	3	2007	2007	Technological	10	\N	\N
317	Hurricane Dolly	Storm	20	21	7	7	2008	2008	Meteorological	2	\N	500000
318	Null	Flood	5	9	1	1	2008	2008	Hydrological	2	\N	1500
319	Null	Storm	22	26	5	5	2008	2008	Meteorological	7	70	\N
320	Null	Storm	10	12	5	5	2008	2008	Meteorological	22	150	\N
321	Null	Storm	5	6	2	2	2008	2008	Meteorological	59	150	\N
322	Null	Storm	14	14	3	3	2008	2008	Meteorological	2	27	150
323	Hurricane Dolly	Storm	23	23	7	7	2008	2008	Meteorological	\N	\N	\N
324	Null	Flood	17	20	3	4	2008	2008	Hydrological	18	\N	1000
325	Null	Flood	9	30	6	6	2008	2008	Hydrological	24	148	11000000
326	Cyclone Nargis	Storm	2	3	5	5	2008	2008	Meteorological	\N	\N	\N
327	Tropical storm "Kammuri" (Julian)	Storm	11	20	8	8	2008	2008	Meteorological	\N	\N	\N
328	Tropical Storm "Fay"	Storm	20	28	8	8	2008	2008	Meteorological	12	\N	400
329	Hurricane Ike	Storm	12	16	9	9	2008	2008	Meteorological	82	\N	200000
330	Null	Flood	6	11	7	7	2008	2008	Hydrological	12	\N	20000
331	Null	Landslide	17	18	9	9	2008	2008	Hydrological	22	\N	\N
332	Helicopter Bell-212	Transport accident	18	18	4	4	2008	2008	Technological	11	\N	\N
333	Bi-motor	Transport accident	4	4	11	11	2008	2008	Technological	15	7	\N
334	Null	Transport accident	19	19	5	5	2008	2008	Technological	24	\N	\N
335	Null	Transport accident	29	29	6	6	2008	2008	Technological	14	28	\N
336	Null	Transport accident	7	7	7	7	2008	2008	Technological	11	\N	\N
337	Null	Transport accident	18	18	10	10	2008	2008	Technological	11	20	\N
338	Null	Transport accident	7	7	11	11	2008	2008	Technological	17	5	\N
339	Null	Miscellaneous accident	20	20	6	6	2008	2008	Technological	12	20	\N
340	Null	Flood	20	20	11	12	2008	2008	Hydrological	21	\N	700000
341	Null	Flood	29	19	12	1	2008	2009	Hydrological	\N	\N	32584
342	Null	Flood	13	7	9	10	2008	2008	Hydrological	18	\N	839573
343	Helicopter UH-1H	Transport accident	5	5	8	8	2008	2008	Technological	10	\N	\N
344	Null	Transport accident	10	10	10	10	2008	2008	Technological	22	27	\N
345	Null	Drought	\N	\N	4	\N	2008	2008	Climatological	\N	\N	10000000
346	Null	Storm	29	30	1	1	2008	2008	Meteorological	4	\N	\N
347	Null	Storm	9	11	4	4	2008	2008	Meteorological	3	\N	\N
348	Null	Storm	28	28	4	4	2008	2008	Meteorological	\N	200	\N
349	Null	Storm	11	22	12	12	2008	2008	Meteorological	5	\N	\N
350	Null	Extreme temperature	11	14	12	12	2008	2008	Meteorological	\N	\N	\N
351	Null	Earthquake	21	21	2	2	2008	2008	Geophysical	\N	3	2100
352	Null	Flood	29	16	12	1	2008	2009	Hydrological	\N	\N	30000
353	Null	Storm	4	9	1	1	2008	2008	Meteorological	12	\N	\N
354	Hurricane "Gustav"	Storm	1	1	9	9	2008	2008	Meteorological	43	\N	2100000
355	Hurricane Hanna	Storm	28	28	8	8	2008	2008	Meteorological	7	\N	\N
356	Null	Wildfire	20	9	6	7	2008	2008	Climatological	1	\N	\N
357	Bimoteur	Transport accident	22	22	8	8	2008	2008	Technological	10	\N	\N
358	Null	Transport accident	8	8	8	8	2008	2008	Technological	12	26	\N
359	Null	Transport accident	5	5	10	10	2008	2008	Technological	10	30	\N
360	Null	Transport accident	13	13	9	9	2008	2008	Technological	25	135	\N
361	House	Miscellaneous accident	3	3	4	4	2008	2008	Technological	10	\N	2
362	Null	Wildfire	13	18	11	11	2008	2008	Climatological	\N	20	55000
363	Null	Storm	9	10	4	4	2009	2009	Meteorological	9	72	750
364	Null	Transport accident	16	16	3	3	2009	2009	Technological	11	18	\N
365	Null	Transport accident	16	16	4	4	2009	2009	Technological	18	66	\N
366	Gas intoxication	Industrial accident	21	21	3	3	2009	2009	Technological	11	1	\N
367	Null	Transport accident	27	27	3	3	2009	2009	Technological	17	59	\N
368	Nightclub "Santika"	Miscellaneous accident	1	1	1	1	2009	2009	Technological	66	200	\N
369	Null	Flood	24	20	3	4	2009	2009	Hydrological	2	60	5000
370	Null	Extreme temperature	26	28	1	1	2009	2009	Meteorological	58	\N	\N
371	Bombardier Dash 8 Q400	Transport accident	12	12	2	2	2009	2009	Technological	50	\N	\N
372	Null	Transport accident	22	22	3	3	2009	2009	Technological	14	\N	\N
373	Null	Flood	13	\N	12	12	2007	2007	Hydrological	3	\N	15000
374	Null	Drought	\N	\N	1	6	2007	2009	Climatological	\N	\N	2100000
375	Null	Extreme temperature	21	27	5	5	2007	2007	Meteorological	22	\N	\N
376	Null	Flood	27	2	7	8	2007	2007	Hydrological	\N	\N	38000
377	Null	Wildfire	27	30	7	7	2007	2007	Climatological	26	\N	\N
378	Null	Transport accident	19	19	2	2	2007	2007	Technological	17	45	\N
379	Null	Transport accident	24	24	5	5	2007	2007	Technological	14	3	\N
380	Null	Transport accident	19	19	8	8	2007	2007	Technological	22	\N	\N
381	Null	Transport accident	8	8	9	9	2007	2007	Technological	15	\N	\N
382	Null	Transport accident	7	7	10	10	2007	2007	Technological	12	6	\N
383	Null	Transport accident	22	22	12	12	2007	2007	Technological	10	21	\N
384	St Helena Mine	Industrial accident	2	2	10	10	2007	2007	Technological	23	\N	\N
385	Null	Miscellaneous accident	30	30	9	9	2007	2007	Technological	2	\N	\N
386	Home for old people	Miscellaneous accident	6	6	11	11	2007	2007	Technological	15	\N	\N
387	Null	Flood	19	2	12	1	2007	2008	Hydrological	24	\N	2000
388	Favio	Storm	27	27	2	2	2007	2007	Meteorological	\N	\N	\N
389	Null	Transport accident	6	6	3	3	2007	2007	Technological	34	\N	\N
390	Null	Transport accident	29	29	12	12	2007	2007	Technological	12	3	\N
391	Null	Epidemic	25	\N	5	2	2007	2008	Biological	67	\N	10000
392	Null	Storm	14	14	11	11	2008	2008	Meteorological	5	76	\N
393	Null	Flood	19	19	6	6	2008	2008	Hydrological	11	\N	4000
394	Null	Wildfire	30	3	8	9	2008	2008	Climatological	34	25	\N
395	Cholera	Epidemic	15	31	11	5	2008	2009	Biological	65	\N	12752
396	Null	Transport accident	3	3	3	3	2008	2008	Technological	10	\N	\N
397	Null	Transport accident	2	2	3	3	2008	2008	Technological	10	\N	\N
398	Null	Transport accident	3	3	4	4	2008	2008	Technological	17	53	\N
399	Null	Transport accident	27	27	5	5	2008	2008	Technological	28	20	\N
400	Null	Transport accident	7	7	10	10	2008	2008	Technological	27	\N	\N
401	Null	Transport accident	12	12	11	11	2008	2008	Technological	23	9	\N
402	Null	Transport accident	22	22	12	12	2008	2008	Technological	14	\N	5
403	Cholera	Epidemic	15	23	8	7	2008	2009	Biological	4276	\N	98349
404	Null	Transport accident	30	30	6	6	2008	2008	Technological	14	\N	\N
405	Null	Earthquake	30	30	9	9	2009	2009	Geophysical	1195	1798	2500000
406	Null	Earthquake	2	2	9	9	2009	2009	Geophysical	128	1442	338350
407	Null	Storm	3	4	1	1	2009	2009	Meteorological	18	\N	\N
408	Null	Flood	28	3	2	3	2009	2009	Hydrological	3	\N	300
409	Null	Transport accident	15	15	4	4	2009	2009	Technological	29	39	\N
410	Null	Flood	10	10	12	12	2009	2009	Hydrological	\N	\N	\N
411	Diarroheic diseases	Epidemic	\N	\N	1	12	2009	2009	Biological	107	\N	25795
412	Null	Transport accident	12	12	11	11	2009	2009	Technological	32	40	\N
413	Null	Storm	1	3	8	8	2009	2009	Meteorological	2	\N	\N
414	Null	Flood	1	9	4	4	2009	2009	Hydrological	\N	\N	200
415	Hurricane Bill	Storm	23	23	8	8	2009	2009	Meteorological	\N	3	\N
416	Null	Earthquake	8	8	11	11	2009	2009	Geophysical	2	100	1410
417	Null	Flood	15	18	9	9	2009	2009	Hydrological	38	\N	10000
418	Null	Flood	8	8	10	10	2009	2009	Hydrological	\N	\N	2500
419	Null	Flood	8	8	12	12	2009	2009	Hydrological	6	4	700
420	Null	Landslide	8	8	11	11	2009	2009	Hydrological	14	\N	\N
421	Military plane Air Force Fokker F-27	Transport accident	20	20	5	5	2009	2009	Technological	100	15	\N
422	Ferry "Dumai Express 10"	Transport accident	22	22	11	11	2009	2009	Technological	46	\N	245
423	Coal mine	Industrial accident	16	16	6	6	2009	2009	Technological	41	\N	\N
424	Aldulterated alcool	Miscellaneous accident	23	28	5	5	2009	2009	Technological	25	\N	\N
425	Karaoke club	Miscellaneous accident	4	4	12	12	2009	2009	Technological	20	13	\N
426	Mt. Merapi	Volcanic activity	24	24	10	10	2010	2010	Geophysical	322	454	136686
427	Null	Earthquake	16	16	6	6	2010	2010	Geophysical	17	\N	\N
428	Null	Flood	2	6	10	10	2010	2010	Hydrological	291	3417	9011
429	Null	Flood	23	1	2	3	2010	2010	Hydrological	44	\N	\N
430	Null	Flood	23	25	7	7	2010	2010	Hydrological	21	7	15000
431	Null	Earthquake	25	25	10	10	2010	2010	Geophysical	530	412	11452
432	Null	Flood	1	17	3	3	2010	2010	Hydrological	7	11	110875
433	Null	Flood	21	22	3	3	2010	2010	Hydrological	\N	\N	\N
434	Null	Flood	15	18	10	10	2010	2010	Hydrological	18	20	\N
435	Null	Storm	26	28	12	12	2010	2010	Meteorological	\N	\N	\N
436	Mt. Sinabung	Volcanic activity	29	7	8	9	2010	2010	Geophysical	1	1	15059
437	Null	Flood	22	22	1	1	2010	2010	Hydrological	10	\N	225
438	Null	Flood	2	5	11	11	2010	2010	Hydrological	16	\N	200
439	Null	Flood	11	11	1	1	2010	2010	Hydrological	5	\N	28500
440	Null	Flood	11	11	9	9	2010	2010	Hydrological	24	\N	\N
441	Null	Landslide	12	12	10	10	2010	2010	Hydrological	13	18	\N
442	Null	Transport accident	9	9	8	8	2010	2010	Technological	10	\N	78
443	Ferry	Transport accident	22	22	10	10	2010	2010	Technological	22	\N	44
444	Null	Transport accident	2	2	10	10	2010	2010	Technological	36	30	\N
445	Bridge	Miscellaneous accident	6	6	6	6	2010	2010	Technological	12	25	\N
446	Null	Earthquake	11	11	3	3	2011	2011	Geophysical	1	\N	\N
447	Null	Flood	3	4	1	1	2011	2011	Hydrological	17	\N	\N
448	Null	Flood	\N	\N	3	3	2011	2011	Hydrological	113	\N	65084
449	Null	Flood	4	31	4	5	2011	2011	Hydrological	5	\N	2000
450	Null	Flood	6	7	2	2	2011	2011	Hydrological	\N	\N	60
451	Null	Flood	16	20	1	1	2011	2011	Hydrological	\N	\N	12000
452	Null	Flood	10	11	3	3	2011	2011	Hydrological	21	\N	750
453	Null	Landslide	6	6	5	5	2011	2011	Hydrological	19	4	\N
454	MA-60	Transport accident	7	7	5	5	2011	2011	Technological	25	\N	\N
455	Null	Transport accident	12	12	7	7	2011	2011	Technological	16	\N	\N
456	Ferry "Laut Teduh II"	Transport accident	28	28	1	1	2011	2011	Technological	27	200	427
457	Null	Transport accident	6	6	6	6	2011	2011	Technological	28	\N	70
458	Hurricane Jimena	Storm	2	3	9	9	2009	2009	Meteorological	4	\N	72000
459	Null	Storm	10	18	6	6	2009	2009	Meteorological	1	2	\N
460	Null	Storm	16	18	4	4	2009	2009	Meteorological	6	\N	\N
461	Null	Flood	10	19	9	9	2009	2009	Hydrological	3	\N	18000
462	Null	Flood	3	10	5	5	2009	2009	Hydrological	\N	\N	\N
463	Null	Storm	26	28	3	3	2009	2009	Meteorological	6	25	\N
464	Null	Storm	20	21	7	7	2009	2009	Meteorological	1	\N	\N
465	Null	Storm	10	13	2	2	2009	2009	Meteorological	16	50	\N
466	Hurricane "Ida"	Storm	9	10	11	11	2009	2009	Meteorological	6	\N	\N
467	Hurricane Bill	Storm	23	23	8	8	2009	2009	Meteorological	3	9	\N
468	Tropical storm "Ondoy" (Ketsana)	Storm	29	30	9	9	2009	2009	Meteorological	17	91	178000
469	Tropical storm "Mirinae" (Santi)	Storm	2	3	11	11	2009	2009	Meteorological	2	\N	\N
470	Null	Transport accident	10	10	10	10	2009	2009	Technological	27	\N	13
471	Null	Flood	1	10	9	9	2009	2009	Hydrological	4	\N	1500
472	Null	Flood	1	12	11	11	2009	2009	Hydrological	\N	\N	107670
473	Null	Flood	2	2	10	10	2009	2009	Hydrological	10	14	13000
474	Null	Flood	14	16	7	7	2009	2009	Hydrological	11	\N	\N
475	Hurricane "Ida"	Storm	8	8	11	11	2009	2009	Meteorological	\N	\N	40000
476	Dengue	Epidemic	\N	\N	10	12	2009	2009	Biological	\N	\N	41687
477	Nursery	Miscellaneous accident	5	5	6	6	2009	2009	Technological	49	30	\N
478	Null	Flood	7	8	11	11	2009	2009	Hydrological	15	\N	200000
479	Null	Storm	7	9	5	5	2009	2009	Meteorological	7	\N	\N
480	Null	Storm	23	25	12	12	2009	2009	Meteorological	19	\N	\N
481	Null	Flood	6	9	4	4	2009	2009	Hydrological	\N	\N	1000
482	Null	Flood	20	21	9	9	2009	2009	Hydrological	9	\N	3000
483	Null	Wildfire	5	11	5	5	2009	2009	Climatological	\N	29	\N
484	Null	Wildfire	7	27	7	10	2009	2009	Climatological	2	\N	\N
485	Null	Transport accident	13	13	5	5	2009	2009	Technological	12	\N	16
486	Tropical storm Matthew	Storm	25	25	9	9	2010	2010	Meteorological	3	\N	1075
487	Null	Storm	10	16	5	5	2010	2010	Meteorological	20	\N	\N
488	Null	Flood	26	13	1	2	2010	2010	Hydrological	41	\N	20000
489	Hurricane Frank	Storm	23	24	8	8	2010	2010	Meteorological	6	\N	154000
490	Null	Flood	20	20	9	9	2010	2010	Hydrological	25	\N	1000000
491	Null	Storm	12	16	5	5	2010	2010	Meteorological	5	58	\N
492	Hurricane Earl	Storm	3	3	9	9	2010	2010	Meteorological	1	\N	\N
493	Tropical storm "Alex"	Storm	30	7	6	7	2010	2010	Meteorological	22	\N	170000
494	Hurricane Karl	Storm	15	17	9	9	2010	2010	Meteorological	12	\N	230000
495	Null	Storm	17	20	6	6	2010	2010	Meteorological	20	100	\N
496	Null	Storm	30	3	4	5	2010	2010	Meteorological	30	\N	8000
497	Null	Storm	13	15	3	3	2010	2010	Meteorological	11	\N	\N
498	Tropical storm Hermine	Storm	7	11	9	9	2010	2010	Meteorological	8	\N	\N
499	Oil platform "Deepwater Horizon"	Industrial accident	20	20	4	4	2010	2010	Technological	11	17	\N
500	Null	Flood	20	9	10	11	2010	2010	Hydrological	8	\N	\N
501	Poisoning	Miscellaneous accident	18	18	10	10	2010	2010	Technological	12	\N	\N
502	Stampede	Miscellaneous accident	22	22	11	11	2010	2010	Technological	346	388	\N
503	Null	Earthquake	4	4	4	4	2010	2010	Geophysical	2	232	25000
504	Null	Landslide	21	21	9	9	2010	2010	Hydrological	27	\N	\N
505	Null	Landslide	28	29	9	9	2010	2010	Hydrological	44	\N	\N
506	Helicopter Bell 412	Transport accident	17	18	6	6	2010	2010	Technological	11	\N	\N
507	Helicopter	Transport accident	8	8	12	12	2010	2010	Technological	11	\N	\N
508	Null	Transport accident	3	3	9	9	2010	2010	Technological	13	11	\N
509	Null	Transport accident	18	18	10	10	2010	2010	Technological	18	\N	\N
510	Null	Transport accident	6	6	11	11	2010	2010	Technological	21	\N	\N
511	Null	Transport accident	15	15	6	6	2010	2010	Technological	11	4	\N
512	Pipeline	Industrial accident	19	19	12	12	2010	2010	Technological	27	52	\N
513	Null	Flood	10	10	10	12	2010	2010	Hydrological	258	\N	8970653
514	Dengue	Epidemic	\N	10	8	8	2010	2010	Biological	2	\N	880
515	Null	Drought	\N	\N	3	3	2010	2011	Climatological	\N	\N	6482602
516	Refugee camp "Karreni"	Miscellaneous accident	24	24	3	3	2010	2010	Technological	\N	\N	\N
517	Null	Storm	24	24	4	4	2010	2010	Meteorological	12	70	2700
518	Null	Storm	31	1	12	1	2010	2011	Meteorological	8	13	\N
519	Null	Storm	5	11	2	2	2010	2010	Meteorological	2	\N	\N
520	Null	Storm	23	28	2	2	2010	2010	Meteorological	1	\N	\N
521	Null	Storm	26	26	12	12	2010	2010	Meteorological	\N	\N	\N
522	Null	Earthquake	10	10	1	1	2010	2010	Geophysical	\N	30	600
523	Null	Flood	27	31	3	3	2010	2010	Hydrological	\N	\N	\N
524	Null	Flood	10	11	6	6	2010	2010	Hydrological	20	\N	\N
525	Null	Flood	19	19	12	12	2010	2010	Hydrological	\N	\N	1000
526	Coal mine "Upper Big Branch"	Industrial accident	5	5	4	4	2010	2010	Technological	27	2	\N
527	Gazoduc	Industrial accident	7	7	6	6	2010	2010	Technological	13	\N	\N
528	Gas pipeline	Miscellaneous accident	9	9	9	9	2010	2010	Technological	8	60	\N
529	Tropical storm "Beatrix"	Storm	20	20	6	6	2011	2011	Meteorological	3	\N	450
530	Null	Storm	29	1	5	6	2011	2011	Meteorological	3	200	\N
531	Tropical Storm "Arlene"	Storm	30	1	6	7	2011	2011	Meteorological	22	\N	300000
532	Null	Flood	23	5	3	4	2011	2011	Hydrological	64	\N	716110
533	Null	Storm	31	2	1	2	2011	2011	Meteorological	39	\N	\N
534	Null	Wildfire	\N	\N	3	5	2011	2011	Climatological	\N	\N	\N
535	Tropical storm "Dora"	Storm	20	20	7	7	2011	2011	Meteorological	3	\N	200000
536	Topical storm Juaning (Nock-ten)	Storm	4	6	8	8	2011	2011	Meteorological	18	\N	1000000
537	Null	Storm	22	29	4	4	2011	2011	Meteorological	354	2200	\N
538	Null	Extreme temperature	1	8	2	2	2011	2011	Meteorological	3	\N	120000
539	Coal mine	Industrial accident	3	3	5	5	2011	2011	Technological	14	\N	\N
540	Prison	Miscellaneous accident	20	20	5	5	2011	2011	Technological	14	\N	\N
541	Null	Earthquake	24	24	3	3	2011	2011	Geophysical	1	16	\N
542	Null	Storm	14	16	4	4	2011	2011	Meteorological	46	43	\N
543	Null	Storm	20	25	5	5	2011	2011	Meteorological	176	1150	\N
544	Null	Storm	24	24	5	5	2011	2011	Meteorological	11	\N	\N
545	Null	Flood	1	24	5	5	2011	2011	Hydrological	1	\N	25000
546	Null	Extreme temperature	19	22	7	7	2011	2011	Meteorological	22	\N	\N
547	Null	Wildfire	9	30	4	4	2011	2011	Climatological	2	5	\N
548	Null	Transport accident	12	12	3	3	2011	2011	Technological	14	20	\N
549	Null	Storm	19	19	11	11	2009	2009	Meteorological	1	\N	\N
550	Null	Flood	12	16	7	7	2009	2009	Hydrological	11	\N	20000
551	Null	Transport accident	1	1	2	2	2009	2009	Technological	\N	160	\N
552	Null	Transport accident	1	1	2	2	2009	2009	Technological	\N	100	\N
553	Gold mine	Industrial accident	1	1	6	6	2009	2009	Technological	61	\N	\N
554	Cholera	Epidemic	\N	22	8	11	2009	2009	Biological	5	\N	146
555	Meales	Epidemic	\N	\N	10	2	2009	2010	Biological	50	\N	1200
556	Null	Transport accident	2	2	8	8	2009	2009	Technological	33	\N	\N
557	Null	Storm	15	12	12	1	2010	2011	Meteorological	40	\N	6000
558	Null	Drought	\N	\N	5	\N	2010	2013	Climatological	\N	\N	1667618
559	Null	Transport accident	5	5	5	5	2010	2010	Technological	24	15	\N
560	Null	Transport accident	23	23	10	10	2010	2010	Technological	18	7	\N
561	Null	Transport accident	23	23	12	12	2010	2010	Technological	20	18	\N
562	Orphanage	Miscellaneous accident	9	9	2	2	2010	2010	Technological	15	9	\N
563	House for old people	Miscellaneous accident	1	2	8	8	2010	2010	Technological	22	\N	84
564	Null	Flood	4	4	3	3	2010	2010	Hydrological	\N	\N	820
565	Cholera	Epidemic	4	14	2	3	2010	2010	Biological	3	\N	120
566	Typhoid fever	Epidemic	1	14	1	3	2010	2010	Biological	5	\N	138
567	Null	Transport accident	4	4	7	7	2010	2010	Technological	18	31	\N
568	Hurricane Irene	Storm	28	29	8	8	2011	2011	Meteorological	1	\N	\N
569	Mt. Gamalama	Volcanic activity	4	27	12	12	2011	2011	Geophysical	3	5	2368
570	Null	Flood	1	4	1	2	2011	2011	Hydrological	40	321	200000
571	Null	Transport accident	26	26	6	6	2011	2011	Technological	15	10	\N
572	Null	Transport accident	19	19	5	5	2011	2011	Technological	\N	857	\N
573	Crush	Miscellaneous accident	1	1	1	1	2011	2011	Technological	10	\N	\N
574	Psychological aid centre	Miscellaneous accident	12	13	6	6	2011	2011	Technological	22	27	\N
575	Null	Flood	\N	\N	3	3	2011	2011	Hydrological	\N	\N	\N
576	Null	Transport accident	7	7	1	1	2011	2011	Technological	12	\N	\N
577	Null	Flood	15	9	12	1	2011	2012	Hydrological	\N	\N	5500
578	Null	Flood	\N	\N	12	12	2011	2011	Hydrological	\N	\N	20000
579	Null	Transport accident	14	14	9	9	2011	2011	Technological	17	\N	\N
580	Null	Storm	21	24	8	8	2011	2011	Meteorological	1	20	\N
581	Null	Wildfire	14	16	5	5	2011	2011	Climatological	1	\N	\N
582	Boeing 737	Transport accident	20	20	8	8	2011	2011	Technological	12	3	\N
583	Null	Earthquake	5	5	9	9	2011	2011	Geophysical	10	\N	\N
584	Mt. Lokon	Volcanic activity	11	17	7	7	2011	2011	Geophysical	\N	\N	\N
585	Null	Flood	1	10	4	4	2011	2011	Hydrological	18	\N	3000
586	Null	Flood	18	22	12	12	2011	2011	Hydrological	10	\N	54
587	Null	Flood	17	31	3	3	2011	2011	Hydrological	13	\N	\N
588	Null	Landslide	30	30	11	11	2011	2011	Hydrological	34	\N	\N
589	Helicopter Bell 412	Transport accident	3	3	8	8	2011	2011	Technological	10	\N	\N
590	Cassa 212	Transport accident	29	29	9	9	2011	2011	Technological	18	\N	\N
591	Null	Transport accident	27	27	8	8	2011	2011	Technological	7	\N	93
592	Null	Transport accident	22	22	9	9	2011	2011	Technological	25	\N	11
593	Null	Transport accident	17	17	12	12	2011	2011	Technological	203	\N	13
594	Bridge	Miscellaneous accident	26	26	11	11	2011	2011	Technological	48	39	\N
595	Tropical Cyclone Iggy	Storm	25	25	1	1	2012	2012	Meteorological	16	60	10000
596	Null	Flood	31	31	7	7	2012	2012	Hydrological	8	\N	3770
597	Null	Flood	24	24	7	7	2012	2012	Hydrological	8	\N	625
598	Null	Flood	24	25	12	12	2012	2012	Hydrological	3	\N	10500
599	Null	Drought	\N	\N	3	5	2012	2013	Climatological	\N	\N	1833900
600	Stampede	Miscellaneous accident	31	31	12	12	2012	2012	Technological	16	100	\N
601	Null	Storm	24	27	12	12	2012	2012	Meteorological	\N	\N	\N
602	Null	Storm	12	12	8	8	2012	2012	Meteorological	\N	\N	\N
603	Null	Flood	25	30	3	3	2012	2012	Hydrological	\N	\N	1500
604	Null	Transport accident	6	6	2	2	2012	2012	Technological	11	\N	\N
605	Null	Storm	25	25	2	2	2012	2012	Meteorological	5	\N	\N
606	Null	Earthquake	11	11	4	4	2012	2012	Geophysical	7	107	\N
607	Null	Earthquake	18	18	8	8	2012	2012	Geophysical	6	43	5485
608	Null	Flood	12	12	9	9	2012	2012	Hydrological	\N	\N	1150
609	Null	Flood	25	25	8	8	2012	2012	Hydrological	4	5	1040
610	Null	Flood	7	9	11	11	2012	2012	Hydrological	13	\N	15210
611	Null	Flood	9	9	5	5	2012	2012	Hydrological	5	20	\N
612	Null	Landslide	24	27	5	5	2012	2012	Hydrological	20	100	115
613	Null	Landslide	24	24	5	5	2012	2012	Hydrological	12	\N	\N
614	Superjet 100	Transport accident	9	9	5	5	2012	2012	Technological	46	\N	\N
615	Fooker F 27	Transport accident	21	21	6	6	2012	2012	Technological	10	\N	\N
616	Null	Transport accident	1	1	5	5	2012	2012	Technological	13	\N	\N
617	Null	Transport accident	17	17	6	6	2012	2012	Technological	58	\N	12
618	Ferry	Transport accident	13	13	9	9	2012	2012	Technological	23	\N	\N
619	Null	Transport accident	28	28	9	9	2012	2012	Technological	38	\N	207
620	Null	Earthquake	2	2	7	7	2013	2013	Geophysical	48	2532	53403
621	Null	Flood	15	22	2	2	2013	2013	Hydrological	17	\N	58040
622	Null	Flood	28	30	7	7	2013	2013	Hydrological	12	\N	8140
623	Null	Flood	6	7	4	4	2013	2013	Hydrological	9	\N	1000
624	Null	Transport accident	5	6	1	1	2013	2013	Technological	16	3	\N
625	Null	Extreme temperature	21	22	12	12	2013	2013	Meteorological	10	\N	\N
626	Null	Flood	20	27	6	6	2013	2013	Hydrological	4	\N	100000
627	Null	Transport accident	21	21	3	3	2013	2013	Technological	\N	100	\N
628	Null	Transport accident	6	6	7	7	2013	2013	Technological	47	\N	2000
629	Null	Earthquake	22	22	1	1	2013	2013	Geophysical	1	15	500
630	Null	Earthquake	22	22	10	10	2013	2013	Geophysical	1	3	2735
631	Null	Flood	17	31	1	1	2013	2013	Hydrological	34	\N	248846
632	Null	Flood	3	10	1	1	2013	2013	Hydrological	8	\N	1000
633	Null	Flood	7	11	4	4	2013	2013	Hydrological	11	\N	115000
634	Null	Flood	12	12	9	9	2013	2013	Hydrological	\N	\N	23640
635	Null	Flood	7	14	10	10	2013	2013	Hydrological	\N	\N	16000
636	Null	Landslide	25	27	1	1	2013	2013	Hydrological	21	3	\N
637	Null	Landslide	25	25	3	3	2013	2013	Hydrological	13	\N	\N
638	Null	Transport accident	23	23	7	7	2013	2013	Technological	11	\N	189
639	Null	Transport accident	30	30	9	9	2013	2013	Technological	36	\N	\N
640	Gold mine	Industrial accident	14	14	5	5	2013	2013	Technological	28	\N	10
641	Stampede	Miscellaneous accident	14	14	7	7	2013	2013	Technological	17	38	\N
642	Hurricane Jova	Storm	10	1	10	11	2011	2011	Meteorological	5	\N	50000
643	Null	Flood	5	4	8	1	2011	2012	Hydrological	813	\N	9500000
644	Hurricane Nate	Storm	9	9	9	9	2011	2011	Meteorological	10	\N	\N
645	Null	Flood	10	1	8	11	2011	2011	Hydrological	247	23	1640000
646	Null	Earthquake	11	11	12	12	2011	2011	Geophysical	2	2	150
647	Null	Flood	20	20	10	10	2011	2011	Hydrological	\N	\N	250000
648	Null	Flood	18	18	7	7	2011	2011	Hydrological	3	\N	190000
649	Null	Flood	23	7	8	9	2011	2011	Hydrological	74	\N	\N
650	Null	Drought	\N	\N	9	12	2011	2011	Climatological	\N	\N	2500000
651	Dengue	Epidemic	\N	\N	9	9	2011	2011	Biological	27	\N	37728
652	Null	Transport accident	31	31	12	12	2011	2011	Technological	12	4	\N
653	Null	Drought	\N	\N	6	\N	2011	2011	Climatological	\N	\N	\N
654	Null	Storm	2	4	3	3	2012	2012	Meteorological	41	\N	\N
655	Null	Flood	17	26	9	9	2012	2012	Hydrological	14	\N	71500
656	Null	Earthquake	20	20	3	3	2012	2012	Geophysical	2	11	45000
657	Ernesto	Storm	10	10	8	8	2012	2012	Meteorological	12	\N	\N
658	Hurricane Carlotta	Storm	15	15	6	6	2012	2012	Meteorological	7	\N	87000
659	Null	Transport accident	20	20	4	4	2012	2012	Technological	43	20	\N
660	Null	Transport accident	24	24	6	6	2012	2012	Technological	28	22	\N
661	Gaz factory	Industrial accident	19	19	9	9	2012	2012	Technological	32	26	\N
662	Null	Flood	15	30	8	9	2012	2012	Hydrological	\N	\N	235545
663	Petrochimical plant	Industrial accident	5	5	5	5	2012	2012	Technological	12	129	\N
664	Null	Drought	\N	\N	4	8	2012	2012	Climatological	\N	\N	12000000
665	Null	Storm	30	30	6	6	2012	2012	Meteorological	1	\N	\N
666	Null	Storm	25	30	5	5	2012	2012	Meteorological	\N	\N	\N
667	Null	Storm	6	7	6	6	2012	2012	Meteorological	\N	2	\N
668	Null	Storm	11	13	6	6	2012	2012	Meteorological	\N	3	9000
669	Null	Storm	2	4	7	7	2012	2012	Meteorological	1	\N	\N
670	Null	Storm	7	9	9	9	2012	2012	Meteorological	5	\N	\N
671	Null	Storm	22	23	1	1	2012	2012	Meteorological	2	100	\N
672	Null	Storm	28	29	2	2	2012	2012	Meteorological	14	200	\N
673	Null	Storm	2	3	4	4	2012	2012	Meteorological	\N	\N	3300
674	Null	Storm	14	15	4	4	2012	2012	Meteorological	6	30	\N
675	Tropical storm Fernand	Storm	25	26	8	8	2013	2013	Meteorological	14	\N	5000
676	Hurricane Manuel	Storm	13	20	9	9	2013	2013	Meteorological	169	\N	105000
677	Hurricane Ingrid	Storm	12	17	9	9	2013	2013	Meteorological	23	\N	50000
678	Null	Storm	2	3	8	8	2013	2013	Meteorological	\N	\N	\N
679	Null	Flood	5	8	9	9	2013	2013	Hydrological	13	\N	\N
680	Null	Flood	24	14	9	10	2013	2013	Hydrological	200	\N	1500000
681	Hurricane Barbara	Storm	29	29	5	5	2013	2013	Meteorological	4	\N	12000
682	Null	Transport accident	14	14	10	10	2013	2013	Technological	14	\N	\N
683	Null	Transport accident	7	7	5	5	2013	2013	Technological	25	14	\N
684	Null	Transport accident	4	4	10	10	2013	2013	Technological	12	25	\N
685	Oil company Pemex Building	Industrial accident	31	31	1	1	2013	2013	Technological	37	100	\N
686	Fireworks	Miscellaneous accident	15	15	3	3	2013	2013	Technological	17	80	\N
687	Null	Industrial accident	22	22	8	8	2013	2013	Technological	9	40	1500
688	Null	Flood	25	27	7	7	2013	2013	Hydrological	\N	\N	\N
689	Null	Flood	30	14	9	10	2013	2013	Hydrological	61	\N	3500000
690	Null	Flood	20	8	11	12	2013	2013	Hydrological	23	\N	\N
691	Null	Transport accident	23	23	7	7	2013	2013	Technological	19	\N	\N
692	Null	Transport accident	23	23	10	10	2013	2013	Technological	20	16	\N
693	Null	Transport accident	27	27	12	12	2013	2013	Technological	29	4	\N
694	Null	Transport accident	22	22	7	7	2013	2013	Technological	10	\N	\N
695	Refugees camp	Miscellaneous accident	22	22	3	3	2013	2013	Technological	42	\N	\N
696	Null	Storm	12	13	6	6	2013	2013	Meteorological	4	\N	\N
697	Null	Flood	18	23	4	5	2011	2011	Hydrological	9	\N	\N
698	Hurricane Irene	Storm	27	13	8	9	2011	2011	Meteorological	46	\N	370000
699	Tropical Storm Lee	Storm	4	9	9	9	2011	2011	Meteorological	15	\N	600
700	Null	Storm	31	31	12	12	2011	2011	Meteorological	5	50	\N
701	Null	Storm	29	31	10	10	2011	2011	Meteorological	29	\N	\N
702	Null	Storm	20	20	12	12	2011	2011	Meteorological	6	\N	\N
703	Null	Storm	7	12	1	1	2011	2011	Meteorological	11	\N	\N
704	Null	Storm	17	24	1	1	2011	2011	Meteorological	10	\N	\N
705	Null	Flood	6	9	8	8	2011	2011	Hydrological	2	\N	100
706	Null	Flood	15	30	5	6	2011	2011	Hydrological	5	\N	\N
707	Null	Storm	3	5	4	4	2011	2011	Meteorological	9	\N	\N
708	Null	Storm	13	14	8	8	2011	2011	Meteorological	7	\N	\N
709	Null	Wildfire	4	9	9	9	2011	2011	Climatological	4	\N	\N
710	Null	Wildfire	29	23	5	6	2011	2011	Climatological	2	\N	\N
711	P-51 Mustang	Transport accident	19	19	9	9	2011	2011	Technological	10	60	\N
712	Null	Drought	\N	\N	1	11	2011	2011	Climatological	\N	\N	\N
713	Null	Storm	2	3	10	10	2011	2011	Meteorological	1	167	2606
714	Null	Transport accident	24	24	8	8	2011	2011	Technological	15	42	\N
715	Null	Transport accident	1	1	12	12	2011	2011	Technological	17	\N	\N
716	Null	Transport accident	10	10	12	12	2011	2011	Technological	30	7	\N
717	Null	Transport accident	8	8	4	4	2011	2011	Technological	1	200	\N
718	Cholera	Epidemic	1	17	1	7	2011	2011	Biological	45	\N	1140
719	Null	Transport accident	2	2	8	8	2011	2011	Technological	13	\N	\N
720	Null	Transport accident	31	31	7	7	2011	2011	Technological	19	\N	\N
721	Null	Transport accident	25	25	8	8	2011	2011	Technological	19	20	\N
722	Null	Transport accident	25	25	12	12	2011	2011	Technological	11	\N	\N
723	Hurricane Sandy	Storm	28	28	10	10	2012	2012	Meteorological	54	\N	\N
724	Null	Drought	\N	\N	6	\N	2012	2012	Climatological	\N	\N	\N
725	Null	Drought	\N	\N	6	12	2012	2012	Climatological	\N	\N	\N
726	Hurricane Isaac	Storm	28	29	8	8	2012	2012	Meteorological	1	\N	60000
727	Tropical Storm Dando	Storm	\N	\N	1	1	2012	2012	Meteorological	\N	\N	1350
728	Null	Storm	19	21	12	12	2012	2012	Meteorological	7	\N	\N
729	Null	Storm	25	27	12	12	2012	2012	Meteorological	17	\N	\N
730	Null	Storm	18	23	1	1	2012	2012	Meteorological	3	1	\N
731	Null	Storm	28	2	6	7	2012	2012	Meteorological	28	\N	\N
732	Null	Storm	28	29	4	4	2012	2012	Meteorological	1	100	\N
733	Null	Flood	9	12	6	6	2012	2012	Hydrological	2	\N	300
734	Tropical storm Debby	Storm	22	27	6	6	2012	2012	Meteorological	9	1	17000
735	Null	Extreme temperature	30	19	6	7	2012	2012	Meteorological	123	\N	\N
736	Waldo Canyon Fire	Wildfire	23	10	6	7	2012	2012	Climatological	2	\N	\N
737	Null	Wildfire	3	8	8	8	2012	2012	Climatological	1	\N	1809
738	Null	Flood	24	29	10	10	2012	2012	Hydrological	13	\N	125000
739	Military plane Dakota	Transport accident	5	5	12	12	2012	2012	Technological	11	\N	\N
740	Null	Transport accident	12	12	7	7	2012	2012	Technological	\N	\N	\N
741	Null	Transport accident	25	25	6	6	2012	2012	Technological	19	55	\N
742	Null	Transport accident	15	15	9	9	2012	2012	Technological	11	\N	\N
743	Null	Transport accident	13	13	7	7	2012	2012	Technological	23	26	\N
744	Null	Industrial accident	26	26	5	5	2012	2012	Technological	10	\N	\N
745	Bridge	Miscellaneous accident	10	10	12	12	2012	2012	Technological	13	\N	\N
746	Null	Transport accident	25	25	3	3	2012	2012	Technological	15	28	\N
747	Null	Storm	1	1	6	6	2013	2013	Meteorological	3	\N	2870
748	Null	Flood	12	19	9	9	2013	2013	Hydrological	9	\N	16500
749	Null	Storm	18	22	5	5	2013	2013	Meteorological	29	450	\N
750	Null	Storm	15	17	5	5	2013	2013	Meteorological	6	100	\N
751	Null	Storm	16	18	11	11	2013	2013	Meteorological	11	185	\N
752	Null	Flood	\N	\N	1	1	2013	2013	Hydrological	125	\N	9700
753	Null	Storm	8	9	2	2	2013	2013	Meteorological	15	\N	\N
754	Null	Storm	24	24	11	11	2013	2013	Meteorological	14	\N	\N
755	Null	Storm	17	19	4	4	2013	2013	Meteorological	3	\N	\N
756	Null	Storm	8	9	7	7	2013	2013	Meteorological	\N	\N	\N
757	Null	Storm	29	30	1	1	2013	2013	Meteorological	3	18	1089
758	Null	Storm	26	6	5	6	2013	2013	Meteorological	27	150	170000
759	Null	Storm	9	11	2	2	2013	2013	Meteorological	1	82	4800
760	Null	Extreme temperature	19	22	12	12	2013	2013	Meteorological	19	\N	\N
761	Null	Storm	7	11	4	4	2013	2013	Meteorological	4	\N	\N
762	Null	Flood	27	28	7	7	2013	2013	Hydrological	2	\N	1425
763	Null	Flood	5	12	8	8	2013	2013	Hydrological	3	\N	6000
764	Null	Flood	25	28	5	5	2013	2013	Hydrological	3	\N	300
765	Null	Flood	22	29	4	4	2013	2013	Hydrological	5	\N	300
766	Null	Flood	31	10	10	11	2013	2013	Hydrological	4	\N	4800
767	Null	Wildfire	30	8	5	6	2013	2013	Climatological	\N	8	12
768	Null	Wildfire	6	20	6	6	2013	2013	Climatological	2	\N	84
769	Null	Wildfire	28	12	6	7	2013	2013	Climatological	19	\N	\N
770	Fetilizer plant	Industrial accident	21	21	5	5	2013	2013	Technological	15	200	420
771	Null	Wildfire	3	1	8	9	2013	2013	Climatological	\N	3	\N
772	Null	Wildfire	9	15	9	9	2013	2013	Climatological	1	6	15
773	Null	Transport accident	15	15	3	3	2013	2013	Technological	24	45	\N
774	Null	Transport accident	5	5	9	9	2013	2013	Technological	27	30	\N
775	Null	Transport accident	12	12	11	11	2013	2013	Technological	29	\N	\N
776	Null	Transport accident	22	22	11	11	2013	2013	Technological	11	\N	\N
777	Null	Transport accident	22	22	11	11	2013	2013	Technological	14	\N	\N
778	Null	Transport accident	31	31	1	1	2013	2013	Technological	\N	200	\N
779	Commercial market	Industrial accident	20	20	11	11	2013	2013	Technological	30	29	\N
780	Shanty town	Miscellaneous accident	1	1	1	1	2013	2013	Technological	3	1	\N
781	Null	Transport accident	30	30	10	10	2013	2013	Technological	21	\N	\N
782	Null	Flood	4	4	8	8	2014	2014	Hydrological	\N	4	6900
783	Null	Transport accident	10	10	10	10	2014	2014	Technological	26	\N	\N
784	Null	Extreme temperature	1	9	1	1	2014	2014	Meteorological	\N	\N	\N
785	Elderly house	Miscellaneous accident	23	23	1	1	2014	2014	Technological	32	\N	\N
786	Null	Flood	9	23	3	3	2015	2015	Hydrological	1	\N	2000
787	Null	Flood	13	14	2	2	2015	2015	Hydrological	5	\N	\N
788	Null	Flood	9	23	3	3	2015	2015	Hydrological	69	\N	1000
789	Yellow fever	Epidemic	5	20	12	10	2015	2016	Biological	384	4599	\N
790	Null	Wildfire	1	10	7	7	2015	2015	Climatological	\N	\N	13000
791	Fort McMurray wildfires	Wildfire	1	4	5	7	2016	2016	Climatological	\N	\N	88000
792	Null	Flood	29	1	2	3	2016	2016	Hydrological	54	\N	\N
793	Null	Flood	3	6	3	3	2016	2016	Hydrological	6	\N	\N
794	Null	Flood	16	22	4	4	2016	2016	Hydrological	23	\N	3200
795	Mt. Sinabung	Volcanic activity	\N	\N	9	12	2013	2013	Geophysical	\N	\N	29727
796	Null	Flood	28	30	12	12	2013	2013	Hydrological	\N	\N	22500
797	Null	Flood	14	15	12	12	2013	2013	Hydrological	4	\N	84250
798	Null	Flood	26	28	2	2	2013	2013	Hydrological	3	\N	13860
799	Boris	Storm	30	6	5	6	2014	2014	Meteorological	\N	\N	\N
800	Hurricane Odile	Storm	10	17	9	9	2014	2014	Meteorological	6	135	75000
801	Tropical storm Trudy	Storm	18	20	10	10	2014	2014	Meteorological	6	\N	30000
802	Null	Flood	14	17	1	1	2014	2014	Hydrological	20	\N	128182
803	Null	Flood	24	28	1	1	2014	2014	Hydrological	\N	\N	259100
804	Null	Flood	19	22	1	1	2014	2014	Hydrological	11	\N	\N
805	Null	Storm	16	16	3	3	2014	2014	Meteorological	\N	\N	\N
806	Tropical storm Dolly	Storm	4	8	9	9	2014	2014	Meteorological	1	\N	1500
807	Hurricane Marie	Storm	22	2	8	9	2014	2014	Meteorological	3	\N	30000
808	Hurricane Norbert	Storm	2	11	9	9	2014	2014	Meteorological	3	\N	7500
809	Mt. Sinabung	Volcanic activity	1	1	2	2	2014	2014	Geophysical	32	2	32000
810	Mt. Kelud	Volcanic activity	14	14	2	2	2014	2014	Geophysical	7	70	83088
811	Null	Flood	8	7	1	2	2014	2014	Hydrological	32	\N	20000
812	Null	Flood	25	25	2	2	2014	2014	Hydrological	13	\N	275
813	Null	Flood	22	24	11	11	2014	2014	Hydrological	1	\N	10420
814	Null	Landslide	28	28	1	1	2014	2014	Hydrological	19	\N	\N
815	Null	Landslide	12	20	12	12	2014	2014	Hydrological	108	\N	1900
816	Airbus A320-220	Transport accident	28	28	12	12	2014	2014	Technological	162	\N	\N
817	Null	Transport accident	30	30	7	7	2014	2014	Technological	19	\N	\N
818	Null	Transport accident	29	29	7	7	2014	2014	Technological	17	\N	53
819	Null	Transport accident	16	16	9	9	2014	2014	Technological	21	\N	\N
820	Ferry	Transport accident	7	7	10	10	2014	2014	Technological	43	\N	\N
821	Building in construction	Industrial accident	3	3	6	6	2014	2014	Technological	15	3	\N
822	Gold mine	Industrial accident	5	5	10	10	2014	2014	Technological	18	\N	\N
823	Null	Industrial accident	1	1	7	7	2014	2014	Technological	13	2	\N
824	Null	Flood	30	31	7	8	2014	2014	Hydrological	45	\N	472500
825	Null	Earthquake	18	18	4	4	2014	2014	Geophysical	\N	\N	381
826	Null	Earthquake	7	7	7	7	2014	2014	Geophysical	3	\N	27000
827	Null	Earthquake	5	5	5	5	2014	2014	Geophysical	1	23	17500
828	Null	Flood	7	16	11	11	2014	2014	Hydrological	\N	\N	12000
829	Null	Flood	1	8	9	9	2014	2014	Hydrological	10	\N	73260
830	Null	Flood	\N	\N	12	12	2014	2014	Hydrological	4	\N	27140
831	Null	Flood	13	31	12	12	2014	2014	Hydrological	15	8	18880
832	Null	Extreme temperature	\N	\N	1	1	2014	2014	Meteorological	63	\N	1000000
833	Null	Transport accident	28	28	2	2	2014	2014	Technological	15	13	\N
834	Null	Transport accident	24	24	3	3	2014	2014	Technological	30	20	\N
835	Null	Transport accident	25	25	3	3	2014	2014	Technological	30	20	\N
836	Construction plant of an hospital	Industrial accident	25	25	2	2	2014	2014	Technological	10	17	\N
837	Null	Drought	\N	\N	3	3	2014	2014	Climatological	\N	\N	\N
838	Null	Storm	26	28	3	3	2015	2015	Meteorological	14	229	1242
839	Null	Drought	\N	\N	7	7	2015	2015	Climatological	11	\N	\N
840	Null	Flood	15	23	3	3	2015	2015	Hydrological	\N	\N	8000
841	Hurricane Patricia	Storm	22	28	10	10	2015	2015	Meteorological	14	\N	15000
842	Null	Earthquake	24	24	9	9	2015	2015	Geophysical	\N	62	12185
843	Null	Flood	23	25	1	1	2015	2015	Hydrological	1	\N	8244
844	Null	Flood	5	9	2	2	2015	2015	Hydrological	\N	\N	300
845	Null	Flood	30	2	1	2	2015	2015	Hydrological	2	\N	25000
846	Null	Flood	8	13	2	2	2015	2015	Hydrological	6	\N	\N
847	Null	Landslide	6	6	5	5	2015	2015	Hydrological	13	\N	\N
848	Null	Landslide	3	3	12	12	2015	2015	Hydrological	20	\N	\N
849	Null	Landslide	28	28	3	3	2015	2015	Hydrological	12	\N	\N
850	Null	Wildfire	\N	\N	9	12	2015	2015	Climatological	19	\N	409664
851	Hercules C-130	Transport accident	30	30	6	6	2015	2015	Technological	142	\N	\N
852	ATR 42300	Transport accident	16	16	8	8	2015	2015	Technological	54	\N	\N
853	Null	Transport accident	6	6	12	12	2015	2015	Technological	16	\N	\N
854	Null	Transport accident	13	13	12	12	2015	2015	Technological	14	\N	\N
855	Ferry	Transport accident	19	19	12	12	2015	2015	Technological	78	37	\N
856	Null	Flood	15	\N	7	7	2015	2015	Hydrological	\N	\N	25750
857	Null	Storm	25	26	5	5	2015	2015	Meteorological	14	229	1350
858	Null	Flood	13	23	3	3	2015	2015	Hydrological	\N	\N	3000
859	Null	Transport accident	27	27	1	1	2015	2015	Technological	16	20	\N
860	Null	Transport accident	26	26	3	3	2015	2015	Technological	18	3	\N
861	Null	Transport accident	29	29	7	7	2015	2015	Technological	27	100	\N
862	Null	Transport accident	22	22	11	11	2015	2015	Technological	23	10	\N
863	Null	Transport accident	19	19	12	12	2015	2015	Technological	15	30	\N
864	Null	Transport accident	13	13	2	2	2015	2015	Technological	20	31	\N
865	Null	Transport accident	20	20	12	12	2015	2015	Technological	13	\N	\N
866	Null	Drought	\N	\N	1	5	2015	2017	Climatological	\N	\N	\N
867	Null	Flood	8	13	3	3	2016	2016	Hydrological	5	\N	24000
868	Null	Flood	7	12	2	2	2016	2016	Hydrological	8	\N	80313
869	Null	Flood	7	8	3	3	2016	2016	Hydrological	6	\N	12500
870	Null	Landslide	17	21	6	6	2016	2016	Hydrological	62	\N	\N
871	Null	Drought	\N	\N	5	5	2016	2016	Climatological	\N	\N	2500000
872	Null	Earthquake	16	16	1	1	2016	2016	Geophysical	\N	8	360
873	Null	Landslide	15	15	5	5	2016	2016	Hydrological	15	\N	\N
874	Null	Transport accident	26	26	6	6	2016	2016	Technological	12	\N	1
875	Null	Flood	19	24	2	2	2016	2016	Hydrological	\N	\N	30000
876	Null	Transport accident	11	11	1	1	2016	2016	Technological	21	\N	\N
877	Null	Transport accident	28	28	2	2	2016	2016	Technological	12	28	\N
878	Petrochimical plant	Industrial accident	21	21	4	4	2016	2016	Technological	32	100	\N
879	Null	Extreme temperature	20	26	1	1	2016	2016	Meteorological	14	\N	\N
880	Dormitory	Miscellaneous accident	23	23	5	5	2016	2016	Technological	17	5	\N
881	Null	Drought	\N	\N	1	1	2013	2017	Climatological	\N	\N	4300000
882	Null	Storm	24	25	2	2	2013	2013	Meteorological	1	\N	\N
883	Cleon and Dion	Storm	1	9	12	12	2013	2013	Meteorological	20	\N	\N
884	Null	Storm	18	19	3	3	2013	2013	Meteorological	2	\N	\N
885	Null	Flood	22	31	12	12	2013	2013	Hydrological	5	\N	\N
886	Boeing 777	Transport accident	6	6	7	7	2013	2013	Technological	3	182	\N
887	Null	Storm	10	17	12	12	2014	2014	Meteorological	3	\N	\N
888	Null	Storm	26	27	7	7	2014	2014	Meteorological	\N	\N	300
889	Null	Storm	27	1	4	5	2014	2014	Meteorological	40	15	\N
890	Null	Storm	12	14	10	10	2014	2014	Meteorological	2	\N	\N
891	Null	Earthquake	24	24	8	8	2014	2014	Geophysical	1	250	3000
892	Null	Flood	2	5	12	12	2014	2014	Hydrological	\N	\N	\N
893	Null	Flood	1	18	3	3	2014	2014	Hydrological	32	\N	7185
894	Null	Flood	20	10	1	2	2014	2014	Hydrological	3	2	1000
895	Null	Storm	18	23	5	5	2014	2014	Meteorological	\N	\N	\N
896	Null	Storm	3	6	6	6	2014	2014	Meteorological	2	36	\N
897	Null	Storm	2	6	2	2	2014	2014	Meteorological	9	\N	\N
898	Null	Storm	11	14	2	2	2014	2014	Meteorological	25	\N	\N
899	Null	Storm	1	5	1	1	2014	2014	Meteorological	16	\N	\N
900	Null	Storm	26	29	1	1	2014	2014	Meteorological	13	\N	\N
901	Null	Storm	28	4	2	3	2014	2014	Meteorological	12	\N	\N
902	Null	Storm	15	19	11	11	2014	2014	Meteorological	13	\N	\N
903	Null	Flood	11	13	8	8	2014	2014	Hydrological	2	\N	102000
904	Null	Landslide	22	22	3	3	2014	2014	Hydrological	43	\N	\N
905	Hurricane Iselle	Storm	8	10	8	8	2014	2014	Meteorological	1	\N	834
906	Null	Extreme temperature	5	8	1	1	2014	2014	Meteorological	21	\N	\N
907	Null	Wildfire	11	20	5	5	2014	2014	Climatological	2	\N	429
908	Null	Transport accident	11	11	4	4	2014	2014	Technological	10	30	\N
909	Null	Industrial accident	9	10	1	1	2014	2014	Technological	\N	169	\N
910	Jail	Miscellaneous accident	30	30	4	4	2014	2014	Technological	2	184	\N
911	Null	Drought	\N	\N	1	12	2014	2014	Climatological	\N	\N	\N
912	Null	Earthquake	5	5	8	8	2014	2014	Geophysical	1	2	2000
913	Null	Transport accident	6	6	9	9	2014	2014	Technological	10	7	\N
914	Null	Flood	\N	\N	12	1	2014	2015	Hydrological	11	\N	1500
915	Cholera	Epidemic	\N	\N	2	2	2015	2015	Biological	\N	11	\N
916	Stampede	Miscellaneous accident	20	20	11	11	2014	2014	Technological	11	\N	\N
917	Null	Storm	6	13	5	5	2015	2015	Meteorological	4	\N	\N
918	Null	Storm	29	3	10	11	2015	2015	Meteorological	6	\N	\N
919	Null	Storm	24	28	4	4	2015	2015	Meteorological	4	12	\N
920	Null	Storm	3	5	5	5	2015	2015	Meteorological	1	40	\N
921	Null	Storm	3	8	6	6	2015	2015	Meteorological	\N	\N	\N
922	Null	Storm	7	10	4	4	2015	2015	Meteorological	3	12	\N
923	Null	Storm	12	14	7	7	2015	2015	Meteorological	4	\N	\N
924	Valley Fire	Wildfire	13	31	8	8	2015	2015	Climatological	4	8	600
925	Null	Storm	25	26	3	3	2015	2015	Meteorological	1	12	3300
926	Null	Storm	2	4	8	8	2015	2015	Meteorological	4	40	\N
927	Null	Flood	15	6	12	1	2015	2016	Hydrological	31	50	4000
928	Storm Octavia	Storm	16	22	2	2	2015	2015	Meteorological	10	\N	\N
929	Null	Storm	31	4	1	2	2015	2015	Meteorological	22	\N	\N
930	Null	Drought	\N	\N	1	5	2015	2017	Climatological	\N	\N	2700000
931	Null	Storm	26	30	12	12	2015	2015	Meteorological	50	60	\N
932	Null	Storm	25	4	11	12	2015	2015	Meteorological	18	\N	300
933	Joaquin	Storm	1	13	10	10	2015	2015	Meteorological	25	\N	800
934	Null	Storm	2	4	1	1	2015	2015	Meteorological	10	\N	\N
935	Null	Storm	26	28	1	1	2015	2015	Meteorological	2	\N	\N
936	Null	Flood	23	30	5	5	2015	2015	Hydrological	32	\N	12000
937	Null	Storm	6	13	5	5	2015	2015	Meteorological	6	\N	\N
938	Null	Storm	6	11	1	1	2015	2015	Meteorological	15	\N	\N
939	Null	Storm	16	22	2	2	2015	2015	Meteorological	30	\N	\N
940	Null	Storm	3	5	3	3	2015	2015	Meteorological	13	\N	\N
941	Null	Flood	24	24	5	5	2015	2015	Hydrological	16	\N	12000
942	Null	Flood	14	14	9	9	2015	2015	Hydrological	19	\N	\N
943	Null	Wildfire	13	20	9	9	2015	2015	Climatological	4	\N	\N
944	Butte fire	Wildfire	9	14	9	9	2015	2015	Climatological	3	\N	\N
945	Military Helicopter UH-60	Transport accident	10	10	3	3	2015	2015	Technological	11	\N	\N
946	Null	Transport accident	12	12	5	5	2015	2015	Technological	8	200	\N
947	Storage facility	Industrial accident	23	23	10	10	2015	2015	Technological	\N	660	7574
948	Null	Drought	\N	\N	1	12	2015	2015	Climatological	\N	\N	\N
949	Null	Industrial accident	20	20	5	5	2015	2015	Technological	\N	\N	\N
950	Null	Wildfire	22	13	7	8	2015	2015	Climatological	1	\N	\N
951	Null	Flood	24	5	7	8	2015	2015	Hydrological	\N	\N	600
952	Null	Transport accident	17	17	8	8	2015	2015	Technological	15	6	\N
953	Null	Transport accident	29	29	8	8	2015	2015	Technological	27	\N	\N
954	Null	Transport accident	29	29	8	8	2015	2015	Technological	12	5	\N
955	Null	Transport accident	29	29	11	11	2015	2015	Technological	19	\N	\N
956	Null	Transport accident	27	27	9	9	2015	2015	Technological	10	\N	\N
957	Null	Transport accident	28	28	4	4	2015	2015	Technological	1	241	\N
958	Null	Transport accident	17	17	7	7	2015	2015	Technological	\N	300	\N
959	Gold mine	Industrial accident	25	25	2	2	2015	2015	Technological	18	\N	\N
960	Slum	Miscellaneous accident	29	29	11	11	2015	2015	Technological	2	\N	\N
961	Huts/Slum	Miscellaneous accident	28	28	12	12	2015	2015	Technological	9	\N	\N
962	Null	Transport accident	18	18	1	1	2015	2015	Technological	24	46	\N
963	Null	Storm	4	8	1	1	2016	2016	Meteorological	\N	\N	\N
964	Null	Storm	22	24	6	6	2016	2016	Meteorological	25	\N	2000
965	Null	Storm	25	4	4	5	2016	2016	Meteorological	6	\N	\N
966	Null	Storm	10	15	4	4	2016	2016	Meteorological	1	\N	3000
967	Null	Storm	8	11	5	5	2016	2016	Meteorological	2	10	\N
968	Null	Storm	17	18	3	3	2016	2016	Meteorological	1	\N	\N
969	Null	Storm	22	25	3	3	2016	2016	Meteorological	\N	\N	300
970	Null	Flood	16	19	4	4	2016	2016	Hydrological	9	\N	21000
971	Null	Flood	27	2	5	6	2016	2016	Hydrological	15	\N	\N
972	Null	Storm	21	28	5	5	2016	2016	Meteorological	9	12	\N
973	Null	Storm	4	12	3	3	2016	2016	Meteorological	7	\N	\N
974	Storm Jonas (Snowzilla)	Storm	23	26	1	1	2016	2016	Meteorological	50	12	85000000
975	Null	Storm	22	25	2	2	2016	2016	Meteorological	10	12	\N
976	Null	Wildfire	25	26	6	6	2016	2016	Climatological	\N	\N	36
977	Helicopter	Transport accident	14	14	1	1	2016	2016	Technological	12	\N	\N
978	Null	Industrial accident	6	6	1	1	2016	2016	Technological	\N	\N	\N
979	Null	Flood	30	30	4	4	2016	2016	Hydrological	11	\N	\N
980	Null	Extreme temperature	1	10	1	1	2016	2016	Meteorological	11	20	\N
981	Null	Transport accident	23	23	6	6	2016	2016	Technological	\N	121	\N
982	Null	Transport accident	4	4	3	3	2016	2016	Technological	30	36	\N
983	Null	Flood	1	10	3	3	2016	2016	Hydrological	30	\N	1544
984	Null	Flood	14	21	6	6	2016	2016	Hydrological	\N	\N	300
985	Gustafsen, Wildwood, Elephant Hill Fires	Wildfire	7	15	7	9	2017	2017	Climatological	\N	\N	43441
986	Null	Drought	\N	\N	5	6	2017	2017	Climatological	\N	\N	1420000
987	Null	Flood	21	8	3	4	2017	2017	Hydrological	11	\N	26500
988	Null	Flood	5	20	5	5	2017	2017	Hydrological	2	\N	16113
989	Null	Flood	28	29	8	8	2017	2017	Hydrological	\N	\N	3000
990	Null	Wildfire	\N	\N	7	8	2018	2018	Climatological	\N	\N	3000
991	Null	Flood	22	3	2	3	2018	2018	Hydrological	8	\N	3000
992	Cholera	Epidemic	9	12	10	11	2018	2018	Biological	2	\N	139
993	Null	Transport accident	4	4	9	9	2018	2018	Technological	17	12	\N
994	Null	Storm	21	21	9	9	2018	2018	Meteorological	\N	30	900
995	Null	Extreme temperature	29	5	6	7	2018	2018	Meteorological	70	\N	\N
996	Null	Transport accident	6	6	4	4	2018	2018	Technological	16	13	\N
997	Null	Flood	10	14	5	5	2018	2018	Hydrological	\N	\N	4000
998	Null	Flood	27	5	4	5	2019	2019	Hydrological	1	\N	19500
999	Null	Flood	20	28	2	2	2019	2019	Hydrological	11	\N	\N
1000	Null	Flood	16	22	3	3	2019	2019	Hydrological	19	\N	795
1001	Cyclone Vamco	Storm	19	20	9	9	2015	2015	Meteorological	\N	\N	6300
1002	Null	Flood	16	16	9	9	2015	2015	Hydrological	\N	\N	22000
1003	Tropical storm 'Earl'	Storm	6	7	8	8	2016	2016	Meteorological	54	\N	11000
1004	Null	Flood	3	10	11	11	2016	2016	Hydrological	2	\N	35000
1005	Null	Flood	20	22	9	9	2016	2016	Hydrological	53	\N	\N
1006	Null	Flood	23	10	10	11	2016	2016	Hydrological	2	\N	4500
1007	Null	Flood	30	7	11	12	2016	2016	Hydrological	10	\N	105000
1008	Null	Flood	21	26	12	12	2016	2016	Hydrological	\N	\N	105753
1009	Null	Flood	3	6	9	9	2016	2016	Hydrological	3	\N	6000
1010	Hurricane Newton	Storm	6	7	9	9	2016	2016	Meteorological	11	\N	10500
1011	Null	Earthquake	1	1	8	8	2016	2016	Geophysical	\N	\N	3410
1012	Null	Earthquake	7	7	12	12	2016	2016	Geophysical	104	857	85161
1013	Null	Flood	13	15	11	11	2016	2016	Hydrological	5	\N	19669
1014	Military plane	Transport accident	18	18	12	12	2016	2016	Technological	13	\N	\N
1015	Null	Transport accident	2	2	11	11	2016	2016	Technological	60	\N	\N
1016	Gold mine	Industrial accident	26	26	10	10	2016	2016	Technological	11	\N	\N
1017	Null	Flood	11	19	7	7	2016	2016	Hydrological	\N	\N	1354
1018	Null	Flood	29	5	9	10	2016	2016	Hydrological	5	\N	3000
1019	Null	Flood	3	6	2	2	2016	2016	Hydrological	2	\N	\N
1020	Fireworks market	Miscellaneous accident	20	20	12	12	2016	2016	Technological	42	72	\N
1021	Null	Flood	14	22	9	9	2016	2016	Hydrological	13	\N	6000
1022	Null	Earthquake	8	8	9	9	2017	2017	Geophysical	98	250	1200000
1023	Beatriz	Storm	1	3	6	6	2017	2017	Meteorological	6	\N	\N
1024	Hurricane 'Franklin'	Storm	7	7	8	8	2017	2017	Meteorological	\N	\N	300
1025	Cyclone 'Cempaka'	Storm	28	29	11	11	2017	2017	Meteorological	11	35	\N
1026	Hurricane Katia	Storm	7	8	9	9	2017	2017	Meteorological	3	\N	1110
1027	Null	Earthquake	17	17	9	9	2017	2017	Geophysical	369	6000	250000
1028	Null	Flood	12	15	5	5	2017	2017	Hydrological	7	11	25000
1029	Null	Flood	3	3	3	3	2017	2017	Hydrological	8	\N	17410
1030	Null	Landslide	9	12	2	2	2017	2017	Hydrological	12	\N	50500
1031	Null	Flood	3	17	11	11	2017	2017	Hydrological	9	\N	12000
1032	Tropical storm 'Lidia'	Storm	30	2	8	9	2017	2017	Meteorological	20	\N	\N
1033	Null	Earthquake	15	15	12	12	2017	2017	Geophysical	4	36	8859
1034	Null	Flood	29	29	4	4	2017	2017	Hydrological	12	4	355
1035	Null	Flood	19	24	11	11	2017	2017	Hydrological	2	\N	2280
1036	Null	Flood	1	3	6	6	2017	2017	Hydrological	4	\N	282345
1037	Null	Landslide	1	1	4	4	2017	2017	Hydrological	28	17	\N
1038	Null	Transport accident	14	14	7	7	2017	2017	Technological	10	9	\N
1039	Null	Transport accident	30	30	4	4	2017	2017	Technological	11	50	\N
1040	Null	Transport accident	1	1	1	1	2017	2017	Technological	40	\N	194
1041	Firework factory	Industrial accident	26	26	10	10	2017	2017	Technological	46	10	\N
1042	Null	Flood	21	21	2	2	2017	2017	Hydrological	2	\N	400
1043	Mt. Agung	Volcanic activity	22	28	9	11	2017	2017	Geophysical	\N	\N	133349
1044	Null	Flood	26	7	9	10	2017	2017	Hydrological	2	\N	800
1045	Null	Transport accident	13	13	4	4	2017	2017	Technological	24	9	\N
1046	Null	Transport accident	21	21	5	5	2017	2017	Technological	17	31	\N
1047	Null	Transport accident	12	12	12	12	2017	2017	Technological	11	12	\N
1048	Null	Transport accident	19	19	12	12	2017	2017	Technological	12	2	\N
1049	Firework depot	Miscellaneous accident	8	9	5	5	2017	2017	Technological	14	22	\N
1050	Null	Earthquake	28	28	9	9	2018	2018	Geophysical	4140	\N	2000000
1051	Oil well	Industrial accident	25	25	4	4	2018	2018	Technological	21	38	\N
1052	Null	Flood	11	12	10	10	2018	2018	Hydrological	35	\N	20000
1053	Null	Flood	26	4	11	12	2018	2018	Hydrological	13	\N	3000
1054	Null	Flood	22	26	3	3	2018	2018	Hydrological	3	1	12000
1055	Null	Flood	6	10	12	12	2018	2018	Hydrological	9	\N	5463
1056	Null	Flood	21	23	2	2	2018	2018	Hydrological	20	\N	100000
1057	Null	Earthquake	5	5	8	8	2018	2018	Geophysical	564	1584	445343
1058	Anak Krakatoa	Volcanic activity	22	22	12	12	2018	2018	Geophysical	453	14059	33719
1059	Null	Landslide	22	22	2	2	2018	2018	Hydrological	15	14	50000
1060	Tropical storm 'Vicente'	Storm	19	23	10	10	2018	2018	Meteorological	14	\N	\N
1061	Null	Earthquake	23	23	1	1	2018	2018	Geophysical	1	11	13800
1062	Null	Earthquake	29	29	7	7	2018	2018	Geophysical	14	135	102717
1063	Null	Earthquake	19	19	8	8	2018	2018	Geophysical	10	24	755
1064	Mt. Agung	Volcanic activity	14	14	1	1	2018	2018	Geophysical	\N	\N	50000
1065	Null	Landslide	31	1	12	1	2018	2019	Hydrological	33	\N	\N
1066	Boeing 737	Transport accident	29	29	10	10	2018	2018	Technological	189	\N	\N
1067	Null	Transport accident	8	8	9	9	2018	2018	Technological	21	\N	\N
1068	Null	Transport accident	18	18	6	6	2018	2018	Technological	180	\N	\N
1069	Ferry 'KM Lestari'	Transport accident	4	4	7	7	2018	2018	Technological	34	\N	155
1070	Ferry	Transport accident	14	14	9	9	2018	2018	Technological	13	\N	155
1071	Null	Flood	5	6	3	3	2018	2018	Hydrological	\N	\N	3000
1072	Null	Flood	23	23	7	7	2018	2018	Hydrological	\N	\N	5817
1073	Null	Earthquake	16	16	2	2	2018	2018	Geophysical	\N	4	3000
1074	Null	Flood	20	23	9	9	2018	2018	Hydrological	20	\N	\N
1075	Hurricane Willa	Storm	23	23	10	10	2018	2018	Meteorological	6	\N	10000
1076	Helicopter	Transport accident	16	16	2	2	2018	2018	Technological	14	\N	\N
1077	Null	Transport accident	20	20	7	7	2018	2018	Technological	13	\N	\N
1078	Fireworks depot	Miscellaneous accident	5	5	7	7	2018	2018	Technological	12	\N	\N
1079	Gold mine	Industrial accident	26	26	2	2	2019	2019	Technological	13	\N	19
1080	Null	Flood	17	17	1	1	2019	2019	Hydrological	2	\N	2650
1081	Null	Flood	6	8	3	3	2019	2019	Hydrological	9	4	168393
1082	Null	Flood	25	27	4	5	2019	2019	Hydrological	18	2	13000
1083	Null	Landslide	21	23	1	1	2019	2019	Hydrological	84	47	6596
1084	Null	Earthquake	28	28	2	2	2019	2019	Geophysical	\N	48	1715
1085	Null	Earthquake	17	17	3	3	2019	2019	Geophysical	9	45	1250
1086	Null	Flood	16	18	3	3	2019	2019	Hydrological	206	915	58625
1087	Null	Landslide	20	20	3	3	2019	2019	Hydrological	5	\N	860
1088	Null	Flood	25	26	4	4	2019	2019	Hydrological	2	\N	2258
1089	Bombardier Challenger 601	Transport accident	5	5	5	5	2019	2019	Technological	13	\N	\N
1090	Null	Transport accident	7	7	3	3	2019	2019	Technological	23	33	\N
1091	Oleoduc	Industrial accident	18	18	1	1	2019	2019	Technological	125	22	\N
1092	Sugar Refinery	Industrial accident	7	7	2	2	2008	2008	Technological	13	40	\N
1093	Cyclone Vamco	Storm	15	21	9	9	2015	2015	Meteorological	3	\N	\N
1094	Hurricane Hermine	Storm	1	6	9	9	2016	2016	Meteorological	3	\N	13500
1095	Null	Flood	19	23	9	9	2016	2016	Hydrological	1	\N	\N
1096	Null	Storm	26	1	11	12	2016	2016	Meteorological	8	33	\N
1097	Null	Storm	13	19	12	12	2016	2016	Meteorological	22	\N	\N
1098	Hurricane 'Matthew'	Storm	8	12	10	10	2016	2016	Meteorological	49	\N	\N
1099	Null	Storm	9	14	12	12	2016	2016	Meteorological	31	\N	2000
1100	Null	Flood	15	16	8	8	2016	2016	Hydrological	3	\N	22500
1101	Null	Transport accident	22	22	11	11	2016	2016	Technological	18	20	\N
1102	Null	Transport accident	21	21	10	10	2016	2016	Technological	30	35	\N
1103	Null	Transport accident	18	18	9	9	2016	2016	Technological	28	33	\N
1104	Null	Flood	6	16	10	10	2016	2016	Hydrological	4	\N	204000
1105	Null	Flood	1	10	12	12	2016	2016	Hydrological	14	\N	582343
1106	Null	Storm	24	28	4	4	2016	2017	Meteorological	6	19	\N
1107	Null	Earthquake	7	7	11	11	2016	2016	Geophysical	\N	\N	120
1108	Sand Fire	Wildfire	24	1	7	8	2016	2016	Climatological	2	\N	420
1109	Clayton Fire	Wildfire	13	16	8	8	2016	2016	Climatological	\N	\N	\N
1110	Null	Wildfire	\N	31	11	12	2016	2016	Climatological	14	191	\N
1111	Ballooning	Transport accident	30	30	7	7	2016	2016	Technological	16	\N	\N
1112	Null	Transport accident	23	23	10	10	2016	2016	Technological	13	31	\N
1113	Null	Transport accident	29	29	9	9	2016	2016	Technological	1	110	\N
1114	Party in a festival	Miscellaneous accident	2	2	12	12	2016	2016	Technological	36	2	\N
1115	Null	Flood	9	16	8	8	2016	2016	Hydrological	13	\N	70000
1116	Null	Flood	8	13	3	3	2016	2016	Hydrological	5	\N	\N
1117	Null	Flood	9	9	11	11	2016	2016	Hydrological	6	\N	600
1118	Null	Flood	25	3	7	8	2016	2016	Hydrological	7	\N	6900
1119	Null	Storm	6	13	1	1	2017	2017	Meteorological	3	\N	\N
1120	Null	Flood	28	1	4	5	2017	2017	Hydrological	20	70	\N
1121	Null	Storm	5	8	8	8	2017	2017	Meteorological	\N	30	600
1122	Null	Storm	31	5	12	1	2017	2018	Meteorological	22	\N	\N
1123	Null	Storm	7	8	6	6	2017	2017	Meteorological	9	\N	6918
1124	Null	Storm	8	21	2	2	2017	2017	Meteorological	5	\N	200000
1125	Tropical depression 'Ex-Dineo'	Storm	\N	\N	1	3	2017	2017	Meteorological	251	128	100000
1126	Null	Storm	25	29	6	6	2017	2017	Meteorological	\N	\N	\N
1127	Null	Storm	25	28	3	3	2017	2017	Meteorological	1	\N	\N
1128	Hurricane Harvey	Storm	25	29	8	8	2017	2017	Meteorological	88	24	555000
1129	Null	Storm	27	2	2	3	2017	2017	Meteorological	4	12	600
1130	Null	Flood	5	2	7	8	2017	2017	Hydrological	23	\N	1000000
1131	Null	Flood	10	8	10	11	2017	2017	Hydrological	9	\N	605000
1132	Null	Storm	9	11	5	5	2017	2017	Meteorological	\N	\N	\N
1133	Null	Storm	6	9	3	3	2017	2017	Meteorological	2	15	600
1134	Null	Storm	9	12	6	6	2017	2017	Meteorological	\N	2	\N
1135	Null	Storm	5	6	11	11	2017	2017	Meteorological	\N	8	\N
1136	Typhoon 'Doksuri'	Storm	17	17	9	9	2017	2017	Meteorological	\N	\N	28500
1137	Hurricane 'Irma'	Storm	10	28	9	9	2017	2017	Meteorological	97	\N	\N
1138	Null	Storm	9	10	10	10	2017	2017	Meteorological	11	18	\N
1139	Null	Drought	\N	\N	2	3	2017	2020	Climatological	\N	\N	6900000
1140	Null	Flood	1	31	1	1	2017	2017	Hydrological	96	\N	1800000
1141	Null	Flood	25	3	11	12	2017	2017	Hydrological	22	\N	385498
1142	Tropical Storm Talas	Storm	17	19	7	7	2017	2017	Meteorological	\N	\N	60
1143	Null	Storm	13	15	3	3	2017	2017	Meteorological	11	12	\N
1144	Null	Storm	18	23	1	1	2017	2017	Meteorological	24	200	\N
1145	Null	Flood	15	15	7	7	2017	2017	Hydrological	10	\N	\N
1146	Null	Flood	22	22	2	2	2017	2017	Hydrological	\N	\N	300
1147	Hurricane 'Maria'	Storm	26	27	9	9	2017	2017	Meteorological	4	\N	\N
1148	Tropical depression'16/Hurricane 'Nate'	Storm	7	8	10	10	2017	2017	Meteorological	\N	\N	60
1149	Wall Fire, Alamo Fire, Whittier Fire	Wildfire	6	10	7	7	2017	2017	Climatological	\N	\N	9
1150	Tubbs, Atlas, Nuns Fires	Wildfire	1	31	6	12	2017	2017	Climatological	43	185	\N
1151	Military plane KC-130	Transport accident	10	10	7	7	2017	2017	Technological	16	\N	\N
1152	Null	Transport accident	4	4	1	1	2017	2017	Technological	\N	103	\N
1153	Cosmetics factory	Industrial accident	20	20	11	11	2017	2017	Technological	1	125	\N
1154	Null	Drought	1	31	3	12	2017	2017	Climatological	\N	\N	\N
1155	Appartment building	Miscellaneous accident	28	28	12	12	2017	2017	Technological	13	3	\N
1156	'Thomas'	Wildfire	4	31	12	12	2017	2017	Climatological	2	2	\N
1157	Null	Transport accident	21	21	4	4	2017	2017	Technological	19	\N	\N
1158	Null	Drought	\N	\N	5	6	2017	2018	Climatological	\N	\N	\N
1159	Null	Flood	14	19	5	5	2017	2017	Hydrological	3	\N	200
1160	Knysna fire	Wildfire	7	13	6	6	2017	2017	Climatological	9	\N	\N
1161	Null	Transport accident	7	7	6	6	2017	2017	Technological	43	\N	\N
1162	Null	Transport accident	2	2	12	12	2017	2017	Technological	21	20	\N
1163	Null	Storm	1	3	3	3	2018	2018	Meteorological	9	\N	\N
1164	Null	Transport accident	4	4	1	1	2018	2018	Technological	19	254	\N
1165	Null	Flood	14	15	4	4	2018	2018	Hydrological	\N	\N	1596
1166	Kilauea	Volcanic activity	3	30	5	5	2018	2018	Geophysical	\N	\N	2500
1167	Carr and Mendocino Complex fires	Wildfire	27	31	7	8	2018	2018	Climatological	14	\N	\N
1168	Null	Storm	6	7	8	8	2018	2018	Meteorological	\N	18	\N
1169	Null	Storm	13	15	4	4	2018	2018	Meteorological	3	\N	\N
1170	Null	Flood	15	20	10	10	2018	2018	Hydrological	5	\N	\N
1171	Null	Storm	3	5	1	1	2018	2018	Meteorological	22	\N	\N
1172	Null	Storm	26	28	12	12	2018	2018	Meteorological	2	\N	\N
1173	Hurricane Florence	Storm	12	18	9	9	2018	2018	Meteorological	53	\N	1500000
1174	Null	Landslide	8	14	1	1	2018	2018	Hydrological	21	28	1338
1175	Hurricane Michael	Storm	10	11	10	10	2018	2018	Meteorological	49	\N	5000
1176	Null	Storm	19	22	7	7	2018	2018	Meteorological	\N	\N	\N
1177	Null	Transport accident	22	22	3	3	2018	2018	Technological	18	10	\N
1178	Null	Transport accident	29	30	3	3	2018	2018	Technological	20	3	\N
1179	Null	Transport accident	6	6	7	7	2018	2018	Technological	55	\N	\N
1180	Null	Storm	21	24	1	1	2018	2018	Meteorological	10	\N	\N
1181	Null	Flood	3	11	9	9	2018	2018	Hydrological	2	\N	\N
1182	Null	Storm	13	15	5	5	2018	2018	Meteorological	5	\N	75
1183	Tropical storm 'Alberto'	Storm	27	30	5	5	2018	2018	Meteorological	5	\N	\N
1184	Camp Fire	Wildfire	1	31	6	12	2018	2018	Climatological	88	\N	250000
1185	Null	Transport accident	6	6	10	10	2018	2018	Technological	20	\N	\N
1186	Null	Transport accident	19	19	7	7	2018	2018	Technological	17	\N	\N
1187	Null	Drought	\N	\N	1	12	2018	2018	Climatological	\N	\N	\N
1188	Woolsey Fire	Wildfire	8	21	11	11	2018	2018	Climatological	2	3	\N
1189	Null	Transport accident	19	19	10	10	2018	2018	Technological	27	4	\N
1190	Null	Transport accident	9	9	1	1	2018	2018	Technological	\N	200	\N
1191	Typhoid fever	Epidemic	7	16	8	11	2018	2018	Biological	12	5164	\N
1192	Null	Transport accident	7	7	11	11	2018	2018	Technological	47	\N	\N
1193	Null	Transport accident	15	16	11	11	2018	2018	Technological	42	\N	\N
1194	Null	Flood	25	1	2	3	2019	2019	Hydrological	1	\N	6000
1195	Null	Storm	23	25	2	2	2019	2019	Meteorological	2	12	\N
1196	Null	Storm	18	21	1	1	2019	2019	Meteorological	10	\N	\N
1197	Null	Flood	26	4	2	3	2019	2019	Hydrological	1	\N	8000
1198	Null	Flood	21	25	4	4	2019	2019	Hydrological	73	\N	1000
1199	Null	Storm	13	14	4	4	2019	2019	Meteorological	8	12	\N
1200	Null	Flood	14	31	3	3	2019	2019	Hydrological	5	\N	2000
1201	Null	Flood	8	12	3	3	2019	2019	Hydrological	10	\N	\N
1202	Null	Storm	29	31	1	1	2019	2019	Meteorological	22	\N	\N
1203	Null	Storm	24	26	4	4	2019	2019	Meteorological	5	\N	\N
1204	Cyclone 'Idai'	Storm	14	14	3	3	2019	2019	Meteorological	628	186	270000
1205	Null	Storm	31	2	10	11	2019	2019	Meteorological	1	\N	\N
1206	Null	Storm	11	15	1	1	2019	2019	Meteorological	13	57	\N
1207	Tropical cylone 'Pabuk'	Storm	4	4	1	1	2019	2019	Meteorological	7	\N	720885
1208	Null	Storm	3	4	3	3	2019	2019	Meteorological	28	90	\N
1209	Coal mine	Industrial accident	3	3	2	2	2019	2019	Technological	18	\N	\N
1210	Null	Flood	2	2	5	5	2019	2019	Hydrological	13	\N	\N
1211	Null	Flood	11	18	2	2	2019	2019	Hydrological	26	\N	\N
1212	Gold mine	Industrial accident	15	15	2	2	2019	2019	Technological	65	\N	\N
1213	Null	Flood	\N	10	3	1	2019	2020	Hydrological	41	\N	11190
1214	Null	Storm	13	14	6	6	2020	2020	Meteorological	\N	\N	60000
1215	Null	Drought	\N	\N	12	2	2020	2022	Climatological	\N	\N	1580000
1216	Null	Flood	18	24	4	4	2020	2020	Hydrological	30	\N	10600
1217	Null	Flood	16	17	3	3	2020	2020	Hydrological	3	\N	10000
1218	Null	Flood	26	30	4	4	2020	2020	Hydrological	1	\N	12936
1219	Null	Flood	2	6	6	6	2019	2019	Hydrological	7	\N	\N
1220	Null	Flood	31	3	12	1	2019	2020	Hydrological	66	110	501000
1221	Null	Flood	19	21	12	12	2019	2019	Hydrological	6	\N	60000
1222	Null	Earthquake	14	14	7	7	2019	2019	Geophysical	8	134	5790
1223	Null	Wildfire	\N	\N	2	9	2019	2019	Climatological	\N	\N	\N
1224	Tropical cyclone 'Lorena'	Storm	20	20	9	9	2019	2019	Meteorological	1	\N	200
1225	Tropical storm 'Fernand'	Storm	5	6	9	9	2019	2019	Meteorological	1	\N	\N
1226	Null	Earthquake	2	2	8	8	2019	2019	Geophysical	6	4	2100
1227	Null	Earthquake	26	26	9	9	2019	2019	Geophysical	31	179	247239
1228	Null	Flood	12	17	12	12	2019	2019	Hydrological	14	\N	5000
1229	Null	Transport accident	17	17	6	6	2019	2019	Technological	12	43	\N
1230	Null	Transport accident	23	23	12	12	2019	2019	Technological	28	13	\N
1231	Ferry	Transport accident	17	17	6	6	2019	2019	Technological	22	39	\N
1232	Ferry	Transport accident	23	23	8	8	2019	2019	Technological	22	\N	\N
1233	Matches factory	Industrial accident	21	21	6	6	2019	2019	Technological	30	\N	\N
1234	Null	Flood	9	14	6	6	2019	2019	Hydrological	1	\N	52000
1235	Null	Flood	3	9	6	6	2019	2019	Hydrological	2	\N	55495
1236	Null	Flood	26	27	10	10	2019	2019	Hydrological	\N	\N	9435
1237	Building in construction	Industrial accident	22	22	6	6	2019	2019	Technological	38	24	\N
1238	Null	Flood	11	20	9	9	2019	2019	Hydrological	12	\N	435000
1239	Tropical storm 'Narda'	Storm	30	30	9	9	2019	2019	Meteorological	2	\N	1000
1240	Null	Transport accident	29	29	5	5	2019	2019	Technological	21	30	\N
1241	Null	Transport accident	18	18	12	12	2019	2019	Technological	14	12	\N
1242	Null	Flood	28	28	6	6	2019	2019	Hydrological	2	\N	142
1243	Null	Flood	27	4	11	12	2019	2019	Hydrological	3	\N	500
1244	Null	Flood	4	5	4	4	2020	2020	Hydrological	4	\N	100
1245	Null	Flood	11	15	6	6	2020	2020	Hydrological	7	3	12000
1246	Null	Flood	6	8	12	12	2020	2020	Hydrological	2	2	1850
1247	Null	Flood	13	26	2	2	2020	2020	Hydrological	6	\N	115000
1248	Null	Flood	20	28	4	4	2020	2020	Hydrological	\N	\N	2000
1249	Null	Flood	8	8	5	5	2020	2020	Hydrological	7	\N	3805
1250	Null	Flood	3	31	7	7	2020	2020	Hydrological	105	51	14483
1251	Null	Flood	21	31	10	10	2020	2020	Hydrological	15	\N	10000
1252	Tropical storm 'Cristobal'	Storm	3	3	6	6	2020	2020	Meteorological	\N	\N	606
1253	Null	Flood	8	10	8	8	2020	2020	Hydrological	3	\N	5100
1254	Null	Flood	9	10	11	11	2020	2020	Hydrological	27	\N	90000
1255	Null	Flood	19	22	1	1	2020	2020	Hydrological	10	\N	\N
1256	Tropical storm Linfa	Storm	1	24	10	10	2020	2020	Meteorological	38	\N	759360
1257	Hurricane 'Hanna'	Storm	25	26	7	7	2020	2020	Meteorological	5	\N	\N
1258	Null	Earthquake	4	4	6	6	2020	2020	Geophysical	\N	\N	1490
1259	Lewotolo Volcano	Volcanic activity	29	31	11	12	2020	2020	Geophysical	\N	\N	19736
1260	Mount Semeru	Volcanic activity	1	1	12	12	2020	2020	Geophysical	\N	\N	550
1261	Null	Flood	4	6	3	3	2020	2020	Hydrological	2	\N	40000
1262	Null	Flood	9	16	4	4	2020	2020	Hydrological	\N	\N	25000
1263	Null	Flood	22	4	5	6	2020	2020	Hydrological	4	\N	41837
1264	Null	Flood	1	1	8	8	2020	2020	Hydrological	\N	\N	23461
1265	Null	Flood	12	15	12	12	2020	2020	Hydrological	\N	\N	18200
1266	Null	Flood	11	11	2	2	2020	2020	Hydrological	\N	\N	10905
1267	Null	Landslide	28	28	9	9	2020	2020	Hydrological	11	\N	170
1268	Migrants	Transport accident	23	23	1	1	2020	2020	Technological	10	\N	10
1269	Null	Flood	14	15	1	1	2020	2020	Hydrological	\N	\N	7213
1270	Null	Flood	23	28	1	1	2020	2020	Hydrological	10	\N	75000
1271	Null	Flood	28	29	1	1	2020	2020	Hydrological	9	22	2100
1272	Null	Flood	26	28	2	2	2020	2020	Hydrological	10	\N	112000
1273	Null	Flood	20	21	3	3	2020	2020	Hydrological	\N	\N	84609
1274	Null	Flood	29	1	3	4	2020	2020	Hydrological	1	\N	56488
1275	Null	Flood	30	5	4	5	2020	2020	Hydrological	2	\N	110000
1276	Null	Flood	3	5	6	6	2020	2020	Hydrological	\N	\N	1835
1277	Null	Flood	18	19	6	6	2020	2020	Hydrological	\N	\N	10000
1278	Null	Flood	2	10	12	12	2020	2020	Hydrological	5	\N	110000
1279	Tropical storm 'Noul' (Leon)	Storm	18	21	9	9	2020	2020	Meteorological	\N	\N	\N
1280	Null	Earthquake	23	23	6	6	2020	2020	Geophysical	10	24	24369
1281	Tropical storm 'Gamma'	Storm	2	6	10	10	2020	2020	Meteorological	6	\N	3500
1282	Hurricane 'Eta'	Storm	2	4	11	11	2020	2020	Meteorological	31	\N	\N
1283	Hurricane 'Zeta'	Storm	7	11	10	10	2020	2020	Meteorological	\N	\N	\N
1284	Null	Storm	23	31	5	5	2019	2019	Meteorological	3	150	\N
1285	Null	Storm	16	18	12	12	2019	2019	Meteorological	18	\N	\N
1286	Null	Storm	27	3	11	12	2019	2019	Meteorological	10	\N	\N
1287	Tropical cyclone 'Dorian'	Storm	28	6	8	9	2019	2019	Meteorological	10	\N	\N
1288	Tropical storm ' Imelda'	Storm	17	21	9	9	2019	2019	Meteorological	5	\N	1000
1289	Null	Drought	\N	\N	7	2	2019	2020	Climatological	\N	\N	\N
1290	Null	Flood	11	11	9	9	2019	2019	Hydrological	19	\N	158000
1291	Null	Storm	20	21	10	10	2019	2019	Meteorological	4	\N	\N
1292	Null	Earthquake	5	5	7	7	2019	2019	Geophysical	\N	\N	150
1293	Tropical cylone 'Barry'	Storm	13	15	7	7	2019	2019	Meteorological	1	\N	\N
1294	Saddleridge fire & Sandalwood fire	Wildfire	10	17	10	10	2019	2019	Climatological	3	12	312
1295	Kincade Fire	Wildfire	26	31	10	10	2019	2019	Climatological	\N	2	660
1296	Bimoteur	Transport accident	21	21	6	6	2019	2019	Technological	11	\N	\N
1297	Bimotor	Transport accident	30	30	6	6	2019	2019	Technological	10	\N	\N
1298	Tourist boat 'Conception'	Transport accident	2	2	9	9	2019	2019	Technological	67	\N	\N
1299	Null	Flood	6	9	6	6	2019	2019	Hydrological	3	\N	600
1300	Null	Storm	11	12	11	11	2019	2019	Meteorological	4	20	\N
1301	Null	Drought	1	31	1	12	2019	2019	Climatological	\N	\N	750000
1302	Null	Flood	2	11	12	12	2019	2019	Hydrological	2	\N	3500
1303	Null	Storm	20	23	5	5	2020	2020	Meteorological	2	\N	\N
1304	Null	Storm	10	10	11	11	2020	2020	Meteorological	11	\N	\N
1305	Tropical cyclone 'Sinlaku'	Storm	1	3	8	8	2020	2020	Meteorological	4	\N	\N
1306	Hurricane 'Eta'	Storm	8	12	11	11	2020	2020	Meteorological	12	\N	\N
1307	Null	Storm	17	21	11	11	2020	2020	Meteorological	10	\N	210
1308	Null	Flood	22	23	8	8	2020	2020	Hydrological	1	\N	40000
1309	Null	Flood	16	21	12	12	2020	2020	Hydrological	1	\N	139000
1310	Null	Flood	17	20	5	5	2020	2020	Hydrological	1	\N	10000
1311	Null	Storm	6	9	4	4	2020	2020	Meteorological	\N	\N	\N
1312	Null	Storm	2	3	5	5	2020	2020	Meteorological	2	\N	\N
1313	Null	Drought	\N	\N	1	12	2020	2020	Climatological	45	\N	\N
1314	Tropical storm 'Noul' (Leon)	Storm	18	21	9	9	2020	2020	Meteorological	1	\N	\N
1315	Null	Storm	10	14	4	4	2020	2020	Meteorological	38	200	\N
1316	Null	Storm	21	24	4	4	2020	2020	Meteorological	3	31	\N
1317	Null	Storm	10	12	1	1	2020	2020	Meteorological	10	\N	\N
1318	Hurricane 'Hanna'	Storm	25	25	7	7	2020	2020	Meteorological	\N	\N	\N
1319	Hurricane 'Delta'	Storm	7	11	10	10	2020	2020	Meteorological	4	\N	9400
1320	Hurricane 'Sally'	Storm	11	18	9	9	2020	2020	Meteorological	8	\N	\N
1321	Hurricane 'Zeta'	Storm	24	30	10	10	2020	2020	Meteorological	6	\N	\N
1322	Hurricane 'Laura'	Storm	27	28	8	8	2020	2020	Meteorological	33	\N	6500
1323	Null	Storm	29	9	4	5	2020	2020	Meteorological	2	2	50500
1324	Null	Flood	25	14	11	12	2020	2020	Hydrological	29	\N	691659
1325	Tropical storm Linfa	Storm	9	31	10	10	2020	2020	Meteorological	6	\N	274923
1326	Null	Transport accident	11	11	10	10	2020	2020	Technological	18	40	\N
1327	Null	Storm	8	12	8	8	2020	2020	Meteorological	4	\N	\N
1328	Null	Storm	27	27	5	5	2020	2020	Meteorological	\N	\N	\N
1329	Null	Storm	2	5	3	3	2020	2020	Meteorological	25	300	12000
1330	Null	Storm	27	28	3	3	2020	2020	Meteorological	\N	\N	\N
1331	Null	Flood	10	17	2	2	2020	2020	Hydrological	\N	\N	3000
1332	Tropical storm 'Cristobal'	Storm	7	7	6	6	2020	2020	Meteorological	1	\N	\N
1333	Hurricane 'Isaias'	Storm	31	2	7	8	2020	2020	Meteorological	16	\N	\N
1334	August Complex fire	Wildfire	16	1	8	10	2020	2020	Climatological	32	\N	\N
1335	Null	Flood	7	10	2	2	2020	2020	Hydrological	3	\N	200
1336	Null	Transport accident	2	3	3	3	2020	2020	Technological	25	60	\N
\.


--
-- Data for Name: fact_table; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.fact_table (month_key, country_key, education_key, population_key, quality_of_life_key, health_key, event_key, quality_of_life, development_index, human_development_index) FROM stdin;
0	0	0	0	0	0	\N	90	1	1
1	0	0	0	0	0	\N	90	1	1
2	0	0	0	0	0	\N	90	1	1
3	0	0	0	0	0	\N	90	1	1
4	0	0	0	0	0	26	90	1	1
5	0	0	0	0	0	22	90	1	1
6	0	0	0	0	0	23	90	1	1
7	0	0	0	0	0	24	90	1	1
8	0	0	0	0	0	21	90	1	1
9	0	0	0	0	0	\N	90	1	1
10	0	0	0	0	0	25	90	1	1
11	0	0	0	0	0	\N	90	1	1
12	1	1	1	1	1	\N	90	1	1
13	1	1	1	1	1	\N	90	1	1
14	1	1	1	1	1	\N	90	1	1
15	1	1	1	1	1	45	90	1	1
16	1	1	1	1	1	52	90	1	1
17	1	1	1	1	1	\N	90	1	1
18	1	1	1	1	1	\N	90	1	1
19	1	1	1	1	1	\N	90	1	1
20	1	1	1	1	1	\N	90	1	1
21	1	1	1	1	1	\N	90	1	1
22	1	1	1	1	1	\N	90	1	1
23	1	1	1	1	1	\N	90	1	1
24	2	2	2	2	2	\N	90	1	1
25	2	2	2	2	2	77	90	1	1
26	2	2	2	2	2	\N	90	1	1
27	2	2	2	2	2	\N	90	1	1
28	2	2	2	2	2	\N	90	1	1
29	2	2	2	2	2	213	90	1	1
30	2	2	2	2	2	\N	90	1	1
31	2	2	2	2	2	\N	90	1	1
32	2	2	2	2	2	\N	90	1	1
33	2	2	2	2	2	\N	90	1	1
34	2	2	2	2	2	\N	90	1	1
35	2	2	2	2	2	214	90	1	1
36	3	3	3	3	3	\N	90	1	1
37	3	3	3	3	3	\N	90	1	1
38	3	3	3	3	3	\N	90	1	1
39	3	3	3	3	3	233	90	1	1
40	3	3	3	3	3	\N	90	1	1
41	3	3	3	3	3	\N	90	1	1
42	3	3	3	3	3	\N	90	1	1
43	3	3	3	3	3	241	90	1	1
44	3	3	3	3	3	\N	90	1	1
45	3	3	3	3	3	\N	90	1	1
46	3	3	3	3	3	\N	90	1	1
47	3	3	3	3	3	\N	90	1	1
48	4	4	4	4	4	\N	90	1	1
49	4	4	4	4	4	\N	90	1	1
50	4	4	4	4	4	264	90	1	1
51	4	4	4	4	4	414	90	1	1
52	4	4	4	4	4	\N	90	1	1
53	4	4	4	4	4	\N	90	1	1
54	4	4	4	4	4	\N	90	1	1
55	4	4	4	4	4	413	90	1	1
56	4	4	4	4	4	\N	90	1	1
57	4	4	4	4	4	\N	90	1	1
58	4	4	4	4	4	\N	90	1	1
59	4	4	4	4	4	\N	90	1	1
60	5	5	5	5	5	\N	90	1	1
61	5	5	5	5	5	\N	90	1	1
62	5	5	5	5	5	\N	90	1	1
63	5	5	5	5	5	\N	90	1	1
64	5	5	5	5	5	\N	90	1	1
65	5	5	5	5	5	\N	90	1	1
66	5	5	5	5	5	\N	90	1	1
67	5	5	5	5	5	\N	90	1	1
68	5	5	5	5	5	\N	90	1	1
69	5	5	5	5	5	\N	90	1	1
70	5	5	5	5	5	\N	90	1	1
71	5	5	5	5	5	435	90	1	1
72	6	6	6	6	6	\N	90	1	1
73	6	6	6	6	6	\N	90	1	1
74	6	6	6	6	6	\N	90	1	1
75	6	6	6	6	6	449	90	1	1
76	6	6	6	6	6	581	90	1	1
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68	37	37	37	37	37	486	81	1	1
69	37	37	37	37	37	509	81	1	1
70	37	37	37	37	37	510	81	1	1
71	37	37	37	37	37	507	81	1	1
72	38	38	38	38	38	\N	81	1	1
73	38	38	38	38	38	538	81	1	1
74	38	38	38	38	38	534	81	1	1
75	38	38	38	38	38	\N	81	1	1
76	38	38	38	38	38	539	81	1	1
77	38	38	38	38	38	529	81	1	1
78	38	38	38	38	38	535	81	1	1
79	38	38	38	38	38	649	81	1	1
80	38	38	38	38	38	644	81	1	1
81	38	38	38	38	38	642	81	1	1
82	38	38	38	38	38	\N	81	1	1
83	38	38	38	38	38	646	81	1	1
84	39	39	39	39	39	\N	81	1	1
85	39	39	39	39	39	\N	81	1	1
86	39	39	39	39	39	656	81	1	1
87	39	39	39	39	39	659	81	1	1
88	39	39	39	39	39	\N	81	1	1
89	39	39	39	39	39	658	81	1	1
90	39	39	39	39	39	\N	81	1	1
91	39	39	39	39	39	657	81	1	1
92	39	39	39	39	39	661	81	1	1
93	39	39	39	39	39	\N	81	1	1
94	39	39	39	39	39	\N	81	1	1
95	39	39	39	39	39	\N	81	1	1
96	40	40	40	40	40	685	81	1	1
97	40	40	40	40	40	\N	81	1	1
98	40	40	40	40	40	686	81	1	1
99	40	40	40	40	40	\N	81	1	1
100	40	40	40	40	40	681	81	1	1
101	40	40	40	40	40	\N	81	1	1
102	40	40	40	40	40	\N	81	1	1
103	40	40	40	40	40	675	81	1	1
104	40	40	40	40	40	676	81	1	1
105	40	40	40	40	40	682	81	1	1
106	40	40	40	40	40	\N	81	1	1
107	40	40	40	40	40	\N	81	1	1
108	41	41	41	41	41	\N	81	1	1
109	41	41	41	41	41	\N	81	1	1
110	41	41	41	41	41	\N	81	1	1
111	41	41	41	41	41	825	81	1	1
112	41	41	41	41	41	799	81	1	1
113	41	41	41	41	41	\N	81	1	1
114	41	41	41	41	41	826	81	1	1
115	41	41	41	41	41	807	81	1	1
116	41	41	41	41	41	800	81	1	1
117	41	41	41	41	41	801	81	1	1
118	41	41	41	41	41	\N	81	1	1
119	41	41	41	41	41	\N	81	1	1
120	42	42	42	42	42	859	81	1	1
121	42	42	42	42	42	864	81	1	1
122	42	42	42	42	42	838	81	1	1
123	42	42	42	42	42	\N	81	1	1
124	42	42	42	42	42	857	81	1	1
125	42	42	42	42	42	\N	81	1	1
126	42	42	42	42	42	861	81	1	1
127	42	42	42	42	42	\N	81	1	1
128	42	42	42	42	42	\N	81	1	1
129	42	42	42	42	42	841	81	1	1
130	42	42	42	42	42	862	81	1	1
131	42	42	42	42	42	863	81	1	1
132	43	43	43	43	43	876	81	1	1
133	43	43	43	43	43	877	81	1	1
134	43	43	43	43	43	\N	81	1	1
135	43	43	43	43	43	878	81	1	1
136	43	43	43	43	43	\N	81	1	1
137	43	43	43	43	43	\N	81	1	1
138	43	43	43	43	43	\N	81	1	1
139	43	43	43	43	43	1003	81	1	1
140	43	43	43	43	43	1009	81	1	1
141	43	43	43	43	43	\N	81	1	1
142	43	43	43	43	43	1004	81	1	1
143	43	43	43	43	43	1020	81	1	1
144	44	44	44	44	44	\N	81	1	1
145	44	44	44	44	44	\N	81	1	1
146	44	44	44	44	44	\N	81	1	1
147	44	44	44	44	44	1045	81	1	1
148	44	44	44	44	44	1046	81	1	1
149	44	44	44	44	44	1023	81	1	1
150	44	44	44	44	44	\N	81	1	1
151	44	44	44	44	44	1024	81	1	1
152	44	44	44	44	44	1022	81	1	1
153	44	44	44	44	44	\N	81	1	1
154	44	44	44	44	44	\N	81	1	1
155	44	44	44	44	44	1047	81	1	1
156	45	45	45	45	45	\N	81	1	1
157	45	45	45	45	45	1073	81	1	1
158	45	45	45	45	45	\N	81	1	1
159	45	45	45	45	45	\N	81	1	1
160	45	45	45	45	45	\N	81	1	1
161	45	45	45	45	45	\N	81	1	1
162	45	45	45	45	45	1077	81	1	1
163	45	45	45	45	45	\N	81	1	1
164	45	45	45	45	45	1074	81	1	1
165	45	45	45	45	45	1060	81	1	1
166	45	45	45	45	45	\N	81	1	1
167	45	45	45	45	45	\N	81	1	1
168	46	46	46	46	46	1091	81	1	1
169	46	46	46	46	46	\N	81	1	1
170	46	46	46	46	46	1090	81	1	1
171	46	46	46	46	46	\N	81	1	1
172	46	46	46	46	46	1089	81	1	1
173	46	46	46	46	46	1219	81	1	1
174	46	46	46	46	46	\N	81	1	1
175	46	46	46	46	46	\N	81	1	1
176	46	46	46	46	46	1224	81	1	1
177	46	46	46	46	46	\N	81	1	1
178	46	46	46	46	46	1243	81	1	1
179	46	46	46	46	46	1241	81	1	1
180	47	47	47	47	47	\N	81	1	1
181	47	47	47	47	47	\N	81	1	1
182	47	47	47	47	47	\N	81	1	1
183	47	47	47	47	47	\N	81	1	1
184	47	47	47	47	47	\N	81	1	1
185	47	47	47	47	47	1252	81	1	1
186	47	47	47	47	47	1257	81	1	1
187	47	47	47	47	47	1253	81	1	1
188	47	47	47	47	47	\N	81	1	1
189	47	47	47	47	47	1281	81	1	1
190	47	47	47	47	47	1254	81	1	1
191	47	47	47	47	47	\N	81	1	1
0	48	48	48	48	48	3	79	2	0
1	48	48	48	48	48	4	79	2	0
2	48	48	48	48	48	2	79	2	0
3	48	48	48	48	48	18	79	2	0
4	48	48	48	48	48	\N	79	2	0
5	48	48	48	48	48	31	79	2	0
6	48	48	48	48	48	33	79	2	0
7	48	48	48	48	48	30	79	2	0
8	48	48	48	48	48	29	79	2	0
9	48	48	48	48	48	19	79	2	0
10	48	48	48	48	48	\N	79	2	0
11	48	48	48	48	48	20	79	2	0
12	49	49	49	49	49	41	79	2	0
13	49	49	49	49	49	38	79	2	0
14	49	49	49	49	49	44	79	2	0
15	49	49	49	49	49	42	79	2	0
16	49	49	49	49	49	54	79	2	0
17	49	49	49	49	49	39	79	2	0
18	49	49	49	49	49	56	79	2	0
19	49	49	49	49	49	62	79	2	0
20	49	49	49	49	49	76	79	2	0
21	49	49	49	49	49	\N	79	2	0
22	49	49	49	49	49	63	79	2	0
23	49	49	49	49	49	36	79	2	0
24	50	50	50	50	50	78	79	2	0
25	50	50	50	50	50	87	79	2	0
26	50	50	50	50	50	205	79	2	0
27	50	50	50	50	50	\N	79	2	0
28	50	50	50	50	50	220	79	2	0
29	50	50	50	50	50	\N	79	2	0
30	50	50	50	50	50	206	79	2	0
31	50	50	50	50	50	\N	79	2	0
32	50	50	50	50	50	209	79	2	0
33	50	50	50	50	50	219	79	2	0
34	50	50	50	50	50	217	79	2	0
35	50	50	50	50	50	208	79	2	0
36	51	51	51	51	51	248	79	2	0
37	51	51	51	51	51	230	79	2	0
38	51	51	51	51	51	232	79	2	0
39	51	51	51	51	51	245	79	2	0
40	51	51	51	51	51	255	79	2	0
41	51	51	51	51	51	\N	79	2	0
42	51	51	51	51	51	257	79	2	0
43	51	51	51	51	51	\N	79	2	0
44	51	51	51	51	51	243	79	2	0
45	51	51	51	51	51	253	79	2	0
46	51	51	51	51	51	231	79	2	0
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48	52	52	52	52	52	259	79	2	0
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50	52	52	52	52	52	260	79	2	0
51	52	52	52	52	52	268	79	2	0
52	52	52	52	52	52	421	79	2	0
53	52	52	52	52	52	423	79	2	0
54	52	52	52	52	52	\N	79	2	0
55	52	52	52	52	52	\N	79	2	0
56	52	52	52	52	52	405	79	2	0
57	52	52	52	52	52	418	79	2	0
58	52	52	52	52	52	416	79	2	0
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60	53	53	53	53	53	437	79	2	0
61	53	53	53	53	53	429	79	2	0
62	53	53	53	53	53	\N	79	2	0
63	53	53	53	53	53	\N	79	2	0
64	53	53	53	53	53	\N	79	2	0
65	53	53	53	53	53	427	79	2	0
66	53	53	53	53	53	430	79	2	0
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69	53	53	53	53	53	426	79	2	0
70	53	53	53	53	53	438	79	2	0
71	53	53	53	53	53	\N	79	2	0
72	54	54	54	54	54	451	79	2	0
73	54	54	54	54	54	450	79	2	0
74	54	54	54	54	54	446	79	2	0
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79	54	54	54	54	54	589	79	2	0
80	54	54	54	54	54	583	79	2	0
81	54	54	54	54	54	\N	79	2	0
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83	54	54	54	54	54	569	79	2	0
84	55	55	55	55	55	595	79	2	0
85	55	55	55	55	55	605	79	2	0
86	55	55	55	55	55	\N	79	2	0
87	55	55	55	55	55	606	79	2	0
88	55	55	55	55	55	611	79	2	0
89	55	55	55	55	55	615	79	2	0
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91	55	55	55	55	55	607	79	2	0
92	55	55	55	55	55	608	79	2	0
93	55	55	55	55	55	\N	79	2	0
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95	55	55	55	55	55	598	79	2	0
96	56	56	56	56	56	629	79	2	0
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100	56	56	56	56	56	640	79	2	0
101	56	56	56	56	56	\N	79	2	0
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103	56	56	56	56	56	\N	79	2	0
104	56	56	56	56	56	634	79	2	0
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106	56	56	56	56	56	\N	79	2	0
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109	57	57	57	57	57	809	79	2	0
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112	57	57	57	57	57	\N	79	2	0
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114	57	57	57	57	57	817	79	2	0
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132	59	59	59	59	59	872	79	2	0
133	59	59	59	59	59	868	79	2	0
134	59	59	59	59	59	867	79	2	0
135	59	59	59	59	59	\N	79	2	0
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138	59	59	59	59	59	1017	79	2	0
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149	60	60	60	60	60	1036	79	2	0
150	60	60	60	60	60	1038	79	2	0
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172	62	62	62	62	62	\N	79	2	0
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178	62	62	62	62	62	\N	79	2	0
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8	64	64	64	64	64	\N	73	3	0
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16	65	65	65	65	65	\N	73	3	0
17	65	65	65	65	65	\N	73	3	0
18	65	65	65	65	65	\N	73	3	0
19	65	65	65	65	65	\N	73	3	0
20	65	65	65	65	65	\N	73	3	0
21	65	65	65	65	65	48	73	3	0
22	65	65	65	65	65	\N	73	3	0
23	65	65	65	65	65	\N	73	3	0
24	66	66	66	66	66	79	73	3	0
25	66	66	66	66	66	\N	73	3	0
26	66	66	66	66	66	\N	73	3	0
27	66	66	66	66	66	\N	73	3	0
28	66	66	66	66	66	\N	73	3	0
29	66	66	66	66	66	\N	73	3	0
30	66	66	66	66	66	\N	73	3	0
31	66	66	66	66	66	\N	73	3	0
32	66	66	66	66	66	\N	73	3	0
33	66	66	66	66	66	212	73	3	0
34	66	66	66	66	66	211	73	3	0
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37	67	67	67	67	67	238	73	3	0
38	67	67	67	67	67	239	73	3	0
39	67	67	67	67	67	\N	73	3	0
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41	67	67	67	67	67	\N	73	3	0
42	67	67	67	67	67	\N	73	3	0
43	67	67	67	67	67	\N	73	3	0
44	67	67	67	67	67	\N	73	3	0
45	67	67	67	67	67	\N	73	3	0
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49	68	68	68	68	68	261	73	3	0
50	68	68	68	68	68	262	73	3	0
51	68	68	68	68	68	\N	73	3	0
52	68	68	68	68	68	\N	73	3	0
53	68	68	68	68	68	\N	73	3	0
54	68	68	68	68	68	\N	73	3	0
55	68	68	68	68	68	\N	73	3	0
56	68	68	68	68	68	\N	73	3	0
57	68	68	68	68	68	\N	73	3	0
58	68	68	68	68	68	412	73	3	0
59	68	68	68	68	68	410	73	3	0
60	69	69	69	69	69	\N	73	3	0
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41	131	131	131	131	131	404	71	3	0
42	131	131	131	131	131	\N	71	3	0
43	131	131	131	131	131	403	71	3	0
44	131	131	131	131	131	\N	71	3	0
45	131	131	131	131	131	\N	71	3	0
46	131	131	131	131	131	\N	71	3	0
47	131	131	131	131	131	\N	71	3	0
48	132	132	132	132	132	\N	71	3	0
49	132	132	132	132	132	\N	71	3	0
50	132	132	132	132	132	\N	71	3	0
51	132	132	132	132	132	409	71	3	0
52	132	132	132	132	132	\N	71	3	0
53	132	132	132	132	132	\N	71	3	0
54	132	132	132	132	132	\N	71	3	0
55	132	132	132	132	132	554	71	3	0
56	132	132	132	132	132	\N	71	3	0
57	132	132	132	132	132	555	71	3	0
58	132	132	132	132	132	\N	71	3	0
59	132	132	132	132	132	\N	71	3	0
60	133	133	133	133	133	566	71	3	0
61	133	133	133	133	133	565	71	3	0
62	133	133	133	133	133	564	71	3	0
63	133	133	133	133	133	\N	71	3	0
64	133	133	133	133	133	558	71	3	0
65	133	133	133	133	133	\N	71	3	0
66	133	133	133	133	133	567	71	3	0
67	133	133	133	133	133	\N	71	3	0
68	133	133	133	133	133	\N	71	3	0
69	133	133	133	133	133	\N	71	3	0
70	133	133	133	133	133	\N	71	3	0
71	133	133	133	133	133	\N	71	3	0
72	134	134	134	134	134	576	71	3	0
73	134	134	134	134	134	\N	71	3	0
74	134	134	134	134	134	575	71	3	0
75	134	134	134	134	134	\N	71	3	0
76	134	134	134	134	134	\N	71	3	0
77	134	134	134	134	134	\N	71	3	0
78	134	134	134	134	134	720	71	3	0
79	134	134	134	134	134	719	71	3	0
80	134	134	134	134	134	\N	71	3	0
81	134	134	134	134	134	\N	71	3	0
82	134	134	134	134	134	\N	71	3	0
83	134	134	134	134	134	722	71	3	0
84	135	135	135	135	135	\N	71	3	0
85	135	135	135	135	135	\N	71	3	0
86	135	135	135	135	135	746	71	3	0
87	135	135	135	135	135	\N	71	3	0
88	135	135	135	135	135	\N	71	3	0
89	135	135	135	135	135	\N	71	3	0
90	135	135	135	135	135	\N	71	3	0
91	135	135	135	135	135	\N	71	3	0
92	135	135	135	135	135	\N	71	3	0
93	135	135	135	135	135	\N	71	3	0
94	135	135	135	135	135	\N	71	3	0
95	135	135	135	135	135	\N	71	3	0
96	136	136	136	136	136	752	71	3	0
97	136	136	136	136	136	\N	71	3	0
98	136	136	136	136	136	\N	71	3	0
99	136	136	136	136	136	\N	71	3	0
100	136	136	136	136	136	\N	71	3	0
101	136	136	136	136	136	\N	71	3	0
102	136	136	136	136	136	\N	71	3	0
103	136	136	136	136	136	\N	71	3	0
104	136	136	136	136	136	\N	71	3	0
105	136	136	136	136	136	781	71	3	0
106	136	136	136	136	136	\N	71	3	0
107	136	136	136	136	136	\N	71	3	0
108	137	137	137	137	137	894	71	3	0
109	137	137	137	137	137	\N	71	3	0
110	137	137	137	137	137	\N	71	3	0
111	137	137	137	137	137	\N	71	3	0
112	137	137	137	137	137	\N	71	3	0
113	137	137	137	137	137	\N	71	3	0
114	137	137	137	137	137	\N	71	3	0
115	137	137	137	137	137	\N	71	3	0
116	137	137	137	137	137	\N	71	3	0
117	137	137	137	137	137	\N	71	3	0
118	137	137	137	137	137	916	71	3	0
119	137	137	137	137	137	914	71	3	0
120	138	138	138	138	138	934	71	3	0
121	138	138	138	138	138	915	71	3	0
122	138	138	138	138	138	\N	71	3	0
123	138	138	138	138	138	\N	71	3	0
124	138	138	138	138	138	\N	71	3	0
125	138	138	138	138	138	\N	71	3	0
126	138	138	138	138	138	\N	71	3	0
127	138	138	138	138	138	\N	71	3	0
128	138	138	138	138	138	\N	71	3	0
129	138	138	138	138	138	\N	71	3	0
130	138	138	138	138	138	\N	71	3	0
131	138	138	138	138	138	\N	71	3	0
132	139	139	139	139	139	\N	71	3	0
133	139	139	139	139	139	\N	71	3	0
134	139	139	139	139	139	982	71	3	0
135	139	139	139	139	139	\N	71	3	0
136	139	139	139	139	139	\N	71	3	0
137	139	139	139	139	139	\N	71	3	0
138	139	139	139	139	139	\N	71	3	0
139	139	139	139	139	139	\N	71	3	0
140	139	139	139	139	139	\N	71	3	0
141	139	139	139	139	139	\N	71	3	0
142	139	139	139	139	139	\N	71	3	0
143	139	139	139	139	139	1099	71	3	0
144	140	140	140	140	140	1125	71	3	0
145	140	140	140	140	140	1139	71	3	0
146	140	140	140	140	140	\N	71	3	0
147	140	140	140	140	140	\N	71	3	0
148	140	140	140	140	140	\N	71	3	0
149	140	140	140	140	140	1161	71	3	0
150	140	140	140	140	140	\N	71	3	0
151	140	140	140	140	140	\N	71	3	0
152	140	140	140	140	140	\N	71	3	0
153	140	140	140	140	140	\N	71	3	0
154	140	140	140	140	140	\N	71	3	0
155	140	140	140	140	140	1162	71	3	0
156	141	141	141	141	141	\N	71	3	0
157	141	141	141	141	141	\N	71	3	0
158	141	141	141	141	141	\N	71	3	0
159	141	141	141	141	141	\N	71	3	0
160	141	141	141	141	141	\N	71	3	0
161	141	141	141	141	141	\N	71	3	0
162	141	141	141	141	141	\N	71	3	0
163	141	141	141	141	141	1191	71	3	0
164	141	141	141	141	141	\N	71	3	0
165	141	141	141	141	141	\N	71	3	0
166	141	141	141	141	141	1192	71	3	0
167	141	141	141	141	141	\N	71	3	0
168	142	142	142	142	142	\N	71	3	0
169	142	142	142	142	142	1211	71	3	0
170	142	142	142	142	142	1204	71	3	0
171	142	142	142	142	142	\N	71	3	0
172	142	142	142	142	142	\N	71	3	0
173	142	142	142	142	142	\N	71	3	0
174	142	142	142	142	142	\N	71	3	0
175	142	142	142	142	142	\N	71	3	0
176	142	142	142	142	142	\N	71	3	0
177	142	142	142	142	142	\N	71	3	0
178	142	142	142	142	142	\N	71	3	0
179	142	142	142	142	142	\N	71	3	0
180	143	143	143	143	143	\N	71	3	0
181	143	143	143	143	143	\N	71	3	0
182	143	143	143	143	143	\N	71	3	0
183	143	143	143	143	143	\N	71	3	0
184	143	143	143	143	143	\N	71	3	0
185	143	143	143	143	143	\N	71	3	0
186	143	143	143	143	143	\N	71	3	0
187	143	143	143	143	143	\N	71	3	0
188	143	143	143	143	143	\N	71	3	0
189	143	143	143	143	143	\N	71	3	0
190	143	143	143	143	143	\N	71	3	0
191	143	143	143	143	143	\N	71	3	0
\.


--
-- Data for Name: health; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.health (health_key, domestic_general_government_health_expenditure, hospital_beds, immunization_hepb3, immunization_dpt, immunization_measles, immunization_pol3, number_of_surgical_procedures, number_of_infant_deaths, number_of_stillbirths, number_of_deaths_ages_20_24, physicians_per_1000, prevalence_of_overweight, diabetes_prevalence, prevalence_of_hiv_total, adults_living_with_hiv, adults_newly_infected_with_hiv, children_living_with_hiv, children_newly_infected_with_hiv) FROM stdin;
0	6.59905815	3.1	14	93	94	93	\N	1800	1037	1307	\N	58.6	\N	\N	\N	\N	\N	\N
1	6.4866991	3.02	14	95	93	95	\N	1825	1083	1311	1.9086	59.2	\N	\N	\N	\N	\N	\N
2	6.57271051	2.96	14	94	94	99	\N	1845	1129	1307	\N	59.7	\N	\N	\N	\N	\N	\N
3	6.70117044	2.85	28	92	93	96	\N	1860	1138	1298	1.959	60.2	\N	\N	\N	\N	\N	\N
4	7.52118206	2.8	42	91	91	93	\N	1869	1126	1288	\N	60.7	\N	\N	\N	\N	\N	\N
5	7.47694063	2.78	56	89	90	90	\N	1871	1114	1276	2.0384	61.2	\N	\N	\N	\N	\N	\N
6	7.30276871	2.8	70	87	88	87	\N	1866	1116	1256	\N	61.7	8.4	\N	\N	\N	\N	\N
7	7.4011817	2.79	70	91	89	91	\N	1855	1110	1249	2.3962	62.2	\N	\N	\N	\N	\N	\N
8	7.3582077	2.72	55	91	90	91	\N	1839	1107	1263	2.4509	62.7	\N	\N	\N	\N	\N	\N
9	7.23180246	2.67	55	91	90	91	\N	1820	1114	1292	2.4961	63.2	\N	\N	\N	\N	\N	\N
10	7.58065939	2.62	69	91	89	91	\N	1799	1097	1325	2.5388	63.7	\N	\N	\N	\N	\N	\N
11	7.67784119	2.6	70	91	89	91	\N	1777	1087	1352	2.3105	64.1	\N	\N	\N	\N	\N	\N
12	7.56277943	2.53	71	91	90	91	\N	1757	1089	1366	2.6102	\N	\N	\N	\N	\N	\N	\N
13	7.58277988	2.55	71	91	90	91	\N	1736	1083	1365	2.4251	\N	\N	\N	\N	\N	\N	\N
14	7.60929585	2.52	74	91	90	91	\N	1715	1072	1349	2.4425	\N	\N	\N	\N	\N	\N	\N
15	\N	\N	74	91	90	91	\N	1692	\N	1325	\N	\N	\N	\N	\N	\N	\N	\N
16	6.62940884	3.2	93	96	92	92	\N	27762	12382	20208	\N	61.9	\N	\N	\N	\N	\N	\N
17	6.80890989	3.18	93	96	92	93	\N	27585	12336	20399	\N	62.5	\N	\N	\N	\N	\N	\N
18	6.9233551	3.14	93	96	92	93	\N	27261	12454	20301	\N	63.1	\N	\N	\N	\N	\N	\N
19	7.25172758	3.13	94	96	92	94	\N	26788	12805	19942	\N	63.7	\N	\N	\N	\N	\N	\N
20	7.87523222	3.08	92	95	90	93	\N	26200	12247	19418	\N	64.2	\N	\N	\N	\N	\N	\N
21	7.94476509	3.05	92	95	92	93	\N	25530	12147	18902	\N	64.8	\N	0.5	960000	34000	\N	\N
22	7.92789316	2.97	91	96	92	94	\N	24844	11987	18706	\N	65.3	9.4	0.5	980000	33000	\N	\N
23	7.90049934	2.93	90	94	91	93	\N	24184	11883	18800	\N	65.8	\N	0.5	1000000	33000	\N	\N
24	7.94619036	2.89	91	94	92	93	\N	23594	11799	19246	\N	66.4	\N	0.5	1000000	31000	\N	\N
25	8.23888111	2.83	92	95	92	93	\N	23089	11795	19981	\N	66.9	\N	0.5	1100000	32000	\N	\N
26	8.45250511	2.8	92	95	92	93	\N	22671	11810	20745	\N	67.4	\N	0.5	1100000	32000	\N	\N
27	8.55732727	2.77	93	95	92	94	\N	22334	11849	21292	\N	67.9	\N	0.4	1100000	32000	\N	\N
28	8.51218987	2.87	93	95	92	94	\N	22068	11861	21433	\N	\N	\N	0.4	1100000	31000	\N	\N
29	8.47234249	\N	91	94	92	93	\N	21847	11855	21133	2.6036	\N	\N	0.4	1200000	30000	\N	\N
30	8.52492332	\N	91	94	90	93	\N	21652	11844	20515	\N	\N	\N	0.4	1200000	29000	\N	\N
31	\N	\N	91	94	90	93	\N	21451	\N	19828	\N	\N	\N	\N	\N	\N	\N	\N
32	2.46497631	1.05	98	98	96	98	\N	44987	18512	9637	3.5303	58.9	\N	0.3	190000	14000	1900	500
33	2.4219811	1.02	98	98	96	98	\N	43211	18000	9860	3.762	59.5	\N	0.3	190000	14000	2200	700
34	2.52675962	1.06	98	98	96	98	\N	41560	17560	10399	3.843	60.1	\N	0.3	200000	13000	2400	620
35	2.61655498	1.03	97	96	96	96	\N	40080	17321	11213	3.8988	60.6	\N	0.3	210000	13000	2400	550
36	2.86067677	1.02	95	95	96	95	\N	38731	17106	12107	3.9581	61.2	\N	0.3	220000	14000	2500	500
37	2.8809936	1.05	93	95	95	95	\N	37469	16826	12856	3.9972	61.7	\N	0.3	230000	14000	2500	500
38	2.91415977	1.04	98	97	98	97	\N	36250	16514	13264	4.2008	62.3	15.6	0.3	240000	16000	2500	500
39	3.00721955	1.03	99	99	99	99	\N	35073	16133	13135	4.2236	62.8	\N	0.3	250000	17000	2500	500
40	3.12253189	1.03	82	83	89	83	\N	33910	15793	12758	4.311	63.3	\N	0.3	260000	18000	2500	500
41	2.89231014	1.03	84	87	97	87	\N	32728	15485	12611	4.4526	63.9	\N	0.3	270000	17000	2400	500
42	2.98734331	1	82	87	97	87	1303	31538	15333	12938	4.6493	64.4	\N	0.3	280000	17000	2400	500
43	2.84779787	1	93	93	96	96	\N	30368	15271	13547	4.6488	64.9	\N	0.3	290000	18000	2300	500
44	2.75801349	0.99	58	85	76	85	\N	29178	15287	14169	4.7654	\N	\N	0.3	300000	18000	2300	500
45	2.6718502	0.98	55	88	97	88	\N	28010	15296	14770	4.8496	\N	\N	0.3	320000	18000	2300	500
46	2.67891455	\N	56	82	73	82	\N	26892	15136	15457	\N	\N	\N	0.4	330000	18000	2300	500
47	\N	\N	56	82	73	82	\N	25833	\N	16242	\N	\N	\N	0.4	340000	18000	2300	500
48	0.73213077	\N	65	72	77	79	\N	164001	66751	23995	\N	19.8	\N	0.2	200000	43000	2700	1500
49	0.83084285	\N	66	72	79	78	\N	159233	65867	24197	\N	20.5	\N	0.2	240000	46000	3600	1900
50	1.01869869	\N	76	73	76	77	\N	154301	64869	24184	\N	21.2	\N	0.2	280000	46000	4500	2200
51	0.89791238	\N	82	77	76	83	\N	149371	63706	23884	\N	21.9	\N	0.2	320000	45000	5600	2500
52	0.92164314	0.59	82	78	74	85	\N	144552	62222	23339	0.2635	22.7	\N	0.3	350000	45000	6700	2800
53	0.66109073	0.57	83	81	78	82	\N	139744	60411	22756	0.243	23.4	\N	0.3	390000	45000	8000	3100
54	0.70177156	0.62	81	81	80	81	\N	134784	58826	22547	\N	24.2	5.1	0.3	420000	44000	9300	3400
55	0.76724905	0.83	86	87	82	87	\N	129886	57229	22479	0.2007	24.9	\N	0.3	440000	43000	11000	3500
56	0.81686825	0.99	92	92	87	92	\N	124880	55434	22526	0.3121	25.7	\N	0.3	470000	40000	12000	3600
57	0.99250942	0.94	88	88	86	90	\N	119782	53740	22531	\N	26.5	\N	0.3	480000	37000	13000	3700
58	1.15799761	0.98	84	84	87	85	\N	114762	51944	22610	0.2738	27.4	\N	0.3	500000	34000	14000	3700
59	1.37558305	0.99	84	84	88	85	\N	109901	50229	22697	\N	28.2	\N	0.4	510000	31000	15000	3600
60	1.34984493	1.04	85	85	90	88	\N	105291	48540	22779	0.3767	\N	\N	0.4	510000	30000	16000	3500
61	1.395854	\N	85	85	89	87	\N	100791	47093	22988	0.4269	\N	\N	0.4	520000	28000	17000	3400
62	1.42157829	\N	85	85	88	85	\N	96878	45857	23112	0.4651	\N	\N	0.4	520000	26000	17000	3300
63	\N	\N	85	85	88	85	\N	93233	\N	23167	\N	\N	\N	0.4	520000	24000	18000	3200
64	1.278759	0.8	\N	47	21	14	\N	90613	25531	10811	\N	20.5	\N	1.6	150000	20000	20000	6700
65	1.44412029	\N	\N	44	21	8	\N	88733	25484	10811	\N	21.1	\N	1.7	160000	20000	22000	6700
66	1.72198606	\N	43	48	58	43	\N	86660	25469	10810	\N	21.7	\N	1.7	180000	20000	25000	7200
67	2.13843656	\N	45	49	48	36	\N	84273	25582	10782	\N	22.3	\N	1.8	190000	21000	27000	7400
68	2.60045815	\N	47	50	46	36	\N	81692	25660	10730	0.1313	22.9	\N	1.9	200000	21000	29000	7700
69	1.67409575	\N	49	51	62	56	\N	79094	25603	10664	\N	23.6	\N	1.9	220000	20000	31000	7800
70	1.71321797	\N	50	52	57	50	\N	76429	25525	10558	\N	24.2	2.9	1.9	230000	20000	33000	8400
71	1.56333554	\N	52	53	65	54	\N	73672	25415	10440	\N	24.8	\N	1.9	240000	20000	35000	8400
72	1.69516742	\N	54	54	59	48	\N	71175	25444	10343	\N	25.5	\N	2	250000	19000	37000	8200
73	1.31816006	\N	55	55	56	55	\N	69010	25392	10276	\N	26.2	\N	2	260000	18000	37000	7600
74	1.23424077	\N	55	59	51	57	\N	67198	25458	10247	\N	26.8	\N	1.9	270000	18000	39000	7700
75	1.19753671	\N	55	59	45	53	\N	65848	25538	10259	\N	27.5	\N	1.9	280000	17000	40000	8000
76	1.29187	\N	52	56	42	47	\N	64778	25673	10300	0.2146	\N	\N	1.9	280000	17000	41000	8100
77	1.06878412	\N	59	63	50	56	\N	63772	25745	10349	\N	\N	\N	1.9	290000	16000	41000	7400
78	1.04434741	\N	53	57	51	51	\N	62880	25967	10420	\N	\N	\N	1.8	300000	16000	40000	6200
79	\N	\N	53	57	51	51	\N	62212	\N	10534	\N	\N	\N	1.8	300000	16000	39000	5200
80	1.22052443	\N	\N	82	79	82	\N	18087	7330	2632	\N	15.7	\N	1	76000	3200	5900	830
81	0.95991439	\N	80	80	78	80	\N	17129	7095	2644	\N	16.2	\N	0.9	76000	2800	6000	750
82	0.97199392	\N	82	82	79	82	\N	16273	6863	2508	\N	16.7	\N	0.9	75000	2400	6100	630
83	1.02431202	\N	91	91	89	91	\N	15398	6645	2257	0.2444	17.2	\N	0.9	75000	2000	6100	560
84	1.21738589	\N	92	94	92	95	\N	14471	6405	1975	0.2378	17.7	\N	0.9	75000	1800	6100	500
85	1.36283231	0.84	91	90	90	90	\N	13519	6146	1751	0.2302	18.3	\N	0.8	76000	1600	6000	500
86	1.27987134	0.7	91	91	88	91	\N	12609	5917	1648	0.2263	18.8	2.9	0.8	76000	1400	5800	500
87	1.406703	\N	91	90	84	90	\N	11775	5671	1628	0.1651	19.4	\N	0.8	75000	1300	5600	500
88	1.41955817	0.7	86	86	79	71	\N	11073	5456	1649	\N	19.9	\N	0.8	75000	1300	5300	500
89	1.23977208	\N	91	91	83	92	\N	10493	5269	1665	0.1927	20.5	\N	0.7	75000	1200	4900	500
90	1.34465146	0.8	92	92	84	92	\N	9982	5120	1658	\N	21.1	\N	0.7	74000	1200	4500	200
91	1.33381462	0.9	93	93	84	91	\N	9523	4979	1643	\N	21.7	\N	0.7	74000	1200	4200	200
92	1.51867294	\N	93	93	84	91	\N	9092	4842	1605	\N	\N	\N	0.6	73000	1100	3800	200
93	1.66258287	\N	92	92	84	90	\N	8661	4696	1543	\N	\N	\N	0.6	73000	1000	3500	200
94	1.69888663	\N	92	92	84	94	\N	8284	4573	1485	\N	\N	\N	0.6	72000	1000	3100	200
95	\N	\N	92	92	84	94	\N	7938	\N	1432	\N	\N	\N	0.5	72000	1000	2800	100
96	2.013062	2.1	96	98	96	98	\N	12466	7513	9723	\N	22.3	\N	1.8	670000	21000	18000	1700
97	2.2303164	\N	96	98	96	98	\N	11740	7166	8966	0.2875	23.1	\N	1.7	660000	19000	17000	1500
98	2.41405702	\N	96	98	96	98	\N	11069	6843	8279	0.2959	24	\N	1.7	650000	18000	16000	1300
99	2.60726309	\N	98	99	98	99	\N	10438	6547	7697	0.3164	24.9	\N	1.7	630000	16000	15000	1100
100	2.64681911	\N	98	99	98	99	\N	9838	6252	7238	0.3387	25.8	\N	1.6	620000	15000	14000	840
101	2.50096035	2.1	98	99	98	99	\N	9277	5965	6874	0.3906	26.7	\N	1.6	610000	14000	12000	670
102	2.72706866	\N	98	99	98	99	\N	8738	5664	6613	\N	27.6	7.5	1.5	600000	13000	11000	500
103	2.68024039	\N	98	99	98	99	\N	8236	5396	6452	\N	28.6	\N	1.5	580000	13000	10000	500
104	2.62275028	\N	99	99	99	99	\N	7774	5148	6409	\N	29.6	\N	1.4	570000	12000	8800	500
105	2.78856063	\N	99	99	99	99	\N	7343	4932	6465	\N	30.6	\N	1.4	560000	11000	7600	500
106	2.74870181	\N	99	99	99	99	\N	6932	4748	6557	0.4651	31.6	\N	1.3	540000	10000	6400	200
107	2.85137558	\N	99	99	99	99	\N	6543	4575	6646	0.445	32.6	\N	1.3	530000	9300	5200	100
108	2.76579475	\N	99	99	99	99	\N	6178	4420	6676	0.8075	\N	\N	1.2	520000	8600	4300	100
109	2.69087815	\N	97	97	96	97	\N	5834	4251	6629	0.805	\N	\N	1.2	510000	7800	3500	100
110	2.7152462	\N	97	97	96	97	\N	5503	4098	6504	0.9188	\N	\N	1.1	510000	7100	2800	100
111	\N	\N	97	97	96	97	\N	5191	\N	6337	\N	\N	\N	1	500000	6500	2400	100
112	3.07617569	2.8	79	81	64	75	\N	53752	21229	28082	\N	46.5	\N	15.9	4400000	410000	250000	72000
113	3.61328125	\N	83	84	69	79	\N	54092	21161	27678	\N	47.2	\N	16.2	4600000	390000	270000	73000
114	3.671134	2.41	83	85	68	79	\N	52751	21114	26798	0.6988	47.9	\N	16.5	4800000	380000	290000	72000
115	3.73152447	2.39	76	82	73	77	\N	49598	21110	25485	0.6968	48.6	\N	16.9	5000000	370000	320000	68000
116	4.23951578	\N	74	81	77	75	\N	44926	21134	23909	0.7074	49.2	\N	17.3	5200000	370000	340000	58000
117	4.44811392	2.3	71	77	72	72	\N	40694	21016	22211	0.7207	49.9	\N	17.7	5500000	360000	360000	45000
118	4.53395033	\N	76	75	77	71	\N	38338	20926	20471	0.7227	50.6	7	18.1	5700000	350000	370000	34000
119	4.5380373	\N	70	71	79	69	\N	37180	20837	18910	0.7277	51.2	\N	18.4	5900000	330000	370000	31000
120	4.52993202	\N	73	81	78	79	\N	36173	20649	17537	0.7422	51.9	\N	18.7	6200000	310000	380000	26000
121	4.75114346	\N	85	85	84	85	\N	35302	20493	16373	0.7541	52.5	\N	19	6400000	290000	380000	23000
122	5.01728439	\N	85	85	86	85	\N	34249	20415	15412	0.7814	53.2	\N	19.2	6600000	270000	380000	17000
123	4.99312115	\N	76	76	85	76	\N	33356	20272	14589	0.7675	53.8	\N	19.3	6800000	260000	370000	14000
124	4.98211432	\N	76	76	70	76	\N	32777	20106	13850	0.7833	\N	\N	19.4	7000000	250000	360000	15000
125	5.07550335	\N	74	74	70	74	\N	31810	19874	13162	0.7874	\N	\N	19.4	7200000	230000	350000	12000
126	5.35265827	\N	77	77	72	77	\N	30937	19612	12529	0.7923	\N	\N	19.3	7300000	210000	330000	11000
127	\N	\N	77	77	72	77	\N	30153	\N	11940	\N	\N	\N	19.1	7500000	200000	310000	12000
128	\N	\N	65	68	67	69	\N	20791	10010	6051	0.1255	33.3	\N	18	1200000	62000	160000	25000
129	\N	3	68	70	68	71	\N	22017	10407	5939	\N	33.8	\N	17.1	1100000	59000	160000	24000
130	\N	\N	72	73	69	73	\N	23113	10806	5830	0.0544	34.3	\N	16.5	1100000	57000	160000	23000
131	\N	\N	75	75	70	75	\N	23711	11135	5710	0.0596	34.8	\N	15.9	1100000	56000	150000	22000
132	\N	\N	73	73	76	69	\N	24133	11333	5562	0.121	35.3	\N	15.5	1100000	54000	150000	20000
133	2.75335717	\N	90	89	90	89	\N	23804	11335	5388	0.1272	35.7	\N	15.2	1100000	53000	140000	17000
134	2.1196537	1.7	94	93	92	93	\N	23680	11163	5137	0.0817	36.2	9.8	15	1100000	48000	140000	14000
135	1.99878275	\N	97	95	97	95	\N	21931	10857	4892	0.0807	36.6	\N	14.8	1100000	44000	130000	9500
136	2.01807022	\N	95	95	93	95	\N	21210	10386	4667	0.0834	37	\N	14.5	1100000	42000	120000	9000
137	2.73156643	\N	91	91	92	92	\N	20245	9358	4489	0.124	37.3	\N	14.3	1100000	39000	110000	8000
138	1.55136812	\N	87	87	86	88	\N	19665	8392	4347	0.1815	37.7	\N	14	1200000	36000	110000	7700
139	1.78890914	\N	90	90	95	90	\N	18753	7743	4198	0.1788	38.2	\N	13.6	1200000	33000	100000	6600
140	1.79418128	\N	89	89	90	89	\N	18018	7335	4104	0.1859	\N	\N	13.2	1200000	29000	96000	5800
141	2.78293462	\N	89	89	88	89	\N	17196	7169	4063	0.2096	\N	\N	12.8	1200000	24000	90000	5100
142	1.35826993	\N	90	90	85	90	\N	16615	7113	4053	\N	\N	\N	12.4	1200000	24000	84000	4700
143	\N	\N	90	90	85	90	\N	16354	\N	4079	\N	\N	\N	11.9	1200000	19000	79000	5100
\.


--
-- Data for Name: month; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.month (month_key, name, month, quarter, year, decade) FROM stdin;
0	January	1	1	2005	201
1	February	2	1	2005	201
2	March	3	1	2005	201
3	April	4	2	2005	201
4	May	5	2	2005	201
5	June	6	2	2005	201
6	July	7	3	2005	201
7	August	8	3	2005	201
8	September	9	3	2005	201
9	October	10	4	2005	201
10	November	11	4	2005	201
11	December	12	4	2005	201
12	January	1	1	2006	201
13	February	2	1	2006	201
14	March	3	1	2006	201
15	April	4	2	2006	201
16	May	5	2	2006	201
17	June	6	2	2006	201
18	July	7	3	2006	201
19	August	8	3	2006	201
20	September	9	3	2006	201
21	October	10	4	2006	201
22	November	11	4	2006	201
23	December	12	4	2006	201
24	January	1	1	2007	201
25	February	2	1	2007	201
26	March	3	1	2007	201
27	April	4	2	2007	201
28	May	5	2	2007	201
29	June	6	2	2007	201
30	July	7	3	2007	201
31	August	8	3	2007	201
32	September	9	3	2007	201
33	October	10	4	2007	201
34	November	11	4	2007	201
35	December	12	4	2007	201
36	January	1	1	2008	201
37	February	2	1	2008	201
38	March	3	1	2008	201
39	April	4	2	2008	201
40	May	5	2	2008	201
41	June	6	2	2008	201
42	July	7	3	2008	201
43	August	8	3	2008	201
44	September	9	3	2008	201
45	October	10	4	2008	201
46	November	11	4	2008	201
47	December	12	4	2008	201
48	January	1	1	2009	201
49	February	2	1	2009	201
50	March	3	1	2009	201
51	April	4	2	2009	201
52	May	5	2	2009	201
53	June	6	2	2009	201
54	July	7	3	2009	201
55	August	8	3	2009	201
56	September	9	3	2009	201
57	October	10	4	2009	201
58	November	11	4	2009	201
59	December	12	4	2009	201
60	January	1	1	2010	202
61	February	2	1	2010	202
62	March	3	1	2010	202
63	April	4	2	2010	202
64	May	5	2	2010	202
65	June	6	2	2010	202
66	July	7	3	2010	202
67	August	8	3	2010	202
68	September	9	3	2010	202
69	October	10	4	2010	202
70	November	11	4	2010	202
71	December	12	4	2010	202
72	January	1	1	2011	202
73	February	2	1	2011	202
74	March	3	1	2011	202
75	April	4	2	2011	202
76	May	5	2	2011	202
77	June	6	2	2011	202
78	July	7	3	2011	202
79	August	8	3	2011	202
80	September	9	3	2011	202
81	October	10	4	2011	202
82	November	11	4	2011	202
83	December	12	4	2011	202
84	January	1	1	2012	202
85	February	2	1	2012	202
86	March	3	1	2012	202
87	April	4	2	2012	202
88	May	5	2	2012	202
89	June	6	2	2012	202
90	July	7	3	2012	202
91	August	8	3	2012	202
92	September	9	3	2012	202
93	October	10	4	2012	202
94	November	11	4	2012	202
95	December	12	4	2012	202
96	January	1	1	2013	202
97	February	2	1	2013	202
98	March	3	1	2013	202
99	April	4	2	2013	202
100	May	5	2	2013	202
101	June	6	2	2013	202
102	July	7	3	2013	202
103	August	8	3	2013	202
104	September	9	3	2013	202
105	October	10	4	2013	202
106	November	11	4	2013	202
107	December	12	4	2013	202
108	January	1	1	2014	202
109	February	2	1	2014	202
110	March	3	1	2014	202
111	April	4	2	2014	202
112	May	5	2	2014	202
113	June	6	2	2014	202
114	July	7	3	2014	202
115	August	8	3	2014	202
116	September	9	3	2014	202
117	October	10	4	2014	202
118	November	11	4	2014	202
119	December	12	4	2014	202
120	January	1	1	2015	202
121	February	2	1	2015	202
122	March	3	1	2015	202
123	April	4	2	2015	202
124	May	5	2	2015	202
125	June	6	2	2015	202
126	July	7	3	2015	202
127	August	8	3	2015	202
128	September	9	3	2015	202
129	October	10	4	2015	202
130	November	11	4	2015	202
131	December	12	4	2015	202
132	January	1	1	2016	202
133	February	2	1	2016	202
134	March	3	1	2016	202
135	April	4	2	2016	202
136	May	5	2	2016	202
137	June	6	2	2016	202
138	July	7	3	2016	202
139	August	8	3	2016	202
140	September	9	3	2016	202
141	October	10	4	2016	202
142	November	11	4	2016	202
143	December	12	4	2016	202
144	January	1	1	2017	202
145	February	2	1	2017	202
146	March	3	1	2017	202
147	April	4	2	2017	202
148	May	5	2	2017	202
149	June	6	2	2017	202
150	July	7	3	2017	202
151	August	8	3	2017	202
152	September	9	3	2017	202
153	October	10	4	2017	202
154	November	11	4	2017	202
155	December	12	4	2017	202
156	January	1	1	2018	202
157	February	2	1	2018	202
158	March	3	1	2018	202
159	April	4	2	2018	202
160	May	5	2	2018	202
161	June	6	2	2018	202
162	July	7	3	2018	202
163	August	8	3	2018	202
164	September	9	3	2018	202
165	October	10	4	2018	202
166	November	11	4	2018	202
167	December	12	4	2018	202
168	January	1	1	2019	202
169	February	2	1	2019	202
170	March	3	1	2019	202
171	April	4	2	2019	202
172	May	5	2	2019	202
173	June	6	2	2019	202
174	July	7	3	2019	202
175	August	8	3	2019	202
176	September	9	3	2019	202
177	October	10	4	2019	202
178	November	11	4	2019	202
179	December	12	4	2019	202
180	January	1	1	2020	203
181	February	2	1	2020	203
182	March	3	1	2020	203
183	April	4	2	2020	203
184	May	5	2	2020	203
185	June	6	2	2020	203
186	July	7	3	2020	203
187	August	8	3	2020	203
188	September	9	3	2020	203
189	October	10	4	2020	203
190	November	11	4	2020	203
191	December	12	4	2020	203
\.


--
-- Data for Name: population; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.population (population_key, life_expectancy_at_birth_f, life_expectancy_at_birth_m, life_expectancy_at_birth_t, net_migration, population_ages_0_14, population_ages_15_19, population_ages_20_24, population_ages_24_29, population_ages_30_34, population_ages_35_39, population_ages_40_44, population_ages_45_49, population_ages_50_54, population_ages_55_59, population_ages_60_64, population_ages_65_up, rural_population, rural_population_growth_rate, rural_poverty_rate, urban_population, urban_population_growth_rate, urban_poverty_rate) FROM stdin;
0	82.6	77.9	80.1926829268293	1326431	5699388	2176774	2224116	2162471	2182321	2355672	2746155	2616579	2312163	2005420	1533102	4229595	19.878	0.557844254173616	\N	80.122	1.04061858829188	\N
1	82.7	78.1	80.3439024390244	1326431	5667703	2204841	2259501	2201714	2190448	2307589	2705963	2664884	2366995	2069935	1609828	4321770	19.787	0.551491248878675	\N	80.213	1.12384675481251	\N
2	82.9	78.3	80.5439024390244	1326431	5635757	2227626	2288132	2246798	2204519	2279262	2634544	2712998	2422688	2122127	1695397	4419171	19.604	0.0419781487099549	\N	80.396	1.19901884209158	\N
3	83	78.5	80.6951219512195	1326431	5616013	2241710	2315671	2298129	2227389	2271998	2548658	2757265	2481678	2169817	1786582	4532190	19.422	0.150191983656897	\N	80.578	1.30902990520455	\N
4	83.3	78.8	80.9951219512195	1326431	5608093	2239995	2343097	2350113	2258947	2277249	2469160	2782789	2541508	2219902	1874437	4663591	19.242	0.210657043137183	\N	80.758	1.36489394771959	\N
5	83.5	79.1	81.2463414634146	1241416	5606922	2219822	2367035	2397648	2298169	2287377	2409731	2778436	2599243	2275195	1952382	4812931	19.063	0.177253215195272	\N	80.937	1.33326871439499	\N
6	83.6	79.4	81.4487804878049	1241416	5636891	2223289	2368232	2427587	2333870	2290912	2356489	2732863	2657763	2329364	2019605	4962461	18.904	0.141129967876975	\N	81.096	1.17495264216968	\N
7	83.8	79.6	81.6487804878049	1241416	5657280	2217399	2388630	2445763	2383782	2304063	2330762	2657575	2719377	2393654	2076842	5139105	18.863	0.868694356405575	\N	81.137	1.13636233305053	\N
8	83.9	79.7	81.7487804878049	1241416	5671952	2194613	2427191	2447830	2440359	2322946	2325376	2563210	2767831	2464597	2123739	5333340	18.822	0.838999350897815	\N	81.178	1.1071099946107	\N
9	83.9	79.8	81.8	1241416	5691799	2158911	2470174	2444037	2492440	2348723	2329518	2472997	2786797	2536506	2168973	5536588	18.782	0.792587517646634	\N	81.218	1.05460141956621	\N
10	84	79.9	81.9	1210159	5709424	2112855	2494099	2444905	2524658	2378392	2330976	2398681	2763581	2597239	2216487	5731613	18.741	0.527807559356073	\N	81.259	0.796807975480466	\N
11	84	79.9	81.9	1210159	5740699	2085616	2500077	2493161	2552362	2427908	2347157	2362742	2722428	2655918	2279526	5941934	18.7	0.913336125759693	\N	81.3	1.18279215486163	\N
12	84	79.9	81.9	1210159	5799752	2057136	2482387	2562764	2566008	2488844	2366969	2351477	2651187	2711857	2351676	6155289	18.65	0.931952478221833	\N	81.35	1.26116200732881	\N
13	84.2	80	82.0487804878049	1210159	5882337	2033323	2452840	2645612	2579832	2559202	2396751	2363646	2569527	2761788	2433158	6387204	18.589	1.08492803121353	\N	81.411	1.48750598693977	\N
14	84.2	80	82.0487804878049	1210159	5957010	2015849	2419086	2716205	2605615	2624663	2436519	2384556	2496670	2789037	2513692	6634505	18.518	1.0323383832027	\N	81.482	1.50218820550071	\N
15	84.2	80	82.0487804878049	1210159	5995422	2002179	2379944	2752199	2644672	2670784	2480479	2399972	2440373	2778185	2580427	6880603	18.438	0.656644458992974	\N	81.562	1.18772430444538	\N
16	80.1	75	77.4878048780488	5428756	61707218	21607754	20649612	19450365	19729293	20896980	22591734	22288251	20080671	17223481	12908085	36383152	20.072	0.0733898148736528	\N	79.928	1.13588459113456	\N
17	80.3	75.2	77.6878048780488	5428756	62115320	21754531	20912588	19673553	19642164	20596282	22335460	22494311	20524843	17826286	13562009	36942770	19.901	0.108670280303657	\N	80.099	1.17796815968651	\N
18	80.6	75.5	77.9878048780488	5428756	62324459	21923545	21151864	19959372	19611593	20373180	22003454	22634172	20993099	18346012	14340725	37570070	19.731	0.0931570901609545	\N	80.269	1.16306776101756	\N
19	80.6	75.6	78.0390243902439	5428756	62414797	22089895	21373622	20270131	19646800	20218899	21635767	22690220	21459340	18812938	15180035	38301901	19.562	0.0856572616332229	\N	80.438	1.15618567133535	\N
20	80.9	76	78.390243902439	5428756	62456435	22193580	21572650	20552603	19738689	20098506	21271155	22633062	21859564	19265310	15977459	39152786	19.394	0.0141332145804876	\N	80.606	1.08529029428822	\N
21	81	76.2	78.5414634146342	4961716	62498933	22219640	21762768	20796349	19882467	20006770	20951291	22472033	22161562	19736741	16682443	40156146	19.228	-0.0300018427486857	\N	80.772	1.03534480069191	\N
22	81.1	76.3	78.6414634146341	4961716	62395007	22210101	22087579	21117161	20060961	19928382	20662301	22192756	22288762	20131620	17222772	41286340	19.056	-0.17176717755585	\N	80.944	0.93950541093758	\N
23	81.2	76.4	78.7414634146342	4961716	62220502	22076579	22434161	21459006	20316859	19904974	20450023	21858288	22356093	20548556	17685821	42567079	18.881	-0.188989154899031	\N	81.119	0.94956550837067	\N
24	81.2	76.4	78.7414634146342	4961716	62001634	21844306	22747841	21805447	20622111	19929224	20292710	21487701	22345721	20945417	18089255	43948751	18.701	-0.265051290084759	\N	81.299	0.914510413562637	\N
25	81.3	76.5	78.8414634146341	4961716	61818661	21604685	22980425	22171414	20969040	20024698	20186709	21145548	22270145	21292369	18496152	45426535	18.517	-0.255415159548918	\N	81.483	0.95943078191871	\N
26	81.2	76.3	78.690243902439	4774029	61657987	21400768	23078070	22542519	21333785	20188306	20114110	20855782	22121854	21553458	18926913	46965442	18.329	-0.284256234098651	\N	81.671	0.966674782180289	\N
27	81.1	76.1	78.5390243902439	4774029	61459046	21339950	23066039	22896433	21693177	20406393	20078016	20614910	21893331	21716009	19338826	48569567	18.138	-0.322855438046257	\N	81.862	0.958268060593122	\N
28	81.1	76.1	78.5390243902439	4774029	61313248	21292039	22904727	23232319	22030039	20660071	20056555	20409928	21570767	21783204	19737418	50131749	17.942	-0.453841679756109	\N	82.058	0.871785260117191	\N
29	81.2	76.2	78.6390243902439	4774029	61148289	21246964	22647439	23511960	22344468	20936883	20058275	20236600	21191547	21754944	20095370	51665417	17.744	-0.58325455730801	\N	82.256	0.767437430461766	\N
30	81.4	76.3	78.7878048780488	4774029	60902964	21203139	22385857	23690068	22652713	21229126	20106565	20091891	20819859	21642774	20384023	53220954	17.541	-0.695262032744607	\N	82.459	0.701867775195684	\N
31	81.4	76.3	78.7878048780488	4774029	60531991	21145453	22156629	23725981	22946722	21516625	20201494	19961798	20483404	21443442	20574321	54796261	17.336	-0.824661438105005	\N	82.664	0.599210762260319	\N
32	77.999	72.575	75.3	-562404	33749096	10324459	9581485	8853282	8369332	7342016	6342087	5280930	4323303	3258153	2618291	5962762	23.692	0.11167801180592	\N	76.308	1.82420878524429	\N
33	78.035	72.532	75.296	-562404	33798545	10447428	9670681	8939848	8472398	7529042	6516549	5453678	4489447	3404476	2694135	6144401	23.384	0.147672580663442	\N	76.616	1.8590281344028	\N
34	78.039	72.447	75.255	-562404	33787851	10612567	9758583	9047406	8550202	7735324	6691495	5642110	4649783	3582867	2767993	6344810	23.08	0.17750313761612	\N	76.92	1.88206292256786	\N
35	78.026	72.342	75.194	-562404	33739827	10800133	9850031	9162967	8613030	7943965	6868431	5839810	4808361	3780663	2848672	6559632	22.778	0.17824244769517	\N	77.222	1.88721556631294	\N
36	78.004	72.233	75.128	-562404	33692627	10969976	9955661	9269959	8676710	8129281	7050937	6036665	4972571	3978053	2949713	6781773	22.48	0.159842847415204	\N	77.52	1.86191341992348	\N
37	77.979	72.135	75.065	-422477	33666194	11091375	10084613	9361506	8749205	8276247	7240420	6226475	5146568	4162941	3078480	7008937	22.185	0.117173388078255	\N	77.815	1.81796631467998	\N
38	77.952	72.056	75.011	-422477	33640734	11150497	10260275	9465854	8838653	8394537	7439151	6408579	5323130	4328439	3221290	7224215	21.889	0.0515758490797851	\N	78.111	1.7744572453399	\N
39	77.922	71.997	74.966	-422477	33657460	11145616	10457829	9559654	8932157	8475522	7645147	6581698	5507326	4482555	3389970	7439123	21.595	0.00305232375938382	\N	78.405	1.73097530755872	\N
40	77.89	71.958	74.93	-422477	33693379	11101311	10654612	9654825	9026033	8533385	7846200	6751378	5696010	4631863	3574087	7664064	21.301	-0.0552207900612247	\N	78.699	1.68983234295214	\N
41	77.86	71.943	74.908	-422477	33707136	11059535	10816546	9768926	9116915	8590029	8024732	6927537	5884729	4787723	3758249	7913125	21.007	-0.112142908580838	\N	78.993	1.65056526440047	\N
42	77.837	71.954	74.904	-300000	33676708	11046772	10923127	9909714	9204739	8657070	8170380	7114812	6070550	4956396	3933358	8194621	20.715	-0.158599751358101	\N	79.285	1.61013604556509	\N
43	77.826	71.99	74.917	-300000	33676044	11061055	10987020	10087245	9303320	8727072	8277574	7300220	6238522	5117529	4080737	8477148	20.423	-0.216377556093139	\N	79.577	1.5708748882209	\N
44	77.827	72.046	74.947	-300000	33614045	11102334	10995541	10294568	9404210	8809673	8355443	7499260	6403877	5291121	4222035	8785351	20.133	-0.266178940038251	\N	79.867	1.52773148162835	\N
45	77.844	72.118	74.992	-300000	33512294	11156027	10969453	10505672	9513343	8901648	8413833	7697817	6570060	5472596	4362465	9115671	19.844	-0.319440697492789	\N	80.156	1.48761300066204	\N
46	77.879	72.203	75.054	-300000	33405803	11196583	10943429	10680499	9640376	8996249	8469007	7874167	6742852	5654641	4510104	9461864	19.556	-0.370590771968483	\N	80.444	1.45002297233125	\N
47	77.879	72.203	75.054	-300000	33310119	11209593	10939819	10795774	9789880	9090150	8531964	8015794	6924917	5833054	4669454	9822231	19.269	-0.42021464078884	\N	80.731	1.4143747761486	\N
48	69.107	65.579	67.334	-1333685	67618156	22134037	20987223	20516083	18781505	16809601	14479111	11605365	9216719	7427192	5850849	10863627	54.058	-0.119982703096022	\N	45.942	3.07746462438665	\N
49	69.565	65.899	67.717	-1333685	67697354	21931364	21258493	20668419	19174168	17242413	14965065	12197702	9564905	7533575	5921088	11163634	53.262	-0.153859617501482	\N	46.738	3.04736254502646	\N
50	70.025	66.228	68.105	-1333685	67957690	21681416	21373239	20858317	19517780	17666518	15426138	12785547	10008807	7685593	5983068	11429869	52.465	-0.183851506328241	\N	47.535	3.01470927794316	\N
51	70.474	66.554	68.485	-1333685	68391140	21482068	21228061	21143445	19782893	18079405	15884058	13327884	10542951	7908790	6037599	11661061	51.665	-0.21324010850987	\N	48.335	2.99229541377777	\N
52	70.905	66.872	68.853	-1333685	68992007	21376482	20859712	21463226	19989436	18469464	16344530	13816615	11134196	8220749	6100949	11852841	50.866	-0.229367256791318	\N	49.134	2.96874980696441	\N
53	71.311	67.182	69.205	-454447	69716216	21367934	20414317	21666895	20206311	18819300	16799511	14276999	11735231	8627918	6202534	12001059	50.086	-0.207537485107733	\N	49.914	2.91280934009964	\N
54	71.69	67.485	69.542	-454447	69917357	21671341	20360708	21531120	20514061	19086518	17196089	14708889	12191487	9104927	6469522	12363667	49.405	-0.0210845599133991	\N	50.595	2.70302720446254	\N
55	72.047	67.784	69.866	-454447	70249118	21990318	20436501	21191667	20862905	19296278	17563640	15145339	12603644	9616855	6780787	12714313	48.724	-0.0362916067632649	\N	51.276	2.68870491926569	\N
56	72.383	68.081	70.179	-454447	70600834	22311883	20621626	20755297	21192061	19482760	17906208	15583921	12993259	10147093	7136460	13073681	48.045	-0.0625941318397963	\N	51.955	2.65628613315295	\N
57	72.698	68.371	70.481	-454447	70843582	22614696	20869351	20386195	21401644	19696538	18228524	16018124	13394252	10670455	7537589	13467036	47.365	-0.114506066147422	\N	52.635	2.6112791471733	\N
58	72.992	68.651	70.768	-494777	70928717	22877885	21144361	20183149	21431269	19960388	18530768	16440352	13824071	11169666	7982733	13909899	46.687	-0.173950895901836	\N	53.313	2.54772031433686	\N
59	73.264	68.914	71.035	-494777	71228822	23048357	21423844	20103029	21265277	20236537	18767267	16804384	14222978	11587994	8418643	14449236	46.011	-0.237934081635893	\N	53.989	2.48060257193435	\N
60	73.515	69.156	71.282	-494777	71230548	23194452	21756307	20189465	20939629	20593402	18984842	17174581	14655754	11989126	8905531	15037314	45.341	-0.290682444333394	\N	54.659	2.40955382199953	\N
61	73.748	69.375	71.509	-494777	71069736	23299761	22102651	20399464	20534409	20947837	19195948	17536494	15104727	12382352	9419261	15677890	44.675	-0.345256883092995	\N	55.325	2.34560697392157	\N
62	73.967	69.572	71.716	-494777	70944816	23342742	22411039	20657797	20182568	21171086	19423483	17869919	15542793	12782842	9922820	16373650	44.015	-0.390431636388131	\N	55.985	2.28381798088284	\N
63	73.967	69.572	71.716	-494777	70941104	23318346	22653270	20918156	19973248	21193374	19680740	18165985	15954982	13200117	10394846	17129452	43.359	-0.436439683580507	\N	56.641	2.23010935628228	\N
64	52.614	47.893	50.165	357301	9111255	2126694	1748847	1418630	1176042	879930	796441	608881	432547	365854	277520	490965	44	0.906610847853287	\N	56	5.65449742019371	\N
65	53.642	48.821	51.143	357301	9459742	2194950	1816010	1470792	1223672	918942	809919	643251	452891	370884	284357	504496	43.236	1.86796692762772	\N	56.764	4.97464879942458	\N
66	54.726	49.807	52.177	357301	9823509	2265258	1887441	1529035	1266004	973473	815501	679987	479858	374037	294790	516470	42.476	1.90717644032449	\N	57.524	5.0105924402647	\N
67	55.839	50.826	53.243	357301	10201777	2337538	1961519	1591993	1305976	1037069	819658	715901	511669	377968	306919	527657	41.718	1.90989493407563	\N	58.282	5.01966522581942	\N
68	56.953	51.85	54.311	357301	10590934	2412281	2036170	1657875	1348896	1099538	832508	746504	545713	386699	318071	539092	40.966	1.88482405238829	\N	59.034	4.98586279172289	\N
69	58.033	52.848	55.35	166267	10987155	2490136	2110233	1725665	1397912	1154723	859934	769515	580175	402447	326965	551385	40.217	1.82622748637208	\N	59.783	4.93227212928482	\N
70	59.052	53.79	56.33	166267	11418718	2564512	2179107	1793200	1449221	1201336	897963	782487	612604	421523	331424	568566	39.472	1.76432636731329	\N	60.528	4.87262349690642	\N
71	59.992	54.66	57.236	166267	11849941	2643680	2248468	1864181	1506105	1242585	950666	787805	647217	446567	334190	586520	38.732	1.70521587711144	\N	61.268	4.81291353028581	\N
72	60.841	55.447	58.054	166267	12280862	2728503	2318461	1936786	1567409	1281295	1011803	791709	680988	475922	337760	604295	37.998	1.63872821484832	\N	62.002	4.74289874279112	\N
73	61.591	56.14	58.776	166267	12710363	2820443	2389817	2008788	1631335	1322536	1071551	803879	709585	507233	345765	620479	37.269	1.56028283148803	\N	62.731	4.66635747013067	\N
74	62.237	56.737	59.398	32066	13136045	2920715	2463585	2079144	1696733	1369482	1124113	829929	730901	538940	360183	634612	36.554	1.50174428807543	\N	63.446	4.57220933179748	\N
75	62.783	57.242	59.925	32066	13571355	3025675	2538205	2147750	1763007	1419666	1169249	866480	742881	568675	377420	652140	35.851	1.43635402152184	\N	64.149	4.48020433880439	\N
76	63.252	57.677	60.379	32066	13999872	3138929	2615485	2215530	1831841	1474595	1208731	916670	747416	600355	399700	667665	35.161	1.37876441159101	\N	64.839	4.39203509910461	\N
77	63.666	58.064	60.782	32066	14421730	3260975	2697137	2283242	1902094	1533590	1245661	974766	750733	631327	425673	682865	34.486	1.33773771293477	\N	65.514	4.31180314839867	\N
78	64.039	58.416	61.147	32066	14837599	3392242	2785583	2352180	1972076	1595355	1285262	1031686	762217	657655	453487	699952	33.823	1.3016764857377	\N	66.177	4.24982377385174	\N
79	64.039	58.416	61.147	32066	15248424	3532518	2882566	2423471	2040757	1658972	1330695	1082040	787212	677390	481968	720250	33.175	1.28407907063163	\N	66.825	4.19296192786897	\N
80	65.312	60.738	63.088	-295987	4919913	1598559	1592202	727283	868011	815911	713228	532957	466474	333099	256168	449549	80.826	1.42376629303271	\N	19.174	2.19344027197012	\N
81	66.15	61.567	63.927	-295987	4884569	1561916	1679692	840807	824228	828609	740400	558122	478007	352428	262764	466143	80.707	1.38047704478093	\N	19.293	2.14655160439467	\N
82	66.904	62.342	64.697	-295987	4846707	1561312	1662249	1051696	744933	848920	758456	593692	482929	376688	269714	482657	80.587	1.34067308439315	\N	19.413	2.10949988211833	\N
83	67.569	63.062	65.394	-295987	4808363	1598400	1553204	1324440	658445	870088	768372	636249	485652	402954	278318	499372	80.429	1.28312048405077	\N	19.571	2.28996470781328	\N
84	68.145	63.72	66.014	-295987	4779983	1644906	1416808	1574428	620697	875818	775594	677976	493973	426480	290475	516492	80.07	1.05223901478387	\N	19.93	3.31731485333765	\N
85	68.64	64.313	66.56	-149999	4769772	1672595	1316568	1728450	673506	854633	785342	712258	513169	444445	307140	534328	79.706	1.08350820256841	\N	20.294	3.34908730062363	\N
86	69.072	64.842	67.043	-149999	4787157	1687479	1312536	1737319	819147	799406	798529	730444	539533	453252	324569	552123	79.337	1.12482599189132	\N	20.663	3.3907932516779	\N
87	69.47	65.315	67.48	-149999	4803021	1674328	1378223	1637636	1062934	708863	823529	740118	576922	456919	347317	570705	78.963	1.15792451540894	\N	21.037	3.42424711508669	\N
88	69.854	65.742	67.888	-149999	4825072	1640566	1483796	1477651	1345695	619203	847987	744498	619246	459815	372059	590745	78.585	1.16997708997338	\N	21.415	3.43073508309497	\N
89	70.234	66.127	68.273	-149999	4859074	1601470	1578258	1339857	1572397	588114	852376	749599	657254	468882	393827	613379	78.201	1.14827620027409	\N	21.799	3.41536520647582	\N
90	70.61	66.474	68.637	-149999	4905112	1567611	1630334	1275763	1685617	648066	827293	758898	685445	487938	410000	639356	77.812	1.10500698618853	\N	22.188	3.37241820988723	\N
91	70.975	66.785	68.977	-149999	4948930	1535431	1651567	1276534	1699415	794438	775483	774368	704924	514620	419278	671233	77.418	1.05757634724575	\N	22.582	3.32537807444196	\N
92	71.318	67.062	69.289	-149999	5006532	1503233	1639677	1342629	1601100	1035988	686549	799422	714540	550671	422891	706111	77.02	1.01486028018694	\N	22.98	3.27737495822157	\N
93	71.629	67.312	69.57	-149999	5070166	1476205	1604197	1446045	1441283	1314151	597792	822809	718317	590807	425608	742385	76.612	0.959202128902874	\N	23.388	3.25022442790301	\N
94	71.909	67.538	69.823	-149999	5127182	1460767	1563125	1538264	1304261	1536522	567223	826606	723168	627060	434565	777796	76.195	0.900626105522849	\N	23.805	3.21366227921854	\N
95	71.909	67.538	69.823	-149999	5170334	1460325	1528306	1589299	1241298	1647970	626899	802188	732822	654662	453519	811352	75.768	0.837982559310065	\N	24.232	3.17781513618208	\N
96	75.619	68.71	72.099	59008	13924391	5111600	5273478	5322179	5555804	5784742	5399775	4919508	3944854	2893250	2214148	5072462	62.589	-1.31946536566635	\N	37.411	4.02171277434503	\N
97	75.981	69.138	72.499	59008	13704044	5028493	5199796	5314264	5529471	5801789	5497363	5037071	4121645	3046300	2283429	5248872	61.327	-1.43287309071174	\N	38.673	3.92175699477365	\N
98	76.383	69.563	72.916	59008	13492036	4968823	5093390	5293330	5505502	5789254	5605595	5132254	4301901	3209422	2370324	5420240	60.05	-1.54435630334258	\N	39.95	3.8086082474163	\N
99	76.815	69.978	73.341	59008	13284646	4932766	4967685	5249124	5483215	5758542	5711782	5215169	4482740	3378614	2472673	5594052	58.758	-1.64920153667651	\N	41.242	3.70866885158336	\N
100	77.265	70.374	73.766	59008	13083013	4906373	4845119	5174498	5457400	5725917	5797678	5302678	4655450	3551439	2588781	5778515	57.457	-1.73550757528209	\N	42.543	3.60935451216024	\N
101	77.725	70.749	74.184	167314	12890536	4875183	4744942	5070085	5419539	5699914	5853816	5403924	4812620	3728624	2717577	5978272	56.144	-1.82207949473314	\N	43.856	3.52924359815393	\N
102	78.186	71.104	74.593	167314	12819758	4863776	4699012	4932031	5335923	5649207	5847658	5482036	4924519	3904982	2854632	6204889	55.302	-1.03102235120902	\N	44.698	2.38177508348844	\N
103	78.64	71.446	74.992	167314	12720502	4852284	4701137	4786591	5233122	5600865	5822170	5567768	5014475	4088027	3002696	6446370	54.555	-0.890697712274414	\N	45.445	2.12667717502957	\N
104	79.078	71.779	75.378	167314	12601016	4841814	4738465	4650543	5106617	5546874	5786228	5647831	5092161	4269132	3158501	6705347	53.807	-0.926765025411668	\N	46.193	2.08636411484452	\N
105	79.49	72.102	75.747	167314	12475316	4832367	4786690	4544401	4958997	5475848	5748403	5706826	5170603	4435276	3319594	6984420	53.057	-0.972831452759917	\N	46.943	2.04142288941411	\N
106	79.863	72.412	76.091	97222	12350897	4819462	4829646	4481171	4800098	5379063	5709896	5739781	5255158	4579301	3484908	7285138	52.306	-1.02343811237841	\N	47.694	1.98928888012459	\N
107	80.189	72.704	76.403	97222	12170444	4754882	4872244	4513075	4694603	5262110	5647715	5750416	5340686	4710756	3663355	7591016	51.552	-1.07899310185976	\N	48.448	1.94156013754868	\N
108	80.468	72.977	76.683	97222	12010548	4666043	4890627	4583800	4597746	5134997	5579100	5736759	5425885	4817810	3850998	7915508	50.8	-1.12425934230437	\N	49.2	1.88546106272637	\N
109	80.704	73.228	76.931	97222	11863232	4563778	4884251	4675688	4519282	5003944	5501947	5703352	5503696	4908009	4038660	8262645	50.051	-1.1699787160322	\N	49.949	1.82629129954117	\N
110	80.9	73.46	77.15	97222	11713485	4464515	4855822	4761374	4473247	4877824	5412380	5657985	5563525	4993984	4213507	8637966	49.308	-1.21209144846065	\N	50.692	1.76009094466907	\N
111	80.9	73.46	77.15	97222	11553638	4378506	4807904	4822404	4466694	4763033	5308840	5605417	5598953	5082441	4367653	9044496	48.57	-1.25786269793264	\N	51.43	1.69551994112433	\N
112	55.927	51.104	53.447	862221	14786130	5346081	4998065	4272413	3767971	3169409	2669078	2246265	1860511	1396784	1159714	2208174	40.464	-0.0952710831329213	\N	59.536	2.1539801080897	\N
113	56.281	51.439	53.795	862221	14791617	5333275	5111198	4387788	3828951	3239333	2722388	2291045	1911789	1442891	1168273	2260934	39.923	-0.0823848473151366	\N	60.077	2.16821224137716	\N
114	56.994	52.038	54.452	862221	14840942	5287290	5210534	4527655	3885194	3314295	2774540	2336817	1955330	1502982	1174071	2310141	39.384	-0.067797001639187	\N	60.616	2.18467924143766	\N
115	57.995	52.853	55.36	862221	14932291	5218537	5290195	4683232	3948589	3392018	2827297	2383933	1994473	1570546	1182939	2355445	38.846	-0.0413363480887665	\N	61.154	2.21775604755682	\N
116	59.218	53.833	56.46	862221	15053477	5144373	5345125	4840482	4035628	3469923	2884339	2432811	2034720	1636525	1203227	2396396	38.313	0.00994917029705168	\N	61.687	2.2593302979005	\N
117	60.565	54.906	57.669	919697	15196945	5076652	5372759	4988325	4154807	3548462	2948272	2483439	2079076	1695836	1239044	2433353	37.782	0.0596329017177781	\N	62.218	2.31239696005493	\N
118	61.935	55.993	58.895	919697	15401412	5012545	5355955	5089350	4265145	3622657	3034131	2547536	2134265	1754508	1290239	2495993	37.254	0.11716683233515	\N	62.746	2.36956213449542	\N
119	63.236	57.027	60.06	919697	15600147	4961658	5320630	5188832	4404075	3689485	3127141	2617809	2194947	1810959	1357346	2559573	36.728	0.159364169844966	\N	63.272	2.41615873332643	\N
120	64.394	57.951	61.099	919697	15800774	4920646	5270518	5278062	4562009	3755160	3220294	2693708	2259186	1866414	1433406	2626871	36.207	0.175671898106549	\N	63.793	2.42442571960463	\N
121	65.359	58.728	61.968	919697	16009828	4885528	5214167	5345561	4720251	3832464	3305200	2773142	2324900	1922966	1508654	2701460	35.688	0.139989959687362	\N	64.312	2.39406473406266	\N
122	66.108	59.342	62.649	727026	16223293	4855550	5158219	5384502	4865305	3931743	3378167	2853132	2391507	1981669	1577664	2785619	35.172	0.0758276410354681	\N	64.828	2.33137782779205	\N
123	66.654	59.803	63.153	727026	16420143	4840329	5104766	5395643	5010401	4079888	3453241	2925052	2446940	2026379	1625816	2878983	34.659	0.00264363518024856	\N	65.341	2.26014461613465	\N
124	67.064	60.162	63.538	727026	16618491	4830807	5052429	5373029	5138735	4252178	3522228	3001193	2504206	2072017	1669030	2975322	34.15	-0.0625368459002804	\N	65.85	2.19291873963855	\N
125	67.398	60.463	63.857	727026	16805770	4833393	5003550	5326580	5245539	4437119	3595232	3079701	2563697	2118958	1709599	3073322	33.645	-0.126111714302677	\N	66.355	2.12767299835243	\N
126	67.679	60.726	64.131	727026	16963349	4858842	4960242	5271518	5325121	4617345	3688227	3157520	2626187	2167926	1750923	3171038	33.144	-0.183981430866601	\N	66.856	2.06848480453102	\N
127	67.679	60.726	64.131	727026	17081570	4913211	4924091	5217398	5374110	4781215	3810040	3233235	2692132	2219400	1794715	3267575	32.646	-0.240580143097643	\N	67.354	2.01548003295595	\N
128	44.962	41.573	43.241	-512676	4993345	1561421	1298635	1035271	756999	576168	445103	350969	286036	203271	193762	375716	65.89	0.750965094400302	\N	34.11	-0.0666628753133472	\N
129	45.535	42.193	43.853	-512676	5009935	1546960	1313633	1054357	778217	582638	449502	353462	290573	206938	188416	381136	66.074	0.929222961511846	\N	33.926	0.109495858140618	\N
130	46.603	43.276	44.947	-512676	5048695	1528354	1332394	1068618	803668	589821	453674	356387	292443	215279	180713	386222	66.257	1.09935296881223	\N	33.743	0.281885444751979	\N
131	48.14	44.81	46.504	-512676	5108435	1510515	1351811	1079993	831096	599289	457592	359457	292619	225904	173007	390116	66.44	1.27952273560697	\N	33.56	0.459899149495046	\N
132	50.068	46.724	48.449	-512676	5187117	1499100	1367131	1092253	857040	612629	461567	362152	292624	235408	168493	391598	66.622	1.45728565362915	\N	33.378	0.639938612526558	\N
133	52.239	48.884	50.64	-622997	5283500	1496851	1376461	1107835	879021	630101	466185	364052	293176	241805	168675	390068	66.804	1.62677140301074	\N	33.196	0.807208623699139	\N
134	54.471	51.117	52.896	-622997	5387543	1479845	1363295	1125377	908018	661852	482643	373547	298857	247869	173645	391923	66.985	1.806980674545	\N	33.015	0.989668495186914	\N
135	56.578	53.24	55.032	-622997	5508283	1474184	1346049	1140638	929280	699198	500577	384002	305942	252339	182898	391912	67.166	1.96793235416517	\N	32.834	1.14833308301087	\N
136	58.412	55.106	56.897	-622997	5638052	1479018	1329502	1150158	942924	739537	520486	395431	314000	256014	194333	391111	67.346	2.04531129919547	\N	32.654	1.22794267316597	\N
137	59.892	56.632	58.41	-622997	5764685	1492005	1318817	1151243	951670	777519	543880	408092	322513	260204	205077	391147	67.496	1.97722127948747	\N	32.504	1.29432586809941	\N
138	60.984	57.778	59.534	-584288	5878455	1510954	1317027	1145064	957426	808201	571927	422234	331226	265598	213613	392921	67.615	1.83984061826914	\N	32.385	1.29692205874524	\N
139	61.719	58.565	60.294	-584288	5986056	1517655	1310095	1144265	970149	827842	602996	437829	341017	271474	219538	401561	67.704	1.6808367320412	\N	32.296	1.27409384280022	\N
140	62.22	59.105	60.812	-584288	6064488	1533435	1313565	1137326	983888	842175	639342	454566	351908	279278	224405	412367	67.763	1.54651666935413	\N	32.237	1.27654356252103	\N
141	62.598	59.501	61.195	-584288	6122210	1558954	1328103	1125243	995162	853227	677196	473156	363670	288630	228883	424461	67.791	1.4516887041322	\N	32.209	1.32349714884316	\N
142	62.899	59.798	61.49	-584288	6174257	1594436	1350444	1112461	999534	863258	710937	494841	376151	298642	234001	436533	67.79	1.41966571378716	\N	32.21	1.42424874688139	\N
143	62.899	59.798	61.49	-584288	6229216	1638895	1377829	1105162	994874	872602	737527	520295	389420	308669	240442	447992	67.758	1.42665638495326	\N	32.242	1.57316861683581	\N
\.


--
-- Data for Name: quality_of_life; Type: TABLE DATA; Schema: public; Owner: postgres
--

COPY public.quality_of_life (quality_of_life_key, access_to_drinking_water, access_to_sanitation, access_to_basic_handwashing_facilities, unemployment_rate_f, unemployment_rate_m, unemployment_rate_t, maternal_leave_benefits, access_to_electricity_total, access_to_electricity_urban, access_to_electricity_rural, part_time_employment_t, part_time_employment_f, part_time_employment_m) FROM stdin;
0	99.23464422	99.80519484	\N	6.46600008010864	7.01700019836426	6.76000022888184	\N	100	100	100	38.2000007629395	48.8499984741211	28.8299999237061
1	99.23461957	99.75033789	\N	6.09200000762939	6.52199983596802	6.32000017166138	\N	100	100	100	39.6500015258789	50.1100006103516	30.3600006103516
2	99.23549716	99.69595411	\N	5.65299987792969	6.38399982452393	6.03999996185303	\N	100	100	100	38.25	48.689998626709	28.8899993896484
3	99.23607708	99.6414571	\N	5.65199995040894	6.57200002670288	6.1399998664856	\N	100	100	100	39.4500007629395	49.7200012207031	30.2299995422363
4	99.23635504	99.5868457	\N	7.00500011444092	9.53299999237061	8.34000015258789	40	100	100	100	42.6100006103516	52.3300018310547	33.6500015258789
5	99.23634886	99.53213067	\N	7.24300003051758	8.79399967193604	8.0600004196167	\N	100	100	100	41.1199989318848	51.3699989318848	31.7199993133545
6	99.23589396	99.47721571	\N	7.00899982452393	7.95900011062622	7.51000022888184	35	100	100	100	40.2599983215332	50.0200004577637	31.3899993896484
7	99.23432608	99.42171918	\N	6.81699991226196	7.71600008010864	7.28999996185303	\N	100	100	100	38.8899993896484	48.8600006103516	29.7999992370605
8	99.23268617	99.36619078	\N	6.59700012207031	7.49700021743774	7.07000017166138	37	100	100	100	40.0999984741211	49.75	31.2800006866455
9	99.23098502	99.31064352	\N	6.38899993896484	7.37799978256226	6.90999984741211	\N	100	100	100	42.7700004577637	52.4500007629395	33.9700012207031
10	99.22922139	99.25507123	\N	6.29199981689453	7.46199989318848	6.90999984741211	55	100	100	100	40.3600006103516	50.1100006103516	31.5400009155273
11	99.22739547	99.19947682	\N	6.24100017547607	7.68100023269653	7	\N	100	100	100	40	49.5099983215332	31.3299999237061
12	99.22553764	99.14388406	\N	5.85099983215332	6.7810001373291	6.34000015258789	55	100	100	100	40.9000015258789	50.1699981689453	32.4500007629395
13	99.22363119	99.08828896	\N	5.48899984359741	6.13899993896484	5.82999992370605	\N	100	100	100	38.4099998474121	47.8199996948242	29.8400001525879
14	99.22164984	99.03268117	\N	5.25	6.03000020980835	5.65999984741211	\N	100	100	100	41.8699989318848	50.8699989318848	33.689998626709
15	99.22181066	99.03286158	\N	9.38599967956543	9.52600002288818	9.46000003814697	\N	100	\N	\N	42.2700004577637	50.7900009155273	34.6699981689453
16	98.8536874	99.8817868	\N	5.09600019454956	5.06599998474121	5.07999992370605	\N	100	100	100	26.6599998474121	34.9099998474121	19.5100002288818
17	98.86083682	99.88154042	\N	4.625	4.61499977111816	4.61999988555908	\N	100	100	100	26.4300003051758	34.5099983215332	19.4500007629395
18	98.86794461	99.88129549	\N	4.49599981307983	4.72499990463257	4.61999988555908	\N	100	100	100	26.1200008392334	34.2099990844727	19.1200008392334
19	98.87501291	99.8810546	\N	5.41400003433228	6.09299993515015	5.78000020980835	\N	100	100	100	26.7800006866455	34.1800003051758	20.2900009155273
20	98.88203953	99.88081511	\N	8.05900001525879	10.2760000228882	9.25	\N	100	100	100	30.7800006866455	37.8699989318848	24.3999996185303
21	98.97895208	99.86076619	\N	8.60999965667725	10.5080003738403	9.63000011444092	\N	100	100	100	28.8799991607666	35.9599990844727	22.5300006866455
22	99.07488707	99.84103269	\N	8.46100044250488	9.37100028991699	8.94999980926514	\N	100	100	100	28.5499992370605	35.7900009155273	22.1599998474121
23	99.16968809	99.82162867	\N	7.88700008392334	8.22700023651123	8.06999969482422	\N	100	100	100	27.7900009155273	34.9799995422363	21.4200000762939
24	99.26337949	99.80256859	\N	7.06899976730347	7.62799978256226	7.36999988555908	\N	100	100	100	27	34.0900001525879	20.7099990844727
25	99.35588121	99.78386084	\N	6.06199979782104	6.26200008392334	6.17000007629395	\N	100	100	100	27.2999992370605	34.6500015258789	20.8099994659424
26	99.44715776	99.7655241	\N	5.17799997329712	5.36700010299683	5.28000020980835	\N	100	100	100	27.7199993133545	35.0200004577637	21.2900009155273
27	99.53713865	99.74755356	\N	4.78900003433228	4.93900012969971	4.86999988555908	\N	100	100	100	26.3899993896484	33.439998626709	20.1800003051758
28	99.62581578	99.72996764	\N	4.31199979782104	4.40199995040894	4.3600001335144	\N	100	100	100	26.5499992370605	33.5900001525879	20.3299999237061
29	99.71312112	99.71277377	\N	3.84100008010864	3.95099997520447	3.90000009536743	\N	100	100	100	25.3199996948242	32.0900001525879	19.3299999237061
30	99.79904438	99.69599445	\N	3.61100006103516	3.72099995613098	3.67000007629395	\N	100	100	100	24.7700004577637	31.3700008392334	18.9200000762939
31	99.88352668	99.67961928	\N	8.34500026702881	7.7960000038147	8.05000019073486	\N	100	\N	\N	27.9799995422363	34.1800003051758	22.5100002288818
32	93.09668937	81.27377788	\N	3.90899991989136	3.36800003051758	3.55999994277954	\N	98.932728	99.605581	96.76558019035	22.6599998474121	33.5699996948242	16.3700008392334
33	93.71099729	82.07830717	\N	3.89000010490417	3.38899993896484	3.5699999332428	\N	99.11416	99.705865	97.175480958877	23.6000003814697	34.7799987792969	16.9799995422363
34	94.32032157	82.87293106	\N	4	3.41899991035461	3.63000011444092	\N	98.1106262207031	99.3383636474609	94.0188774255628	26.5799999237061	37.9900016784668	19.7199993133545
35	94.90809059	83.65830449	\N	4.02899980545044	3.77900004386902	3.86999988555908	\N	98.914037	99.725953	96.1614784465745	26.75	37.8699989318848	20.1000003814697
36	95.36710258	84.43419231	\N	5.35400009155273	5.36399984359741	5.3600001335144	100	98.4097290039063	99.4668426513672	94.7643798444367	28.3500003814697	39.0299987792969	21.8899993896484
37	95.82133427	85.20102819	\N	5.17999982833862	5.36999988555908	5.30000019073486	\N	99.236696	99.703549	97.5991857046315	27.7399997711182	38.310001373291	21.3899993896484
38	96.27120298	85.95971004	89.66001526	5.13199996948242	5.19199991226196	5.17000007629395	100	99.064094543457	99.7253265380859	96.7044850339172	27.3299999237061	37.8600006103516	20.9699993133545
39	96.71644433	86.70980432	89.68317442	4.88399982452393	4.89400005340576	4.8899998664856	\N	99.111637	99.650006	97.156979858956	27.5100002288818	38.0499992370605	21.0100002288818
40	97.15725463	87.45178303	89.70633655	4.9539999961853	4.88399982452393	4.90999984741211	100	99.2320251464844	99.7692184448242	97.2473026235041	27.1599998474121	37.4900016784668	20.7600002288818
41	97.5936259	88.18573213	89.72949429	4.84800004959106	4.78800010681152	4.80999994277954	\N	99.172928	99.63725	97.4269296534203	26.7700004577637	37.310001373291	20.3600006103516
42	98.02544354	88.91148404	89.75249473	4.44700002670288	4.22800016403198	4.30999994277954	100	99	99.3	97.8517740684543	26.8999996185303	37.4700012207031	20.4200000762939
43	98.45286453	89.62944687	89.77550185	3.91000008583069	3.82999992370605	3.85999989509583	\N	99.5	99.8	98.331067891438	26.1299991607666	36.6500015258789	19.6299991607666
44	98.87578129	90.33947554	89.79834169	3.60199999809265	3.31200003623962	3.42000007629395	100	100	100	100	25.3999996185303	35.8499984741211	18.9699993133545
45	99.26913243	91.04184497	89.82111114	3.42899990081787	3.18899989128113	3.27999997138977	\N	99.5	99.8	98.2882080243438	25.1900005340576	35.7099990844727	18.6700000762939
46	99.47726394	91.73666093	89.84379235	3.51699995994568	3.45700001716614	3.48000001907349	\N	100	100	100	25.9799995422363	36.6199989318848	19.1499996185303
47	99.67956828	92.42406261	\N	4.09700012207031	4.66699981689453	4.44999980926514	\N	100	\N	\N	\N	\N	\N
48	80.02217385	49.29277182	\N	10.039999961853	6.76599979400635	7.94000005722046	\N	85.4211120605469	96.7489318847656	75.7939949730175	32.9799995422363	45.9799995422363	26.1000003814697
49	80.92466101	51.63089589	69.85283043	9.2790002822876	6.58199977874756	7.55000019073486	\N	90.62	97.048828125	84.9786315316531	33.0400009155273	44.9199981689453	26.6200008392334
50	81.81767312	53.99525073	70.04840506	9.9040002822876	6.94600009918213	8.0600004196167	\N	91.1	98.2	84.6671686286269	32.7400016784668	43.810001373291	26.2999992370605
51	82.70159068	56.38531405	70.24471508	8.10400009155273	6.66300010681152	7.21000003814697	\N	92.73	97.6933517456055	88.0865546359025	32.5299987792969	42.1100006103516	26.7099990844727
52	83.57565413	58.79885691	70.44077974	6.70499992370605	5.74399995803833	6.1100001335144	100	93.55	98.9	88.3821688725424	32.3600006103516	41.4199981689453	26.7999992370605
53	84.43671954	61.23020925	70.63218206	6.38800001144409	5.12799978256226	5.6100001335144	\N	94.15	98.96	89.3565179950132	32.7400016784668	42.5499992370605	26.7000007629395
54	85.27144926	63.65928867	73.35761843	5.56400012969971	4.89499998092651	5.15000009536743	100	94.83	99.35	90.2011284604576	33.2799987792969	43.4500007629395	27.0400009155273
55	86.09794725	66.11190851	76.05299916	4.78599977493286	4.27500009536743	4.46999979019165	\N	96	99.2	92.6323947288045	33.6699981689453	44.1199989318848	27.2299995422363
56	86.91591354	68.58672819	78.71796572	4.27199983596802	4.38199996948242	4.34000015258789	100	96.4642583061542	99.6731650809369	92.9942041681205	36.5499992370605	45.4500007629395	31.0799999237061
57	87.72586319	71.08355243	81.35312153	3.88199996948242	4.15299987792969	4.05000019073486	\N	97.01	99.74	93.9762504080437	33.5400009155273	43.9099998474121	27.1499996185303
58	88.52735296	73.60086085	83.95799441	4.4229998588562	4.56300020217896	4.51000022888184	100	97.5373674369822	99.8313935861281	94.9177642160956	31.6200008392334	41.3699989318848	25.5799999237061
59	89.32043532	76.13784121	86.53271571	3.86899995803833	4.56899976730347	4.30000019073486	\N	97.62	99.8	95.0620025675624	30.7000007629395	40.560001373291	24.4799995422363
60	90.10462418	78.69303054	89.07706113	3.59899997711182	4.05900001525879	3.88000011444092	100	98.14	99.89	96.0303586103137	31.0599994659424	41.1500015258789	24.5799999237061
61	90.88029952	81.2661059	91.59156142	4.18100023269653	4.54099988937378	4.40000009536743	\N	98.51	99.88	96.8134079568893	32.2299995422363	42.1500015258789	25.7999992370605
62	91.64729028	83.85609129	94.0763809	3.34800004959106	3.79800009727478	3.61999988555908	\N	98.85	99.89	97.5271691517377	32.6399993896484	42.3899993896484	26.2399997711182
63	92.41534961	86.462642	94.10706813	3.77800011634827	4.60699987411499	4.28000020980835	\N	98.85	\N	\N	35.7400016784668	45.1699981689453	29.5400009155273
64	46.33601912	34.72263851	\N	3.0220000743866	4.72599983215332	3.88199996948242	\N	29.5962238311768	51.8093376159668	1.32498881356757	\N	\N	\N
65	47.15022864	35.99128127	\N	2.9779999256134	4.72200012207031	3.85800004005432	\N	30.6465549468994	53.2539596557617	0.965576784056293	\N	\N	\N
66	47.96147053	37.25930604	\N	2.92499995231628	4.70300006866455	3.82100009918213	\N	37.5	66.1	\N	\N	\N	\N
67	48.77040378	38.52751059	\N	2.87899994850159	4.69600009918213	3.79299998283386	\N	38.49	61.31	6.60939361517007	\N	\N	\N
68	49.57516542	39.79427161	\N	2.84200000762939	4.70699977874756	3.77999997138977	100	33.8041839599609	57.6685028076172	\N	\N	\N	\N
69	50.37684093	41.06079267	\N	10.9250001907349	7.94999980926514	9.43000030517578	\N	34.8797264099121	73.9696273803711	\N	\N	\N	\N
70	51.17483374	42.32666372	\N	7.72100019454956	7.01000022888184	7.3600001335144	100	34.6	82.5	\N	\N	\N	\N
71	51.9685411	43.59147171	25.94168867	7.71500015258789	6.98899984359741	7.34700012207031	\N	37.1010246276855	70.7206573486328	\N	\N	\N	\N
72	52.75734684	44.85479322	26.09391769	7.74100017547607	7	7.36600017547607	100	38.2489929199219	68.7236175537109	\N	\N	\N	\N
73	53.5415069	46.11702927	26.24511041	7.75400018692017	6.99900007247925	7.37200021743774	\N	32	51	\N	\N	\N	\N
74	54.31692835	47.37448057	26.39339879	7.7810001373291	7.01200008392334	7.39200019836426	100	42	64	3.8150702987396	\N	\N	\N
75	55.08427644	48.62794482	26.5392	7.80700016021729	7.02400016784668	7.41200017929077	\N	41.7973785400391	67.9861068725586	\N	\N	\N	\N
76	55.84290632	49.87698012	26.68230262	7.80999994277954	7.01300001144409	7.40799999237061	100	43.0016098022461	69.4484634399414	\N	\N	\N	\N
77	56.59174872	51.12074396	26.82229525	7.8289999961853	7.01900005340576	7.4210000038147	\N	45.29	65.27	7.33344863532473	\N	\N	\N
78	56.88303903	51.39362406	26.95980034	7.83500003814697	7.01200008392334	7.4210000038147	\N	45.6703147888184	72.3714752197266	\N	\N	\N	\N
79	57.16773762	51.66032915	27.09419377	8.77400016784668	7.90100002288818	8.33300018310547	\N	45.6703147888184	\N	\N	\N	\N	\N
80	60.294322	23.33220447	\N	1.17999994754791	1.08399999141693	1.13100004196167	\N	20.5	66.8	9.51645207111159	\N	\N	\N
81	61.22719385	26.14679527	\N	1.20000004768372	1.21700000762939	1.20899999141693	\N	31.8314018249512	75.9830093383789	21.2769666153161	\N	\N	\N
82	62.12338724	28.98279548	\N	1.192999958992	1.32299995422363	1.25999999046326	\N	35.086009979248	78.4249038696289	24.645890133261	26.9799995422363	32.0699996948242	22.1200008392334
83	62.9930786	31.85696911	62.57489425	0.819999992847443	0.819999992847443	0.819999992847443	\N	26.4	87	11.6540437225952	27.1399993896484	32.939998626709	21.6800003051758
84	63.87999387	34.84063238	62.69676083	0.560000002384186	0.600000023841858	0.579999983310699	50	41.6110191345215	83.3402862548828	31.2243051192286	28.4899997711182	33.0099983215332	24.0200004577637
85	64.73036087	37.84219611	62.82032527	0.790000021457672	0.75	0.769999980926514	\N	31.1	91.3	15.7724382109896	25.4799995422363	31.3600006103516	19.5100002288818
86	65.54445489	40.8613316	62.94558205	0.479999989271164	0.680000007152557	0.579999983310699	50	48.198657989502	93.2182922363281	36.4734779229828	23.8299999237061	29.3099994659424	18.2999992370605
87	66.32257759	43.89771493	63.07254222	0.499000012874603	0.519999980926514	0.509999990463257	\N	51.529842376709	94.3766403198242	40.1147739435467	23.5300006866455	27.3400001525879	20.1299991607666
88	67.06475682	46.9506025	64.49106226	0.523000001907349	0.361999988555908	0.439999997615814	50	54.885139465332	95.2520065307617	43.8848663984841	19.8500003814697	25.4400005340576	14.5
89	67.77182986	50.02047495	65.89103445	0.689999997615814	0.689999997615814	0.689999997615814	\N	56.1	96.9	44.7267537359728	19.2299995422363	24.0499992370605	14.7799997329712
90	68.44384896	53.10657357	67.27171566	0.456999987363815	0.328000009059906	0.389999985694885	50	68.8477020263672	98.0794219970703	60.5123122466418	19.3600006103516	25.2399997711182	13.9099998474121
91	69.08113407	56.20854526	68.63269854	0.855000019073486	0.592999994754791	0.720000028610229	\N	76.6266784667969	99.2468719482422	70.0286113979845	16.0900001525879	20.8700008392334	11.6199998855591
92	69.68376913	59.32568468	69.97338241	0.171000003814697	0.109999999403954	0.140000000596046	50	89.07	99.06	86.0893433824926	16.7900009155273	21.7600002288818	12.039999961853
93	70.25363342	62.45973544	71.29451271	0.17399999499321	0.112999998033047	0.14300000667572	\N	91.8340148925781	99.7136611938477	89.4285277218657	\N	\N	\N
94	70.79082652	65.60982804	72.59513859	0.178000003099442	0.116999998688698	0.146999999880791	\N	93	99.7	90.9067723240737	21.9099998474121	24.7600002288818	19.2999992370605
95	71.21988497	68.76930002	73.87465491	0.379000008106232	0.28600001335144	0.331000000238419	\N	93	\N	\N	\N	\N	\N
96	95.89888739	93.83781676	\N	1.21000003814697	1.47000002861023	1.35000002384186	\N	93.0115737915039	99.4493408203125	89.1635606426257	\N	\N	\N
97	96.27914601	94.13753606	\N	1.12199997901917	1.30299997329712	1.22000002861023	\N	99.146201481454	99.6260098482606	98.8436328100157	\N	\N	\N
98	96.6510406	94.4425781	\N	1.06599998474121	1.27699995040894	1.17999994754791	\N	94.2364654541016	99.4823303222656	90.7465020142134	\N	\N	\N
99	97.01439615	94.75302481	\N	1.03999996185303	1.29999995231628	1.17999994754791	\N	94.8505630493164	99.5189971923828	91.5738082942638	\N	\N	\N
100	97.36888549	95.06909558	\N	0.875	1.01199996471405	0.949000000953674	100	98.96	99.01	98.9229784019544	18.1000003814697	18.8199996948242	17.5
101	97.7144676	95.39077552	84.70167328	0.620000004768372	0.620000004768372	0.620000004768372	\N	99.7	100	99.4656597389115	18.1399993896484	18.5300006866455	17.7999992370605
102	98.04012068	95.72517684	84.73123772	0.675999999046326	0.646000027656555	0.660000026226044	100	99.3592834472656	99.8181915283203	98.988369684072	14.4499998092651	15.3100004196167	13.710000038147
103	98.35799726	96.06462166	84.75746196	0.531000018119812	0.621999979019165	0.579999983310699	\N	99.1086235489221	99.4498197685449	98.8244028081014	15.8299999237061	14.8299999237061	16.9899997711182
104	98.67060441	96.40752741	84.78372605	0.238999992609024	0.25900000333786	0.25	100	99.4270629882813	99.8817291259766	99.0367347323226	16.7199993133545	17.6299991607666	15.9700002670288
105	98.97793277	96.75388237	84.81005803	0.564000010490417	0.593999981880188	0.579999983310699	\N	99.483642578125	99.7691497802734	99.2310356728785	15.9799995422363	16.7000007629395	15.3699998855591
106	99.25917058	97.10370657	84.83642515	0.611000001430511	0.591000020503998	0.600000023841858	100	99.6	99.7	99.5088173434328	17.9300003051758	18.5799999237061	17.3899993896484
107	99.44567029	97.45533132	84.86289749	0.712000012397766	0.671999990940094	0.689999997615814	\N	99.8521270751953	99.8476943969727	99.856292857105	17.1900005340576	17.6299991607666	16.8299999237061
108	99.76972457	97.79090683	84.88929973	0.841000020503998	0.820999979972839	0.829999983310699	100	99.9	99.9	99.9	16.8299999237061	17.0900001525879	16.6200008392334
109	99.84851617	98.12521791	84.91559635	0.748000025749207	0.787999987602234	0.769999980926514	\N	99.82	99.91	99.7301834152617	16.8299999237061	17.3600006103516	16.3999996185303
110	99.96483315	98.42052549	84.94168259	0.736000001430511	0.705999970436096	0.720000028610229	\N	99.9	99.9	99.9	17.2199993133545	17.6000003814697	16.8899993896484
111	100	98.71311912	84.96759329	1.08899998664856	1.10899996757507	1.10000002384186	\N	99.9	\N	\N	21.8099994659424	22.3600006103516	21.3600006103516
112	87.16428233	64.01580626	\N	36.4389991760254	23.5209999084473	29.1200008392334	\N	80.8	85.9780044555664	73.1814585878757	10.4200000762939	15.6199998855591	7.15999984741211
113	87.67812704	65.04813012	\N	35.8440017700195	22.5510005950928	28.3400001525879	\N	80.7	86.0884628295898	72.5913031195979	10.0699996948242	14.6099996566772	7.19000005722046
114	88.18248627	66.07165911	\N	33.0880012512207	21.4570007324219	26.5400009155273	\N	82	86.2152786254883	75.5122260328554	8.9399995803833	13.4099998474121	6.03999996185303
115	88.67766946	67.08632138	\N	25.8190002441406	19.7509994506836	22.4099998474121	\N	81.9	86.3540878295898	74.8880696960349	14.5900001525879	20.1200008392334	10.4200000762939
116	89.16270481	68.0912245	\N	25.5769996643066	21.9220008850098	23.5200004577637	60	82.6	86.5005187988281	76.3198436501129	15.8800001144409	21.2700004577637	11.7200002670288
117	89.63843841	69.08668367	\N	27.0200004577637	22.8740005493164	24.6800003051758	\N	82.9	86.6501922607422	76.7243090147065	14.7299995422363	20.2600002288818	10.5299997329712
118	90.10468946	70.07234949	\N	27.2360000610352	22.5979995727539	24.6399993896484	60	83.6	86.7987365722656	78.2142283162069	13.5699996948242	18.3999996185303	9.85999965667725
119	90.56175402	71.04814234	43.34615471	27.0939998626709	22.8780002593994	24.7299995422363	\N	85.3	86.9426422119141	82.4761070014308	15.0500001907349	20.3299999237061	11.0100002288818
120	91.00903337	72.01358167	43.47679019	26.5480003356934	22.9740009307861	24.5599994659424	60	85.2	87.0818405151367	81.8936436207879	15.3100004196167	20.4899997711182	11.25
121	91.44727967	72.96880358	43.60692689	27.0429992675781	23.1700000762939	24.8899993896484	\N	86	87.2171020507813	83.8146895540799	14.5299997329712	19.2999992370605	10.8199996948242
122	91.87634387	73.9135389	43.73631354	27.5480003356934	23.2240009307861	25.1499996185303	60	85.3	87.3492279052734	81.5229144900915	14.7700004577637	19.9899997711182	10.7200002670288
123	92.29629284	74.84761764	43.86494561	29.0130004882813	24.5580005645752	26.5400009155273	\N	84.2	87.4789962768555	78.0009938385937	14.9300003051758	20.2999992370605	10.789999961853
124	92.70702351	75.77086841	43.99257483	29.2830009460449	25.2199993133545	27.0400009155273	66	84.4	87.6071929931641	78.1753887219661	15.6899995803833	20.7000007629395	11.7799997329712
125	93.10863459	76.68318836	44.11920031	29.0709991455078	25.1480007171631	26.9099998474121	\N	84.7	87.7345962524414	78.658955126732	15.75	20.8600006103516	11.7399997711182
126	93.5012265	77.58447964	44.24482361	30.5139999389648	26.80299949646	28.4699993133545	\N	85	87.8618774414063	79.2272132822694	15.2200002670288	20.0100002288818	11.4499998092651
127	93.88505744	78.47461071	44.36969558	31.0359992980957	27.753999710083	29.2199993133545	\N	85	\N	\N	20.4799995422363	25.8299999237061	16.3199996948242
128	70.16310803	44.25558931	\N	4.74300003051758	4.32999992370605	4.53800010681152	\N	35.5729522705078	85.1774063110352	9.89366999236692	\N	\N	\N
129	69.63880335	43.63137284	\N	4.95499992370605	4.40100002288818	4.68100023269653	\N	37.2	91.4	9.37075879719893	\N	\N	\N
130	69.11454478	43.00931651	\N	5.1729998588562	4.47700023651123	4.8289999961853	\N	36.1982192993164	85.1723098754883	11.2569620317354	\N	\N	\N
131	68.58996496	42.3891721	\N	5.42899990081787	4.58799982070923	5.01399993896484	\N	36.5125122070313	85.1899337768555	11.9246964584432	\N	\N	\N
132	68.06548108	41.77119879	42.64874582	5.56500005722046	4.58599996566772	5.08300018310547	100	43.3690818728747	90.8619412200543	19.5748931125496	\N	\N	\N
133	67.54071095	41.1551677	42.61307711	5.75799989700317	4.6399998664856	5.20900011062622	\N	40.4581832885742	85.2436599731445	18.20354858217	\N	\N	\N
134	67.01607639	40.54131187	42.57760589	5.98799991607666	4.72800016403198	5.36999988555908	100	36.9	83.2	14.0800511921723	44.9099998474121	52.4500007629395	37.2999992370605
135	66.49118469	39.92942468	42.54212984	5.69500017166138	4.58500003814697	5.15299987792969	\N	44	85.2937393188477	23.8136172462348	\N	\N	\N
136	65.96647418	39.3197202	42.50685281	5.45100021362305	4.4850001335144	4.98199987411499	100	38.336353302002	85.3117446899414	15.5594355833177	\N	\N	\N
137	65.45410818	38.71708617	42.47745776	5.16599988937378	4.34800004959106	4.76999998092651	\N	32.3	83.4	7.69180816983564	61.2200012207031	70.120002746582	52.0699996948242
138	64.95492911	38.1206465	42.45413384	5.17700004577637	4.35200023651123	4.77799987792969	100	33.7	81.2	10.9493129842419	\N	\N	\N
139	64.46896436	37.52919272	42.4366939	5.19099998474121	4.35799980163574	4.78800010681152	\N	39.6762275695801	85.345344543457	17.8912529762655	\N	\N	\N
140	63.99662473	36.94167282	42.42512965	5.19199991226196	4.35300016403198	4.78499984741211	100	40.1442832946777	85.3523483276367	18.6373818161936	\N	\N	\N
141	63.53877337	36.35716003	42.41964219	5.20599985122681	4.3600001335144	4.7960000038147	\N	40.6163597106934	85.3585739135742	19.3583485197003	\N	\N	\N
142	63.09495688	35.77433736	42.41984006	5.2480001449585	4.39300012588501	4.83300018310547	\N	41.0891075134277	85.3646697998047	20.051849024487	41	48.3600006103516	35.3699989318848
143	62.66645761	35.19236284	42.42611114	5.79099988937378	4.8899998664856	5.35099983215332	\N	41.0891075134277	\N	\N	\N	\N	\N
\.


--
-- Name: country country_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.country
    ADD CONSTRAINT country_pkey PRIMARY KEY (country_key);


--
-- Name: education education_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.education
    ADD CONSTRAINT education_pkey PRIMARY KEY (education_key);


--
-- Name: event event_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.event
    ADD CONSTRAINT event_pkey PRIMARY KEY (event_key);


--
-- Name: health health_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.health
    ADD CONSTRAINT health_pkey PRIMARY KEY (health_key);


--
-- Name: month month_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.month
    ADD CONSTRAINT month_pkey PRIMARY KEY (month_key);


--
-- Name: population population_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.population
    ADD CONSTRAINT population_pkey PRIMARY KEY (population_key);


--
-- Name: quality_of_life quality_of_life_pkey; Type: CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.quality_of_life
    ADD CONSTRAINT quality_of_life_pkey PRIMARY KEY (quality_of_life_key);


--
-- Name: fact_table fk_country; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_country FOREIGN KEY (country_key) REFERENCES public.country(country_key);


--
-- Name: fact_table fk_education; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_education FOREIGN KEY (education_key) REFERENCES public.education(education_key);


--
-- Name: fact_table fk_event; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_event FOREIGN KEY (event_key) REFERENCES public.event(event_key);


--
-- Name: fact_table fk_health; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_health FOREIGN KEY (health_key) REFERENCES public.health(health_key);


--
-- Name: fact_table fk_month; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_month FOREIGN KEY (month_key) REFERENCES public.month(month_key);


--
-- Name: fact_table fk_population; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_population FOREIGN KEY (population_key) REFERENCES public.population(population_key);


--
-- Name: fact_table fk_quality_of_life; Type: FK CONSTRAINT; Schema: public; Owner: postgres
--

ALTER TABLE ONLY public.fact_table
    ADD CONSTRAINT fk_quality_of_life FOREIGN KEY (quality_of_life_key) REFERENCES public.quality_of_life(quality_of_life_key);


--
-- PostgreSQL database dump complete
--