diff --git a/AEY_Part1.py b/AEY_Part1.py
new file mode 100755
index 0000000..2715f63
--- /dev/null
+++ b/AEY_Part1.py
@@ -0,0 +1,26 @@
+import pandas
+
+wages = pandas.read_csv("wages.csv")
+
+gender_Experience=wages[["gender","yearsExperience"]]
+
+ordered_gender_Experience=gender_Experience.sort(['gender','yearsExperience'], ascending=[True,True])
+
+unique_combos=ordered_gender_Experience.drop_duplicates()
+
+print("Unique combinations of gender/years experience:", unique_combos)
+
+wages_highschool = wages[wages.yearsSchool == 12]
+
+wages_college = wages[wages.yearsSchool == 16]
+
+ordered_wages_HS = wages_highschool.sort(columns='wage', ascending=True)
+
+ordered_wages_C = wages_college.sort(columns='wage', ascending=True)
+
+minWage_HS = ordered_wages_HS.iloc[0,3]
+
+minWage_C = ordered_wages_C.iloc[0,3]
+
+print("Effect of graduating college on minimum wage:", minWage_C - minWage_HS)
+
diff --git a/Exercise5_AEY_JC.py b/Exercise5_AEY_JC.py
new file mode 100755
index 0000000..099a89e
--- /dev/null
+++ b/Exercise5_AEY_JC.py
@@ -0,0 +1,59 @@
+import pandas
+print("Question1")
+#Question 1 Part 1
+wages=pandas.read_csv("wages.csv",header=0,sep=",")
+reduced=wages[['gender', 'yearsExperience']]
+sorted1=reduced.sort_values(['gender', 'yearsExperience'], ascending=[True, False])
+done=sorted1.drop_duplicates()
+print(done)
+
+#Question 1 Part 2
+wages = pandas.read_csv("wages.csv")
+gender_Experience=wages[["gender","yearsExperience"]]
+ordered_gender_Experience=gender_Experience.sort(['gender','yearsExperience'], ascending=[True,True])
+unique_combos=ordered_gender_Experience.drop_duplicates()
+print("Unique combinations of gender/years experience:", unique_combos)
+
+print("Question2")
+# Question 2 part 1
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.drop('yearsSchool', axis=1, inplace=True)
+sorted2=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+part1=duplicates.tail(1)
+print("Highest earner", part1)
+
+# Question 2 part 2
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.drop('yearsSchool', axis=1, inplace=True)
+sorted2=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+part2=duplicates.head(1)
+print("Lowest earner", part2)
+
+# Question 2 part 3
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+top10=duplicates.tail(10)
+top10.to_csv("top10.csv")
+total = 0
+with open('top10.csv') as f:
+    for line in f:
+        finded = line.find('female')
+        if finded != -1 and finded != 0:
+            total += 1
+print("Number of women in the top 10 earners", total)
+
+print("Question3")
+#Question 3
+wages_highschool = wages[wages.yearsSchool == 12]
+wages_college = wages[wages.yearsSchool == 16]
+ordered_wages_HS = wages_highschool.sort(columns='wage', ascending=True)
+ordered_wages_C = wages_college.sort(columns='wage', ascending=True)
+minWage_HS = ordered_wages_HS.iloc[0,3]
+minWage_C= ordered_wages_C.iloc[0,3]
+print("Effect of graduating college on minimum wage:", minWage_C - minWage_HS)
diff --git a/earnings.py b/earnings.py
new file mode 100755
index 0000000..1ec30cc
--- /dev/null
+++ b/earnings.py
@@ -0,0 +1,25 @@
+import pandas
+
+#Part 1
+wages=pandas.read_csv("wages.csv",header=0,sep=",")
+reduced=wages[['gender', 'yearsExperience']]
+sorted1=reduced.sort_values(['gender', 'yearsExperience'], ascending=[True, False])
+done=sorted1.drop_duplicates()
+print(done)
+
+#Part 2
+wages = pandas.read_csv("wages.csv")
+gender_Experience=wages[["gender","yearsExperience"]]
+ordered_gender_Experience=gender_Experience.sort(['gender','yearsExperience'], ascending=[True,True])
+unique_combos=ordered_gender_Experience.drop_duplicates()
+print("Unique combinations of gender/years experience:", unique_combos)
+
+#Part 3
+wages_highschool = wages[wages.yearsSchool == 12]
+wages_college = wages[wages.yearsSchool == 16]
+ordered_wages_HS = wages_highschool.sort(columns='wage', ascending=True)
+ordered_wages_C = wages_college.sort(columns='wage', ascending=True)
+minWage_HS = ordered_wages_HS.iloc[0,3]
+minWage_C = ordered_wages_C.iloc[0,3]
+print("Effect of graduating college on minimum wage:", minWage_C - minWage_HS)
+
diff --git a/q2part1.py b/q2part1.py
new file mode 100755
index 0000000..b1eaa95
--- /dev/null
+++ b/q2part1.py
@@ -0,0 +1,8 @@
+print("Highest earner")
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.drop('yearsSchool', axis=1, inplace=True)
+sorted2=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+duplicates.tail(1)
+
diff --git a/question1.py b/question1.py
new file mode 100755
index 0000000..428117c
--- /dev/null
+++ b/question1.py
@@ -0,0 +1,10 @@
+#import pandas. read the csv. read the two columns. sort by both columns in order. drop duplicates. print.
+import pandas
+wages=pandas.read_csv("wages.csv",header=0,sep=",")
+reduced=wages[['gender', 'yearsExperience']]
+sorted1=reduced.sort_values(['gender', 'yearsExperience'], ascending=[True, False])
+done=sorted1.drop_duplicates()
+print(done)
+
+
+
diff --git a/question2.py b/question2.py
new file mode 100755
index 0000000..87f6cc8
--- /dev/null
+++ b/question2.py
@@ -0,0 +1,33 @@
+# Question 2 part 1
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.drop('yearsSchool', axis=1, inplace=True)
+sorted2=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+part1=duplicates.tail(1)
+print("Highest earner", part1)
+
+# Question 2 part 2
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.drop('yearsSchool', axis=1, inplace=True)
+sorted2=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+part2=duplicates.head(1)
+print("Lowest earner", part2)
+
+# Question 2 part 3
+import pandas
+ex5data=pandas.read_csv("wages.csv")
+sorted1=ex5data.sort_values("wage")
+duplicates=sorted2.drop_duplicates("wage")
+top10=duplicates.tail(10)
+top10.to_csv("top10.csv")
+total = 0
+with open('top10.csv') as f:
+    for line in f:
+        finded = line.find('female')
+        if finded != -1 and finded != 0:
+            total += 1
+print("Number of women in the top 10 earners", total)
+