burton-doherty submission #8
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| ###Exercise 5-1### | ||
| import pandas as pd | ||
| wages=pd.read_table("wages.csv",",") | ||
| gen_years=wages.iloc[0:len(wages),0:2] | ||
| gen_years=gen_years.sort_values(by=['gender','yearsExperience'], ascending=[1,1]) | ||
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Owner
There was a problem hiding this comment. The question was asking to print out only the unique combinations. You can use drop_duplicates to only keep the unique combinations: -0.25 |
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| gen_years.to_csv('ex5_1.txt', header=True, index=False, sep=" ") | ||
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| ###Exercise 5-2### | ||
| import pandas as pd | ||
| wages=pd.read_table("wages.csv",",") | ||
| wage_low=wages.iloc[0:len(wages),[0,1,3]] | ||
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Owner
There was a problem hiding this comment. Or you can use: |
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| wage_low=wage_low.sort_values(by=['wage'], ascending=[1]) | ||
| print ("The lowest wage in both genders is:") | ||
| print (wage_low[:1]) | ||
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| wage_high=wages.iloc[0:len(wages),[0,1,3]] | ||
| wage_high=wage_high.sort_values(by=['wage'], ascending=[0]) | ||
| print ("The highest wage in both genders is:") | ||
| print (wage_high[:1]) | ||
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| wages_10=wage.high.iloc[0:10,0:2] | ||
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| Ftot=wages_10.gender.eq('female').sum() | ||
| print ("Number of Females in the Top 10 Wages:") | ||
| print (Ftot) | ||
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| ###Exercise 5-3### | ||
| import pandas as pd | ||
| wages=pd.read_table("wages.csv",",") | ||
| no_college=min(wages.wage[wages.yearsSchool==12]) | ||
| yes_college=min(wages.wage[wages.yearsSchool==16]) | ||
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| print("The minimum wage for non college grads is", no_college) | ||
| print("The minimum wage for college grads is", yes_college) | ||
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Or you can just use read_csv:
wages=pandas.read_csv("wages.csv")