Midlige_McCownSubmission#7
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…pygit add Exercise5c.py
lyy005
reviewed
Oct 5, 2017
| str = gender + ' ' + exp + '\n' | ||
| with open('new.txt', 'a') as n: | ||
| n.write(str) | ||
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Missing the unique and sorting part of the question.
data=pandas.read_csv("wages.csv")
genderYears=data.iloc[:,0:2]
unique_genderYears=genderYears.drop_duplicates()
sorted=unique_genderYears.sort_values(by=['gender', 'yearsExperience'])
sorted.to_csv('sortedUniqueWagesPython.txt',header=False,index=False,sep=' ')
-0.5
lyy005
reviewed
Oct 5, 2017
| print (cc.tail(n=1)) | ||
| print ("Top 10 Female Earners") | ||
| numoffemales=wages[wages['wage']>=wages['wage'].nlargest(10).iloc[-1]]['gender'].eq('female').sum() | ||
| print (numoffemales) |
lyy005
reviewed
Oct 5, 2017
| ed16=wages[wages.yearsSchool==16] #16 years of education | ||
| minimum16=min(ed16.wage) #minimum wage of 16 | ||
| print (minimum16-minimum12) | ||
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