# question 3 30 points data analysis of a field study john has done a field study and 4944881

Question 3 (30 points): data Analysis of a field study John has done a field study and the result is saved inEmployment.csv file. The stufy is about employment and type of employment of each graduated students from college in differentmajors. He needs some help with data analysis Question 3.a (3 points): Help John to read the file using Pandas In [272]: df
= pd.”?”(‘Employment.csv’)
# the function in pd to read .csv files Question 3.b (5 points): Help him to find the null values and put them 0 wherever thereis a null value In [ ]: Result
= df.’?&#39;(0)
# put the proper function ? Question 3.c (3 points): John does not know the total number of participants, but he hasthe data of male and female participants Generate a new column that shows total number of participants inthe field study based on each major. The name of the coloum is total. In [269]: df[‘total’]
= df[‘?’]
+ df[‘?’]
# select the columns? Question 3.d (5 points): He wants to have % of female participants for each major Generate another new column that shows % of the female studentsparticipant in the feild study based on each major. The name of the coloum is WomenShare In [268]: df[‘WomenShare’]
= df[‘?’]
/df[‘?’]
# select the columns? Questions 3.e: (3 points). Find the number of students that do not have college_jobs ineach major. Show the result as a new column ‘non_college_jobs’ In [ ]: df[‘non_college_jobs’]
= df[‘?’]
df[‘?’]
# select the columns Questions 3.f: (8 points). Find the % of the unemployed students in each major. In [270]: df[‘unemployedRate’]
= 100
*(df[‘?’]
df[‘?’])
/(df[‘?’])
# select the columns? Question 3.g (3 points): Save all result in a csv file called FinalResult.csv In [ ]: df.’?&#39;(‘YesToPython.csv’)
# function used to save the data in .csv format Question 3.h (Extra credit: 2 points) Find total of students based on major_category and show them ina pie chart Check the last part of the HW4 In [264]: Result
= df.groupby(df[‘major_category’])[‘total’].’?&#39;()
# We are looking for total of students. In [267]:
import pygalpiec
= ‘?&#39;()
for var
in list(‘?’):
# the missing value is index of the Result piec.add(str(var),’?’)
# the missing item is value associted to var in the Series Valuepiec.render_to_file(‘Majors.svg’) . . .