Question

Exercise 3: Remove rows with missing data You need to use the dropna() method of a dataframe. More info here: https:/pandas pydata organdas docs/stable/generated pandas.DataFrame dropna.html Drop all rows that have missing data in any of the columns. Assign the resulting dataframe to the variable salaries_nonull Print the .count() summary of the datatrame to confirm that you've removed missing data (the counts should be the same for all columns) In [10): # Your code here Out[10]: rank discipline yrs.since.phd yrs.service 397 397 397 397 397 397 salary dtype: int64

Answer 1

##in question the dataset is not provided, so creating some

##random data

##In case of any issues please comment, i will definitely help you.

##please rate +ve :)

import numpy as np

import pandas as pd

##in question the original dataframe is not given,

##assuming salaries is the dataframe name

##below is dummy data set

data=[[1,'Maths',10,5,'M',20000],[2,'Maths',10,5,'M',1000],[1,np.nan,10,5,'M',20000],[1,'Maths',10,5,np.nan,20000]]

salaries = pd.DataFrame(data, columns=['rank','discipline','yrs.since.phd','yrs.service','sex','salaey'])

##below is the only code you require.

salaries_nonull=salaries.dropna()

salaries_nonull.count()

##below is the only code you require. salaries_nonull-salaries.dropna() salaries_nonull.count() rank discipline yrs.since.phd yrs. service sex salaey dtype: int64 2 2 2 2 2 2

Note: Just last two lines the answer for your question. i have done on dummy data as original data is not provided in the question