Get count of missing values of column in Pandas python

Get count of missing values of column in pandas python.  Let’s see how to

  • Get number of missing values of each column in pandas python
  • Get number of missing values of single column in pandas python.

First let’s create a dataframe.

import pandas as pd
import numpy as np

#Create a DataFrame
df1 = {
    'Name':['George','Andrea','micheal','maggie','Ravi','Xien','Jalpa',np.nan],
    'State':['Arizona','Georgia','Newyork','Indiana','Florida','California',np.nan,np.nan],
    'Gender':["M","F","M","F","M","M",np.nan,np.nan],      
    'Score':[63,48,56,75,np.nan,77,np.nan,np.nan]
    
   }

df1 = pd.DataFrame(df1,columns=['Name','State','Gender','Score'])
print(df1)

df1 will be

Get count of missing values in each columns pandas python 1

 

Get count of missing values of each columns in pandas python:

Count of missing value of each column in pandas is created by using isnull().sum() function as shown below.

df1.isnull().sum()

So the count of missing values will be

Get count of missing values in each columns pandas python 2

 

Get count of missing values of single column in pandas python:

Number of missing values of “Score” column in pandas is identified as shown below

df1.Score.isnull().sum()

So the number of missing values of Score column is

3

 

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