Pandas: Find integer index of rows with missing data in pandas dataframe
Pandas Indexing: Exercise-24 with Solution
Write a Pandas program to find integer index of rows with missing data in a given dataframe.
Sample Solution:
Python Code :
import pandas as pd
import numpy as np
df = pd.DataFrame({
'school_code': ['s001','s002','s003','s001','s002','s004'],
'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'],
'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'],
'date_of_birth': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'],
'weight': [35, None, 33, 30, 31, None]},
index = ['t1', 't2', 't3', 't4', 't5', 't6'])
print("Original DataFrame:")
print(df)
index = df['weight'].index[df['weight'].apply(np.isnan)]
df_index = df.index.values.tolist()
print("\nInteger index of rows with missing data in 'weight' column of the said dataframe:")
print([df_index.index(i) for i in index])
Sample Output:
Original DataFrame: school_code class name date_of_birth weight t1 s001 V Alberto Franco 15/05/2002 35.0 t2 s002 V Gino Mcneill 17/05/2002 NaN t3 s003 VI Ryan Parkes 16/02/1999 33.0 t4 s001 VI Eesha Hinton 25/09/1998 30.0 t5 s002 V Gino Mcneill 11/05/2002 31.0 t6 s004 VI David Parkes 15/09/1997 NaN Integer index of rows with missing data in 'weight' column of the said dataframe: [1, 5]
Python Code Editor:
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