Pandas DataFrame: Count the NaN values in one or more columns in DataFrame
Pandas: DataFrame Exercise-35 with Solution
Write a Pandas program to count the NaN values in one or more columns in DataFrame.
Sample data:
Original DataFrame
attempts name qualify score
0 1 Anastasia yes 12.5
1 3 Dima no 9.0
2 2 Katherine yes 16.5
3 3 James no NaN
4 2 Emily no 9.0
5 3 Michael yes 20.0
6 1 Matthew yes 14.5
7 1 Laura no NaN
8 2 Kevin no 8.0
9 1 Jonas yes 19.0
Number of NaN values in one or more columns:
2
Sample Solution :
Python Code :
import pandas as pd
import numpy as np
exam_data = {'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'score': [12.5, 9, 16.5, np.nan, 9, 20, 14.5, np.nan, 8, 19],
'attempts': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
'qualify': ['yes', 'no', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'no', 'yes']}
df = pd.DataFrame(exam_data)
print("Original DataFrame")
print(df)
print("\nNumber of NaN values in one or more columns:")
print(df.isnull().values.sum())
Sample Output:
Original DataFrame attempts name qualify score 0 1 Anastasia yes 12.5 1 3 Dima no 9.0 2 2 Katherine yes 16.5 3 3 James no NaN 4 2 Emily no 9.0 5 3 Michael yes 20.0 6 1 Matthew yes 14.5 7 1 Laura no NaN 8 2 Kevin no 8.0 9 1 Jonas yes 19.0 Number of NaN values in one or more columns: 2
Python-Pandas Code Editor:
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