Pandas Practice Set-1: Create a DataFrame of booleans from diamonds DataFrame

Last update on September 13 2025 12:47:03 (UTC/GMT +8 hours)

39. Create a Boolean DataFrame Indicating Missing Values

Write a Pandas program to create a DataFrame of booleans (True if missing, False if not missing) from diamonds DataFrame.

Sample Solution:

Python Code:

import pandas as pd
diamonds = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/diamonds.csv')
print("Original Dataframe:")
print(diamonds.head())
print("\nDataFrame of booleans:")
print(diamonds.isnull().head(20))

Sample Output:

Original Dataframe:
   carat      cut color clarity  depth  table  price     x     y     z
0   0.23    Ideal     E     SI2   61.5   55.0    326  3.95  3.98  2.43
1   0.21  Premium     E     SI1   59.8   61.0    326  3.89  3.84  2.31
2   0.23     Good     E     VS1   56.9   65.0    327  4.05  4.07  2.31
3   0.29  Premium     I     VS2   62.4   58.0    334  4.20  4.23  2.63
4   0.31     Good     J     SI2   63.3   58.0    335  4.34  4.35  2.75

DataFrame of booleans:
    carat    cut  color  clarity  ...    price      x      y      z
0   False  False  False    False  ...    False  False  False  False
1   False  False  False    False  ...    False  False  False  False
2   False  False  False    False  ...    False  False  False  False
3   False  False  False    False  ...    False  False  False  False
4   False  False  False    False  ...    False  False  False  False
5   False  False  False    False  ...    False  False  False  False
6   False  False  False    False  ...    False  False  False  False
7   False  False  False    False  ...    False  False  False  False
8   False  False  False    False  ...    False  False  False  False
9   False  False  False    False  ...    False  False  False  False
10  False  False  False    False  ...    False  False  False  False
11  False  False  False    False  ...    False  False  False  False
12  False  False  False    False  ...    False  False  False  False
13  False  False  False    False  ...    False  False  False  False
14  False  False  False    False  ...    False  False  False  False
15  False  False  False    False  ...    False  False  False  False
16  False  False  False    False  ...    False  False  False  False
17  False  False  False    False  ...    False  False  False  False
18  False  False  False    False  ...    False  False  False  False
19  False  False  False    False  ...    False  False  False  False

[20 rows x 10 columns]

For more Practice: Solve these Related Problems:

Write a Pandas program to generate a DataFrame of booleans where True indicates missing values in the diamonds DataFrame.
Write a Pandas program to create and display a boolean mask of missing values for all columns in the diamonds DataFrame.
Write a Pandas program to convert the diamonds DataFrame into a boolean DataFrame indicating non-missing (True) and missing (False) values.
Write a Pandas program to create a boolean DataFrame that flags missing entries and then count the total number of missing values per row.

Go to:

PREV : Create a Bar Plot of 'value_counts' for 'cut' Series.
NEXT : Count Missing Values in Each Series.

Python Code Editor:

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