Pandas Practice Set-1: Check the number of rows and columns and drop those row if 'any' values are missing in a row of diamonds DataFrame

Last update on May 03 2025 13:08:36 (UTC/GMT +8 hours)

41. Drop Rows with Any Missing Values and Check Shape

Write a Pandas program to check the number of rows and columns and drop those row if 'any' values are missing in a row of 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("Number of rows and columns:")
print(diamonds.shape)
print("After droping those rows where values are missing:")
print(diamonds.dropna(how='any').shape)

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
Number of rows and columns:
(53940, 10)
After droping those rows where values are missing:
(53940, 10)

For more Practice: Solve these Related Problems:

Write a Pandas program to drop rows that contain any missing values in the diamonds DataFrame and display the new shape.
Write a Pandas program to remove rows with any NaNs from the diamonds DataFrame and compare the row counts before and after.
Write a Pandas program to drop rows with missing data in any column and then reset the index of the cleaned DataFrame.
Write a Pandas program to drop rows with any missing values and output the number of rows removed.

Go to:

Previous: Write a Pandas program to count the number of missing values in each Series of diamonds DataFrame.
Next: Write a Pandas program to drop a row if any or all values in a row are missing of diamonds DataFrame on two specific columns.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.