w3resource

Pandas Practice Set-1: Drop a row if any or all values in a row are missing of diamonds DataFrame on two specific columns

Pandas Practice Set-1: Exercise-42 with Solution

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..

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("\nAfter droping those rows where any value in a row is missing in carat and cut columns:")
print(diamonds.dropna(subset=['carat', 'cut'], how='any').shape)
print("\nAfter droping those rows where all values in a row are missing in carat and cut columns:")
print(diamonds.dropna(subset=['carat', 'cut'], how='all').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

After droping those rows where any value in a row is missing in carat and cut columns:
(53940, 10)

After droping those rows where all values in a row are missing in carat and cut columns:
(53940, 10)

Python Code Editor:

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

Previous: 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.
Next: Write a Pandas program to set an existing column as the index of diamonds DataFrame.

What is the difficulty level of this exercise?



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://198.211.115.131/python-exercises/pandas/practice-set1/pandas-practice-set1-exercise-42.php