Pandas implements data row filtering for specified columns containing missing values

Pandas implements data row filtering for specified columns containing missing values

When we need to analyze a piece of data, we often need to clean the data. An important part of data cleaning is to delete or fill in missing values. In pandas, we can use the dropna() method to delete data rows containing missing values, or use the fillna() method to fill missing values. However, in some cases, we need to find all the rows that contain missing values ​​in the specified data column. This article will introduce how to use pandas to achieve this requirement.

First, we create a DataFrame with missing values:

import pandas as pd
import numpy as np

df = pd.DataFrame({
   
    
    'A': [1, 2, np