How to Subset a Pandas DataFrame Based on a List of Values?

Subsetting Pandas DataFrames Based on a List of Values

Selecting rows in a Pandas dataframe based on a specific value is straightforward using the equality operator. However, when dealing with multiple values, a more flexible approach is required. This article explains how to subset a dataframe using a list of values.

Problem:

Consider the following dataframe:

df = DataFrame({'A': [5,6,3,4], 'B': [1,2,3,5]})

df

     A   B
0    5   1
1    6   2
2    3   3
3    4   5

We want to select rows where column 'A' matches values in a given list, such as [3, 6]:

list_of_values = [3, 6]

y = df[df['A'] in list_of_values]

Solution:

The isin method of the dataframe provides a convenient way to achieve this:

df[df['A'].isin([3, 6])]

This returns the following rows:

     A    B
1    6    2
2    3    3

For the inverse selection, excluding rows with values in the given list, use the ~ operator:

df[~df['A'].isin([3, 6])]

This returns the remaining rows:

   A  B
0  5  1
3  4  5

Using the isin method, you can easily select or exclude rows based on a list of values, providing a more versatile solution for data extraction from Pandas dataframes.

The above is the detailed content of How to Subset a Pandas DataFrame Based on a List of Values?. For more information, please follow other related articles on the PHP Chinese website!