How to Select Pandas DataFrame Rows Based on a List of Values?

Selecting Rows from a DataFrame Based on a List of Values in Pandas

This question addresses the challenge of subsetting rows from a Pandas dataframe based on a list of values.

Question:

Given the dataframe:

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

How can we select rows where the 'A' column values match elements in a list, such as:

list_of_values = [3, 6]

Answer:

To filter the dataframe based on a list of values, we can utilize the isin method:

y = df[df['A'].isin(list_of_values)]

Result:

   A  B
1  6  2
2  3  3

To exclude rows with values not present in the list, we can use the logical not operator (~) with isin:

z = df[~df['A'].isin(list_of_values)]

Result:

   A  B
0  5  1
3  4  5

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