How can I replace values in a specific Pandas DataFrame column based on a condition?

Barbara Streisand
Release: 2024-10-31 12:26:25
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How can I replace values in a specific Pandas DataFrame column based on a condition?

Pandas DataFrame: Replace Specific Column Values Based on Condition

In a DataFrame, it's often necessary to replace specific values within a column based on a predefined condition. Consider the following DataFrame:

                 Team  First Season  Total Games
0      Dallas Cowboys          1960          894
1       Chicago Bears          1920         1357
2   Green Bay Packers          1921         1339
3      Miami Dolphins          1966          792
4    Baltimore Ravens          1996          326
5  San Franciso 49ers          1950         1003
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Suppose we need to replace all values greater than 1990 in the 'First Season' column with 1. To achieve this, the following command can be utilized:

df.loc[df['First Season'] > 1990, 'First Season'] = 1
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This line selectively targets the 'First Season' column based on the condition specified in the square brackets (df['First Season'] > 1990). The = sign assigns the value 1 to the selected elements, ensuring that only the 'First Season' column is affected.

The resulting DataFrame will appear as follows:

                 Team  First Season  Total Games
0      Dallas Cowboys          1960          894
1       Chicago Bears          1920         1357
2   Green Bay Packers          1921         1339
3      Miami Dolphins          1966          792
4    Baltimore Ravens             1          326
5  San Franciso 49ers          1950         1003
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It's important to note that the syntax for this operation involves two key components:

  • df.loc[, ]: This selects the rows and columns specified by the boolean mask.
  • = : This assigns the specified value to the selected column(s).

Furthermore, if the goal is to create a boolean indicator instead of replacing values, the condition can be used to generate a boolean Series, which can then be converted to integers by casting its dtype to int. This will transform True and False values into 1 and 0, respectively.

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