What Is The Process For Deleting Rows From A Pandas DataFrame Using A Conditional Expression In Python?

To delete rows from a Pandas DataFrame based on a conditional expression, you can use the drop() method along with a boolean mask.

Here’s an example:

import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({'A': [1, 2, 3, 4, 5],
                   'B': [6, 7, 8, 9, 10]})

# Define the condition
condition = df['A'] > 2

# Use the boolean mask to drop rows
df = df.drop(df[condition].index)



   A  B
0  1  6
1  2  7

In this example, we create a DataFrame with two columns ‘A’ and ‘B’. We then define a condition using a Boolean expression df['A'] > 2. This condition returns True for rows where the value of column ‘A’ is greater than 2.

The drop() method is used with the index of the rows that match the condition (df[condition].index) to remove those rows from the DataFrame. Finally, the modified DataFrame is printed.

Note: The drop() method does not modify the original DataFrame. If you want to modify the DataFrame in-place, you can set the inplace parameter to True while calling the drop() method.

df.drop(df[condition].index, inplace=True)

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