Question

How to remove specific rows in python dataframe

Answer 1

To remove specific rows in a Python DataFrame, one can use the 'drop' method with the appropriate row indexes or boolean indexing to filter out rows based on conditions. After deletion, 'reset_index' can be used to reset the DataFrame's index, if needed.

Step-by-step explanation:

To remove specific rows in a Python DataFrame, typically done using the pandas library, you can use several methods, depending on the criteria of the rows you want to remove. If you know the index of the rows you wish to delete, you can use the drop method. Alternatively, if you want to remove rows based on a condition, you can use boolean indexing.

Here's an example of using the drop method:

import pandas as pd
# Assuming df is your DataFrame
# To drop rows with index 1 and 3
new_df = df.drop([1, 3], axis=0)

If you want to remove rows where a specific column meets a condition:

# Assuming you want to remove rows where the 'age' column is less than 18
new_df = df[df['age'] >= 18]

After removing specific rows, you can reset the index of the DataFrame using reset_index, if necessary:

# To reset the index and drop the old index column
new_df = new_df.reset_index(drop=True)