Get the absolute values in Pandas

Get the absolute values in Pandas

In Pandas, you can get the absolute values of numerical data within a DataFrame or Series using the abs() method. This method is straightforward to use and is applied element-wise to each value in the DataFrame or Series, converting all negative values to their positive counterparts.

Here's a simple example of how to use it:

import pandas as pd # Create a DataFrame with some negative values df = pd.DataFrame({ 'A': [1, -2, 3, -4], 'B': [-5, 6, -7, 8], 'C': [9, -10, 11, -12] }) # Apply the abs() method to get the absolute values df_absolute = df.abs() print(df_absolute)

This will output a DataFrame where all the values are the absolute values from the original df:

 A B C 0 1 5 9 1 2 6 10 2 3 7 11 3 4 8 12

If you want to get the absolute values of a single Series (a single column in a DataFrame), you do it like this:

# Get the absolute values for column 'A' only df['A'] = df['A'].abs() print(df)

This will modify only column 'A' in df to contain absolute values:

 A B C 0 1 -5 9 1 2 6 -10 2 3 -7 11 3 4 8 -12

Use the abs() method whenever you need to ensure that all numbers in a DataFrame or Series are non-negative, which is a common requirement in many data analysis tasks.

More Tags

remote-debugging pdf icons android-radiogroup nslayoutconstraint pg uniqueidentifier multibranch-pipeline job-control visual-studio-code

More Programming Guides

Other Guides

More Programming Examples