fix settingwithcopywarning

How to Fix SettingWithCopyWarning in Pandas

Python Pandas is a popular python library that allows you to easily work with data and files. Sometimes, while using pandas, you may get SettingWithCopyWarning message. In this article, we will learn how to fix this problem.


What is SettingWithCopyWarning?

When you filter a dataframe, you can slice it to get a view or copy, depending on its layout and other factors. A view is a view into original data, so if you modify the view it may modify the original object. On the other hand, a copy as the name suggests is a copy, and modifying it does not affect the original data. The SettingWithCopyWarning error appears in case of chained assignments because the interpreter is unable to predict if the filtered dataframe will return a copy or view, and so it does not know if it will have to assign values back to original data or not.


How to Fix SettingWithCopyWarning in Pandas

This warning was created to flag confusing chained assignments such as the one shown below, which does not always work as expected. For example, if the first selection returns a copy, then you will get SettingWithCopyWarning.

df[df['A'] > 2]['B'] = new_val  # new_val not set in df

In fact, it will also offer a suggestion to rewrite as follows.

df.loc[df['A'] > 2, 'B'] = new_val

You can either fix your existing command as per the suggestion offered by your python interpreter, or completely disable it using the following command.

import pandas as pd
pd.options.mode.chained_assignment = None  # default='warn'

In this article, we have learnt how to fix SettingWithCopyWarning messages in Python pandas.

Also read:

How to Get Row Count of Pandas DataFrame
How to Merge DataFrames in Pandas Based on Columns
How to Change Default Display Manager in Ubuntu
How to Fix “Please Install All Available Updates”
How to Change Login Screen Background in Ubuntu

Leave a Reply

Your email address will not be published.