How Can I Effectively Handle Pandas' SettingWithCopyWarning?

Handling SettingWithCopyWarning in Pandas

While upgrading Pandas from 0.11 to 0.13.0rc1, users may encounter numerous SettingWithCopyWarning messages. One such example is:

E:\FinReporter\FM_EXT.py:449: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_index,col_indexer] = value instead
quote_df['TVol']   = quote_df['TVol']/TVOL_SCALE

Understanding the Warning

The SettingWithCopyWarning flags potentially confusing "chained" assignments like:

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

This doesn't always work as expected, especially when the first selection returns a copy. To resolve this issue, use:

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

Addressing the Warning in the Provided Code

In the provided code snippet:

quote_df['TVol']   = quote_df['TVol']/TVOL_SCALE

you're effectively performing a chained assignment equivalent to:

quote_df = quote_df[quote_df['A'] > 2]
quote_df['TVol'] = new_val

This pattern cannot be distinguished from the negative example and triggers the warning.

Disabling the Warning

If you're confident that the writes won't affect the original frame, disable the warning with:

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

Additional Information

For further understanding, refer to these resources:

• Pandas User Guide: Indexing and selecting data
• Python Data Science Handbook: Data Indexing and Selection
• Real Python: SettingWithCopyWarning in Pandas
• Dataquest: SettingwithCopyWarning: How to Fix This Warning in Pandas
• Towards Data Science: Explaining the SettingWithCopyWarning in pandas

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