How to Understand and Handle Pandas' SettingWithCopyWarning?

SettingWithCopyWarning: Explanation and Handling in Pandas

The SettingWithCopyWarning, introduced in Pandas 0.13.0rc1, alerts users to potential issues when setting values on slices or copies of DataFrames. This warning aims to prevent confusion and unexpected behavior.

Understanding the Warning

The warning arises due to "chained assignments," where a value is set on a slice or copy of a DataFrame, such as:

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

In this example, the first selection (df[df['A'] > 2]) returns a copy, and attempting to set 'B' on this copy won't update the original DataFrame 'df'. To correctly update 'df', use the loc accessor:

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

Handling the Warning

1. Ignoring the Warning

If you are certain that you don't need the changes to be reflected back to the original DataFrame, you can disable the warning:

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

2. Using loc and iloc

For assignments on slices or copies, use the loc or iloc accessors, which allow direct modification of the original DataFrame:

df.loc[df['A'] > 2, 'B'] = new_val
df.iloc[2:5, 4] = [1, 8, 8]

3. Creating a copy

If you need a new reference for your DataFrame, create a copy using DataFrame.copy() before modifying it:

new_df = df.copy()
new_df['C'] = df['A'] + df['B']

4. Regenerating the DataFrame

In your specific case, instead of modifying the original quote_df, you could regenerate a new DataFrame with the desired changes:

quote_df = pd.read_csv(StringIO(str_of_all), sep=',', names=list('ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefg'))
quote_df.rename(columns={'A':'STK', 'B':'TOpen', ...}, inplace=True)
quote_df['TVol'] = quote_df['TVol'] / TVOL_SCALE
quote_df['TAmt'] = quote_df['TAmt'] / TAMT_SCALE
quote_df['TDate'] = quote_df.TDate.map(lambda x: x[0:4]+x[5:7]+x[8:10])

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