How do I calculate the sum of specific columns across rows in a Pandas DataFrame?

Computing Sum of Rows in a DataFrame for Specific Columns

To address your DataFrame, where you aim to add a column 'e' representing the sum of columns 'a', 'b', and 'd', the appropriate operation using the specified columns and DataFrame is as follows:

df['e'] = df[['a', 'b', 'd']].sum(axis=1, numeric_only=True)

Here, sum(axis=1) computes the sum along each row, effectively adding the values in columns 'a', 'b', and 'd' for each row. The numeric_only=True parameter ensures that only numeric columns are considered, ignoring non-numeric ones like 'c'.

Alternative Approach: Excluding Specific Columns

If you wish to exclude columns from the sum, you can create a list of the desired columns and exclude unwanted ones:

col_list = list(df)
col_list.remove('d')
df['e'] = df[col_list].sum(axis=1)

This approach allows you to select the specific columns for the calculation.

Additional Notes:

• The provided code requires Pandas version 2.0 to function correctly.
• The sum method can also be used to compute the sum of entire columns, not just rows.
• Refer to the Pandas documentation for more details on the sum method: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sum.html

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