Why Doesn't `del df.column_name` Work for Deleting Pandas DataFrame Columns?

Deleting Columns from Pandas DataFrames: del vs. drop()

In Pandas, deleting columns from a DataFrame can seem straightforward. However, why doesn't the syntax del df.column_name work as anticipated?

While it's possible to access Series via df.column_name, attempting to delete the column using del df.column_name fails. The proper method for column deletion is through the drop() function.

To delete a column using drop(), specify the column name and set the axis argument to 1 (for columns). Alternatively, use the columns keyword to specify the columns to be dropped. For example:

df = df.drop('column_name', axis=1)  # Old syntax
df = df.drop(columns='column_name')  # New syntax

To perform column deletion without reassigning the DataFrame, use inplace=True as follows:

df.drop('column_name', axis=1, inplace=True)

Additionally, columns can be dropped by number using the axis=1 argument and indexing the df.columns object. To drop columns 1, 2, and 4 (zero-based indexing), do the following:

df.columns[[0, 1, 3]]  # Select columns to drop
df = df.drop(df.columns[[0, 1, 3]], axis=1)

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