You could provide a list of columns to be dropped and return back the dataframe with only the columns needed using the drop() function on a pandas dataframe.

Just saying colsToDrop = ['a']
df.drop(colsToDrop, axis=1)

would return a dataframe with just the columns b and c.

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop.html

You could provide a list of columns to be dropped and return back the DataFrame with only the columns needed using the drop() function on a Pandas DataFrame.

Just saying

colsToDrop = ['a']
df.drop(colsToDrop, axis=1)

would return a DataFrame with just the columns b and c.

The drop method is documented here.