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I'm trying to figure out the fastest way to drop columns in df using a list of column names. this is a fancy feature reduction technique. This is what I am using now, and it is taking forever. Any suggestions are highly appreciated.
important2=(important[:-(len(important)-500)])
for i in important:
if i in important2:
pass
else:
df_reduced.drop(i, axis=1, inplace=True)
df_reduced.head()
464
We can use Pandas drop() function to drop multiple columns from a dataframe. Pandas drop() is versatile and it can be used to drop rows of a dataframe as well. To use Pandas drop() function to drop columns, we provide the multiple columns that need to be dropped as a list.
You can drop columns by index by using DataFrame. drop() method and by using DataFrame. iloc[]. columns property to get the column names by index.
use a list containing the columns to be dropped:
good_bye_list = ['column_1', 'column_2', 'column_3']
df_reduced.drop(good_bye_list, axis=1, inplace=True)
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