Having difficulty dropping multiple columns from a Pandas dataframe

Question

I have a newly created Pandas dataframe, which for some reason I can't drop the columns from.

RangeIndex: 2617 entries, 0 to 2616 Columns: 111 entries, access to zoning dtypes: object(111) memory usage: 2.2+ MB None

print list(df)

['access', 'age', 'attic', 'basement_type', 'bathrooms', 'bedrooms_total', 'buyer', 'buyer_city', 'buyer_country', 'buyer_postal_code', 'colisting_agent_id', 'construction', 'csa_number', 'date_expired_hidden', 'date_listed', 'date_sold', 'date_unconditional', 'distance_to_schools', 'distance_to_transportation', 'district', 'ensuites', 'exterior_features', 'exterior_finish', 'fireplace_types', 'fireplaces', 'flooring', 'fuel', 'heating', 'id', 'interior_features', 'internet_remarks']

df = df.drop(['buyer', 'buyer_city', 'buyer_country', 'colisting_agent_id'], axis=1, inplace=True)


print list(df)```



TypeErrorTraceback (most recent call last)
<ipython-input-63-1db0e7488634> in <module>()
      6 
      7 
----> 8 print list(df)

TypeError: 'NoneType' object is not iterable

Vishnudev Krishnadas · Accepted Answer · 2019-06-15 07:22:59Z

1

The inplace=True argument will drop at the source i.e. the dataframe itself and returns None.

So, when you use inplace=True then don't assign it back to df

Here the error is because the df variable is assigned to None and calling a list constructor on None will raise an error.

>>> df.drop(list_of_cols_to_drop, axis=1, inplace=True)

edited Jun 15, 2019 at 7:22

answered Jun 15, 2019 at 7:17

Vishnudev Krishnadas

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1 Comment

user4718221 Over a year ago

makes total sense! Thank you

Anton vBR · Accepted Answer · 2019-06-15 07:16:20Z

1

Either you should do:

df = df.drop(['buyer', 'buyer_city', 'buyer_country'], axis=1)

Or:

df.drop(['buyer', 'buyer_city', 'buyer_country'], axis=1, inplace=True)

answered Jun 15, 2019 at 7:16

Anton vBR

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