Remove unwanted columns in a python dataframe

Question

I'm new to python/panda. This dataframe is part of a lab exercise.

Following is the dataframe. The result has 20 rows and 384 columns.

           country almond angelica anise anise_seed apple apple_brandy /
55620  Switzerland     No       No    No         No    No           No   
55621  Switzerland    Yes       No    No         No   Yes           No   
55622  Switzerland     No       No    No         No    No           No   
55623  Switzerland     No       No    No         No    No           No   
55624  Switzerland     No       No    No         No    No           No   
55625  Switzerland     No       No    No         No    No           No   
55626  Switzerland     No       No    No         No    No           No   
55627  Switzerland     No       No    No         No    No           No   
55628  Switzerland    Yes       No    No         No    No           No

I want to remove all the columns where value is 'No' and create a subset of this dataframe without these columns. From the above data set it means only columns 'almond' and 'apple' have a value other than 'No'. So the subset should look like,

           country almond apple 
55620  Switzerland     No    No
55621  Switzerland    Yes   Yes
55622  Switzerland     No    No
55623  Switzerland     No    No
55624  Switzerland     No    No
55625  Switzerland     No    No
55626  Switzerland     No    No
55627  Switzerland     No    No   
55628  Switzerland    Yes    No

Can you show us what you have tried so far?

CarlosSR
– CarlosSR

2020-05-11 11:04:58 +00:00
Commented May 11, 2020 at 11:04 — CarlosSR
– CarlosSR, Commented May 11, 2020 at 11:04

jezrael · Accepted Answer · 2020-05-11 10:00:49Z

3

First check by eq for equality and then test if at least one matched value in DataFrame.any:

df = df.loc[:, df.ne('No').any()]
print (df)
           country almond apple
55620  Switzerland     No    No
55621  Switzerland    Yes   Yes
55622  Switzerland     No    No
55623  Switzerland     No    No
55624  Switzerland     No    No
55625  Switzerland     No    No
55626  Switzerland     No    No
55627  Switzerland     No    No
55628  Switzerland    Yes    No

answered May 11, 2020 at 10:00

jezrael

868k103 gold badges1.4k silver badges1.3k bronze badges

Sign up to request clarification or add additional context in comments.

2 Comments

pradeept Over a year ago

Thanks, that worked! May I know where/how 'eq' was used here?

jezrael Over a year ago

@pradeept - Sure, it is better for easy chain by anoter functions and also better readable, because less ()

Collectives™ on Stack Overflow

Remove unwanted columns in a python dataframe

1 Answer 1

2 Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

2 Comments

Your Answer

Sign up or log in

Post as a guest

Related