How to slice a dataframe with specific column names + range of columns?

Question

Given any pandas dataframe. I want to select columns A, B and F:Z

I have tried to do it df.loc[:, ['A','B','F':'Z']] but it didn't work. Please advise how to do this.

score 4 · Accepted Answer · answered Jan 28 '21 at 18:52

4

We can do two slice then combine

df.loc[:, ['A','B']].join(df.loc[:,'F':'Z'])

And side solution change all name to position then we can do

df.iloc[:,np.r_[1,2,5:999]]

answered Jan 28 '21 at 18:52

BENY

Thanks! Please advise if it's possible to do it with `df.columns not in ['C', 'D', 'E']` in some way? – SteveS Jan 28 '21 at 18:56
1

@SteveS `out = df.drop(['C','D','E'],axis=1)` – BENY Jan 28 '21 at 19:03
The `df[df.columns.difference(['C', 'D', 'E'])]` is also an option – SteveS Jan 28 '21 at 19:08
https://stackoverflow.com/questions/14940743/selecting-excluding-sets-of-columns-in-pandas – SteveS Jan 28 '21 at 19:08

1 Answers1