How to delete all columns in DataFrame except certain ones?

Solution 1:

In [48]: df.drop(df.columns.difference(['a','b']), 1, inplace=True)
Out[48]:
   a  b
0  1  2
1  4  3
2  8  9

or:

In [55]: df = df.loc[:, df.columns.intersection(['a','b'])]

In [56]: df
Out[56]:
   a  b
0  1  2
1  4  3
2  8  9

PS please be aware that the most idiomatic Pandas way to do that was already proposed by @Wen:

df = df[['a','b']]

df = df.loc[:, ['a','b']]

Another option to add to the mix. I prefer this approach for readability.

df = df.filter(['a', 'b'])

Where the first positional argument is items=[]

You can also use a like argument or regex to filter.
Helpful if you have a set of columns like ['a_1','a_2','b_1','b_2']

You can do

df = df.filter(like='b_')

and end up with ['b_1','b_2']

Pandas documentation for filter.