CODEWITHSUNDEEP
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TylerNG
TylerNG

Reputation: 941

Dropping column names that doesn't contain number

I have a df with the following column names:

Name, Id, xyz,..., ijk, 1, 2, 3, val1, val2,...

I want to drop all the columns whose name doesn't contain number and only keep Name and Id. Is there an efficient way to do this?

The result would be: Name, Id, 1, 2, 3, val1, val2,...

Thanks!

Upvotes: 2

Views: 90

Answers (2)

Tai
Tai

Reputation: 7994

With str.match based on MaxU's answer. 

new_columns = df.columns[df.columns.astype(str).str.match("(.*\d.*)|Id|Name")]
df[new_columns]

Upvotes: 3

MaxU - stand with Ukraine
MaxU - stand with Ukraine

Reputation: 210832

IIUC:

df = df.loc[:, df.columns.astype(str).str.contains('\d') | df.columns.isin(['Name','Id'])]

Demo:

In [224]: df
Out[224]:
   Name  Id  xyz  ijk  1  2  3  val1  val2
0     1   2    3    4  5  6  7     8     9

In [225]: df = df.loc[:, df.columns.astype(str).str.contains('\d') | df.columns.isin(['Name','Id'])]

In [226]: df
Out[226]:
   Name  Id  1  2  3  val1  val2
0     1   2  5  6  7     8     9

Upvotes: 4

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