CODEWITHSUNDEEP
pythonpandas
valid
valid

Reputation: 63

copy multiple columns with same name but different number into new df in python/pandas

I've got a huge dataframe physioDf and want to copy some of the columns into a different df called smallPysioDf. I know, that I can copy individual columns like this:

smallPhysioDf['column_name'] = physioDf['column_name'].values

But I now want to copy 30 columns belonging to the same Variable. Each column names starts the same (e.g. "VariableName_") but end with a specific number from 1 to 30. What would be the fastest way to copy all of those columns into smallPhysioDf? I believe I would have to use a for loop but I am not sure how. Very happy for any help.

Upvotes: 0

Views: 783

Answers (2)

Toby Petty
Toby Petty

Reputation: 4680

It will be quickest to select all columns at once:

columns = [f"VariableName_{i}" for i in range(1, 31, 1)]
smallPhysioDf = physioDf[columns].copy()

If smallPhysioDf already exists you can instead append (if the VariableName columns are already in the DataFrame), or merge (if the VariableName columns are new).

Upvotes: 1

Quang Hoang
Quang Hoang

Reputation: 150785

You can use filter to extract the column names:

for c in physioDf.filter(regex='^VariableName_').columns:
      smallPhysioDf[c] = physioDf[c]

Or you can use f-string:

for n in range(1,31):
    col_name = f'VariableName_{n}'
    smallPhysioDf[col_name] = physioDf[col_name]

Upvotes: 0

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