efficient way to subset and rename data.frame columns together in Python

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In R data.table you can subset and rename columns at the same time. You can also select a column multiple times and rename it at the time of selection. Extremely fast and convenient. Can you do the same thing in Python? So far, all i have been able to do is separately selecting and renaming columns. It's really a pain for such a simple operation!

For example, my data.table DT has four columns A, B, C, D. in R you can:

subset_DT = DT[,.(A, B, second_A = A, rename_D = D)]

This subsets columns A, B, A, D and at the same time renames the second A and D columns to second_A and rename_D columns. So that subset_DT would have four columns; A, B, second_A, rename_D.

how can I do this neatly (in one straight forward operation) in Python pandas without separating the subset and renaming operations?

pandas python
2 Answers

try the following code:

df=df.rename(columns = {'second_A':'A','rename_D':'D'})
user_27721180

You can use assign:

df = pd.DataFrame([list('abcd')], columns=list('ABCD'))
#   A  B  C  D
#0  a  b  c  d

df[['A','B']].assign(second_A = df.A, rename_D = df.D)
#   A  B second_A rename_D
#0  a  b        a        d
user_39443220
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