Selecting and renaming columns at the same time

Question

I looked around but could not find the solution for this. In R's dplyr we can select and rename column in one line of code.

select(Com=Commander,Sco=Score)

I'm trying to do the same thing in pandas but could not find feasible solution for it yet!

Let's say we have this sample data

# Create an example dataframe
data = {'Commander': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], 
        'Date': ['2012, 02, 08', '2012, 02, 08', '2012, 02, 08', '2012, 02, 08', '2012, 02, 08'], 
        'Score': [4, 24, 31, 2, 3]}
df = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df


           Commander          Date  Score
Cochice        Jason  2012, 02, 08      4
Pima           Molly  2012, 02, 08     24
Santa Cruz      Tina  2012, 02, 08     31
Maricopa        Jake  2012, 02, 08      2
Yuma             Amy  2012, 02, 08      3

and want to select and rename Commander and Score columns like this

df[['Com'=='Commander','Sco'=='Score']]

ValueError: Item wrong length 2 instead of 5.

How can I do that ?

Answer 1

df.rename(columns = {"presentColumnName" : "NametoWhichYouWantTOChangeTo", "presentColumnName":"NametoWhichYouWantTOChangeTo"}, inplace=True)

for your example

df.rename(columns = {"Com" : "Commander", "Sco":"Score"}, inplace=True)

Answer 2

Try this:

df.columns = ['Com', 'Date', 'Sco']

Answer 3

You can do it in the same way in python as you did in R, using datar:

>>> from datar.all import tibble, select, f
>>> 
>>> data = {'Commander': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], 
...         'Date': ['2012, 02, 08', '2012, 02, 08', '2012, 02, 08', '2012, 02, 08', '2012, 02, 08'], 
...         'Score': [4, 24, 31, 2, 3]}
>>> 
>>> df = tibble(**data)
>>> df >> select(Com=f.Commander,Sco=f.Score)
       Com     Sco
  <object> <int64>
0    Jason       4
1    Molly      24
2     Tina      31
3     Jake       2
4      Amy       3

Disclaimer: I am the author of the datar package.