Renaming columns using numbers from a range in python/pandas

Question

I'm stuck with the following situation. I'm pretty sure I'm missing something simple, but I tried a lot of suggestions here and at other sites, and haven't found what I'm looking for.

I have a dataframe with a lot of randomly named columns (courtesy of provided csv file). I would like to rename these columns using digits from the range function.

Since I'm renaming all columns, I could do it directly using

df.columns = [str(x) for x in range(1,2000)]

However, hypothetically, could I do it through the rename() function? Maybe using a lambda? I have tried many different variations, but I'm getting all sorts of errors. I'm looking for the syntax to give me the equivalent of

 df.rename(columns= (str(x) for x in range(1,2000)))

where rename assigns the name to the columns sequentially based on the given range. The above does't work. But is there a way to make it work?

Thank you!

Answer 1

You can pass a dict to rename's columns kwarg:

df.rename(columns={x:y for x,y in zip(df.columns,range(0,len(df.columns)))})

That will take:

>>> df
   ID1  ID2 POS1 POS2     TYPE TYPEVAL
1    A  001    1    5    COLOR     RED
2    A  001    1    5   WEIGHT    50KG
3    A  001    1    5   HEIGHT   160CM
4    A  002    6   19   FUTURE     YES
5    A  002    6   19  PRESENT      NO
6    B  001   26   34   COLOUR    BLUE
7    B  001   26   34   WEIGHT    85KG
8    B  001   26   34   HEIGHT   120CM
9    C  001   10   13   MOBILE   NOKIA
10   C  001   10   13   TABLET    ASUS

And give you:

>>> df.rename(columns={x:y for x,y in zip(df.columns,range(0,len(df.columns)))})
    0    1   2   3        4      5
1   A  001   1   5    COLOR    RED
2   A  001   1   5   WEIGHT   50KG
3   A  001   1   5   HEIGHT  160CM
4   A  002   6  19   FUTURE    YES
5   A  002   6  19  PRESENT     NO
6   B  001  26  34   COLOUR   BLUE
7   B  001  26  34   WEIGHT   85KG
8   B  001  26  34   HEIGHT  120CM
9   C  001  10  13   MOBILE  NOKIA
10  C  001  10  13   TABLET   ASUS