How do I include many columns in pd.melt function instead of just typing each and everyone out?

Question

I have a data set that has the following columns. funciton: pd.melt() years name date m1 m2 m3 m4 m5 m6 …. to m12

I set me variable name to month and try to include m1-m12, but I just cant get it to work. it will instead put everything in the new week column which looks like week year name date m1 m2 I don't want the week year name date, is there a way to just put m1-m12 in like indexing? i have tried it it didn't work

Could you provide a sample of your input and expected output? — Jon Clements, Apr 24 '22 at 22:58
As Jon mentioned, a sample dataframe with expected output dataframe will be helpful — sammywemmy, Apr 24 '22 at 23:07
Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking. — Community, Apr 25 '22 at 02:05

score 0 · Answer 1 · answered Apr 24 '22 at 23:30

0

sample output
month
m1
m2
m3
...
m12
here is the answer i come up with using iloc!
sorry for asking a easy question that I can figure out myself
pd.melt(.......value_vars=billboard.iloc[-12:])

answered Apr 24 '22 at 23:30

Jenwei Tan

1
1

Kindly mark it as accepted or delete the question, so it is no longer an active question – sammywemmy Apr 25 '22 at 00:35
Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers [in the help center](/help/how-to-answer). – Community Apr 25 '22 at 00:55
hi! how do i do that? – Jenwei Tan Apr 26 '22 at 01:32

How do I include many columns in pd.melt function instead of just typing each and everyone out?

1 Answers1