python - Convert a column of timestamps into periods in pandas

Question

I have a column of timestamps that need to be converted into period ('Month'). e.g.

1985-12-31 00:00:00 to 1985-12

Pandas have a .to_period function, but it only works for timestamps index, not column. So you can only have a period index, but not a period column?

And it only work if timestamps is the only index. That is, if timestamps are part of a multIndex, the .to_period() function doesn't work as well.

It seems that Pandas assume people will always use timestamps and periods as index, but not a single column, which is apparently not the case.

Anyway I can get around with this? Or if not in Pandas, can it be done in numpy?

Thanks!

Answer 1

I came across this thread today, and after further digging found that Pandas .15 affords an easier option use .dt, you can avoid the step of creating an index and create the column directly. You can use the following to get the same result:

df[1] = df[0].dt.to_period('M')