Pandas Period to to_timestamp giving me TypeError

Question

I have a Pandas Dataframe of the format as shown below:

   Month     Count  
   2021-02    100
   2021-03    200

Where the "Month" column is obtained from a timestamp using dt.to_period('M').

Now I have to convert this "Month" column to a fiscal quarter and I have used some approaches to convert the Period to a "datetime" object using "to_timestamp", but I get the error

TypeError: unsupported Type Int64Index

Is there another way to approach this problem?

Can you add your code to question? – jezrael Jul 08 '21 at 05:43 — jezrael, Jul 08 '21 at 05:43

score 7 · Answer 1 · edited Jul 17 '21 at 00:47

If working with a column, it is necessary to add .dt. If omitting it, Pandas tries to convert DatetimeIndex and if it does not exist, it raises an error, because it called DataFrame.to_timestamp instead of Series.dt.to_timestamp:

df['Date'] = df['Month'].to_timestamp()

TypeError: unsupported Type RangeIndex

df['Date'] = df['Month'].dt.to_timestamp()
print (df)
     Month  Count       Date
0  2021-02    100 2021-02-01
1  2021-03    200 2021-03-01

The solution for a fiscal quarter is to use Series.dt.qyear. Better documentation is here:

df['fquarter'] = df['Month'].dt.qyear
print (df)
     Month  Count  fquarter
0  2021-02    100      2021
1  2021-03    200      2021

Pandas Period to to_timestamp giving me TypeError

1 Answers1