Reputation: 1801
I have a chronologically-sorted datetime Series(note the index values on the left-hand side)
9 1971-04-10
84 1971-05-18
2 1971-07-08
53 1971-07-11
28 1971-09-12
474 1972-01-01
153 1972-01-13
13 1972-01-26
129 1972-05-06
98 1972-05-13
111 1972-06-10
225 1972-06-15
For my purpose, only the sorted indices matter, so I would like to replace the datetime values with their indices in the original pandas Series (perhaps through reindexing) to return a new Series like this:
0 9
1 84
2 2
3 53
4 28
5 474
6 153
7 13
8 129
9 98
10 111
11 225
where the 'indices' on the left-hand-side are the new 'index' column and the 'indices' on the right are the original index column for datetime values.
What is the easier way to do this?
Thank you.
Upvotes: 0
Views: 329
Reputation: 1272
You can point your index to a list as follows
df.index = list(range(len(df))
where df
is your dataframe
Upvotes: 1
Reputation: 3462
If you are okay with constructing a new object:
series = pd.Series(old_series.index, index=whateveryouwant)
Where specifying the new index is optional..
Upvotes: 1