Getting the index of a timestamp element in a pandas data frame

Question

I have a pandas data frame that I created as follows:

dates = pd.date_range('12-01-2020','12-10-2020')
my_df = pd.DataFrame(dates, columns = ['Date'])

So this gives

        Date
0 2020-12-01
1 2020-12-02
2 2020-12-03
3 2020-12-04
4 2020-12-05
5 2020-12-06
6 2020-12-07
7 2020-12-08
8 2020-12-09
9 2020-12-10

My question is very elementary: What is the correct function to use for returning the index of a given date? I have tried my_df['Date'].index('2020-12-05') , expecting to get 4, but instead I got the following error: 'RangeIndex' object is not callable. I also tried

d = pd.TimeStamp('12-05-2020' + '00:00:00') 
my_df['Date'].index(d)

but I got the same error...I'm confused because I've used.index successfully in similar situations, such as on lists with integers. Any help would be appreciated.

Answer 1

You can also use query without having to reset the index

my_df.query("Date == '2020-12-05'").index.values[0]

or if you want to assign the value to search:

d = pd.to_datetime('12-05-2020') 
my_df.query("Date == @d").index.values[0]

or without loc or query

my_df[my_df.Date == '12-05-2020'].index.values[0]

And your answer:

4

Answer 2

You could reset the index

my_df.reset_index().loc[my_df.Date == '2020-12-05', 'index']

or to get the scalar

my_df.reset_index().loc[my_df.Date == '2020-12-05', 'index'].values[0]