Pandas (Python) Splitting hour and time interval on Index and Column

Question

I have the temperatures being measuered and I want to create a heatmap from it. For this I first have to create a DataFrame where hour and 15 minute intervals are on the Index and the column.

The source data is like this:

date	temperature
2021-08-14 11:14:00	27.8
2021-08-14 11:15:00	27.9
2021-08-14 11:16:00	27.9
2021-08-14 11:17:00	27.9
2021-08-14 11:18:00	27.9
....	....
2021-08-14 11:31:00	28.10
2021-08-14 11:32:00	28.10
2021-08-14 11:33:00	28.10
2021-08-14 11:34:00	28.10

What I want to get is:

date	00	15	30	45
11:00	27.8	27.9	28.1	28.3
12:00	..	..	..	..

So I want the time intervals within the hour to be split on the columns and the index containing the specific hours (on which the columns occur).

Is there any way to do this action in Pandas in an easy way?

Thanks in advance!

Answer 1

Let's first separate hours and minutes (rounded to 15), put them back in the dataframe and use .pivot_table() to build your dataframe with interval means:

>>> h = df['date'].dt.strftime('%H:00').rename('hour')
>>> m = df['date'].dt.floor(freq='15T').dt.minute.rename('minutes')
>>> df.join([h, m]).pivot_table(index='hour', columns='minutes', values='temperature', aggfunc='mean')
minutes                     0          15         30         45
hour                                                           
2021-08-14 11:00:00  28.709492  28.026066  27.991953  28.096947
2021-08-14 12:00:00  27.877558  28.022282  27.720347  28.201100
2021-08-14 13:00:00  27.739935        NaN        NaN        NaN

Answer 2

Use resample and pivot_table to get expected outcome:

out = df.set_index('date').resample('15T').mean()
out = pd.pivot_table(out, index=out.index.strftime('%H:00'),
                          columns=out.index.strftime('%M'),
                          values='temperature')
out = out.rename_axis(index=None, columns=None)

>>> out
         00    15    30
11:00  27.8  27.9  28.1