I’ve got a dataframe with date as first column and time as the name of the other columns.
| Date | 13:00 | 14:00 | 15:00 | 16:00 | … |
|---|---|---|---|---|---|
| 2022-01-01 | B | R | M | M | … |
| 2022-01-02 | B | B | B | M | … |
| 2022-01-03 | R | B | B | M | … |
How could I transform that matrix into a datetime time-series? My objective its something like this:
| Date | Data |
|---|---|
| 2022-01-01 13:00 | B |
| 2022-01-01 14:00 | R |
| 2022-01-01 15:00 | M |
| 2022-01-01 16:00 | M |
| … | … |
I think it could be done using pivot. I would really appreciate any help you could give me. Thanks in advance!!
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Answer
An alternative:
df = pd.DataFrame({'Date': ['2022-01-01', '2022-01-02', '2022-01-03'], '13:00': ['B', 'B', 'R'], '14:00': ['R', 'B', 'R'], '15:00': ['M', 'B', 'B'], '16:00': ['M', 'M', 'M']})
df = df.melt(id_vars='Date', var_name='Time', value_name='Data')
df['Date'] = df['Date'] + ' ' + df['Time']
df = df[['Date', 'Data']]