Pivot matrix to time-series - Python

Rulo 0
Viewed 30

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!!

pivot datetime time-series dataframe python
2 Answers

Try .set_index/.stack. The rest is just convert the string to DateTime:

df = df.set_index("Date").stack().reset_index()
df["Date"] = pd.to_datetime(df["Date"] + " " + df["level_1"])
df = df.rename(columns={0: "Data"})
print(df[["Date", "Data"]])

Prints:

                  Date Data
0  2022-01-01 13:00:00    B
1  2022-01-01 14:00:00    R
2  2022-01-01 15:00:00    M
3  2022-01-01 16:00:00    M
4  2022-01-02 13:00:00    B
5  2022-01-02 14:00:00    B
6  2022-01-02 15:00:00    B
7  2022-01-02 16:00:00    M
8  2022-01-03 13:00:00    R
9  2022-01-03 14:00:00    B
10 2022-01-03 15:00:00    B
11 2022-01-03 16:00:00    M
Andrej Kesely0

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']]
userYE4D0
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