pyufunc.group_dt_hourly#

pyufunc.group_dt_hourly(df, interval=1, col=None)#

Group the DataFrame by hour.

Parameters:

  • df (pd.DataFrame) – input DataFrame with datetime and value columns

  • interval (int, optional) – the time interval to groupby. Defaults to 1.

  • col (list, optional) – specify input column names. if your input column name is not same as default col name, use your own col name. e.g. [“your_datetime_col_name”, “your_value_col_name”]. Defaults to [“datetime”, “value”].

Returns:

grouped DataFrame by hour with count, mean and sum.

Return type:

pd.DataFrame

Example

>>> import pyufunc as pf
>>> import pandas as pd
>>> df = pd.DataFrame({"datetime": pd.date_range(start="2020-01-01",
end="2020-01-02", freq="h"), "value": range(25)})
>>> pf.group_hourly(df, interval=1, col=["datetime", "value"])
The group_hourly require at least two columns
first column: datetime
second column: value
    datetime        count  mean     sum
0       2020-01-01 00:00:00     1       0.0         0
1       2020-01-01 01:00:00     1       1.0         1
2       2020-01-01 02:00:00     1       2.0         2
3       2020-01-01 03:00:00     1       3.0         3
4       2020-01-01 04:00:00     1       4.0         4
5       2020-01-01 05:00:00     1       5.0         5