pandas.api.typing.Resampler.ohlc#

final Resampler.ohlc(numeric_only=False)[source]#

Compute open, high, low and close values of a group, excluding missing values.

This method computes OHLC (Open-High-Low-Close) values, commonly used in financial data analysis to summarize price movements within time periods.

Parameters:

numeric_onlybool, default False: Include only float, int, boolean columns.

Added in version 3.2.0.

Returns:

DataFrame: Open, high, low and close values within each group.

See also

DataFrame.agg: Aggregate using one or more operations over the specified axis.
DataFrame.resample: Resample time-series data.
DataFrame.groupby: Group DataFrame using a mapper or by a Series of columns.

Examples

>>> ser = pd.Series(
...     [1, 3, 2, 4, 3, 5],
...     index=pd.DatetimeIndex(
...         [
...             "2023-01-01",
...             "2023-01-10",
...             "2023-01-15",
...             "2023-02-01",
...             "2023-02-10",
...             "2023-02-15",
...         ]
...     ),
... )
>>> ser.resample("MS").ohlc()
            open  high  low  close
2023-01-01     1     3    1      2
2023-02-01     4     5    3      5