bigframes.pandas.DataFrame.resample#

DataFrame.resample(rule: str, *, closed: Literal['right', 'left'] | None = None, label: Literal['right', 'left'] | None = None, on: Hashable = None, level: Hashable | Sequence[Hashable] | None = None, origin: Timestamp | datetime | datetime64 | int | float | str | Literal['epoch', 'start', 'start_day', 'end', 'end_day'] = 'start_day') → DataFrameGroupBy[source]#

Resample time-series data.

Examples:

>>> import bigframes.pandas as bpd
>>> data = {
...     "timestamp_col": pd.date_range(
...         start="2021-01-01 13:00:00", periods=30, freq="1s"
...     ),
...     "int64_col": range(30),
...     "int64_too": range(10, 40),
... }

Resample on a DataFrame with index:

>>> df = bpd.DataFrame(data).set_index("timestamp_col")
>>> df.resample(rule="7s").min()
                     int64_col  int64_too
timestamp_col
2021-01-01 12:59:55          0         10
2021-01-01 13:00:02          2         12
2021-01-01 13:00:09          9         19
2021-01-01 13:00:16         16         26
2021-01-01 13:00:23         23         33

[5 rows x 2 columns]

Resample with column and origin set to start:

>>> df = bpd.DataFrame(data)
>>> df.resample(rule="7s", on = "timestamp_col", origin="start").min()
                     int64_col  int64_too
timestamp_col
2021-01-01 13:00:00          0         10
2021-01-01 13:00:07          7         17
2021-01-01 13:00:14         14         24
2021-01-01 13:00:21         21         31
2021-01-01 13:00:28         28         38

[5 rows x 2 columns]

Parameters:

• rule (str) The offset string representing target conversion. Offsets ME, YE, QE, BME, BA, BQE, and W are not supported.

• closed (Literal['left'] | None) Which side of bin interval is closed. The default is left for all supported frequency offsets.

• label (Literal['right'] | Literal['left'] | None) Which bin edge label to label bucket with. The default is left for all supported frequency offsets.

• on (str, default None) For a DataFrame, column to use instead of index for resampling. Column must be datetime-like.

• level (str or int, default None) For a MultiIndex, level (name or number) to use for resampling. level must be datetime-like.

• origin (str, default 'start_day') The timestamp on which to adjust the grouping. Must be one of the following: epoch: origin is 1970-01-01 start: origin is the first value of the timeseries start_day: origin is the first day at midnight of the timeseries Origin values end and end_day are not supported.

Returns:

DataFrameGroupBy object.

Return type:

DataFrameGroupBy