resample(freq, dim, how='mean', skipna=None, closed=None, label=None, base=0, keep_attrs=False)¶
Resample this object to a new temporal resolution.
Handles both downsampling and upsampling. Upsampling with filling is not yet supported; if any intervals contain no values in the original object, they will be given the value
freq : str
String in the ‘#offset’ to specify the step-size along the resampled dimension, where ‘#’ is an (optional) integer multipler (default 1) and ‘offset’ is any pandas date offset alias. Examples of valid offsets include:
- ‘AS’: year start
- ‘QS-DEC’: quarterly, starting on December 1
- ‘MS’: month start
- ‘D’: day
- ‘H’: hour
- ‘Min’: minute
The full list of these offset aliases is documented in pandas [R29].
dim : str
Name of the dimension to resample along (e.g., ‘time’).
how : str or func, optional
Used for downsampling. If a string,
howmust be a valid aggregation operation supported by xarray. Otherwise,
howmust be a function that can be called like
how(values, axis)to reduce ndarray values along the given axis. Valid choices that can be provided as a string include all the usual Dataset/DataArray aggregations (
var), as well as
skipna : bool, optional
Whether to skip missing values when aggregating in downsampling.
closed : ‘left’ or ‘right’, optional
Side of each interval to treat as closed.
label : ‘left or ‘right’, optional
Side of each interval to use for labeling.
base : int, optionalt
For frequencies that evenly subdivide 1 day, the “origin” of the aggregated intervals. For example, for ‘24H’ frequency, base could range from 0 through 23.
keep_attrs : bool, optional
If True, the object’s attributes (attrs) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes.
resampled : same type as caller
This object resampled.
[R29] (1, 2) http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases