xarray.core.resample.DatasetResample¶
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class
xarray.core.resample.
DatasetResample
(*args, dim=None, resample_dim=None, **kwargs)¶ DatasetGroupBy object specialized to resampling a specified dimension
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__init__
(*args, dim=None, resample_dim=None, **kwargs)¶ Create a GroupBy object
Parameters: - obj (Dataset or DataArray) – Object to group.
- group (DataArray) – Array with the group values.
- squeeze (boolean, optional) – If “group” is a coordinate of object, squeeze controls whether the subarrays have a dimension of length 1 along that coordinate or if the dimension is squeezed out.
- grouper (pd.Grouper, optional) – Used for grouping values along the group array.
- bins (array-like, optional) – If bins is specified, the groups will be discretized into the specified bins by pandas.cut.
- restore_coord_dims (bool, optional) – If True, also restore the dimension order of multi-dimensional coordinates.
- cut_kwargs (dict, optional) – Extra keyword arguments to pass to pandas.cut
Methods
__init__
(*args[, dim, resample_dim])Create a GroupBy object all
([dim])Reduce this DatasetResample’s data by applying all along some dimension(s). any
([dim])Reduce this DatasetResample’s data by applying any along some dimension(s). apply
(func[, args, shortcut])Apply a function over each Dataset in the groups generated for resampling and concatenate them together into a new Dataset. argmax
([dim, skipna])Reduce this DatasetResample’s data by applying argmax along some dimension(s). argmin
([dim, skipna])Reduce this DatasetResample’s data by applying argmin along some dimension(s). asfreq
()Return values of original object at the new up-sampling frequency; essentially a re-index with new times set to NaN. assign
(**kwargs)Assign data variables by group. assign_coords
([coords])Assign coordinates by group. backfill
([tolerance])Backward fill new values at up-sampled frequency. bfill
([tolerance])Backward fill new values at up-sampled frequency. count
([dim])Reduce this DatasetResample’s data by applying count along some dimension(s). ffill
([tolerance])Forward fill new values at up-sampled frequency. fillna
(value)Fill missing values in this object by group. first
([skipna, keep_attrs])Return the first element of each group along the group dimension interpolate
([kind])Interpolate up-sampled data using the original data as knots. last
([skipna, keep_attrs])Return the last element of each group along the group dimension max
([dim, skipna])Reduce this DatasetResample’s data by applying max along some dimension(s). mean
([dim, skipna])Reduce this DatasetResample’s data by applying mean along some dimension(s). median
([dim, skipna])Reduce this DatasetResample’s data by applying median along some dimension(s). min
([dim, skipna])Reduce this DatasetResample’s data by applying min along some dimension(s). nearest
([tolerance])Take new values from nearest original coordinate to up-sampled frequency coordinates. pad
([tolerance])Forward fill new values at up-sampled frequency. prod
([dim, skipna])Reduce this DatasetResample’s data by applying prod along some dimension(s). reduce
(func[, dim, keep_attrs])Reduce the items in this group by applying func along the pre-defined resampling dimension. std
([dim, skipna])Reduce this DatasetResample’s data by applying std along some dimension(s). sum
([dim, skipna])Reduce this DatasetResample’s data by applying sum along some dimension(s). var
([dim, skipna])Reduce this DatasetResample’s data by applying var along some dimension(s). where
(cond[, other])Return elements from self or other depending on cond. Attributes
dims
groups
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