xarray.core.resample.DatasetResample¶
-
class
xarray.core.resample.
DatasetResample
(*args, **kwargs)¶ DatasetGroupBy object specialized to resampling a specified dimension
-
__init__
(*args, **kwargs)¶ Create a GroupBy object
- Parameters
- objDataset or DataArray
Object to group.
- groupDataArray
Array with the group values.
- squeezeboolean, 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.
- grouperpd.Grouper, optional
Used for grouping values along the group array.
- binsarray-like, optional
If bins is specified, the groups will be discretized into the specified bins by pandas.cut.
- restore_coord_dimsbool, optional
If True, also restore the dimension order of multi-dimensional coordinates.
- cut_kwargsdict, optional
Extra keyword arguments to pass to pandas.cut
Methods
__init__
(*args, **kwargs)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])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
(**kwargs)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
groups
-