xarray.core.resample.DataArrayResample¶
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class
xarray.core.resample.
DataArrayResample
(*args, dim=None, resample_dim=None, **kwargs)¶ DataArrayGroupBy object specialized to time resampling operations over a specified dimension
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__init__
(self, *args, dim=None, resample_dim=None, **kwargs)¶ Create a GroupBy object
- Parameters
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__
(self, \*args[, dim, resample_dim])Create a GroupBy object
all
(self[, dim, axis])Reduce this DataArrayResample’s data by applying all along some dimension(s).
any
(self[, dim, axis])Reduce this DataArrayResample’s data by applying any along some dimension(s).
apply
(self, func[, args, shortcut])Backward compatible implementation of
map
argmax
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying argmax along some dimension(s).
argmin
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying argmin along some dimension(s).
asfreq
(self)Return values of original object at the new up-sampling frequency; essentially a re-index with new times set to NaN.
assign_coords
(self[, coords])Assign coordinates by group.
backfill
(self[, tolerance])Backward fill new values at up-sampled frequency.
bfill
(self[, tolerance])Backward fill new values at up-sampled frequency.
count
(self[, dim, axis])Reduce this DataArrayResample’s data by applying count along some dimension(s).
ffill
(self[, tolerance])Forward fill new values at up-sampled frequency.
fillna
(self, value)Fill missing values in this object by group.
first
(self[, skipna, keep_attrs])Return the first element of each group along the group dimension
interpolate
(self[, kind])Interpolate up-sampled data using the original data as knots.
last
(self[, skipna, keep_attrs])Return the last element of each group along the group dimension
map
(self, func[, shortcut, args])Apply a function to each array in the group and concatenate them together into a new array.
max
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying max along some dimension(s).
mean
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying mean along some dimension(s).
median
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying median along some dimension(s).
min
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying min along some dimension(s).
nearest
(self[, tolerance])Take new values from nearest original coordinate to up-sampled frequency coordinates.
pad
(self[, tolerance])Forward fill new values at up-sampled frequency.
prod
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying prod along some dimension(s).
quantile
(self, q[, dim, interpolation, …])Compute the qth quantile over each array in the groups and concatenate them together into a new array.
reduce
(self, func[, dim, axis, keep_attrs, …])Reduce the items in this group by applying func along some dimension(s).
std
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying std along some dimension(s).
sum
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying sum along some dimension(s).
var
(self[, dim, axis, skipna])Reduce this DataArrayResample’s data by applying var along some dimension(s).
where
(self, cond[, other])Return elements from self or other depending on cond.
Attributes
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