# xarray.core.resample.DataArrayResample¶

class xarray.core.resample.DataArrayResample(*args, dim=None, resample_dim=None, **kwargs)

DataArrayGroupBy object specialized to time resampling operations over a specified dimension

__init__(*args, dim=None, resample_dim=None, **kwargs)

Create a GroupBy object

Parameters

Methods

 __init__(*args[, dim, resample_dim]) Create a GroupBy object all([dim, axis]) Reduce this DataArrayResample’s data by applying all along some dimension(s). any([dim, axis]) Reduce this DataArrayResample’s data by applying any along some dimension(s). apply(func[, args, shortcut]) Backward compatible implementation of map Return values of original object at the new up-sampling frequency; essentially a re-index with new times set to NaN. 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, axis]) Reduce this DataArrayResample’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 map(func[, shortcut, args]) Apply a function to each array in the group and concatenate them together into a new array. max([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying max along some dimension(s). mean([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying mean along some dimension(s). median([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying median along some dimension(s). min([dim, axis, skipna]) Reduce this DataArrayResample’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, axis, skipna]) Reduce this DataArrayResample’s data by applying prod along some dimension(s). quantile(q[, dim, interpolation, …]) Compute the qth quantile over each array in the groups and concatenate them together into a new array. reduce(func[, dim, axis, keep_attrs, shortcut]) Reduce the items in this group by applying func along some dimension(s). std([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying std along some dimension(s). sum([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying sum along some dimension(s). var([dim, axis, skipna]) Reduce this DataArrayResample’s data by applying var along some dimension(s). where(cond[, other]) Return elements from self or other depending on cond.

Attributes