Resample objects

Dataset

DatasetResample(*args[, dim, resample_dim])	DatasetGroupBy object specialized to resampling a specified dimension
DatasetResample.asfreq()	Return values of original object at the new up-sampling frequency; essentially a re-index with new times set to NaN.
DatasetResample.backfill([tolerance])	Backward fill new values at up-sampled frequency.
DatasetResample.interpolate([kind])	Interpolate up-sampled data using the original data as knots.
DatasetResample.nearest([tolerance])	Take new values from nearest original coordinate to up-sampled frequency coordinates.
DatasetResample.pad([tolerance])	Forward fill new values at up-sampled frequency.
DatasetResample.all([dim, keep_attrs])	Reduce this Dataset's data by applying all along some dimension(s).
DatasetResample.any([dim, keep_attrs])	Reduce this Dataset's data by applying any along some dimension(s).
DatasetResample.apply(func[, args, shortcut])	Backward compatible implementation of map
DatasetResample.assign(**kwargs)	Assign data variables by group.
DatasetResample.assign_coords([coords])	Assign coordinates by group.
DatasetResample.bfill([tolerance])	Backward fill new values at up-sampled frequency.
DatasetResample.count([dim, keep_attrs])	Reduce this Dataset's data by applying count along some dimension(s).
DatasetResample.ffill([tolerance])	Forward fill new values at up-sampled frequency.
DatasetResample.fillna(value)	Fill missing values in this object by group.
DatasetResample.first([skipna, keep_attrs])	Return the first element of each group along the group dimension
DatasetResample.last([skipna, keep_attrs])	Return the last element of each group along the group dimension
DatasetResample.map(func[, args, shortcut])	Apply a function over each Dataset in the groups generated for resampling and concatenate them together into a new Dataset.
DatasetResample.max([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying max along some dimension(s).
DatasetResample.mean([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying mean along some dimension(s).
DatasetResample.median([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying median along some dimension(s).
DatasetResample.min([dim, skipna, keep_attrs])	Reduce this Dataset's data by applying min along some dimension(s).
DatasetResample.prod([dim, skipna, ...])	Reduce this Dataset's data by applying prod along some dimension(s).
DatasetResample.quantile(q[, dim, method, ...])	Compute the qth quantile over each array in the groups and concatenate them together into a new array.
DatasetResample.reduce(func[, dim, axis, ...])	Reduce the items in this group by applying func along the pre-defined resampling dimension.
DatasetResample.std([dim, skipna, ddof, ...])	Reduce this Dataset's data by applying std along some dimension(s).
DatasetResample.sum([dim, skipna, ...])	Reduce this Dataset's data by applying sum along some dimension(s).
DatasetResample.var([dim, skipna, ddof, ...])	Reduce this Dataset's data by applying var along some dimension(s).
DatasetResample.where(cond[, other])	Return elements from self or other depending on cond.
DatasetResample.dims
DatasetResample.groups	Mapping from group labels to indices.

DataArray

DataArrayResample(*args[, dim, resample_dim])	DataArrayGroupBy object specialized to time resampling operations over a specified dimension
DataArrayResample.asfreq()	Return values of original object at the new up-sampling frequency; essentially a re-index with new times set to NaN.
DataArrayResample.backfill([tolerance])	Backward fill new values at up-sampled frequency.
DataArrayResample.interpolate([kind])	Interpolate up-sampled data using the original data as knots.
DataArrayResample.nearest([tolerance])	Take new values from nearest original coordinate to up-sampled frequency coordinates.
DataArrayResample.pad([tolerance])	Forward fill new values at up-sampled frequency.
DataArrayResample.all([dim, keep_attrs])	Reduce this DataArray's data by applying all along some dimension(s).
DataArrayResample.any([dim, keep_attrs])	Reduce this DataArray's data by applying any along some dimension(s).
DataArrayResample.apply(func[, args, shortcut])	Backward compatible implementation of map
DataArrayResample.assign_coords([coords])	Assign coordinates by group.
DataArrayResample.bfill([tolerance])	Backward fill new values at up-sampled frequency.
DataArrayResample.count([dim, keep_attrs])	Reduce this DataArray's data by applying count along some dimension(s).
DataArrayResample.ffill([tolerance])	Forward fill new values at up-sampled frequency.
DataArrayResample.fillna(value)	Fill missing values in this object by group.
DataArrayResample.first([skipna, keep_attrs])	Return the first element of each group along the group dimension
DataArrayResample.last([skipna, keep_attrs])	Return the last element of each group along the group dimension
DataArrayResample.map(func[, args, shortcut])	Apply a function to each array in the group and concatenate them together into a new array.
DataArrayResample.max([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying max along some dimension(s).
DataArrayResample.mean([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying mean along some dimension(s).
DataArrayResample.median([dim, skipna, ...])	Reduce this DataArray's data by applying median along some dimension(s).
DataArrayResample.min([dim, skipna, keep_attrs])	Reduce this DataArray's data by applying min along some dimension(s).
DataArrayResample.prod([dim, skipna, ...])	Reduce this DataArray's data by applying prod along some dimension(s).
DataArrayResample.quantile(q[, dim, method, ...])	Compute the qth quantile over each array in the groups and concatenate them together into a new array.
DataArrayResample.reduce(func[, dim, axis, ...])	Reduce the items in this group by applying func along the pre-defined resampling dimension.
DataArrayResample.std([dim, skipna, ddof, ...])	Reduce this DataArray's data by applying std along some dimension(s).
DataArrayResample.sum([dim, skipna, ...])	Reduce this DataArray's data by applying sum along some dimension(s).
DataArrayResample.var([dim, skipna, ddof, ...])	Reduce this DataArray's data by applying var along some dimension(s).
DataArrayResample.where(cond[, other])	Return elements from self or other depending on cond.
DataArrayResample.dims
DataArrayResample.groups	Mapping from group labels to indices.