xarray.concat

xarray.concat(objs, dim, data_vars='all', coords='different', compat='equals', positions=None, fill_value=<NA>, join='outer')

Concatenate xarray objects along a new or existing dimension.

Parameters

• objs (sequence of Dataset and DataArray objects) – xarray objects to concatenate together. Each object is expected to consist of variables and coordinates with matching shapes except for along the concatenated dimension.

• dim (str or DataArray or pandas.Index) – Name of the dimension to concatenate along. This can either be a new dimension name, in which case it is added along axis=0, or an existing dimension name, in which case the location of the dimension is unchanged. If dimension is provided as a DataArray or Index, its name is used as the dimension to concatenate along and the values are added as a coordinate.

• data_vars ({'minimal', 'different', 'all' or list of str}, optional) –

  These data variables will be concatenated together:

  • ’minimal’: Only data variables in which the dimension already appears are included.

  • ’different’: Data variables which are not equal (ignoring attributes) across all datasets are also concatenated (as well as all for which dimension already appears). Beware: this option may load the data payload of data variables into memory if they are not already loaded.

  • ’all’: All data variables will be concatenated.

  • list of str: The listed data variables will be concatenated, in addition to the ‘minimal’ data variables.

  If objects are DataArrays, data_vars must be ‘all’.

• coords ({'minimal', 'different', 'all' or list of str}, optional) –

  These coordinate variables will be concatenated together:

  • ’minimal’: Only coordinates in which the dimension already appears are included.

  • ’different’: Coordinates which are not equal (ignoring attributes) across all datasets are also concatenated (as well as all for which dimension already appears). Beware: this option may load the data payload of coordinate variables into memory if they are not already loaded.

  • ’all’: All coordinate variables will be concatenated, except those corresponding to other dimensions.

  • list of str: The listed coordinate variables will be concatenated, in addition to the ‘minimal’ coordinates.

• compat ({'identical', 'equals', 'broadcast_equals', 'no_conflicts', 'override'}, optional) –

  String indicating how to compare non-concatenated variables of the same name for potential conflicts. This is passed down to merge.

  • ’broadcast_equals’: all values must be equal when variables are broadcast against each other to ensure common dimensions.

  • ’equals’: all values and dimensions must be the same.

  • ’identical’: all values, dimensions and attributes must be the same.

  • ’no_conflicts’: only values which are not null in both datasets must be equal. The returned dataset then contains the combination of all non-null values.

  • ’override’: skip comparing and pick variable from first dataset

• positions (None or list of integer arrays, optional) – List of integer arrays which specifies the integer positions to which to assign each dataset along the concatenated dimension. If not supplied, objects are concatenated in the provided order.

• fill_value (scalar, optional) – Value to use for newly missing values

• join ({'outer', 'inner', 'left', 'right', 'exact'}, optional) –

  String indicating how to combine differing indexes (excluding dim) in objects

  • ’outer’: use the union of object indexes

  • ’inner’: use the intersection of object indexes

  • ’left’: use indexes from the first object with each dimension

  • ’right’: use indexes from the last object with each dimension

  • ’exact’: instead of aligning, raise ValueError when indexes to be aligned are not equal

  • ’override’: if indexes are of same size, rewrite indexes to be those of the first object with that dimension. Indexes for the same dimension must have the same size in all objects.

• mode, concat_over (indexers,) –

Returns

concatenated

Return type

type of objs

See also

merge(), auto_combine()