larray.LArray.set_labels

LArray.set_labels(self, axis=None, labels=None, inplace=False, **kwargs)

Replaces the labels of one or several axes of the array.

Parameters

axisstring or Axis or dict

Axis for which we want to replace labels, or mapping {axis: changes} where changes can either be the complete list of labels, a mapping {old_label: new_label} or a function to transform labels. If there is no ambiguity (two or more axes have the same labels), axis can be a direct mapping {old_label: new_label}.

labelsint, str, iterable or mapping or function, optional

Integer or list of values usable as the collection of labels for an Axis. If this is mapping, it must be {old_label: new_label}. If it is a function, it must be a function accepting a single argument (a label) and returning a single value. This argument must not be used if axis is a mapping.

inplacebool, optional

Whether or not to modify the original object or return a new array and leave the original intact. Defaults to False.

**kwargs :

axis`=`labels for each axis you want to set labels.

Returns

LArray

Array with modified labels.

See also

AxisCollection.set_labels

Examples

>>> a = ndtest('nat=BE,FO;sex=M,F')
>>> a
nat\sex  M  F
     BE  0  1
     FO  2  3
>>> a.set_labels('sex', ['Men', 'Women'])
nat\sex  Men  Women
     BE    0      1
     FO    2      3

when passing a single string as labels, it will be interpreted to create the list of labels, so that one can use the same syntax than during axis creation.

>>> a.set_labels('sex', 'Men,Women')
nat\sex  Men  Women
     BE    0      1
     FO    2      3

to replace only some labels, one must give a mapping giving the new label for each label to replace

>>> a.set_labels('sex', {'M': 'Men'})
nat\sex  Men  F
     BE    0  1
     FO    2  3

to transform labels by a function, use any function accepting and returning a single argument:

>>> a.set_labels('nat', str.lower)
nat\sex  M  F
     be  0  1
     fo  2  3

to replace labels for several axes at the same time, one should give a mapping giving the new labels for each changed axis

>>> a.set_labels({'sex': 'Men,Women', 'nat': 'Belgian,Foreigner'})
  nat\sex  Men  Women
  Belgian    0      1
Foreigner    2      3

or use keyword arguments

>>> a.set_labels(sex='Men,Women', nat='Belgian,Foreigner')
  nat\sex  Men  Women
  Belgian    0      1
Foreigner    2      3

one can also replace some labels in several axes by giving a mapping of mappings

>>> a.set_labels({'sex': {'M': 'Men'}, 'nat': {'BE': 'Belgian'}})
nat\sex  Men  F
Belgian    0  1
     FO    2  3

when there is no ambiguity (two or more axes have the same labels), it is possible to give a mapping between old and new labels

>>> a.set_labels({'M': 'Men', 'BE': 'Belgian'})
nat\sex  Men  F
Belgian    0  1
     FO    2  3