CategoricalIndex.putmask()

CategoricalIndex.putmask(mask, value) [source] return a new Index of the values set with the mask See also numpy.ndarray.putmask

CategoricalIndex.reindex()

CategoricalIndex.reindex(target, method=None, level=None, limit=None, tolerance=None) [source] Create index with target?s values (move/add/delete values as necessary) Returns: new_index : pd.Index Resulting index indexer : np.ndarray or None Indices of output values in original index

CategoricalIndex.ravel()

CategoricalIndex.ravel(order='C') [source] return an ndarray of the flattened values of the underlying data See also numpy.ndarray.ravel

CategoricalIndex.nunique()

CategoricalIndex.nunique(dropna=True) [source] Return number of unique elements in the object. Excludes NA values by default. Parameters: dropna : boolean, default True Don?t include NaN in the count. Returns: nunique : int

CategoricalIndex.ordered

CategoricalIndex.ordered

CategoricalIndex.order()

CategoricalIndex.order(return_indexer=False, ascending=True) [source] Return sorted copy of Index DEPRECATED: use Index.sort_values()

CategoricalIndex.ndim

CategoricalIndex.ndim return the number of dimensions of the underlying data, by definition 1

CategoricalIndex.nlevels

CategoricalIndex.nlevels

CategoricalIndex.nbytes

CategoricalIndex.nbytes return the number of bytes in the underlying data

CategoricalIndex.min()

CategoricalIndex.min(*args, **kwargs) [source] The minimum value of the object. Only ordered Categoricals have a minimum! Returns: min : the minimum of this Categorical Raises: TypeError If the Categorical is not ordered.