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class pandas.CategoricalIndex[source] -
Immutable Index implementing an ordered, sliceable set. CategoricalIndex represents a sparsely populated Index with an underlying Categorical.
New in version 0.16.1.
Parameters: data : array-like or Categorical, (1-dimensional)
categories : optional, array-like
categories for the CategoricalIndex
ordered : boolean,
designating if the categories are ordered
copy : bool
Make a copy of input ndarray
name : object
Name to be stored in the index
Attributes
Treturn the transpose, which is by definition self asi8basereturn the base object if the memory of the underlying data is categoriescodesdatareturn the data pointer of the underlying data dtypedtype_strflagshas_duplicateshasnansinferred_typeis_all_datesis_monotonicalias for is_monotonic_increasing (deprecated) is_monotonic_decreasingreturn if the index is monotonic decreasing (only equal or is_monotonic_increasingreturn if the index is monotonic increasing (only equal or is_uniqueitemsizereturn the size of the dtype of the item of the underlying data namenamesnbytesreturn the number of bytes in the underlying data ndimreturn the number of dimensions of the underlying data, nlevelsorderedshapereturn a tuple of the shape of the underlying data sizereturn the number of elements in the underlying data stridesreturn the strides of the underlying data valuesreturn the underlying data, which is a Categorical Methods
add_categories(\*args, \*\*kwargs)Add new categories. all([other])any([other])append(other)Append a collection of Index options together argmax([axis])return a ndarray of the maximum argument indexer argmin([axis])return a ndarray of the minimum argument indexer argsort(\*args, \*\*kwargs)as_ordered(\*args, \*\*kwargs)Sets the Categorical to be ordered as_unordered(\*args, \*\*kwargs)Sets the Categorical to be unordered asof(label)For a sorted index, return the most recent label up to and including the passed label. asof_locs(where, mask)where : array of timestamps astype(dtype[, copy])Create an Index with values cast to dtypes. copy([name, deep, dtype])Make a copy of this object. delete(loc)Make new Index with passed location(-s) deleted difference(other)Return a new Index with elements from the index that are not in other.drop(labels[, errors])Make new Index with passed list of labels deleted drop_duplicates(\*args, \*\*kwargs)Return Index with duplicate values removed dropna([how])Return Index without NA/NaN values duplicated(\*args, \*\*kwargs)Return boolean np.ndarray denoting duplicate values equals(other)Determines if two CategorialIndex objects contain the same elements. factorize([sort, na_sentinel])Encode the object as an enumerated type or categorical variable fillna(value[, downcast])Fill NA/NaN values with the specified value format([name, formatter])Render a string representation of the Index get_duplicates()get_indexer(target[, method, limit, tolerance])Compute indexer and mask for new index given the current index. get_indexer_for(target, \*\*kwargs)guaranteed return of an indexer even when non-unique get_indexer_non_unique(target)this is the same for a CategoricalIndex for get_indexer; the API get_level_values(level)Return vector of label values for requested level, equal to the length get_loc(key[, method])Get integer location for requested label get_slice_bound(label, side, kind)Calculate slice bound that corresponds to given label. get_value(series, key)Fast lookup of value from 1-dimensional ndarray. get_values()return the underlying data as an ndarray groupby(values)Group the index labels by a given array of values. holds_integer()identical(other)Similar to equals, but check that other comparable attributes are insert(loc, item)Make new Index inserting new item at location. intersection(other)Form the intersection of two Index objects. is_(other)More flexible, faster check like isbut that works through viewsis_boolean()is_categorical()is_floating()is_integer()is_lexsorted_for_tuple(tup)is_mixed()is_numeric()is_object()is_type_compatible(kind)isin(values[, level])Compute boolean array of whether each index value is found in the passed set of values. item()return the first element of the underlying data as a python join(other[, how, level, return_indexers])this is an internal non-public method map(mapper)Apply mapper function to its categories (not codes). max(\*args, \*\*kwargs)The maximum value of the object. memory_usage([deep])Memory usage of my values min(\*args, \*\*kwargs)The minimum value of the object. nunique([dropna])Return number of unique elements in the object. order([return_indexer, ascending])Return sorted copy of Index putmask(mask, value)return a new Index of the values set with the mask ravel([order])return an ndarray of the flattened values of the underlying data reindex(target[, method, level, limit, ...])Create index with target?s values (move/add/delete values as necessary) remove_categories(\*args, \*\*kwargs)Removes the specified categories. remove_unused_categories(\*args, \*\*kwargs)Removes categories which are not used. rename(name[, inplace])Set new names on index. rename_categories(\*args, \*\*kwargs)Renames categories. reorder_categories(\*args, \*\*kwargs)Reorders categories as specified in new_categories. repeat(n, \*args, \*\*kwargs)Repeat elements of an Index. reshape(\*args, \*\*kwargs)NOT IMPLEMENTED: do not call this method, as reshaping is not supported for Index objects and will raise an error. searchsorted(key[, side, sorter])Find indices where elements should be inserted to maintain order. set_categories(\*args, \*\*kwargs)Sets the categories to the specified new_categories. set_names(names[, level, inplace])Set new names on index. set_value(arr, key, value)Fast lookup of value from 1-dimensional ndarray. shift([periods, freq])Shift Index containing datetime objects by input number of periods and slice_indexer([start, end, step, kind])For an ordered Index, compute the slice indexer for input labels and slice_locs([start, end, step, kind])Compute slice locations for input labels. sort(\*args, \*\*kwargs)sort_values([return_indexer, ascending])Return sorted copy of Index sortlevel([level, ascending, sort_remaining])For internal compatibility with with the Index API stralias of StringMethodssummary([name])sym_diff(\*args, \*\*kwargs)symmetric_difference(other[, result_name])Compute the symmetric difference of two Index objects. take(indices[, axis, allow_fill, fill_value])return a new %(klass)s of the values selected by the indices to_datetime([dayfirst])DEPRECATED: use pandas.to_datetime()instead.to_native_types([slicer])slice and dice then format to_series(\*\*kwargs)Create a Series with both index and values equal to the index keys tolist()return a list of the Index values transpose(\*args, \*\*kwargs)return the transpose, which is by definition self union(other)Form the union of two Index objects and sorts if possible. unique()Return Index of unique values in the object. value_counts([normalize, sort, ascending, ...])Returns object containing counts of unique values. view([cls])where(cond[, other])New in version 0.19.0.
CategoricalIndex[source]
2017-01-12 04:45:16
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