Index.sort_values(return_indexer=False, ascending=True) [source] Return sorted copy of Index

pandas.bdate_range(start=None, end=None, periods=None, freq='B', tz=None, normalize=True, name=None, closed=None, **kwargs) [source] Return a fixed frequency datetime index, with business day as the default frequency Parameters: start : string or datetime-like, default None Left bound for generating dates end : string or datetime-like, default None Right bound for generating dates periods : integer or None, default None If None, must specify start and end freq : string or DateOffset,

MultiIndex.strides return the strides of the underlying data

CategoricalIndex.equals(other) [source] Determines if two CategorialIndex objects contain the same elements.

CategoricalIndex.union(other) [source] Form the union of two Index objects and sorts if possible. Parameters: other : Index or array-like Returns: union : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.union(idx2) Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')

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

CategoricalIndex.is_lexsorted_for_tuple(tup) [source]

DataFrame.is_copy = None

Resampler.std(ddof=1, *args, **kwargs) [source] Compute standard deviation of groups, excluding missing values Parameters: ddof : integer, default 1 degrees of freedom

TimedeltaIndex.is_all_dates