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')

Index.astype(dtype, copy=True) [source] Create an Index with values cast to dtypes. The class of a new Index is determined by dtype. When conversion is impossible, a ValueError exception is raised. Parameters: dtype : numpy dtype or pandas type copy : bool, default True By default, astype always returns a newly allocated object. If copy is set to False and internal requirements on dtype are satisfied, the original data is used to create a new Index or the original Index is returned. New

Index.get_duplicates() [source]

DatetimeIndex.flags

Panel4D.head(n=5) [source]

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

MultiIndex.strides return the strides of the underlying data

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.is_floating() [source]

CategoricalIndex.item() [source] return the first element of the underlying data as a python scalar