TimedeltaIndex.format(name=False, formatter=None, **kwargs) [source] Render a string representation of the Index

TimedeltaIndex.set_value(arr, key, value) [source] Fast lookup of value from 1-dimensional ndarray. Only use this if you know what you?re doing

DatetimeIndex.view(cls=None) [source]

class pandas.Panel(data=None, items=None, major_axis=None, minor_axis=None, copy=False, dtype=None) [source] Represents wide format panel data, stored as 3-dimensional array Parameters: data : ndarray (items x major x minor), or dict of DataFrames items : Index or array-like axis=0 major_axis : Index or array-like axis=1 minor_axis : Index or array-like axis=2 dtype : dtype, default None Data type to force, otherwise infer copy : boolean, default False Copy data from inputs. Only

DatetimeIndex.freq get/set the frequncy of the Index

DatetimeIndex.is_monotonic alias for is_monotonic_increasing (deprecated)

TimedeltaIndex.to_series(**kwargs) [source] Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index Returns: Series : dtype will be based on the type of the Index values.

Series.cat.as_ordered(*args, **kwargs) [source] Sets the Categorical to be ordered Parameters: inplace : boolean (default: False) Whether or not to set the ordered attribute inplace or return a copy of this categorical with ordered set to True

DatetimeIndex.repeat(repeats, *args, **kwargs) [source] Analogous to ndarray.repeat

CategoricalIndex.format(name=False, formatter=None, **kwargs) [source] Render a string representation of the Index