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,

Series.cummax(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative max over requested axis. Parameters: axis : {index (0)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cummax : scalar

CategoricalIndex.factorize(sort=False, na_sentinel=-1) [source] Encode the object as an enumerated type or categorical variable Parameters: sort : boolean, default False Sort by values na_sentinel: int, default -1 Value to mark ?not found? Returns: labels : the indexer to the original array uniques : the unique Index

Panel.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None, **kwargs) [source] Fill NA/NaN values using the specified method Parameters: value : scalar, dict, Series, or DataFrame Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). (values not in the dict/Series/DataFrame will not be filled). This value cannot be a list. method : {?backfil

MultiIndex.is_floating() [source]

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

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

Index.drop(labels, errors='raise') [source] Make new Index with passed list of labels deleted Parameters: labels : array-like errors : {?ignore?, ?raise?}, default ?raise? If ?ignore?, suppress error and existing labels are dropped. Returns: dropped : Index

TimedeltaIndex.argmax(axis=None, *args, **kwargs) [source] Returns the indices of the maximum values along an axis. See numpy.ndarray.argmax for more information on the axis parameter. See also numpy.ndarray.argmax