CategoricalIndex.itemsize return the size of the dtype of the item of the underlying data

MultiIndex.summary(name=None) [source]

EWM.std(bias=False, *args, **kwargs) [source] exponential weighted moving stddev Parameters: bias : boolean, default False Use a standard estimation bias correction Returns: same type as input See also pandas.Series.ewm, pandas.DataFrame.ewm

Series.cumprod(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative product 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: cumprod : scalar

TimedeltaIndex.get_level_values(level) [source] Return vector of label values for requested level, equal to the length of the index Parameters: level : int Returns: values : ndarray

DatetimeIndex.inferred_type

DataFrame.sum(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the sum of the values for the requested axis Parameters: axis : {index (0), columns (1)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series numeric_only : boolean, default None Include only float,

Panel.eq(other, axis=None) [source] Wrapper for comparison method eq

Series.is_unique Return boolean if values in the object are unique Returns: is_unique : boolean

MultiIndex.is_lexsorted_for_tuple(tup) [source] Return True if we are correctly lexsorted given the passed tuple