DataFrame.plot.line(x=None, y=None, **kwds) [source] Line plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

CategoricalIndex.nlevels

class pandas.TimedeltaIndex [source] Immutable ndarray of timedelta64 data, represented internally as int64, and which can be boxed to timedelta objects Parameters: data : array-like (1-dimensional), optional Optional timedelta-like data to construct index with unit: unit of the arg (D,h,m,s,ms,us,ns) denote the unit, optional which is an integer/float number freq: a frequency for the index, optional copy : bool Make a copy of input ndarray start : starting value, timedelta-like, opt

Panel4D.reindex_like(other, method=None, copy=True, limit=None, tolerance=None) [source] Return an object with matching indices to myself. Parameters: other : Object method : string or None copy : boolean, default True limit : int, default None Maximum number of consecutive labels to fill for inexact matches. tolerance : optional Maximum distance between labels of the other object and this object for inexact matches. New in version 0.17.0. Returns: reindexed : same as input Notes

TimedeltaIndex.view(cls=None) [source]

TimedeltaIndex.is_lexsorted_for_tuple(tup) [source]

Panel4D.any(axis=None, bool_only=None, skipna=None, level=None, **kwargs) [source] Return whether any element is True over requested axis Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} 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 Panel bool_only : boolean, default

Index.holds_integer() [source]

DataFrame.rsub(other, axis='columns', level=None, fill_value=None) [source] Subtraction of dataframe and other, element-wise (binary operator rsub). Equivalent to other - dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value. If

Expanding.std(ddof=1, *args, **kwargs) [source] expanding standard deviation Parameters: ddof : int, default 1 Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding