pandas.read_clipboard(**kwargs) [source] Read text from clipboard and pass to read_table. See read_table for the full argument list If unspecified, sep defaults to ?s+? Returns: parsed : DataFrame

Panel4D.rename_axis(mapper, axis=0, copy=True, inplace=False) [source] Alter index and / or columns using input function or functions. A scaler or list-like for mapper will alter the Index.name or MultiIndex.names attribute. A function or dict for mapper will alter the labels. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Parameters: mapper : scalar, list-like, dict-like or function, optional axis : int or string, default 0 copy

Series.radd(other, level=None, fill_value=None, axis=0) [source] Addition of series and other, element-wise (binary operator radd). Equivalent to other + series, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, matchin

Series.reorder_levels(order) [source] Rearrange index levels using input order. May not drop or duplicate levels Parameters: order: list of int representing new level order. (reference level by number or key) axis: where to reorder levels Returns: type of caller (new object)

Panel.mod(other, axis=0) [source] Modulo of series and other, element-wise (binary operator mod). Equivalent to panel % other. Parameters: other : DataFrame or Panel axis : {items, major_axis, minor_axis} Axis to broadcast over Returns: Panel See also Panel.rmod

Panel.update(other, join='left', overwrite=True, filter_func=None, raise_conflict=False) [source] Modify Panel in place using non-NA values from passed Panel, or object coercible to Panel. Aligns on items Parameters: other : Panel, or object coercible to Panel join : How to join individual DataFrames {?left?, ?right?, ?outer?, ?inner?}, default ?left? overwrite : boolean, default True If True then overwrite values for common keys in the calling panel filter_func : callable(1d-array) -&

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

MultiIndex.is_floating() [source]

Series.imag

DataFrame.rpow(other, axis='columns', level=None, fill_value=None) [source] Exponential power of dataframe and other, element-wise (binary operator rpow). 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 val