DataFrame.tz_localize(*args, **kwargs) [source] Localize tz-naive TimeSeries to target time zone. Parameters: tz : string or pytz.timezone object axis : the axis to localize level : int, str, default None If axis ia a MultiIndex, localize a specific level. Otherwise must be None copy : boolean, default True Also make a copy of the underlying data ambiguous : ?infer?, bool-ndarray, ?NaT?, default ?raise? ?infer? will attempt to infer fall dst-transition hours based on order bool-ndarra

GroupBy.apply(func, *args, **kwargs) [source] Apply function and combine results together in an intelligent way. The split-apply-combine combination rules attempt to be as common sense based as possible. For example: case 1: group DataFrame apply aggregation function (f(chunk) -> Series) yield DataFrame, with group axis having group labels case 2: group DataFrame apply transform function ((f(chunk) -> DataFrame with same indexes) yield DataFrame with resulting chunks glued together ca

Index.asof(label) [source] For a sorted index, return the most recent label up to and including the passed label. Return NaN if not found. See also get_loc asof is a thin wrapper around get_loc with method=?pad?

Panel.dtypes Return the dtypes in this object.

TimedeltaIndex.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

Series.ffill(axis=None, inplace=False, limit=None, downcast=None) [source] Synonym for NDFrame.fillna(method=?ffill?)

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)