Series.iget_value()

Series.iget_value(i, axis=0) [source] DEPRECATED. Use .iloc[i] or .iat[i] instead

TimedeltaIndex.is_integer()

TimedeltaIndex.is_integer() [source]

TimedeltaIndex.groupby()

TimedeltaIndex.groupby(values) [source] Group the index labels by a given array of values. Parameters: values : array Values used to determine the groups. Returns: groups : dict {group name -> group labels}

pandas.read_pickle()

pandas.read_pickle(path) [source] Load pickled pandas object (or any other pickled object) from the specified file path Warning: Loading pickled data received from untrusted sources can be unsafe. See: http://docs.python.org/2.7/library/pickle.html Parameters: path : string File path Returns: unpickled : type of object stored in file

Series.cat.rename_categories()

Series.cat.rename_categories(*args, **kwargs) [source] Renames categories. The new categories has to be a list-like object. All items must be unique and the number of items in the new categories must be the same as the number of items in the old categories. Parameters: new_categories : Index-like The renamed categories. inplace : boolean (default: False) Whether or not to rename the categories inplace or return a copy of this categorical with renamed categories. Returns: cat : Catego

Panel4D.set_axis()

Panel4D.set_axis(axis, labels) [source] public verson of axis assignment

CategoricalIndex.to_series()

CategoricalIndex.to_series(**kwargs) [source] Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index Returns: Series : dtype will be based on the type of the Index values.

DataFrame.cummax()

DataFrame.cummax(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative max over 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 Returns: cummax : Series

DatetimeIndex.to_pydatetime()

DatetimeIndex.to_pydatetime() [source] Return DatetimeIndex as object ndarray of datetime.datetime objects Returns: datetimes : ndarray

MultiIndex.dropna()

MultiIndex.dropna(how='any') [source] Return Index without NA/NaN values Parameters: how : {?any?, ?all?}, default ?any? If the Index is a MultiIndex, drop the value when any or all levels are NaN. Returns: valid : Index