DataFrameGroupBy.take(indices, axis=0, convert=True, is_copy=True, **kwargs) Analogous to ndarray.take Parameters: indices : list / array of ints axis : int, default 0 convert : translate neg to pos indices (default) is_copy : mark the returned frame as a copy Returns: taken : type of caller

Series.clip_upper(threshold, axis=None) [source] Return copy of input with values above given value(s) truncated. Parameters: threshold : float or array_like axis : int or string axis name, optional Align object with threshold along the given axis. Returns: clipped : same type as input See also clip

DataFrame.slice_shift(periods=1, axis=0) [source] Equivalent to shift without copying data. The shifted data will not include the dropped periods and the shifted axis will be smaller than the original. Parameters: periods : int Number of periods to move, can be positive or negative Returns: shifted : same type as caller Notes While the slice_shift is faster than shift, you may pay for it later during alignment.

CategoricalIndex.reorder_categories(*args, **kwargs) [source] Reorders categories as specified in new_categories. new_categories need to include all old categories and no new category items. Parameters: new_categories : Index-like The categories in new order. ordered : boolean, optional Whether or not the categorical is treated as a ordered categorical. If not given, do not change the ordered information. inplace : boolean (default: False) Whether or not to reorder the categories inpl

DataFrame.iteritems() [source] Iterator over (column name, Series) pairs. See also iterrows Iterate over DataFrame rows as (index, Series) pairs. itertuples Iterate over DataFrame rows as namedtuples of the values.

Panel4D.at Fast label-based scalar accessor Similarly to loc, at provides label based scalar lookups. You can also set using these indexers.

Series.dt.tz

Index.inferred_type = None

Panel.add_prefix(prefix) [source] Concatenate prefix string with panel items names. Parameters: prefix : string Returns: with_prefix : type of caller

DatetimeIndex.order(return_indexer=False, ascending=True) [source] Return sorted copy of Index DEPRECATED: use Index.sort_values()