DatetimeIndex.date Returns numpy array of python datetime.date objects (namely, the date part of Timestamps without timezone information).

Rolling.sum(*args, **kwargs) [source] rolling sum Parameters: how : string, default None (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.rolling, pandas.DataFrame.rolling

Rolling.var(ddof=1, *args, **kwargs) [source] rolling variance 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.rolling, pandas.DataFrame.rolling

classmethod MultiIndex.from_product(iterables, sortorder=None, names=None) [source] Make a MultiIndex from the cartesian product of multiple iterables Parameters: iterables : list / sequence of iterables Each iterable has unique labels for each level of the index. sortorder : int or None Level of sortedness (must be lexicographically sorted by that level). names : list / sequence of strings or None Names for the levels in the index. Returns: index : MultiIndex See also MultiInd

Series.sub(other, level=None, fill_value=None, axis=0) [source] Subtraction of series and other, element-wise (binary operator sub). Equivalent to series - other, 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, matchi

CategoricalIndex.remove_unused_categories(*args, **kwargs) [source] Removes categories which are not used. Parameters: inplace : boolean (default: False) Whether or not to drop unused categories inplace or return a copy of this categorical with unused categories dropped. Returns: cat : Categorical with unused categories dropped or None if inplace. See also rename_categories, reorder_categories, add_categories, remove_categories, set_categories

Series.str.rsplit(pat=None, n=-1, expand=False) [source] Split each string in the Series/Index by the given delimiter string, starting at the end of the string and working to the front. Equivalent to str.rsplit(). New in version 0.16.2. Parameters: pat : string, default None Separator to split on. If None, splits on whitespace n : int, default -1 (all) None, 0 and -1 will be interpreted as return all splits expand : bool, default False If True, return DataFrame/MultiIndex expanding

Series.str.zfill(width) [source] Filling left side of strings in the Series/Index with 0. Equivalent to str.zfill(). Parameters: width : int Minimum width of resulting string; additional characters will be filled with 0 Returns: filled : Series/Index of objects

Series.cummin(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative minimum over requested axis. Parameters: axis : {index (0)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cummin : scalar

Series.str.extractall(pat, flags=0) [source] For each subject string in the Series, extract groups from all matches of regular expression pat. When each subject string in the Series has exactly one match, extractall(pat).xs(0, level=?match?) is the same as extract(pat). New in version 0.18.0. Parameters: pat : string Regular expression pattern with capturing groups flags : int, default 0 (no flags) re module flags, e.g. re.IGNORECASE Returns: A DataFrame with one row for each match