MultiIndex.get_major_bounds(start=None, end=None, step=None, kind=None) [source] For an ordered MultiIndex, compute the slice locations for input labels. They can be tuples representing partial levels, e.g. for a MultiIndex with 3 levels, you can pass a single value (corresponding to the first level), or a 1-, 2-, or 3-tuple. Parameters: start : label or tuple, default None If None, defaults to the beginning end : label or tuple If None, defaults to the end step : int or None Slice st

Series.str.cat(others=None, sep=None, na_rep=None) [source] Concatenate strings in the Series/Index with given separator. Parameters: others : list-like, or list of list-likes If None, returns str concatenating strings of the Series sep : string or None, default None na_rep : string or None, default None If None, NA in the series are ignored. Returns: concat : Series/Index of objects or str Examples When na_rep is None (default behavior), NaN value(s) in the Series are ignored. >

Index.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}

CategoricalIndex.duplicated(*args, **kwargs) [source] Return boolean np.ndarray denoting duplicate values Parameters: keep : {?first?, ?last?, False}, default ?first? first : Mark duplicates as True except for the first occurrence. last : Mark duplicates as True except for the last occurrence. False : Mark all duplicates as True. take_last : deprecated Returns: duplicated : np.ndarray

Grouper.ax

Index.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs) [source] return a new %(klass)s of the values selected by the indices For internal compatibility with numpy arrays. Parameters: indices : list Indices to be taken axis : int, optional The axis over which to select values, always 0. allow_fill : bool, default True fill_value : bool, default None If allow_fill=True and fill_value is not None, indices specified by -1 is regarded as NA. If Index doesn?t hold NA, raise

Panel4D.all(axis=None, bool_only=None, skipna=None, level=None, **kwargs) [source] Return whether all elements are True over requested axis Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Panel bool_only : boolean, defaul

DataFrameGroupBy.size() [source] Compute group sizes See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Series.str.isalpha() [source] Check whether all characters in each string in the Series/Index are alphabetic. Equivalent to str.isalpha(). Returns: is : Series/array of boolean values

TimedeltaIndex.freqstr Return the frequency object as a string if its set, otherwise None