pandas.cut(x, bins, right=True, labels=None, retbins=False, precision=3, include_lowest=False) [source] Return indices of half-open bins to which each value of x belongs. Parameters: x : array-like Input array to be binned. It has to be 1-dimensional. bins : int or sequence of scalars If bins is an int, it defines the number of equal-width bins in the range of x. However, in this case, the range of x is extended by .1% on each side to include the min or max values of x. If bins is a seq

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

DataFrame.__iter__() [source] Iterate over infor axis

GroupBy.__iter__() [source] Groupby iterator Returns: Generator yielding sequence of (name, subsetted object) for each group

Series.keys() [source] Alias for index

DatetimeIndex.is_mixed() [source]

CategoricalIndex.transpose(*args, **kwargs) [source] return the transpose, which is by definition self

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

DatetimeIndex.argsort(*args, **kwargs) [source] Returns the indices that would sort the index and its underlying data. Returns: argsorted : numpy array See also numpy.ndarray.argsort

Series.compress(condition, *args, **kwargs) [source] Return selected slices of an array along given axis as a Series See also numpy.ndarray.compress