Series.set_axis()

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

Series.set_value()

Series.set_value(label, value, takeable=False) [source] Quickly set single value at passed label. If label is not contained, a new object is created with the label placed at the end of the result index Parameters: label : object Partial indexing with MultiIndex not allowed value : object Scalar value takeable : interpret the index as indexers, default False Returns: series : Series If label is contained, will be reference to calling Series, otherwise a new object

Series.sem()

Series.sem(axis=None, skipna=None, level=None, ddof=1, numeric_only=None, **kwargs) [source] Return unbiased standard error of the mean over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument Parameters: axis : {index (0)} 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, colla

Series.select()

Series.select(crit, axis=0) [source] Return data corresponding to axis labels matching criteria Parameters: crit : function To be called on each index (label). Should return True or False axis : int Returns: selection : type of caller

Series.searchsorted()

Series.searchsorted(v, side='left', sorter=None) [source] Find indices where elements should be inserted to maintain order. Find the indices into a sorted Series self such that, if the corresponding elements in v were inserted before the indices, the order of self would be preserved. Parameters: v : array_like Values to insert into self. side : {?left?, ?right?}, optional If ?left?, the index of the first suitable location found is given. If ?right?, return the last such index. If there

Series.sample()

Series.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None) [source] Returns a random sample of items from an axis of object. New in version 0.16.1. Parameters: n : int, optional Number of items from axis to return. Cannot be used with frac. Default = 1 if frac = None. frac : float, optional Fraction of axis items to return. Cannot be used with n. replace : boolean, optional Sample with or without replacement. Default = False. weights : str or ndarra

Series.rsub()

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

Series.rtruediv()

Series.rtruediv(other, level=None, fill_value=None, axis=0) [source] Floating division of series and other, element-wise (binary operator rtruediv). Equivalent to other / series, 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

Series.rpow()

Series.rpow(other, level=None, fill_value=None, axis=0) [source] Exponential power of series and other, element-wise (binary operator rpow). Equivalent to other ** series, 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 leve

Series.round()

Series.round(decimals=0, *args, **kwargs) [source] Round each value in a Series to the given number of decimals. Parameters: decimals : int Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point. Returns: Series object See also numpy.around, DataFrame.round