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

Series.add(other, level=None, fill_value=None, axis=0) [source] Addition of series and other, element-wise (binary operator add). 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, matching

class pandas.Series(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False) [source] One-dimensional ndarray with axis labels (including time series). Labels need not be unique but must be any hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. Statistical methods from ndarray have been overridden to automatically exclude missing data (currently represented as NaN) Operation

Series.abs() [source] Return an object with absolute value taken?only applicable to objects that are all numeric. Returns: abs: type of caller

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

Warning In v0.16.0, the pandas.rpy interface has been deprecated and will be removed in a future version. Similar functionality can be accessed through the rpy2 project. See the updating section for a guide to port your code from the pandas.rpy to rpy2 functions. Updating your code to use rpy2 functions In v0.16.0, the pandas.rpy module has been deprecated and users are pointed to the similar functionality in rpy2 itself (rpy2 >= 2.4). Instead of importing import pandas.rpy.common as com

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.std(ddof=1, *args, **kwargs) [source] rolling standard deviation 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

Rolling.min(*args, **kwargs) [source] rolling minimum Parameters: how : string, default ?min? (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.rolling, pandas.DataFrame.rolling

Rolling.skew(**kwargs) [source] Unbiased rolling skewness Returns: same type as input See also pandas.Series.rolling, pandas.DataFrame.rolling