Pandas Window对象

生成window对象

.rolling calls:pandas.DataFrame.rolling(),pandas.Series.rolling()
.expanding
calls:pandas.DataFrame.expanding(),pandas.Series.expanding()
.ewm calls: pandas.DataFrame.ewm(), pandas.Series.ewm()
例如数据框DataFrame的window对象生成
DataFrame.rolling(window, min_periods=None, freq=None, center=False, win_type=None, on=None, axis=0)
window：窗口的长度
min_periods=窗口移动最小的间隔，默认为1
center：是否在中间位置显示计算值，默认为Flase
win_type：
on：指定窗口移动的列，默认为索引列
axis：指定窗口移动方向
标准移动窗口函数：

Function	Describe
Rolling.count()	rolling count of number of non-NaN
Rolling.sum(*args,?**kwargs)	rolling sum
Rolling.mean(*args,?**kwargs)	rolling mean
Rolling.median(**kwargs)	rolling median
Rolling.var([ddof])	rolling variance
Rolling.std([ddof])	rolling standard deviation
Rolling.min(*args,?**kwargs)	rolling minimum
Rolling.max(*args,?**kwargs)	rolling maximum
Rolling.corr([other,?pairwise])	rolling sample correlation
Rolling.cov([other,?pairwise,?ddof])	rolling sample covariance
Rolling.skew(**kwargs)	Unbiased rolling skewness
Rolling.kurt(**kwargs)	Unbiased rolling kurtosis
Rolling.apply(func[,?args,?kwargs])	rolling function apply
Rolling.quantile(quantile,?**kwargs)	rolling quantile
Window.mean(*args,?**kwargs)	window mean
Window.sum(*args,?**kwargs)	window sum

标准扩展窗口：

Function	Describe
Expanding.count(**kwargs)	expanding count of number of non-NaN
Expanding.sum(*args,?**kwargs)	expanding sum
Expanding.mean(*args,?**kwargs)	expanding mean
Expanding.median(**kwargs)	expanding median
Expanding.var([ddof])	expanding variance
Expanding.std([ddof])	expanding standard deviation
Expanding.min(*args,?**kwargs)	expanding minimum
Expanding.max(*args,?**kwargs)	expanding maximum
Expanding.corr([other,?pairwise])	expanding sample correlation
Expanding.cov([other,?pairwise,?ddof])	expanding sample covariance
Expanding.skew(**kwargs)	Unbiased expanding skewness
Expanding.kurt(**kwargs)	Unbiased expanding kurtosis
Expanding.apply(func[,?args,?kwargs])	expanding function apply
Expanding.quantile(quantile,?**kwargs)	expanding quantile

指数权重移动窗口：

Function	Describe
EWM.mean(*args,?**kwargs)	exponential weighted moving average
EWM.std([bias])	exponential weighted moving stddev
EWM.var([bias])	exponential weighted moving variance
EWM.corr([other,?pairwise])	exponential weighted sample correlation
EWM.cov([other,?pairwise,?bias])	exponential weighted sample covariance