Q-jpddlmZddlmZmZddlmZddlmZm Z m Z m Z  ddededed e d ed ed efd Z y))Series)DictLikeInt)Imports) v_lowerboundv_offsetv_seriesv_talibNcloselengthddoftaliboffsetkwargsreturnc t|dd}d|vr|dt|d}n|}t|t||}|yt |trd|cxkr|krnn t|nd}t |}t |}tdr|rddlm }|||} n"|j||j|} |dk7r| j|} d |vr| j|d d d || _d | _| S)aRolling Variance Calculates a rolling Variance. Parameters: close (Series): ```close``` Series length (int): The period. Default: ```30``` ddof (int): Delta Degrees of Freedom. Default: ```1``` talib (bool): If installed, use TA Lib. Default: ```True``` offset (int): Post shift. Default: ```0``` Other Parameters: fillna (value): ```pd.DataFrame.fillna(value)``` Returns: (Series): 1 column Note: * TA Lib does not have a ```ddof``` parameter. * The divisor used in calculations is: ```N - ddof```, where ```N``` is the number of elements. To use ```ddof```, set ```talib=False```.  min_periodsNrr)VAR)rfillnaT)inplaceVAR_ statistics)rintr max isinstancer rrrrrollingvarshiftrnamecategory) r r r rrrrmode_talrvariances k/Users/jameslopez/projects/TradingBot25/.venv/lib/python3.12/site-packages/pandas_ta/statistics/variance.pyr$r$ s8&!R (F6-#8#D&/0  UC 4 5E }"4-!t2Df2D3t9!Du~H f FwHuf%==[=AEEdK{>>&)6x($76(OHM$H O)NNNN)pandasrpandas_ta._typingrrpandas_ta.mapsrpandas_ta.utilsrrr r boolr$r&r%r-sb+"EE "&$(= == =!= =#+= =r&