Q: AttributeError: ("module 'pandas' has no attribute 'rolling_std'" I have an error ocurred in a code in Python- Jupyter. I am new in python.
    Here is the code:
```import pandas as pd
import numpy as np

def score(SeriesTemps, window):
    # normalization
    SeriesTempsNorm=(SeriesTemps-SeriesTemps.mean())/(SeriesTemps[:-1].std() + 1)  # "+ 1" to avoid division by 0

    #model 
    rollingStd = SeriesTempsNorm.apply(lambda x : pd.rolling_std(x,window=window), axis = 0)
    scoreSeason = rollingStd.iloc[-1] / rollingStd.iloc[window-1]   #division of the last element by the first no NaN (offset du to the computation of the rolling std)
    scoreYear = rollingStd.iloc[-1] / rollingStd.iloc[:-1].mean()  #mean variance as denominator


    def mergeScore(scoreSeason, scoreYear):    # we take the right score
        if scoreSeason == np.inf:     # if the Seasonal score is inf, their is no seasonnality effect, we take the score over the past year to avoid inf score
            return scoreYear
        else: return min(scoreSeason,scoreYear)      # else it might be a seasonnality effect, then we take the season score

    score = scoreSeason.combine(other = scoreYear, func= lambda x, y : mergeScore(x,y))

    return score

def groupedScore(SeriesTemps):

    # normalization
    SeriesTempsNorm=(SeriesTemps-SeriesTemps.mean())/(SeriesTemps[:-1].std() + 1) # "+ 1" to avoid division by 0

    #model
    return SeriesTempsNorm[1:].std() / SeriesTempsNorm[:-1].std() 

def scores_computation(SeriesTemps,group,window):
    if group < 6:
        # compute the score with concidering seasonnality 
        return score(SeriesTemps,window)
    else:
        # compute the score without considering seasonnality
        return groupedScore(SeriesTemps)

The error ocurred where it's used pd.rolling_std. I don't know why it doesn't work beacuse I used this code before and it worked perfect.
Anyone knows what happen?
I saw the answer to the same question but it doesn't work for me.
Thank you
