Standardize columns of a dataframe 
Is there a function which standardizes data in the columns of a dataframe?  If not, can we introduce it? 

Through standardization, one can re-scale the data to have a mean of zero and standard deviation of one. I use standardization regularly for two purposes

- To facilitate interpretation of regression estimates. [Here ](https://stats.stackexchange.com/questions/29781/when-conducting-multiple-regression-when-should-you-center-your-predictor-varia)is a related discussion on Cross Validated. 
- To facilitate inspection of plots of time-series. Especially when I like to understand whether different series co-move over time, plotting them on the scale helps. 

So far, I use a simple function:

    def standardize(self, df, label):
        """
        standardizes a series with name ``label'' within the pd.DataFrame
        ``df''.
        """
        df = df.copy(deep=True)
        series = df.loc[:, label]
        avg = series.mean()
        stdv = series.std()
        series_standardized = (series - avg)/ stdv
    return series_standardized

I thought if there could be a function standardize which can be used similarly to the ``rolling`` function, such as ``df.standardize()``. 