def standardize(x, offset=None, scale=None):
    """   
    This is function for standarization of input series.

    **Args:**

    * `x` : series (1 dimensional array)

    **Kwargs:**

    * `offset` : offset to remove (float). If not given, \
        the mean value of `x` is used.

    * `scale` : scale (float). If not given, \
        the standard deviation of `x` is used.
        
    **Returns:**

    * `xs` : standardized series
    """
    if offset == None:
        offset = np.array(x).mean()
    else:
        try:
            offset = float(offset)
        except:
            raise ValueError('The argument offset is not None or float') 
    if scale == None:
        scale = np.array(x).std()
    else:
        try:
            scale = float(scale)
        except:
            raise ValueError('The argument scale is not None or float')    
    try:
        x = np.array(x, dtype="float64")
    except:
        raise ValueError('The argument x is not numpy array or similar.')         
    return (x - offset) / scale
This is function for standarization of input series.

    **Args:**

    * `x` : series (1 dimensional array)

    **Kwargs:**

    * `offset` : offset to remove (float). If not given, \
        the mean value of `x` is used.

    * `scale` : scale (float). If not given, \
        the standard deviation of `x` is used.
        
    **Returns:**

    * `xs` : standardized series