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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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