如何使用 Dataframe 应用函数来规范化数据

Question

I'm trying to normalize new data with the mean and std values which I already have got.

t = np.array([[1,2,3],
     [4,5,6],
     [7,8,9]])

tt = np.array([[1,1,1],
     [100,100,100]])

a = pd.DataFrame(t, columns=['a','b','c'])
b = pd.DataFrame(tt, columns=['a', 'b', 'c'], index=['mean', 'std'])

def standardize(x, y):
    return (x - y.loc['mean']) / y.loc['std']

a.apply(standardize(a,b))

I want to get normalized dataframe that each values is calculated by 'b' dataframe's mean and std on each columns with apply function

ex) a[0]['a'] = (a[0]['a'] - b['mean']['a']) / b['std'][a]

any better ways would be fine as well. Thanks..

Answer 1

(a-b.loc['mean'])/b.loc['std']

如果您将b定义为b=bT ，则

(a-b['mean'])/b['std']

Answer 2

You already have it. Do standardize(a,b) instead of a.apply(standardize(a,b)) .