Python 列计算 groupby后计算 更改数据类型

import pandas as pd
import  numpy as np

df = pd.DataFrame({'key1':list('aabba'),
                  'key2': ['one','two','one','two','one'],
                  'data1': ['1','3','5','7','9'],
                  'data2': ['2','4','6','8','10']})

df[['data1','data2']]=df[['data1','data2']].astype('int')/10

# df=df/10
print(df)
grouped1 = df['data1'].astype(float).groupby(df['key1']).mean()     #先将data1转换成浮点型，然后分组求均值
grouped1=grouped1/10
print(grouped1)

  key1 key2  data1  data2
0    a  one    0.1    0.2
1    a  two    0.3    0.4
2    b  one    0.5    0.6
3    b  two    0.7    0.8
4    a  one    0.9    1.0
key1
a    0.043333
b    0.060000
Name: data1, dtype: float64

Process finished with exit code 0