我有一个有n行的数据帧，我想从m个类中随机为每一行分配一个类，这样所有类的比例都是相同的。
示例：
>>> classes = ['c1','c2','c3','c4']
>>> df = pd.DataFrame(np.random.randn(100, 5), columns = list("abcde"))
>>> df
a b c d e
0 -0.341559 1.499159 0.269614 -0.198663 -1.081290
1 -1.966477 1.902292 -0.092296 -1.730710 -1.342866
2 1.188634 -2.851902 1.130480 -0.495677 -0.569557
3 -0.816190 1.205463 1.157507 -0.217025 -0.160752
4 -2.001114 -0.818852 -0.696057 -0.874615 -0.577101
.. ... ... ... ... ...
95 0.502192 0.434275 0.358244 -0.763562 -0.787102
96 -1.071011 0.045387 0.297905 -0.120974 0.185418
97 2.458274 -1.852953 -0.049336 -0.150604 -0.292824
98 1.992513 -0.431639 0.566920 -1.289439 0.626914
99 0.685915 -0.723009 -0.168497 1.630057 1.587378
[100 rows x 5 columns]
预期输出：
>>> df
a b c d e class
0 -0.341559 1.499159 0.269614 -0.198663 -1.081290 c3
1 -1.966477 1.902292 -0.092296 -1.730710 -1.342866 c4
2 1.188634 -2.851902 1.130480 -0.495677 -0.569557 c2
3 -0.816190 1.205463 1.157507 -0.217025 -0.160752 c3
4 -2.001114 -0.818852 -0.696057 -0.874615 -0.577101 c1
.. ... ... ... ... ... ...
95 0.502192 0.434275 0.358244 -0.763562 -0.787102 c1
96 -1.071011 0.045387 0.297905 -0.120974 0.185418 c3
97 2.458274 -1.852953 -0.049336 -0.150604 -0.292824 c2
98 1.992513 -0.431639 0.566920 -1.289439 0.626914 c1
99 0.685915 -0.723009 -0.168497 1.630057 1.587378 c2
[100 rows x 6 columns]
等级比例相同的
这应该完成的工作
classes = ['c1','c2','c3','c4']
df = pd.DataFrame(np.random.randn(100, 5), columns = list("abcde"))
classes = np.repeat(classes, df.shape[0]/len(classes))
np.random.shuffle(classes)
df['class'] = classes