假设我有以下数据框,并希望按ys进行分组:
xs ys
0 0 0
1 1 0
2 2 1
3 3 1
我可以通过运行
来做到这一点grouped = df.groupby('ys')
我可以很好地遍历这个新的groupby对象,但我想要一个group
在以下循环中访问的数据帧列表:
for name, group in grouped:
do_something(group)
这可能吗?
答案 0 :(得分:10)
当然,只需迭代群组!
>>> import pandas as pd, numpy as np
>>> df = pd.DataFrame(dict(xs=list(range(4)), ys=[0,0,1,1]))
>>> df
xs ys
0 0 0
1 1 0
2 2 1
3 3 1
>>> grouped = df.groupby('ys')
>>> dataframes = [group for _, group in grouped]
>>> dataframes
[ xs ys
0 0 0
1 1 0, xs ys
2 2 1
3 3 1]
>>>