遍历多个数据框

Question

##1    
M_members = [1000 , 1450, 1900]  
M = pd.DataFrame(M_members)

##2
a_h_members = [0.4 , 0.6 , 0.8 ]
a_h = pd.DataFrame(a_h_members) 

##3
d_h_members = [0.1 , 0.2 ]
d_h = pd.DataFrame(d_h_members)

因为我想要的输出是数据帧形式：

1000 0.4 0.1
1000 0.4 0.2
1000 0.6 0.1
1000 0.6 0.2
1000 0.8 0.1
1000 0.8 0.2
1450 0.4 0.1
1450 0.4 0.2
1450 0.6 0.1
1450 0.6 0.2
1450 0.8 0.1
1450 0.8 0.2
1900 0.4 0.1
1900 0.4 0.2
1900 0.6 0.1
1900 0.6 0.2
1900 0.8 0.1
1900 0.8 0.2

实际上我想为更多的数据帧做这个循环。

Answer 1

使用itertools.product

>>> import itertools
>>> pd.DataFrame(itertools.product(*[M_members, a_h_members, d_h_members]))

       0    1    2
0   1000  0.4  0.1
1   1000  0.4  0.2
2   1000  0.6  0.1
3   1000  0.6  0.2
4   1000  0.8  0.1
5   1000  0.8  0.2
6   1450  0.4  0.1
7   1450  0.4  0.2
8   1450  0.6  0.1
9   1450  0.6  0.2
10  1450  0.8  0.1
11  1450  0.8  0.2
12  1900  0.4  0.1
13  1900  0.4  0.2
14  1900  0.6  0.1
15  1900  0.6  0.2
16  1900  0.8  0.1
17  1900  0.8  0.2

Answer 2

如果您从数据帧开始，您可以使用重复的交叉合并：

dfs = [M, a_h, d_h]

from functools import reduce

out = (reduce(lambda a,b: a.merge(b, how='cross'), dfs)
      .set_axis(range(len(dfs)), axis=1)
      )

输出：

       0    1    2
0   1000  0.4  0.1
1   1000  0.4  0.2
2   1000  0.6  0.1
3   1000  0.6  0.2
4   1000  0.8  0.1
5   1000  0.8  0.2
6   1450  0.4  0.1
7   1450  0.4  0.2
8   1450  0.6  0.1
9   1450  0.6  0.2
10  1450  0.8  0.1
11  1450  0.8  0.2
12  1900  0.4  0.1
13  1900  0.4  0.2
14  1900  0.6  0.1
15  1900  0.6  0.2
16  1900  0.8  0.1
17  1900  0.8  0.2

Answer 3

根据您的数据大小，pyjanitor 中的 expand_grid 可能有助于提高性能：

# pip install pyjanitor
import janitor as jn
import pandas as pd

others = {'a':M, 'b':a_h, 'c':d_h}
jn.expand_grid(others = others)

       a    b    c
       0    0    0
0   1000  0.4  0.1
1   1000  0.4  0.2
2   1000  0.6  0.1
3   1000  0.6  0.2
4   1000  0.8  0.1
5   1000  0.8  0.2
6   1450  0.4  0.1
7   1450  0.4  0.2
8   1450  0.6  0.1
9   1450  0.6  0.2
10  1450  0.8  0.1
11  1450  0.8  0.2
12  1900  0.4  0.1
13  1900  0.4  0.2
14  1900  0.6  0.1
15  1900  0.6  0.2
16  1900  0.8  0.1
17  1900  0.8  0.2

您可以降低列级别或展平它：

jn.expand_grid(others = others).droplevel(axis = 1, level = 1)

       a    b    c
0   1000  0.4  0.1
1   1000  0.4  0.2
2   1000  0.6  0.1
3   1000  0.6  0.2
4   1000  0.8  0.1
5   1000  0.8  0.2
6   1450  0.4  0.1
7   1450  0.4  0.2
8   1450  0.6  0.1
9   1450  0.6  0.2
10  1450  0.8  0.1
11  1450  0.8  0.2
12  1900  0.4  0.1
13  1900  0.4  0.2
14  1900  0.6  0.1
15  1900  0.6  0.2
16  1900  0.8  0.1
17  1900  0.8  0.2

遍历多个数据框

Iterating over multiple dataframes

python

loops

dataframe

pandas