将两个不同大小的数据框合二为一

Question

我希望将两个大小不同的数据框附加在一起。我试过追加、合并、连接——我知道我很接近但错过了一些相当容易的东西。我是自学 Python 的新手。

import pandas as pd

data1 = [['lj', 22.72, 37, 9.8], ['nc', 13.24, 30.9, 4.4],['bm', 13.77, 26.3, 9.3], ['jl', 12, 25.9, 7.2]]
df = pd.DataFrame(data1, columns= ['Name', 'Proj', 'Ceil', 'Floor'])
print(df)

data2 = [['0', 50, 55, 25, 20], ['1', 49, 54, 24, 19], ['2', 33, 2, 27, 18], ['3', 14, 60, 17, 35], ['4', 45, 40, 48, 10], ['5', 10, 15, 35, 30], ['6', 57, 75, 27, 27], ['7', 22, 17, 18, 11], ['8', 3, 6, 26, 36], ['9', 12, 32, 5, 3]]
df2 = pd.DataFrame(data2, columns=['sim_id', 'lj', 'nc', 'bn', 'jl'])
print(df2)

	Name	Proj	Ceil	Floor
0	lj	22.72	37	9.8
1	nc	13.24	30.9	4.4
2	bm	13.77	26.3	9.3
3	jl	12	25.9	7.2

	sim_id	lj	nc	bn	jl
0	0	50	55	25	20
1	1	49	54	24	19
2	2	33	2	27	18
3	3	14	60	17	35
4	4	45	40	48	10
5	5	10	15	35	30
6	6	57	75	27	27
7	7	22	17	18	11
8	8	3	6	26	36
9	9	12	32	5	3

期望的输出

	Name	Proj	Ceil	Floor	sim_id	proj
0	lj	22.72	37	9.8	0	50
0	lj	22.72	37	9.8	1	49
0	lj	22.72	37	9.8	2	33
0	lj	22.72	37	9.8	3	14
0	lj	22.72	37	9.8	4	45
0	lj	22.72	37	9.8	5	10
0	lj	22.72	37	9.8	6	57
0	lj	22.72	37	9.8	7	22
0	lj	22.72	37	9.8	8	3
0	lj	22.72	37	9.8	9	12
1	nc	13.24	30.9	4.4	0	55
1	nc	13.24	30.9	4.4	1	54
1	nc	13.24	30.9	4.4	2	2
1	nc	13.24	30.9	4.4	3	60
1	nc	13.24	30.9	4.4	4	40
1	nc	13.24	30.9	4.4	5	15
1	nc	13.24	30.9	4.4	6	75
1	nc	13.24	30.9	4.4	7	17
1	nc	13.24	30.9	4.4	8	6
1	nc	13.24	30.9	4.4	9	32
2	bm	13.77	26.3	9.3	0	25
2	bm	13.77	26.3	9.3	1	24
2	bm	13.77	26.3	9.3	2	27
2	bm	13.77	26.3	9.3	3	17
2	bm	13.77	26.3	9.3	4	48
2	bm	13.77	26.3	9.3	5	35
2	bm	13.77	26.3	9.3	6	27
2	bm	13.77	26.3	9.3	7	18
2	bm	13.77	26.3	9.3	8	26
2	bm	13.77	26.3	9.3	9	5
3	jl	12	25.9	7.2	0	20
3	jl	12	25.9	7.2	1	19
3	jl	12	25.9	7.2	2	18
3	jl	12	25.9	7.2	3	35
3	jl	12	25.9	7.2	4	10
3	jl	12	25.9	7.2	5	30
3	jl	12	25.9	7.2	6	27
3	jl	12	25.9	7.2	7	11
3	jl	12	25.9	7.2	8	36
3	jl	12	25.9	7.2	9	3

Answer 1

您可以使用merge。但是您需要一个公共列来连接两个数据框。由于您没有任何公共列，因此一种方法是创建一个临时列仅用于连接，然后将其删除。如下所示。

import pandas as pd

data1 = [['lj', 22.72, 37, 9.8], ['nc', 13.24, 30.9, 4.4],['bm', 13.77, 26.3, 9.3], ['jl', 12, 25.9, 7.2]]
df = pd.DataFrame(data1, columns= ['Name', 'Proj', 'Ceil', 'Floor'])
print(df)

data2 = [['0', 50, 55, 25, 20], ['1', 49, 54, 24, 19], ['2', 33, 2, 27, 18], ['3', 14, 60, 17, 35], ['4', 45, 40, 48, 10], ['5', 10, 15, 35, 30], ['6', 57, 75, 27, 27], ['7', 22, 17, 18, 11], ['8', 3, 6, 26, 36], ['9', 12, 32, 5, 3]]
df2 = pd.DataFrame(data2, columns=['sim_id', 'lj', 'nc', 'bn', 'jl'])
print(df2)
#add the below lines
df['temp']=1
df2['temp']=1
df3 = pd.merge(df,df2, on=['temp'])
df3 = df3.drop('temp', axis=1)
print(df3)