CODEWITHSUNDEEP
pandasmergeappendconcatenationunion
Ian
Ian

Reputation: 35

Combine two dataframes of dfiferent size into one

I am looking to append two dataframes together that are different in size. I have tried append, merge, concat - I know I am close but missing something fairly easy. I am new to Python learning on my own.

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

Desired Output

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

Upvotes: 1

Views: 36

Answers (1)

Arun Palanisamy
Arun Palanisamy

Reputation: 5459

You can use merge. But you would need a common column to join both the dataframes. Since you don't have any common column, one way is to create a temporary column just for join and then drop it. Something like below.

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)

Upvotes: 1

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