i have a sample pandas data frame:
import pandas as pd
df = {'ID': [73, 68,1,94,42,22, 28,70,47, 46,17, 19, 56, 33 ],
'CloneID': [1, 1, 1, 1, 1, 2, 2, 3, 3, 3, 4, 4, 4, 4 ],
'VGene': ['64D', '64D', '64D', 61, 61, 61, 311, 311, 311, 311, 311, 311, 311, 311]}
df = pd.DataFrame(df)
it looks like this:
df
Out[7]:
CloneID ID VGene
0 1 73 64D
1 1 68 64D
2 1 1 64D
3 1 94 61
4 1 42 61
5 2 22 61
6 2 28 311
7 3 70 311
8 3 47 311
9 3 46 311
10 4 17 311
11 4 19 311
12 4 56 311
13 4 33 311
i want to write a simple script to output each cloneID to a different output file. so in this case there would be 4 different files. the first file would be named 'CloneID1.txt' and it would look like this:
CloneID ID VGene
1 73 64D
1 68 64D
1 1 64D
1 94 61
1 42 61
second file would be named 'CloneID2.txt':
CloneID ID VGene
2 22 61
2 28 311
third file would be named 'CloneID3.txt':
CloneID ID VGene
3 70 311
3 47 311
3 46 311
and last file would be 'CloneID4.txt':
CloneID ID VGene
4 17 311
4 19 311
4 56 311
4 33 311
the code i found online was:
import pandas as pd
data = pd.read_excel('data.xlsx')
for group_name, data in data.groupby('CloneID'):
with open('results.csv', 'a') as f:
data.to_csv(f)
but it outputs everything to one file instead of multiple files.
You can do something like the following:
In [19]:
gp = df.groupby('CloneID')
for g in gp.groups:
print('CloneID' + str(g) + '.txt')
print(gp.get_group(g).to_csv())
CloneID1.txt
,CloneID,ID,VGene
0,1,73,64D
1,1,68,64D
2,1,1,64D
3,1,94,61
4,1,42,61
CloneID2.txt
,CloneID,ID,VGene
5,2,22,61
6,2,28,311
CloneID3.txt
,CloneID,ID,VGene
7,3,70,311
8,3,47,311
9,3,46,311
CloneID4.txt
,CloneID,ID,VGene
10,4,17,311
11,4,19,311
12,4,56,311
13,4,33,311
So here we iterate over the groups in for g in gp.groups:
and we use this to create the result file path name and call to_csv
on the group so the following should work for you:
gp = df.groupby('CloneID')
for g in gp.groups:
path = 'CloneID' + str(g) + '.txt'
gp.get_group(g).to_csv(path)
Actually the following would be even simpler:
gp = df.groupby('CloneID')
gp.apply(lambda x: x.to_csv('CloneID' + str(x.name) + '.txt'))
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