I have a csv file, when I read into pandas data frame, it looks like:
data = pd.read_csv(\'test1.csv\')
print(data)
output looks like:
You can try create dictionary of DataFrames by groupby, if column result has many different values:
print data
v1 v2 v3 result
0 12 31 31 0
1 34 52 4 1
2 32 4 5 1
3 7 89 2 0
datas = {}
for i, g in data.groupby('result'):
#print 'data_' + str(i)
#print g
datas.update({'data_' + str(i) : g.reset_index(drop=True)})
print datas['data_0']
v1 v2 v3 result
0 12 31 31 0
1 7 89 2 0
print datas['data_1']
v1 v2 v3 result
0 34 52 4 1
1 32 4 5 1