i have the following dataset:
A B C D E F 154.6175111 148.0112337 155.7859835 1 1 x 255 253.960131 242.5382584 1 1 x 251.9665958 235.1105659 185.9121703 1 1 x 137.9974994 225.3985177 254.4420772 1 1 x 85.74722877 116.7060415 158.4608395 1 1 x 123.6969939 140.0524405 132.6798037 1 1 x 133.3251695 80.08976196 38.81201612 1 1 y 118.0718812 243.5927927 255 1 1 y 189.5557302 139.9046713 91.90519519 1 1 y 172.3117291 188.000268 129.8155501 1 1 y 48.07634611 21.9183119 25.99669279 1 1 y 23.40525987 8.395857933 25.62371342 1 1 y 228.753009 164.0697727 172.6624107 1 1 z 203.3405006 173.9368303 189.8103708 1 1 z 184.9801932 117.1591341 87.94739034 1 1 z 29.55251224 46.03945452 70.7433477 1 1 z 143.6159623 120.6170926 155.0736604 1 1 z 142.5421179 128.8916843 169.6013111 1 1 z
i want to combine x y z into another dataframe like this:
A B C D E F 154.6175111 148.0112337 155.7859835 1 1 x ->first x value 133.3251695 80.08976196 38.81201612 1 1 y ->first y value 228.753009 164.0697727 172.6624107 1 1 z ->first z value
and i want these dataframes for each x y z value like first, second third and so on.
how can i select and combine them?
desired output:
A B C D E F 154.6175111 148.0112337 155.7859835 1 1 x 133.3251695 80.08976196 38.81201612 1 1 y 228.753009 164.0697727 172.6624107 1 1 z A B C D E F 255 253.960131 242.5382584 1 1 x 118.0718812 243.5927927 255 1 1 y 203.3405006 173.9368303 189.8103708 1 1 z A B C D E F 251.9665958 235.1105659 185.9121703 1 1 x 189.5557302 139.9046713 91.90519519 1 1 y 184.9801932 117.1591341 87.94739034 1 1 z A B C D E F 137.9974994 225.3985177 254.4420772 1 1 x 172.3117291 188.000268 129.8155501 1 1 y 29.55251224 46.03945452 70.7433477 1 1 z A B C D E F 85.74722877 116.7060415 158.4608395 1 1 x 48.07634611 21.9183119 25.99669279 1 1 y 143.6159623 120.6170926 155.0736604 1 1 z A B C D E F 123.6969939 140.0524405 132.6798037 1 1 x 23.40525987 8.395857933 25.62371342 1 1 y 142.5421179 128.8916843 169.6013111 1 1 z
Advertisement
Answer
Use GroupBy.cumcount
for counter and then loop by another groupby object:
g = df.groupby('F').cumcount() for i, g in df.groupby(g): print (g)