Sorry for the title which is maybe more complicated than the problem itself ;)
I have de following pandas dataframe
grh anc anc1 anc2 anc3 anc4 anc5 anc6 anc7
1 2 5 0.10000 0.12000 0.1800 0.14000 0.15000 0.1900 0.20000
2 3 7 0.03299 0.05081 0.0355 0.02884 0.03054 0.0332 0.03115
3 4 3 0.00000 0.00000 0.0000 0.00000 0.00000 0.0000 0.00000
4 5 4 0.00000 0.00000 0.0000 0.00000 0.00000 0.0000 0.00000
5 6 1 0.10000 0.10000 0.1000 0.10000 0.10000 0.1000 0.10000
anc8 anc9 anc10
1 0.10000 0.21000 0.24000
2 0.02177 0.04903 0.04399
3 0.00000 0.00000 0.00000
4 0.00000 0.00000 0.00000
5 0.10000 0.10000 0.10000
I would like to add new columns with a forloop lap1, lap2, ....depending on the values of variable anc. For instance, on the first row, anc=5 so lap1 should be equal to the value of anc5 (0.1500), lap2 equal to anc6 (0.1900)...on the second row lap1=anc7 (0.03115), lap2=anc8 (0.02177),...
So, the output should look like
grh anc anc1 anc2 anc3 anc4 anc5 anc6 anc7 anc8 anc9 anc10 lap1 lap2 lap3
2 5 0.10000 0.12000 0.18000 0.14000 0.15000 0.19000 0.20000 0.1000 0.21000 0.24000 0.15000 0.19000 0.20000
3 7 0.03299 0.05081 0.0355 0.02884 0.03054 0.0332 0.03115 0.02177 0.04903 0.04399 0.03115 0.02177 0.04903
4 3 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
5 4 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
6 1 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000 0.10000
I've tried something very basic, but doesn't seem to work
for i in range(1,4):
j=df['anc']+i
df['lap'+str(i)]= df['anc'+str(j)]
I would be very grateful if you have any idea. Thks
A bit of a 'brute-force' approach, but I can't see how you can do this otherwise:
df[[f"lap{i}" for i in range(1,4)]]= \
df.apply(lambda x: \
pd.Series({f"lap{j}": x[f"anc{int(j+x['anc']-1)}"] for j in range(1,4)}) \
, axis=1)
(Assuming per your sample, that you have max lap at 3)