I have a dataframe of 145 columns, one column is variable A and the rest are subsets of variable B. What I want is a new dataframe of two columns, A and B. I want to make sure all the B values in the new dataframe have the corresponding A values.
A simplified example of 'original' dataframe:
A B1 B2
0 1 6 11
1 2 7 12
2 3 8 13
3 4 9 14
4 5 10 15
And what I would like to achieve:
A B
0 1 6
1 2 7
2 3 8
3 4 9
4 5 10
5 1 11
6 2 12
7 3 13
8 4 14
9 5 15
I have tried to do it like this but have manage to only get the equivalent of B1 and A, the rest vanishes.
original_data = data[1:145]
filtered_data = pd.DataFrame(columns = ['A', 'B'])
columns = list(original_data)
for values in columns:
for row in pressure_data:
filtered_data["B"] = original_data[values]
filtered_data["A"] = data['A']
I'd appreciate any tips/advice! Many thanks.
