I have the following data:
df = pd.DataFrame({'id' : [1,2,3,4,5,6], 'category' : [1,3,1,4,3,2], 'day1' : [10,20,30,40,50,60], 'day2' : [1,2,3,4,5,7], 'day3' : [0,1,2,3,7,9] })
df
id category day1 day2 day3
0 1 1 10 1 0
1 2 3 20 2 1
2 3 1 30 3 2
3 4 4 40 4 3
4 5 3 50 5 7
5 6 2 60 7 9
It is time series data and I need to prepare the new DataFrame as records of ('id', 'category', 'day'):
df = pd.DataFrame({'id' : [1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,6,6,6], 'category' : [1,1,1,3,3,3,1,1,1,4,4,4,3,3,3,2,2,2], 'day' : [10,1,0,20,2,1,30,3,2,40,4,3,50,5,7,60,7,9]})
df
id category day
0 1 1 10
1 1 1 1
2 1 1 0
3 2 3 20
4 2 3 2
5 2 3 1
6 3 1 30
7 3 1 3
8 3 1 2
9 4 4 40
10 4 4 4
11 4 4 3
12 5 3 50
13 5 3 5
14 5 3 7
15 6 2 60
16 6 2 7
17 6 2 9
But I don't know how to do it without looping by every DataFrame cell