My data frame has 6 columns and multiple rows. I would like to calculate how much the values in a row have increased or decreased (in percents) in relation to the index.
DataFrame such as::
a = np.random.randint(0,70, (10,7))
df = pd.DataFrame(np.random.randint(0,70, (10,7)), columns=['A', 'B', 'C', 'D', 'E', 'F', 'G'])
df = df.set_index(['C'])
>Solution :
something like this?
(df/df.index.values.reshape(-1,1)-1)*100
output
C A B D E F G
--- --------- -------- --------- -------- --------- --------
30 100 -53.3333 33.3333 53.3333 66.6667 106.667
51 -94.1176 0 -23.5294 -70.5882 3.92157 -43.1373
32 93.75 -31.25 93.75 59.375 -12.5 34.375
63 -6.34921 -60.3175 -1.5873 -11.1111 -73.0159 3.1746
52 3.84615 -28.8462 -9.61538 23.0769 -15.3846 -11.5385
41 4.87805 -36.5854 -21.9512 14.6341 36.5854 -82.9268
30 -33.3333 -20 30 -46.6667 -80 -20
61 -78.6885 -13.1148 -31.1475 -31.1475 -49.1803 -21.3115
7 700 0 700 785.714 200 871.429
16 75 37.5 -12.5 56.25 112.5 143.75