How to split a DataFrame in pandas in predefined percentages?
Use numpy.split
:
a, b, c = np.split(df, [int(.2*len(df)), int(.5*len(df))])
Sample:
np.random.seed(100)
df = pd.DataFrame(np.random.random((20,5)), columns=list('ABCDE'))
#print (df)
a, b, c = np.split(df, [int(.2*len(df)), int(.5*len(df))])
print (a)
A B C D E
0 0.543405 0.278369 0.424518 0.844776 0.004719
1 0.121569 0.670749 0.825853 0.136707 0.575093
2 0.891322 0.209202 0.185328 0.108377 0.219697
3 0.978624 0.811683 0.171941 0.816225 0.274074
print (b)
A B C D E
4 0.431704 0.940030 0.817649 0.336112 0.175410
5 0.372832 0.005689 0.252426 0.795663 0.015255
6 0.598843 0.603805 0.105148 0.381943 0.036476
7 0.890412 0.980921 0.059942 0.890546 0.576901
8 0.742480 0.630184 0.581842 0.020439 0.210027
9 0.544685 0.769115 0.250695 0.285896 0.852395
print (c)
A B C D E
10 0.975006 0.884853 0.359508 0.598859 0.354796
11 0.340190 0.178081 0.237694 0.044862 0.505431
12 0.376252 0.592805 0.629942 0.142600 0.933841
13 0.946380 0.602297 0.387766 0.363188 0.204345
14 0.276765 0.246536 0.173608 0.966610 0.957013
15 0.597974 0.731301 0.340385 0.092056 0.463498
16 0.508699 0.088460 0.528035 0.992158 0.395036
17 0.335596 0.805451 0.754349 0.313066 0.634037
18 0.540405 0.296794 0.110788 0.312640 0.456979
19 0.658940 0.254258 0.641101 0.200124 0.657625
Creating a dataframe with 70% values of original dataframe
part_1 = df.sample(frac = 0.7)
Creating dataframe with rest of the 30% values
part_2 = df.drop(part_1.index)