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

1. Creating a dataframe with 70% values of original dataframe
   part_1 = df.sample(frac = 0.7)

2. Creating dataframe with rest of the 30% values
   part_2 = df.drop(part_1.index)