CODEWITHSUNDEEP
pythonpandassplitdataframe
Boosted_d16
Boosted_d16

Reputation: 14062

Pandas Python DataFrames: How to split dataframes

I have a df

df = pd.DataFrame(np.random.randn(11,3))

           0         1         2
0   0.102645 -1.530977  0.408735
1   1.081442  0.615082 -1.457931
2   1.852951  0.360998  0.178162
3   0.726028  2.072609 -1.167996
4  -0.454453  1.310887 -0.969910
5  -0.098552 -0.718283  0.372660
6   0.334170 -0.347934 -0.626079
7  -1.034541 -0.496949 -0.287830
8   1.870277  0.508380 -2.466063
9   1.464942 -0.020060 -0.684136
10 -1.057930  0.295145  0.161727

How can I split this in a given number of subsections, lets say 2 for now.

Something like this 

           0         1         2
0   0.102645 -1.530977  0.408735
1   1.081442  0.615082 -1.457931
2   1.852951  0.360998  0.178162
3   0.726028  2.072609 -1.167996
4  -0.454453  1.310887 -0.969910

           0         1         2
5  -0.098552 -0.718283  0.372660
6   0.334170 -0.347934 -0.626079
7  -1.034541 -0.496949 -0.287830
8   1.870277  0.508380 -2.466063
9   1.464942 -0.020060 -0.684136
10 -1.057930  0.295145  0.161727

Ideally I would like to use np.array_split(df, 2) but it throws an error as its not an array.

Is there a built in function to do this? I don't particularly want to use df.loc[a:b] because its difficult to calculate the start and end depending on the given number of sub-dataframes needed.

Upvotes: 0

Views: 183

Answers (1)

mtadd
mtadd

Reputation: 2555

Try the following. It should return an array of n sub-dataframes if concatenated would return the original dataframe in question.

import math

def split(df, n):
    size = math.ceil(len(df) / n)
    return [ df[i:i + size] for i in range(0, len(df), size) ]

Upvotes: 1

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