Split a large pandas dataframe

Use np.array_split:

Docstring:
Split an array into multiple sub-arrays.

Please refer to the ``split`` documentation.  The only difference
between these functions is that ``array_split`` allows
`indices_or_sections` to be an integer that does *not* equally
divide the axis.

In [1]: import pandas as pd

In [2]: df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
   ...:                           'foo', 'bar', 'foo', 'foo'],
   ...:                    'B' : ['one', 'one', 'two', 'three',
   ...:                           'two', 'two', 'one', 'three'],
   ...:                    'C' : randn(8), 'D' : randn(8)})

In [3]: print df
     A      B         C         D
0  foo    one -0.174067 -0.608579
1  bar    one -0.860386 -1.210518
2  foo    two  0.614102  1.689837
3  bar  three -0.284792 -1.071160
4  foo    two  0.843610  0.803712
5  bar    two -1.514722  0.870861
6  foo    one  0.131529 -0.968151
7  foo  three -1.002946 -0.257468

In [4]: import numpy as np
In [5]: np.array_split(df, 3)
Out[5]: 
[     A    B         C         D
0  foo  one -0.174067 -0.608579
1  bar  one -0.860386 -1.210518
2  foo  two  0.614102  1.689837,
      A      B         C         D
3  bar  three -0.284792 -1.071160
4  foo    two  0.843610  0.803712
5  bar    two -1.514722  0.870861,
      A      B         C         D
6  foo    one  0.131529 -0.968151
7  foo  three -1.002946 -0.257468]

Be aware that np.array_split(df, 3) splits the dataframe into 3 sub-dataframes, while the split_dataframe function defined in @elixir's answer, when called as split_dataframe(df, chunk_size=3), splits the dataframe every chunk_size rows.

Example:

With np.array_split:

df = pd.DataFrame([1,2,3,4,5,6,7,8,9,10,11], columns=['TEST'])
df_split = np.array_split(df, 3)

...you get 3 sub-dataframes:

df_split[0] # 1, 2, 3, 4
df_split[1] # 5, 6, 7, 8
df_split[2] # 9, 10, 11

With split_dataframe:

df_split2 = split_dataframe(df, chunk_size=3)

...you get 4 sub-dataframes:

df_split2[0] # 1, 2, 3
df_split2[1] # 4, 5, 6
df_split2[2] # 7, 8, 9
df_split2[3] # 10, 11

Hope I'm right, and that this is useful.

I wanted to do the same, and I had first problems with the split function, then problems with installing pandas 0.15.2, so I went back to my old version, and wrote a little function that works very well. I hope this can help!

# input - df: a Dataframe, chunkSize: the chunk size
# output - a list of DataFrame
# purpose - splits the DataFrame into smaller chunks
def split_dataframe(df, chunk_size = 10000): 
    chunks = list()
    num_chunks = len(df) // chunk_size + 1
    for i in range(num_chunks):
        chunks.append(df[i*chunk_size:(i+1)*chunk_size])
    return chunks