How to Split a Data Frame

Split a data frame into six equal parts based on number of rows without knowing the number of rows - pandas

You can use np.array_split():

dfs = np.array_split(df, 6)

for index, df in enumerate(dfs):
    df.to_csv(f'df{index+1}.csv')

>>> print(dfs)

[   ID Job  Salary
 0   1   A     100
 1   2   B     200
 2   3   B      20,

    ID Job  Salary
 3   4   C     150
 4   5   A     500
 5   6   A     600,

    ID Job  Salary
 6   7   A     200
 7   8   B     150,

    ID Job  Salary
 8   9   C     110
 9  10   B     200,

     ID Job  Salary
 10  11   B     220
 11  12   A     150,

     ID Job  Salary
 12  13   C      20
 13  14   B      50]

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]

Pandas Split Dataframe into two Dataframes at a specific row

iloc

df1 = datasX.iloc[:, :72]
df2 = datasX.iloc[:, 72:]

(iloc docs)

How to split data frame into x and y

The correct way to slice is x = train.iloc[:, 0:2].

Split a pandas dataframe into two dataframes efficiently based on some condition

IICU

Use boolean select

m=df.score>15

Lessthan15=df[~m]
Morethan15=df[m]

Morethan15

LessThan15

Split a dataframe into smaller dataframes in R using dplyr

We may use gl to create the grouping column in group_split

library(dplyr)
df1 %>%
      group_split(grp = as.integer(gl(n(), 59, n())), .keep = FALSE)

---

Related Topics