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

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I have a df as shown below.

df:

ID   Job   Salary
1    A     100
2    B     200
3    B     20
4    C     150
5    A     500
6    A     600
7    A     200
8    B     150
9    C     110
10   B     200
11   B     220
12   A     150
13   C     20
14   B     50

I would like to split the df into 6 equal parts based on the number of rows. Expected Output df1:

ID   Job   Salary
1    A     100
2    B     200
3    B     20

df2:

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

df3:

ID   Job   Salary
7    A     200
8    B     150

df4:

ID   Job   Salary
9    C     110
10   B     200

df5:

ID   Job   Salary
11   B     220
12   A     150

df6:

ID   Job   Salary
13   C     20
14   B     50

Note: Since there are 14 rows first two dfs can have 3 rows and the remaining 4 dfs should have 2 rows.

And I would like to save all dfs as csv dynamically

pandas dataframe python
1 Answers

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]
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