python dataframe group rows based on row num

Question

I have a dataframe with 40 rows, and I want to iterate over it so I will have 4 iteration with 10 rows each, serially.

So group#0 will be rows 0-9 , group#1 will be rows 10-19 and so on.

How can I do it?

You should write your question in [a Minimal, Reproducible Example](https://stackoverflow.com/help/minimal-reproducible-example) — Amazing Things Around You, Jun 20 '19 at 12:28

score 0 · Answer 1 · answered Jun 20 '19 at 12:23

0

import pandas as pd
import numpy as np

df1 = {
    'State':['Arizona','Georgia','Newyork','Indiana','Florida'],
   'Score1':[4,47,55,74,31]}

df1 = pd.DataFrame(df1,columns=['State','Score1'])
print(df1)

We need to add value (here 430) to the index to generate row number and the result is stored in a new column as shown below.

df1['New_ID'] = df1.index + 430
print(df1)

answered Jun 20 '19 at 12:23

AB7098

36
2

Could you explain in your answer how to iterate over the dataframe now with your proposed solution, as was asked in the Question? – NOhs Jun 20 '19 at 12:28

score 0 · Accepted Answer · answered Jun 20 '19 at 12:27

2 solutions from this stackoverflow question : How to iterate over consecutive chunks of Pandas dataframe efficiently

I advise you to check the link.

Solution from DSM :

for k,g in df.groupby(np.arange(len(df))//10):
    print(k,g)

Solution from Ryan :

def chunker(seq, size):
    return (seq[pos:pos + size] for pos in xrange(0, len(seq), size))

for i in chunker(df,5):
    print i

python dataframe group rows based on row num

2 Answers2