iterrows pandas get next rows value

Firstly, your "messy way" is ok, there's nothing wrong with using indices into the dataframe, and this will not be too slow. iterrows() itself isn't terribly fast.

A version of your first idea that would work would be:

row_iterator = df.iterrows()
_, last = row_iterator.next()  # take first item from row_iterator
for i, row in row_iterator:
    print(row['value'])
    print(last['value'])
    last = row

The second method could do something similar, to save one index into the dataframe:

last = df.irow(0)
for i in range(1, df.shape[0]):
    print(last)
    print(df.irow(i))
    last = df.irow(i)

When speed is critical you can always try both and time the code.

There is a pairwise() function example in the itertools document:

from itertools import tee, izip
def pairwise(iterable):
    "s -> (s0,s1), (s1,s2), (s2, s3), ..."
    a, b = tee(iterable)
    next(b, None)
    return izip(a, b)

import pandas as pd
df = pd.DataFrame(['AA', 'BB', 'CC'], columns = ['value'])

for (i1, row1), (i2, row2) in pairwise(df.iterrows()):
    print i1, i2, row1["value"], row2["value"]

Here is the output:

0 1 AA BB
1 2 BB CC

But, I think iter rows in a DataFrame is slow, if you can explain what's the problem you want to solve, maybe I can suggest some better method.