Access previous row while iterating on rows of a dataframe using iterrows

Question

I am iterating through the rows of a dataframe using iterrows:

for index, row in df.iterrows():
    pass

Given that the index here contains datetime objects, how can we easily access the row at the previous index (i-1) while being at level index (i) ?

Thanks

Does this answer your question? [Python Pandas iterrows() with previous values](https://stackoverflow.com/questions/25473153/python-pandas-iterrows-with-previous-values) — Anurag Dabas, May 15 '21 at 06:57
Yes I have seen this before asking my question... and I am not so sure how they convert an datetime to int using int(index)... — fqntom, May 15 '21 at 07:00

Paras Gupta · Accepted Answer · 2021-05-15T07:28:11.570

2

You can try below

row_ = None
for index, row in df.iterrows():
    # processing logic here (use row_ as prev row and "row" as current)
    row_ = row

row_ will be None if index is 0 else it will be previous row. This logic should work for any index type

edited May 15 '21 at 07:28

answered May 15 '21 at 07:14

Paras Gupta

was a type. fixed it :P. Other simple way is using row_ initialized as None out side loop and after using it, you can set row_ as row at the end of the loop – Paras Gupta May 15 '21 at 07:19
Well in fact df.iloc[index-1] doesnt work at my index is a datetime and not an integer – fqntom May 15 '21 at 07:21
Editted that, it should work for any index – Paras Gupta May 15 '21 at 07:23

1 Answers1