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 — Anurag Dabas
– Anurag Dabas, Commented May 15, 2021 at 6:57
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
– fqntom, Commented May 15, 2021 at 7:00

Paras Gupta · Accepted Answer · 2021-05-15 07:28:11Z

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, 2021 at 7:28

answered May 15, 2021 at 7:14

Paras Gupta

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3 Comments

Paras Gupta Over a year ago

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

fqntom Over a year ago

Well in fact df.iloc[index-1] doesnt work at my index is a datetime and not an integer

Paras Gupta Over a year ago

Editted that, it should work for any index

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