iterrows pandas get next rows value

Question

I have a df in pandas

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

I want to iterate over rows in

Answer 1

a combination of answers gave me a very fast running time. using the shift method to create new column of next row values, then using the row_iterator function as @alisdt did, but here i changed it from iterrows to itertuples which is 100 times faster.

my script is for iterating dataframe of duplications in different length and add one second for each duplication so they all be unique.

# create new column with shifted values from the departure time column
df['next_column_value'] = df['column_value'].shift(1)
# create row iterator that can 'save' the next row without running for loop
row_iterator = df.itertuples()
# jump to the next row using the row iterator
last = next(row_iterator)
# because pandas does not support items alteration i need to save it as an object
t = last[your_column_num]
# run and update the time duplications with one more second each
for row in row_iterator:
    if row.column_value == row.next_column_value:
         t = t + add_sec
         df_result.at[row.Index, 'column_name'] = t
    else:
         # here i resetting the 'last' and 't' values
         last = row
         t = last[your_column_num]

Hope it will help.