justinhchae

# same iterrows() solution with change log
curr_year = 2020
past_year = 2010
change_log = []
# loop through index and rows of df
for idx, row in df.iterrows():
    if row[col1].year > curr_year:
        new_year = row[col2].year
        # save reference data as tuple
        records = tuple((row['case_id']

justinhchae

# iterate through a DataFrame with iterrows()
curr_year = 2020
past_year = 2010
# loop through index and rows of df
for idx, row in df.iterrows():
  # compare years as integers
  if row[col1].year > curr_year:
     
     # return received_date's year as integer
     new_year = row[col2].year

justinhchae

import pandas as pd


col1 = 'event_date'
col_new = str(col1 + '_new')
col2 = 'received_date'
curr_year = 2020
past_year = 2010

# given a dataframe df with col1 and col2 as datetime columns