![]() ![]() ![]() get_duplicates () #Get all the duplicate rows dupes = changes. drop_duplicates ( subset =, take_last = True ) #We want to know where the duplicate account numbers are, that means there have been changes dupe_accts = changes. concat (, ignore_index = True ) # Let's see what changes in the main columns we care about changes = full_set. read_excel ( 'sample-address-new.xlsx', 'Sheet1', na_values = ) old = "old" new = "new" #Join all the data together and ignore indexes so it all gets added full_set = pd. read_excel ( 'sample-address-old.xlsx', 'Sheet1', na_values = ) new = pd. ![]() format ( * x ) # Read in the two files but call the data old and new and create columns to track old = pd. Import pandas as pd import numpy as np # Define the diff function to show the changes in each field def report_diff ( x ): return x if x = x else ' '. ![]()
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