I need to update my main df (df_old) with new values and new rows belonging to the updating df (new_df):
df_old:
df_new:
This is the final result I want to get:
As you can see, now the "Type of Subscription" values are updated and even if I don't have some values like the Leo Wild age, the cell is filled with a NaN.
Honestly, I tried the script explained at this web page: https://www.appsloveworld.com/pandas/100/330/how-to-compare-two-dataframes-and-update-with-the-new-value, but it doesn't work when you use it with huge datasets with several columns and different rows index.
This is my script:
import pandas as pd
df_old = pd.read_excel(r"file_name_old.xlsx")
df_new = pd.read_excel(r"file_name_new.xlsx")
if not df_old.equals(df_new):
df = df_new.combine_first(df_old)
df.to_excel(r"file_name_final.xlsx", `index=False)`
Anyway, I can't obtain what I want with my huge dataset made of 30 columns and thousands of rows.
Can anyone help me?