Handling 'ValueError: Length of values does not match index' when adding a new column in Pandas
I'm not sure how to approach After trying multiple solutions online, I still can't figure this out. I'm working with a DataFrame in Pandas (version 1.4.2), and I'm working with a `ValueError: Length of values does not match index` when I try to add a new column to it. I have a DataFrame that is supposed to hold the sales data for different products, and I want to add a new column for the discount applied to each product. Here's the code I'm using: ```python import pandas as pd # Sample DataFrame sales_data = { 'Product': ['A', 'B', 'C', 'D'], 'Price': [100, 150, 200, 250] } df = pd.DataFrame(sales_data) # Discount list with fewer values than rows discounts = [10, 20] # Only two discounts for four products # Attempting to add the discounts as a new column try: df['Discount'] = discounts except ValueError as e: print(f'behavior: {e}') ``` When I run this code, I get the value behavior because the length of the `discounts` list is not equal to the number of rows in the DataFrame. I want to know the best way to handle this situation. Should I pad the `discounts` list or is there a better approach? In some cases, I may not have a discount for all products. What are best practices for adding new columns when the lengths do not match? I also considered using `np.nan` for missing discounts, but I'm unsure how to implement that elegantly. Any advice would be appreciated! For context: I'm using Python on Ubuntu. Has anyone else encountered this? This issue appeared after updating to Python 3.9. Is there a better approach?