Hello!
In the Practice Lab “Flight Delays and Cancellations – Working with Time Series Data” (Course: Python for Data Analytics, Module 5: Time Series), in Step 5: Speed of Changes, we first need to calculate the percentage change for the Arrivals_Delayed column and save it in the variable cancel_pct_change.
Later in this step, we need to find the rows in df_per_month where the percentage change is greater than 50%. However, this is done by referring to the variable cancel_pct_change, which does not belong to the df_per_month DataFrame.
Is it possible to select data from a DataFrame by referring to a variable that does not belong to the DataFrame itself?
Thanks in advance!
Hi @VeronikaS!
The short answer to your question is: yes, it is possible, and this notebook is intentional.
The longer answer:
The key idea is that pandas selects rows by index, not by whether a variable is a column of the DataFrame.
So when you create a series_from_df with a certain filter for the original_df, your series_from_df will still have the same indexes that came from the original_df.
When you move on and do something like `original_df[series_from_df>0.5]`, you are basically saying: “Give me the rows of original_df with the index that corresponds to True in this series_from_df condition"
This only works because the index of df_per_month and cancel_pct_change are identical. If they didn’t match, there would be an error.
Happy learning in 2026 
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@imgabidotcom Thank you for the excellent explanation! I also wish you happy learning and testing in 2026!
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