AI & MACHINE LEARNING PROGRAM • LEVEL 19 — SEQUENCES & TIME SERIES
Create a Lag Feature with Python
Learn create a lag feature with python with a short, executable Python example.
PROBLEM UNDERSTANDING
Input and expected output
No input required
[(12, 10), (15, 12), (14, 15)]
COMPLETE PYTHON PROGRAM
Complete Python implementation
values=[10,12,15,14] print(list(zip(values[1:],values[:-1])))
CURRENT STEP
Select Start to walk through the important lines.
SELECTED LINE
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EXPECTED OUTPUT FOR THE SAMPLE
[(12, 10), (15, 12), (14, 15)]
PROGRAM EXPLANATION
Algorithm and explanation
- Initialize the sample values used to create a lag feature.
- Apply Lag and Time series to compute the required result.
- Display the result for create a lag feature and compare it with the documented sample output.
This example of create a lag feature computes the result directly from the prepared sample data. It demonstrates Lag and Time series and prints a deterministic result that can be checked against the sample output.
EFFICIENCY
Time and space complexity
O(n)
O(n)
DEBUGGING CHECKLIST
Common mistakes
For create a lag feature, keep the data shape and value types consistent with Lag.
Apply Lag in the same order shown by the algorithm; changing the order can change the result.
Verify the final Lag and Time series result against the sample before trying new data.