Preparing and visualizing the data
Accurate data preparation is key to building effective machine learning models. Now it's time to apply the skills you've learned.
Your data needs three columns for the statsforecast library:
unique_id: series IDds: series timestampy: series values
Apply the necessary steps to clean and reformat your data for time series forecasting. The dataset has been preloaded as ts, and pandas is imported as pd.
แบบฝึกหัดนี้เป็นส่วนหนึ่งของหลักสูตร
Designing Forecasting Pipelines for Production
แบบฝึกหัดเชิงโต้ตอบแบบลงมือทำ
ลองทำแบบฝึกหัดนี้โดยเติมโค้ดตัวอย่างนี้ให้สมบูรณ์
# Convert the period column to datetime and sort the data by period
ts["____"] = pd.____(ts["period"])
ts = ts.____("period")