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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 ID
  • ds: series timestamp
  • y: 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.

この演習はコースの一部です

Designing Forecasting Pipelines for Production

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実践的なインタラクティブ演習

このサンプルコードを完成させて、この演習に挑戦してみましょう。

# Convert the period column to datetime and sort the data by period
ts["____"] = pd.____(ts["period"])
ts = ts.____("period")
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