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.

Это упражнение является частью курса

Designing Forecasting Pipelines for Production

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Интерактивное практическое упражнение

Попробуйте выполнить это упражнение, дополнив этот пример кода.

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

Редактировать и запускать код