Challenge 2
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You are faced with a task similar to the previous one: convert data to stationary. You will remove seasonality in the Seasonality Time Series.csv dataset using the difference method. Track a certain amount of time for which the time pattern repeats and use the difference method:
- Read the dataset.
- Analyze how long patterns repeat (visualize
"Var"and"Date"columns of thedfDataFrame in this order). - Use the resulting number (it is
8) for the difference method. Perform the differentiation for the"Var"column. Save the obtained result within thedf_diffvariable. - Visualize the transformed data.
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Completion rate improved to 3.85Challenge 2
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Swipe to start coding
You are faced with a task similar to the previous one: convert data to stationary. You will remove seasonality in the Seasonality Time Series.csv dataset using the difference method. Track a certain amount of time for which the time pattern repeats and use the difference method:
- Read the dataset.
- Analyze how long patterns repeat (visualize
"Var"and"Date"columns of thedfDataFrame in this order). - Use the resulting number (it is
8) for the difference method. Perform the differentiation for the"Var"column. Save the obtained result within thedf_diffvariable. - Visualize the transformed data.
Løsning
Skift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående mulighederTak for dine kommentarer!
Awesome!
Completion rate improved to 3.85single
