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Time Series Analysis

bookChallenge 1

Opgave

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Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv dataset to turn it from non-stationary to stationary:

  1. Read the dataset.
  2. Test for data stationarity (use adfuller) and display results.
  3. Visualize the initial values of the "Price" column.
  4. Transform data (the "Price" column of the df DataFrame) from non-stationary to stationary using the difference method (using the .diff() method with periods = 1 parameter). Drop NA values. Assign the result to the new_diff variable.
  5. Visualize the modified data (new_diff).
  6. Rerun the ADF test for updated data (new_diff).

Løsning

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Sektion 5. Kapitel 3
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bookChallenge 1

Opgave

Swipe to start coding

Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv dataset to turn it from non-stationary to stationary:

  1. Read the dataset.
  2. Test for data stationarity (use adfuller) and display results.
  3. Visualize the initial values of the "Price" column.
  4. Transform data (the "Price" column of the df DataFrame) from non-stationary to stationary using the difference method (using the .diff() method with periods = 1 parameter). Drop NA values. Assign the result to the new_diff variable.
  5. Visualize the modified data (new_diff).
  6. Rerun the ADF test for updated data (new_diff).

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 5. Kapitel 3
single

single

close

Awesome!

Completion rate improved to 3.85

bookChallenge 1

Stryg for at vise menuen

Opgave

Swipe to start coding

Time for new challenges! Here is the first challenge, the idea of which is to process the pr_HH Spot Price.csv dataset to turn it from non-stationary to stationary:

  1. Read the dataset.
  2. Test for data stationarity (use adfuller) and display results.
  3. Visualize the initial values of the "Price" column.
  4. Transform data (the "Price" column of the df DataFrame) from non-stationary to stationary using the difference method (using the .diff() method with periods = 1 parameter). Drop NA values. Assign the result to the new_diff variable.
  5. Visualize the modified data (new_diff).
  6. Rerun the ADF test for updated data (new_diff).

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

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