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Please enable JavaScript in your browser settings or update your browser.Learn Challenge 1 | Non-Stationary Models
Time Series Analysis

bookChallenge 1

Task

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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).

Solution

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SectionΒ 5. ChapterΒ 3
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bookChallenge 1

Swipe to show menu

Task

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).

Solution

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Everything was clear?

How can we improve it?

Thanks for your feedback!

SectionΒ 5. ChapterΒ 3
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