Challenge 1 | Non-Stationary Models
Time Series Analysis

Course Content

Time Series Analysis

## Time Series Analysis

1. Time Series: Let's Start

2. Time Series Processing

3. Time Series Visualization

# Challenge 1

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:

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`).

Everything was clear?

Section 5. Chapter 3

# Challenge 1

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:

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`).