Challenge 2 | 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 2

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:

2. Analyze how long patterns repeat (visualize `"Var"` and `"Date"` columns of the `df` DataFrame in this order).
3. Use the resulting number (it is `8`) for the difference method. Perform the differentiation for the `"Var"` column. Save the obtained result within the `df_diff` variable.
4. Visualize the transformed data.

Everything was clear?

Section 5. Chapter 4

# Challenge 2

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:
2. Analyze how long patterns repeat (visualize `"Var"` and `"Date"` columns of the `df` DataFrame in this order).
3. Use the resulting number (it is `8`) for the difference method. Perform the differentiation for the `"Var"` column. Save the obtained result within the `df_diff` variable.