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-
-
-**WARNING:** Merging all the time series gists into a single module.
-
-## Stationarity & Unit Roots
-
-Stationarity is one of the fundamental concepts in time series analysis. The **time series data model works on the principle that the [_data is stationary_](https://www.analyticsvidhya.com/blog/2021/04/how-to-check-stationarity-of-data-in-python/) and [_data has no unit roots_](https://www.analyticsvidhya.com/blog/2018/09/non-stationary-time-series-python/)**, this means:
- * the data must have a constant mean (across all periods),
- * the data should have a constant variance, and
- * auto-covariance should not be dependent on time.
-
-Let's understand the concept using the following example, for more information check [this link](https://www.analyticsvidhya.com/blog/2018/09/non-stationary-time-series-python/).
-
-![Non-Stationary Time Series](https://cdn.analyticsvidhya.com/wp-content/uploads/2018/09/ns5-e1536673990684.png)
-
-
-
-| ADF Test | KPSS Test | Series Type | Additional Steps |
-| :---: | :---: | :---: | --- |
-| ✅ | ✅ | _stationary_ | |
-| ❌ | ❌ | _non-stationary_ | |
-| ✅ | ❌ | _difference-stationary_ | Use differencing to make series stationary. |
-| ❌ | ✅ | _trend-stationary_ | Remove trend to make the series _strict stationary. |
-
-
-
-## Time Series Featuring
-
-Time series analysis is a special segment of AI/ML application development where a feature is dependent on time. The code here is desgined to create a *sequence* of `x` and `y` data needed in a time series problem. The function is defined with two input parameters (I) **Lootback Period (T) `n_lookback`**, and (II) **Forecast Period (H) `n_forecast`** which can be visually presented below.
-
-
-
-![prediction-sequence](https://i.stack.imgur.com/YXwMJ.png)
-
-
-
-## Getting Started
-
-The code is publically available at [**GitHub gists**](https://gist.github.com/ZenithClown) which is a simple platform for sharing *code snippets* with the community. To use the code, simply clone the code like:
-
-```shell
-git clone https://gist.github.com/ZenithClown/.git ts_utils
-export PYTHONPATH="${PYTHONPATH}:ts_utils"
-```
-
-Done, you can now easily import the function with *python* notebooks/code-files like:
-
-```python
-from ts_featuring import CreateSequence
-```
-
-
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diff --git a/stationarity.py b/stationarity.py
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A functional approach to check stationarity using different models
and the function attrbutes are as defined below.
+(`More Information