Time series
------------------------------------------------------------------------

This section is very introductory.



Moving avarage
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Take in mind the simple mean (unweighted).

+---------+------------+------------+
|    X    | X.shift(1) | X.shift(2) |
+---------+------------+------------+
| $x_{1}$ |     NaN    |     NaN    |
+---------+------------+------------+
| $x_{2}$ |   $x_{1}$  |     NaN    |
+---------+------------+------------+
| $x_{3}$ |   $x_{2}$  |   $x_{1}$  |
+---------+------------+------------+
| $x_{4}$ |   $x_{3}$  |   $x_{2}$  |
+---------+------------+------------+
| $x_{5}$ |   $x_{4}$  |   $x_{3}$  |
+---------+------------+------------+



Then you can construct a sum of each column.



Material 
----------------------------------------------------------------------------------------

.. list-table:: Notebooks
    :widths: 10 20
    :header-rows: 1

    * - Model
      - Material

    * - Introduction financial series
      - `Notebook introduction <https://github.com/it-ces/PUBLIC-AI/blob/main/time-serie/Introducci%C3%B3n_a_las_series_financieras_return(Ai_page).ipynb>`_
    * -  Introduction to decomposition
      - `Notebook decomposition <https://github.com/it-ces/PUBLIC-AI/blob/main/time-serie/Decomposition_times_series_(ai_page).ipynb>`_
    * - Introduction to ARIMA
      - `Notebook intro ARIMA <https://github.com/it-ces/PUBLIC-AI/blob/main/time-serie/ARIMA.ipynb>`_
    * -  ARIMA excersice
      - `Notebook excercise <https://github.com/it-ces/PUBLIC-AI/blob/main/time-serie/running.ipynb>`_