Time Series Examples

This repository contains examples of time series analysis.

This repository contains twelve files and one folder:

1. data_files - A folder containing subfolders of .csv files for this repository. The subfolders are titled by subject, i.e. financial_data contains fundamental data, price_data contains stock prices, and supporting_data contains general time series data for analysis

2. gitignore - Contains the files excluded from this repository

3. Obtain_and_Append_Data.ipynb - A notebook which contains code that appends time series data from an API, to avoid request limitations

4. README.md - This document

5. Time Series Stock Sample Data.ipynb - A Jupyter Notebook containing examples of preparing time series data for analysis

6. Time_Series_Models_Examples.ipynb - A Jupyter Notebook containing multiple time series models

7. Weather_data.ipynb - A Jupyter Notebook containing a visualization of weather data

8. fundamental_trend_analysis.ipynb - A Jupyter Notebook containing analysis of fundamental financial data

9. requirements.txt - The requirements file for running the files of this repository

10. stationarity_check_funtion.py - Contains a funtion that neatly displays the results of a Dickey-Fuller test

11. time_series.yml - A file for replicating the environment required to run the files within this repository

12. time_series_removing_trends_and_decomposition.ipynb - A Jupyter Notebook containing the removal of trends for time series analysis

13. trend_analysis.ipynb - A Jupyter Notebook containing examples of stationarity

Relevant Articles Written About This Repository:

1. "Working With Time Series Data" (Towards Data Science) - An article about time series data visualizations with matplotlib and Plotly, based on Time Series Stock Sample Data.ipynb - Published December 19, 2019

2. "Time Series and Trend Analysis" (Data Driven Investor) - An article about time series trend analysis using matplotlib, its mpl component, and statsmodels based on trend_analysis.ipynb - Published December 26, 2019

3. "Achieving Stationarity With Time Series Data" (Towards Data Science) - An article about stationarity in time series data based on time_series_removing_trends_and_decomposition.ipynb - Published January 9, 2020

4. "Time Series Decomposition and Statsmodels Parameters" (Towards Data Science) - An article about time series decomposition models using the statsmodels module based on time_series_removing_trends_and_decomposition.ipynb - Published January 16, 2020, Updated July 11, 2020