The Python Visualization Repository for Time Series Forecasting Analysis Practices

To GitHub users, welcome to our repository for visualizing time series forcasting by using Python/Jupyter Notebook for making the collection of codes for using in Time Series Forecasting practices. This repository is the collaboration between Charunthon Limseelo (Microsoft Learn Student Ambassadors) and Sirisa Kornnawawat (Google Developer Student Club), to train or have a practice for senior project.

Requirements

This repository is used in Python 3.11.5 in Jupyter Notebook framework with some significant libraries or packages that we need to additionally install in the code editor/PATH environment, which are:

1. Pandas
2. Matplotlib
3. Tensorflow Keras
4. Sklearn (Scikit Learn)
5. Seaborn
6. Numpy

What's inside the repository

In this repository, we include lots of practices datasets even from books or external data from UCI (UC Irvine Machine Learning Repository) and Kaggle datasets. Additionally, we would like to drop the references below here and include the csv file inside our repository to look the data inside the datasets easily. Also, we put the code that we have done inside this repo to look up on the functions that we have use to train in Time Series prediction.

References

• Peixeiro, M. (2022). Time series forecasting in Python. Manning Publications Co. Click Here
• Yadav, A. (2021, August 19). NSE-TATAGLOBAL stock price prediction. Kaggle. DOI