Time Series forecasting with ARIMA in Python
What you will need:
- A Google Colab account: https://colab.research.google.com/
- Upload your Time Series data to Google Drive (connected to Google Colab) - Remember to connect your Google Drive to Google Colab
- Note where the location of the data when you uploaded to Google Drive - you will need to specify this PATH for the Python program to run successfully
- To use Google Colab, the version of Python needed is the Jupyter Notebooks which has the .ipynb file name extension
- Open the .ipynb version of the Ptyhon program in Google Colab
- If you have Python installed on your PC/laptop - you can use the .py filename extension
- To be able to use the .py version, you will also need Visual Studio Code: https://code.visualstudio.com/
- Visual Studio Code also supports the .ipynb version but you will need to install the support extension - done within Visual Studio Code