Spot Price Forcasting Notebook
A notebook that forecasts Spot Pricing for an instance in Amazon Web Services (AWS). This uses boto3 to retrieve data from Amazon Web Service, organize the data into a dataframe, predict and plot observed and future data using Prophet and Plotly.
This notebook was created in Python 3 environment. Make sure the notebook's kernel is set to Python 3. It's preferable to use the latest version of Python (3.6 at the time of this readme).
The notebook requires boto3 in order to retrieve data from AWS. To install and configure boto, use the following command:
pip install boto3
and follow the directions in order to setup the proper configurations.
Installing nodejs & ipywidgets
pip install ipywidgets jupyter nbextension enable --py widgetsnbextension
conda install -c conda-forge ipywidgets
JupyterLab users will need to use an additional command in order for the input widgets to display:
jupyter labextension install @jupyter-widgets/jupyterlab-manager
Users who are having issues installing the widgets for JupyterLab or those who aren't using the latest version should refer to version compatiblity page and select the command that is compaitible to your version of JupyterLab.
Before installing fbprophet, PyStan must be installed first along with a compiler. Refer to the installation page for more details depending on the operating system.
To install Plotly, use the following command:
pip install plotly
JupyterLab users will need to use an additional command in order for the graphs to display:
jupyter labextension install @jupyterlab/plotly-extension