eda_examples

Instructions

1. Pull the repo to your local machine or OpenOnDemand scratch storage.
2. Create a Python environment using requirements.txt.
3. You can run the analysis in timeseries_data_cleaning.ipynb which will load the data from temps_premade.xlsx.
4. If you would like to make your own data, you can try running the Notebook faker_timeseries_temp_data.ipynb. In that case, the Notebook will output a file, temps.xlsx with the newly generated data.