I'm starting to create some Streamlit apps for BDG2 for interactive data exploration and model building. These apps can be used to better understand the data-set and used for my future teachings. My plan is to:
[x] Explore building attributes (floor area, EUI, etc.) per selected site(s)
[x] Explore weather data per selected site
[x] Calculate HDD/CDD with customizable base temperatures per selected site(s)
[ ] Create a site meters exploration tool (WIP app link)
[x] Number of meters per site
[x] Distribution of meter readings per selected site
[x] Time-series meter reading plot per selected site
[ ] Heatmap showing distances between meters per site, allows selection of different distance metrics (correlation, Euclidean, etc.)
[ ] Clustering analysis of meters per site with customizable SKLearn parameters
[ ] Create a building meter analysis/modelling tool (not started)
[ ] TBD, probably something related to customizable regression models with SKLearn
For context Streamlit is a super easy-to-use tool to create data apps in Python. Compared to traditional dashboards like plotly dash or superset, you can utilize the full potential of Python like creating ML models and perform in-depth analysis. They will also host the apps for free (at least for now).
I noticed there is already a notebook folder in this repository, I wonder how does the app files fit in? They are not really markdown files as they need to rendered by Streamlit or run locally. Would it be possible to include the app links in the readme.md once they are complete?
Oh and for those interested I will write a tutorial on how to create these apps. Also please feel free to comment on what kind of analysis you would like to see. Cheers.
cmiller8
commented
3 years ago
Hello friends,
I'm starting to create some Streamlit apps for BDG2 for interactive data exploration and model building. These apps can be used to better understand the data-set and used for my future teachings. My plan is to:
For context Streamlit is a super easy-to-use tool to create data apps in Python. Compared to traditional dashboards like plotly dash or superset, you can utilize the full potential of Python like creating ML models and perform in-depth analysis. They will also host the apps for free (at least for now).
I noticed there is already a notebook folder in this repository, I wonder how does the app files fit in? They are not really markdown files as they need to rendered by Streamlit or run locally. Would it be possible to include the app links in the readme.md once they are complete?
Oh and for those interested I will write a tutorial on how to create these apps. Also please feel free to comment on what kind of analysis you would like to see. Cheers.