Streamlit Dashboard for a project
Budget: ₹1,500 – ₹12,500 INR
I need a simple Streamlit dashboard built in Python that loads data from a numpy .npz file and displays investment analysis charts. The dashboard should run locally with streamlit run app.py.
What I need:
5 pages using Streamlit multi-page routing. Each page shows metrics and 2-3 Plotly charts for a different asset. The charts are: IRR probability distribution (histogram/KDE), DSCR by year (bar chart), and a scenario comparison (horizontal bar chart). One sidebar with a scenario dropdown that updates the charts.
Tech stack: Python, Streamlit, Plotly, numpy. No database, no authentication, no deployment needed. Desktop only.
Data: I will provide a .npz file with pre-computed numpy arrays (IRR distributions, DSCR arrays, scenario values). I will give you the exact key names and shapes. You just load and display — no modelling or calculations needed on your side.
Design: I will provide a logo and a colour palette (6 hex codes). Clean, professional look. Custom CSS for the sidebar and metric tiles.
Deliverables: Working app, requirements.txt, README with one-line run instruction. Code must be clean — chart functions in one file, data loading in another.
What I need:
5 pages using Streamlit multi-page routing. Each page shows metrics and 2-3 Plotly charts for a different asset. The charts are: IRR probability distribution (histogram/KDE), DSCR by year (bar chart), and a scenario comparison (horizontal bar chart). One sidebar with a scenario dropdown that updates the charts.
Tech stack: Python, Streamlit, Plotly, numpy. No database, no authentication, no deployment needed. Desktop only.
Data: I will provide a .npz file with pre-computed numpy arrays (IRR distributions, DSCR arrays, scenario values). I will give you the exact key names and shapes. You just load and display — no modelling or calculations needed on your side.
Design: I will provide a logo and a colour palette (6 hex codes). Clean, professional look. Custom CSS for the sidebar and metric tiles.
Deliverables: Working app, requirements.txt, README with one-line run instruction. Code must be clean — chart functions in one file, data loading in another.