During my self-taught data science journey, I kept hitting the same wall: I'd learn a concept in a notebook, but turning it into an interactive dashboard felt like starting over.
So I started building reusable Streamlit templates. Every time I learned something new — clustering, A/B testing, ML pipelines — I turned it into a dashboard I could reuse.
Here are the 5 templates I use most:
1. Sales Analytics Dashboard
Filters, KPI cards, revenue by category, customer segment breakdown, monthly trends. Great for any e-commerce dataset. Just swap the CSV and it works.
2. EDA Auto-Explorer
Upload any CSV and get instant summary statistics, distributions, correlations, and missing value analysis. Saved me hours of repetitive pandas code.
3. ML Model Trainer
Select a target column and feature columns. Train Logistic Regression, Random Forest, and XGBoost side by side. Compare metrics and view feature importance.
4. Customer Segmentation
KMeans clustering with elbow method, PCA visualization, and segment profile tables. Download your data with cluster labels attached.
5. A/B Test Analyzer
Upload experiment data, get conversion rates, p-values, confidence intervals, and plain-English interpretation of whether your result is significant.
Why Streamlit?
One file, one command, instant web app. No HTML, no CSS, no JavaScript. Just Python.
Get the Templates
I packaged all 5 with sample datasets and a setup guide:
→ Streamlit Dashboard Templates (https://deepanshu647.gumroad.com/l/nlkuun)
$15
I'm Deepanshu — self-taught data scientist, building tools for data learners.
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