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Check the Pickup
Exploratory data analysis app for a pickup service, built to explore Streamlit: interactive visualizations, descriptive stats, and dynamic filters.
Stack
What happened?
- 01
The question
What can an honest exploration of a real pickup-service dataset teach us?
- 02
The problem
Raw data does not speak: you have to listen before claiming anything.
- 03
The hypothesis
An interactive Streamlit app with visualizations and filters will make exploration natural and shareable.
- 04
The build
Exploratory analysis app: descriptive statistics, interactive visualizations, dynamic filters — all to explore the dataset.
- 05
The failure
The first draft was a chain of charts with no question. Impressive, but useless: nobody knew what to conclude.
- 06
The discovery
EDA is a conversation with the data. One clear question at a time, and the chart becomes an answer, not a decoration.
- 07
The result
A Streamlit app for interactive exploration of the service — a foundation before any model.
- 08
The next frontier
Turning some observations into testable hypotheses (model, segmentation) and telling insights as stories.