dataset
Large dataset, simple reading
The core improvement is turning a wide, messy source file into an experience that is quick to understand even for a non-specialist audience.
Lots of data. One clear story.
Trending videos. Categories, regions and time in one clear view.
Python · SQL · Looker Studio
What changes.
- 339,990
- trending videos analysed
- 18
- categories
- 7 months
- 14 Nov 2017 → 14 Jun 2018
From raw file to clear reading.
Python cleaning and a public delivery in Looker Studio.
A story at different scales.
Categories, regions and time to understand which videos stand out.
Take a closer look.
How it was built.Decisions, evidence and details
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Real technical integration
It combines Python data preparation with a public Looker Studio delivery, closing the loop from raw data to navigable visual output.
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Readable storytelling
The case does not stop at chart output. It orders regions, dates, and categories so the dashboard reads like a story rather than a pile of visual noise.
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Project flow
01
Load and clean
Notebook workflow to detect delimiters, normalize columns, remove duplicates, and prepare the base file.
02
Date conversion
Time standardization to support clean comparisons between 2017 and 2018.
03
EDA and visual structure
Quick exploration of nulls, categories, regions, and counts to decide which signals deserved to become visible.
04
Public Looker Studio delivery
A published Looker Studio dashboard with a time series, geographic map, and side explanation card in one guided view.
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Real dashboard captures
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Python notebook
Real notebook snippets used to load the CSV, clean columns, convert dates, and export the EDA that feeds the dashboard.
insights
What the dashboard makes visible
Visual dominance
Entertainment
Entertainment clearly appears as the strongest category in the ranking shown by the dashboard.
Time comparison
2017 → 2018
The time series supports a compact reading of how category activity evolves across the visible two-year span.
Regional reading
5 regions
The map gives users a faster regional comparison than raw tables and supports interactive exploration by place.
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Deliverables
Preparation notebook
A reproducible notebook for CSV cleanup, date handling, and basic EDA report generation.
Public Looker Studio dashboard
A public visualization that brings KPIs, geography, time, and categories into one readable flow.
Support PDF
A short support document explaining the dashboard goal and its value as an open exploration tool.
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Why it leads the portfolio
It leads the portfolio because it combines data cleanup, visual judgment, and clear communication in a format that is easy to consume. It shows that I do not just analyze data, I can also turn it into an experience other people can use.