U.S. YouTube Video Trends: A Tableau Dashboard & Story
An interactive Tableau dashboard that visualizes U.S. YouTube trending data to reveal viewer sentiment, top channels, and regional content preferences.
What do trending YouTube videos reveal about American viewers? In this Tableau project, I analyzed U.S. YouTube trending data to uncover patterns in viewer sentiment, identify top-performing creators, and explore regional content preferences.
- Data Source
- What I Set Out to Discover
- Interactive Dashboard
- Guided Story: A Walkthrough of Insights
- Key Takeaways
- Behind the Visualizations
- Final Thoughts
Data Source
For my data visualization project, I am using datasets containing statistics on trending YouTube videos in the U.S. These datasets were originally sourced from Kaggle and then transformed and cleaned by Udacity for educational purposes. The cleaned datasets can be found in my GitHub repo.
Data source: Kaggle
What I Set Out to Discover
I designed four interactive visualizations to tell a story and answer deeper questions that go beyond surface metrics like views or likes. These business questions guided the structure and design of the dashboard:
- Do more popular videos also attract more criticism?
- Which creators consistently break through the noise?
- Are some categories winning because of volume, or higher per-video impact?
- How does content preference vary across the U.S.?
Interactive Dashboard
Let’s explore the full dashboard here! Filter by category, hover over the charts for tooltips, and uncover deeper insights as you interact with the data.
Guided Story: A Walkthrough of Insights
This Tableau Story walks you through the key findings, one insight at a time.
Key Takeaways
- Popularity attracts polarity. Trending videos with high likes often come with a high number of dislikes.
- Big brands dominate. Marvel Entertainment and YouTube Spotlight top the charts in total views.
- Music wins in impact. Fewer videos, but each with massive reach.
- Geography matters. Music reigns nationwide, but Entertainment and Gaming see regional spikes.
Behind the Visualizations
The analysis is powered by four main visualizations:
1. Top 20 YouTube Channels (Bar Chart):
To identify the most influential creators, I built a bar chart ranking the top 20 YouTube channels by total views. Since trending videos in the dataset appear repeatedly across multiple dates (as long as it remained trending), I used Tableau’s Level of Detail (LOD) calculation to extract the maximum value of views per unique video, avoiding duplicate entries. Then I aggregated these values to get the total views per channel.
2. Likes vs. Dislikes Across YouTube Categories (Scatter Plot):
The scatter plot reveals the relationship between likes and dislikes for trending videos in different categories. Each data point represents an individual video. The shape of each point corresponds to the video’s category, so users can immediately identify content types without relying on color alone.
Because the same video could appear on multiple trending days, I again applied an LOD calculation to capture only each video’s highest recorded engagement (likes and dislikes), instead of a cumulative total across multiple entries.
I also added a “Category Name” filter to let users focus on specific genres (like Comedy or Music) and investigate how sentiment patterns vary.
3. Video and View Counts by Category (Dual-Axis Bar Chart):
This chart addresses an important question: is volume or impact more important in content trends?
I created a dual-axis chart to show:
- Bar chart: Total view counts per category (aggregated from highest view count per video)
- Dot plot: Number of unique trending videos in that category
I also structured the hierarchy with “Channel Title” nested under “Category Name”, so users can drill down into specific creators within each genre.
4. Top YouTube Categories by State (Interactive Map):
The interactive map shows regional preferences with each state colored by its most popular YouTube category (based on total views). This visualization offers a regional perspective on video trends and helps understand geographic differences in content preferences.
Users can also apply the “Category Name” filter to see where specific content types are trending, even if they’re not the most dominant in that state. This interaction makes it easy to investigate niche audiences or regional differences in taste.
Tooltips
Every visualization includes tooltips that appear when users hover over data points. These tooltips provide additional context such as video titles, channel names, categories, view counts, likes, and dislikes, without cluttering the visual space. This design choice keeps the interface clean while giving users quick access to details for deeper insight.
Final Thoughts
With Tableau, I turned a complex dataset into an accessible, interactive tool that surfaces insights through design and exploration. But this project was more than just building a dashboard. It was an exercise in turning raw data into narrative. Beyond the technical skills, this project pushed me to think like a storyteller, to guide users through the data, not just analyze it.
