[OC] Every fan-flagged skippable episode in 14 long-running anime, mapped across each show's run. Detective Conan has 548 of them, roughly 210 hours. Visualization

August 3, 2026
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AC
By Alex Cartwright
[OC] Every fan-flagged skippable episode in 14 long-running anime, mapped across each show's run. Detective Conan has 548 of them, roughly 210 hours. Visualization
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Data Analysis

What This Visualization Shows

This data visualization displays "[OC] Every fan-flagged skippable episode in 14 long-running anime, mapped across each show's run. Detective Conan has 548 of them, roughly 210 hours." and provides a clear visual representation of the underlying data patterns and trends. The visualization focuses on Source: MyAnimeList community filler flags, scraped August 2026. These are viewer votes, not official studio designations. Hours are flagged episodes times 23 minutes (a typical episode without the ad break); MAL lists these shows at 23 to 25 minutes per episode, so every total is rounded down, never up. Sailor Moon is first season only, since that is where nearly all its flags sit.

Tool: Python and matplotlib.

Why I made it: I wanted to start Detective Conan this summer, then found out its own fans have flagged 548 of the 1205 episodes as skippable. That's 210 hours. **You could watch Breaking Bad, The Wire, Game of Thrones and Squid Game back to back in the time this one show spends on episodes its own audience tells you to skip!**

The pattern that made it worth mapping: "filler" turns out to be two different things wearing one word. The blue shows are scattered padding, aired to buy time while the manga got further ahead. The orange shows have one solid block at the end, which is the show catching up to the books and improvising its own ending. If you know what happened to Game of Thrones after it passed the novels, that's exactly it, except anime has been doing it since the 90s. It's why Fullmetal Alchemist 2003 reads as "53% filler" even though that block IS the story of that version, and plenty of fans prefer its ending.

You can mostly diagnose a show's production history from the shape of the strip. Scattered lines: the manga was too slow. A block at the end: the studio ran out of book. Naruto is the hybrid case, its end block is 80 straight episodes of treading water until Shippuden could pick the manga back up.

Episode tables per series with the exact episode numbers: [https://bingerun.com/anime-filler-index/](https://bingerun.com/anime-filler-index/), which allows us to understand complex relationships and insights within the data through visual storytelling.

Deep Dive into the Topic

Technology data visualization provides insights into digital trends, user behavior, and system performance that drive innovation and improve user experiences. This field encompasses everything from website analytics and app usage patterns to system performance monitoring and cybersecurity threat visualization.

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Data Analysis and Insights

The patterns revealed in this visualization demonstrate the importance of systematic data analysis in understanding complex phenomena. By examining different data segments, time periods, and categorical breakdowns, we can identify trends that inform strategic planning and decision-making processes.

Statistical analysis of this data reveals variations across different dimensions that provide insights into underlying drivers and relationships. These patterns help identify areas of opportunity, potential risks, and key performance indicators that can guide future actions and resource allocation.

The analytical approach used in this visualization enables comparison across different categories, time periods, or geographic regions, revealing insights that support evidence-based decision-making. This type of analysis is essential for organizations seeking to optimize performance and understand complex market dynamics.

Significance and Applications

This data visualization has important implications for understanding trends and patterns that affect decision-making across multiple sectors. The insights derived from this analysis can inform policy development, business strategy, resource allocation, and operational improvements.

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The broader significance lies in how this information contributes to our understanding of complex systems and relationships. This knowledge helps predict future trends, identify potential challenges, and develop more informed approaches to problem-solving and opportunity identification.

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About the Author

Alex Cartwright

Alex Cartwright

Senior Data Visualization Expert

Alex Cartwright is a renowned data visualization specialist and infographic designer with over 15 years of experience in...

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Visualization Details

Published8/3/2026
CategoryData Analysis
TypeVisualization
Views10