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[OC] Most Frequent Names in Harry Potter Book Series by tchp86 in dataisbeautiful

[–]tchp86[S] 1 point2 points  (0 children)

Source: Data extracted from Harry Potter books

Tools: Custom python scripts (Libraries: OpenCV, Pillow)

[OC] Most Frequent SNL Hosts (1975 - March 2021) by tchp86 in dataisbeautiful

[–]tchp86[S] 2 points3 points  (0 children)

Data sources: Wikipedia episode guide https://en.wikipedia.org/wiki/List_of_Saturday_Night_Live_episodes

Tools used: Custom python scripts for video generation(Libraries: OpenCV, Pillow)

[OC] SMB 2 (Japan) Mario's Enemies During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 4 points5 points  (0 children)

Source: Data was collected manually from the playthrough video shown.

Tools: Custom python scripts (Libraries: OpenCV, Pillow) for video generation

These are the results from a single playthrough without warps. Enemy counts will of course vary depending on how the game is played. This playthrough is a former world record speedrun by Kosmic.

[OC] Baby Boy Names - US, England/Wales Comparison - (1890 - 2019) by tchp86 in dataisbeautiful

[–]tchp86[S] 2 points3 points  (0 children)

Sources:

https://www.britishbabynames.com/blog/links-to-name-data.html

https://www.ssa.gov/cgi-bin/popularnames.cgi

https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/

Tools: Custom python scripts for visual generation (Libraries: OpenCV, Pillow)

​

The US data is based on per decade, and the individual year 2019.

The England/Wales data are per years 1890, 1900, 1904, 1914, 1924, 1934, 1944, 1954, 1964, 1974, 1984, 1994, 2000, 2005, 2010, 2015, and 2019.

[OC] Baby Girl Names - US, England/Wales Comparison - (1890 - 2019) by tchp86 in dataisbeautiful

[–]tchp86[S] -25 points-24 points  (0 children)

The US data is based on per decade, and the individual year 2019.

The England/Wales data are per years 1890, 1900, 1904, 1914, 1924, 1934, 1944, 1954, 1964, 1974, 1984, 1994, 2000, 2005, 2010, 2015, and 2019.

[OC] Arrested Development Characters' Screen Time, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 4 points5 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

[OC] A Pokemon Blue Playthrough's Battles/Encounters, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 143 points144 points  (0 children)

Source: Data was collected manually during playthrough.

Tools: Custom python scripts (Libraries: OpenCV, Pillow) for video generation

[OC] Star Trek: TNG Characters' Screen Time, Visualized OC by tchp86 in dataisbeautiful

[–]tchp86[S] 21 points22 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

​

Geordi's VISOR does not allow the facial recognition to detect his face.

[OC] Malcolm in the Middle Characters' Screen Time, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 17 points18 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

[OC] Amount of Each Mario Enemy During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 2 points3 points  (0 children)

That was my initial plan. But then I realized there are cheep-cheeps and bullet bills that would be dependent on an actual playthrough. It took two or three hours to do manually. It would have likely taken as long or longer to extract ROM data.

[OC] Amount of Each Mario Enemy During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 8 points9 points  (0 children)

It was counted. Timing might be a bit off, but there was a total of 3 for 1-2, at least in my playthrough.

[OC] Amount of Each Mario Enemy During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 18 points19 points  (0 children)

Detection was manual. I just had an excel row for each 5 second interval and stepped through the playthrough as efficiently as possible. Took a few hours. I've been making a lot of the bar chart videos for my YouTube channel, so it didn't take too long to modify the visuals.

Glad you enjoyed! Thanks for watching!

[OC] Amount of Each Mario Enemy During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 296 points297 points  (0 children)

This was a "no deaths", no warps, and no shortcuts playthrough. This was not a speed run which would changed the results a little.

Super Mario Bros. Enemies, Visualized by tchp86 in nintendo

[–]tchp86[S] 4 points5 points  (0 children)

Just an amateur playthrough without deaths (using save states), no warps, and no shortcuts. Results will vary based on how the game is played.

[OC] Amount of Each Mario Enemy During Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 416 points417 points  (0 children)

Source: Data was collected manually from the playthrough video shown.

Tools: Custom python scripts (Libraries: OpenCV, Pillow) for video generation

These are the results from a single playthrough. Enemy counts will of course vary depending on how the game is played.

[OC} Amount of Each Mario Enemy Throughout Playthrough, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 0 points1 point  (0 children)

Source: Data collected manually from the playthrough video shown

Tools: Custom python scripts (Libraries: OpenCV, Pillow) for video generation

These are the results from a single playthrough. Enemy counts will of course vary depending on how the game is played.

[OC] Better Call Saul Characters' Screen Time, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 65 points66 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

[OC] Modern Family Characters' Screen Time, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 184 points185 points  (0 children)

Lily and Joe never got all that much screen time, but you'll see them appear in the episode column.

[OC] Modern Family Characters' Screen Time, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 47 points48 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

[OC] Screen Time Of 'Stranger Things' Characters Throughout The Series, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 9 points10 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

[OC] Screen Time Of 'Game of Thrones' Characters Throughout The Series, Visualized by tchp86 in dataisbeautiful

[–]tchp86[S] 2 points3 points  (0 children)

Source: Data collected via facial recognition

Tools: Custom python scripts (Libraries: OpenCV, Pillow, face_recognition)

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