Analyzing Anime data in R
Since there’s lot of great anime content out there it would be awesome if one could do some data exploration (as data about anime is openly largely available) and identify the anime of their likes or their choices by having a look at the genres, other people’s opinions and observations and the like. Human beings have a great visual perception.
This behavior is very natural so to speak, because out of a lot of anime that are out there, some end up being very very popular and the members/followers for those anime are huge but the little known ones don’t have many people talking about them…
However, for TV, the number of episodes seems to be on the higher side of around 35 episodes per anime on an average. For movies, specials and OVA, it is around 1 or 2 and for ONA, it’s around 5 episodes per anime respectively.
Also, amongst categorical columns, we can see that most of the anime are TV anime and the most prevalent genre amongst all the anime is Hentai with 785 entries. This is a misleading stat, which I will explain why in the section on histogram and countplots. The top 5 anime by ranking are all movies and one TV anime.
Following are some of the characteristics that make anime unique.Complex Plots. One of anime's distinctive features is the type of plots in which it appears. ... Adult Focus. ... Exaggerated Physical Features. ... Limited Animation.
Animation Techniques Anime uses classical animation production means of storyboarding, character design, and voice acting. It is a form of limited animation in which instead of drawing each frame animator reuses common parts between frames. It means no need to illustrate a completely new scene every time.
Anime (pronounced AH-nee-may ) is a term for a style of Japanese comic book and video cartoon animation in which the main characters have large doe-like eyes. Many Web sites are devoted to anime. Anime is the prevalent style in Japanese comic books or manga .
It combines graphic art, characterization, cinematography, and other forms of imaginative and individualistic techniques. Compared to Western animation, anime production generally focuses less on movement, and more on the detail of settings and use of "camera effects", such as panning, zooming, and angle shots.
Anime is almost entirely drawn by hand. It takes skill to create hand-drawn animation and experience to do it quickly.
2D Anime Is Currently More Popular in Japan Although much of the rest of the world has developed towards creating primarily 3D animation, the core market for animation in Japan still largely has a preference for 2D works.
Anime Top 10Top 10 Best Rated (bayesian estimate) (Top 50)#titlerating1Fullmetal Alchemist: Brotherhood (TV)9.082Steins;Gate (TV)9.043Clannad After Story (TV)9.028 more rows
hanguk aeniTo distinguish it from its Japanese counterpart, Korean animation is often called hanguk aeni (Korean: 한국 애니; lit. Korean animation) or guksan aeni (Korean: 국산 애니; lit. domestic animation).
Due to soundtracks, characters, animation and story, just like drugs. So it's addicting, at least in the case of some. The art styles and backgrounds are very well-done compared to american animation (no offense to those who enjoy cartoons).
This is due to anime often being an adaption from manga, where it is harder to convey emotion without the use of screen tones, backgrounds, or some form of over exaggeration. These effects often find their way into Animes, and is more often referred to under a more catch-all term: Manga effects.
Anime, a style of Japanese animation inspired by their manga comics, also makes use of 2D animation. Some of the biggest anime hits are: Dragonball Z. Naruto.
However, for TV, the number of episodes seems to be on the higher side of around 35 episodes per anime on an average. For movies, specials and OVA, it is around 1 or 2 and for ONA, it’s around 5 episodes per anime respectively.
Before moving on to the plots, we will read in the data and do some descriptive analysis to find out important statistics pertaining to the data. We will also process the data in order to make it ready for plotting.
Looking at the two plots, we can actually see that the mean is a good estimate of the overall population for rating because most of the ratings are contained in a region very tightly bound around the mean. The continuous line which is overlaid on top of the bins is called as the kernel density estimate and it is an estimator fit to approximate the frequenies of the observations for all continuous values in the range of that particular variable.