Select Language

AI社区

公开数据集

1000年,Netflix显示

1000年,Netflix显示

0.08M
335 浏览
0 喜欢
0 次下载
0 条讨论
Arts and Entertainment,Internet,Movies and TV Shows Classification

数据结构 ? 0.08M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Context Netflix in the past 5-10 years has captured a large populate of viewers. With more viewers, there most likely an increase of show variety. However, do people understand the distribution of ratings on Netflix shows? Content Because of the vast amount of time it would take to gather 1,000 shows one by one, the gathering method took advantage of the Netflix’s suggestion engine. The suggestion engine recommends shows similar to the selected show. As part of this data set, I took 4 videos from 4 ratings (totaling 16 unique shows), then pulled 53 suggested shows per video. The ratings include: G, PG, TV-14, TV-MA. I chose not to pull from every rating (e.g. TV-G, TV-Y, etc.). Acknowledgements The data set and the research article can be found at [The Concept Center](http://theconceptcenter.com/simple-research-study-netflix-shows-analysis/) Inspiration I was watching Netflix with my wife and we asked ourselves, why are there so many R and TV-MA rating shows?
    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:0 去赚积分?
    • 335浏览
    • 0下载
    • 0点赞
    • 收藏
    • 分享