A Collection of Data Science Take-Home Challenges


On-Line Video Challenge



Goal


The company of this challenge allows users to upload videos online, just like YouTube.

This company is interested in knowing whether a video is "hot" (i.e. trending up in terms of popularity), stable or going down. Understanding this would allow to optimize the videos promoted on the home-page and, therefore, maximize ads revenue.


Challenge Description


Company XYZ is an online video streaming company, just like YouTube or Dailymotion.

The Head of Product has identified as a major problem for the site a very high home page drop-off rate. That is, users come to the home-page and then leave the site without taking any action or watching any video. Since customer acquisition costs are very high, this is a huge problem: the company is spending a lot of money to acquire users who don't generate any revenue.

Currently, the videos shown on the home page to new users are manually chosen. The Head of Product had this idea of creating a new recommended video section on the home page.

She asked you the following:

Data


We have 2 tables downloadable by clicking here.

The 2 tables are:

    video_count - provides information about how many times each video was seen by day

Columns:


    video_features - characteristics of the video.

Columns:

Example


    Let's check one video: how many times was it seen on a given day?

head (video_count, 1)

Column Name Value Description
video_id 2303 id of the video
count 22 it was seen just 22 times.
date 2015-01-07 on Jan, 7th.

    Let's now check the characteristics of that video 2303:

subset(video_features, video_id == 2303)

Column Name Value Description
video_id 2303 It is the video we care about. Same as above
video_length 1071 the video lasts almost 18 min (1071 seconds)
video_language Cn the video is in Chinese
video_upload_date 2014-12-10 was uploaded on Dec, 10
video_quality 1080p video quality is 1080p, i.e. very high




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