laudebugs/kenya-web-project

Provided a dataset of the top 500 Kenyan websites according to Alexa on July 2020 as well as performed some analysis on the dataset # Kenya Web Project For a more complete picture of the process and a richer guide to the project, find here. For this simple project, I wanted to answer the question, are the websites that Kenyans access accessible to a populus that is keen on data consumption. I used, on average, 100MB of data and I could not afford to access websites that would use even 5MB on a single page. And therefore, the websites that used the least amount of data, but that were also fast were the ones I tended to access from day to day. WhatsApp is a good example of a situation where I would get the most value for the data I used. If I turned off automatic video and image downloads, I could spend just 10MB each day communicating with friends as opposed to using direct text messages that were more expensive (a bundle of 200 text messages from Safaricom would cost Kes 10, each with a limit of ~160 characters). Brings back memories of how I started to use short-forms like _imy_ and _gn_ among others to use every single character of a text message. ## The Dataset The dataset consists of the top 499 websites in Kenya according to Alexa obtained on 4th July 2020. For each website, I performed a lighthouse report and added two key value pairs to the json describing the website, i.e. the performance and the size of the website on download. This dataset if found at data/combinedWebData.json ```json { "daily pageviews per visitor": "10.00", "% of Traffic From Search": "28.30%", "site": "Kabarak.ac.ke", "rank": 257, "Size of page downloaded": "45,606KB", "daily time on site": "23:23", "performance": 0.04, "total Sites Linking In": "139" } ``` For each website, the full lighthouse report is also available in the data/complete-reports folder. ## Project Stages and Guide on DIY steps 1. Data Collection and Preparation I gathered data from Alexa of the 500 most popular websites in Kenya here. To parse the data, I ran a simple java script to transform the dataset into json format here ```bash # compi …