A Data Scientist Job Map Visualization Tool using Python, D3.js and MySQL
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This document outlines a project to build an interactive map showing cities with available data scientist jobs and the most in-demand programming languages in those cities. It scrapes job postings to extract city, language, and other data, stores the data in database tables, then uses Python, PHP, jQuery, and D3.js to build an API and visualization that allows users to select a language and see corresponding cities with open data scientist roles along with other popular languages for those locations. The goal is to provide useful information to help data scientists identify job opportunities around the world.
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Breaking Down the Latest Spectrum Internet Plans.pdfInternet Bundle Now Explore updated Spectrum Internet Plans with expert guidance, your trusted Internet Service Provider reliable Spectrum Customer Service.
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34 Global Mobile Commerce_ Strategies, Implementation and Case Studies (Premi...
34 Global Mobile Commerce_ Strategies, Implementation and Case Studies (Premi...Nguyễn Minh Thương mại điện tử
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A Data Scientist Job Map Visualization Tool using Python, D3.js and MySQL
- 1. What cities are in demand for a Data Scientist, today? Andrea Gigli https://about.me/andrea.gigli
- 2. Goal • To build a map of the cities offering jobs for Data Scientists • To make the map interactive, allowing users to select a language and see the cities offering a Data Scientist job for a selected programming language • To show other “hot” languages for the selection above
- 3. Tools • Python for – Scraping web site, elaborating data and retrieving Latitude and Longitude – Building an API for querying the data base and make the map interactive • PhpMyAdmin for storing data • Jquery for passing arguments to Python • D3.js for visualization
- 4. Where we got data (1/2) Job_url
- 5. Where we got data (2/2) Job_id Job_skill Job_degree Job_language Job_city
- 6. Where we stored data Jobposting Table Joblanguage Table
- 7. How we make the map interactive Click here!
- 8. Here we are! It changes! It changes! It changes!