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Exploring the Kaggle Data Science Survey

Discover the top tools Kaggle participants use for data science and machine learning.

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9 Tasks1,500 XP

Loved by learners at thousands of companies

Project Description

When beginning a career in data science, one often wonders what programming tools and languages are being used in the industry, and what skills one should learn first. By exploring the 2017 Kaggle Data Science Survey results, you can learn about the tools used by 10,000+ people in the professional data science community. Before starting this project, you should be comfortable manipulating data frames and have some experience working with the `tidyverse` packages `dplyr`, `tidyr`, and `ggplot2`. This project uses a subset of the [2017 Kaggle Machine Learning and Data Science Survey]( dataset. If you want to know more about the tools and techniques Kaggle participants use, check out the full [report of the Kaggle 2017 survey results](

Project Tasks

  1. 1
    Welcome to the world of data science
  2. 2
    Using multiple tools
  3. 3
    Counting users of each tool
  4. 4
    Plotting the most popular tools
  5. 5
    The R vs Python debate
  6. 6
    Plotting R vs Python users
  7. 7
    Language recommendations
  8. 8
    The most recommended language by the language used
  9. 9
    The moral of the story




Data ManipulationData VisualizationCase Studies
Amber Thomas Headshot

Amber Thomas

Journalist-Engineer at The Pudding

Amber Thomas is a journalist-engineer at The Pudding, an online collection of data-driven, visual essays. Before joining The Pudding, she was a marine biologist, collecting data on all things beneath the waves. Follow her on Twitter ( @ProQuesAsker) or on her personal website.
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Lloyds Banking Group

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Harvard Business School

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Decision Science Analytics, USAA