Popular Data Science Questions

  • Guided Project
  • 0.7 hours
  • Intermediate
  • Python

Practice analyzing Data Science Stack Exchange data with Python to identify the most popular topics and guide content creation.

Overview

In this project, you'll take on the role of a data analyst at a company that creates data science educational content. To decide what material to produce, you'll analyze data from Data Science Stack Exchange to determine the most popular and in-demand topics. You'll query the Data Science Stack Exchange database using SQL to extract relevant data. Then you'll use Python to clean, analyze and visualize the data to identify topic trends. Through this process, you'll develop valuable real-world data analysis skills as you work with messy data, explore insights and make data-driven recommendations on what content the company should prioritize creating to meet demand. You'll strengthen your SQL querying skills, enhance your Python data analysis and visualization abilities, and gain experience in leveraging data to inform content strategy. Objective: Analyze Data Science Stack Exchange data to identify the most popular data science topics and guide the creation of high-demand educational content.

What You'll Learn

  • Determine data science content to write
  • Identify how the most popular content is trending

Before You Start

  • Resolving ambiguous language to clarify analysis requests
  • Communicating data analysis results to non-technical business audiences
  • Defining and evaluating business metrics to track performance
  • Identifying how data science fits into the overall business context and workflow

Project Steps

11 steps

  1. 1 Introduction
  2. 2 Stack Exchange
  3. 3 Stack Exchange Data Explorer
  4. 4 Getting the Data
  5. 5 Exploring the Data
  6. 6 Cleaning the Data
  7. 7 Most Used and Most Viewed
  8. 8 Relations Between Tags
  9. 9 Enter Domain Knowledge
  10. 10 Just a Fad?
  11. 11 Next Steps

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