Project overview
In this project, you’ll take on the role of a data engineer tasked with processing and summarizing Hacker News posts from 2014. Using Python, you’ll read in JSON data, filter the most popular posts, clean the text fields, and build a data pipeline to find the most frequent words in the titles.
This hands-on project allows you to apply essential data engineering skills, including parsing JSON, cleaning text data, and constructing an efficient data pipeline. You’ll gain experience working with real-world data while building a practical tool to summarize large datasets. Some familiarity with Python is recommended.
Objective: Use Python to process Hacker News data and build a data pipeline that identifies the top keywords in post titles from 2014.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Understanding functional programming basics in Python
- Building simple data pipelines using the functional paradigm
- Implementing a pipeline API using advanced Python concepts like decorators
- Adding dependencies and a scheduler to Python data pipelines
Projects steps
Step 1: Introduction to the Data
Step 2: Loading the JSON Data
Step 3: Filtering the Stories
Step 4: Convert to CSV
Step 5: Extract Title Column
Step 6: Clean the Titles
Step 7: Create the Word Frequency Dictionary
Step 8: Sort the Top Words
Step 9: Next Steps
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