Project overview
In this project, you’ll step into the role of a data analyst to explore and analyze a dataset from Hacker News, a popular tech-focused community site. You’ll apply your skills in string handling, object-oriented programming, and date management in Python to uncover trends in user submissions and understand what drives post popularity.
This practical project enhances your data analysis abilities and helps you interpret complex real-world datasets. By deriving meaningful insights, you’ll showcase in-demand skills for data analyst roles.
Objective: Use Python to analyze Hacker News data, identifying factors that contribute to post popularity and enhancing your analytical abilities.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Cleaning and preparing text data in Python
- Exploring data using loops in Python
- Processing dates using the datetime library in Python
Projects steps
Step 1: Introduction
Step 2: Removing Headers from a List of Lists
Step 3: Extracting Ask HN and Show HN Posts
Step 4: Calculating the Average Number of Comments for Ask HN and Show HN Posts
Step 5: Finding the Amount of Ask Posts and Comments by Hour Created
Step 6: Calculating the Average Number of Comments for Ask HN Posts by Hour
Step 7: Sorting and Printing Values from a List of Lists
Step 8: Next Steps
Master skills faster with Dataquest
Go from zero to job-ready
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
Challenge yourself with exercises
Work with real data from day one with interactive lessons and hands-on exercises.
Showcase your path certification
Share the evidence of your hard work with your network and potential employers.
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
Recommended projects
Investigating Fandango Movie Ratings
Practice using R to analyze movie ratings data, compare 2015 vs 2016 ratings, and apply sampling and distributions to investigate bias.
NYC Schools Perceptions
Practice data cleaning, analysis, and visualization in R to explore survey data and showcase your skills with R Notebooks.
Investigating Fandango Movie Ratings
Practice statistical analysis in Python to investigate movie rating bias and determine if Fandango inflated ratings.
Building Fast Queries on a CSV
Practice implementing an inventory system for a laptop store using Python classes, dictionaries, and binary search.
Garden Simulator Text Based Game
Practice using OOP, error handling, and randomness in Python to create an interactive gardening game simulator.
Predicting Heart Disease
Practice building a K Nearest Neighbors classifier in Python to predict heart disease risk from patient data.
Word Raider
Practice using Python variables, lists, loops, conditionals, and file handling to build an interactive word-guessing game.
Predicting Condominium Sale Prices
Practice using linear regression in R to predict condominium sale prices based on size and location in New York City.
Kaggle Data Science Survey
Practice analyzing survey data in Python to uncover insights about data science careers and skills.