Project Sep 05, 2018 Data Science Portfolio Project: Where to Advertise an E-learning Product In this stats portfolio project, we use pandas, matplotlib, and Seaborn to research the two best markets for advertising an e-learning product.
Guest Post Aug 22, 2018 What to Consider When Choosing Colors for Data Visualization Data Visualisation can be defined as representing numbers with shapes – and no matter what these shapes look like (areas, lines, dots), they need to have a color. Use these tips to pick the right colors.
Project Aug 15, 2018 Data Science Portfolio Project: Is Fandango Still Inflating Ratings? In this portfolio project, we analyze movie ratings data to determine whether there have been any changes in Fandango's rating system.
Guest Post Aug 08, 2018 How to Overcome That Awkward Silence in Interviews We’ve all been there: what we thought was an excellent interview quickly degrades as we sit with the hiring manager in silence. Here are six ways you can overcome awkward interview silence.
Guest Post Jul 23, 2018 Top 20 Python AI and Machine Learning Open Source Projects Use these open source projects to get started with machine learning and artificial intelligence today.
Python Jul 18, 2018 Basic Statistics in Python: Probability When studying statistics, you will inevitably have to learn about probability. In this post, we explore what probability is, normal distributions, and the z-score — all within the context of wine data.
Guest Post Jul 11, 2018 Preparing for the Data Science Job Hunt Job hunting is stressful, especially if you’re moving into an entirely new field. In this post, we give tips on finding data science jobs, looking up salaries, and what to do before you apply.
Project Jul 09, 2018 Data Science Project Style Guide We've been building guided projects for three years — here is what we've learned, and tips that will help you in your job hunt.
Python Jul 03, 2018 Basic Statistics in Python: Descriptive Statistics Statistics, done correctly, allows us to extract knowledge from the vague, complex, and difficult real world. In this post, we explore descriptive statistics.
Guest Post Jun 27, 2018 DIY AI for the Future AI is set to disrupt our current society on a major scale. Check out these new DIY projects you can try at home.
Guest Post Jun 20, 2018 Top 12 Essential Command Line Tools for Data Scientists Increase your productivity with this overview of a dozen Unix-like operating system command line tools.
Python Jun 13, 2018 Python Generators Tutorial Python generators are a powerful, but misunderstood tool. Use this tutorial to begin understanding, and using, generators.
Guest Post Jun 11, 2018 Take These 7 Small Steps To Make a Big Career Move Changing careers isn’t as difficult as you may think. To make things a little less intimidating, here are 7 small steps to make a big career move.
Data Science Jun 08, 2018 Programming Best Practices For Data Science When programming for data science, most people switch between a prototype mindset and a production mindset. Learn more here.
Guest Post May 30, 2018 How to Overcome Imposter Syndrome For Good Imposter syndrome is a widespread phenomenon. If you're feeling stuck, use these tips to turn your desire to succeed into an advantage.
Updates May 25, 2018 What's New in Dataquest v1.85: Takeaways, Intermediate R, and More In this post, we give you a quick overview of what we've released recently, and what's coming up.
Python May 23, 2018 Data Retrieval and Cleaning: Tracking Migratory Patterns In this post, we walk through investigating, retrieving, and cleaning migratory bird data.
Data Visualization May 21, 2018 Generating Climate Temperature Spirals in Python In this blog post, we recreate Ed Hawkins' climate spirals in Python. In addition to Python, we use pandas and matplotlib.
R May 16, 2018 Using Linear Regression for Predictive Modeling in R In this post, we use linear regression in R to build a model that predicts cherry tree volume.
Guest Post May 09, 2018 Top 10 Machine Learning Algorithms for Beginners ML algorithms are those that can learn from data and improve from experience, without human intervention. Get up to speed on the 10 most important ones for beginners.
Data Visualization May 02, 2018 This Artist Turns the Forest Floor into Data Visualizations We’re all familiar with data visualizations — word clouds, pie charts, pivot tables — but how does one put enquiries in paint? Patty Haller, a landscape artist from Seattle WA, may have figured that out.
Data Visualization Apr 25, 2018 Using Box Plots to Explore Women's Height Data The Digital Panopticon contains data about British convicts in the 19th century. This post explores convicted women's height data from the project.
Data Science Apr 23, 2018 What Does it Mean to Be a Senior Data Scientist? My job title is ‘Senior Data Scientist’ and I often joke I’ve no idea what that means. But here are some ideas.
R Apr 17, 2018 Five Reasons for Historians to Learn R Should academics learn to code? Check out this list and decide for yourself.
Data Visualization Apr 11, 2018 Learning From Bank Data: Women Across the World This post explores visualizations of gender-related data from the World Bank World Development Indicators (WDI).
Jupyter Apr 04, 2018 Jupyter Notebook for Beginners: A Tutorial Use this tutorial to learn the basics of creating your first Jupyter Notebook, the important terminology, and how easily notebooks can be shared and published online.
Python Apr 02, 2018 Python Regular Expressions Cheat Sheet Keep this regex cheat sheet nearby as you code, as a quick, handy reference.
WHM Mar 30, 2018 Visualizing Women's Marches: Part 2 We explore data from the 2017 Women's Marches, and create visualizations of the turnout.
WHM Mar 28, 2018 Exploring Women's Army Auxiliary Corps Data Author Sharon Howard digs through a unique data set that explores the service records from women who joined the Women’s Army Auxiliary Corps from 1917–1920.
WHM Mar 26, 2018 Visualizing Women's Marches: Part 1 In this post, we collect and clean two 2017 Women's Marches data sets, to better understand the scale of the events.
WHM Mar 23, 2018 18 Inspiring Women In AI, Big Data, Data Science, Machine Learning Women are underrepresented in STEM fields, but these inspiring women are making their mark. Read about groundbreakers in AI, Analytics, Big Data, Data Science, Machine Learning, and Robotics.
Guest Post Mar 21, 2018 5 Ways to Find Interesting Data Sets Well-trafficked data sets don't offer much opportunities for new questions. Here are some tips on finding more unique data sets you can really dig into.
R Mar 15, 2018 R Fundamentals: Building a Simple Grade Calculator Use this tutorial to learn the basics of R by building a simple grade calculator.
Updates Mar 06, 2018 What's New in Dataquest v1.63: Hotkeys, Custom Hints, and More We have a few exciting new features, including in-mission search, updated hotkeys, and custom hints for errors. Come check them out.
Data Science Feb 20, 2018 Data Science Glossary Our handy glossary demystifies data science terms. Use it to start learning today—from fundamentals to machine learning techniques.
Docker Feb 15, 2018 How to Install and Configure Docker Swarm on Ubuntu In this post, we go through how to install and configure Docker Swarm on an Ubuntu 16.04 server. You should know a bit about Docker and Ubuntu before starting.
Motivation Feb 08, 2018 Fixing Education: Motivation and Freedom People learn better when they learn what they want to, on their own terms. We believe motivation and freedom are key to education—learn more in this post.
Project Feb 06, 2018 10 Data Science Projects You Can Join Today Finding the right data can be difficult. And even once you have it, how do you collaborate with others to make sense of it? These projects will help you get started.
R Feb 01, 2018 Control Structures in R: Using If-Else Statements and Loops In this tutorial, we teach you how to use control structures by building a simple algorithm that tells you who won or lost a soccer match.
Cloud Jan 30, 2018 Introduction to AWS for Data Scientists In this post, we give an overview of useful AWS services for data scientists — what they are, why they're useful, and how much they cost.
Python Jan 25, 2018 Introduction to Functional Programming in Python New to functional programming in Python? Use this tutorial to get up to speed quickly, from how it's different from object-oriented programming, to how to switch between the two easily.
Updates Jan 23, 2018 What's New in Dataquest v1.52: R, SQL, Postgres, and a Better Dashboard We are excited to announce several new courses and a few new features we think you'll love. Courses include R Fundamentals, SQL Fundamentals, Building a Data Pipeline, Kaggle Fundamentals, and more.
Data Science Jan 18, 2018 How to Write a Bootcamp Review that Actually Helps People From university programs to week-long cohorts, it can be difficult to pick a data science program. Quality reviews are a big help.
SQL Jan 17, 2018 Want a Job in Data? Learn This. Ignoring SQL will make it much harder to get a job in data. We tell you why.
Python Jan 11, 2018 Introduction to Python Ensembles This post takes you through the basics of ensembles — what they are and why they work so well — and provides a hands-on tutorial for building basic ensembles.
Postgres Jan 10, 2018 Postgres Internals: Building a Description Tool In this post, learn about Postgres' internal tables and use Python to build your own description dictionary from scratch.
Cloud Jan 04, 2018 How to Set Up a Free Data Science Environment on Google Cloud In this post, we walk through how to set up a data science environment on Google Cloud Platform—from why you should do it, to configuring Jupyter Notebook.
Machine Learning Jan 03, 2018 Learning Curves for Machine Learning This tutorial uses a real world data set to teach you how to diagnose and reduce bias and variance, for more accurate machine learning models.
Tips Dec 20, 2017 Adding Axis Labels to Plots With pandas This quick read shows you how to add axis labels to plots, without needing to learn Matplotlib.
Pandas Dec 13, 2017 Pandas Concatenation Tutorial In this tutorial, we walk through several methods of combining data using pandas.
Pandas Dec 08, 2017 Using Excel with pandas In this tutorial, we show you how to work with Excel files in pandas—from setting up your computer, to moving and visualizing data.
Python Nov 27, 2017 Regular Expressions for Data Scientists In this tutorial, learn how to use regular expressions and the pandas library to manage large data sets.
PyData Nov 22, 2017 Setting Up the PyData Stack on Windows This step-by-step guide uses Anaconda to show you how to set up a fully functional PyData stack on your local Windows machine.
Community Nov 16, 2017 How to Start a Data Science Meetup Use these tips to start your own meetup, and avoid the pitfalls. We cover choosing a time, finding a location, securing presentations, and getting sponsors.
Kaggle Oct 25, 2017 Kaggle Fundamentals: The Titanic Competition Learn how to succeed in the Kaggle 'Titanic' competition with this free tutorial.
Data Science Oct 17, 2017 Five Essential Traits of a Data Scientist To truly be successful, every data scientist should have these five traits.
SQL Oct 06, 2017 SQL Fundamentals Do you use Python for data science but have always wanted to work with databases? Learn about some of the advantages of databases for data analysis and the basics of SQL.
Postgres Sep 30, 2017 Loading Data into Postgres using Python and CSVs Demystifying how Python can be used to load data from CSV files into Postgres. In this tutorial we will go over the basics of Postgres using the psycopg2 library.
Python Sep 25, 2017 Explore Happiness Data Using Python Pivot Tables Learn how to quickly extract valuable insights by slicing, filtering, and grouping your data using pandas pivot tables.
Python Sep 05, 2017 How to Generate FiveThirtyEight Graphs in Python Impressed by the graphs on popular site FiveThirtyEight? This quick tutorial gets you started making your own eye-catching visualizations.
Machine Learning Aug 31, 2017 Machine Learning Fundamentals: Predicting Airbnb Prices Learn about machine learning and build your very first model from scratch to predict Airbnb prices using k-nearest neighbors.
Updates Aug 30, 2017 What's New in v1.29: New Mission Interface, PayPal and more! Read about the latest features from Dataquest, including our improved mission interface, PayPal and more.
Python Aug 29, 2017 Python Cheat Sheet for Data Science: Intermediate Do you want to learn Python for Data Science? Download this free Python cheatsheet. Includes DateTime, List Comprehension, Sets, and more.
Jobs Aug 15, 2017 How to get your first job as a data scientist. Learn the secret to getting a data science job, even if you have no experience.
SQL Aug 10, 2017 SQL Intermediate: PostgreSQL, Subqueries, and more! Learn how to work with SQL in more detail including setting up tables in PostgreSQL, views, subqueries, and more.
Pandas Aug 04, 2017 Using pandas with large data Learn how to use simple techniques to reduce memory usage by almost 90% and work with bigger data using pandas.
Python Jul 20, 2017 Python Cheat Sheet for Data Science: Basics What to learn Python? Download this free Python Cheatsheet. It includes strings, lists, dictionaries, loops and more.
Python Jul 13, 2017 Should I learn Python 2 or 3? A walkthrough of the key history of Python 2 and Python 3 to help you make the best decision when learning the popular programming language.
Pandas Jul 05, 2017 Understanding SettingwithCopyWarning in pandas Everything you need to know about the most common (and most misunderstood) warning in pandas.
Python Jun 29, 2017 Web Scraping with Python and BeautifulSoup This intermediate tutorial teaches you how to scrape data from multiple pages using Python and BeautifulSoup.
Kaggle Jun 22, 2017 The tips and tricks I used to succeed on Kaggle Learn from the tips and tricks Vik used to rank first in Kaggle competitions.
Jobs Jun 15, 2017 What's the difference between a data analyst, scientist and engineer? Find out about the three main job descriptions in the new and exciting field of data: Data Scientist, Data Analyst, and Data Engineer.
SQL May 09, 2017 SQL Basics: Working with Databases Learn the basics of SQL and Databases while analyzing a data set on bike rentals. Includes the database file so you can follow along.
Kaggle May 05, 2017 Getting Started with Kaggle: House Prices Competition Get started with Kaggle competitions. Learn how to prepare your data, train a model and make a submission.
Updates May 02, 2017 What's New in v1.19: Multiscreen, Concepts, Dataset Preview and More! Read about the latest features from Dataquest, including Multiscreen,Concepts, Dataset Preview, and more.
Jobs May 01, 2017 How to become a data scientist Learn how to become a data scientist without taking 10000 courses.
Numpy Apr 13, 2017 NumPy Cheat Sheet — Python for Data Science Download a free NumPy Cheatsheet to help you work with data in Python. Includes importing, exporting, filtering, sorting, scalar and vector maths, and more.
Updates Mar 23, 2017 Get paid to write for the Dataquest Blog: The Community Writers Program Join the Dataquest community writers program and get paid to contribute to our blog.
Python Mar 22, 2017 Turbocharge Your Data Acquisition using the data.world Python Library Learn how to use data.world's Python library to streamline working with data sets.
Data Engineering Mar 15, 2017 Building An Analytics Data Pipeline In Python This tutorial teaches you to build an end to end data pipeline using Python. Use data engineering to transform website log data into usable visitor metrics.
Updates Mar 02, 2017 What's New in v1.14: Data Engineering Path & Performance Improvements! Read about the latest features from Dataquest, including our new data engineering path, dramatically faster code running speed and much, much more!
Python Feb 21, 2017 Pandas Cheat Sheet — Python for Data Science Download a free pandas cheatsheet to help you work with data in Python. It includes importing, exporting, cleaning data, filter, sorting, and more.
Data Visualization Feb 09, 2017 1 tip for effective data visualization in Python Data visualization is a common way to represent tabular data in an easier to parse format. In this tutorial, you'll learn how to make effective data visualizations in Python.
Data Engineering Jan 25, 2017 What is Data Engineering? Data engineers build pipelines that prepare and transform data for data scientists. We explore what a data engineer does, and why the role is necessary.
Portfolio Jan 14, 2017 How to present your data science portfolio on GitHub Companies are increasingly looking at portfolios when making hiring decisions. Learn how to present the perfect data science portfolio on GitHub.
Motivation Jan 06, 2017 The Six Elements of the Perfect Data Science Learning Tool Learn about the key elements that the ideal data science learning tool should have to help you get a job, and what we're doing to incorporate these elements.
Data Cleaning Dec 28, 2016 Preparing and Cleaning Data for Machine Learning Learn how to prepare data, the first step in a machine learning project. Includes feature selection and converting ordinal and nominal features.
Jobs Dec 14, 2016 How to get a data science job Learn what you can do to get a job in data science, a new and exciting field with a shortage of skilled workers.
Pandas Dec 02, 2016 Pandas Tutorial: Data analysis with Python: Part 2 We cover how to use the groupby, aggregate, and apply methods to do advanced computations in Python.
Nov 23, 2016 Whats New in v1.10: Answer diffs, Improved Q&A! Read about the latest new features from Dataquest, including two new courses, answer diffing, and improvements to our Q&A.
Python Nov 17, 2016 Python Web Scraping Tutorial using BeautifulSoup Web scraping allows us to extract information from web pages. In this tutorial, you'll learn how to perform web scraping with Python.
Motivation Nov 11, 2016 I barely graduated college, and that's okay The story of how I taught myself Data Science and became inspired to build Dataquest.
Python Nov 04, 2016 What's New in Dataquest v1.9: Console, hotkeys, and more! Read about the latest new features from Dataquest, including console, hotkeys, and more!
Pandas Oct 25, 2016 Pandas Tutorial: Data analysis with Python: Part 1 Pandas is a Python library that can make data analysis much simpler. In this introduction, we'll walk through using pandas to load and analyze data.
Numpy Oct 18, 2016 NumPy Tutorial: Data analysis with Python This NumPy tutorial introduces key concepts and teaches you to analyze data efficiently. It includes comparing, filtering, reshaping, and combining NumPy arrays.
Jupyter Oct 12, 2016 28 Jupyter Notebook tips, tricks, and shortcuts Jupyter Notebook is a powerful tool for data analysis. We share with you 28 tips, tricks, and shortcuts to turn you into a Jupyter power user!
SQLite Oct 03, 2016 Working with SQLite Databases using Python and Pandas In this post, you'll learn to query, update, and create SQLite databases in Python. We'll also show you how to use the pandas package to speed up your workflow.
Project Sep 13, 2016 18 places to find data sets for data science projects A collection of the best places to find free data sets for data visualization, data cleaning, machine learning, and data processing projects.
Python Sep 08, 2016 Working with streaming data: Using the Twitter API to capture tweets In this post, you'll learn how to work with streaming data for data science in Python, with an example using Twitter's API.
Portfolio Aug 12, 2016 The key to building a data science portfolio that will get you a job Companies are increasingly looking at portfolios when making hiring decisions. Learn how to build an impressive data science portfolio, with examples.
Project Jul 21, 2016 How I built a Slack bot to help me find an apartment in San Francisco Learn how to build and deploy a bot to identify the best rental properties using Craigslist, Slack, and Python.
Portfolio Jul 05, 2016 Building a data science portfolio: Machine learning project Learn how to build an end to end machine learning project—a key part of any data science portfolio.
Resources Jun 24, 2016 7 awesome data science newsletters to keep you informed Everything you need to know about data science, delivered right to your inbox. We share our pick of the 7 best data science newsletters.
Portfolio Jun 14, 2016 Building a Data Science Portfolio: Setting Up a Blog Learn how to show off your work by setting up a data science blog using Jupyter Notebooks, Pelican, and Github Pages.
Portfolio Jun 02, 2016 Building a data science portfolio: Storytelling with data Learn how to build the first component in a well-rounded data science portfolio by learning how to tell stories with data.
Matplotlib May 12, 2016 Matplotlib tutorial: Plotting tweets mentioning Trump, Clinton, and Sanders This matplotlib tutorial shows you how to create plots using Python and data from tweets mentioning presidential candidates.
Kaggle May 03, 2016 How to get into the top 15 of a Kaggle competition using Python Learn how to place in the top 15 of the Kaggle Expedia competition using Python, pandas, scikit-learn and more.
Python Mar 01, 2016 Python and JSON: Working with large datasets using Pandas Working with large JSON datasets can be a pain, particularly when they are too large to fit into memory. In cases like this, a combination of command line tools and Python can make
Interview Feb 19, 2016 How Rob Hipps used Dataquest to land a data analysis job Learn how Dataquest helped Rob Hipps get his data analysis career started and land a job with 3M.
Interview Feb 18, 2016 How Patrick Kennedy used Dataquest to transition into data science Learn how Dataquest helped Patrick Kennedy get into the data science world after a career as an executive.
Python Jan 11, 2016 Python for data science: Getting started Use our tutorial to get started using Python for data science. We also cover pandas, Jupyter, and Matplotlib.
Interview Dec 30, 2015 How Data Scientist Yassine Alouini keeps his skills sharp Learn how Dataquest has helped Yassine Alouini better work with and analyze data.
Interview Dec 30, 2015 How Helena Tan went from Investment Banking to Data Science Learn how Dataquest has helped Helena Tan to better understand Python and work with data.
Interview Dec 14, 2015 Data Science at Stitch Fix: An interview with Brad Klingenberg An interview with Brad Klingenberg at Stitch Fix — a data science driven personal styling service for women.
Data Cleaning Dec 10, 2015 Cleaning CSV Data Using the Command Line and csvkit Learn how to clean data on the command line using csvkit.
Docker Nov 25, 2015 DigitalOcean and Docker for Data Science A tutorial on setting up DigitalOcean and Docker for data science, for a super-fast data science environment.
Docker Nov 22, 2015 Docker for Data Science: Running a Dockerized Jupyter Server A tutorial on setting up a Docker data science environment using Docker containers and the popular Jupyter Notebook.
Data Visualization Nov 12, 2015 Python data visualization: Comparing 7 tools See how 7 Python data visualization tools can be used together to perform analysis.
Interview Nov 02, 2015 Data Scientist Interview: Benjamin Root Learn about matplotlib and how to contribute to open source projects in our interview with Benjamin Root.
PySpark Oct 26, 2015 PySpark: How to install and Integrate with the Jupyter Notebook A tutorial on installing PySpark on your computer and get started working with large data sets using the Jupyter Notebook.
Machine Learning Oct 21, 2015 Machine Learning with Python: A Tutorial This tutorial gets you started using machine learning with Python, Pandas, and scikit-learn.
Interview Oct 11, 2015 Trey Causey: Data Scientist Interview An interview with Trey Causey, a data scientist who has worked for the New York Times, NFL Franchises, Facebook, Zulily, and more.
Spark Oct 09, 2015 Apache Spark: An Introduction Learn about Apache Spark, a powerful tool for data analysis on large datasets that's faster than Hadoop.
Python Oct 07, 2015 Python vs R: head to head data analysis Which is better — Python or R? We compare the two languages side by side and see how they perform on the same analysis steps.
Stories Oct 05, 2015 How Dataquest helped Patrick Nelli, VP of Corporate Analytics at Health Catalyst Learn how Dataquest user Patrick Nelli improve his understanding of data in his role as VP of Corporate Analytics.
Python Sep 08, 2015 Python API tutorial - An Introduction to using APIs Learn about APIs by analyzing data from the international space station in this step-by-step Python API tutorial.
Sep 02, 2015 Practice Makes Perfect: Announcing Tracks, Challenges, and Projects Find out how projects, challenges, and tracks can help you learn data science.
Data Cleaning Aug 13, 2015 Data Cleaning with Python — MoMAs Artwork Collection A step-by-step tutorial on data cleaning (or data munging) a dataset from the MoMA with Python, using the Pandas module.
Python Jul 27, 2015 K nearest neighbors in Python: A tutorial Learn how to use the k nearest neighbors technique and scikit-learn to group NBA basketball players.
Motivation Jul 14, 2015 How to Actually Learn Data Science The data science skills gap means that many people are learning or trying to learn data science. But where do you start?
NLP Jun 09, 2015 Natural Language Processing with Python Tutorial In this tutorial, you're learn how to do some basic Natural Language Processing in Python.
Python Apr 06, 2015 Python Counter Class and Probability Mass Functions This post walks you through a few applications of the Python Counter Class.
NLP Mar 17, 2015 Naive bayes: Predicting movie review sentiment In this post, we use the naive bayes algorithm to predict the sentiment of movie reviews. We'll also do some natural language processing to extract features to train the algorithm from the text of the reviews.
Python Feb 15, 2015 k-means clustering US Senators In this post, we'll explore cluster US Senators using an interactive Python environment.
Motivation Feb 09, 2015 Learning data science: A better way From recent college grads who want to branch out, to marketers looking to be more quantitative, to startup founders wanting to develop algorithms, it seems like everyone these days is interested in data.
