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February Edition: Data Visualization

8 of the best articles on visualizing data

Data visualization is an essential step in any data science process. It’s the final bridge between the data scientist and end users. It communicates, validates, confronts and educates. And when done correctly, it opens up the insights from a data science project to a wider audience.

Great data visualization is more than painting a pretty picture with numbers. In fact, that’s often only a small part of it. We also need to consider other factors such as the type of audience seeing the visuals, the level of data literacy, the need for interactivity and the overall story that multiple graphs are telling.

These 8 articles make up our top picks for posts that provide helpful tools for data visualization, new insights on where the practice is headed, and interesting examples on how charts can be used effectively to tell a story.

Benjamin Cooley, TDS Editorial Associate.


Large Scale Visualizations and Mapping with Datashader

By Finn Qiao – 6 min read

If you’ve ever tried to create a swarm plot or relational plot of over 100,000 points with Matplotlib or Seaborn, you would be no stranger to the scenario of twiddling your thumbs as the plot loads. Luckily, Datashader is a great option to represent large datasets in a meaningful manner quickly.


3rd Wave Data Visualization

By Elijah Meeks – 12 min read

First came Clarity on how to visualize data. Then came new Systems to guide best practice. Now, we are entering the third wave of data visualization: Convergence. Elijah Meeks explains why practitioners need to shift their emphasis away from individual charts to the construction, evaluation and delivery of the products where those charts appear.


Airbnb Rental Listings Dataset Mining

By Sarang Gupta – 11 min read

New York City has been one of the hottest markets for Airbnb, with over 52,000 listings as of November 2018. This exploratory analysis of the Airbnb dataset from Inside Airbnb investigates the rental landscape in NYC through static and interactive visualisations.


5 Quick and Easy Data Visualizations in Python with Code

By George Seif – 7 min read

Matplotlib is a popular Python library that can be used to create your data visualizations quite easily. However, setting up the data, parameters, figures, and plotting can get quite messy and tedious to do every time you do a new project. This blog post looks at 5 data visualizations and how to write some quick and easy reusable functions for them with Python’s Matplotlib.


Visualizing bike mobility in London using interactive maps and animations

By Eden Au – 9 min read

Reports have shown that 77% of Londoners agree that cycling is the fastest way to make short-distance journeys. Let’s see how we can visualize a bike sharing system using graphs, maps, and animations.


The Next Level of Data Visualization in Python

By Will Koehrsen – 8 min read

The sunk-cost fallacy is one of many harmful cognitive biases to which humans fall prey. It refers to our tendency to continue to devote time and resources to a lost cause because we have already spent – sunk – so much time in the pursuit.


Insights From Raw NBA Shot Log Data and an Exploration of the Hot Hand Phenomenon

By Aimun Khan – 14 min read

Data science and the game of basketball are becoming more and more intertwined each year. This piece explores the prevalence of the "hot hand" phenomenon by visualizing NBA shot data.


117 Days Of My Tinder Profile In Data

By Brayden Gerrard – 5 min read

Data can often be very personal, like this visual exploration of four months of Tinder activity. Brayden Gerrard dives into how his likes, superlikes and messages may or may not have lead to actual dates.


We also thank all the great new writers who joined us recently, Andrew Kruger, Kelly Lougheed, Iftekher Mamun, Leonard Meerwood, Amy Vogel, Steve Driscoll, Preston Lim, Ricardo Ocampo, Samantha Bansil, René Bremer, Danny Kay, Dakota Lovins, Jack Ballinger, Lili Jiang, Christopher Doughty, Helena T Shi, Joel Quesada, Ayush Pant, Paul Pinard, Roman Moser, Ignacio Hagopian, Chirag Chadha, and many others. We invite you to take a look at their profiles and check out their work.


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