Variance

51 posts
McKinsey thinks the data world needs more dataviz talent

Note about last week: While not blogging, I delivered four lectures on three topics over five days: one on the use of data analytics in marketing for a marketing class at Temple; two on the interplay of analytics and data visualization, at Yeshiva and a JMP Webinar; and one on how to live during the Data Revolution at NYU. This week, I'm back at blogging. McKinsey publishes a report confirming...

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Plotted performance guaranteed not to predict future performance

Kaiser Fung (Junkcharts, Principal Analytics Prep) finds a chart on French financial instruments conveys a misleading message on relative returns while failing to describe the relative risks.

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Crazy rich Asians inspire some rich graphics

On the occasion of the hit movie Crazy Rich Asians, the New York Times did a very nice report on Asian immigration in the U.S. The first two graphics will be of great interest to those who have attended my free dataviz seminar (coming to Lyon, France in October, by the way. Register here.), as it deals with a related issue. The first chart shows an income gap widening between...

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Crazy rich Asians inspire some rich graphics

Kaiser Fung (Junkcharts, Principal Analytics Prep) examines several charts made by New York Times on income distribution among Asian Americans, as the hit movie Crazy Rich Asians dominates the U.S. box office in September.

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Two thousand five hundred ways to say the same thing

Wallethub published a credit card debt study, which includes the following map: Let's describe what's going on here. The map plots cities (N = 2,562) in the U.S. Each city is represented by a bubble. The color of the bubble ranges from purple to green, encoding the percentile ranking based on the amount of credit card debt that was paid down by consumers. Purple represents 1st percentile, the lowest amount...

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This map steals story-telling from the designer

Stolen drugs is a problem at federal VA hospitals according to the following map. *** Let's evaluate this map from a Trifecta Checkup perspective. VISUAL - Pass by a whisker. The chosen visual form of a map is standard for geographic data although the map snatches story-telling from our claws, just as people steal drugs from hospitals. Looking at the map, it's not clear what the message is. Is there...

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Common charting issues related to connecting lines, labels, sequencing

The following chart about "ranges and trends for digital marketing salaries" has some problems that appear in a great number of charts. The head tilt required to read the job titles. The order of the job titles is baffling. It's neither alphabetical nor by salary. The visual form suggests that we could see trends in salaries reading left-right, but the only information about trends is the year on year salary...

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Fantastic visual, but the Google data need some pre-processing

Another entry in the Google Newslab data visualization project that caught my eye is the "How to Fix It" project, illustrating search queries across the world that asks "how." The project web page is here. The centerpiece of the project is an interactive graphic showing queries related to how to fix home appliances. Here is what it looks like in France (It's always instructive to think about how they would...

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Lines, gridlines, reference lines, regression lines, the works

This post is part 2 of an appreciation of the chart project by Google Newslab, advised by Alberto Cairo, on the gender and racial diversity of the newsroom. Part 1 can be read here. In the previous discussion, I left out the following scatter bubble plot. This plot is available in two versions, one for gender and one for race. The key question being asked is whether the leadership in...

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Well-structured, interactive graphic about newsrooms

Today, I take a detailed look at one of the pieces that came out of an amazing collaboration between Alberto Cairo, and Google's News Lab. The work on diversity in U.S. newsrooms is published here. Alberto's introduction to this piece is here. The project addresses two questions: (a) gender diversity (representation of women) in U.S. newsrooms and (b) racial diversity (representation of white vs. non-white) in U.S. newsrooms. One of...

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