Category Archives: Charts

DataViz: Chart-Topping Songs as Graphs and Diagrams (From FlowingData)

Billboard ranked the top 100 songs since the creation of their Hot 100 list in 1958. The list is based on airplay and sales.


Small Multiples, Tableau and Ben Jones


My BI world is changing a bit as I move more towards using Cognos and Tableau at work. In particular, I have a lot of status reports and dashboards to create for my leadership and I have been doing these mostly in Tableau.

I had a situation recently where I wanted to create a small multiples chart versus using a 3D Bar Chart that already existed. I have created small multiples charts fairly easily in Ben JonesMicroStrategy in my previous work, but have never created one before in Tableau. I reached out to Ben Jones (photo, right) at Tableau. I have been a big fan of Ben’s DataRemixed blog for quite some time and have blogged about Ben many times in the past. Ben was gracious enough to create a simple example small multiples chart for me to use to accomplish what I wanted to visualize. I was really impressed that Ben and Tableau did not put me through any red tape for him to help me. He saw I had a need and he helped me.

Much thanks to Ben for his help and I hope this example is useful to you.

Best Regards,


Small Multiples

Edward TufteA small multiple (sometimes called trellis chart, lattice chart, grid chart, or panel chart) is a series or grid of small similar graphics or charts, allowing them to be easily compared. The term was popularized by data visualization pioneer, Edward Tufte.

According to Tufte (Envisioning Information, p. 67):

At the heart of quantitative reasoning is a single question: Compared to what? Small multiple designs, multivariate and data bountiful, answer directly by visually enforcing comparisons of changes, of the differences among objects, of the scope of alternatives. For a wide range of problems in data presentation, small multiples are the best design solution.

A Small Multiples Example by Andrew Gelman

One of the most well-known examples of the use of small multiples is Andrew Gelman’s analysis of public support for vouchers, broken down by religion/ethnicity, income, and state (see image below).

GelmanMr. Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).

Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.

[Click on Image to Enlarge]

Gelman Voucher Map Using Small Multiples

My Small Multiples Chart

Since I cannot show you what I used the small multiples chart for related to my job, I made an illustrative, simple example related to home sales in different regions for the past six months. Below is an example of my chart, which I created using Tableau.

[Click on Image to Enlarge]

Home Sales Small Multiples

Adding Trend Lines

One of the key features I wanted to use in my chart was to be able to show trend lines for each small multiple.

However, when I clicked on Trend Lines -> Show Trend Lines, I kept getting the following error message:

Trend Lines Error Message Panel

Ben pointed out that in my original chart, the Columns shelf, Month needed to be a Continuous data type (green pill) rather than a Discrete data type (blue pill).  If you click in the Month pill, you should be able to select “Change to Continuous” and then you should be able to add a trend line. This occurs because you can only calculate a trend line when two axes are involved. The way I had it set up, the Columns were just different categories or attributes, rather than continuous measures.

I thought this would be a nice tip to pass along.

I hope to be able to share more Tableau tips as I become more proficient with the tool.

DataViz Humor: Eleven Humorous Everyday Life Graphs We Can All Relate To by Wumo

Wumo, formerly Wulffmorgenthaler, is a webcomic and newspaper comic strip created by Danish writer/artist duo Mikael Wulff and Anders Morgenthaler. The name of the strip was a portmanteau created from the pair’s surnames. The name was also given to a satirical TV series, broadcast on the Danish channel DR2 in 2005. In June 2012, the strip changed its name to ‘Wumo’.

Wumo debuted in 2001 as a comic strip competition entry named Kalzone, completed a few hours before the entry deadline. Submitted under the pseudonym “Pernille Richter Andersson”, the strip won the competition, and a one month run in the national newspaper Politiken. The strip became a regular feature on DR’s internet culture portal in 2002, and in October 2003 it became a regular daily newspaper strip in Politiken.

As of June 2012, ‘Wumo’ is printed daily in Politiken (Denmark), Aftonbladet (Sweden), Dagbladet (Norway), Die Welt (Germany), Helsingin Sanomat (Finland) and online-only in De Telegraaf (Holland) – and on its own .com website,

Starting in November 2013, Wumo appears in newspapers across the United States, including Washington Post and the New York Daily News, which is replacing the comic strip Get Fuzzy with Wumo.

In March 2014, Wumo replaced the comic strip Doonesbury in The New York Times.

enhanced-1180-1397555059-5 enhanced-4888-1397555057-1 enhanced-5264-1397555060-11 enhanced-5517-1397555056-9 enhanced-6624-1397555055-24 enhanced-6683-1397555055-11 enhanced-7064-1397555059-9 enhanced-7793-1397555055-8 enhanced-7949-1397555404-17 enhanced-17116-1397555058-1 enhanced-31478-1397555058-14








Disney DataViz: 2015 Walt Disney World Crowd Calendar


I have decided to create a new data visualization blog post theme specifically for topics related to Disney. This new theme will be called Disney DataViz.

To start off this theme, I could not think of any better chart to present than Dave Shute’s 2015 Walt Disney World Crowd Calendar. Dave’s site is blog and discusses everything you need to know for your first visit to Walt Disney World.

I encourage you to visit Dave’s site since he is the mastermind behind this wonderful chart.

For now, I am off to Disneyland.

Best regards,


2015 Crowd Calendar for Walt Disney World

Mr. Shute has provided his projections for Walt Disney World 2015 weekly crowds.

Dave plans on creating at least one revision of it in the summer of 2014, after the full set of 2014-2015 school calendars that he analyzes are out.

Dates in it are the beginning of the week, and the forecast covers the following 9 days.

Crowd levels are ranked by week from 1-11 in the following way:

1: Lowest of the year

2: Lower

3: Low

4: Low-plus

5: Moderate-minus

6: Moderate

7: Moderate-plus

8: High-minus

9: High

10: Higher

11: Highest

How To Interpret The 2015 Disney World Crowd Calendar

Dates are the beginning of the week.

The “low crowd” weeks–those colored green, and rated 1-4–represent the only crowd levels a family visiting for the first time, and unsure if it will ever return, should consider.

However, lower crowds, especially lowest crowds, do not always mean a better week. The lowest weeks are low for a reason–typically because they are in the hurricane or the ride closure seasons.

The “moderate crowd” weeks–those in black and rated 5-7–have crowd levels Mr. Shute would not recommend to first time visitors. However, he would go during such weeks himself with no hesitation, and think these levels are OK for returning visitors who don’t need to see everything and already know how to work Walt Disney World.

The “high crowd” weeks–those in red, rated 8-11–should be avoided by everyone. They aren’t, which is why they are so high.

The Disney World Crowd Calendar Goes Up To “11″

The influence of the Unofficial Guide  and has led almost all Disney World crowd calendars to top out at 10.

However, Mr. Shute has always thought that the really nastiest weeks of the year deserved an 11 for emphasis.

So, in homage to Spinal Tap, he has assigned 11 to “highest.”

NOTE: The 2014 Walt Disney World Crowd Calendar can be see here.


2015 Walt Disney World Crowd Calendar - DRAFT



Chart: Hey Girl, will you be my Valentine?

Valentine's Day

Source: Colleen Barrett, Valentine’s Day Visualized,,

WSJ DataViz: Hiring Slowdown Blurs Growth View

Dismal Jobs Report Raises Questions Over Economy’s Strength as Year Ended; Bad Weather a Factor?

Source: Brenda Cronin and Jonathan House, The Wall Street Journal, January 10, 2014.

WSJ - Still A Long Way to Close The Job Gap
The U.S. job gap created during the most recent recession remains, and while payrolls are being added to the economy, they haven’t kept pace with population growth.  
American employers added a disappointing 74,000 jobs in December, a tally at odds with recent signs that the economy is gaining traction and moving beyond the supports put in place after the recession.The jobless rate fell to 6.7% from 7% for the month, the Labor Department said, though the decline mostly reflects job seekers giving up their search and leaving the workforce.

A Historical Perspective – U.S. Unemployment Since 1948

WSJ - U.S. Unemployment - A Historical Perspective

WSJ - How 2013 Compares

The downbeat readings were partly attributed to distortions caused by bad weather, and many economists warned that the report may prove to be a fluke. Employers, too, are reporting a mixed take on the economy and their labor needs.

The report is likely to temper the Federal Reserve’s recent optimism about the health of the economy, but economists and analysts say it won’t alter the central bank’s course in reducing its bond-buying program. In December, Fed policy makers decided to cut the bond purchases by $10 billion, to $75 billion, starting this month. Fed officials said they expect to dial back the program steadily in 2014, as long as the economy looks strong enough to advance without such support.

The weak job numbers didn’t appear to faze stock investors but fueled a rally in bonds. The Dow Jones Industrial Average was little changed, dropping 7.71 points, or less than 0.1%, to 16437.05. The yield on the 10-year Treasury note, which moves inversely to its price, dropped 0.106 percentage point to 2.858%, its steepest daily slide since Sept. 20.

Michael Jones, chief investment officer at RiverFront Investment Group, said $75 billion in bond purchases is still big enough to support the stock market and he expects the Fed to move ahead with another $10 billion cut in its bond-buying program when it meets later this month. “Given that the Fed is still supporting us,” he said, the market shouldn’t take a big hit “despite the conflicting data.”

In recent weeks, a host of favorable economic benchmarks—showing expansion in manufacturing, brisk growth in gross domestic product, and strong exports—fueled expectations that the economy had shifted into a phase of faster growth that would translate into more jobs. Consumer confidence and spending have held up and businesses, with an eye to rising demand, are beginning to invest in new hires and equipment.

At Hayes Cos., a maker of metal parts in Pineville, La., “our biggest obstacle right now is finding skilled labor,” said Chief Executive James Hayes. The energy boom is driving business at the family-owned manufacturer, which makes parts for equipment in the oil and gas industry, as well as for train tank cars and other purposes.

“We need welders, fitters, machinists.…All the things manufacturing companies need, we need it,” Mr. Hayes said. “We have the work, we have no people.” The company aims to add another 75 jobs in the next few years to its current workforce of 140, he said.

The picture in Friday’s job report was far different from what Mr. Hayes painted. Government payrolls declined by 13,000 in December, and health care—usually a steady source of job growth—declined by 1,000. Construction jobs, which are often weather-dependent, declined by 16,000. Manufacturing payrolls expanded just 9,000.

One piece of good news in Friday’s report was a substantially revised increase in November’s tally, to 241,000 new jobs from 203,000. “Typically when you have upward revisions to prior months’ data, that’s an indication that things are getting better,” said Ward McCarthy, chief financial economist at Jefferies LLC. December’s 74,000 tally—the Labor Department’s first estimate—in turn, could be revised in next month’s report.

Friday’s weak jobs number may have been due less to weather than payback for an exceptionally strong reading in November, said Tom Porcelli, chief U.S. economist at RBC Capital Markets. It looks as if November’s “241,000 is an outlier just like [December's] 74,000 is an outlier,” Mr. Porcelli said. “The answer is somewhere in the middle.”

WSJ - Monthly Change in Nonfarm PayrollsSome labor-market softness is evident at Complete Advanced Maintenance Co., of Ebensburg, Pa. Camco just let six workers go, said President Warren Myers—marking the firm’s first layoffs in years. Camco, which tests and repairs electrical switching gear for heavy industry, mines and steel mills, has seen demand shrink for work on equipment for coal mines and coal-fired power plants.

The layoffs brought the company’s workforce down to about 45 employees. Mr. Myers said he hopes to call back the laid-off workers, but it is too soon to tell if business will pick up.

December’s jobs report puts a sober capstone on what had otherwise been a promising finish to 2013. The 182,000 average monthly jobs gains in the past year were nearly unchanged from those of 2012. The labor-force participation rate, which measures the share of the population available to work, declined in December from 63% to 62.8%, returning to the 35-year low touched in October. The ranks of those looking for a job for more than a year was 2.6 million in December.

Long-term unemployment, a hallmark of the 4½-year recovery, changed little between November and December. The number of people out of work for 27 weeks or longer held steady at 3.9 million last month, or 37.7% of all unemployed individuals.

WSJ - Where Jobs Were Added

In late December, federal emergency unemployment benefits to 1.3 million long-term unemployed expired. In some states, unemployed individuals could have received benefits for up to 73 weeks before the program expired. Lawmakers in Washington are considering an extension but remain divided about a number of aspects, including how to pay for it.

Meanwhile, last month’s most significant job gains were in sectors that traditionally aren’t high-paying, such as retail, which added 55,000 positions. The temporary-help sector increased by 40,000.

Bracing for breaking into a tough job market, Adam Kleven began looking for work months before his graduation last month from the University of Michigan, where he studied political science and communications.

Mr. Kleven, who is 21 years old, said he applied for more than a dozen jobs before landing his first interview. He ended up with two job offers as a legal assistant and started work this past week with a Northville, Mich., firm.

“I feel lucky,” he said. “I have a lot of friends with business degrees who are still looking for jobs, and I’m a liberal-arts major.”

DataViz: What Your Favorite Drink Says About Your Politics


Graphic courtesy Jennifer Dube, National Media Research Planning and Placement LLC
[Click on the image to enlarge]

Former Mississippi governor and uber-Republican Haley Barbour loves bourbon. Franklin Roosevelt mixed martinis. And, as it turns out, those two partisans have something in common with their base voters: Consumer data suggests Democrats prefer clear spirits, while Republicans like their brown liquor.

Democratic drinkers are more likely to sip Absolut and Grey Goose vodkas, while Republican tipplers are more likely to savor Jim Beam, Canadian Club and Crown Royal. That research comes from consumer data supplied by GFK MRI, and analyzed by Jennifer Dube of National Media Research Planning and Placement, an Alexandria-based Republican consulting firm.

The results are fascinating: Analyzing voting habits of those who imbibe, Dube found that 14 of the top 15 brands that indicate someone is most likely to vote are wines.

If you saw someone at your New Years party drinking Kendall-Jackson or Robert Mondavi wines, that person is highly likely to vote, and they’re likely to vote Republican. Someone who saviors a Chateau Ste. Michelle Merlot, one of Washington State’s top producers, or Smoking Loon, they’re likely to cast ballots for Democrats.

Columbia Crest, Ravenswood, Francis Coppola and Charles Shaw (better known as two-buck Chuck) all produce wines Democrats favor. Fish Eye, Bogle and Franzia drinkers are more likely to lean right.

And, perhaps not surprisingly, given the relative youth of those involved, people who take shots of Jagermeister or Don Julio are much less likely to vote.

The ironies abound. The comedian Bill Maher once accused House Speaker John Boehner of doing a shot of Wild Turkey every time House Republicans voted to defund Obamacare; little did he know Wild Turkey is one of the most heavily Republican brands. Smoking Loon, the Democratic-leaning wine, was formerly run by Don Sebastiani, who served three terms in the California state Assembly — as a Republican.

Rum appears to be the most bipartisan drink. Both Bacardi and Captain Morgan Spiced Rum fall right in the middle of the political spectrum.

So, for those hoping the spirit of bipartisanship infuses 2014, perhaps ringing in the new year with a rum punch is the best way to celebrate. Send a shot of Jim Beam to your friends at the Republican National Committee, and a shot of Jameson to your friends at the Democratic National Committee.

Champagne, as it turns out, is mostly a Democratic drink.


Source: Reid Wilson, What your favorite drink says about your politics, in one chart, GovBeat, The Washington Post, December 31, 2013.

DataViz: 217 Years of Homicide in New York City

NYC Murder Rates

As of Dec. 29, 2013, the number of homicides recorded for New York City for 2013 stood at 332. It’s a drop of 20% below the homicide rate of 2012 (419 murders) and the first time in over half a century that the city saw less than one murder a day on average. The historical data for homicide rates come from the National Archive of Criminal Justice Data.

The reasons behind the dramatic decline of the past two decades will continue to spark fierce debate. Was the drop in the 1990s due to police commissioner William J. Bratton’s focus on broken windows, or the impact of the Supreme Court’s Roe v. Wade decision legalizing abortion, as famously argued in Freakonomics? And did more recent declines happen as a result of “proactive policing”—programs such as “stop and frisk” and “Operation Crew Cut“—or in spite of it?

NOTE: Readers of the original article on Quartz have commented that the above chart is misleading because it doesn’t take changes in population into account. That is true in general, but it in this particular case, adjusting for population does not do much to change how the data look and takes away from the chart’s simplicity—the point is to express the total number of murders that took place in a given year.

Nonetheless, it’s a fair point, so here is a chart of murders in New York City on a per capita basis going back to 1900.

NYC Murder Rates Scatter Plot
Source: Ritchie King, Onwards and upwards, 217 years of homicide in New York, Quartz, December 31, 2013,

Data Visualization: 10 Corporations Control Almost Everything You Buy

Who owns what

(Click to enlarge)

Ten mega corporations control the output of almost everything you buy; from household products to pet food to jeans.

According to this chart via Reddit, called “The Illusion of Choice,” these corporations create a chain that begins at one of 10 super companies. You’ve heard of the biggest names, but it’s amazing to see what these giants own or influence.

(Note: The chart shows a mix of networks. Parent companies may own, own shares of, or may simply partner with their branch networks. For example, Coca-Cola does not own Monster, but distributes the energy drink. Another note: We are not sure how up-to-date the chart is. For example, it has not been updated to reflect P&G’s sale of Pringles to Kellogg’s in February.)

Here are just a few examples: Yum Brands owns KFC and Taco Bell. The company was a spin-off of Pepsi. All Yum Brands restaurants sell only Pepsi products because of a special partnership with the soda-maker.

$84 billion-company Proctor & Gamble — the largest advertiser in the U.S. — is paired with a number of diverse brands that produce everything from medicine to toothpaste to high-end fashion. All tallied, P&G reportedly serves a whopping 4.8 billion people around the world through this network.

$200 billion-corporation Nestle — famous for chocolate, but which is the biggest food company in the world — owns nearly 8,000 different brands worldwide, and takes stake in or is partnered with a swath of others. Included in this network is shampoo company L’Oreal, baby food giant Gerber, clothing brand Diesel, and pet food makers Purina and Friskies.

Unilever, of soap fame, reportedly serves 2 billion people around the world, controlling a network that produces everything from Q-tips to Skippy peanut butter.

media consolidation

And it’s not just the products you buy and consume, either. In recent decades, the very news and information that you get has bundled together: 90% of the media is now controlled by just six companies, down from 50 in 1983, according to a Frugal Dad infographic from last year.

It gets even more macro, too: 37 banks have merged to become just four — JPMorgan Chase, Bank of America, Wells Fargo and CitiGroup in a little over two decades, according to this Federal Reserve map.

The nation’s 10 largest financial institutions hold 54% of our total financial assets; in 1990, they held 20%. As MotherJones reports, the number of banks has dropped from more than 12,500 to about 8,000.

(Click to enlarge)

bank consolidation


Source: Chris Miles, 10 Corporations Control Almost Everything You Buy — This Chart Shows How,, October 31, 2013,

A Classification of Chart Types (Jorge Camoes)

A Classification of Chart Types

Jorge CamoesJorge Camoes (photo, right) of, posted an interesting blog the other day about chart classification.  A few weeks ago, Jorge needed a classification of chart types for his upcoming book, and reinventing the wheel was the last thing he wanted to do. He started with Andrew Abela’s well-known classification and the Juice Analytics version. It was a good starting point for him, but it did not fit into his work, so Jorge decided to design his own classification (it’s always nice to have new standards), inspired by this one but also by others, like Stephen Few’s Chart Tamer.

Here is Jorge’s idea: a chart can:

(a) help you compare data points faster but keeps each data point as the basic information unit


(b) help you generalize  the data and find patterns, making the data points less relevant. These roles should be as mutually exclusive as possible (but in real world that’s harder than expected).

There are six types of questions, three of them involving data comparison and the other three data reduction. The questions are:

  • Comparison: comparing and sorting data points;
  • Composition: part-to-whole comparisons;
  • Distribution: comparison of data points along an axis;
  • Relationship: relationship patterns between two or more variables;
  • Evolution: time patterns;
  • Profiling:  pattern comparison.


  • The first row lists the most commonly used chart in the category (it’s a fact, not something he agrees with);
  • Only charts that can be made in Excel are included;
  • Depending on the question and the task, a chart type can be found in more than one category;
  • You may find it bizarre to list a dot as a chart type, but one/off dots are critical in some tasks (monitoring) so I though they deserved to be included;
  • There are no neutral and objective taxonomies.

I found this to be a useful new classification chart to add to my bag of tricks. It is motivating me to make one that is MicroStrategy-specific. Let me tinker a bit and see what I come up with. In the interim, I would love to hear your thoughts and comments.

Stay tuned.



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