Percentage of NCAA Teams Playing for the National Title in Each Sport

Back in 2014, the NCAA said that the BCS would be no more, and the College Football Playoff was born. College Football moved from two participants to four participants, a 50% jump!

However, with 128 teams in the FBS, that means the percentage of teams making the playoffs is a whopping 3.125%.

Meanwhile, the Men’s Basketball playoff is upon us, which lets in a field of 68 teams across 351 teams, for a percentage of 19%.

What about every other NCAA sport? If you were to play a different sport, what percentage of teams have a shot at the end of the season of playing for the National Title?

Information was gathered about all of the NCAA sports where championships are offered. The focus was on Division I, but some sports have a “combined” championship which spans divisions, like Skiing and Women’s Bowling. Source data was originally collected in January 2013 and updated in March 2015 where new information was available.


For Men’s sports, on average 28% of teams make it in. For Women’s sports, 21% of teams. Men’s, despite the low representation percentage in Football, get a boost from Wrestling, Fencing, and Gymnastics.

Men’s and Women’s basketball have a similar number of competing teams.  In fact, there are only two schools which offer Men’s but not Women’s, The Citadel and VMI.

  • Men’s – 351 Teams, 68 Playoff Spots, 19%
  • Women’s – 349 Teams, 64 Playoff Spots, 18%

Also, take a look at the difference between the Football Bowl Subdivision (1-A) and the Football Championship Division (1-AA).

  • FBS – 128 teams, 4 Playoff Spots, 3%
  • FCS – 126 teams, 24 Playoff Spots, 19%

One could argue that every week during the regular season in the FBS is an “elimination game” on the road to the playoffs, and there are certainly the non-playoff bowl games to consider, but I will leave that debate to the masses.

The other way to “split” this data is to look at it by the type of sport that it is. Some sports are truly team sports, like Football, Basketball, and Soccer.

There are also a few sports which are at its core individual sports, but the structure of the event brings a team element into play and the team as a whole qualifies for the event. Examples include Cross Country, Golf, and Women’s Bowling.

Other sports are based on individual qualification and the “team” component only comes into play if you as an individual have qualified for the Championships. Examples of this include Fencing, Wrestling, Swimming, and Track.  Hence, sports like these might have a higher number of teams representing them, but may only have a single athlete or two from that school that have qualified.


The bar charts give you a percentage, but the following scatter plots should help illustrate the volume of teams participating and making the playoffs.


And here’s that same chart colored by sport type:


So if you want to be playing for a national championship, Men’s FBS Football may not be the best sport to do it in. Have you considered Men’s Gymnastics?

Source information here: NCAATeamsAndPlayoffs_2015.csv

I am also happy to hear comments and corrections on information that I might have missed.

‘Jeopardy!’ and ‘Wheel of Fortune’ Airtimes in Graphs and Maps

Category: ‘Game Shows’

Answer: Between ‘Jeopardy!’ and ‘Wheel of Fortune’, this program is shown first each day.

Question: What is…well, it depends on where you live.

I grew up in New Jersey, and every weeknight, ‘Jeopardy!’ started at 7:00pm and ‘Wheel of Fortune’ came on directly after at 7:30pm.  One year when I was visiting family in Virginia, and I entered a Bizarro world where ‘Wheel’ was on FIRST, and ‘Jeopardy!’ second.

Many years later, I had a thought.  What do most Americans see first?  ‘Jeopardy!’ or ‘Wheel’?

There are 210 different media markets in the United States.  From the research I’ve gathered from the ‘Jeopardy!’ and ‘Wheel’ websites, 206 of the 210 media markets have a local TV affiliate which airs the shows.  Now I will admit that the four missing markets may indeed get these shows.  Perhaps the listings on the show websites were not complete, or perhaps they receive these broadcasts from neighboring markets.  I’m not quite sure.

129 of the markets show ‘Jeopardy!’ first, and 77 of the markets show ‘Wheel’ first.  There’s also information available about the approximate number of televisions in a given media market, and to that end 74 million televisions get ‘Jeopardy!’ first, and 40 million get ‘Wheel’ first.


However, just seeing the numbers isn’t the full picture.  What does this information look like on a map?  Well, here you go.


It’s interesting to take a geographic look at markets which show ‘Wheel’ first.  There’s a concentration on the east coast, and pockets across the nation.

For the majority of the nation, when you watch these shows, they come one right after the other.  That’s not the case across the entire nation, as this next set of graphs will show.


‘Jeopardy!’ tends to get a much earlier start time overall.  A number of markets will choose to show ‘Jeopardy!’ early on in the day, especially those markets in the mid-west which tend to show ‘Jeopardy!’ before the local news, and ‘Wheel’ a few hours later right before Prime Time.  If you want to be the first in the nation to see the show, I recommend moving to the Montgomery-Selma, Alabama market.  They show new episodes at 9:30am local time.  The last market in the nation to air new episodes is the Lafayette, Louisiana market, which starts the show at 12:36 AM.  KATC-3 airs ABC Prime Time shows, Local News, Jimmy Kimmel, Nightline, Inside Edition, and then finally good ol’ ‘Jeopardy!’.

Wheel of Fortune is a much different story.  There are four time slots: 6:00, 6:30, 7:00, and 7:30.  That’s it.  No deviation.  No late nights or early mornings.

Here’s a look of the build over time, with respect to local time. You can see ‘Jeopardy!’ gradually building up through the day, and then in the ‘Power Hours’ between 6:00 and 8:00, ‘Wheel’ is shown for everyone.  And finally, our friends in the Lafayette market get to see ‘Jeopardy!’ in the late late evening.


And here’s what this looks like on a map.  The lighter the color, the earlier in the day it’s shown.  For ‘Jeopardy!’, you’ll notice that most of the early showings happen in the Central time zone.  Interestingly, most of the largest markets in the US show ‘Jeopardy!’ closer to prime time.  However, Chicago shows it at 2:30pm local time on the station WLS.


‘Wheel’, as mentioned before, is much more uniform.  Earlier 6pm to 7pm times in the Central and Mountain time zones, with Eastern and Pacific tending to air in the 7pm to 8pm hour.


Now, what happens if we take a look at time as it relates to a single time zone?  A show may air at 7:00pm in the East, but when it’s shown at 7:00pm on the west coast, it’ll be 10:00pm back east.  These graphs show the build over time with time zone shifts applied as they relate to the Eastern time zone.  So, when something is shown at 7:30pm Eastern and 6:30pm Central, they’re actually on at the same time.


Here’s that build over time, with Montgomery kicking things off at 10:30am and Lafayette shutting it down at 1:36am Eastern Tim the following morning.  ‘Wheel’ is more spread out in this case, with the final showing at 11:30pm Eastern Time in the Honolulu market.


Here’s what those time shifts look like on a map, with the gradients scaled to show later times in a darker hue.  First, ‘Jeopardy!’.


Then, ‘Wheel’.


When we look at the difference in times between shows within the same market, the majority of airings have one show directly after the other.  When that is not the case, ‘Jeopardy!’ will often be shown first, then a gap, then ‘Wheel’ later on in the day.  In fact, there is only one market in the US which shows Wheel first and then doesn’t show ‘Jeopardy!’ right after, and that’s our friends in Lafayette who show ‘Wheel’ at 6:30pm and wait until 12:36am to show ‘Jeopardy!’.


Here’s those time differences shown geographically as well.  Blue hues are ‘Jeopardy!’, and Red hues are ‘Wheel’.  Notice there are only two red hues, since ‘Wheel’ is always followed directly by ‘Jeopardy!’ in those markets, save for Lafayette.


Finally, I wondered which networks aired the shows, as in ABC, CBS, FOX, NBC, MYTV, or Independents.  The results were actually quite surprising and extremely spread out, but skewed in favor for ABC, CBS, and NBC.  Here’s a look at the number of markets plus the number of televisions within those markets for both shows.



You’ll notice that in terms of number of markets, it’s fairly even between ABC, CBS, and NBC.  However, ABC affiliates have coverage in the top four markets (New York, Los Angeles, Chicago, and Philadelphia) and six of the top eight, which skews the number of TVs highly in their favor.

Fun Fact: In 23 of the 206 markets, the two shows are actually shown on DIFFERENT networks.  Most of these cases tend to be in the Central and Mountain time zones.




Overall, I hope you enjoyed.  If you want the tl;dr version:

  • ‘Jeopardy!’ is shown first in more media markets in the US
  • ‘Jeopardy!’ times are more spread throughout the day
  • ‘Wheel of Fortune’ has ‘Power Hours’ from 6pm to 8pm where the entire nation sees the show
  • The number of ABC, CBS, and NBC affiliates is fairly even, although ABC has more of the higher-population markets

Update: May 6, 2014

Not surprisingly, I’ve gotten some of the data points wrong. Reddit user RAS310 asked me:
Just the other day I was thinking about which affiliate airs the shows the most. Do you know which market is the sole one that airs Wheel at 6:30 Eastern? I thought none of them aired the show before 7.

This caused me to look back into some of my original data points. Well, it seems that the question has revealed a problem with the Wheel of Fortune website and with the KML files I used to draw the maps.

The airtime at 6:30 Eastern came back as the ROCHESTER, MN-MASON CITY, IA-AUSTIN, MN. This is wrong for two reasons.

Wheel recently changed how you can look up airtimes. Before it was a clickable map of the US, and it showed you the TV Markets and what time they aired Wheel. They went to an newer version based on ZIP code look up. I looked up a sample ZIP code for Austin, MN (55912). When you plug it into the Wheel website, KXAN-TV, a station in Austin, TX showed up. I didn’t realize I was looking at a Texas station, so I picked up the wrong airtime.

That didn’t explain the time zone shift though, as TX and MN are both Central time. It also looks like there’s a mix-up in the KML file of the TV Markets I obtained that switched the labels for Rochester, MN and Rochester, NY. I did time-zone shifts based on the codes for those, so Rochester, MN is EST for the color shifts, and Rochester, NY is CST for their color shifts.

So, a number of errors on my part in gathering the data.

Happy to hear any additional thoughts in the comments.

Measuring My Kia Optima Hybrid MPGs

I recently leased a 2012 Kia Optima Hybrid.  I’ve been doing a lot of driving for work lately, so I decided to get a mid-size car that could handle a lot of highway miles plus give me decent MPGs.

Being the numbers nerd that I am, I’ve been keeping track of various different stats.

The EPA estimates for the car when I bought it were 40 Highway & 35 City for an average of 37.

After the first nine fill-ups, I’ve been disappointed.  I was averaging 29.9 MPGs, WAY below the EPA estimates.

Here’s a graph showing the numbers through the first nine fill-ups:

My numbers are extremely off.  Why is this?  There are a few options:

  • The brand of car doesn’t actually give the MPGs promised
  • My specific car doesn’t actually give the MPGs promised
  • I’m a terrible driver who drives inefficiently
  • The gallons being dispensed at the pump are not the gallons actually being put into the car

Let’s examine each of these:

 “The brand of car doesn’t actually give the MPGs promised.”

Right after leasing the car, Kia (and parent company Hyundai) was docked by the EPA for overstating their MPG numbers.  The new estimates were 39 Highway and 34 City, for an average of 36.  Kia is trying to make it right, though, through partial reimbursements that you can read about here.

Even with the “new” estimates, however, I’m still way off the mark.

How do I compare with other Kia Optima Hybrid owners?  My co-worked showed me an amazing site called Fuelly, which is essentially a fuel stat-tracking website.  The added value of the website, however, is that you can look at all other owners of the same model and see how you compare to them.

Here’s the link to the list of other 2012 Kia Optima Hybrid owners.

Here’s some basic statistical data about the Optima, as of December 20, 2012:

MPG City: 34
MPG Highway: 39
Mean: 34
Median: 33
Mode: 30
Range: 20
Standard Deviation: 4.91

The mean is right at the MPG City number, and the median and mode are to the left of that.

For comparison’s sake, here’s a screenshot and some basic statistical data about the 2012 Toyota Prius from December 20, 2012.

MPG City: 51
MPG Highway: 48
Mean: 49.04
Median: 49
Mode: 49
Range: 20
Standard Deviation: 4.41

The mean, median, and mode all fall within the EPA estimates.

Perhaps my sample size is too small?  My personal number of 30 MPGs is -.81 Standard Deviations off the mean, so perhaps it means that problem is multi-faceted: The MPGs for the brand are not what was promised, AND there are problems with my particular car.  Let’s examine the second half of that point next.

“My specific car doesn’t actually give the MPGs promised” and “I’m a terrible driver who drives inefficiently”

According to my rough statistics, I’m -.81 Standard Deviations off the mean.  So, what’s wrong with my particular car?  Is it a problem with the car or with the driver?  Or both?

In regards to the car, it’s a brand-new lease, so I would hope that there is nothing wrong with it.  After the latest fill-up, I decided to check the tire pressure.  The tires are meant to have 44 psi, but each tire was hovering between 30 to 34.  Yikes!  I’ll have to see if this gives me an improvement.

Looking at various sites about getting better fuel efficient driving, I stumbled up this post specifically about the Kia Optima Hybrid, including this video about “best practices”.

So perhaps the problem is my individual car (which I will have to continue investigating), but perhaps the problem is my driving?  I feel that I’ve tried to adjust to the hybrid, but perhaps I can I still do better?

Instead of a tachometer, the Optima Hybrid has an “efficiency” gauge that gives instant feedback of “good”, “medium”, and “poor” driving.  There’s even an “Eco Score” that gives you points for driving “efficiently”.  I throw that in quotes because it’s based on what the car thinks is ideal, but from a gamification point-of-view it creates an incentive for me to try to drive better to earn virtual “points”, which should (in theory) correspond with better MPGs.  I didn’t start tracking my Eco Points until my 7th fuel-up, and in a future post I’ll see if there’s a relationship between tank MPG and Eco Points.

[Image from CNET.]

Another potentially contributing factor would be where I live and the current weather.  I’m doing a lot of travel between Pennsylvania and New Jersey, and it involves a lot of up and down through rolling hills.  We’re also moving into winter, and as a result the car is very cold in the morning and has frost, meaning I need to burn fuel to defrost and to heat the car up when I start driving.  Will other seasons be better for my MPGs?

“The gallons being dispensed at the pump are not the gallons actually being put into the car”

The last thing we’ll look at today is about the trust you have at the pump about the gallons that you purchased.  At the end of November, I had two fuel-ups at the same station in New Jersey where my MPGs seemed really low compared to the average.  When I fueled up the second time there, the tank was about 1/6 full but I noticed that they dispensed nearly a full tank’s worth of fuel.  Something seemed off here.

Fortunately there are consumer-protection groups such as local Weights and Measures departments.  I placed a call and they’re investigating, so we’ll see if I was dealing with a crooked gas station, or perhaps my far really did take a full tank of fuel.

From an overall point of view for MPGs, since it’s a ratio of miles divided by gallons, you have to assume that the gallons being dispensed at the pump are the actual gallons being put into your tank.  If not, any calculation you do will be suspect.


So what’s next?  I see a few actions:

  • Take my car back to the dealer for a check-up
  • Try to drive my car with more efficiency in mind
  • Post pictures of graphs to a new Tumblr site
  • Post fuel updates to my Fuelly account
  • Keep making graphs, because graphs are cool

Got any tips for fuel-efficient driving?  Leave them in the comments!

My Halloween Candy in Graphs – 2012

Last year I decided the best way to have fun on Halloween was to make graphs.  It was so much fun, I decided to do it again this year.

When the night was over, we had a whole lot more leftover candy than last year.  Did we buy too much candy?  Did not enough Trick-or-Treaters visit this year?  Why didn’t we run out of candy like we did last year?

The basic premise was the same:

  • Buy candy
  • Count the candy before the night begins
  • Count the number of kids that trick-or-treat
  • Count the candy midway through the night
  • Note the time when the last piece of a specific candy is taken
  • Count the candy at the end of the night
  • Make graphs

Last Year’s Stats – 2011

  • 419 Treats, 379 Treats taken by Trick-or-Treaters
  • 189 Trick-or-Treaters
  • 2 Hours of Trick-or-Treating
  • 2.01 Treats taken per Trick-or-Treater

This Year’s Stats – 2012

  • 430 Treats, 307 Treats taken by Trick-or-Treaters
  • 216 Trick-or-Treaters
  • 1:45 Hours of Trick-of-Treating
  • 1.42 Treats taken per Trick-or-Treater

What a difference!  We bought about the same about of Treats as the year prior, yet we had a LOT more leftover candy, even though there were more Trick-or-Treaters.

Because of this, we only ran out of two types of candy: M&M’s Peanut and Skittles, and we ran out of those types in the final 15 minutes.

Here’s a graph showing the starting and ending percentages of the different candies:

Purple marks if it was taken LESS relative to other candies.
Orange marks if it was taken MORE relative to other candies.

Let’s also group the candy types together and see if there’s a trend:

Candy that was in Bar form (for example, Hershey’s and Snickers) was less popular than candy in Bit form (for example, M&Ms and Starburst).

Sugar-based candies (Skittles and Starburst) were more popular than Chocolate and Nut candies.  This is a departure from last year, when we had a bunch of Starburst left over!

In last year’s post I noted that trying to put all candies individually on a line chart would make it messy, and very hard to get any information out of the chart.  This year, I decided to use a Trellis chart to help alleviate that problem.

In this chart, each brand gets its own view.  However, for the candy types where I didn’t have a large starting amount, it’s hard to discern differences.  If we start each brand at 100% and work downwards from there, we can see trends of how quickly (or slowly) a particular type of candy was taken, and since we counted at the mid-point, we can see which types went faster earlier or later in the evening.


Here is where this gets REALLY geeky.

Last year I put together a basic line chart highlighting the inverse relationship between number of Trick-or-Treaters and the amount of pieces they took.  As it turns out, my formula for calculating that number was flawed.

Here’s last year’s chart:

What was flawed about it was the way I calculated the number of pieces per Trick-or-Treater.  Last year I took a full count of the candy at specific times:

  • At the start
  • During the middle
  • When a brand of candy ran out
  • At the end

Here’s a screenshot of my Excel sheet from last year.  Any cell with a gray background means an actual observation, and white cells represent a formula to approximate what the best-guess of the remaining amount was.

The problem was with the old formula.  Last year I had assumed that the amount between observation points should have been:

S = Second Observation Point
F = First Observation Point
RR = Number of 15 Minute Intervals Remaining until Second Observation Point
TR = Total Number of 15 Minute Intervals between First and Second Observation Point

S + ((F-S) * RR/TR) = Candy Remaining for a Given Interval

This is pretty similar to a standard depreciation formula as you move from Date A to Date B.

However, that assumes the same amount of Trick-or-Treaters in each 15-minute interval, which was NOT the case.  Given that I knew how many kids visited within each 15-minute interval, I could better refine the formula to approximate the number of pieces remaining within each time block.

S = Second Observation Point
F = First Observation Point
RTT = Number of Trick-or-Treaters remaining until Second Observation Point
TTT = Total Number of Trick-or-Treaters between First and Second Observation Point

S + ((F-S) * RTT/TTT) = Candy Remaining for a Given Interval.

This leads to a much more refined formula.  Here’s last year’s chart again, with the old and new formulas:

So now that we’ve established a new (and hopefully better) formula, we can compare this year to last year using the same methodology:

Interesting things to note:

  • For the most part, the amount of Trick-or-Treaters visiting in each 15 minute block was about the same, with the exception of 7:30.  We had a rush of kids at that point!
  • Because we didn’t run out of very many types of candy this year, it was much more difficult to get more specific numbers behind how many pieces each kid took.  However, it can be generally observed that on average, each kid took less than they took last year, especially towards the end of the night.
  • From this it’s easier to explain why we had so much more leftover candy than last year; each Trick-or-Treater took less on average.


This year we picked up seven different types of multi-pack bags.  In every instance, we received more candy than what was promised on the bag, which was a nice plus.

Favorites and Non-Favorites

Last year we saw that sugar-based candies where the least likely to be taken by the Trick-or-Treaters.  What about this year?

This is a relatively boring graph, in that there’s very little movement.  That in itself tells a story, though, in the fact that for the most part, kids were taking candy in roughly equal proportions.  Was this because we broke the three types out into three separate buckets?  Were kids just evenly grabbing from each?

Compared to last year, the increase of sugar candies compared to the average is the most interesting. What was the difference?  Did more kids take a liking to Skittles and Starburst?  Did we do a better job preventing the smaller Starburst packages from falling to the bottom of the bucket?  These are the mysteries of life that allude us all.
Just for kicks, here’s the graph comparing Bar candies to Bit candies:

Again, very little movement!

Intervals for Trick-or-Treating

We had 216 total Trick-or-Treaters.  I was able to track two things with each group:

  • How many kids in a group
  • What time that group arrived

There were 60 total groups of Trick-or-Treaters, with an average size of 3.6.

Here’s the distribution of groups:

This makes for interesting visualizations when you decide the time interval to split it by:

Planning for Next Halloween

  • Do we have too many types of candy?  I think that we do.  Next year, I want to simplify it by having only two or three choices.  This will also allow me to get better counts at more frequent intervals, resulting in more accurate calculations.  It will also create an actual choice for the Trick-or-Treater.  “Do I want Candy A or Candy B?”
  • Right now, with so many choices, most kids don’t think about it.  They take some candy, say thank you, and move onto the next house.  However, if you declare that they have a choice, it makes them think about what they might actually want to take.
  • What types of candy should we offer next year?
  • I wanted to also note the type of costumes Trick-or-Treaters had, and note trends, however with so many kids it was difficult to make effective observations and take notes.  I wonder what I can do next year to make capturing information easier?

Now, who wants to help me eat this leftover candy? Month In Review – 2011-11

Every month we’re going to attempt to do a meta-review of the site, using graphs of course.


We had a “soft launch” towards the end of October with a few hits, but we really took off in November, starting with a post about my Halloween Candy experiences this year, which was shared out by Geekadelphia.

Red bars represent days with new posts, and Blue bars are days without new posts.

We thought an interesting stat to look at would be the number of pageviews per visitor.  On days where the diamond is above 1, it represents where on average people clicked on something else within the site beyond just their initial entry page.  The highest day for that was 11/10/2011, when Drew had his post on Scrabble.

All in all, we’re very happy that in our first month we had 737 visits and 1,049 pageviews.  Thank you!

Visits by Post


(266) – my halloween candy in graphs
(222) – site index
(161) – most valuable cities in ticket to ride
(85) – what word should i play
(62) – top 10 most popular cities in north america
(50) – most populous city by state
(33) – better than watching the detroit lions
(23) – geotagging visualization of philadelphia
(18) – twitter on 11-11-11
(12) – graphs we love: espn’s stats info twitter
(9) – graphlink: invisible bread
(4) – nfl championships per year
(1) – stanley cup 2011 sparklines
(1) – welcome to graphgraph
(102) – category, tag, & author pages (we kept this separate to keep the focus on individual posts or the site index)

Twitter, Facebook & Google Reader

Right now that chart is pretty barren.  However in future months we’ll see a line chart (with hopefully a lot of growth).

Facebook – 5 Likes -> Click here to like us
Twitter – 6 Followers > Click here to follow us
Google Reader – 7 Subscribers -> Click here to access the RSS feed and add us to your favorite reader

Thanks again to everyone for making this first month a success!

Most Populous City By State

The United States has a lot of people in it. However, we wanted to take a look at what was the most populous city within each state, and graph it out.

We took a look only at incorporated cities (as opposed to metropolitan areas) and found some interesting results, especially towards the bottom.

Familiar cities like Boise (ID) and Salt Lake City (UT) are outside the top 100, while cities like Portland (ME) and Cheyenne (WV) aren’t even in the top 500. Burlington, the most populous city in VT, didn’t even crack the top 1000.

Data was compiled from the Census (via Wikipedia 1 2) for cities with population over 100,000 and the World Gazetteer for the remaining Top 1000 cities.

Here’s a text file of the data.

We think taking a look at this in a bar chart gives real perspective on the differences from state-to-state.

Which Word Should I Play?

You are playing Scrabble. Or maybe, because we live in the future, you are playing Words With Friends on a supercomputer that fits in your palm. You have the following tiles: CMOHVER. A quick glance sees that you can play COVER for 10 points. Oh wait, you can also play MOVER (10 points) or even HOVER (11 points). Assuming there are no delightful puns or perhaps a clever response to the word your opponent just played, all three of these plays are basically the same. So which should you play? Does it even make a difference? And if it does make a difference, could a graph possibly help you here?

Continue reading “Which Word Should I Play?”

Top 10 Most Popular Cities in North America

Can you name the ten most populous cities in North America?

I tried and I know that I didn’t get them all.  Specifically, I missed a few cities of our neighbors to the south in Mexico and the north in Canada, which probably speaks to my poor knowledge of geography more than anything else.

Here is the list (taken from Wikipedia), compiled based on the most recent census data from each county:

Rank Country City Population Census
1 Mexico Mexico City 8,873,017 2010
2 USA New York City 8,175,133 2010
3 USA Los Angeles 3,792,621 2010
4 USA Chicago 2,695,598 2010
5 Canada Toronto 2,503,281 2006
6 USA Houston 2,100,017 2010
7 Canada Montréal 1,854,442 2006
8 Mexico Tijuana 1,784,034 2009
9 Mexico Ecatepec de Morelos 1,658,806 2010
10 USA Philadelphia 1,556,396 2010

It’s nice to have them all in a list, but if we graph this data we can hopefully get some additional value from this information.

Continue reading “Top 10 Most Popular Cities in North America”

My Halloween Candy In Graphs

Halloween usually means candy.  Less commonly, Halloween means making geeky graphs on the distribution of candy you give out to Trick-or-Treaters.

This is the first Halloween at my new house, so we didn’t know what to expect.  So, why not graph out everything?

The Stats

  • 419 Treats, 379 Treats taken by Trick-or-Treaters
  • 189 Trick-or-Treaters
  • 2 Hours of Trick-or-Treating
  • 2.01 Treats taken per Trick-or-Treater

Total Candy

Yes, I counted all the candy.  Geekier still, I graphed the starting percentages and ending percentages.

What does it all mean?  Are sugary candies less popular in my neighborhood than straight-up chocolate?

Continue reading “My Halloween Candy In Graphs”