Are you a visualization and graphing expert? Can you identify which tool (R, Excel, Tableau, SPSS, Matlab, JS, Python, or SAS) was used to create each of these graphs? No cheating!

I recently read Tim Matteson's blog where he presented 18 graphs, and had his readers try to guess which software was used to create each of them. I thought it was an interesting exercise, but I was a little disappointed in the graphs. My buddy Paul Kent said I should create my own new/improved version of each graph, and I thought that sounded like a splendid idea! Be sure to click the link above to see the original versions, so you can better appreciate the improvements.

Can you determine which software I used to create each of my improved versions?

**Chart 1**

The biggest problem in the original graph, was that the colors and order of the bar segments didn't make sense - seems like they should be bad-to-good, but the original graph had them in alphabetical order. Also, the Xnn labels along the left-side axis were cluttered and difficult to read. In my version I spaced the labels out more, and also left-aligned them so the 'X's lined up and made them easier to read.

**Chart 2**

In the original chart, having a colored area behind the questions made it look (at first glance) like those were bars, therefore I didn't color that area in my graph. I was a bit confused by the numbers to the left and right of the bars in the original, therefore in my version I color-coded these numbers so the user would know at-a-glance that the left number represented 'disagree' and the right number represented 'agree'. In survey data like this, I think it's important to be able to see whether over 50% of the respondents agree or disagree, so I added a reference line at 50%

**Chart 3**

In the original chart, they had the axis labels along both the left and bottom, showing each label twice. In my plot, I placed the label along the diagonal boxes, allowing me to only show each label once (and also eliminating the sideways labels along the left axis). I used transparent plot markers, so you can see where markers are *stacking*. I also use a different color marker from the axes and text, so the markers stand out more.

**Chart 4**

The original chart used so many grid lines that I found it difficult to follow a line to the axis. I used years rather than months along the x-axis, because that seemed easier to understand for such a long time period (quick - how many years is 70 months!?! see what I mean!)

**Chart 5**

For this one, I left it pretty much as-is, except I placed the labels inside the longer bars (rather than outside), thereby making more room for the bars. I also explain what 'cola' is in the title, since it's an acronym most people probably aren't familiar with - wouldn't want people thinking this was a graph about soft drinks!

**Chart 6**

For this chart, I didn't have the original data, so I decided to go with some data that was similar, but less dense. I'm not sure what the original chart was trying to show, but I can't imagine it was doing a very good job of it (looked like a cluttered mess of points & lines to me).

**Chart 7**

In the original chart, I don't think the circles showed up very well against the black background - therefore I didn't put any circles on my version (if you want to see a black map with circles, have a look at my map with animated circles). Be sure to click here, to see the full size map (to get the full effect)!

**Chart 8**

The original chart was a simple scatter, with '+' markers, and dark grid lines. In my version, I used transparent round markers - this way you can see when multiple markers are stacked in the same location. I also use light grid lines, so the grid doesn't compete with the markers for your attention. I also added some summary statistics in the top/left corner of the graph.

**Chart 9**

I'm not a big fan of using black backgrounds in a graph ... but if you're going to create any kind of graph, at least show the scales along the sides!

**Chart 10**

This is another one I didn't have the exact data for, so I used some similar data. The biggest change I made was using transparent markers so you can see where multiple markers are stacked on top of each other. I also use a grid of reference lines from both axes, rather than just one axis.

**Chart 11**

Although the original chart didn't have any labeling, I suspect it was some of Fisher's classic iris data set, therefore I used some of that data in my chart. The first improvement I made was labeling the graph, so you quickly know what I'm plotting. I also annotate a picture of a labeled iris flower, so you know what a petal and a sepal is.

**Chart 12**

I'm not a big fan of using 3d bars on a 3d map to show data, like they did in the original graph - the taller/front bars inevitably obscure some of the shorter/back bars, etc. Therefore in my graph I show how to plot data as markers on a 2d street map.

**Chart 13**

In the original chart, I'm not sure exactly which year(s) of earthquake data they use, since there is no title or label. In my chart, I show all the major earthquakes for a 40+ year time period, and I also center my map on the Pacific ocean (so it better shows the 'ring of fire'). I also use circles rather than filled dots, so it's easier to see almost-overlapping markers.

**Chart 14**

In charts like this, I really don't like when people use a diverging color scheme (gradient shades of 2 colors, meeting in the middle) - those should be used when the scale goes from bad-to-good, etc. In this case, where the colors represent a simple "Percent of Trials" gradient shades of a single color should be used. They left-justified their Cancer Conditions, which placed them far from the chart, and made it difficult to see which colored blocks went with which label - I right-justified them. Also, it was difficult to determine whether white boxes were light gradients, or no-data. In my chart, I use a hatched pattern for no-data, to make the distinction more obvious.

And in the bottom (bar) chart portion, I was a bit confused by the numbers on top of the bars - after a bit of scrutinizing the graph, I found that the numbers represent the difference in the Actual and Expected time. Therefore I tried to make that more obvious in my bar chart.

**Chart 15**

I don't really have access to any software to do solid-modeling, so instead of doing an animation of a solid-model of the earth (which looked pretty pitiful in the original blog), I am using a different animation. Click here to see it animated.

**Chart 16**

For this chart, my version is a little cleaner, and I've moved a few of the labels to new locations.

**Chart 17**

The original chart had somewhat willy-nilly axis tick marks, and I wasn't real keen on using circles in the legend to coincide with the lines in the graph. I didn't have this exact data, therefore I chose some similar time-series data that I could show three lines overlaid. Notice that in addition to the color legend, I also added a label to the end of each line.

**Chart 18**

For this one, I used slightly different colors, and slightly larger/bolder text, but aside from that it was already a great graph. :-)

OK - time to enter your guesses in the comments section! Which software(s) were used to create which graphs?

Yep, I used SAS to create **all** 18 of these charts! And if you'd like to see the SAS code, I've set up an examples page.

*This content was reposted from the SAS Learning Post. Go there to view the original.*