Most efficient way to find rare Pokémon

Were you the kid who sat there analyzing the amusement park map before entering the park, planning out how you could visit the most rides in the least amount of time? If so, then this blog's for you, my data analyst kindred spirit!

And to get you in the mood, here's one of those amusement park maps. This is a map of Carowinds, the park I went to often when I was a kid:

carowinds_map

 

Some might call it overkill, but if you are serious about your Pokémoning then you will want to use every tool at your disposal - including the most powerful analytics software in the world! In this blog post, I show you how to use SAS software to optimize your search for rare Pokémon.

Let's say you've been playing for a while, and only have 15 of the more rare Pokémon left to catch. While you could try hatching them from eggs, you've decided to try a more analytical approach. You have perused all the online forums and compiled a list of possible sightings of these rare Pokémon, and then determined the closest location of each one. You can now plot these on a map using SAS' GMap Procedure: Read More »

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How to dress (your graph) for success!

The way your graph looks can make all the difference ... two people can graph the exact same data in essentially the same way, but one of the two graphs can be perceived as much better than the other. Hopefully reading my blogs will help you create the better graph!

Way back in my formative high school and college years (1980s & 1990s), there was a lot of emphasis on having the right look. A popular song at the time was ZZ Top's Sharp Dressed Man, TV shows like Miami Vice always had a certain fashion sense about them, and the Dress For Success book told us all what to wear for our interviews. My buddy Anil was probably the sharpest dressed guy in our dorm, and he is now in Abu Dhabi working for one of the largest sovereign wealth funds in the world ... so, apparently all that sharp dressing worked! Here's a picture of Anil dressed for a typical day at college (can you guess what year this was?)

anil_sharp_dressed_man

Well, graphs are no different ... If your graph doesn't have the right look, then it will not be nearly as successful. I recently found some interesting graphs showing social network poll results, that make a good example of this. They weren't bad graphs, per say, but they just didn't have the right look. Read More »

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SAS Author Spotlight: David Dickey

sas forecastingIn the spirit of our “40 and forward” theme to celebrate 40 years of SAS, this blog focuses on David Dickey, an accomplished SAS user since 1974 and a SAS instructor since 1981. He actually co-wrote the original Time Series SAS course in 1981, and helped with the most recent version. He is also the co-author of the classic, SAS for Forecasting Time Series, Second Edition, with John C. Brocklebank; and is currently working on a third edition.

Time series forecasting has come a long way since the first edition published! In this third edition the authors will demonstrate how to model and forecast simple autoregressive (AR) processes using PROC ARIMA, and you will learn how to fit autoregressive and vector ARMA processes using the STATESPACE and VARMAX procedures.

SAS software has also moved forward quite significantly.  Our state-of-the-art solution for large-scale automatic forecasting, SAS Forecast Server, includes the Time Series Studio GUI for time series exploration and segmentation, and the powerful SAS/ETS for econometric and time series analysis.

Forecasting tasks are also available in SAS Studio – click here for a free tutorial to learn about the forecasting tasks you can use in your analysis of time series data in SAS Studio. Read More »

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Do you trust statistics?

One of my favorite quotes is: "You can't believe everything you read on the Internet" - Abe Lincoln, 1868.

And that is especially true when it comes to graphs and statistics. Hardly a day goes by without me seeing a bad graph that misrepresents the data (either intentionally or unintentionally) . Here is a recent bad example I was surprised to find on Statpedia ...

internet_use_statpedia

At first glance the graph seemed like a reasonable way to plot the data, but upon closer examination I found a terrible problem that compromises the data integrity! ... They have plotted the survey results all evenly-spaced (probably as character values), even though the surveys were not performed at evenly-spaced date intervals! This seriously misrepresents the data, especially towards the left side of the graph, when the surveys were performed much less frequently (the slope of the line is much steeper than it should be). Also, after examining the source data, I found that they had left out the value for the first/oldest survey. Read More »

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Everything you need to know about the new Analytics Experience event

SAS is kicking off a new event Sept. 12-14 in Las Vegas called the Analytics Experience. It’s actually not completely new. In the past, we’ve held our annual Analytics and Premier Business Leadership Series conferences in the fall. But as the industry landscape continues to change – SAS continues to prove it’s leading the way.

What does that mean?  Today there is no separation between the analytical guru and the company thought leader. Analytics Experience will allow attendees to wear both hats at one event, offering the perfect mix of thought leadership, analytics, strategies and connections.

kelly_check

Kelly Check

I had the chance to interview SAS’ event organizer and marketer, Kelly Check, about the new changes and what attendees can expect at Analytics Experience 2016.

  1. What is new with the Analytics Experience? (Besides the name change)

Aside from the change in timing – the conference is now in September instead of October – the new twist is combining practitioners and the executives into one event. There’s no longer a boundary between business leaders and analytics pros! And with the new combination, there is a new pricing structure; conference fees are waived for executives (director+) as well as students; discounts are available to practitioners, faculty, partners and others.

  1. Why combine the Analytics and Premier Business Leadership Series conferences?

Former attendees shared feedback that they wanted more choices; they didn’t want to be limited by their title or organization. They wanted to network with analytics gurus of different backgrounds. So while executives can listen to detailed case studies, students and practitioners can hear big ideas from thought leaders. Every attendee can still customize their agenda for the most beneficial insights.

  1. Who should attend?

Anyone who wants to embrace the latest technology and find value in their data – no matter his/her title. Read More »

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How to use SAS software to capture Pokémon!

With the Pokémon Go craze sweeping the world, techies and programmers are looking to apply their skills to gain an advantage over the average user. In this blog post, I show how to use some of SAS' geospatial analytics capabilities to capture a Pikachu.

Let's say you know of a building that has an active Pokéstop with verified Pikachu sightings. First, you'll want to obtain (or create) a floor plan, and save it in an image file (png, jpg, gif, etc).

pikachu_graph_blog_floorplan

Next, you'll want to come up with a convenient coordinate system, and create a grid of unit cells by looping through the grid values in a SAS data step loop, and output 4 coordinates and an id variable for each cell. You can then use Proc GMap to draw the grid, and annotate the image of the floor plan behind the grid (here's my code).

pikachu_graph_blog_grid

Now you'll need to start collecting geospatial data that you can plot as colored areas on the grid. Here, I have determined the x/y grid locations of lures attached to this Pokéstop, and plotted them as dark brown areas on the grid. Can you detect any clustering or trends here? (Note that my friend Kenny, who was a professional/paid gamer, helped me with the finer details of this analysis.) Read More »

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When I grow up, I want to be a data scientist

GettyImages-73773904When I was growing up the term “data science” didn’t even exist, let alone dedicated “data scientist” roles. My friends and colleagues might argue that is because I am yet to grow up (!), but do not let this ruin my lead in to the fact that data science as a field and data scientist as a job title is a very recent smash hit, even though many were doing most of what we call data science decades ago.

Making an assumption that you have read widely on what data science is, beyond the ability to type data scientist into LinkedIn, you know that there are massive opportunities in the field and that these skills are in high demand. I have seen myself firsthand how hard it is to find these skills in the market. Becoming a data scientist can increase your paycheck and set you up for a challenging and rewarding career.

On top of this, a recent Money magazine and PayScale.com study showed that SAS skills are the biggest pay differentiator in the market. SAS and data science together could set you well on your path, so if you are sitting here wondering, “How do I work through the multitude of learning options available to me?” I am here to try to help. Below I have covered three approaches to set you on your path to becoming a data scientist, ideally a SAS skilled one as well!

Read More »

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Jedi SAS Tricks: Explicit SQL Pass-through in DS2

One of the things I’ve come to love most about DS2 is the tight integration with SQL which makes so many data prep chores so much less onerous. An example is DATA program BY group processing. With a traditional DATA step, you must first sort or index the source data before using a BY statement. For example, this program produces an error, because the data has not been properly sorted:

data new;
   keep make model cylinders;
   set work.cars;
   by descending cylinders make model;
   if _n_=10 then stop;
run;

But, because DS2 always retrieves your data with an implicit SQL query, there is no need to pre-sort the data. This program runs just fine:

proc ds2;
title 'DS2 BY processing with base SAS datasets' ;
title2'BY descending cylinders make model';
data;
   keep make model cylinders;
   method run();
   set work.cars;
   by descending cylinders make model;
   if _n_=10 then stop;
   end;
enddata;
run;
quit;

Results of DS2 BY processing without pre-sorting the data
And it makes no difference if the source data resides in SAS or in a Relational Database Management System (RDBMS) like Oracle. Read More »

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Putting the US in the EU ... bucking the Brexit trend!

What would it be like if the US was in the EU? I don't know how that would work out politically, but this map shows how it might look geographically (if the US was literally picked up and moved to Europe!)

My buddy Rick Langston is a bit of a map guy, and occasionally sends me cool examples. He recently sent me one he had seen on twitter (attributed to Randy Olson), that shows the continental United States overlaid on Europe at the geographically correct latitude. I was a bit surprised to see that the entire UK, and several other countries, were farther north than the US!

us_europe_orig

I'm not sure of any practical purpose for such a map, but I immediately knew I had to create one with SAS software! :)

First, I used Proc Gproject to clip the rectangular region of Europe out of the world map. Then I subset the continental US out of the world map, added an offset of 114 degrees to the longitude, and combined it with the Europe map. I plotted the combined map, and used a transparent color for the US.

I always try to make a few improvements when I imitate a graph, and here are the things I (hopefully) improved in this one: Read More »

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Pokémon: Gotta graph 'em all!

So, how many different Pokémon have you caught - and more importantly, how many different kinds are still out there that you haven't caught yet? I've created some graphs that might help you figure it out!

I think my previous blog post might have irritated some of the hardcore Pokémon players out there (based on their comments), by claiming that the only important Pokémon data is Nintendo's stock price. I enjoyed poking my Pokémon-obsessed friends ... but I'll try to make up for it. This time I'm plotting actual Pokémon data, which players might actually find interesting and useful!

To get you in the mood for a blog with real Pokémon data, here's a picture of my friend Jenni with a Spearow on her shoulder:

jenni_spearrow

When the most recent Pokémon game went viral, I started searching the Web to see what it was all about. One of the articles I found had some graphs in it, which of course caught my attention. Read More »

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