I am proud to say that my half-marathon training has increased my step count. January 2016 has been my best month yet. Totally patting myself on the back. Below I've graphed my average daily step count and my total monthly step count and comparing it to Will's for the last 6 months. Recall that I had my Fitbit stolen in October which is why there's a dip in October 2015. My average daily steps in January: 13,608 versus Will's 12,966. My total monthly steps in January: 421,858 versus Will's 401,965. I had a 14.5% increase in activity from December to January. While Will had a minuscule drop in step activity (about -0.4% change). Below is what the daily step counts looked like. The spike on the 17th is my personal record for most daily steps. It also beats Will's daily record of 25,370 steps. I got 27,026 steps that day. Note that in 2015, my daily step record was 20,825. In January 2016 I managed to get above 20,000 steps 5 times. (I only got above 20,000 steps 3 times in 2015). Hooray for running and training! In the last couple of weeks I've slowed down on my training due to a bug I caught, but I'll be running again soon. Stay tuned for February's update next month :)
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Happy Valentine's Day! Combine today with Stata and you get a heart shaped graph. The one I made below was made using graph3d in Stata.
Did you notice I also used the "<3" marker labels here? Hearts on hearts on this graph ;)
Below is the code I used to make the heart graph. I added the title, note, and other options using the graph editor. /* Author: Belen Chavez Stata Heart Code Happy Valentine's Day <3 */ clear all set obs 463 gen t = . local c = 1 forv i = 0(0.05)`=2`c(pi)''{ replace t = `i' in `c' local ++c } gen x = 16*sin(t)^3 gen y = 13*cos(t)-5*cos(2*t)-2*cos(3*t)-cos(4*t) gen mlab = "<3" graph3d x y t , colorscheme(cr) scale(3) markeroptions(mlab(mlab))
Happy Valentine's Day to my blog readers <3
Let's get local. I'm talking about San Diego beer. This is the third post regarding data I've downloaded and cleaned from BreweryDB. For a while now, I've been wanting to map all the breweries in San Diego County. Why? Well, for starters, San Diego is a great place for craft beer enthusiasts and I keep hearing about how many breweries there are in SD County. Secondly, why not? If you've got the data, use it. So now with BreweryDB and their brewery information, I can finally do that. See the map I made below. Note, however, that this map doesn't include ALL breweries in SD County. The data from BreweryDB that I downloaded is only for breweries that had at least one "verified" beer entry in their database. Also, I only included unique breweries, leaving out tasting rooms or additional brewery locations. This left me with 76 breweries which have been mapped below:
This visualization was made with Stata and Google Charts API using the links to brewery icons from BreweryDB. Any breweries without icons are shown with default red markers.
Of the available beers in BreweryDB for these 76 SD County breweries, the make-up of beer styles is as follows:
It's a pretty good variety of beer and it's great if you love Pale Ales, IPAs or Double IPAs as those seem to be the most common types of beers brewed in SD (within the North American Origin Ales category).
Using Stata's gpsbound command, the 2010 Census county shape files, and the latitude and longitude brewery information within the BreweryDB dataset, I summed up the number of breweries in each county and each state.
*This only includes breweries from BreweryDB that had at least one verified beer entry in the database.
California ranks first in terms of unique breweries among states and San Diego County ranks first among the counties from this dataset. San Diego is a pretty great place if you like craft beer (and even if you don't, San Diego is a pretty likable place with perfect weather). The breweries here make all kinds of beers and most tasting rooms are dog and family friendly. Go check one out if you're around. Some of my favorite SD County breweries are:
This is a continuation of the work I did in part 1 using BreweryDB data. I've cleaned most files with brewery and beer information (only 44 files could not be parsed using insheetjson in Stata, but I'm working on those separately, they will be included in my analysis at a later time). For now, this analysis only includes files which I was able to parse.
So, who makes beer? Breweries. What styles are there? Well let me tell you. There are the following styles in BreweryDB. Under each style there are up to 170 beer categories (or sub-styles?) like the ones I described in Part 1.
Looks like the unique count of breweries with North American Origin Ales style surpasses all other counts with close to 3,500 in this (somewhat complete) sample. With the explosion of micro-breweries, and all kinds of people getting into beer, I guess I'm not too surprised. So, what types of beers are contained within this style? I've summarized them here. The top 50% of the North American Origin Ales are made up by the following styles: American-Style India Pale Ale (19%), American-Style Pale Ale (15%), American-Style Amber/Red Ale (11%) and the Imperial or Double India Pale Ale (9%). See table below.
Interesting. To be honest, I don't like IPAs, pale ales, or IIPAs. They're just too hoppy for my taste. Pass me a Belgian instead. On that note, here are the counts of breweries who make Belgian & French Origin Ales.
A lot lower than the North American Origin Ales, but with the IPAs growing out of control (or so it feels like they are here in San Diego), I guess that makes sense. Plus, while there are fewer breweries that make Belgian and French Ales these types of beer seem to have been around longer. For example, the earliest established brewery with Belgian and French Ales is in 1121 by Leffe versus 1471 for the earliest North American Ale which interestingly enough corresponds to the beer style "Golden or a Blonde Ale" made by none other than a Belgian Brewery: Hetanker. Aren't Belgian breweries just the best?
I've mapped the breweries that make Belgian and French Origin Ales below that are located in California, Texas, North Carolina, New York, and D.C. Why these states? These are the states where most of my site's visitors are from :)
Like I said in the first post, there's a lot of data and I've only shown you a little bit of it! Look forward to more posts that use additional variables that I haven't even mentioned and maybe cooler maps. Cheers!
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AuthorMy name is Belen, I like to play with data using Stata during work hours and in my free time. I like blogging about my Fitbit, Stata, and random musings. Archives
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