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Women Who Code Connect!

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Last week I had the honor of being able to attend Women Who Code Connect. I was a whirlwind day of networking, great talks, fun workshops and awesome swag. The morning started off bright and early at the Twitter building in San Francisco. People from all over the country came to recruit or to get a job. The energy was high as we stood in line for our badges. And there was a fun buzz in the air. As a job seeker myself I was excited to make new connections and hope to make an impression. I was pleasantly surprised when I didn't have to wait to network. People in line were so eager that I was able to do some great networking before even getting my badge! After getting my badge and going up to the main conference area I was blown away by all the booths and fun food set up for us that day. There were over 20 booths from different companies and every single one of them was highering! I was so excited I didn't even take the time to see what they had for breakfast. I started in straig...
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Open Source Platforms ... Why aren't you using them yet?

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Open Source Platform. To any data manager, data scientist, or coder when you hear or see those words you think gold mind. Open source platforms are the best thing to utilize for your work. First its free! Second its peer reviewed (in most cases)! Third it gives you the ability to use it as you please! And the list goes on... I think you get my point. For me, having open source tools and resources are essential to my work. I have little to no budget at my disposal for my projects. So when I need other resources to enhance the data set, open resources are my only option. And lucky for me there are tons of data sets, platforms, and tools out there that help me with my work every day. More and more people are learning how to code, but not as many as should. I understand the hesitation behind this. In my generation, scientists used paid programs like Jump, SPSS, Systat, SigmaPlot, MatLab, etc. Because it was the trend... if you had to pay for it it must be the best. Right? Also why...
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Shortcuts to making your R code run faster! Part 1

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The goal of running code is usually to make tasks easier, faster, and more efficient. Sometimes however, it may feel like you are always waiting for your code to run. We will go through a few fun tips that can help speed up that process. 1. Preset your vector or Matrix destinations. Believe it or not that presetting your vector destinations saves your code a lot of running time. This is because when you run a loop or a function and you don't preset your destination R has to hold those variables in its cache memory, however, if you have preset vector ready for variables the values will be routed to that vector. Take this simple example below for instance: # Creating a destination with non-specific number of variables for output vector X = c () # Start timing the loop Strt <- Sys.time () for (i in 1 : 100000 ){ X[i] = i } print ( Sys.time () - Strt) # Print how long it takes to run the loop ## Time difference of 8.179752 secs Ok lets try it with a m...
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