Working With Data Frames

Basketball has been heavy on mind lately. One reason being the All the Smoke podcast that I listen to with Matt Barnes and Stephen Jackson every week. I’ve been listening to the podcast since day one. Another reason has been the recent passing of Kobe Bryant, his daughter Gianna and the seven other lives that were taken in that helicopter accident. When I think of Kobe, I think about my brother and the kids I went to school with. They would shout ‘KOBE’ anytime they threw something. 

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Intro to R Programming

R is a language I’ve been curious about for some time. I started learning a bit about Python when I kept reading and hearing about R. Python and R are the two programming languages most commonly used in data science. Out of curiosity and a bit of boredom, I decided to learn a bit of R syntax. After that experience, I decided to continue learning R. I decided that I would learn more R using DataQuest’s Data Analyst in R track.

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Why Data Science?

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Photo by Jon Tyson on Unsplash

For the past several years, I’ve explored different career paths in tech. I’ve played around with web development but found that was not a good fit for me.  For a long time, I wanted to be a UX designer which later turned into UX writing. I spoke with people who worked in UX, attended meetups and different events that were UX focused. Many of the classes I took as part of my graduate program were design-focused.

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Welcome to Data Sci Dani!

One of the greatest discoveries a man makes, one of his great surprises, is to find he can do what he was afraid he couldn’t do.

— Henry Ford

I’ve decided to face my fear and enter the world of data science. I’ve always admired data visualizations and have long been interested in how data is used to make business decisions. However, the idea of programming combined with statistics has always intimidated me a bit. My goal is to become a data analyst (and eventually a data scientist) by strengthening my programming and statistical skills. I’ll share what I’m learning; I’ll discuss projects, books/articles I’ve read and really any thoughts I have pertaining to data science.