Here I keep up with all things codes, and write about any challenges in the field I've encountered and could be of use to the wider community. My struggles could very easily have been somebody else's, and there's nothing like finding a well documented article to get you over the hump of whatever may be challenging you. I also include other topcis I find interesting, either hobbies or just things from living in the New England area. My hope here is to contribute as much to the coding community as it's contrubuted to me.
It is well believed that a country’s GDP correlates with the expected life span of it’s citizenry. For my latest assignment with Codecademy I analyzed the data of six countries from 2010 through 2017. In the box plot graph above we see the life expectancy of our six countries. The extreme outlier being the nation […]
In my latest Codecademy project I was assigned to use Python and sklearn’s KNeighbor algorithm to find the attributes that could potential make a tweet go viral. But first a quick rundown on what is K nearest-Neighbor (KNN). KNN is a great way to classify data. KNN takes in data points, and uniquely categorizes them […]
In the second part of my Codecademy project I was assigned to build an Naive-Bayes algorithm to tell whether a tweet someone wrote originated from either NYC, London, or Paris. Not gonna lie that sounds hella cool, but before I carry on what is a Naive-Bayes algorithm? NBA is a popular classification machine learning algorithm […]
In my latest codecademy project I used a survey from FiveThirtyEight on What Do Men Think It Means To Be A Man? The whole article is worth a read, and I think these sort of surveys are great for K-Means cluster analysis. After reviewing the survey I decided to look at one questions in particular: […]
Any important part of working with data is the ability to manipulate it into useful data. Whether that’s cleaning it up, or transforming the table so it can be easier to use. Cleaning data is usually the first step in any data science project, and can be where you spend most of your time. How […]
For the second part of my cleaning data series, I’ll go over some simple techniques used to clean data in Python. Python is a powerful tool that constantly amazes me, both in its ability and simplicity. Reviewing data with it can go a long way once you know it. First, how can Python help you […]
Recently I was able to analyze some data from the National Parks Service on endangered species. This project had me using key functions of python to reshape data and plot graphs. Like any good data scientist being able to extract meaning from data is paramount, and as my quest to share knowledge grows, I hope […]
Most practitioners don’t like to mention it, but I’m just following the money, and nothing takes to data science like money. The well-off may like to preach the story of the self made man, but nothing is more adverse to risk-taking than established fortunes, and what is data science if not the most un-risky understanding […]
In my latest article on data science I’ll go deep into using Seaborn. A visual module in python that charts different graphs for us. For my data-set I’m going to use the micro-loan nonprofit group Kiva to get a peek into how loans are distributed. If you want to follow along or find some other […]
Python objects are an essential tool when programming. It can bring real dynamics to what you are trying to achieve, and broaden the creative scope one can accomplish when writing a script. So I wanted to explain some of the basics, and lay out the case for why coding in python can be one of […]
