ABOUT ME
Python Developer & Data Analyst
The Occasional Consultant
I am a Python developer, data analyst, freelance writer, published author and visual artist.
Among other things, I have experience in Web development & design as well as in systems programming, data analysis & visualization [repository]. I am currently working on data analytics, Natural Language Processing & Machine Learning with Python while employing pandas, numpy, scikit-learn, pETL, matplotlib, NLTK, WordNet, etc.
N. Joaquín Acosta
Additionally, I am also keenly interested in how data is and may be used to drive advertising, maximize business' e-commerce potential, and lead to deeper insights in the biological sciences.
I am passionate about translating input from quantitative analyses into specific and actionable business insights for small - medium businesses & organizations; using data to make predictions that will facilitate the process of developing insights, make marketing recommendations, predict customer churn, create customer segmentation & develop models and response analyses based upon discoveries.
I have worked extensively with small & mid-sized businesses within a variety of sectors, including travel & tourism, entertainment, technology, education & legal. I also enjoy working with non-profit organizations, eg., Sea Turtles 911 & Marine University.
Personal projects are available for viewing in my GitHub repository.
I'm exceptional at:
Data Analytics & Visualization
Python
Web Development & Design
Research, Writing & Editing
MY WORK
Recent Projects
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THOUGHTS & STUFF
The 4 Types of Data Analytics
Correlation between the Power Clean & the Shotput in Collegiate Athletes
I have added a new repository to my GitHub repositories which aims to answer the following question: does better performance (ability to lift heavier weights) in the power clean lead to better performance (greater distance) in the shot put for female collegiate athletes?
The question is explored in Python (Jupyter notebook) and uses Kendall's τ Coefficient to test our hypothesis.
Road Bridge Condition (2013)
A simple interactive bar chart using the C3.js data visualization library to plot the percent of all structurally deficienct and all functionally obsolete bridges across all US states in the year 2013. The same can be done in Python using the C3PyO wrapper for the aforementioned data visualization library. Demo only.
