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ams939's Academy of Natural Sciences of Drexel University COOP 2018 code repository

Python 0.14% Jupyter Notebook 99.86%
bioinformatics bioinformatics-data biological-data-analysis biodiversity python jupyter-notebooks internship ansp coop

coop2018's Introduction

Academy of Natural Sciences of Drexel University Spring-Summer 2018 COOP code repository

This is a repository for three major projects I completed during my COOP period at the Academy of Natural Sciences of Drexel University in Philadelphia from April - September 2018. Below is a bried summary of each project, project folders also contain documentation and examples of important aspects of the projects as README files. The projects have also been documented with examples as Jupyter Notebooks, many of the scripts have also been throroughly commented.

Projects included in this repository

Project # 1: API Prototype for a central repository to local database data pipeline

A prototype of a Python API that mimics the behavior of iDigBio's Python API (https://github.com/iDigBio/idigbio-search-api/wiki) but pulls data from a local PostgreSQL database. Scripts in this folder also facilitate pulling data from iDigBio with their API and loading it into the local PostgreSQL database. Documentation and examples for the usage of this API are located in the Notebooks folder in a folder called "Dataworkflow".

Project #2: Data Visualization Exploration with Jupyter Notebooks

An exploration into data visualization primarily using the Python module called Altair. This project consists of collection of notebooks within the Notebooks folder, in the "Intro to Altair Folder". The notebooks deal with a variety of different default datasets and visualize them in various ways. The primary purpose of these notebooks was for myself to learn using Altair and to illustrate some of the basic functionalities of Altair.

Project #3: American Feline Habitat Research Project

A research project focused on exploring the habitats of four species in the felidae family living in North & South America. These species are panthera onca, leopardus pardalis, puma concolor and lynx canadensis. The centra piece of this project is a machine learning algortihm known as the Self-Organizing Map, which will be used for analyzing collected species & habitat data.

Folders

APIPrototype - Contains Project #1 code

HabitatProject - Contains Project #3 code and Jupyter Notebook visualizations of project data at various stages. More information in folder's README file.

JupyterNotebooks - Contains Project #2 Notebooks, Project #1 documentation Notebook and Project #2 documentation Notebook.

If there are any questions about the code or projects within this repository, contact me at [email protected].

coop2018's People

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