Programming Resources: Python

Intro to Python with an emphasis on data management and analysis,. Variable assignment, loops, conditionals, lists, and functions using the Jupyter notebook IDE.

Introduction to common tools for data analysis in Python, including Pandas dataframes and Pyplot for graphing and charting.

This workshop covers how to gain access to data available through a RESTful API through Python. Workshop participants will learn how to traverse a tree structure and convert it to other data structures, such as a tabular dataframe, prior to analysis.

This workshop is designed to introduce participants to the benefits of using Python and SQL in combination to analyze data sets.

In this workshop, participants will use MongoDB and the CORD-19 dataset from the Allen institute to: 1) Query a Sample Mongo DB, using filters and aggregations. 2) Use PyMongo to populate a remote (Atlas) MongoDB with JSON documents downloaded from the CORD-19 research data set. 3) Query the CORD-19 research data set, create a text search index, and parse results as JSON documents and Pandas dataframes.

This workshop will provide a review of basic machine learning concepts, and will introduce Python and scikit-learn tools for machine learning. Emphasis will be on the programming work involved in preparing data, populating and building a ML model using scikit-learn libraries, and reading results.

This workshop provides a review of python text processing skills and techniques that will be used extensively in the DSI machine learning and natural language processing workshops.

This workshop is designed for programmers, data scientists, and researchers who would like to get started with machine learning for document processing and natural language processing.

This is the official guide for beginners using Python to program.