Python is one of the most popular programming languages for data analysis. Therefore, it is important to have a basic working knowledge of the language in order to access more complex topics in data science and natural language processing. The purpose of this one-day course is to introduce the development process in python using a project-based, hands-on approach.
This course is focused on Python development in a data context for those who aren’t familiar with Python. Other courses like Python Data Analysis focus on data analytics with Python, not on Python development itself.
The main workshop will run from 11am – 6pm with an hour break for lunch around 1pm. For those that are new to programming, there will be an optional introductory session from 9am – 11am aimed at getting you comfortable enough with Python development to follow along in the main session.
Introductory Session: Python for New Programmers (9am – 11am)
The morning session will teach the fundamentals of Python to those who are new to programming. Learners would be grouped with a TA to ensure their success in the second session. The goal of this session is to ensure that students can demonstrate basic concepts in a classroom environment through successful completion of hands-on exercises. This beginning session will cover the following basic topics and exercises:
- Executing Programs
- Object Oriented Programming
- Write a function to determine if input is even or odd
- Read data from a file
- Count the words/lines in a file
At the end of this session, students should be familiar enough with programming concepts in Python to be able to follow along in the second session. They will have acquired a learning cohort in their classmates and instructors to help them learn Python more thoroughly in the future, and they will have observed Python development in action.
Main Session: Building a Python Application (11am – 6pm)
The afternoon session will focus on python application development for those who already know how to program and are familiar with Python. In particular, we’ll build a data application from beginning to end in a workshop fashion. This course would be a prerequisite for all other DDL courses offered that use python.
The following topics will be covered:
- Basic project structure
- virtualenv & virtualenvwrapper
- Building requirements outside the stdlib
- Testing with nose
- Ingesting data with request.py
- Munging data into SQLite Databases
- Some simple computations in Python
- Reporting data with JSON
- Data visualization with Jinja2 and Highcharts
We will build a Python application using the data science workflow: using Python to ingest, munge, compute, report, and even visualize. This is a basic, standard workflow that is repeatable and paves the way for more advanced courses using numerical and statistical packages in Python like Pandas and NumPy. In particular, we’ll use and fetch data from Data.gov, transform it and store it in a SQLite database, then do some simple computation. Then we will use Python to push our analyses out in JSON format and provide a simple reporting technique with Jinja2 and charting using Highcharts.
For more information and to reserve a spot, go to http://bit.ly/1m0y5ws.
Hope to see you there!
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