python_fundamentals

• Original Python seminar given at Fordham University on December 8th, 2018 (parts 1 and 3 stem from this session)
• A more basic seminar given on February 9th, 2019

Overview

Students will learn Python fundamentals, working through basic computer science concepts, practical exercises, and data- and analysis-oriented programming.

The sessions will be divided into two main components, with the first serving as an "Intro to Programming, with Python" sort of class, and the second as an introduction to the NumPy library and, primarily, the Pandas library, both of which are key tools for any analytical Python programmer.

Each part will run approximately two hours, with a 15-minute break in between, and will include lecturing, interactive programming, and Q&A. This will be a fast-paced session; the hope is that the session will provide exposure to relevant, foundational concepts that students can continue to explore outside of the session.

Instructor Bio

Abe Lerman is the Lead Data Scientist for Contently, a SoHo-based technology company focused on corporate branding. He spent the prior year or so as a Python and Data Science Consultant in the Financial Services industry, contracting at Elliott Management and The Blackstone Group. Prior to that, he worked as a Data Scientist in the ad-tech space. He earned a Master of Science degree in Quantitative Finance from Fordham University, and a Bachelor of Arts degree in Mathematics from Skidmore College.

Seminar Details

Part 0: Python Ultra-Basics

• Variables and operators
• Iterables
• Flow control
• Functions

Part 1: Python Basics

• Variables and operators
• Iterables
• Flow control
• Functions
• Classes

Part 2: Analytical Python

• Reading and cleaning data
• Relational data analysis: descriptive statistics, group-by's, joins
• Data visualization

Part 3: Analytical Python

• Reading and cleaning data
• Relational data analysis: descriptive statistics, group-by's, joins
• Data visualization
• A quick look at scikit-learn

Note

This will be a hands-on session - the students will benefit from trying to run the material we discuss. As such, students should come prepared, having downloaded and installed Python and the necessary libraries a priori (I can offer technical support as needed, but this is not the best use of time). The easiest way to do this is to go here, and click the green "Download" button for Python 3.7.

Note the above link leads to a download of the Anaconda Python distribution, which provides Python + a whole lot of third-party libraries and othertools. Students do not have to get Python this way - this just provides an all-in-one download. These notebooks can be run with the following installed:

• Python 3.6+
• numpy
• pandas
• sklearn
• matplotlib
• jupyter

Jupyter Keyboard Shorcuts

To run a cell:

shift + enter

To enter command mode:

escape

The following commands must be run from command mode and operate at the cell level.

Copy, cut, paste cell:

c, x, v

New cell above, below:

a, b

Delete cell:

dd

Convert cell to markdown:

m

See all shortcuts:

h