Introduction to Pandas in Python

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with 'relational' or 'labeled' data both easy and intuitive. It enables doing practical, real world data analysis in Python, simliar to spreadsheet tables in Excel or data frames in R.

In this workshop, we'll work with example data and go through the various steps you might need to prepare data for analysis.

We plan to cover:

• pandas data structures
• loading data
• subsetting and filtering
• calculating summary statistics
• dealing with missing values
• merging data sets
• creating new variables
• basic plotting
• exporting data

Prior knowledge: Students should have basic Python experience. Completion of D-Lab's Python Fundamentals workshop series (or equivalent) should be sufficient.

Technology requirement: A laptop with one of the following is required:

1. Anaconda (based on Python 3.5, though 2.7 is okay); or 
2. Installed Python 3.5 (2.7 okay), IPython version 3.0+ (with notebook support) or Jupyter 1.0, pandas 0.17+, Matplotlib 1.3+; or 
3. BCE Summer 2015