Introduction to Pandas

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http://pad.software-carpentry.org/0xWpg5jKKk

Lesson Maintainers: Greg Watson

This is an introduction to Pandas designed for participants with some basic Python programming experience. These lessons can be taught in a day (~ 6 hours). It starts with an introduction to importing CSV files using the Pandas package, then moves on to work with data frames, how to calculate summary information from a data frame, and a brief introduction to plotting. Then it covers some more advanced stuff.

Getting Started

Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow.
These lessons assume no prior knowledge of the skills or tools.

To get started, follow the directions in the “Setup” tab to download data to your computer and follow any installation instructions.

Prerequisites

This lesson assumes basic knowledge of Python, including how to load modules and write simple Python programs that use functionality such as loops and functions. The Software Carpentry Programming with Python or Plotting and Programming in Python lessons are good measures of the prerequisite skills necessary for this lesson.

For Instructors

If you are teaching this lesson in a workshop, please see the Instructor notes.

Schedule

Setup Download files used in the lesson.
00:00 Starting With Data How can I import data in Python?
What is Pandas?
Why should I use Pandas to work with data?
01:00 Indexing, Slicing and Subsetting DataFrames How can I access specific data within my data set?
How can Python and Pandas help me to analyse my data?
02:00 Data Types and Formats What types of data can be contained in a DataFrame?
Why is the data type important?
02:45 Combining DataFrames Can I work with data from multiple sources?
How can I combine data from different data sets?
03:30 Plotting with ggplot Can I use Python to create plots?
How can I customize plots generated in Python?
04:15 Data Ingest & Visualization What other tools can I use to create plots apart from ggplot?
Why should I use Python to create plots?
05:00 Time Series How can I load a time series in Pandas?
What features are available for working with time series?
05:45 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.