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.

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:

Overview

This workshop helps you to step up your R skills with functional programming. The purrr package provides easy-to-use tools to automate repeated things in your entire R workflow (e.g., wrangling, modeling, and visualization). The end result is cleaner, faster, more readable and extendable code. I highly recommend you to take this workshop (1) if you still write copy-and-paste code, (2) exclusively rely on for loops for automation, and (3) want to know about the joy and power of R functional programming.

Prerequisites

*NOTE: Due to limited resources and staff, we are only able to offer workshops to UC Berkeley affiliates, partners (LBL, UCSF), and invited guests. We respectfully ask you not to register if you are not affliliated with UCB, LBL or UCSF.*

Overview

For this workshop, we'll provide an introduction to visualization with Python. We'll cover visualization theory and plotting with Matplotlib and Seaborn, working through examples in a Jupyter (formerly IPython) notebook. The following plot types will be covered: