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When & Where
Date: 
Thu, October 22, 2020 - 2:00 PM to 5:00 PM
Location: 
Remote (Zoom information forthcoming)
Description
Type: 

*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:

  • line
  • bar
  • scatter
  • boxplot

 

We'll also learn about styles and customizing plots.

Throughout the workshop, we'll discuss the plot types best suited for particular kinds of data.

Basic familiarity with the Python programming language is assumed. New to Python? Consider attending D-Lab's Python Fundamentals series.

Be sure to install Python before the workshop starts - this can take up to an hour to complete (link below).

Primary Tool: 
Python
Details
Training Host: 
Format Detail: 
Remote, hands-on, interactive
Participant Technology Requirement: 
Laptop, Internet connection, Zoom account

Basic Competency

These workshops are designed for participants with beginner fluency. They already have a little coding, tool or method experience but need to learn more intermediate applications such as conditional subsetting and appropriate data visualizations for their research. 

Examples: Introduction to Pandas, R-wrang, Data Visualization with Python, R-graphics, Survey Sampling, Weighting Data, Introduction to Qualtrics, Finding Health Statistics and Data, Data Viz Theory and Best Practices, Python Machine Learning, Machine Learning in R, Intro to Computational Text Analysis, Geospatial Fundamentals in Python/sf/QGIS/ArcGIS, Intermediate Tableau

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