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When & Where
Date: 
Mon, October 26, 2020 - 1:00 PM to 3:30 PM
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Location: 
Remote (Zoom information forthcoming)
Description
Type: 

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:

  • 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

New to Python? Consider attending D-Lab's Python Fundamentals series!

Link: Github repository for the Introduction to Pandas workshop

Training Keywords: 
Data Manipulation and Cleaning, Introductory Programming
Primary Tool: 
Python
Details
Training Host: 
D-lab Facilitator: 
Aaron Culich
Format Detail: 
Hands-on, interactive
Participant Technology Requirement: 
Basic familiarity with Python such as that provided by the D-Lab's Python Fundamentals workshop series. Participants should have a computer with Python 3+ and Jupyter installed. Follow the github link above for more info.

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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