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Pandas is a Python package that provides 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 will 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
Prerequisites: D-Lab’s Python Fundamentals introductory series or equivalent knowledge.
GitHub Repository: https://github.com/dlab-berkeley/Python-Data-Wrangling(link is external)
Software Requirements:Installation Instructions(link is external) for Python Anaconda
Is Python Not working on your laptop?
Attend the workshop anyway, we can provide you with a cloud-based solution(link is external) until you figure out the problems with your local installation.
Feedback: After completing the workshop, please provide us feedback using this form
Questions? Email: dlab-frontdesk@berkeley.edu(link sends e-mail)