[Plsgs] FW: Workshop: Using interactive data visualization to make sense of large datasets

[Armendariz, Amanda - (amandao)]

Amanda Armendariz, MSW
Student Support/Graduate Coordinator
School of Plant Sciences
College of Agriculture & Life Sciences
University of Arizona
Forbes bldg room 319
520-621-1219

From: Oliver, Jeffrey C - (jcoliver) <jcoliver at arizona.edu>
Sent: Tuesday, November 1, 2022 5:38 PM
To: Armendariz, Amanda - (amandao) <amandao at arizona.edu>
Subject: Workshop: Using interactive data visualization to make sense of large datasets

Hi Amanda,

Would you mind sharing this announcement with graduate students in Plant Sciences? Please let me know if you have any questions.

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Using interactive data visualization to make sense of large datasets

Date: Friday, November 18, 2022
Time: 3:00pm - 4:00pm
Location: Virtual
Register: https://libcal.library.arizona.edu/event/9824650

Description
As sensor technology improves, data volumes grow. We now live in a sea of data collected by our phones, smartwatches, and home assistants like Alexa. Science is not any different, new sensors are enabling the collection of large datasets that can be mined for new scientific discoveries. In plant science, sensor technology is being applied to study how plants grow under drought conditions. This workshop will introduce you to common data wrangling Python packages: Pandas allows us to interact with data related to plant growth, while Plotly Express allows us to generate interactive visualizations to make sense of these data. You will learn how to open data, filter data, slice data, and generate informative interactive visualizations from large datasets. Knowing how to handle and make sense of data will be increasingly important, and this workshop is your first step towards that!

Required experience & hardware
This workshop is aimed at anyone who is learning to code or advanced coders with little experience in data visualization. Command line and/or programming experience in Python is helpful, but not required. A computer with internet access is necessary to join the workshop and access the learning materials.

This workshop is part of the University Libraries' Digital Scholarship & Data Science Fellowship program. You can find out more about the program and other workshops being offered through the series at https://data.library.arizona.edu/data-science/ds2f. If you have questions about the program, please e-mail Jeff Oliver (jcoliver at arizona.edu<mailto:jcoliver at arizona.edu>).

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Cheers,

Jeff


Jeffrey C. Oliver, Ph.D (he/him/his)
Data Science Specialist
Data Cooperative<https://data.library.arizona.edu/>
Research Engagement, University Libraries
University of Arizona
Tucson, AZ 85724-5079
GitHub jcoliver<https://github.com/jcoliver>
ORCID 0000-0003-2160-1086<https://orcid.org/0000-0003-2160-1086>
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