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Auto-generated via `{sandpaper}` Source : 7ded246 Branch : main Author : Dazhong Xia <[email protected]> Time : 2024-12-12 15:21:58 +0000 Message : Merge pull request #4 from catalyst-cooperative/learner-profiles Add learner profiles
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title: FIXME | ||
title: Learner Profiles | ||
--- | ||
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This is a placeholder file. Please add content here. | ||
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## Sparky Watts | ||
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#### Profile | ||
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Sparky Watts is a first-year PhD student in an interdisciplinary energy studies department. | ||
As she's preparing for her qualifying exams, Sparky is looking at the available energy | ||
data sources that she could use for her doctoral research. | ||
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A few years ago, a postdoctoral scholar in her research lab worked on an analysis of hourly | ||
demand data published by the EIA. With a clear research question in mind, Sparky is | ||
interested in building on the postdoc's data cleaning scripts and updating them to | ||
include newer years of data, but the code is scattered over several Jupyter Notebooks | ||
without much documentation. None of the other lab members remember much about the | ||
project. | ||
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Though Sparky has taken a Python Software Carpentry workshop before and done some coding | ||
using Pandas in Jupyter Notebooks, she's not quite sure where to start. The data is | ||
larger than other datasets she's worked with before, and she can't even open it in a | ||
spreadsheet to look at a few rows without Excel crashing. Inspired by her experiences | ||
of looking at this postdoc's code, she's hoping to write software that others will be | ||
able to use and adapt for their own work long after she's left the lab. | ||
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#### Background knowledge and skills: | ||
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Has energy domain knowledge and a research area in mind | ||
Recently attended the Data Analysis and Visualization in Python for Ecologists workshop | ||
Can install software using GUI’s | ||
Has recently used Jupyter Notebooks and Pandas to analyze tabular data | ||
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#### Goals: | ||
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Adapt existing cleaning scripts to run more reproducibly on an open-source dataset | ||
Analyze data that's too big to work with in a spreadsheet | ||
Write and document code in a way that others can build on in the future | ||
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## Gene Rator | ||
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#### Profile | ||
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Gene Rator is a postdoctoral researcher studying the carbon intensity of electricity | ||
production. | ||
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He writes his own analysis pipelines using Python scripts that he’s developed over the | ||
years and is comfortable transforming data using Pandas. | ||
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Recently, Gene sent his scripts to a collaborator at another research institute, who | ||
struggled to run the pipeline because it’s heavily tied to Gene's own research | ||
environment. | ||
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Gene needs to publish his own pipeline to both share his work and fulfill publication | ||
requirements. More worryingly, he recently tried re-running the pipeline after making | ||
some small tweaks in response to feedback from a collaborator, and got some unexpected | ||
results - something might be going wrong somewhere in his pipeline, but it's hard to | ||
tell where. | ||
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Gene needs strategies to debug his existing workflow, and a way to effectively share his | ||
work with collaborators and the public. | ||
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#### Background knowledge and skills: | ||
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Proficient in writing Python scripts using Pandas | ||
Uses Git to manage his code locally | ||
Can install software using conda and write his own environment files | ||
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#### Goals: | ||
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Debug unexpected problems in existing pipeline | ||
Specify his pipeline’s software requirements so that others can run it | ||
Publish his pipeline on his Github repository for broader research use | ||
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