lc-workshop
Science Score: 31.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Scientific vocabulary similarity
Low similarity (10.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: tracykteal
- License: other
- Language: Python
- Default Branch: gh-pages
- Size: 384 KB
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Metadata Files
README.md
ecology-workshop
Overview of the ecology workshop
Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This workshop uses a tabular ecology dataset and teaches data cleaning, management, analysis and visualization. There are no pre-requisites, and the materials assume no prior knowledge about the tools.
The workshop uses a single tabular data set that contains observations about adorable small mammals over a long period of time in Arizona. See data.md for more information about this data set, including the download location.
The workshop can be taught using R or Python as the base language.
Overview of the lessons:
- Data organization in spreadsheets and data cleaning with OpenRefine
- Introduction to R or Python
- Data analysis and visualization in R or Python
- SQL for data management
An example of the ecology materials in the wild is this Data Carpentry workshop at CalTech in 2015.
Detailed structure
Day 1 morning: Data organization & cleaning
There are two lessons in this section. The first is a spreadsheet lesson that teaches good data organization, and some data cleaning and quality control checking in a spreadsheet program.
The second lesson uses a spreadsheet-like program called OpenRefine to teach data cleaning and filtering, and to introduce scripting, regular expressions and APIs (application programming interfaces).
Day 1 afternoon and Day 2 morning: Data analysis & visualization
These lessons includes a basic introduction to R or Python syntax, importing CSV data, and subsetting and merging data. It finishes with calculating summary statistics and creating simple plots.
Day 2 afternoon: Data management with SQL
This lesson introduces the concept of a database using SQLite, how to structure data for easy database import, and how to import tabular data into SQLite. Then, it teaches basic queries, combining results and doing queries across multiple tables.
Other lessons
There are a number of other ecology lessons that are not part of the base workshop. Some of these are no longer taught, and some are only taught at extended workshops.
Owner
- Name: Tracy Teal
- Login: tracykteal
- Kind: user
- Repositories: 234
- Profile: https://github.com/tracykteal
Citation (CITATION)
Please cite as: Tracy Teal (eds): "Data Carpentry: Ecology Workshop overview." Version 2017.04.0, April 2017, http://www.datacarpentry.org/ecology-workshop/, FIXME: Add Zenodo DOI.
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