| layout | root | venue | address | country | humandate | contributors | contact | raw | ||||||
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lesson |
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United-States |
April 23-24, 2015 |
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raw.github.com/datacarpentry/2015-04-23-stanford/gh-pages |
#Data Carpentry Python for Ecologists
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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. The lessons below were designed for those interested in working with ecological data in Python.
- Short Introduction to Python
- Starting With Data
- Index Slice Subset
- Data Types and Format
- Merging Data
- Data Analysis Automation: Loops and Functions
- Plotting with Matplotlib
- Putting It All Together
- Accessing SQL using Python
Data for this lesson is from the Portal Project Teaching Database - available on FigShare.
The data files used in this lesson are surveys.csv download link - https://ndownloader.figshare.com/files/2292172 and species.csv download link - https://ndownloader.figshare.com/files/3299483.
Requirements: Data Carpentry's teaching is hands-on, so participants are encouraged to bring in and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop. (We will provide instructions on setting up the required software several days in advance, and the classroom will have computers with the software installed). There are no pre-requisites, and we will assume no prior knowledge about the tools. Participants are required to abide by Software Carpentry's Code of Conduct.
Twitter: #datacarpentry
@datacarpentryData Carpentry is supported by the Gordon and Betty Moore Foundation and a partnership of several NSF-funded BIO Centers (NESCent, iPlant, iDigBio, BEACON and SESYNC) and Software Carpentry, and is sponsored by the Data Observation Network for Earth (DataONE). The structure and objectives of the curriculum as well as the teaching style are informed by Software Carpentry.