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- HTML EXECUTABLE 4.2.1 SERIAL INSTALL
- HTML EXECUTABLE 4.2.1 SERIAL SOFTWARE
- HTML EXECUTABLE 4.2.1 SERIAL CODE
HTML EXECUTABLE 4.2.1 SERIAL SOFTWARE
Software Carpentry - 2-day workshop at UC Santa Barbara Software Carpentry: Reproducible Science with RStudio and GitHub - 2-day workshop at Oxford University Software Carpentry - 2-day workshop at the Monterey Bay Aquarium Research Institute (MBARI) Software Carpentry - 2-day workshop at the Woods Hole Oceanographic Institution (WHOI) ĭata integration and team science - 4 day workshop at NCEAS, California, USA ĭata Carpentry - 2-day workshop at the University of California Merced Open Data Science Training - 2 day workshop at the University of Queensland, Australia This book has been used in the following: Practice, Be a champion for open data science Suggested breakdown for a 2-day workshop: time Either way, you should do everything hands-on on your own computer as you learn.īefore you begin, be sure you are all set up: see the prerequisites in Chapter 2. This is going to be fun, because learning these open data science tools and practices is empowering! This training book is written (and always improving) so you can use it as self-paced learning, or it can be used to teach an in-person workshop where the instructor live-codes. Here you will learn a workflow with R, RStudio, Git, and GitHub, as we describe in Lowndes et al. 2017, Nature Ecology & Evolution: Our path to better science in less time using open data science tools.
HTML EXECUTABLE 4.2.1 SERIAL CODE
Open data science means that methods, data, and code are available so that others can access, reuse, and build from it without much fuss. This training book will introduce you to open data science so you can work with data in an open, reproducible, and collaborative way. 9.6 Clone to a new Rproject (Partner 2).9.5 Clone to a new Rproject (Partner 1).9.4 Give your collaborator administration privileges (Partner 1 and 2).9.3 Create a gh-pages branch (Partner 1).8.5 Conditional statements with if and else.8.4.1 Thinking ahead: cleaning up our code.It can be used to a automate setup scripts for duplicating software package installations on different servers. Pexpect can be used for automating interactive applications such as ssh, ftp, passwd, telnet, etc. 7.4 gather() data from wide to long format Pexpect is a Python module for spawning child applications and controlling them automatically.7.3.2 load tidyverse (which has tidyr inside).6.16.1 Error: unexpected SPECIAL in " %>%".6.7 select() subsets data column-wise (variables).6.5 filter() subsets data row-wise (observations).6.3.2 Look at the variables inside a ame.6.2.2 load tidyverse (which has dplyr inside).People organise code into packages based on functionality and dependencies. Packages are particularly suited for programming in the large, that is building big systems by using and re-using code written by different people at different times.
HTML EXECUTABLE 4.2.1 SERIAL INSTALL
5.2 Install our first package: tidyverse The point of packages¶ Packages are a mechanism for organising and distributing code.4.11 Committing - how often? Tracking changes in your files.4.5 Clone your repository using RStudio.3.10.1 I entered a command and nothing’s happening.3.3.2 Logical operators and expressions.
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2.3 Learning with data that are not your own.