index.html

---
layout: bootcamp
root: .
venue: Stanford
address: Branner Earth Sciences Library, Teaching Corner, Mitchell Earth Sciences Building 2nd Floor
country: United-States
humandate: April 23-24, 2015
humantime: 8:30 am - 4:30 pm
startdate: 2015-04-23
enddate: 2015-04-24
latlng: 
registration: open
instructor: ["Amy Hodge", "Tracy Teal"]
assistant: []
contact: amyhodge@stanford.edu
raw: raw.github.com/datacarpentry/2015-04-23-stanford/gh-pages
eventbrite: 16087912379
---
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<h2>General Information</h2>
<p>
</p>

<p>
Data Carpentry workshops are for any researcher who has data they want to analyze, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data. We will cover data organization in spreadsheets, data cleaning, the command line, and R for data analysis and visualization using examples from biology. Participants should bring their laptops and plan to participate actively. By the end of the workshop learners should be able to more effectively manage and analyze data and be able to apply the tools and approaches directly to their ongoing research. 
<p>
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.
</p>
<p>
Preliminary schedule:
<ul>
<li>  Day 1 morning: Data organization in spreadsheets and data cleaning with OpenRefine
<li>  Day 1 afternoon: Introduction to databases, combining and querying data using SQL
<li>  Day 2 morning: Introduction to R
<li>  Day 2 afternoon: Data analysis and visualization in R
</ul>


</p>

<p>Updates will be posted to this website as they become available.</p>

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<p>Data files for the workshop are available at <a href = "/2015-01-15-cornell/data/biology/">the following link</a></p>

<p>The etherpad for this workshop can be found <a href = "https://etherpad.mozilla.org/7XixtJSZJq">here</a></p>

<p>A static copy of the etherpad as of 5:30 on Friday after the workshop ended is <a href ="etherpad-snapshot-530-Friday.html">here</a></p>
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<p>
  <strong>Who:</strong>
  The course is aimed at faculty, research staff, postdocs, graduate students, advanced undergraduates, and other researchers in any field. No prior computational experience is required. 
</p>

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<p>

<p>
  <strong>Requirements:</strong>
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). <em> There are no pre-requisites, and we will assume no prior knowledge about the tools.</em> Participants are required to abide by Software Carpentry's
<a href="http://software-carpentry.org/conduct.html">Code of Conduct</a>.
</p>

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  <strong>Contact</strong>:
  Please email
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  for questions and information not covered here.
</p>

<p><strong>Twitter</strong>: #datacarpentry</p> @datacarpentry


<h2>Acknowledgements &amp; Support</h2>
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<p>
Data Carpentry is supported by the <a href=http://http://www.moore.org/>Gordon and Betty Moore Foundation</a> and a partnership of several NSF-funded <a href="http://www.nsf.gov/dir/index.jsp?org=BIO" target="_blank">BIO</a> Centers (<a href="http://nescent.org" target="_blank">NESCent</a>, <a href="http://iplantcollaborative.org" target="_blank">iPlant</a>, <a href="http://idigbio.org" target="_blank">iDigBio</a>, <a href="http://beacon-center.org/" target="_blank">BEACON</a> and <a href="http://sesync.org" target="_blank">SESYNC</a>) and <a href="http://software-carpentry.org" target="_blank">Software Carpentry</a>, and is sponsored by the <a href="http://dataone.org" target="_blank">Data Observation Network for Earth</a> (DataONE). The structure and objectives of the curriculum as well as the teaching style are informed by <a href="http://software-carpentry.org" target="_blank">Software Carpentry</a>.
</p>

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<h2>Registration</h2>
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<h2>Schedule</h2>
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<table class="table table-striped">
  <tr> <td>Thursday</td>  <td>09:00</td>  <td><a href = "lessons/excel/ecology-examples/00-intro.html">Better Use of Spreadsheets</a></td> </tr>
  <tr> <td></td>        <td></td>       <td>Refreshments will be served around 10:30.</td> </tr>
  <tr> <td></td>        <td>12:00</td>  <td>Lunch break (on your own)</td> </tr>
  <tr> <td></td>        <td>13:00</td>  <td>Cleaning and managing data with <a href="lessons/OpenRefine/open-refine-demo.html">OpenRefine</a>, <a href="lessons/sql/sql.html">Introduction to relational databases with SQLite</a> </td> </tr>
  <tr> <td></td>        <td></td>       <td>Refreshments will be served around 14:30.</td> </tr>
  <tr> <td></td>        <td>16:00</td>  <td>Wrap-up</td> </tr>
  <tr> <td>Friday</td> <td>09:00</td>  <td> <a href="lessons/R/index.html"> Working with data in R </a></td> </tr>
  <tr> <td></td>        <td></td>       <td>Refreshments will be served around 10:30.</td> </tr>
  <tr> <td></td>        <td>12:00</td>  <td>Lunch break (on your own)</td> </tr>
  <tr> <td></td>        <td>13:00</td>  <td> <a href = "lessons/shell/index.html">Workflows and automating repetitive tasks with command line shell </a>  </td> </tr>
  <tr> <td></td>        <td></td>       <td>Refreshments will be served around 14:30.</td> </tr>
  <tr> <td></td>        <td>16:00</td>  <td>Wrap-up</td> </tr>
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<h2>Additional Resources</h2>

<h3>shell</h3>
<ul>
<li><a href=http://fosswire.com/post/2007/08/unixlinux-command-cheat-sheet/>Unix/Linux Command Reference</a>
<li><a href=https://github.com/swcarpentry/boot-camps/blob/master/shell/shell_cheatsheet.md
>Shell cheat sheet</a>
<li><a href=http://software-carpentry.org/v4/shell/index.html>Software Carpentry shell lessons</a>
</ul>

<h3>R</h3>

<b>Where to learn more about R</b>
<ul>
<li><a href=http://www.statmethods.net/>http://www.statmethods.net/</a> - good for data organization, basics stats and graphs
<li><a href=http://www.gardenersown.co.uk/Education/Lectures/R/anova.htm>http://www.gardenersown.co.uk/Education/Lectures/R/anova.htm</a> - basic parametric and non-parametric stats
<li><a href=http://www.cyclismo.org/tutorial/R/index.html>http://www.cyclismo.org/tutorial/R/index.html</a> - R tutorial
<li><a href=http://www.amazon.com/R-Action-Robert-Kabacoff/dp/1935182390>R in Action</a> - good book as an R reference
<li><a href=http://www.twotorials.com/>http://www.twotorials.com/</a>
<li><a href=http://www.r-bloggers.com/>http://www.r-bloggers.com/</a>
<li><a href=http://tryr.codeschool.com/>http://tryr.codeschool.com/</a>
<li><a href=http://adv-r.had.co.nz/>Advanced R Programming by Hadley Wickham</a>
<li><a href=http://www.computerworld.com/s/article/9239625/Beginner_s_guide_to_R_Introduction>Beginner's Guide to R from Computer World</a>
<li><a href=http://www.scoop.it/t/r-for-journalists>R for Journalists</a>
<li><a href=http://www.r-bloggers.com/>R Bloggers</a>
<li><a href=http://www.inside-r.org/>inside-R</a> 
<li><a href=http://ropensci.org/>rOpenSci</a>
</ul>

<p>
<b>Plotting in R</b>
<ul>
<li><a href=http://www.harding.edu/fmccown/r/>http://www.harding.edu/fmccown/r/</a> - Very simple graphs
<li><a href=https://storify.com/tracykteal/r-galleries>A variety of R gallery recommendations</a>
<li><a href=http://docs.ggplot2.org/>ggplot gallery</a> - extensive and comprehensive; a great resource
<li><a href=http://www.amazon.com/R-Graphics-Cookbook-Winston-Chang-ebook/dp/B00AJ5X7W4/>R Graphics Cookbook</a> - highly recommended
<li><a href=http://www.cookbook-r.com/Graphs/>Some of R Graphics Cookbook plots</a> - a set of some of the plots from the R Graphics Cookbook by Winston Chang
<li><a href=http://rgm3.lab.nig.ac.jp/RGM/R_image_list?page=665&init=true>R Graphical Manual</a> - plots from apparently every R CRAN package
</ul>
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