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r_hadleyverse [2016/11/02 21:19] xaviergb [1.6 Adding geometric objects] |
r_hadleyverse [2016/11/02 22:46] (current) xaviergb [Workshop 3: Intro to ggplot2, tidyr & dplyr] |
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| Link to associated Prezi: [[http://prezi.com/daz9r0cj1si4/|Prezi]] | Link to associated Prezi: [[http://prezi.com/daz9r0cj1si4/|Prezi]] | ||
| - | Download the R script for this lesson: [[http://qcbs.ca/wiki/_media/ggplot.r|Script]] | + | Download the R script for this lesson: {{:workshop3.r|Script}} |
| ===== 1. Plotting in R using the Grammar of Graphics (ggplot2) ===== | ===== 1. Plotting in R using the Grammar of Graphics (ggplot2) ===== | ||
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| ===== ggplot2 - Challenge #1 ===== | ===== ggplot2 - Challenge #1 ===== | ||
| - | Using the ''qplot()'' function, build a basic scatter plot with a title and axis labels from one of the ''CO2'' or ''BOD'' data sets in R. You can load these and explore their contents as follows: | + | //Using the ''qplot()'' function, build a basic scatter plot with a title and axis labels from one of the ''CO2'' or ''BOD'' data sets in R. You can load these and explore their contents as follows:// |
| <code rsplus | > | <code rsplus | > | ||
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| geom_emoji(emoji="1f337") | geom_emoji(emoji="1f337") | ||
| </code> | </code> | ||
| - | {{rplotbear.png?400 |}} | + | |
| - | + | {{:rplotbear.png?400|}} | |
| + | |||
| ---- | ---- | ||
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| ===== ggplot2 - Challenge # 2 ===== | ===== ggplot2 - Challenge # 2 ===== | ||
| - | Produce a colourful plot with linear regression from built in data such as the ''CO2'' dataset or the ''msleep'' dataset: | + | //Produce a colourful plot with linear regression from built in data such as the ''CO2'' dataset or the ''msleep'' dataset:// |
| <code rsplus | > | <code rsplus | > | ||
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| ===== ggplot2 - Challenge # 3 ===== | ===== ggplot2 - Challenge # 3 ===== | ||
| - | Explore a new geom and other plot elements with your own data or built in data. Look [[http://docs.ggplot2.org/current/index.html|here]] for some inspiration and examples! | + | //Explore a new geom and other plot elements with your own data or built in data. Look [[http://docs.ggplot2.org/current/index.html|here]] or [[http://shinyapps.stat.ubc.ca/r-graph-catalog/|here]] for some inspiration and great examples!// |
| <code rsplus | > | <code rsplus | > | ||
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| ---- | ---- | ||
| ===== tidyr CHALLENGE ==== | ===== tidyr CHALLENGE ==== | ||
| - | //Gather and spread the airquality to return the same format as the original data using month and day// | + | //Gather and spread the airquality to return the same format as the original data using month and day.// |
| ++++Solution| | ++++Solution| | ||
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| **Change data from wide to long format** | **Change data from wide to long format** | ||
| - | //(See back to Section 6.3)// | + | //(See back to Section 2.3)// |
| <code rsplus | > | <code rsplus | > | ||
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| ---- | ---- | ||
| - | **CHALLENGE:** | + | |
| + | ===== dplyr CHALLENGE ===== | ||
| //Using the ''ChickWeight'' dataset, create a summary table which displays the weight gain of individual chicks in the study. Employ ''dplyr'' verbs and the ''%>%'' operator.// | //Using the ''ChickWeight'' dataset, create a summary table which displays the weight gain of individual chicks in the study. Employ ''dplyr'' verbs and the ''%>%'' operator.// | ||
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| ---- | ---- | ||
| - | Note that we can group the data frame using more than one factor, using the general syntax as follows: ''group_by(group1, group2, ...)''. This approach allows us to carry out operations on ''group2'' while conserving information on ''group1'' within the summary table. ** HINT HINT ** | + | ==== Ninja Hint ==== |
| + | |||
| + | Note that we can group the data frame using more than one factor, using the general syntax as follows: ''group_by(group1, group2, ...)''. This approach allows us to carry out operations on ''group2'' while conserving information on ''group1'' within the summary table. | ||
| ---- | ---- | ||
| - | **dplyr NINJA CHALLENGE:** | + | |
| + | ===== dplyr NINJA CHALLENGE ===== | ||
| //Using the ''ChickWeight'' dataset, create a summary table which displays the average weight gain of individual chicks for each diet in the study. Employ ''dplyr'' verbs and the ''%>%'' operator.// | //Using the ''ChickWeight'' dataset, create a summary table which displays the average weight gain of individual chicks for each diet in the study. Employ ''dplyr'' verbs and the ''%>%'' operator.// | ||
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| ===== 4. Resources ===== | ===== 4. Resources ===== | ||
| - | Here are some great resources for learning tidyr and dplyr that we used when compiling this workshop: | + | Here are some great resources for learning ggplot2, tidyr and dplyr that we used when compiling this workshop: |
| - | //Reshape / Reshape2// | + | //ggplot2// |
| - | * [[http://seananderson.ca/2013/10/19/reshape.html]] | + | * [[http://shinyapps.stat.ubc.ca/r-graph-catalog/|The R Graph Catalog]] |
| - | * [[http://had.co.nz/reshape/introduction.pdf]] | + | * [[https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf|The RStudio ggplot2 Cheat Sheet]] |
| - | * [[http://cran.r-project.org/web/packages/reshape2/reshape2.pdf]] | + | |
| Lecture notes from Hadley's course Stat 405 (the other lessons are awesome too!) | Lecture notes from Hadley's course Stat 405 (the other lessons are awesome too!) | ||
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| * [[http://stat405.had.co.nz/lectures/19-tables.pdf]] | * [[http://stat405.had.co.nz/lectures/19-tables.pdf]] | ||
| - | //dplyr// | + | //dplyr and tidyr// |
| - | * [[https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html]] | + | * [[https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf|The RStudio Data Wrangling Cheat Sheet]] |
| - | * [[http://seananderson.ca/2014/09/13/dplyr-intro.html]] | + | * [[https://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html|CRAN Intro to dplyr]] |
| + | * [[http://seananderson.ca/2014/09/13/dplyr-intro.html|Sean Anderson's Intro to dplyr and pipes]] | ||
| + | * [[https://rpubs.com/bradleyboehmke/data_wrangling|Bradley Boehmke's Intro to data wrangling]] | ||
