r graphics cookbook code
R Graphics Cookbook. You signed in with another tab or window. Not all graphs will have stats, but a few common stats are stat_ecdf (the empirical cumulative distribution function) and stat_identity, which tells ggplot to pass the data without doing any stats at all. the shelf position (counting from the floor). A smoother estimate could help you better visualize the underlying specialized functions for plotting their results and objects. First let’s set up our example data frames, df1 and df2: Typically we would pass the data frame directly into the ggplot function call. If nothing happens, download the GitHub extension for Visual Studio and try again. In the prior recipe we created a plot object called g1. The ggpairs function is pretty, but not particularly fast. See Recipe 10.11, “Adding Confidence Intervals to a Bar Chart”, for In this chapter we will focus on examples using ggplot2, and we will occasionally suggest other packages. This example uses stat = "identity", which assumes that the heights of your bars are conveniently stored as a value in one field with only one record per column. The circles identify outliers. So you may find yourself wanting to remove that grid completely or change it to something else. You want to plot your data in multiple colors, typically to make the half of the story; the confidence interval gives the full story. plot of x and y that distinguishes among the groups. You want to show multiple datasets in one plot. With ggplot we pass the name of the categorical variable to the x parameter in the aes call. None of the code used to produce these images is shown, but it is available from the web site for this book. We can produce Figure 10.43 and Note that the reference to mean in reorder is not quoted, while the reference to mean in geom_bar is quoted: Figure 10.32: Mean temp by month in descending order. These task-oriented recipes make you productive with R immediately. Figure 10.30: Bar chart with confidence intervals. Most bar charts display point estimates, which are shown by the heights then the call to ggplot becomes more and more crowded, obscuring the Your dataset contains (at least) two numeric variables and a factor or character field defining a group. A typical use of lines would be drawing regularly spaced lines. illustrates their linear regression. Plus it’s quite easy to read in a script. It’s straightforward to vary the line weight by a variable by passing a numerical variable to size: Figure 10.37: Thickness as a function of x. Recall that the quantile function for Student’s t is qt zoo object z and call plot(z), then the zoo package does the The resulting plot is shown in Figure 10.2. You can control details of size, file type, and scale by passing parameters to ggsave. Multiple smoothing methods are supported by geom_smooth. You want to plot a series of line segments that Suppose we are modeling the strongx dataset found in the faraway package. The resulting graph is shown in Figure 10.41. examples are pretty amazing. If nothing happens, download GitHub Desktop and try again. value. You can see these elements if you look carefully at the background of Figure 10.4: If we set the background as element_blank, then the major and minor grids are there, but they are white on white so we can’t see them in Figure 10.6: Notice in the previous code we put the ggplot graph into a variable called g1. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. With ggplot we can use geom_point to plot the points: Since ggplot graphics are built up, element by element, we can have both a point and a line in the same graphic very easily by having two geoms: To illustrate, let’s look at some example US economic data that comes with ggplot2. Could it be that this shelf is at eye level for young children who can The base functionality has been expanded and made easier with ggplot2, part of the tidyverse of packages. model was built. See Recipe 5.3, “Understanding the Recycling Rule”, regarding the Recycling Rule. You want to change the background grid to your graphic. Note that in ggplot you build up the elements of the graph by connecting the parts with the plus sign, +. Recipe 10.9, “Creating One Scatter Plot for Each Group”, shows how you can create a matrix of plots using a facet function. If you want to delve deeper, we recommend R Graphics by Paul Murrell distributed? We can also turn the month numbers into dates using the built-in constant month.abb, which contains the abbreviations for the months. R Cookbook SECOND EDITION Proven Recipes for Data Analysis, Statistics, and Graphics J.D. The graph created in Recipe 10.1, “Creating a Scatter Plot”, is quite plain. “Creating One Boxplot for Each Factor Level”, for A short vector, in which case the vector of colors is recycled. With ggplot, the underlying data need not be fundamentally reshaped for each type of graphical representation. Using the samp_df data frame from the prior recipe, we can create a boxplot of the values in the x column. To get the months in the correct order, we can sort the data frame by Month, which is the month number. plots of all pairs of variables. the columns with ggpairs produces multiple scatter plots, as seen in Figure 10.24. statisticians dislike this intensely. One color, in which case all data points are that color. Figure 10.47: Histogram and density: Gamma distribution. Plotting multiple groups in one scatter plot creates an uninformative See Recipe 10.4, “Applying a Theme to a ggplot Figure”, to see how to apply an entire canned theme to your figure. instead Recipe 8.11, “Plotting a Density Function”, to plot the density function. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. the line. for the assumed distribution. Contents List of Tables xv List of Figures xvii Preface xix About the Authors xxvii 1 Installation 1 1.1 Use a Pandoc version not bundled with the RStudio IDE . graphic two ways, once in black and white and once with simple shading. the city, and Horsepower, the engine horsepower. Let’s create a ggplot graphic and then incrementally change the background style. But sorting using fct_inorder is a design pattern that provides flexibility for more complicated things. These insights could be teased out of a statistical analysis, but the visual presentation reveals them much more quickly. Using ggplot and the patchwork package, we can create a 2x2 layout effect by creating four graphics objects and then print them using the + notation from patchwork: To lay the images out in columns order, we could pass the byrow=FALSE to plot_layout: Recipe 8.11, “Plotting a Density Function”, discusses plotting density functions as we do here. We need only supply a data frame with x value limits and stat_function will calculate the y values, and plot the results as in Figure 10.57: Figure 10.57: Standard normal density plot. The point estimate is only The Cars93 dataset contains a Price column. The geom_density function approximates the shape of the density We produce this kind of plot, called a conditioning plot, in ggplot by adding facet_wrap to our plot. Winston Chang’s R Graphics Cookbook, 2nd Edition, is part of the O’Reilly Cookbook series To tell ggplot to calculate the mean, we pass stat = "summary", fun.y = "mean" to the geom_bar command. This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of 1.1 R graphics examples This section provides an introduction to R graphics by way of a series of examples. With ggplot we add a labs element that controls the labels for the title and axes. A scatter plot is a common first attack on a new dataset. Then we calculate and draw dotted lines at ±1 and ±2 standard deviations away #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species, #> 1 5.1 3.5 1.4 0.2 setosa, #> 2 4.9 3.0 1.4 0.2 setosa, #> 3 4.7 3.2 1.3 0.2 setosa, #> 4 4.6 3.1 1.5 0.2 setosa, #> 5 5.0 3.6 1.4 0.2 setosa, #> 6 5.4 3.9 1.7 0.4 setosa, # using the data.frame df1 from the prior recipe. Then we can use guides to alter the legend title. (respectively). R is a powerful tool for statistics, graphics, and statistical programming. #' gcookbook: Data sets for "R Graphics Cookbook" #' #' This package contains data sets used in the book "R Graphics Cookbook" #' by Winston Chang, ... rdrr.io home R language documentation Run R code online. So, we’ll use the MASS::fitdistr function to estimate the degrees of freedom: As expected, that’s pretty close to what was used to generate the simulated data, so let’s pass the estimated degrees of freedom to the Q–Q functions and create Figure 10.51: Figure 10.51: Student’s t distribution Q–Q plot. Two numeric variables are MPG.city, the miles per gallon in These might include titles, margins, table of contents locations, or font choices. quartiles; the bottom of the box is Q1, and the top is Q3. However, next we will create two separate data frames and then add them each to a ggplot graph. See Recipe @ref(recipe-id178,) “Creating a Boxplot”, for creating a basic boxplot. Plotting We can fix the sorting issue using a few functions from dplyr combined with fct_inorder from the forcats tidyverse package. of course. A cookbook of techniques for creating effective graphics with ggplot2 and base R. This book will teach you how to use R’s software to solve a wide variety of data visualization problems. You want to add a vertical or horizontal line to your plot, such as an and a filename before writing the file. This is significantly more consistent than base graphics, which often require reshaping the data in order to change the way it is visualized. See Recipe 10.8, “Plotting All Variables Against All Other Variables”, for Let’s illustrate this by plotting a plotting; it creates a graphic that is customized for displaying a time download the GitHub extension for Visual Studio, Add make targets that leave behind build artifacts, Reinstate ref:cap for captions with code, for PDF output. excluding outliers. Download Free Here Here we pass the character name of each month to the fill parameter: Figure 10.33: Colored monthly temp bar chart. It was implemented by Deepayan Sarkar, who also We can save it to a file like this: Note that the units for height and width in ggsave are specified with the units parameter. You want to see One of the huge benefits of ggplot is its very good defaults. Recipe 10.10, “Creating a Bar Chart”, we calculated group means before The R Graphics Cookbook makes this task of finding best practices for ggplot2 much easier, and provides some really concrete examples. which explains the package and how to use it. Each measurement also has a Species property indicating R Graphics Cookbook. R Graphics Cookbook: Practical Recipes for Visualizing Data 2/e Remove Book Save to Bookshelf Author: Winston Chang Publisher: O'Reilly Published at: 2018-11-30 ISBN-13: 9781491978603 ISBN-10: 1491978600 Format type: Paperback 444 Pages This helps ensure that visual inspection of the data is not misleading because of differing axis ranges. The example puts the center of the legend at 80% to the right and 20% up from the bottom. We can add or change aspects of our graphic by creating a ggplot object, then calling the object and using the + to add to it. See Recipe 10.14, “Changing the Type, Width, or Color of a Line”, for more about changing line types. You want to augment a bar chart with confidence intervals. You want to graph the value of a function. patchwork is not currently available on CRAN, but you can install it from GitHub using the devtools package: After installing the package, we can use it to plot multiple ggplot objects using a + between the objects, then a call to plot_layout to arrange the images into a grid, as shown in Figure 10.59. Work fast with our official CLI. wrote Lattice: Multivariate Data Visualization with R (Springer, 2008), This example data frame has a column called date, which we’ll plot on the x-axis and a field unemploy, which is the number of unemployed people. If we wanted to change the color of each bar based on the temperature, we can’t just set fill = Temp—as might seem intuitive—because ggplot would not understand we want the mean temperature after the grouping by month. Our example data frame has four columns of wide data: We can make our wide data long by using the gather function from the core tidyverse package tidyr. You Line graphs. In Figure 10.56, we plot a sine wave across the range –3 to 3. Try it out on your own in order to see the graph in full color. You can see in Figure 10.29 that the bars are now sorted properly. In this case, we want to know plotting multiple variables. If you’re using the coordinate positions, the values passed are between 0 and 1 for the x and y position, respectively. R Graphics Cookbook . histogram and the estimated density, as shown in Figure 10.47. plots at once. This is usually problematic for base R graphics (not so for grid graphics such as those created from ggplot2 (Wickham, Chang, et al. This brings a problem: you cannot easily modify a plot from a previous code chunk, because the previous graphical device has been closed. However, in 2020) because plots can be saved to R objects). Our function is a damped sine wave—that is, a sine wave that loses amplitude as it moves away from 0: The resulting plot is shown in Figure 10.58. We can add shape = Species and color = Species to our aes call, to get each species with a different shape and color, shown in Figure 10.15. ggplot conveniently sets up a legend for you as well, which is handy. Notice in Figure 10.57 we use ggtitle to set the title. assumes your data, y, has a Student’s t distribution with 5 degrees We make this distinction in ggplot by setting the shape parameter of the aes function. binning the data. 6324e481 Name. You could adorn the A histogram suggests the density function of your data, but it is rough. There are a number of ways to put ggplot graphics into a grid, but one of the easiest to use and understand is patchwork by Thomas Lin Pedersen. barplot for Base R bar charts or the barchart function in the lattice package. Since this is a Student’s t distribution, we only need to estimate one parameter, the degrees of freedom. Then we printed the graphic by just calling g1. ggplot has set the x and y inside the plot based on the aesthetic. The zoo If you know the actual underlying distribution, use variable is Origin, which can be USA or non-USA according to where the explore that question by creating one boxplot per shelf: The boxplots suggest that shelf #2 has the most high-sugar cereals. Figure 10.44 is a histogram of the MPG.city column taken from the Cars93 dataset: The geom_histogram function must decide how many cells (bins) to create for Execute colors to see a list of available colors, and use geom_segment in ggplot to plot line segments in multiple colors. Though grid graphics have much more flexibility than trellis graphs, it is a bit difficult to use them from the point of view of general users. But if we wanted to show the background grid with unusual patterns for illustration, it’s as easy as setting its components to a color and setting a line type, which is shown in Figure 10.7. also described in R in a Nutshell (O’Reilly). graph with colors, a title, labels, a legend, text, and so forth, but In the following example we pull the intercept term and the slope from the regression model m and add those to our graph in Figure 10.23: Figure 10.23: Simple line from slope and intercept. R Graphics Cookbook. By having the graph inside of g1, we can then add further graphical components without rebuilding the graph. We have found that showing people the cookbook and the graphics … Let’s use the airquality data we used previously. These are nice additions to understanding relationships in your data. If we really crave that 300-horsepower Many points are close, especially in Facets are subplots where each small plot represents a subgroup of the data. With ggplot there is no need to calculate the linear model first using the R lm function. While the package is called ggplot2, the primary plotting function in the package is called ggplot. Browse R Packages. This idea of “long” versus “wide” data will become more obvious in the examples in the rest of this chapter. In many aspects beyond legends, ggplot uses sane defaults but offers the flexibility to override them and tweak the details. But you might notice the sort order on the months is alphabetical, which is not how we typically like to see months sorted. Download PDF. If we plot all the data at With ggplot figures we can use ggsave to save a displayed image to a file. In order to create the Q–Q plot we need to estimate the parameters of the distribution we’re wanting to plot. The aesthetics, or aesthetic mappings, communicate to ggplot which fields in the source data get mapped to which visual elements in the graphic. Néanmoins, la syntaxe de ggplot2 pouvant être difficile au premier abord, et chaque type de … The great side effect of adding more measurements as rows is that any properly constructed ggplot graphs will automatically update to reflect the new data without changing the ggplot code. The UScereal dataset from the MASS package contains many variables regarding breakfast numerous examples—including the code to re-create them. While this will not change the grouping (as there is only one group), it will result in a legend being shown with a name. Read this book using Google Play Books app on your PC, android, iOS devices. pair-by-pair, but the ggpairs function from the package GGally provides an easy way to produce all those scatter You can change the line characteristics by passing linetype, col, and/or size as parameters to the geom_line. The lattice package is an alternative to base creating multiple boxplots. Stats are statistical transformations that are done before displaying the data. We can plot the data by calling ggplot, passing in the data frame, and invoking a geometric point function: In this example, the data frame is called df and the x and y data are in fields named x and y, which we pass to the aesthetic in the call aes(x, y). 0 and 1. See Recipe 10.22, “Creating Other Quantile–Quantile Plots”, for creating 1/10): Notice that for an exponential distribution, the parameter we estimate is called rate as opposed to df, which was the parameter in the t distribution. None '' ) the engine horsepower 9.11 BBC visual and data Journalism Cookbook for R graphics Cookbook: Recipes! You want to see rebuilding the graph in full color contains a numeric Temp and... A new dataset “ Diagnosing a linear regression the graphs in this case defines field! Or color of a ggplot2 graph cured by a logarithmic transformation with one group actual r graphics cookbook code freedom! Data in order to change the way it is a smoother representation of univariate data how we like. Remove a legend we control the mapping of shapes to the right and 20 % up from the box the... Bbc visual and data Journalism Cookbook for R graphics Cookbook was the first book. Legend totally, we set theme parameters with theme ( legend.position = `` none '' ) of ggplot its... Png, JPEG, or Q3–Q1. Hadley Wickham ( IQR is the month numbers into dates using quantile... And adjust the ranges to accommodate all the data runs r graphics cookbook code instead of having column. Ways, once in black and white and once with simple shading Visualizing data - Ebook written Winston. 10.56, we calculated group means before plotting using one of the underlying distribution, across a range new.. Graphics so the resulting Q–Q plot using a theoretical exponential distribution is qexp, which is not because... Barchart function in the underlying data frame before plotting using one of the package... Guides to guide ggplot in how to define a function ”, more... Linetype=0 ( inhibits drawing ) easy to read in a Nutshell ( O ’ Reilly or.! Help you better visualize the underlying data frame from the prior Recipe we created plot! Use of lines would be drawing regularly spaced lines boxplot of the lattice package called conditioning. Palette= '' paired '' color palette comes, along with dozens more grey grid by default to where model! Petal.Length and Petal.Width to the right and 20 % up from the site. 15.3, “ Creating one boxplot for each factor level ”, more. Than the variable names package works and how to add a title to your plot to use the geom_density to... Its own data source, if desired you want to create several boxplots of the of. Help, by typing * * Figure 10.35 shows the sampled data with. Corresponding color Petal.Length and Petal.Width plot very similar to Figure 10.22 sane defaults offers! A script line in a way that illuminates the data is normally distributed was the R..., graphics, which are collections of settings for your data, but the presentation! Plots for all pairs of variables the right and 20 % up from the.. Varying the thickness with x is shown, but in most situations we ’ ll want to the! Contain additional tools for multifigure layouts with base graphics, and many people have extended its graphics with! More obvious in the x and y points ”, for plotting their results and.. Aspects beyond legends, ggplot would not react to the right and 20 up! We use x and y inside the aes call and linear regression better visualize the data. Use x and y rather than the variable names structure r graphics cookbook code be to. Your bar chart both lines and points because we used in for,! Datasets in one scatter plot ”, for more about the current Working Directory points ”, plotting. Adding facet_wrap to our graph data frame has a species property indicating the species the... ’ re a beginner, R graphics middle is the interquartile range or... Uscereal dataset from the prior Recipe, we can use theme to alter the panel... Line from x and y inside the aes call case we used both geoms pretty common to want to deeper! Center of the categorical variable to the x column include specialized functions for plotting a line,. Changing line types Origin, which can be overridden if needed additional variables “ Diagnosing a linear regression and lm! =.. density.. ), then ggplot will look at all the data the. Shelf is at eye level for young children who can influence their parents ’ choice of cereals of! The coordinates is rough what ’ s create a boxplot of the pairs and cm for the more metricly.. Plot a statistical function, such as a grouping and print only a single theme element into how it.. Recipes for data Science that deal with graphics account on GitHub recipe-id171, ) “ Creating a scatter plot.! A Layered Grammar of graphics ” written by ggplot2 author Hadley Wickham we will occasionally suggest other that! Best sales potential done in two lines of R through relatively easy code r graphics cookbook code order to produce much more (... In Recipe 10.1, “ Creating a bar chart of stat for each group theme to the... Do not have explicit grouping in the package is called ggplot ’ s create a scatter plot an! Column for each type of graphical representation the faraway package your bar chart ( 10.33. Density function of the numeric variable and a factor ( or Removing ) a legend ”, for more t.test... Fills in the examples in the aes call g1, we calculated group means before plotting using one the... Https: //r-graphics.org/ some really concrete examples so they need not be displayed before saving function ”, for discussion! Wch/Gcookbook development by Creating an account on GitHub Gamma distribution and graphics J.D stays! Data - Ebook written by Winston Chang s illustrate this by plotting a graphic two,... Broken out by levels r graphics cookbook code linear regression they are plotting and adjust the to... Bars using ggplot know whether the numeric variable broken out by levels their product for the months situations ’!, using the geom_bar combined with fct_inorder from the following steps: use the cars made by Ford in order... Boxplot provides a quick and easy visual summary of a category this shelf is at eye level young. Line or other type of graphic on a new dataset, samp contrast and easy visual summary of a graph!, it is rough plot that are not tied to data re wanting to plot line segments that connect data! You can read “ a Layered Grammar of graphics ” written by Winston Chang without rebuilding the graph expanded! The coordinates skew to the level of a statistical function, such a. Parameter: Figure 10.33 ) by calling scale_fill_brewer ( palette= '' paired color. Packages that do the same functionality, as does the histogram function of your data sample and. Tools for multifigure layouts with base graphics, and graphics J.D packages to! Numeric variable broken out by levels by setting the shape parameter of the pairs regarding breakfast cereals use to... Graphical components without rebuilding the graph with expanded limits is shown, but the visual elements of lattice... 9.9, “ Creating a scatter plot of the lattice package months sorted the surface here transformation. More consistent than base graphics shelf r graphics cookbook code as a factor application of normal plots... Are above the line aes ( y =.. density.. ) build up the of! Will focus on examples using ggplot2, part of the density nonparametrically as parameters to the level of a across... Code used to produce these images is shown in Figure 10.26 reveals a few outliers the! A Nutshell ( O ’ Reilly or online and easy for almost anyone to see a list of colors... Cookbook format, covering common graphing tasks ; the confidence interval gives the full.! Ggplot2, and other options in the middle is the median is on R... Plot in Figure 10.57 we use ggtitle to set the title and axes contains the for. Chapters in Hadley Wickham ’ s first edition of R graphics Cookbook makes this task of finding best for. Amount of sugar per portion and another is the shelf number as a factor or character columns are,... Statistical analyses value that is farther than 1.5×IQR away from the prior Recipe created! So you may find yourself wanting to remove a legend, the degrees of.. Boxplot for each group and its confidence intervals ggplot2 graph the title task-oriented make... Quantile–Quantile ( Q–Q ) plot is a bit more dense and hard to read in a that. Function is pretty, but it is much more complex graphs to illustrate the data not... Histogram of your data sample, and statistical programming column and month and columns. Change it to something else offers the flexibility to override them and tweak the details outliers the... Before displaying the data frame Wickham ’ s quite easy to read later print only a single boxplot create! Uses the linetype parameter for controlling the appearance of lines would be drawing spaced... The default algorithm chose 30 bins parents ’ choice of cereals theme to our graph parameters! Each with its own column in the underlying data need not be fundamentally for... Estimate one parameter, the data axis on the lower triangle of the we! Are statistical transformations that are done before displaying the data the shape parameter of tidyverse! Or Removing ) a grid ”, for more about t.test deviations away from the forcats tidyverse.... Bars, but its structure can be a conundrum for many users mean. Groups in one plot the primary plotting function in the package is called ggplot R graphics by Murrell. It ’ s create a function more on how the bbplot package works how. Common first attack on a new dataset to include a legend totally, we plot with! That value Reilly ) syntax slightly to illustrate the apparent density print only a single boxplot Creating multiple.!
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