class: center, middle, inverse, title-slide # Plotting in .mono[R] ## EC 425/525, Lab 5 ### Edward Rubin ### 10 May 2019 --- class: inverse, middle # Prologue --- name: schedule # Schedule ## Last time Regession ## Today Plotting in .mono[R] (especially `ggplot2`) --- layout: true # Plotting --- name: plotting class: inverse, middle --- name: plot ## The default option: `plot()` While we'll quickly move on to other options, .mono[R]'s `plot()` function (in the default `graphics` package) is a great tool for basic data exploration—it's fast, simple, and flexible. -- In fact, `plot()` is a generic function, that works for many classes. -- .hi-slate[General arguments] for `plot()`: - `x` and `y` for coordinates - `type =` {`"p"`oints, `"l"`ines, *etc.*} .it[.grey-light[(optional)]] - `xlab`, `ylab`, `main`, and `sub` for axis labels and (sub)title .it[.grey-light[(optional)]] - `col` and `pch` for color and plot character .it[.grey-light[(optional)]] - `lty` and `lwd` for line type, and line width .it[.grey-light[(optional)]] --- layout: false class: clear, middle Let's see `plot()` in action. ```r # Define two vectors a <- seq(from = 0, to = 2*pi, by = 0.2) b <- sin(a) ``` --- layout: true class: clear, middle --- name: ex-plot ```r plot(x = a, y = b) ``` <img src="05RPlot_files/figure-html/ex-plot1-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, xlab = "x", ylab = "sin(x)") ``` <img src="05RPlot_files/figure-html/ex-plot2-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, xlab = "x", ylab = "sin(x)", col = "blue") ``` <img src="05RPlot_files/figure-html/ex-plot3-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, xlab = "x", ylab = "sin(x)", col = "blue", type = "l") ``` <img src="05RPlot_files/figure-html/ex-plot4-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, xlab = "x", ylab = "sin(x)", col = "blue", type = "b") ``` <img src="05RPlot_files/figure-html/ex-plot5-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, xlab = "x", ylab = "sin(x)", col = "blue", type = "s") ``` <img src="05RPlot_files/figure-html/ex-plot6-1.svg" style="display: block; margin: auto;" /> --- name: multiple `plot()` is essentially calling `points()` or `lines()`. You can layer plots by using these individual functions. --- ```r plot(x = a, y = b, col = "blue") ``` <img src="05RPlot_files/figure-html/ex-plot7-1.svg" style="display: block; margin: auto;" /> --- ```r plot(x = a, y = b, col = "blue"); points(x = a, y = -b, col = "orange") ``` <img src="05RPlot_files/figure-html/ex-plot8-1.svg" style="display: block; margin: auto;" /> --- `graphics` also offers a nice histogram function in `hist()`. --- name: hist ```r hist(x = b, breaks = 10, col = "purple", xlab = "sin(x)", main = "Wow.") ``` <img src="05RPlot_files/figure-html/ex-hist-1.svg" style="display: block; margin: auto;" /> --- That said/done, further customization/manipulation of your graphics using `graphics` plotting functions can become quite difficult. .note[Enter] `ggplot2` --- layout: true # ggplot2 --- name: ggplot2 class: inverse, middle --- name: gg-intro ## The grammar The `ggplot2` package offers an incredibly flexible, diverse, and powerful set of functions for creating graphics in .mono[R]. -- The `gg` stands for the *grammar of graphics*. -- `ggplot2` 1. centers on a .hi-slate[data frame] (the `data` argument) 1. maps variables to .hi-slate[aesthetics] (the `aes` argument) 1. .hi-slate[layers geometries] to *build up* your graphic .note[Note] The package is called `ggplot2`, but the main function is `ggplot()`. --- name: ggplot ## `ggplot()` Main arguments 1. .hi-pink[`data`] Your dataset. As a data frame (or `tibble`). -- 2. .hi-purple[`aes()`] Maps variables in `data` to "aesthetics" like `x`, `color`, `shape`. -- .ex[Example] A time series of problems, `color` defined by money ```r library(ggplot2) ggplot( data = pretend_df, aes(x = time, y = problems, color = money) ) ``` --- name: layers ## Layers The `ggplot()` function doesn't plot anything—it *sets up* the plot. To create the actual figure, you layer .hi-slate[geometries] (*e.g.*, `geom_point()`), -- <br>.hi-slate[scales] (*e.g.*, `scale_color_manual()`), -- and other .hi-slate[options] (*e.g.*, `xlab()`). -- You .hi-slate[add layers] using the addition sign (`+`). -- .ex[Example] A time series of problems, `color` defined by money ```r library(ggplot2) ggplot( data = pretend_df, aes(x = time, y = problems, color = money) *) + *geom_point() + geom_line() ``` --- layout: true class: clear, middle --- Alright, let's build a plot. We'll use the `economics` dataset that comes with `ggplot2` <br>(because economics). --- <div id="htmlwidget-aa858461c03c2410cb5b" style="width:100%;height:auto;" class="datatables html-widget"></div> <script type="application/json" data-for="htmlwidget-aa858461c03c2410cb5b">{"x":{"filter":"none","fillContainer":false,"data":[["1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49","50","51","52","53","54","55","56","57","58","59","60","61","62","63","64","65","66","67","68","69","70","71","72","73","74","75","76","77","78","79","80","81","82","83","84","85","86","87","88","89","90","91","92","93","94","95","96","97","98","99","100","101","102","103","104","105","106","107","108","109","110","111","112","113","114","115","116","117","118","119","120","121","122","123","124","125","126","127","128","129","130","131","132","133","134","135","136","137","138","139","140","141","142","143","144","145","146","147","148","149","150","151","152","153","154","155","156","157","158","159","160","161","162","163","164","165","166","167","168","169","170","171","172","173","174","175","176","177","178","179","180","181","182","183","184","185","186","187","188","189","190","191","192","193","194","195","196","197","198","199","200","201","202","203","204","205","206","207","208","209","210","211","212","213","214","215","216","217","218","219","220","221","222","223","224","225","226","227","228","229","230","231","232","233","234","235","236","237","238","239","240","241","242","243","244","245","246","247","248","249","250","251","252","253","254","255","256","257","258","259","260","261","262","263","264","265","266","267","268","269","270","271","272","273","274","275","276","277","278","279","280","281","282","283","284","285","286","287","288","289","290","291","292","293","294","295","296","297","298","299","300","301","302","303","304","305","306","307","308","309","310","311","312","313","314","315","316","317","318","319","320","321","322","323","324","325","326","327","328","329","330","331","332","333","334","335","336","337","338","339","340","341","342","343","344","345","346","347","348","349","350","351","352","353","354","355","356","357","358","359","360","361","362","363","364","365","366","367","368","369","370","371","372","373","374","375","376","377","378","379","380","381","382","383","384","385","386","387","388","389","390","391","392","393","394","395","396","397","398","399","400","401","402","403","404","405","406","407","408","409","410","411","412","413","414","415","416","417","418","419","420","421","422","423","424","425","426","427","428","429","430","431","432","433","434","435","436","437","438","439","440","441","442","443","444","445","446","447","448","449","450","451","452","453","454","455","456","457","458","459","460","461","462","463","464","465","466","467","468","469","470","471","472","473","474","475","476","477","478","479","480","481","482","483","484","485","486","487","488","489","490","491","492","493","494","495","496","497","498","499","500","501","502","503","504","505","506","507","508","509","510","511","512","513","514","515","516","517","518","519","520","521","522","523","524","525","526","527","528","529","530","531","532","533","534","535","536","537","538","539","540","541","542","543","544","545","546","547","548","549","550","551","552","553","554","555","556","557","558","559","560","561","562","563","564","565","566","567","568","569","570","571","572","573","574"],["1967-07-01","1967-08-01","1967-09-01","1967-10-01","1967-11-01","1967-12-01","1968-01-01","1968-02-01","1968-03-01","1968-04-01","1968-05-01","1968-06-01","1968-07-01","1968-08-01","1968-09-01","1968-10-01","1968-11-01","1968-12-01","1969-01-01","1969-02-01","1969-03-01","1969-04-01","1969-05-01","1969-06-01","1969-07-01","1969-08-01","1969-09-01","1969-10-01","1969-11-01","1969-12-01","1970-01-01","1970-02-01","1970-03-01","1970-04-01","1970-05-01","1970-06-01","1970-07-01","1970-08-01","1970-09-01","1970-10-01","1970-11-01","1970-12-01","1971-01-01","1971-02-01","1971-03-01","1971-04-01","1971-05-01","1971-06-01","1971-07-01","1971-08-01","1971-09-01","1971-10-01","1971-11-01","1971-12-01","1972-01-01","1972-02-01","1972-03-01","1972-04-01","1972-05-01","1972-06-01","1972-07-01","1972-08-01","1972-09-01","1972-10-01","1972-11-01","1972-12-01","1973-01-01","1973-02-01","1973-03-01","1973-04-01","1973-05-01","1973-06-01","1973-07-01","1973-08-01","1973-09-01","1973-10-01","1973-11-01","1973-12-01","1974-01-01","1974-02-01","1974-03-01","1974-04-01","1974-05-01","1974-06-01","1974-07-01","1974-08-01","1974-09-01","1974-10-01","1974-11-01","1974-12-01","1975-01-01","1975-02-01","1975-03-01","1975-04-01","1975-05-01","1975-06-01","1975-07-01","1975-08-01","1975-09-01","1975-10-01","1975-11-01","1975-12-01","1976-01-01","1976-02-01","1976-03-01","1976-04-01","1976-05-01","1976-06-01","1976-07-01","1976-08-01","1976-09-01","1976-10-01","1976-11-01","1976-12-01","1977-01-01","1977-02-01","1977-03-01","1977-04-01","1977-05-01","1977-06-01","1977-07-01","1977-08-01","1977-09-01","1977-10-01","1977-11-01","1977-12-01","1978-01-01","1978-02-01","1978-03-01","1978-04-01","1978-05-01","1978-06-01","1978-07-01","1978-08-01","1978-09-01","1978-10-01","1978-11-01","1978-12-01","1979-01-01","1979-02-01","1979-03-01","1979-04-01","1979-05-01","1979-06-01","1979-07-01","1979-08-01","1979-09-01","1979-10-01","1979-11-01","1979-12-01","1980-01-01","1980-02-01","1980-03-01","1980-04-01","1980-05-01","1980-06-01","1980-07-01","1980-08-01","1980-09-01","1980-10-01","1980-11-01","1980-12-01","1981-01-01","1981-02-01","1981-03-01","1981-04-01","1981-05-01","1981-06-01","1981-07-01","1981-08-01","1981-09-01","1981-10-01","1981-11-01","1981-12-01","1982-01-01","1982-02-01","1982-03-01","1982-04-01","1982-05-01","1982-06-01","1982-07-01","1982-08-01","1982-09-01","1982-10-01","1982-11-01","1982-12-01","1983-01-01","1983-02-01","1983-03-01","1983-04-01","1983-05-01","1983-06-01","1983-07-01","1983-08-01","1983-09-01","1983-10-01","1983-11-01","1983-12-01","1984-01-01","1984-02-01","1984-03-01","1984-04-01","1984-05-01","1984-06-01","1984-07-01","1984-08-01","1984-09-01","1984-10-01","1984-11-01","1984-12-01","1985-01-01","1985-02-01","1985-03-01","1985-04-01","1985-05-01","1985-06-01","1985-07-01","1985-08-01","1985-09-01","1985-10-01","1985-11-01","1985-12-01","1986-01-01","1986-02-01","1986-03-01","1986-04-01","1986-05-01","1986-06-01","1986-07-01","1986-08-01","1986-09-01","1986-10-01","1986-11-01","1986-12-01","1987-01-01","1987-02-01","1987-03-01","1987-04-01","1987-05-01","1987-06-01","1987-07-01","1987-08-01","1987-09-01","1987-10-01","1987-11-01","1987-12-01","1988-01-01","1988-02-01","1988-03-01","1988-04-01","1988-05-01","1988-06-01","1988-07-01","1988-08-01","1988-09-01","1988-10-01","1988-11-01","1988-12-01","1989-01-01","1989-02-01","1989-03-01","1989-04-01","1989-05-01","1989-06-01","1989-07-01","1989-08-01","1989-09-01","1989-10-01","1989-11-01","1989-12-01","1990-01-01","1990-02-01","1990-03-01","1990-04-01","1990-05-01","1990-06-01","1990-07-01","1990-08-01","1990-09-01","1990-10-01","1990-11-01","1990-12-01","1991-01-01","1991-02-01","1991-03-01","1991-04-01","1991-05-01","1991-06-01","1991-07-01","1991-08-01","1991-09-01","1991-10-01","1991-11-01","1991-12-01","1992-01-01","1992-02-01","1992-03-01","1992-04-01","1992-05-01","1992-06-01","1992-07-01","1992-08-01","1992-09-01","1992-10-01","1992-11-01","1992-12-01","1993-01-01","1993-02-01","1993-03-01","1993-04-01","1993-05-01","1993-06-01","1993-07-01","1993-08-01","1993-09-01","1993-10-01","1993-11-01","1993-12-01","1994-01-01","1994-02-01","1994-03-01","1994-04-01","1994-05-01","1994-06-01","1994-07-01","1994-08-01","1994-09-01","1994-10-01","1994-11-01","1994-12-01","1995-01-01","1995-02-01","1995-03-01","1995-04-01","1995-05-01","1995-06-01","1995-07-01","1995-08-01","1995-09-01","1995-10-01","1995-11-01","1995-12-01","1996-01-01","1996-02-01","1996-03-01","1996-04-01","1996-05-01","1996-06-01","1996-07-01","1996-08-01","1996-09-01","1996-10-01","1996-11-01","1996-12-01","1997-01-01","1997-02-01","1997-03-01","1997-04-01","1997-05-01","1997-06-01","1997-07-01","1997-08-01","1997-09-01","1997-10-01","1997-11-01","1997-12-01","1998-01-01","1998-02-01","1998-03-01","1998-04-01","1998-05-01","1998-06-01","1998-07-01","1998-08-01","1998-09-01","1998-10-01","1998-11-01","1998-12-01","1999-01-01","1999-02-01","1999-03-01","1999-04-01","1999-05-01","1999-06-01","1999-07-01","1999-08-01","1999-09-01","1999-10-01","1999-11-01","1999-12-01","2000-01-01","2000-02-01","2000-03-01","2000-04-01","2000-05-01","2000-06-01","2000-07-01","2000-08-01","2000-09-01","2000-10-01","2000-11-01","2000-12-01","2001-01-01","2001-02-01","2001-03-01","2001-04-01","2001-05-01","2001-06-01","2001-07-01","2001-08-01","2001-09-01","2001-10-01","2001-11-01","2001-12-01","2002-01-01","2002-02-01","2002-03-01","2002-04-01","2002-05-01","2002-06-01","2002-07-01","2002-08-01","2002-09-01","2002-10-01","2002-11-01","2002-12-01","2003-01-01","2003-02-01","2003-03-01","2003-04-01","2003-05-01","2003-06-01","2003-07-01","2003-08-01","2003-09-01","2003-10-01","2003-11-01","2003-12-01","2004-01-01","2004-02-01","2004-03-01","2004-04-01","2004-05-01","2004-06-01","2004-07-01","2004-08-01","2004-09-01","2004-10-01","2004-11-01","2004-12-01","2005-01-01","2005-02-01","2005-03-01","2005-04-01","2005-05-01","2005-06-01","2005-07-01","2005-08-01","2005-09-01","2005-10-01","2005-11-01","2005-12-01","2006-01-01","2006-02-01","2006-03-01","2006-04-01","2006-05-01","2006-06-01","2006-07-01","2006-08-01","2006-09-01","2006-10-01","2006-11-01","2006-12-01","2007-01-01","2007-02-01","2007-03-01","2007-04-01","2007-05-01","2007-06-01","2007-07-01","2007-08-01","2007-09-01","2007-10-01","2007-11-01","2007-12-01","2008-01-01","2008-02-01","2008-03-01","2008-04-01","2008-05-01","2008-06-01","2008-07-01","2008-08-01","2008-09-01","2008-10-01","2008-11-01","2008-12-01","2009-01-01","2009-02-01","2009-03-01","2009-04-01","2009-05-01","2009-06-01","2009-07-01","2009-08-01","2009-09-01","2009-10-01","2009-11-01","2009-12-01","2010-01-01","2010-02-01","2010-03-01","2010-04-01","2010-05-01","2010-06-01","2010-07-01","2010-08-01","2010-09-01","2010-10-01","2010-11-01","2010-12-01","2011-01-01","2011-02-01","2011-03-01","2011-04-01","2011-05-01","2011-06-01","2011-07-01","2011-08-01","2011-09-01","2011-10-01","2011-11-01","2011-12-01","2012-01-01","2012-02-01","2012-03-01","2012-04-01","2012-05-01","2012-06-01","2012-07-01","2012-08-01","2012-09-01","2012-10-01","2012-11-01","2012-12-01","2013-01-01","2013-02-01","2013-03-01","2013-04-01","2013-05-01","2013-06-01","2013-07-01","2013-08-01","2013-09-01","2013-10-01","2013-11-01","2013-12-01","2014-01-01","2014-02-01","2014-03-01","2014-04-01","2014-05-01","2014-06-01","2014-07-01","2014-08-01","2014-09-01","2014-10-01","2014-11-01","2014-12-01","2015-01-01","2015-02-01","2015-03-01","2015-04-01"],[507.4,510.5,516.3,512.9,518.1,525.8,531.5,534.2,544.9,544.6,550.4,556.8,563.8,567.6,568.8,572.3,577.4,577.2,584.2,589.5,589.7,594.7,601.1,601.7,603.5,610.8,614.1,619.4,621.4,623.7,629.6,634.9,633.2,637,643.4,647.2,649.5,653.9,660.1,659.3,657.6,666.6,677.2,680.4,683,689.8,692.2,700.8,699.9,706,714.1,716.9,722.1,729.6,732.6,737.3,750.4,753.8,759.2,762.9,771.2,777.7,782.5,796.3,801.8,807.5,817.9,827.2,834.2,837.2,843.1,845.8,855.7,854.9,870.9,869.8,878.6,878.4,886.4,891.6,903.3,912.7,924.3,929.9,939.8,956.6,956.8,961,958,963.6,977.4,991.3,992.6,997.2,1021.2,1029.1,1042.2,1049.4,1057.2,1063.2,1078,1094.4,1109.5,1110.1,1117.3,1127.8,1125.1,1142.9,1152.1,1160.5,1171.4,1179.5,1191.7,1214.1,1217.4,1233.7,1240.7,1249.7,1259.6,1266.3,1283.2,1288.5,1297.4,1314.3,1330,1339.3,1333,1358.9,1381.4,1400.2,1415.9,1429.8,1430.8,1451,1456.9,1471,1484.7,1500.5,1506.3,1521.6,1535,1542.3,1562.7,1579.6,1590.1,1619.7,1638.1,1646,1661.7,1670.7,1701.6,1705.6,1712.4,1699.5,1704.3,1723,1751.2,1767.7,1784.1,1820.4,1830.2,1855.5,1874.7,1889.4,1908.1,1909.1,1918.2,1938.5,1945.7,1969.8,1968.2,1966.2,1972.4,1989.9,1997.4,2021.4,2024.4,2027.2,2045.9,2050.2,2075.1,2083.7,2108.9,2130.7,2154.7,2167.4,2180.1,2183.1,2208.6,2231.8,2251,2280.8,2309,2324.8,2339.1,2361.8,2370.4,2397.9,2423.8,2408.1,2436.4,2462.6,2479.8,2501.2,2500.5,2518.4,2540.3,2538.2,2578.6,2590,2626.3,2648.6,2656.8,2668.4,2705.9,2699.3,2725.9,2762.7,2805.6,2767.1,2782.7,2822.8,2838.3,2831.2,2834.7,2846.5,2869,2873.5,2893.4,2911.1,2984.6,2945.9,2941.7,3010.8,2949.9,3016.5,3028.4,3054.1,3063.9,3088.4,3110.7,3147,3142.9,3151.1,3160.9,3190.9,3230.7,3238.5,3277.8,3280.4,3311,3335.6,3359.3,3384.3,3391.4,3430.4,3447,3476.3,3499.9,3503.9,3514.5,3558.6,3567.5,3582.4,3601.7,3636.8,3638.1,3650,3659.7,3700.7,3747.2,3744.8,3771.5,3786.7,3792.5,3821.3,3838.5,3865,3886.7,3887.1,3888.4,3877.8,3857.6,3883.3,3929.7,3923.9,3950,3957.1,3982.4,3985.4,4001.2,3992.9,4020.6,4037.7,4101.9,4116.8,4134.3,4149,4176.1,4195,4223,4239.3,4273.9,4303.5,4319.5,4355.6,4359.7,4374.3,4371.4,4412.4,4441.3,4458.8,4487.7,4499.9,4530.5,4552,4573.4,4590.7,4604.8,4652.3,4665.4,4690.7,4689.2,4728.8,4740.8,4783,4795.5,4833.3,4846,4862.3,4871.9,4871.7,4906.5,4911.5,4954.4,4999,4991.8,5027.1,5042.5,5035.9,5077.8,5120.1,5108.9,5156.1,5196.4,5231.6,5247.2,5253.7,5275.8,5299,5320,5351.5,5375,5401.7,5434.9,5457.7,5477.6,5482.8,5484.3,5518.2,5573,5611.8,5625.6,5661.2,5685.2,5716.4,5714.4,5748.4,5775,5812.9,5863.3,5897.2,5915.6,5951,5991.8,6025.8,6042.7,6098.2,6099.1,6128.2,6159.7,6223.6,6253.4,6281.9,6309.5,6354.8,6407.4,6431.2,6467.2,6568.2,6564.7,6648.7,6714.8,6701,6737.2,6773.6,6793.7,6828.7,6913.1,6919.6,6934.5,6979.1,7009.8,7029.3,7022.1,7036.2,7083.1,7097.1,7109.2,7146.1,7054.8,7250.2,7209.6,7190,7217.7,7259.7,7276.7,7345.6,7321.8,7366.1,7424.2,7449,7426.1,7469.3,7499.8,7552.6,7579.5,7573.6,7627.5,7661.7,7669.2,7722.9,7783.8,7878.9,7874,7890.6,7950.4,7974.3,8037.3,8072.1,8121,8141.6,8212.9,8204.6,8270.7,8294.4,8373,8417.9,8458.4,8516.5,8521.2,8575.7,8622.5,8715.9,8680.6,8775.3,8867.9,8872.6,8923.6,8959.6,8987.7,9026.8,9100.1,9134.7,9168.1,9223.3,9254.1,9283.8,9360.4,9368.6,9393.9,9413.3,9431.2,9516.5,9553.1,9590.8,9631.6,9670.6,9708.9,9723.3,9759.6,9800.6,9837.5,9853.9,9928.6,9947.6,9963.2,9955.7,10004.2,10044.6,10093.3,10149.4,10151.1,10140.3,10083.2,9983.3,9851.2,9744.2,9792.1,9775.7,9742.9,9741.9,9759.7,9807.6,9835.2,9961.9,9875.4,9924.6,9946.1,10000.6,10003.4,10034.7,10095.5,10106.9,10140.2,10165.9,10184.3,10247.1,10268.9,10343.7,10399.8,10436.1,10474.7,10512.4,10583.5,10624.6,10653.1,10676.4,10727.1,10745.6,10790.6,10827.6,10828.7,10827.3,10905.5,10979.2,10994.3,11030.2,11029,11032.5,11074.8,11104.8,11179.6,11199.9,11222.8,11245.2,11303.2,11371.4,11378.8,11373.3,11407.1,11462.4,11484.7,11511.6,11559.6,11602.1,11671.5,11686.3,11663.9,11714.4,11807.1,11825.2,11864.3,11922.6,11944.4,12017,12044.6,12096.4,12142.2,12122,12080.8,12095.9,12161.5,12158.9],[198712,198911,199113,199311,199498,199657,199808,199920,200056,200208,200361,200536,200706,200898,201095,201290,201466,201621,201760,201881,202023,202161,202331,202507,202677,202877,203090,203302,203500,203675,203849,204008,204156,204401,204607,204830,205052,205295,205540,205788,206024,206238,206466,206668,206855,207065,207260,207462,207661,207881,208114,208345,208555,208740,208917,209061,209212,209386,209545,209725,209896,210075,210278,210479,210656,210821,210985,211120,211254,211420,211577,211746,211909,212092,212289,212475,212634,212785,212932,213074,213211,213361,213513,213686,213854,214042,214246,214451,214625,214782,214931,215065,215198,215353,215523,215768,215973,216195,216393,216587,216771,216931,217095,217249,217381,217528,217685,217861,218035,218233,218440,218644,218834,219006,219179,219344,219504,219684,219859,220046,220239,220458,220688,220904,221109,221303,221477,221629,221792,221991,222176,222379,222585,222805,223053,223271,223477,223670,223865,224053,224235,224438,224632,224843,225055,225295,225547,225801,226027,226243,226451,226656,226849,227061,227251,227522,227726,227953,228186,228417,228612,228779,228937,229071,229224,229403,229575,229761,229966,230187,230412,230641,230822,230989,231157,231313,231470,231645,231809,231992,232188,232392,232599,232816,232993,233160,233322,233473,233613,233781,233922,234118,234307,234501,234701,234907,235078,235235,235385,235527,235675,235839,235993,236160,236348,236549,236760,236976,237159,237316,237468,237602,237732,237900,238074,238270,238466,238679,238898,239113,239307,239477,239638,239788,239928,240094,240271,240459,240651,240854,241068,241274,241467,241620,241784,241930,242079,242252,242423,242608,242804,243012,243223,243446,243639,243809,243981,244131,244279,244445,244610,244806,245021,245240,245464,245693,245884,246056,246224,246378,246530,246721,246906,247114,247342,247573,247816,248067,248281,248479,248659,248827,249012,249306,249565,249849,250132,250439,250751,251057,251346,251626,251889,252135,252372,252643,252913,253207,253493,253807,254126,254435,254718,254964,255214,255448,255703,255992,256285,256589,256894,257232,257548,257861,258147,258413,258679,258919,259152,259414,259680,259963,260255,260566,260867,261163,261425,261674,261919,262123,262352,262631,262877,263152,263436,263724,264017,264301,264559,264804,265044,265270,265495,265755,265998,266270,266557,266843,267152,267456,267715,267943,268151,268364,268595,268853,269108,269386,269667,269976,270284,270581,270878,271125,271360,271585,271821,272083,272342,272622,272912,273237,273553,273852,274126,274372,274626,274838,275047,275304,275564,275836,276115,276418,276714,277003,277277,277526,277790,277992,278198,278451,278717,279001,279295,279602,279903,280203,280471,280716,280976,281190,281409,281653,281877,282126,282385,282653,282932,283201,283453,283696,283920,284137,284350,284581,284810,285062,285309,285570,285843,286098,286341,286570,286788,286994,287190,287397,287623,287864,288105,288360,288618,288870,289106,289313,289518,289714,289911,290125,290346,290584,290820,291072,291321,291574,291807,292008,292192,292368,292561,292779,292997,293223,293463,293719,293971,294230,294466,294694,294914,295105,295287,295490,295704,295936,296186,296440,296707,296972,297207,297431,297647,297854,298060,298281,298496,298739,298996,299263,299554,299835,300094,300340,300574,300802,301021,301254,301483,301739,302004,302267,302546,302807,303054,303287,303506,303711,303907,304117,304323,304556,304798,305045,305309,305554,305786,306004,306208,306402,306588,306787,306984,307206,307439,307685,307946,308189,308418,308633,308833,309027,309212,309191,309376,309562,309767,309989,310218,310451,310657,310853,311042,311205,311367,311548,311729,311923,312139,312355,312587,312810,313003,313191,313373,313537,313705,313881,314052,314247,314449,314673,314909,315129,315341,315532,315701,315869,316041,316220,316395,316594,316799,317019,317253,317470,317679,317867,318032,318200,318373,318552,318728,318927,319133,319354,319588,319804,320013,320201,320367,320534,320707,320887],[12.5,12.5,11.7,12.5,12.5,12.1,11.7,12.2,11.6,12.2,12,11.6,10.6,10.4,10.4,10.6,10.4,10.9,10,9.4,9.9,9.5,10,10.9,11.7,11.5,11.5,11.3,11.5,11.7,11.7,11.6,12.3,13.3,12.3,11.7,13.2,13.1,12.9,13,13.3,12.9,13.1,13.1,13.3,13,13.4,14.4,13.6,13.6,12.9,13,12.8,12.9,12.4,12.6,11.5,11.3,11.5,11.4,11.4,11.8,12,12.7,13.4,13.4,12.1,12.2,12.4,12.8,12.8,13.2,12.8,13.6,12.8,14,14,14.4,14,13.8,13,12.7,12.3,12.5,12.7,11.6,12.3,13,13.4,13.6,12.8,12.1,12.3,13.9,17,13.9,12.3,12.6,12.6,13,12.3,11.5,11.3,11.9,11.8,11.2,11.8,10.9,11.2,11.2,10.8,10.6,10.9,9.9,9.8,8.5,9.8,9.9,9.8,10.2,10.1,10.5,10.7,10.7,10.8,11,11.4,10.7,10.5,10.3,9.8,9.5,10.3,9.9,10,10.2,10,10,10.6,10.5,10.7,10.4,9.8,9.3,10,9.2,8.9,9.3,9.4,9.8,9.6,9.8,9.8,10.5,10.6,10.4,10.5,10.6,11.1,11,11.5,11.2,10.5,10.4,10.3,10.3,10.4,10.2,11.7,11.4,11.9,12.5,12.7,12,12.2,11.6,11.7,12.4,11.7,11.6,12,11.9,11.1,10.7,10.3,10.3,10.4,10.5,10,9.6,9.4,8.5,9,8.7,9,9.1,9.7,9.5,9.4,11.1,10.9,10.9,10.5,10.5,11,11.2,11.2,11.2,10.3,10.6,9.7,8.5,8.1,9.4,10.5,9,8.5,7.5,6.7,8.5,8.4,8,8,8.7,9.3,9.1,8.6,8.8,8.7,8.4,6.6,7.8,8.2,6.4,9.1,7.9,7.9,3.8,7.5,7,6.8,6.5,7,7.6,7.9,8,7.5,7.9,7.5,8.1,7.7,7.8,7.9,7.8,8.2,8,7.7,7.7,8,8.4,8.9,7.9,7.6,7.6,7.7,7.1,7.5,7.9,8,7.2,7.4,8.1,7.8,8.2,8,7.9,8,7.5,7.5,7.3,7.4,8.2,8.7,8.3,7.4,8,7.7,8.2,7.6,7.9,8.1,8.6,8.4,9.1,8.8,9.2,9.2,9.4,9.4,9.5,9.1,9.2,8.2,7.4,7.3,9.9,8.3,8.4,8.3,8.2,7.7,7.2,7,7.1,6.3,5.6,5.6,8.4,6.4,5.9,6.2,5.8,7.1,6.3,6.4,5.9,6.2,6.5,6.4,6.5,6.9,7.3,7,6.3,6.5,6.1,6.4,6.1,6.1,6.5,6,5.5,6.1,6.1,6,5,6.1,6.5,6.1,5.9,6,5.8,5.8,5.7,5.6,5.7,5.8,5.9,6.2,6,5.5,5.4,5.6,5.6,5.8,5.8,6.7,6.8,6.9,6.6,6.3,6.2,6.3,6.2,5.8,5.6,5.7,5.2,5.7,5.6,5.3,4.5,4.3,4.2,4.1,4,3.5,3.9,4.1,3.7,4.7,4.2,3.9,4.4,4.2,4.2,4.6,4.6,3.8,4,3.8,3.5,4,4.1,4.5,4.3,3.7,3.7,5,6.1,6.3,2.7,3.4,3.8,5.6,5.3,5.3,5.1,5.6,5.4,4.6,4.4,4.9,4.7,4.7,4.5,4.5,4.7,4.6,4.6,5.1,4.9,5.5,5.3,4.5,4.6,4.7,4.8,4.5,4.5,4.5,4.7,4.7,5,4.5,4.6,3.9,3.8,3.4,6.3,2.9,2.7,2.7,2.1,3,2.2,1.9,2.4,2.3,2.6,2.7,2.8,3.7,3.8,3.7,3.4,3.2,3.4,2.9,3,3,3.1,3.2,3,3,3.3,3.6,3.2,3,2.8,2.8,2.6,2.8,2.8,2.5,3,3.4,3.9,4,3.5,7.9,5.6,4.4,3.7,4.4,5.4,6.3,6.5,6.5,5.9,6.1,6.7,8.1,6.7,6,4.9,5.9,5.4,5.7,5.7,5.6,5.2,5,5.6,6,5.9,5.9,5.8,5.6,5.4,5.3,5.9,6.2,6.4,6,5.9,5.9,6.1,6.3,6.2,5.7,5.5,5.6,6.4,6.6,6.7,6.9,7,7,7.1,6.6,6.4,6.5,7.1,8.2,10.5,4.5,4.7,4.9,5.1,5.2,5.3,5.1,5.3,5.2,4.7,4.3,4.1,4.9,5,4.8,5,5.1,5.1,5.1,4.7,4.6,4.6,4.5,5,5.5,5.7,5.2,5.6],[4.5,4.7,4.6,4.9,4.7,4.8,5.1,4.5,4.1,4.6,4.4,4.4,4.5,4.2,4.6,4.8,4.4,4.4,4.4,4.9,4,4,4.2,4.4,4.4,4.4,4.7,4.5,4.8,4.6,4.6,4.5,4.6,4.1,4.7,4.9,5.1,5.4,5.2,5.2,5.6,5.9,6.2,6.3,6.4,6.5,6.7,5.7,6.2,6.4,5.8,6.5,6.4,6.2,6.2,6.6,6.6,6.7,6.6,5.4,6.1,6,5.6,5.7,5.7,6.1,5.7,5.2,5.5,5,4.9,5,5.2,4.9,5.4,5.5,5.1,4.7,5,5.1,4.8,5,4.6,5.3,5.7,5,5.3,5.5,5.2,5.7,6.3,7.1,7.2,8.7,9.4,8.8,8.6,9.2,9.2,8.6,9.5,9,9,8.2,8.7,8.2,8.3,7.8,7.7,7.9,7.8,7.7,8.4,8,7.5,7.2,7.2,7.3,7.9,6.2,7.1,7,6.7,6.9,7,6.8,6.5,6.7,6.2,6.1,5.7,6,5.8,5.8,5.6,5.9,5.5,5.6,5.9,5.9,5.9,5.4,5.6,5.6,5.9,4.8,5.5,5.5,5.3,5.7,5.3,5.8,6,5.8,5.7,6.4,7,7.5,7.7,7.5,7.7,7.5,7.4,7.1,7.1,7.4,6.9,6.6,7.1,7.2,6.8,6.8,6.9,6.9,7.1,7.5,7.7,8.1,8.5,9.5,8.5,8.7,9.5,9.7,10,10.2,11.1,9.8,10.4,10.9,12.3,11.3,10.1,9.3,9.3,9.4,9.3,8.7,9.1,8.3,8.3,8.2,9.1,7.5,7.5,7.3,7.6,7.2,7.2,7.3,6.8,7.1,7.1,6.9,6.9,6.6,6.9,7.1,6.9,7.1,7,6.8,6.7,6.9,6.8,6.7,6.8,7,6.9,7.1,7.4,7,7.1,7.1,6.9,6.6,6.6,7.1,6.6,6.5,6.5,6.4,6,6.3,6.2,6,6.2,6.3,6.4,5.9,5.9,5.8,6.1,5.9,5.7,5.6,5.7,5.9,5.6,5.4,5.4,5.4,5.3,5.4,5.6,5,4.9,4.9,4.8,4.9,5.1,5.3,5.1,4.8,5.2,5.2,5.4,5.4,5.6,5.8,5.7,5.9,6,6.2,6.7,6.6,6.4,6.9,7,7.3,6.8,7.2,7.5,7.8,8.1,8.2,8.3,8.5,8.8,8.7,8.6,8.8,8.6,9,9,9.3,8.6,8.5,8.5,8.4,8.1,8.3,8.2,8.2,8.3,8,8.3,8.3,8.6,9.2,9.3,9.1,9.2,9.3,9,8.9,9.2,10,9,8.7,8,8.1,8.3,8.3,9.1,7.9,8.5,8.3,7.9,8.2,8,8.3,8.3,7.8,8.3,8.6,8.6,8.3,8.3,8.4,8.5,8.3,7.7,7.8,7.8,8.1,7.9,8.3,8,8,8.3,7.8,8.2,7.7,7.6,7.5,7.4,7,6.8,6.7,6,6.9,6.7,6.8,6.7,5.8,6.6,6.8,6.9,6.8,6.8,6.2,6.5,6.3,5.8,6.5,6,6.1,6.2,5.8,5.8,6.1,6,6.1,5.8,5.7,6,6.3,5.2,6.1,6.1,6,5.8,6.1,6.6,5.9,6.3,6,6.8,6.9,7.2,7.3,7.7,8.2,8.4,8.3,8.4,8.9,9.5,11,8.9,9,9.5,9.6,9.3,9.6,9.6,9.5,9.7,10.2,9.9,11.5,10.3,10.1,10.2,10.4,10.3,10.4,10.6,10.2,10.2,9.5,9.9,11,8.9,9.2,9.6,9.5,9.7,9.5,9.4,9.2,9.3,9,9.1,9,8.8,9.2,8.4,8.6,8.5,8.7,8.6,9.1,8.7,8.4,8.5,7.3,8,8.4,8,7.9,8.3,7.5,8.3,8.5,9.1,8.6,8.2,7.7,8.7,8.8,8.7,8.4,8.6,8.4,9,8.7,8.7,9.4,7.9,9,9.7,9.7,10.2,10.4,9.8,10.5,10.7,11.7,12.3,13.1,14.2,17.2,16,16.3,17.8,18.9,19.8,20.1,20,19.9,20.4,22.1,22.3,25.2,22.3,21,20.3,21.2,21,21.9,21.6,21.1,21.5,20.9,21.6,22.3,22,22.4,22,20.5,20.9,20.5,21,19.8,19.2,19.1,19.9,20.1,17.5,18.5,18.8,19.7,18.5,17.6,16.2,17.5,17.7,17.1,17,16.6,16.3,16.8,16.5,16.1,17,17,15.9,16.2,15.9,15.6,14.5,13.2,13.5,13.3,13.3,13.5,12.8,12.6,13.4,13.1,12.2,11.7],[2944,2945,2958,3143,3066,3018,2878,3001,2877,2709,2740,2938,2883,2768,2686,2689,2715,2685,2718,2692,2712,2758,2713,2816,2868,2856,3040,3049,2856,2884,3201,3453,3635,3797,3919,4071,4175,4256,4456,4591,4898,5076,4986,4903,4987,4959,4996,4949,5035,5134,5042,4954,5161,5154,5019,4928,5038,4959,4922,4923,4913,4939,4849,4875,4602,4543,4326,4452,4394,4459,4329,4363,4305,4305,4350,4144,4396,4489,4644,4731,4634,4618,4705,4927,5063,5022,5437,5523,6140,6636,7501,7520,7978,8210,8433,8220,8127,7928,7923,7897,7794,7744,7534,7326,7230,7330,7053,7322,7490,7518,7380,7430,7620,7545,7280,7443,7307,7059,6911,7134,6829,6925,6751,6763,6815,6386,6489,6318,6337,6180,6127,6028,6309,6080,6125,5947,6077,6228,6109,6173,6109,6069,5840,5959,5996,6320,6190,6296,6238,6325,6683,6702,6729,7358,7984,8098,8363,8281,8021,8088,8023,7718,8071,8051,7982,7869,8174,8098,7863,8036,8230,8646,9029,9267,9397,9705,9895,10244,10335,10538,10849,10881,11217,11529,11938,12051,11534,11545,11408,11268,11154,11246,10548,10623,10282,9887,9499,9331,9008,8791,8746,8762,8456,8226,8537,8519,8367,8381,8198,8358,8423,8321,8339,8395,8302,8460,8513,8196,8248,8298,8128,8138,7795,8402,8383,8364,8439,8508,8319,8135,8310,8243,8159,7883,7892,7865,7862,7542,7574,7398,7268,7261,7102,7227,7035,6936,6953,6929,6876,6601,6779,6546,6605,6843,6604,6568,6537,6518,6682,6359,6205,6468,6375,6577,6495,6511,6590,6630,6725,6667,6752,6651,6598,6797,6742,6590,6922,7188,7368,7459,7764,7901,8015,8265,8586,8439,8736,8692,8586,8666,8722,8842,8931,9198,9283,9454,9460,9415,9744,10040,9850,9787,9781,9398,9565,9557,9325,9183,9056,9110,9149,9121,8930,8763,8714,8750,8542,8477,8630,8583,8470,8331,7915,7927,7946,7933,7734,7632,7375,7230,7375,7187,7153,7645,7430,7427,7527,7484,7478,7328,7426,7423,7491,7313,7318,7415,7423,7095,7337,6882,6979,7031,7236,7253,7158,7102,7000,6873,6655,6799,6655,6608,6656,6454,6308,6476,6368,6306,6422,5941,6047,6212,6259,6179,6300,6280,6100,6032,5976,6111,5783,6004,5796,5951,6025,5838,5915,5778,5716,5653,5708,5858,5733,5481,5758,5651,5747,5853,5625,5534,5639,5634,6023,6089,6141,6271,6226,6484,6583,7042,7142,7694,8003,8258,8182,8215,8304,8599,8399,8393,8390,8304,8251,8307,8520,8640,8520,8618,8588,8842,8957,9266,9011,8896,8921,8732,8576,8317,8370,8167,8491,8170,8212,8286,8136,7990,7927,8061,7932,7934,7784,7980,7737,7672,7651,7524,7406,7345,7553,7453,7566,7279,7064,7184,7072,7120,6980,7001,7175,7091,6847,6727,6872,6762,7116,6927,6731,6850,6766,6979,7149,7067,7170,7237,7240,7645,7685,7497,7822,7637,8395,8575,8937,9438,9494,10074,10538,11286,12058,12898,13426,13853,14499,14707,14601,14814,15009,15352,15219,15098,15046,15113,15202,15325,14849,14474,14512,14648,14579,14516,15081,14348,14046,13828,13728,13956,13853,13958,13756,13806,13929,13599,13309,13071,12812,12828,12696,12636,12668,12688,12657,12449,12106,12141,12026,12272,12497,11967,11653,11735,11671,11736,11357,11241,11251,11161,10814,10376,10280,10387,10384,9696,9761,9453,9648,9568,9237,8983,9071,8688,8979,8705,8575,8549]],"container":"<table class=\"display\">\n <thead>\n <tr>\n <th> <\/th>\n <th>date<\/th>\n <th>pce<\/th>\n <th>pop<\/th>\n <th>psavert<\/th>\n <th>uempmed<\/th>\n <th>unemploy<\/th>\n <\/tr>\n <\/thead>\n<\/table>","options":{"pageLength":8,"columnDefs":[{"className":"dt-right","targets":[2,3,4,5,6]},{"orderable":false,"targets":0}],"order":[],"autoWidth":false,"orderClasses":false,"lengthMenu":[8,10,25,50,100]}},"evals":[],"jsHooks":[]}</script> --- name: ex-gg .smaller[Set up the plot. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) ``` <img src="05RPlot_files/figure-html/gg0-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Label the axes. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") ``` <img src="05RPlot_files/figure-html/gg1-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Draw some points. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point() ``` <img src="05RPlot_files/figure-html/gg2-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Map the `size` to the median duration of unemployment. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop, size = uempmed)) + ylab("Unemployment rate") + xlab("Date") + geom_point() ``` <img src="05RPlot_files/figure-html/gg3-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Change the `shape` of the points. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop, size = uempmed)) + ylab("Unemployment rate") + xlab("Date") + geom_point(shape = 1) ``` <img src="05RPlot_files/figure-html/gg4-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Map points' `color` to the median duration of unemployment. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop, size = uempmed)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed)) ``` <img src="05RPlot_files/figure-html/gg5-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Add some transparency (`alpha`) to our points. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop, size = uempmed)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5) ``` <img src="05RPlot_files/figure-html/gg6-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Same size points; all bigger. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) ``` <img src="05RPlot_files/figure-html/gg7-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Change our theme—maybe you're a minimalist (but want slightly larger fonts)? ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + theme_minimal(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg8-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Want your figure to look like Stata made it? ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + ggthemes::theme_stata(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg9-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[The "pander" theme from the `ggthemes` package. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + ggthemes::theme_pander(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg10-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Change (and label) our color scale. .note[Note] `viridis` [is the best](https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html). ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + ggthemes::theme_pander(base_size = 14) + scale_color_viridis_c("Dur. unemp.") ``` <img src="05RPlot_files/figure-html/gg11-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[Connect the dots. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_line(color = "grey80") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + ggthemes::theme_pander(base_size = 14) + scale_color_viridis_c("Dur. unemp.") ``` <img src="05RPlot_files/figure-html/gg12-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[How about a smoother? ```r ggplot(data = economics, aes(x = date, y = unemploy/pop)) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + geom_smooth(se = F) + ggthemes::theme_pander(base_size = 14) + scale_color_viridis_c("Dur. unemp.") ``` <img src="05RPlot_files/figure-html/gg13-1.svg" style="display: block; margin: auto;" /> ] --- .smaller[The `group` aesthetic separates groups. ```r ggplot(data = economics, aes(x = date, y = unemploy/pop, group = date < ymd(19900101))) + ylab("Unemployment rate") + xlab("Date") + geom_point(aes(color = uempmed), alpha = 0.5, size = 3) + geom_smooth(se = F) + ggthemes::theme_pander(base_size = 14) + scale_color_viridis_c("Dur. unemp.") ``` <img src="05RPlot_files/figure-html/gg14-1.svg" style="display: block; margin: auto;" /> ] --- .note[Note] The `ymd()` function comes from the `lubridate` package. --- `ggplot2` knows histogams. --- name: gg-hist A histogram. .smaller[ ```r ggplot(data = economics, aes(x = unemploy/pop)) + xlab("Unemployment rate") + geom_histogram(color = "white", fill = "#e64173") + ggthemes::theme_pander(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg-hist1-1.svg" style="display: block; margin: auto;" /> ] --- Add a horizontal line where count = 0. .smaller[ ```r ggplot(data = economics, aes(x = unemploy/pop)) + xlab("Unemployment rate") + geom_histogram(color = "white", fill = "#e64173") + geom_hline(yintercept = 0) + ggthemes::theme_pander(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg-hist2-1.svg" style="display: block; margin: auto;" /> ] --- `ggplot2` knows densities. --- name: gg-density A density plot. .smaller[ ```r ggplot(data = economics, aes(x = unemploy/pop)) + xlab("Unemployment rate") + geom_density(color = NA, fill = "#e64173") + geom_hline(yintercept = 0) + ggthemes::theme_pander(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg-density1-1.svg" style="display: block; margin: auto;" /> ] --- Now with Epanechnikov kernel! .smaller[ ```r ggplot(data = economics, aes(x = unemploy/pop)) + xlab("Unemployment rate") + geom_density(kernel = "epanechnikov", color = NA, fill = "#e64173") + geom_hline(yintercept = 0) + ggthemes::theme_pander(base_size = 14) ``` <img src="05RPlot_files/figure-html/gg-density2-1.svg" style="display: block; margin: auto;" /> ] --- `ggplot2` itself is incredibly flexible/powerful. But there are [even more packages](https://www.ggplot2-exts.org/gallery/) that extend its power—_e.g._, `ggthemes`, `gganimate`, `cowplot`, `ggmap`, `ggExtra`, and (of course) `viridis`. --- name: gg-more Gapminder meets `gganimate` .center[] --- US births by month since 1933 <img src="05RPlot_files/figure-html/ex-new-ts-1.svg" style="display: block; margin: auto;" /> --- layout: true # ggplot2 --- name: ggsave ## Saving plots You can save your `ggplot2`-based figures using `ggsave()`. --- ## `ggsave()` Option 1 By default, `ggsave()` saves the last plot printed to the screen. ```r # Create a simple scatter plot ggplot(data = fun_df, aes(x = x, y = y)) + geom_point() # Save our simple scatter plot ggsave(filename = "simple_scatter.pdf") ``` -- .note[Notes] - This example creates a PDF. Change to `".png"` for PNG, *etc.* - There several helpful, optional arguments: `path`, `width`, `height`, `dpi`. --- ## `ggsave()` Option 2 You can assign your `ggplot()` objects to memory ```r # Create a simple scatter plot named 'gg_points' gg_points <- ggplot(data = fun_df, aes(x = x, y = y)) + geom_point() ``` -- We can then save this figure with the name `gg_points` using `ggsave()` ```r # Save our simple scatter plot name 'ggsave' ggsave( filename = "simple_scatter.pdf", plot = gg_points ) ``` --- layout: false # Resources ## There's always more `ggplot2` 1. .mono[RStudio]'s [cheat sheet for `ggplot2`](https://github.com/rstudio/cheatsheets/blob/master/data-visualization-2.1.pdf). 1. `ggplot2` [reference index](https://ggplot2.tidyverse.org/reference/index.html) 1. The `tidyverse` [page](https://ggplot2.tidyverse.org) on `ggplot2`. 1. Hadley Wickham's on [*Data visualization*](https://r4ds.had.co.nz/data-visualisation.html) in his data science book. --- # Table of contents .pull-left[ ### Default options .smaller[ 1. [`plot()`](#plot) - [Description](#plot) - [Examples](#ex-plot) - [Layering plots](#add) 1. [`hist()`](#hist) ]] .pull-right[ ### ggplot2 .smaller[ 1. [`ggplot2`](#ggplot2) - [Intro](#gg-intro) - [`ggplot()`](#ggplot) - [Layers](#layers) - [Building a plot](#gg-ex) - [Histogram](#gg-hist) - [Density](#gg-density) - [More](#gg-more) - [Saving](#ggsave) 1. [More resources](#resources) ]] --- exclude: true