{"id":864,"date":"2015-07-30T16:36:49","date_gmt":"2015-07-30T23:36:49","guid":{"rendered":"http:\/\/homepages.uc.edu\/~yaozo\/wordpress\/?p=864"},"modified":"2015-07-30T16:36:49","modified_gmt":"2015-07-30T23:36:49","slug":"using-loops-with-ggplot2","status":"publish","type":"post","link":"https:\/\/zhuoyao.net\/index.php\/2015\/07\/30\/using-loops-with-ggplot2\/","title":{"rendered":"Using Loops with ggplot2"},"content":{"rendered":"
http:\/\/reed.edu\/data-at-reed\/resources\/R\/loops_with_ggplot2.html\n\n\nlibrary<\/span>(<\/span>stringr<\/span>)<\/span>\nlibrary<\/span>(<\/span>reshape2<\/span>)<\/span>\nlibrary<\/span>(<\/span>ggplot2<\/span>)<\/span>\nlibrary<\/span>(<\/span>ggthemes<\/span>)<\/span>\nlibrary<\/span>(<\/span>pander<\/span>)<\/span>\n\n# update this file path to point toward appropriate folders on your computer<\/span>\n\n# folder where you want the graphs to be saved:<\/span>\nresults<\/span> <-<\/span> \"\/Users\/majerus\/Desktop\/NJAIS\/results\/\"<\/span>  \n\n# folder where the data is saved:<\/span>\nlabor<\/span> <-<\/span> \"\/Users\/majerus\/Desktop\/NJAIS\/data\/dept_labor\/age_lvl\/\"<\/span>\n\n# create list of all .csv files in folder <\/span>\nfile_list<\/span> <-<\/span> list.files<\/span>(<\/span>path<\/span>=<\/span>labor<\/span>, pattern<\/span>=<\/span>\"*.csv\"<\/span>)<\/span> \n\n# read in each .csv file in file_list and rbind them into a data frame called data.labor <\/span>\ndata.labor<\/span> <-<\/span> \n  do.call<\/span>(<\/span>\"rbind\"<\/span>, \n          lapply<\/span>(<\/span>file_list<\/span>, \n                 function<\/span>(<\/span>x<\/span>)<\/span> \n                   cbind<\/span>(<\/span>year<\/span> =<\/span> as.numeric<\/span>(<\/span>str_sub<\/span>(<\/span>x<\/span>, 1<\/span>, 4<\/span>)<\/span>)<\/span>,\n                         read.csv<\/span>(<\/span>paste<\/span>(<\/span>labor<\/span>, x<\/span>, sep<\/span>=<\/span>''<\/span>)<\/span>, \n                            stringsAsFactors<\/span> =<\/span> FALSE<\/span>)<\/span>)<\/span>)<\/span>)<\/span>\n\n# remove commas from numeric variables<\/span>\ndata.labor<\/span>[<\/span>,c<\/span>(<\/span>3<\/span>:<\/span>12<\/span>)<\/span>]<\/span> <-<\/span> lapply<\/span>(<\/span>\n                          data.labor<\/span>[<\/span>,c<\/span>(<\/span>3<\/span>:<\/span>12<\/span>)<\/span>]<\/span>, \n                          function<\/span>(<\/span>x<\/span>)<\/span> {<\/span>as.numeric<\/span>(<\/span> \n                            gsub<\/span>(<\/span>\",\"<\/span>, \"\"<\/span>, x<\/span>)<\/span>)<\/span>}<\/span>)<\/span>\n\n# drop 2010 from data then data and projections will occur in 5 year intervals <\/span>\ndata.labor<\/span> <-<\/span> subset<\/span>(<\/span>data.labor<\/span>, data.labor<\/span>$<\/span>year<\/span>!=<\/span>2010<\/span>)<\/span>\n\n# rename cols <\/span>\ncolnames<\/span>(<\/span>data.labor<\/span>)<\/span> <-<\/span> c<\/span>(<\/span>\"Year\"<\/span>,   \"County\"<\/span>, \"Total\"<\/span>,  \n                          \"Under 5\"<\/span>,  '5 to 9 years'<\/span>, '10 to 14 years'<\/span>, '15 to 19 years'<\/span>, \n                          \"X20.24\"<\/span>, \"X25.29\"<\/span>, \"X30.34\"<\/span>, \"X35.39\"<\/span>, \"X40.44\"<\/span>)<\/span>\n\n# select columns of interest<\/span>\nkeep<\/span> <-<\/span> c<\/span>(<\/span>\"Year\"<\/span>, \"County\"<\/span>, \"Total\"<\/span>, 'Under 5'<\/span>, \n          '5 to 9 years'<\/span>, '10 to 14 years'<\/span>, '15 to 19 years'<\/span>)<\/span>\n\ndata.labor<\/span> <-<\/span> data.labor<\/span>[<\/span>keep<\/span>]<\/span>\n\n# melt data to long format <\/span>\ndata.labor.long<\/span> <-<\/span> melt<\/span>(<\/span>data.labor<\/span>, id.vars<\/span>=<\/span>c<\/span>(<\/span>\"County\"<\/span>, \"Year\"<\/span>)<\/span>, variable.name<\/span>=<\/span>\"category\"<\/span>)<\/span>\n\n# remove total projections and state level projections from data<\/span>\ndata.labor.long<\/span> <-<\/span> subset<\/span>(<\/span>data.labor.long<\/span>, data.labor.long<\/span>$<\/span>category<\/span>!=<\/span>'Total'<\/span>)<\/span>\ndata.labor.long<\/span> <-<\/span> subset<\/span>(<\/span>data.labor.long<\/span>, data.labor.long<\/span>$<\/span>County<\/span>!=<\/span>'New Jersey'<\/span>)<\/span>\n \n# create graphing function<\/span>\ncounty.graph<\/span> <-<\/span> function<\/span>(<\/span>df<\/span>, na.rm<\/span> =<\/span> TRUE<\/span>, ...<\/span>)<\/span>{<\/span>\n  \n  # create list of counties in data to loop over <\/span>\n  county_list<\/span> <-<\/span> unique<\/span>(<\/span>df<\/span>$<\/span>County<\/span>)<\/span>\n  \n  # create for loop to produce ggplot2 graphs <\/span>\n  for<\/span> (<\/span>i<\/span> in<\/span> seq_along<\/span>(<\/span>county_list<\/span>)<\/span>)<\/span> {<\/span> \n    \n    # create plot for each county in df <\/span>\n    plot<\/span> <-<\/span> \n      ggplot<\/span>(<\/span>subset<\/span>(<\/span>df<\/span>, df<\/span>$<\/span>County<\/span>==<\/span>county_list<\/span>[<\/span>i<\/span>]<\/span>)<\/span>,\n             aes<\/span>(<\/span>Year<\/span>, value<\/span>\/<\/span>1000<\/span>, group<\/span> =<\/span> County<\/span>, colour<\/span> =<\/span> category<\/span>)<\/span>)<\/span> +<\/span> \n      \n      geom_line<\/span>(<\/span>size<\/span>=<\/span>2<\/span>)<\/span> +<\/span>\n      facet_wrap<\/span>(<\/span> ~<\/span>  category<\/span>, ncol<\/span>=<\/span>2<\/span>)<\/span> +<\/span>\n      \n      theme_pander<\/span>(<\/span>)<\/span> +<\/span>\n      theme<\/span>(<\/span>legend.position<\/span>=<\/span>\"none\"<\/span>)<\/span> +<\/span> \n      \n      scale_y_continuous<\/span>(<\/span>\"County Population within Age Categories (thousands)\"<\/span>, \n                         limits<\/span>=<\/span>c<\/span>(<\/span>0<\/span>, max<\/span>(<\/span>df<\/span>$<\/span>value<\/span>[<\/span>df<\/span>$<\/span>County<\/span>==<\/span>county_list<\/span>[<\/span>i<\/span>]<\/span>]<\/span>)<\/span>)<\/span>\/<\/span>1000<\/span>)<\/span> +<\/span>\n      scale_x_continuous<\/span>(<\/span>\"Year\"<\/span>)<\/span> +<\/span>\n      \n      ggtitle<\/span>(<\/span>paste<\/span>(<\/span>county_list<\/span>[<\/span>i<\/span>]<\/span>, ' County, New Jersey \\n'<\/span>, \n                    \"County Population Projection within Age Categories (thousands) \\n\"<\/span>,\n                    sep<\/span>=<\/span>''<\/span>)<\/span>)<\/span>\n    \n    # save plots as .png<\/span>\n    # ggsave(plot, file=paste(results, <\/span>\n    #                        'projection_graphs\/county_graphs\/',<\/span>\n    #                        county_list[i], \".png\", sep=''), scale=2)<\/span>\n   \n    # save plots as .pdf<\/span>\n    # ggsave(plot, file=paste(results, <\/span>\n    #                        'projection_graphs\/county_graphs\/',<\/span>\n    #                        county_list[i], \".pdf\", sep=''), scale=2)<\/span>\n    \n    # print plots to screen<\/span>\n    print<\/span>(<\/span>plot<\/span>)<\/span>\n  }<\/span>\n}<\/span>\n\n# run graphing function on long df<\/span>\ncounty.graph<\/span>(<\/span>data.labor.long<\/span>)\n\n\n\n<\/span><\/code><\/pre>\n
 <\/p>\n","protected":false},"excerpt":{"rendered":"
http:\/\/reed.edu\/data-at-reed\/resources\/R\/loops_with_ggplot2.html library(stringr) library(reshape2) library(ggplot2) library(ggthemes) library(pander) # update this file path to point toward appropriate folders on your computer # folder where you want the… <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-864","post","type-post","status-publish","format-standard","hentry","category-r"],"_links":{"self":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts\/864","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/comments?post=864"}],"version-history":[{"count":0,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts\/864\/revisions"}],"wp:attachment":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/media?parent=864"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/categories?post=864"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/tags?post=864"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}