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Assignment 7 PS 3780 Data Literacy & Visualization, Summer 2022 Due Date: Thursday, July 7, 2022 at 11:59 p.m. Please save your visualizations and answers to these questions as one .pdf �le (use the �save as� function in most word processors). Be sure to include your name, your teammate's name if there is anyone, and the assignment number. Submit the �le to Carmen by the due date. Remember we are looking for professional visualizations so please include a meaningful title as well as axis labels and a legend. Part I: API and World Bank 1. Apply the World Bank API to extract female life expectancy data. Compare the trends of the United States, the European Union, the entire World (this group is included in the data) as well as a fourth country or collection. Write a paragraph to describe the plot you created and explain which fourth option you included and why. Make sure to include axis labels, a title, and a legend for your plot. (2 pts) Some hints: Use WDI() command from WDI package to implement the World Bank API, and set indicator = �SP.DYN.LE00.FE.IN� in the parentheses. You can also truncate data by setting �start = � and �end = �. If using plot( ) , create appropriate subsets and add lines to an initial plot. Set the ylim to ensure that all cases are visible. 2. Repeat the prior question for a World Bank indicator of your choice - please choose one for which there is enough data! Include the same countries / groups as in the previous plot. In addition to describing the plot, make sure you de�ne the indicator you used, with what unit it is measured, and why you chose it. Make sure to include axis labels, a title, and a legend for your plot. (3 pts) Some hints: Use WDIsearch() to look for a particular indicator available from the World Bank API. Most of the plotting code from the �rst part should work as long as you change the appropriate dataset name, variable name, and ylim values. 1 Part 2: Endangered Species Download from the Carmen the endangered_by_state.csv �le. Create and discuss the two visualizations described below. Include copies of the graphs and the code used to create them. Map Create a choropleth map indicating the amount of endangered species of *All* types within each state while changing the default color scheme. Which states have the most endangered species? Is there any geographic clustering? (3 pt) Some hints: What does �All" mean - check the Organism.type variable. How do you want to de�ne colors? Use RColorBrewer. Load the map data using map_data(�state�). Use the scale_fill_distiller( ) option and specify palette = to choose your colorscheme. Boxplot Create a boxplot indicating the count of endangered species of speci�c types across the states. In the one graph, show boxplots for the organism types of Bird, Mammal, Plant, and Reptile. Fill the boxes with di�erent colors. What di�erences and similarities stand out between the species? (2 pt) 2 rec 7-1 - WDI API, Linegraph, Boxplot, Map ############ Better colors #install.packages("RColorBrewer") library(RColorBrewer) display.brewer.all() display.brewer.pal(5, "Blues") brewer.pal.info myclrs <- colorramppalette(c("red",="" "yellow",="" "green"))(5)="" scales::show_col(myclrs)="" #############="" making="" sure="" all="" packages="" are="" loaded="" #install.packages("ggplot2")="" library(ggplot2)="" #install.packages("wdi")="" library(wdi)="" #############="" the="" wdi="" api="" #this="" command="" prints="" the="" data,="" how="" do="" we="" save="" it="" to="" use="" later?="" #wdi(country="all" ,="" indicator="NY.GNS.ICTR.GN.ZS" ,="" start="1980," end="2020)" sample=""><- wdi(country="all" ,="" indicator="ST.INT.RCPT.XP.ZS" ,="" start="1995," end="2019)" #notes="" about="" the="" function:="" ##="" to="" indicate="" a="" particular="" country,="" you="" need="" to="" use="" iso-2="" country="" code="" or="" download="" all="" the="" data="" and="" subset="" after="" ##="" there="" are="" tons="" of="" different="" indicators="" available="" -="" we="" can="" use="" the="" search="" function="" ##="" be="" aware="" that="" for="" many="" indicators="" there="" will="" be="" a="" bunch="" of="" missing="" data,="" so="" choose="" your="" start="" and="" end="" years="" with="" consideration="" #what="" does="" that="" indicator="" mean="" and="" how="" can="" we="" find="" what="" we="" want?="" wdisearch("tourism")="" #wouldn't="" we="" all="" like="" to="" be="" tourists="" right="" now="" wdisearch("gross="" savings")="" #there="" we="" see="" the="" example="" used.="" what="" if="" we="" want="" something="" else?="" #############="" line="" plots="" #="" for="" ggplot()="" function:="" #####="" make="" one="" dataset="" with="" all="" countries="" you="" want="" to="" plot="" #####="" ggplot()="" will="" separate="" the="" countries="" when="" you="" tell="" it="" to="" #####="" ggplot()="" will="" also="" make="" sure="" the="" limits="" are="" appropriate="" subset=""><-sample[sample$country %in%="" c("australia",="" "portugal",="" "thailand",="" "jamaica",="" "egypt,="" arab="" rep."),]="" p=""><- ggplot(data="subset)" p="" +="" geom_line(aes(x="year," y="ST.INT.RCPT.XP.ZS," color="country," lty="country)," lwd="3)" +="" labs(title="Tourism Reliance" ,="" x="Year" ,="" y="Tourism (% GDP)" ,="" color="Country" ,="" lty="Country" )="" p="" +="" geom_line(aes(x="year," y="ST.INT.RCPT.XP.ZS," color="country," lty="country)," lwd="3)" +="" scale_color_brewer(palette="Dark2" )="" +="" labs(title="Tourism Reliance" ,="" x="Year" ,="" y="Tourism (% GDP)" ,="" color="Country" ,="" lty="Country" )="" p="" +="" geom_line(aes(x="year," y="ST.INT.RCPT.XP.ZS," color="country," lty="country)," lwd="3)" +="" scale_color_manual(values="myclrs)" +="" labs(title="Tourism Reliance" ,="" x="Year" ,="" y="Tourism (% GDP)" ,="" color="Country" ,="" lty="Country" )="" ############="" endangered="" species="" setwd("c:/users/dadada135/desktop/ps="" 3780="" -="" data="" literacy/datasets")="" #="" set="" working="" directory="" so="" r="" knows="" where="" to="" look="" for="" files="" #="" customize="" this="" line="" for="" your="" own="" computer="" end=""><- read.csv("endangered_by_state.csv")="" #############="" exploring="" the="" dataset="" summary(end)="" table(end$organism.type)="" birds=""><- end[end$organism.type="" %in%="" c("bird"),]="" #############="" boxplot="" b=""><- ggplot(data="birds)" b="" +="" geom_boxplot(aes(x="Organism.Type," y="Count," fill="Organism.Type))" #############="" choropleth="" map="" #install.packages("maps")="" library(maps)="" map_data("state")="" m=""><- ggplot(data = birds) #### initialize the data #### call geom_map and tell it which map and which variable to plot #### make sure the map fits #### set the color palette #### turn off axes m + geom_map(color="black", aes(map_id = name, fill = count), map = map_data("state")) + expand_limits(x = map_data("state")$long, y = map_data("state")$lat) + scale_fill_distiller(palette = "purd", direction =1) + labs(x="", y= "") + theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.text.y = element_blank(), axis.ticks.y = element_blank()) m + geom_map(color="black", aes(map_id = name, fill = count), map = map_data("state")) + expand_limits(x = map_data("state")$long, y = map_data("state")$lat) + scale_fill_gradient(low = "green", high = "blue") + labs(x="", y= "") + theme(axis.text.x = element_blank(), axis.ticks.x = element_blank(), axis.text.y = element_blank(), axis.ticks.y = element_blank()) assignment 7 ps 3780 data literacy & visualization, summer 2022 due date: thursday, july 7, 2022 at 11:59 p.m. please save your visualizations and answers to these questions as one .pdf �le (use the �save as� function in most word processors). be sure to include your name, your teammate's name if there is anyone, and the assignment number. submit the �le to carmen by the due date. remember we are looking for professional visualizations so please include a meaningful title as well as axis labels and a legend. part i: api and world bank 1. apply the world bank api to extract female life expectancy data. compare the trends of the united states, the european union, the entire world (this group is included in the data) as well as a fourth country or collection. write a paragraph to describe the plot you created and explain which fourth option you included and why. make sure to include axis labels, a title, and a legend for your plot. (2 pts) some hints: use wdi() command from wdi package to implement the world bank api, and set indicator = �sp.dyn.le00.fe.in� in the parentheses. you can also truncate data by setting �start = � and �end = �. if using plot( ) , create appropriate subsets and add lines to an initial plot. set the ylim to ensure that all cases are visible. 2. repeat the prior question for a world bank indicator of your choice - please choose one for which there is enough data! include the same countries / groups as in the previous plot. in addition to describing the plot, make sure you de�ne the indicator you used, with what unit it is measured, and why you chose it. make sure to include axis labels, a title, and a legend for your plot. (3 pts) some hints: use wdisearch() to look for a particular indicator available from the world bank api. most of the plotting code from the �rst part should work as long as you change the appropriate dataset name, variable name, and ylim values. 1 part 2: endangered species download from the carmen the endangered_by_state.csv �le. create and discuss the two visualizations described below. include copies of the graphs and the code used to create them. map create a choropleth map indicating the amount of endangered species of *all* types within each state while changing the default color scheme. which states have the most endangered species? is there any geographic clustering? (3 pt) some hints: what does �all" mean - check the organism.type variable. how do you want to de�ne colors? use rcolorbrewer. load the map data using map_data(�state�). use the scale_fill_distiller( ) option and specify palette = to choose your colorscheme. boxplot create a boxplot indicating the count of endangered species of speci�c types across the states. in the one graph, show boxplots for the organism types of bird, mammal, plant, and reptile. fill the boxes with di�erent colors. what di�erences and similarities stand out between the species? (2 pt) 2 ggplot(data="birds)" ####="" initialize="" the="" data="" ####="" call="" geom_map="" and="" tell="" it="" which="" map="" and="" which="" variable="" to="" plot="" ####="" make="" sure="" the="" map="" fits="" ####="" set="" the="" color="" palette="" ####="" turn="" off="" axes="" m="" +="" geom_map(color="black" ,="" aes(map_id="Name," fill="Count)," map="map_data("state"))" +="" expand_limits(x="map_data("state")$long," y="map_data("state")$lat)" +="" scale_fill_distiller(palette="PuRd" ,="" direction="1)" +="" labs(x="" ,="" y="" )="" +="" theme(axis.text.x="element_blank()," axis.ticks.x="element_blank()," axis.text.y="element_blank()," axis.ticks.y="element_blank())" m="" +="" geom_map(color="black" ,="" aes(map_id="Name," fill="Count)," map="map_data("state"))" +="" expand_limits(x="map_data("state")$long," y="map_data("state")$lat)" +="" scale_fill_gradient(low="green" ,="" high="blue" )="" +="" labs(x="" ,="" y="" )="" +="" theme(axis.text.x="element_blank()," axis.ticks.x="element_blank()," axis.text.y="element_blank()," axis.ticks.y="element_blank())" assignment="" 7="" ps="" 3780="" data="" literacy="" &="" visualization,="" summer="" 2022="" due="" date:="" thursday,="" july="" 7,="" 2022="" at="" 11:59="" p.m.="" please="" save="" your="" visualizations="" and="" answers="" to="" these="" questions="" as="" one="" .pdf="" �le="" (use="" the="" �save="" as�="" function="" in="" most="" word="" processors).="" be="" sure="" to="" include="" your="" name,="" your="" teammate's="" name="" if="" there="" is="" anyone,="" and="" the="" assignment="" number.="" submit="" the="" �le="" to="" carmen="" by="" the="" due="" date.="" remember="" we="" are="" looking="" for="" professional="" visualizations="" so="" please="" include="" a="" meaningful="" title="" as="" well="" as="" axis="" labels="" and="" a="" legend.="" part="" i:="" api="" and="" world="" bank="" 1.="" apply="" the="" world="" bank="" api="" to="" extract="" female="" life="" expectancy="" data.="" compare="" the="" trends="" of="" the="" united="" states,="" the="" european="" union,="" the="" entire="" world="" (this="" group="" is="" included="" in="" the="" data)="" as="" well="" as="" a="" fourth="" country="" or="" collection.="" write="" a="" paragraph="" to="" describe="" the="" plot="" you="" created="" and="" explain="" which="" fourth="" option="" you="" included="" and="" why.="" make="" sure="" to="" include="" axis="" labels,="" a="" title,="" and="" a="" legend="" for="" your="" plot.="" (2="" pts)="" some="" hints:="" ="" use="" wdi()="" command="" from="" wdi="" package="" to="" implement="" the="" world="" bank="" api,="" and="" set="" indicator="�SP.DYN.LE00.FE.IN�" in="" the="" parentheses.="" you="" can="" also="" truncate="" data="" by="" setting="" �start="�" and="" �end="�." ="" if="" using="" plot(="" )="" ,="" create="" appropriate="" subsets="" and="" add="" lines="" to="" an="" initial="" plot.="" set="" the="" ylim="" to="" ensure="" that="" all="" cases="" are="" visible.="" 2.="" repeat="" the="" prior="" question="" for="" a="" world="" bank="" indicator="" of="" your="" choice="" -="" please="" choose="" one="" for="" which="" there="" is="" enough="" data!="" include="" the="" same="" countries="" groups="" as="" in="" the="" previous="" plot.="" in="" addition="" to="" describing="" the="" plot,="" make="" sure="" you="" de�ne="" the="" indicator="" you="" used,="" with="" what="" unit="" it="" is="" measured,="" and="" why="" you="" chose="" it.="" make="" sure="" to="" include="" axis="" labels,="" a="" title,="" and="" a="" legend="" for="" your="" plot.="" (3="" pts)="" some="" hints:="" ="" use="" wdisearch()="" to="" look="" for="" a="" particular="" indicator="" available="" from="" the="" world="" bank="" api.="" ="" most="" of="" the="" plotting="" code="" from="" the="" �rst="" part="" should="" work="" as="" long="" as="" you="" change="" the="" appropriate="" dataset="" name,="" variable="" name,="" and="" ylim="" values.="" 1="" part="" 2:="" endangered="" species="" download="" from="" the="" carmen="" the="" endangered_by_state.csv="" �le.="" create="" and="" discuss="" the="" two="" visualizations="" described="" below.="" include="" copies="" of="" the="" graphs="" and="" the="" code="" used="" to="" create="" them.="" map="" create="" a="" choropleth="" map="" indicating="" the="" amount="" of="" endangered="" species="" of="" *all*="" types="" within="" each="" state="" while="" changing="" the="" default="" color="" scheme.="" which="" states="" have="" the="" most="" endangered="" species?="" is="" there="" any="" geographic="" clustering?="" (3="" pt)="" some="" hints:="" ="" what="" does="" �all"="" mean="" -="" check="" the="" organism.type="" variable.="" ="" how="" do="" you="" want="" to="" de�ne="" colors?="" use="" rcolorbrewer.="" ="" load="" the="" map="" data="" using="" map_data(�state�).="" ="" use="" the="" scale_fill_distiller(="" )="" option="" and="" specify="" palette="to" choose="" your="" colorscheme.="" boxplot="" create="" a="" boxplot="" indicating="" the="" count="" of="" endangered="" species="" of="" speci�c="" types="" across="" the="" states.="" in="" the="" one="" graph,="" show="" boxplots="" for="" the="" organism="" types="" of="" bird,="" mammal,="" plant,="" and="" reptile.="" fill="" the="" boxes="" with="" di�erent="" colors.="" what="" di�erences="" and="" similarities="" stand="" out="" between="" the="" species?="" (2="" pt)="">