Rassign4.R



Rassign4.RserioMon Oct 28 06:19:25 2019#Visual Analytics R Assignment 4#Ethan Martin#Set Working Directory#Load Packages#install.packages("tidyverse")require(tidyverse)## Loading required package: tidyverse## Warning: package 'tidyverse' was built under R version 3.5.3## -- Attaching packages --------------------------------------------------------------------------------------------------------------------- tidyverse 1.2.1 --## v ggplot2 3.2.1 v purrr 0.2.5## v tibble 2.1.3 v dplyr 0.8.3## v tidyr 0.8.2 v stringr 1.3.1## v readr 1.1.1 v forcats 0.4.0## Warning: package 'ggplot2' was built under R version 3.5.3## Warning: package 'tibble' was built under R version 3.5.3## Warning: package 'tidyr' was built under R version 3.5.2## Warning: package 'readr' was built under R version 3.5.1## Warning: package 'dplyr' was built under R version 3.5.3## Warning: package 'stringr' was built under R version 3.5.2## -- Conflicts ------------------------------------------------------------------------------------------------------------------------ tidyverse_conflicts() --## x dplyr::filter() masks stats::filter()## x dplyr::lag() masks stats::lag()require(reshape2)## Loading required package: reshape2## Warning: package 'reshape2' was built under R version 3.5.3## ## Attaching package: 'reshape2'## The following object is masked from 'package:tidyr':## ## smithsrequire(plyr)## Loading required package: plyr## Warning: package 'plyr' was built under R version 3.5.1## -------------------------------------------------------------------------## You have loaded plyr after dplyr - this is likely to cause problems.## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:## library(plyr); library(dplyr)## -------------------------------------------------------------------------## ## Attaching package: 'plyr'## The following objects are masked from 'package:dplyr':## ## arrange, count, desc, failwith, id, mutate, rename, summarise,## summarize## The following object is masked from 'package:purrr':## ## compactrequire(scales)## Loading required package: scales## Warning: package 'scales' was built under R version 3.5.2## ## Attaching package: 'scales'## The following object is masked from 'package:purrr':## ## discard## The following object is masked from 'package:readr':## ## col_factorrequire(viridis)## Loading required package: viridis## Warning: package 'viridis' was built under R version 3.5.3## Loading required package: viridisLite## Warning: package 'viridisLite' was built under R version 3.5.2## ## Attaching package: 'viridis'## The following object is masked from 'package:scales':## ## viridis_pal#Get dataNBAstatsAll <- read.csv("Seasons_Stats.csv")#Now we have the stats for every NBA year through 2017#Now I just want the stats from 2017, the most recent year.NBAstats2017 <- filter(NBAstatsAll, Year==2017)#Now we reorder it by PTs scored with the name as the keyNBA2017 <- NBAstats2017 %>% group_by(Player) %>% arrange(desc(PTS)) %>% top_n(50, PTS)NBA2017 <- NBA2017[1:50,-1:-2]NBA2017 <- NBA2017[,-2:-4]NBA2017 <- NBA2017[,-5:-26]NBA2017 <- NBA2017[,-3]NBA2017 <- NBA2017[,-10:-13]NBA2017 <- NBA2017[,c(1,2,3,21,4,5,6,10,11,12,7,8,9,13:20)]NBA2017$Player <- with(NBA2017, reorder(Player, PTS))NBA2017.m <- melt(NBA2017)## Using Player as id variablesNBA2017.m <- ddply(NBA2017.m, .(variable), transform, rescale = rescale(value))heat2 <- ggplot(data=NBA2017.m, aes(x=variable, y=Player)) + geom_tile(aes(fill = rescale), color = "white") + scale_fill_viridis() + labs(title = "NBA per game performance of top 50 scorers 2017")base_size <- 9heat2 + theme_grey(base_size = base_size) + labs(x = "", y = "") + scale_x_discrete(expand = c(0, 0)) + scale_y_discrete(expand = c(0, 0)) + theme(legend.position = "none", axis.ticks = element_blank(), axis.text.x = element_text(size = base_size *0.8, angle = 330, hjust = 0, color = "grey50"))nba <- read.csv(";)nba$Name <- with(nba, reorder(Name, PTS))nba.m <- melt(nba)## Using Name as id variablesnba.m <- ddply(nba.m, .(variable), transform, rescale = rescale(value))heat <- ggplot(data=nba.m, aes(x=variable, y=Name)) + geom_tile(aes(fill = rescale), color = "white") + scale_fill_viridis() + labs(title = "NBA per game performance of top 50 scorers 2008")base_size <- 9heat + theme_grey(base_size = base_size) + labs(x = "", y = "") + scale_x_discrete(expand = c(0, 0)) + scale_y_discrete(expand = c(0, 0)) + theme(legend.position = "none", axis.ticks = element_blank(), axis.text.x = element_text(size = base_size *0.8, angle = 330, hjust = 0, color = "grey50"))require(gridExtra)## Loading required package: gridExtra## Warning: package 'gridExtra' was built under R version 3.5.3## ## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':## ## combinegrid.arrange(heat, heat2, ncol=2) ................
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