(This article was first published on

I recently gathered fish harvest data from the U.S. National Oceanic and Atmospheric Administarion (NOAA), which I downloaded from Infochimps. The data is fish harvest by weight and value, by species for 21 years, from 1985 to 2005. Here is a link to a google document of the data I used below: https://spreadsheets.google.com/ccc?key=0Aq6aW8n11tS_dFRySXQzYkppLXFaU2F5aC04d19ZS0E&hl=en**Recology**, and kindly contributed to R-bloggers)

################# Fish harvest data ########################################

setwd("/Mac/R_stuff/Blog_etc/Infochimps/Fishharvest") # Set path

library(ggplot2)

library(googleVis)

library(Hmisc)

fish <- read.csv("fishharvest.csv") # read data

fish2 <- melt(fish,id=1:3,measure=4:24) # melt table

year <- rep(1985:2005, each = 117)

fish2 <- data.frame(fish2,year) # replace year with actual values

# Google visusalization API

fishdata <- data.frame(subset(fish2,fish2$var == "quantity_1000lbs",-4),value_1000dollars=subset(fish2,fish2$var == "value_1000dollars",-4)[,4])

names(fishdata)[4] <- "quantity_1000lbs"

fishharvest <- gvisMotionChart(fishdata, idvar="species", timevar="year")

plot(fishharvest)

Data: fishdata, Chart ID: MotionChart_2011-01-17-08-09-24

R version 2.12.1 (2010-12-16),

Google Terms of Use

fishdatagg2 <- ddply(fish2,.(species,var),summarise,

mean = mean(value),

se = sd(value)/sqrt(length(value))

)

fishdatagg2 <- subset(fishdatagg2,fishdatagg2$var %in% c("quantity_1000lbs","value_1000dollars"))

limit3 <- aes(ymax = mean + se, ymin = mean - se)

bysppfgrid <- ggplot(fishdatagg2,aes(x=reorder(species,rank(mean)),y=mean,colour=species)) + geom_point() + geom_errorbar(limit3) + facet_grid(. ~ var, scales="free") + opts(legend.position="none") + coord_flip() + scale_y_continuous(trans="log")

ggsave("bysppfgrid.jpeg")

To

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