R Final Project
Tony
8/2/2019
- Data Exploration: This should include summary statistics, means, medians, quartiles, or any other relevant information about the data set. Please include some conclusions in the R Markdown text.
theURL<-"https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/COUNT/fishing.csv"
fishingData<-read.table(file=theURL, header= TRUE, sep=",")
head(fishingData)## X site totabund density meandepth year period sweptarea
## 1 1 1 76 0.002070281 804 1978 1977-1989 36710.00
## 2 2 2 161 0.003519799 808 2001 2000-2002 45741.25
## 3 3 3 39 0.000980515 809 2001 2000-2002 39775.00
## 4 4 4 410 0.008039216 848 1979 1977-1989 51000.00
## 5 5 5 177 0.005933375 853 2002 2000-2002 29831.25
## 6 6 6 695 0.021800501 960 1980 1977-1989 31880.00summary(fishingData)## X site totabund density
## Min. : 1.0 Min. : 1.0 Min. : 2.0 Min. :0.0000148
## 1st Qu.: 37.5 1st Qu.: 37.5 1st Qu.: 55.5 1st Qu.:0.0007757
## Median : 74.0 Median : 74.0 Median : 155.0 Median :0.0026311
## Mean : 74.0 Mean : 74.2 Mean : 216.1 Mean :0.0047137
## 3rd Qu.:110.5 3rd Qu.:110.5 3rd Qu.: 283.5 3rd Qu.:0.0064955
## Max. :147.0 Max. :148.0 Max. :1230.0 Max. :0.0309239
## meandepth year period sweptarea
## Min. : 804 Min. :1977 1977-1989:97 Min. : 7970
## 1st Qu.:1410 1st Qu.:1980 2000-2002:50 1st Qu.: 41400
## Median :1993 Median :1982 Median : 54420
## Mean :2413 Mean :1988 Mean : 64800
## 3rd Qu.:3312 3rd Qu.:2001 3rd Qu.: 79810
## Max. :4865 Max. :2002 Max. :223440nrows<-nrow(fishingData)
ncolumns<-ncol((fishingData))
dfDimensions<-data.frame(cbind(nrows, ncolumns))
dfDimensions## nrows ncolumns
## 1 147 8The means and medians of the variables
means<-sapply(fishingData[, c("density", "meandepth")], mean)
medians<-sapply(fishingData[, c("density", "meandepth")], median)
means_mediansDF<-data.frame(cbind(means, medians))
means_mediansDF## means medians
## density 4.713711e-03 2.631079e-03
## meandepth 2.413088e+03 1.993000e+03The correlation of the variables
cor(fishingData$density, fishingData$meandepth)## [1] -0.58236382.Data wrangling: Please perform some basic transformations. They will need to make sense but could include column renaming, creating a subset of the data, replacing values, or creating new columns with derived data (for example – if it makes sense you could sum two columns together)
head(fishingData)## X site totabund density meandepth year period sweptarea
## 1 1 1 76 0.002070281 804 1978 1977-1989 36710.00
## 2 2 2 161 0.003519799 808 2001 2000-2002 45741.25
## 3 3 3 39 0.000980515 809 2001 2000-2002 39775.00
## 4 4 4 410 0.008039216 848 1979 1977-1989 51000.00
## 5 5 5 177 0.005933375 853 2002 2000-2002 29831.25
## 6 6 6 695 0.021800501 960 1980 1977-1989 31880.00newfishingData<-fishingData[,c("X", "totabund","density", "meandepth", "year", "sweptarea")]
head(newfishingData)## X totabund density meandepth year sweptarea
## 1 1 76 0.002070281 804 1978 36710.00
## 2 2 161 0.003519799 808 2001 45741.25
## 3 3 39 0.000980515 809 2001 39775.00
## 4 4 410 0.008039216 848 1979 51000.00
## 5 5 177 0.005933375 853 2002 29831.25
## 6 6 695 0.021800501 960 1980 31880.00names(newfishingData)[names(newfishingData)=="X"]<-"ID"
names(newfishingData)[names(newfishingData)=="X"]<-"Id"
names(newfishingData)[names(newfishingData)=="totabund"]<-"Total_Fish_Per_Site"
names(newfishingData)[names(newfishingData)=="density"]<-"Density"
names(newfishingData)[names(newfishingData)=="meandepth"]<-"MeanDepth"
names(newfishingData)[names(newfishingData)=="year"]<-"Year"
names(newfishingData)[names(newfishingData)=="sweptarea"]<-"SweptArea"
head(newfishingData)## ID Total_Fish_Per_Site Density MeanDepth Year SweptArea
## 1 1 76 0.002070281 804 1978 36710.00
## 2 2 161 0.003519799 808 2001 45741.25
## 3 3 39 0.000980515 809 2001 39775.00
## 4 4 410 0.008039216 848 1979 51000.00
## 5 5 177 0.005933375 853 2002 29831.25
## 6 6 695 0.021800501 960 1980 31880.00- Graphics: Please make sure to display at least one scatter plot, box plot and histogram. Don’t be limited to this. Please explore the many other options in R packages such as ggplot2.
require(ggplot2)## Loading required package: ggplot2boxplot((newfishingData$Total_Fish_Per_Site))
hist(newfishingData$Total_Fish_Per_Site, main="Total Fish per Site Histogram", xlab="Total Fish per Site")
plot(Total_Fish_Per_Site ~ Year, data=newfishingData, main="Total_Fish_Per_Site Plotted Against Year")
abline(lm(newfishingData$Total_Fish_Per_Site ~ newfishingData$Year))
summary(lm(newfishingData$Total_Fish_Per_Site ~ newfishingData$Year))##
## Call:
## lm(formula = newfishingData$Total_Fish_Per_Site ~ newfishingData$Year)
##
## Residuals:
## Min 1Q Median 3Q Max
## -256.41 -139.17 -51.17 86.16 1080.49
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9484.198 3584.590 2.646 0.00905 **
## newfishingData$Year -4.663 1.803 -2.586 0.01071 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 216.4 on 145 degrees of freedom
## Multiple R-squared: 0.04407, Adjusted R-squared: 0.03748
## F-statistic: 6.685 on 1 and 145 DF, p-value: 0.01071- Meaningful question for analysis: Please state at the beginning a meaningful question for analysis. Use the first three steps and anything else that would be helpful to answer the question you are posing from the data set you chose. Please write a brief conclusion paragraph in R markdown at the end.
Question: Is there a correlation to how certain deep-sea fish populations were affected when commercial fishing began in locations with deeper water than in previous years?
Based on our scatterplot we can tell certain deep-sea fish populations were affected when commercial fishing begin in those locations with deeper water. We see there is a decrease in fish population from the previous years. I believe that some deep-sea fish species up to the commerical fishing zones and get caught, thus reducing their population over the years.
- BONUS – place the original .csv in a github file and have R read from the link. This will be a very useful skill as you progress in your data science education and career.
# url<-"https://raw.githubusercontent.com/Sizzlo/Rdatasets/master/csv/COUNT/fishing.csv"
# fishingdata<-read.csv(url)