Data Analysis for 203 Project
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Data Analysis for 203 Project
Example of Analysis(Fertilizer)
With steps clearly illustrated in the guiding document, we are able to generate the following graphs that ought to be useful.
fert: Main DataSet of fertilizer consumption in KG per hectare of arable land.
g20Fert: DataSet for countries.
“T”: Transposed DataSet
“Pure”: Take out the Characters in the main dataframe.
A little function that eliminates the x before number-name columns
destroyX = function(es) {
f = es
for (col in c ( 1:ncol(f))){
if (startsWith (colnames(f)[col], "X") == TRUE){
colnames(f)[col] <- substr(colnames(f)[col], 2 , 100)
}
}
assign(deparse(substitute(es)), f, inherits = TRUE)
}
G20 Countries Country Code
g20State <- c ( "CAN" , "USA" , "AUS" , "GBR" , "FRA" , "DEU" , "ITA" , "JPN" , "BRA" , "RUS"
, "IND" , "CHN" , "ZAF" , "MEX" , "ARG" , "TUR" , "SAU" , "KOR" , "IDN" , "EUU")
The G20 consists of the G7, BRICS, and 7 other important economic entities, such as Australia, Saudi Arabia, and Rep.Korea.
Import Fertilizer Data
fert <- read .csv ("D://URochester/Course MATH 203 Intro to Math Stat/ProjectDataFile/FertilizerFile .csv") attach(fert)
g20Fert <- subset(fert, Country .Code %in% g20State, select = c (Country .Name:X2020)) detach(fert)
g20PureFert <- subset(g20Fert, select=c (X2000 :X2020))
g20Fert <- destroyX(g20Fert)
g20PureFert <- destroyX(g20PureFert)
Summary of Fertilizer Data for each year
library(stargazer)
##
## Please cite as:
## Hlavac, Marek (2022) . stargazer: Well-Formatted Regression and Summary Statistics Tables .
## R package version 5 .2 .3 . https://CRAN .R-project .org/package=stargazer
stargazer(g20Fert,type="text")
##
## ============================================
## Statistic N Mean St . Dev . Min Max
## --------------------------------------------
## 2000 20 159 .697 114 .156 11 .417 455 .959
## 2001 20 157 .321 110 .493 12 .940 424 .276
## 2002 20 156 .848 111 .543 11 .493 417 .970
## 2003 20 161 .765 111 .603 11 .004 427 .047
## 2004 20 165 .592 115 .577 11 .420 453 .196
## 2005 20 162 .075 119 .577 11 .793 478 .152
## 2006 20 155 .191 99 .196 12 .481 376 .726
## 2007 20 170 .420 110 .468 14 .253 406 .250
## 2008 20 143 .957 95 .007 15 .883 374 .214
## 2009 20 138 .830 95 .601 15 .635 385 .425
## 2010 20 154 .014 102 .862 15 .725 424 .378
## 2011 20 159 .436 105 .657 16 .187 440 .830
## 2012 20 162 .866 108 .068 15 .434 450 .769
## 2013 20 164 .896 106 .919 15 .298 449 .037
## 2014 20 169 .151 112 .641 15 .901 464 .776
## 2015 20 165 .258 108 .949 16 .663 464 .558
## 2016 20 167 .495 106 .353 18 .687 459 .090
## 2017 20 171 .167 105 .848 20 .328 445 .248
## 2018 20 169 .990 105 .230 20 .814 420 .359
## 2019 20 167 .722 100 .657 22 .591 398 .023
##
Boxplot for each Country in 2 decades
i <- 1
Tg20PureFert <- as .data .frame(t(g20PureFert))
colnames(Tg20PureFert) <- g20Fert[,1]
boxplot(Tg20PureFert$China, Tg20PureFert$`United States ` , Tg20PureFert$France,
horizontal = TRUE , xlab = "Fertilizer Usage(kg/ha)" ,
names = c ( "China" , "US" , "France"), main="Distribution of Fertilizer Usage(kg/ha) over 20 decades
Distribution of Fertilizer Usage(kg/ha) over 20 decades
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400
Fertilizer Usage(kg/ha)
Time Series Plots
par (mfrow=c (2 ,2))
a <- c (2000:2020)
i <- 1
while(i < 21){
plot(a,g20PureFert[i,],type= 'l ' ,
main=g20Fert[i,1],xlab="Year" ,ylab="Fertilizer Usage(kg/ha)") i=i+1
}
2023-03-29