From 8c2e16f3e7270eb923720fb715dd7cf44aff1fa2 Mon Sep 17 00:00:00 2001 From: Alex Date: Fri, 2 May 2025 20:19:42 -0600 Subject: [PATCH] Updated graphs --- Data_Analysis.r | 34 +++++++++++++++++----------------- Scripts/Data_Proc_Script.r | 2 +- 2 files changed, 18 insertions(+), 18 deletions(-) diff --git a/Data_Analysis.r b/Data_Analysis.r index 4685dcf..33c7442 100644 --- a/Data_Analysis.r +++ b/Data_Analysis.r @@ -1,17 +1,17 @@ -library(tidyverse) -DATA_PATH <- "./Raw_Output/" -source("Scripts/Data_Proc_Script.r") -DAT <- GET_ALL_DATA(DATA_PATH) - - -COUNTY_DATA <-DAT %>% group_by(Year,Major_Event,County_Name) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) - -STATE_EVENT_DATA <- DAT %>% group_by(Year,Major_Event) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) - -STATE_TYPE_DATA <- DAT %>% group_by(Year,Impact) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) - -ggplot(aes(x=Year,y=Employment,group-Impact,fill=Impact),data=STATE_TYPE_DATA)+geom_bar(stat = "identity") -ggplot(aes(x=Year,y=STATE_TOTAL/10^6,group-Impact,fill=Impact),data=STATE_TYPE_DATA)+geom_bar(stat = "identity") - -ggplot(aes(x=Year,y=Employment,group-Major_Event,fill=Major_Event),data=STATE_EVENT_DATA)+geom_bar(stat = "identity") + scale_fill_discrete(name = "Economic Event") - +library(tidyverse) +DATA_PATH <- "./Raw_Output/" +source("Scripts/Data_Proc_Script.r") +DAT <- GET_ALL_DATA(DATA_PATH) + + +COUNTY_DATA <-DAT %>% group_by(Year,Major_Event,County_Name) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) + +STATE_EVENT_DATA <- DAT %>% group_by(Year,Major_Event) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) + +STATE_TYPE_DATA <- DAT %>% group_by(Year,Impact) %>% summarize(Employment =sum(Employment ),Labor_Income =sum(Labor_Income),Value_Added=sum(Value_Added),Output=sum(Output),Subcounty=sum(Subcounty),Special=sum(Special),County=sum(County),State=sum(State),STATE_TOTAL=sum(STATE_TOTAL),Federal=sum(Federal)) + +ggplot(aes(x=Year,y=Employment,group-Impact,fill=Impact),data=STATE_TYPE_DATA)+geom_bar(stat = "identity") +ggplot(aes(x=Year,y=STATE_TOTAL/10^6,group=Impact,fill=Impact),data=STATE_TYPE_DATA)+geom_bar(stat = "identity")+ylab("Wyoming Taxes (Million USD)") + +ggplot(aes(x=Year,y=Employment,group-Major_Event,fill=Major_Event),data=STATE_EVENT_DATA)+geom_bar(stat = "identity") + scale_fill_discrete(name = "Economic Event") +ggplot(aes(x=Year,y=STATE_TOTAL/10^6,group=Major_Event,fill=Major_Event),data=STATE_EVENT_DATA)+geom_bar(stat = "identity") + scale_fill_discrete(name = "Economic Event")+ylab("Wyoming Taxes (Million USD)") \ No newline at end of file diff --git a/Scripts/Data_Proc_Script.r b/Scripts/Data_Proc_Script.r index bc3e13e..117678d 100644 --- a/Scripts/Data_Proc_Script.r +++ b/Scripts/Data_Proc_Script.r @@ -19,7 +19,7 @@ GET_YEAR_DATA <- function(C_YEAR,DATA_PATH){ DAT[grep('Skid',DAT$Event),"Group"] <- "Skid" DAT[grep('Purchase',DAT$Event),"Group"] <- "Beet Purchase" DAT[grep('Truck',DAT$Event),"Group"] <- "Transportation" - DAT[DAT$Event=="Gas Production (Campbell)","Group"] <- "Gas Produciton" + DAT[DAT$Event=="Gas Production (Campbell)","Group"] <- "Gas Production" DAT[is.na(DAT$Group),"Group"] <- "Processing Facilities" #Remove the direct transportation effects induced by by beet purchases, by adding in a negative impact of rail and truck equal to the direct effect found in the first run. DAT[grep('Adjustment',DAT$Event),"Group"] <- "Beet Purchase"