cavedave · July 24, 2022 06:33 · cavedave · Jul 24, 2022
diff --git a/coalandtotal.r b/coalandtotal.r
 library(dplyr)
 library(lubridate)
 library(tidyverse)

 gridwatch <-
  read_csv(
    file = "gridwatch.csv")
    

 #get date int data format
 gridwatch$timestamp<-ymd_hms(gridwatch$timestamp)
 head(gridwatch)

 data<-gridwatch %>% group_by(week=floor_date(gridwatch$timestamp, "week")) %>%
   summarize(amount=sum(coal), rest=sum(demand))
 #make a column with % coal
 data<-data %>%
  mutate(perCoal = (amount/rest)*100)
 data3<-data
 
   #more cleaning up the dataframe
 data3 <- data.frame(amount=data3$amount,
                    rest=data3$rest,
                    perCoal=data3$perCoal,
  date = data3$week,
                 year = as.numeric(format(data3$week, format = "%Y")),
                 month = as.numeric(format(data3$week, format = "%m")),
                 week = as.numeric(format(data3$week, format = "%d")))
 data3$perCoal <- round(data3$perCoal)
 head(data3)

 #first and last weeks are partial messing up things remove them

 dataw<-data3
 dataw = dataw[-1,]
 dataw <- slice(dataw, 1:(n() - 1)) 

 #data source  writes 23 gw as 23401 as current usage
 #so i think get rid of last 3 numerals and tthats the gws


 dataw$rest<-dataw$rest/1000
 dataw$rest<-round(dataw$rest)

 A<-ggplot(data=dataw, aes(x=date, y=rest)) +
  geom_line()
 A <- A + scale_colour_grey()
 plot.title = 'UK Electricity Usage'
 plot.subtitle = 'Gridwatch Data'

 A <- A + ggtitle(bquote(atop(.(plot.title), atop(italic(.(plot.subtitle)), ""))))

 A <- A + scale_y_continuous()  
 A <- A + theme(panel.background = element_blank())


 #put this year at bottom
 #gg<-gg + scale_y_reverse()

 #change title and such
 A <- A + theme(plot.title=element_text(hjust=0.5),legend.position="none")
 #p <- p + theme(axis.text=element_text(size=12))
 A <- A+ theme(plot.title = element_text(size=17))
 #p <- p+ theme(plot.subtitle = element_text(size=10))
 A <- A+ xlab("")
 A <- A+ ylab("Weekly GWatts")
 A <- A + theme(axis.ticks=element_blank())

 A
 ggsave("totalenergy.png", dpi=700)


 #next graph
 p<-ggplot(data=data3, aes(x=date, y=perCoal)) +
  geom_bar(aes(fill = perCoal),stat="identity")+
       scale_fill_gradient(low = "lightgreen", high = "black", na.value = NA)
 p
 p <- p + scale_colour_grey(name="% UK power from Coal")
 plot.title = 'UK Electricity from Coal'
 plot.subtitle = 'Gridwatch Data'

 p <- p + ggtitle(bquote(atop(.(plot.title), atop(italic(.(plot.subtitle)), ""))))
 p <- p + scale_y_continuous(labels = scales::percent_format(scale = 1))

 p

 p <- p + theme(panel.background = element_blank())


 #put this year at bottom
 #gg<-gg + scale_y_reverse()

 #change title and such
 p <- p + theme(plot.title=element_text(hjust=0.5),legend.position="none")
 #p <- p + theme(axis.text=element_text(size=12))
 p <- p+ theme(plot.title = element_text(size=17))
 #p <- p+ theme(plot.subtitle = element_text(size=10))
 p <- p+ xlab("")
 p <- p+ ylab("")
 p <- p + theme(axis.ticks=element_blank())
 p
 ggsave("Barchart2.png", dpi=700)
	library(dplyr)
	library(lubridate)
	library(tidyverse)

	gridwatch <-
	read_csv(
	file = "gridwatch.csv")


	#get date int data format
	gridwatch$timestamp<-ymd_hms(gridwatch$timestamp)
	head(gridwatch)

	data<-gridwatch %>% group_by(week=floor_date(gridwatch$timestamp, "week")) %>%
	summarize(amount=sum(coal), rest=sum(demand))
	#make a column with % coal
	data<-data %>%
	mutate(perCoal = (amount/rest)*100)
	data3<-data

	#more cleaning up the dataframe
	data3 <- data.frame(amount=data3$amount,
	rest=data3$rest,
	perCoal=data3$perCoal,
	date = data3$week,
	year = as.numeric(format(data3$week, format = "%Y")),
	month = as.numeric(format(data3$week, format = "%m")),
	week = as.numeric(format(data3$week, format = "%d")))
	data3$perCoal <- round(data3$perCoal)
	head(data3)

	#first and last weeks are partial messing up things remove them

	dataw<-data3
	dataw = dataw[-1,]
	dataw <- slice(dataw, 1:(n() - 1))

	#data source writes 23 gw as 23401 as current usage
	#so i think get rid of last 3 numerals and tthats the gws


	dataw$rest<-dataw$rest/1000
	dataw$rest<-round(dataw$rest)

	A<-ggplot(data=dataw, aes(x=date, y=rest)) +
	geom_line()
	A <- A + scale_colour_grey()
	plot.title = 'UK Electricity Usage'
	plot.subtitle = 'Gridwatch Data'

	A <- A + ggtitle(bquote(atop(.(plot.title), atop(italic(.(plot.subtitle)), ""))))

	A <- A + scale_y_continuous()
	A <- A + theme(panel.background = element_blank())


	#put this year at bottom
	#gg<-gg + scale_y_reverse()

	#change title and such
	A <- A + theme(plot.title=element_text(hjust=0.5),legend.position="none")
	#p <- p + theme(axis.text=element_text(size=12))
	A <- A+ theme(plot.title = element_text(size=17))
	#p <- p+ theme(plot.subtitle = element_text(size=10))
	A <- A+ xlab("")
	A <- A+ ylab("Weekly GWatts")
	A <- A + theme(axis.ticks=element_blank())

	A
	ggsave("totalenergy.png", dpi=700)


	#next graph
	p<-ggplot(data=data3, aes(x=date, y=perCoal)) +
	geom_bar(aes(fill = perCoal),stat="identity")+
	scale_fill_gradient(low = "lightgreen", high = "black", na.value = NA)
	p
	p <- p + scale_colour_grey(name="% UK power from Coal")
	plot.title = 'UK Electricity from Coal'
	plot.subtitle = 'Gridwatch Data'

	p <- p + ggtitle(bquote(atop(.(plot.title), atop(italic(.(plot.subtitle)), ""))))
	p <- p + scale_y_continuous(labels = scales::percent_format(scale = 1))

	p

	p <- p + theme(panel.background = element_blank())


	#put this year at bottom
	#gg<-gg + scale_y_reverse()

	#change title and such
	p <- p + theme(plot.title=element_text(hjust=0.5),legend.position="none")
	#p <- p + theme(axis.text=element_text(size=12))
	p <- p+ theme(plot.title = element_text(size=17))
	#p <- p+ theme(plot.subtitle = element_text(size=10))
	p <- p+ xlab("")
	p <- p+ ylab("")
	p <- p + theme(axis.ticks=element_blank())
	p
	ggsave("Barchart2.png", dpi=700)