I am using an online ONS dataset of inflation and trying to chart it, but when plotting it with ggplot the x-axis is not in chronological order. (the order is random)
Here is my code, with the link to the dataset:
install.packages("tidyverse")
library("tidyverse")
install.packages("lubridate")
library("lubridate")
#webscraping the ONS inflation csv file
cpi<-read.csv(url("https://www.ons.gov.uk/generator?format=csv&uri=/economy/inflationandpriceindices/timeseries/d7g7/mm23"))
#removing rows 1 to 7 which contain descriptors, keeping this as a dataframe
cpi<-cpi[-c(1,2,3,4,5,6,7),,drop=FALSE]
#renaming columns as date and inflation
cpi<- cpi %>% rename(date=Title)
cpi<- cpi %>% rename(inflation=CPI.ANNUAL.RATE.00..ALL.ITEMS.2015.100)
#proper title characters for date
cut_cpi$date<- str_to_title(cut_cpi$date)
#subsetting cpi dataset in order to have only the data from the row of 2020 JAN to the last row
cut_cpi<- cpi[(which(cpi$date=="2020 JAN")):nrow(cpi),]
#plotting inflation in a line chart
ggplot(cut_cpi,aes(x=date,y=inflation,group=1,))+geom_line(colour="black")+labs(title="CPI inflation from January 2020") +theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
I think the problem might have to do with dates as that is a character rather than a date. But I cannot turn that into date class.
I tried with this
cut_cpi$date <- as_factor(cut_cpi$date)
cut_cpi$date <- as_date(cut_cpi$date, format='%Y %b')
I tried checking the locale and it is not a problem
> Sys.setlocale("LC_TIME")
[1] "English_United Kingdom.1252"
You had two issues.
1- inflation was stored as character not a number so it couldn't be plotted
2- date was stored as a character, not a date, so it would just be plotted in alphabetical order. It has to be a date so it can be sorted properly, then just format the scale so that it prints the date in the format that you want.
library("tidyverse")
library("lubridate")
#webscraping the ONS inflation csv file
cpi<-read.csv(url("https://www.ons.gov.uk/generator?format=csv&uri=/economy/inflationandpriceindices/timeseries/d7g7/mm23"))
#removing rows 1 to 7 which contain descriptors, keeping this as a dataframe
cpi<-cpi[-c(1,2,3,4,5,6,7),,drop=FALSE]
#renaming columns as date and inflation
cpi<- cpi %>% rename(date=Title)
cpi<- cpi %>% rename(inflation=CPI.ANNUAL.RATE.00..ALL.ITEMS.2015.100)
#proper title characters for date
#THIS FAILS. cut_cpi data.frame hasn't been created yet so this doesn't work. Unnecessary so just remove it.
#cut_cpi$date<- str_to_title(cut_cpi$date)
#subsetting cpi dataset in order to have only the data from the row of 2020 JAN to the last row
cut_cpi<- cpi[(which(cpi$date=="2020 JAN")):nrow(cpi),]
#NEW
cut_cpi<- cut_cpi %>%
mutate(real_date_format= parse_date_time(cut_cpi$date, orders = "%Y %b")) %>%
arrange(desc(real_date_format))
#plotting inflation in a line chart
#NEW
# remove extra comma on aes
# converted inflation to numeric (was character)
# converted real_date_format to date (was datetime). scale_x_date breaks with datetime
ggplot(cut_cpi,aes(x=as_date(real_date_format), y=as.numeric(inflation),group=1))+
geom_line(colour="black")+
labs(title="CPI inflation from January 2020") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1)) +
#NEW
scale_x_date(date_breaks = "1 month", date_labels = "%b %Y")