getCountryGWPv.Rmd

---
title: "getCountryGWPv"
author: "GeoffRussell"
date: "2023-11-25"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(readxl)
```

## Data 

```{r}
dfc <- read_xlsx("Statistical_Review_of_World_Energy_2023.xlsx",sheet="Solar Capacity",skip=2) 
lookup<-c(
  'Megawatts'='...1',
  '2000'='...6',
  '2001'='...7',
  '2002'='...8',
  '2003'='...9',
  '2004'='...10',
  '2005'='...11',
  '2006'='...12',
  '2007'='...13',
  '2008'='...14',
  '2009'='...15',
  '2010'='...16',
  '2011'='...17',
  '2012'='...18',
  '2013'='...19',
  '2014'='...20',
  '2015'='...21',
  '2016'='...22',
  '2017'='...23',
  '2018'='...24',
  '2019'='...25',
  '2020'='...26',
  '2021'='...27',
  '2022'='...28'
  )
dfcr<-dfc %>% rename(all_of(lookup))
getCountry<-function(c) {
  dfcr %>% filter(`Megawatts` %in% c) %>% mutate("Country"=`Megawatts`)  
}

dfcountries<-getCountry(c("Total World","US","China","Australia","Japan","Sweden","United Arab Emirates","Ukraine","Turkey","Switzerland","France","Netherlands","Canada","Italy","Germany","UK","Total Europe")) %>% select(Country,`2005`:`2022`) %>%
  pivot_longer(cols=`2005`:`2022`,names_to="Year",values_to="MW") %>%
  mutate(GW=`MW`/1000)

write_csv(dfcountries,"GWByCountry.csv")

```