Create a T-account plot for a balance sheet or income statement using ggplot2 in R

financial_taccount_ggplot

library(tidyverse)
library(scales)

scrapy_stocks <- function(stock){
  if ("rvest" %in% installed.packages()) {
    library(rvest)
  }else{
    install.packages("rvest")
    library(rvest)
  }
  for (i in 1:length(stock)) {
    tryCatch(
      {
        url <- "https://finance.yahoo.com/quote/"
        url <- paste0(url,stock[i],"/financials?p=",stock[i])
        wahis.session <- html_session(url)                                
        p <-    wahis.session %>%
          html_nodes(xpath = '//*[@id="Col1-1-Financials-Proxy"]/section/div[3]/table')%>%
          html_table(fill = TRUE)
        IS <- p[[1]]
        colnames(IS) <- paste(IS[1,])
        IS <- IS[-c(1,5,12,20,25),]
        names_row <- paste(IS[,1])
        IS <- IS[,-1]
        IS <- apply(IS,2,function(x){gsub(",","",x)})
        IS <- as.data.frame(apply(IS,2,as.numeric))
        rownames(IS) <- paste(names_row)
        temp1 <- IS
        url <- "https://finance.yahoo.com/quote/"
        url <- paste0(url,stock[i],"/balance-sheet?p=",stock[i])
        wahis.session <- html_session(url)
        p <-    wahis.session %>%
          html_nodes(xpath = '//*[@id="Col1-1-Financials-Proxy"]/section/div[3]/table')%>%
          html_table(fill = TRUE)
        BS <- p[[1]]
        colnames(BS) <- BS[1,]
        BS <- BS[-c(1,2,17,28),]
        names_row <- BS[,1]
        BS <- BS[,-1] 
        BS <- apply(BS,2,function(x){gsub(",","",x)})
        BS <- as.data.frame(apply(BS,2,as.numeric))
        rownames(BS) <- paste(names_row)
        temp2 <- BS
        url <- "https://finance.yahoo.com/quote/"
        url <- paste0(url,stock[i],"/cash-flow?p=",stock[i])
        wahis.session <- html_session(url)
        p <-    wahis.session %>%
          html_nodes(xpath = '//*[@id="Col1-1-Financials-Proxy"]/section/div[3]/table')%>%
          html_table(fill = TRUE)
        CF <- p[[1]]
        colnames(CF) <- CF[1,]
        CF <- CF[-c(1,3,11,16),]
        names_row <- CF[,1]
        CF <- CF[,-1] 
        CF <- apply(CF,2,function(x){gsub(",","",x)})
        CF <- as.data.frame(apply(CF,2,as.numeric))
        rownames(CF) <- paste(names_row)
        temp3 <- CF
        assign(paste0(stock[i],'.f'),value = list(IS = temp1,BS = temp2,CF = temp3),envir = parent.frame())
        
      },
      error = function(cond){
        message(stock[i], "Give error ",cond)
      }
    )
  }
}

scrapy_stocks("MSFT")
  
AAPL.f$BS %>% rownames_to_column("Position") %>% as_tibble() %>% mutate(stock = "Apple") %>% select(1, USD = 2, stock) %>% 
  bind_rows(MSFT.f$BS %>% rownames_to_column("Position") %>% as_tibble() %>% mutate(stock = "Microsoft") %>% select(1, USD = 2, stock)) %>% 
  filter(Position %in% c("Total Current Assets",
                         "Total Assets",
                         "Total Current Liabilities",
                         "Total Liabilities",
                         "Total Stockholder Equity")) %>% 
  spread(Position, USD) %>% 
  mutate(`Total Fixed Assets` = `Total Assets`-`Total Current Assets`,
         `Total Long-term liabilities` = `Total Liabilities`-`Total Current Liabilities`) %>% 
  select(-`Total Liabilities`, -`Total Assets`) %>% 
  gather(Position, USD, -stock) %>% arrange(stock) %>% 
  mutate(al = case_when(str_detect(Position, "Asset") ~ "assets",
                                   T ~ "liabilities")) -> balancesheets

balancesheets %>% 
  ggplot(aes(x = al, y = USD, fill = Position)) + 
  geom_col(alpha = 0.8, color = "black") +
  geom_text(aes(label = str_c(Position, number(USD/1000, big.mark = "'"), sep = "\n")), position = position_stack(vjust = 0.5), size = 3) +
  geom_text(data = balancesheets %>% group_by(stock, al) %>% summarise(USD = sum(USD)), aes(x = al, y = -10000000, label = number(USD/1000, big.mark = "'"), fill = "green"), size = 3) +
  geom_segment(x = 1.5, y = 0, xend = 1.5, yend = 1000000000000, color = "black", size = 1) +
  scale_x_discrete(position = "top") +
  scale_fill_brewer(palette = "Spectral") +
  facet_wrap(~ stock) +
  labs(title = "Balance Sheets",
       subtitle = "Q3 2018, in million USD",
       y = "",
       x = "") +
  theme_classic() +
  theme(legend.position = "none",
        plot.title = element_text(hjust=0.5),
        plot.subtitle = element_text(hjust=0.5),
        axis.line.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks = element_blank())




AAPL.f$IS %>% rownames_to_column("Position") %>% as_tibble() %>% mutate(stock = "Apple") %>% select(1, USD = 2, stock) %>%
  filter(Position %in% c("Total Revenue",
                         "Cost of Revenue",
                         "Total Operating Expenses",
                         "Total Other Income/Expenses Net",
                         "Income Tax Expense",
                         "Net Income")) %>% 
  spread(Position, USD) %>% 
  mutate(`Operating Expenses` = `Total Operating Expenses`-`Cost of Revenue`) %>% 
  select(-`Total Operating Expenses`) %>% 
  gather(Position, USD, -stock) %>% arrange(stock) %>% 
  mutate(ei = case_when(Position %in% c("Total Revenue", "Total Other Income/Expenses Net") ~ "income",
                        T ~ "expenses")) %>% 
  ggplot(aes(x = ei, y = USD, fill = reorder(Position, USD))) + 
  geom_col(alpha = 0.8, color = "black") +
  geom_text(aes(label = str_c(Position, number(USD/1000, big.mark = "'"), sep = "\n")), position = position_stack(vjust = 0.5), size = 3) +
  geom_segment(x = 1.5, y = 10, xend = 1.5, yend = 1000000000000, color = "black") +
  scale_x_discrete(position = "top") +
  scale_fill_brewer(palette = "Spectral") +
  facet_wrap(~ stock) +
  labs(title = "Apple Inc.'s Income Statement",
       subtitle = "Q3 2018, in million USD",
       y = "",
       x = "") +
  theme_classic() +
  theme(legend.position = "none",
        plot.title = element_text(hjust=0.5),
        plot.subtitle = element_text(hjust=0.5),
        axis.line.y = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks = element_blank())