Iteratively subset dataframes and apply to plot function using R-CodePudding

Given a dataframe df and code to plot its subset sub1 <- df[, c('date', 'price', 'type')] as follows:

df <- structure(list(date = c("2021-10-1", "2021-10-2", "2021-10-3", 
"2021-10-4", "2021-10-5", "2021-10-6", "2021-10-7", "2021-10-8", 
"2021-10-9", "2021-10-10", "2021-10-11", "2021-10-12", "2021-10-13", 
"2021-10-14"), value = c(190.3, 174.9, 163.2, 168.4, 168.6, 
168.2, 163.5, 161.6, 172.9, 166.5, 175.2, 197.7, 212.1, 177.9
), price = c(191.3, 175.9, 164.2, 169.4, 169.6, 169.2, 164.5, 
162.6, 173.9, 167.5, 176.2, 198.7, 213.1, 178.9), quantity = c(192.3, 
176.9, 165.2, 170.4, 170.6, 170.2, 165.5, 163.6, 174.9, 168.5, 
177.2, 199.7, 214.1, 179.9), type = c(1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L)), class = "data.frame", row.names = c(NA, 
-14L))

Code to plot:

df$date <- as.Date(df$date)
df$type <- as.factor(df$type)
df %>% 
  select(date, price, type) %>% 
  mutate(date = as.Date(date)) %>% 
  rename(value = price) %>% 
  ggplot(aes(x=date, y=value, group=type, color = type, fill = type))   
  geom_area(alpha=0.4, position = "identity")  
  theme(
    text = element_text(size=20),
    plot.margin=unit(c(1, 1, 1.5, 1.2), 'cm')
  )  
  scale_y_continuous(breaks = range(df$value),
                 expand = expansion(mult = c(0, 0.1), add = c(1, 0)))  
  scale_x_date(breaks = range(df$date))
ggsave(filename = './{value}.png', device = 'png')

Out:

Now, I hope to iteratively generate multiple sub-dataframes, such as (please note date and type are two common columns):

sub1 <- df[, c('date', 'value', 'type')]
sub2 <- df[, c('date', 'price', 'type')]
sub3 <- df[, c('date', 'quantity', 'type')]
...

and loop all dataframes to plotting code, finally save them one by one using the name of value.png, price.png,...

How could I do that in R? Thanks a lot.

EDIT1:

lapply(c("value", "price", "quantity"), function(variable) {
  png(paste0(variable, ".png"))
  ggplot(aes(x=date, y=value, group=type, color = type, fill = type))   
  geom_area(alpha=0.4, position = "identity")  
  theme(
    text = element_text(size=20),
    plot.margin=unit(c(1, 1, 1.5, 1.2), 'cm')
  )  
  scale_y_continuous(breaks = range(df$value),
                 expand = expansion(mult = c(0, 0.1), add = c(1, 0)))  
  scale_x_date(breaks = range(df$date))
  dev.off()})

CodePudding user response：

I use for loop, it works, welcome to share other solutions:

df$date <- as.Date(df$date)
df$type <- as.factor(df$type)

cols <- c('value', 'price', 'quantity')
for (col in cols){
  p <- df %>% 
  select(date, col, type) %>% 
  mutate(date = as.Date(date)) %>% 
  rename(value = col) %>% 
  ggplot(aes(x=date, y=value, group=type, color = type, fill = type))   
  geom_area(alpha=0.4, position = "identity")  
  theme(
    text = element_text(size=20),
    plot.margin=unit(c(1, 1, 1.5, 1.2), 'cm')
  )  
  scale_y_continuous(breaks = range(df$value),
                 expand = expansion(mult = c(0, 0.1), add = c(1, 0)))  
  scale_x_date(breaks = range(df$date))
  print(p)
}

Out: