I would like to subset two dataframes by their columns, whilst retaining the 1st column (containing names), then I want to generate a plot for each subset of the original dataframes. The trick is that they each have one column per month, and I then aggregate those columns to obtain a barplot.
I've generated an example with random data to illustrate my problem:
df1 <- data.frame(name = c("name1","name2","name3","name4"),
month1 = c(5,6,7,8),
month2 = c(10,11,12,13),
month3 = c(15,16,17,18))
df2 <- data.frame(name = c("name1","name2","name3","name4"),
month1 = c(22,23,24,25),
month2 = c(31,34,35,39),
month3 = c(42,43,45,46))
A data.frame: 4 × 4
name month1 month2 month3
<chr> <dbl> <dbl> <dbl>
name1 5 10 15
name2 6 11 16
name3 7 12 17
name4 8 13 18
A data.frame: 4 × 4
name month1 month2 month3
<chr> <dbl> <dbl> <dbl>
name1 22 31 42
name2 23 34 43
name3 24 35 45
name4 25 39 46
So essentially, here I would like to have three subset frames, one for each month column, whilst retaining the name column. This is how I manually achieve this:
month1description1 <- df1 %>%
select("name","month1") %>%
rename("description 1" = "month1")
month1description2 <- df2 %>%
select("name","month1") %>%
rename("description 2" = "month1")
month1plot <- left_join(month1description1, month1description2, by = c("name"))
rm(month1description1,month1description2)
month1plot <- melt(month1plot, id = "name")
name variable value
<chr> <fct> <dbl>
name1 description 1 5
name2 description 1 6
name3 description 1 7
name4 description 1 8
name1 description 2 22
name2 description 2 23
name3 description 2 24
name4 description 2 25
##Plot
month1 <- month1plot %>%
ggplot(aes(x = name, y = value, fill = variable)) +
geom_bar(stat = "identity", position = position_stack()) +
labs(title = "Plot Title",
subtitle = "month 1",
x="",
y="Count") +
scale_fill_viridis_d(name = "", option = "inferno", begin = 0.3, end = 0.7, direction = -1) +
scale_shape_tableau() +
theme_economist() +
theme(plot.background = element_rect(fill = "white"),
plot.title = element_text(hjust = 0.5),
plot.subtitle = element_text(hjust = 0.5),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1),
plot.margin = unit(c(1,1,1,1), "cm"))
month1
I then plot this dataframe, and the color/fill element in ggplot is the variable added by characterizing the content of each original frame (description 1 and description 2).
Generally speaking, this does not represent an inordinate amount of code, and I would be happy keeping it as it is, but when faced with 12+ months in the form of columns, and needing 12+ individual plots, the code seems a little clunky.
Is there a way to at least generate each of the subset dataframes in a more efficient manner than splitting, aggregating and melting each one?
