(I am newbie in R).
I have created a outer function with 3 inner functions that preprocess data & plot.
Issues I am facing is in using country name dynamically - in passing them on y axis
and also use them inside labs for titles/subtitles
.
Adding snapshot below of problem areas (This is working when I am using static country name)
But when I use country names argument i.e bench_country
like {bench_country}
or !!bench_country
or !!enquo(bench_country)
then it doesn't work.
Adding snapshot below of problem areas (This is not working with argument bench_country
= India)
I have used {}
for other arguments that works but {bench_country}
has been causing issues at most places
Adding Code below to replicate issue:
library(tidyverse)
library(glue)
library(scales)
gapminder <- read.csv("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder-FiveYearData.csv")
gapminder <- gapminder %>% mutate_if(is.character, as.factor)
################ fn_benchmark_country ################
fn_benchmark_country_last <-
function(bench_country = India){
bench_country = enquo(bench_country) # <======================================= enquo used
gapminder_benchmarked_wider <- gapminder %>%
select(country, year, gdpPercap) %>%
pivot_wider(names_from = country, values_from = gdpPercap) %>%
arrange(year) %>%
# map_dbl( ~{.x - India })
mutate(across(-1, ~ . - !!bench_country))
# Reshaping back to Longer
gapminder_benchmarked_longer <- gapminder_benchmarked_wider %>%
pivot_longer(cols = !year, names_to = "country", values_to = "benchmarked")
# Joining tables
gapminder_joined <- left_join(x = gapminder, y = gapminder_benchmarked_longer, by = c("year","country"))
# converting to factor
gapminder_joined$country <- as.factor(gapminder_joined$country)
# gapminder_joined <<- gapminder_joined
# (this pushes it to Global evrn)
return(gapminder_joined)
}
################ ----------------------------- ################
################ fn_year_filter ################
# filtering years
fn_year_filter_last <-
function(gapminder_joined, year_start, year_end){
gapminder_joined %>%
filter(year %in% c(year_start,year_end)) %>%
arrange(country, year) %>%
group_by(country) %>%
mutate(benchmark_diff = benchmarked[2] - benchmarked[1],
max_pop = max(pop)) %>%
ungroup() %>%
arrange(benchmark_diff) %>%
filter(max_pop > 30000000) %>%
mutate(country = droplevels(country)) %>%
select(country, year, continent, benchmarked, benchmark_diff) %>%
# ---
mutate(country = fct_inorder(country)) %>%
group_by(country) %>%
mutate(benchmarked_end = benchmarked[2],
benchmarked_start = benchmarked[1] ) %>%
ungroup()
}
################ ----------------------------- ################
################ fn_create_plot ################
fn_create_plot_last <-
function(df, year_start, year_end, bench_country ){
# plotting
ggplot(df) +
geom_segment(aes(x = benchmarked_start, xend = benchmarked_end,
y = country, yend = country,
col = continent), alpha = 0.5, size = 7) +
geom_point(aes(x = benchmarked, y = country, col = continent), size = 9, alpha = .8) +
geom_text(aes(x = benchmarked_start + 8, y = country,
label = paste(round(benchmarked_start))),
col = "grey50", hjust = "right") +
geom_text(aes(x = benchmarked_end - 4.0, y = country,
label = round(benchmarked_end)),
col = "grey50", hjust = "left") +
# scale_x_continuous(limits = c(20,85)) +
scale_color_brewer(palette = "Pastel2") +
labs(title = glue("Countries GdpPerCap at {year_start} & {year_end})"),
subtitle = "Meaning Difference of gdpPerCap of countries taken wrt India \n(Benchmarked India in blue line) \nFor Countries with pop > 30000000 \n(Chart created by ViSa)",
col = "Continent",
x = glue("GdpPerCap Difference at {year_start} & {year_end} (w.r.t India)") ) +
# Adding benchmark line
geom_vline(xintercept = 0, col = "blue", alpha = 0.3) +
geom_label( label="India- as Benchamrked line", x=8000, y= !!bench_country, # {bench_country}
label.padding = unit(0.35, "lines"), # Rectangle size around label
label.size = 0.15, color = "black") +
# background & theme settings
theme_classic() +
theme(legend.position = "top",
axis.line = element_blank(), # axis.text = element_blank()
axis.ticks = element_blank()
) +
# Adding $ to the axis (from scales lib) <=========================
scale_x_continuous(labels = label_dollar())
}
################ ----------------------------- ################
################ Calling functions ################
fn_run_all_last <-function(bench_country = India, year_start = 1952, year_end = 2007){
year_start = year_start
year_end = year_end
# Function1 for PreProcess Benchmarked Country
gapminder_joined <- fn_benchmark_country_last({{bench_country}})
# Function2 to PreProcess dates & pass df to function3 to plot
Plot_last <- fn_year_filter_last(gapminder_joined, year_start, year_end) %>%
fn_create_plot_last(., year_start, year_end, {{bench_country}})
# Pusing plot object to global
Plot_last <<- Plot_last
# Printing Plot
Plot_last
}
fn_run_all_last(India, 1952, 2007)
To make your code work use
rlang::as_label(enquo(bench_country))
ingeom_label
instead of!!bench_country
or the other options you have tried. Whileenquo
quotes the argumentrlang::as_label
converts the argument or the expression to a string which can then be used as label.With this change I get:
EDIT For reference here is the full code for the plotting function. I also adjusted the code to take make the title and axis label "dynamic". To avoid duplicating code I add new variable at the beginning of the function which I assign the country label as a character: