R/hist_plot.R

In shudengnyc/shutool: Frequntly used functions to explore Omic data sets

hist_plot = function (df, tgt_var, nbreaks = 15, nbin = 30){
  tgt_var = deparse(substitute(tgt_var))
  tgt_var_med = round(median(pull(df, tgt_var), na.rm = TRUE), 3)
  ggplot(df) + 
    geom_histogram(aes(x = get(tgt_var)),color = "black",fill = "white",bins = nbin) + 
    stat_summary(aes(x = 0, y = get(tgt_var), xintercept = stat(y) ), fun = median, geom = "vline", colour = "red", linetype = "twodash") +
    stat_summary(aes(x = 0, y = get(tgt_var), label = paste0("\n \n Mid: ", round(stat(y),2), "%")), 
                 fun = median, geom = "text", colour = "black", fontface='bold', position = position_nudge(x = tgt_var_med, y = Inf)) +
    scale_x_continuous(breaks = scales::pretty_breaks(n = nbreaks)) +
    labs(x = tgt_var, y ="") +
    theme_linedraw() #theme_minimal()
}

#------------------------------ Archieve 
# # df should be long format
# # tgt_var : column name of interest 
# hist_plot = function(df, tgt_var, nbreaks = 15, nbin =  30) {
#   tgt_var = deparse(substitute(tgt_var))
#   tgt_var_med = round(median(pull(df, tgt_var), na.rm = TRUE), 3)
#   ggplot(df) +
#     geom_histogram(aes(x = get(tgt_var)),
#                    color = "black" ,
#                    fill  = "white",
#                    bins  = nbin) +
#     scale_x_continuous(breaks = scales::pretty_breaks(n = nbreaks)) +
#     geom_vline(xintercept = tgt_var_med,
#                colour     = "red",
#                linetype   = "twodash") +
#     annotate("text",
#               label = paste0(" \n \n Median : ", tgt_var_med),
#               x = tgt_var_med,
#               y = Inf
#               ) +
#     labs(x = tgt_var) +
#     theme_bw()
# }
# 
# 
# # hist_plot(mtcars,mpg, 10)
# # ... %>% hist_plot(., Columname)
# 
# 
#