Bar plot function

Plot a bar plot using ggplot2.

bar_plot(
  df,
  x_var,
  fill_var = NULL,
  y_var = NULL,
  style = c("stack", "fill", "dodge")[1],
  group_by_x_var = TRUE,
  y_percent = TRUE,
  percent_accuracy = 1,
  y_lim = NULL,
  y_breaks = 2000,
  x_breaks = NULL,
  y_breaks_end = 1e+05,
  title = NULL,
  subtitle = NULL,
  title_size = 14,
  subtitle_size = 10,
  title_margin = 1,
  y_lab = NULL,
  x_lab = NULL,
  background_color = "moccasin",
  panel_grid_color = "grey",
  panel_grid_size = 0.3,
  contour_line_size = 0.1,
  axis_size = 0.3,
  axis_text_angle = 0,
  text_size = 8,
  fill_colors = c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3", "#FF7F00", "#FFFF33",
    "#A65628", "#F781BF"),
  legend_pos = "bottom",
  legend_labels = ggplot2::waiver(),
  label_breaks = ggplot2::waiver(),
  legend_background = "transparent",
  legend_row = NULL,
  legend_col = NULL
)

Arguments

df	Data frame.
x_var	Variable for x axis, use string name. Recommended that `x_var` is in character in df.
fill_var	Variable for the different colors in bars, use string name. Use NULL if only one color for bars.
y_var	Variable for y axis, if NULL, count is used.
style	3 different styles of bar plots, "stack", "fill", or "dodge". fill requires y_percent TRUE.
group_by_x_var	Only relevant for style dodge. Boolean indicating if percentages should be for x_var or fill_var.
y_percent	If TRUE, y axis is in percent form. Otherwise in count form.
percent_accuracy	Set accuracy for `percent_format`.
y_lim	Limit on y axis.
x_breaks, y_breaks	Length between each break on x/y axis.
y_breaks_end	Break end, default for 100000. Works for all count values below that.
title	Plot title, NULL if no title.
subtitle	Small text under title, NULL if no subtitle.
title_size	Text size of title in pt.
subtitle_size	Text size of subtitle in pt.
title_margin	Distance between subtitle and title in pt. If no subtitle, title_margin 0.5*title_size.
y_lab	Y-axis label, use NULL for no label.
x_lab	X-axis label, use NULL for no label.
background_color	Color of the panel background.
panel_grid_color	Color of the panel grid lines.
panel_grid_size	Size of the panel grid lines in plot, useful to change if large dpi!
contour_line_size	Contour around bars size.
axis_size	Size of the axis lines.
axis_text_angle	Angle of the tick texts, 45 is recommended for many x levels.
text_size	Size of the text in pt.
fill_colors	Color of the different categories in fill_var.
legend_pos	Position of the legend in plot, if c(1,1), c(1,0) etc, legend inside plot.
legend_labels	Label for each legend key.
label_breaks	Order of the legend keys.
legend_background	Color of the legend background.
legend_row	How many rows for the legends.
legend_col	How many columns for the legends.

Value

ggplot object containing bar plot.

Examples


# Style stack
bar_plot(df = ggplot2::diamonds, x_var = 'color',
fill_var = 'cut', y_breaks = 2)
bar_plot(df = ggplot2::diamonds, x_var = 'color',
fill_var = 'cut', y_percent = FALSE, y_breaks = 2000)

# Style stack with y variable included
df <- ggplot2::diamonds %>% dplyr::group_by_('color', 'cut') %>%
  dplyr::summarise(y = dplyr::n())
#> Warning: group_by_() is deprecated. 
#> Please use group_by() instead
#> 
#> The 'programming' vignette or the tidyeval book can help you
#> to program with group_by() : https://tidyeval.tidyverse.org
#> This warning is displayed once per session.
bar_plot(df = df, x_var = 'color',
  fill_var = 'cut', y_var = 'y', y_breaks = 2)

# Style fill
bar_plot(df = ggplot2::diamonds, x_var = 'color', fill_var = 'cut',
y_breaks = 10, style = 'fill')

# Style dodge grouped by x_var (color in this case)
bar_plot(df = ggplot2::diamonds, x_var = 'color', fill_var = 'cut',
style = 'dodge', y_breaks = 10)
bar_plot(df = ggplot2::diamonds, x_var = 'color', fill_var = 'cut',
style = 'dodge', y_percent = FALSE, y_breaks = 2000)

# Style dodge grouped by fill_var (cut in this case)
bar_plot(df = ggplot2::diamonds, x_var = 'color', fill_var = 'cut',
style = 'dodge', group_by_x_var = FALSE, y_breaks = 10)

# Since bar_plot() returns ggplot object, it is possible to add more features
# Here we zoom the plot using coord_cartesian():
df <- dplyr::filter(ggplot2::diamonds, clarity %in% c('SI1', 'SI2', 'VS2'))
bar_plot(df = df, x_var = 'clarity',
style = 'dodge', y_percent = FALSE, y_breaks = 2000) +
  ggplot2::coord_cartesian(ylim = c(8000, 14000))

Arguments

Value

Examples

Contents