plot_histogram: Generate a histogram.

In bcgov/elucidate: Convenience Functions to Help Researchers Elucidate Patterns in Their Data

Generate a histogram.

Description

Easily generate a histogram of a variable using ggplot2 with a simplified customization interface for common modifications with static (ggplot) and interactive (plotly) output options. The static output is useful for producing static reports (e.g. for manuscripts) and is readily customized further using ggplot2 syntax. The interactive output is helpful for exploring the data and producing dynamic html reports. See this blog post for an introduction to ggplot2.

Usage

plot_histogram(
  data,
  x,
  ...,
  binwidth = NULL,
  bins = 30,
  position = c("identity", "stack", "dodge"),
  stat = c("bin", "count"),
  na.rm = TRUE,
  fill_var = NULL,
  colour_var = NULL,
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  title_hjust = 0.5,
  caption = NULL,
  caption_hjust = 0,
  fill_var_title = NULL,
  colour_var_title = NULL,
  xlim = c(NA, NA),
  xbreaks = ggplot2::waiver(),
  transform_x = FALSE,
  x_transformation = "log10",
  x_var_labs = ggplot2::waiver(),
  fill_var_order = NULL,
  colour_var_order = NULL,
  fill_var_labs = NULL,
  colour_var_labs = NULL,
  fill_var_values = NULL,
  colour_var_values = NULL,
  palette = c("plasma", "C", "magma", "A", "inferno", "B", "viridis", "D", "cividis",
    "E"),
  palette_direction = c("d2l", "l2d"),
  palette_begin = 0,
  palette_end = 1,
  alpha = 0.6,
  greyscale = FALSE,
  line_size = 1.1,
  rug = FALSE,
  rug_colour = "black",
  rug_alpha = 0.8,
  dnorm = FALSE,
  dnorm_colour = "black",
  dnorm_line_type = c("dashed", "solid", "dotted", "dotdash", "longdash", "twodash"),
  dnorm_line_size = 1.1,
  dnorm_alpha = 0.6,
  dnorm_y_axis = TRUE,
  theme = c("bw", "classic", "grey", "light", "dark", "minimal"),
  text_size = 14,
  font = c("sans", "serif", "mono"),
  facet_var = NULL,
  facet_var_order = NULL,
  facet_var_labs = NULL,
  facet_var_strip_position = c("top", "bottom"),
  facet_var_text_bold = TRUE,
  legend_position = c("right", "left", "top", "bottom"),
  omit_legend = FALSE,
  interactive = FALSE,
  aesthetic_options = FALSE
)

Arguments

data	A data frame or tibble containing the dependent measure "x" and any grouping variables.
x	The name of a numeric variable you want a histogram of (quoted or unquoted), e.g. x = "variable" or x = variable.
...	graphical parameters (not associated with variables) to be passed to geom_histogram, e.g. colour or fill, to be applied to all bars. To see some of the available options in a web browser, set the aesthetic_options argument to TRUE.
binwidth	Determines the aggregation level for bin construction in units of x. Default = 1.
bins	Instead of specifying the binsize using binwidth, you can specify a total number of bins to display. If you choose to do so, set binwidth = NULL.
position	Determines how bars are organized when a grouping variable is assigned to fill or colour. Valid options include "identity" (the default),"stack", and "dodge"
stat	Determines how the y-axis is constructed. Typically one would not change this from the default of "bin" for a histogram, although "count" is another sensible option. See stat_bin & stat_count for details.
na.rm	If set to TRUE (the default), missing values will be omitted before plotting.
fill_var	Use if you want to assign a variable to the histogram bar fill colour, e.g. fill_var = "grouping_variable" or fill_var = grouping_variable. Produces separate sets of bars for each level of the fill variable. See aes for details.
colour_var	Use if you want to assign a variable to the histogram bar outline colour, e.g. colour_var = "grouping_variable" or colour_var = grouping_variable. Produces separate sets of bars for each level of the colour variable. See aes for details.
xlab	Specify/overwrite the x-axis label using a character string, e.g. "x-axis label"
ylab	Specify/overwrite the y-axis label using a character string, e.g. "y-axis label"
title	Add a main title to the plot using a character string, e.g. "Distribution of X"
title_hjust	Left-to-right/horizontal justification (alignment) of the main plot title. Accepts values from 0 (far left) to 1 (far right). Default is 0.5 (centre).
caption	Add a figure caption to the bottom of the plot using a character string.
caption_hjust	Left-to-right/horizontal justification (alignment) of the caption. Accepts values from 0 (far left) to 1 (far right). Default is 0 (left).
fill_var_title	If a variable has been assigned to fill using fill_var, this allows you to modify the variable label in the plot legend.
colour_var_title	If a variable has been assigned to colour using colour_var, this allows you to modify the variable label in the plot legend.
xlim	Specify the x-axis limits, e.g. xlim = c(lower_limit, upper_limit). Use NA for the existing minimum or maximum value of x, e.g. the default is xlim = c(NA, NA).
xbreaks	This allows you to change the break points to use for tick marks via a numeric vector. seq is particularly useful here. See scale_x_continuous for details. If xbreaks is specified, then xlim should be also.
transform_x	Would you like to transform the x axis? (TRUE or FALSE)
x_transformation	If transform_x = TRUE, this determines the transformation to be applied. Common choices include "log10" (the default), "log2", "sqrt", or "exp". See scale_continuous for details.
x_var_labs	Allows you to modify the labels displayed with the x-axis tick marks. See scale_x_continuous for details.
fill_var_order	If a variable has been assigned to fill using fill_var, this allows you to modify the order of the variable groups, e.g. fill_var = grouping_variable, fill_var_order = c("group_2", "group_1"). See fct_relevel for details.
colour_var_order	If a variable has been assigned to colour using colour_var, this allows you to modify the order of the variable groups, e.g. colour_var = grouping_variable, fill_var_order = c("group_2", "group_1"). See fct_relevel for details.
fill_var_labs	If a variable has been assigned to fill using fill_var, this allows you to modify the labels of the variable groups, e.g. fill_var = grouping_variable, fill_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
colour_var_labs	If a variable has been assigned to colour using colour_var, this allows you to modify the labels of the variable groups, e.g. colour_var = grouping_variable, colour_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
fill_var_values	If a variable has been assigned to fill using fill_var, this allows you to modify the colours assigned to the fill of each of the variable groups, e.g. fill_var = grouping_variable, fill_var_values = c("blue", "red"). See scale_fill_manual for details. For the colour options available in base R, see colour_options.
colour_var_values	If a variable has been assigned to colour using colour_var, this allows you to modify the colours assigned to the outline of each of the variable groups, e.g. colour_var = grouping_variable, colour_var_values = c("blue", "red"). See scale_fill_manual for details. For the colour options available in base R, see colour_options.
palette	If a variable is assigned to fill_var or colour_var, this determines which viridis colour palette to use. Options include "plasma" or "C" (default), "magma" or "A", "inferno" or "B", "viridis" or "D", and "cividis" or "E". See this link for examples. You can override these colour palettes with fill_var_values or colour_var_values.
palette_direction	Choose "d2l" for dark to light (default) or "l2d" for light to dark.
palette_begin	Value between 0 and 1 that determines where along the full range of the chosen colour palette's spectrum to begin sampling colours. See scale_fill_viridis_d for details.
palette_end	Value between 0 and 1 that determines where along the full range of the chosen colour palette's spectrum to end sampling colours. See scale_fill_viridis_d for details.
alpha	This adjusts the transparency/opacity of the histogram(s), ranging from 0 = 100% transparent to 1 = 100% opaque.
greyscale	Set to TRUE if you want the plot converted to greyscale.
line_size	This modifies the thickness of the histogram bar outlines.
rug	Set this to TRUE to add rug lines to the bottom of the plot.
rug_colour	Determines the colour of the rug lines (if rug = TRUE).
rug_alpha	This adjusts the transparency/opacity of the rug lines (if rug = TRUE) with valid values ranging from 0 = 100% transparent to 1 = 100% opaque.
dnorm	Set this to TRUE to add a normal/Gaussian density curve to the plot. Ignored if x is a date vector or "transform_x" = TRUE.
dnorm_colour	Determines the colour of the normal density curve (if dnorm = TRUE).
dnorm_line_type	The type of line to use to draw the normal density curve (if dnorm = TRUE). Options include "dashed" (default), "solid", "dotted", "dotdash", "longdash", and "twodash".
dnorm_line_size	Adjusts the thickness of the normal density curve (if dnorm = TRUE).
dnorm_alpha	This adjusts the transparency/opacity of the normal density curve (if dnorm = TRUE) with valid values ranging from 0 = 100% transparent to 1 = 100% opaque.
dnorm_y_axis	Set this to FALSE to omit the secondary y-axis that is drawn if dnorm = TRUE to show the scale for the normal density curve.
theme	Adjusts the theme using 1 of 6 predefined "complete" theme templates provided by ggplot2. Currently supported options are: "classic", "bw" (the elucidate default), "grey" (the ggplot2 default), "light", "dark", & "minimal". See theme_bw for more information.
text_size	This controls the size of all plot text. Default = 14.
font	This controls the font of all plot text. Default = "sans" (Arial). Other options include "serif" (Times New Roman) and "mono" (Courier New).
facet_var	Use if you want separate plots for each level of a grouping variable (i.e. a faceted plot), e.g. facet_var = "grouping_variable" or facet_var = grouping_variable. See facet_wrap for details.
facet_var_order	If a variable has been assigned for faceting using facet_var, this allows you to modify the order of the variable groups, e.g. facet_var = grouping_variable, facet_var_order = c("group_2", "group_1"). See fct_relevel for details.
facet_var_labs	If a variable has been assigned for faceting using facet_var, this allows you to modify the labels of the variable groups which will appear in the facet strips, e.g. facet_var = grouping_variable, facet_var_labs = c("group_1_new_label" = "group_1_old_label", "group_2_new_label" = "group_2_old_label"). See fct_recode for details.
facet_var_strip_position	If a variable has been assigned for faceting using facet_var, this allows you to modify the position of the facet strip labels. Sensible options include "top" (the default) or "bottom".
facet_var_text_bold	If a variable has been assigned for faceting using facet_var, this allows you to use boldface (TRUE/default or FALSE) for the facet strip label text.
legend_position	This allows you to modify the legend position. Options include "right" (the default), "left", "top", & "bottom".
omit_legend	Set to TRUE if you want to remove/omit the legends.
interactive	Determines whether a static ggplot object or an interactive html plotly object is returned. See ggplotly for details.
aesthetic_options	If set to TRUE, opens a web browser to the tidyverse online aesthetic options vignette.

Value

A ggplot object or plotly object depending on whether static or interactive output was requested.

Author(s)

Craig P. Hutton, [e-mail]

References

Wickham, H. (2016). ggplot2: elegant graphics for data analysis. New York, N.Y.: Springer-Verlag.

See Also

geom_histogram, dnorm, geom_line, ggplotly

Examples

data(mtcars) #load the mtcars data

plot_histogram(mtcars, x = mpg, fill = "blue")


plot_histogram(mtcars, x = mpg, fill = "blue")

plot_histogram(mtcars, x = mpg,
              fill = "blue", colour = "black")

plot_histogram(mtcars, x = mpg,
               colour_var = cyl, fill = "white")

plot_histogram(mtcars, x = mpg,
              fill_var = cyl, position = "identity") #default in elucidate

plot_histogram(mtcars, x = mpg,
              fill_var = cyl, position = "dodge", binwidth = 1)

plot_histogram(mtcars, x = mpg,
               fill_var = cyl, position = "stack") #default in ggplot2

plot_histogram(mtcars, x = mpg,
               fill = "blue", binwidth = 5)

plot_histogram(mtcars, x = mpg,
               fill = "blue", binwidth = NULL, bins = 30) #default in ggplot2

plot_histogram(mtcars, x = mpg,
               fill = "blue", interactive = TRUE)

plot_histogram(mtcars, x = mpg,
               fill_var = cyl, binwidth = 5, interactive = TRUE)

bcgov/elucidate documentation built on Sept. 3, 2022, 7:16 p.m.