Generate a bar plot of missing values for a variable.

Easily generate bar plots of missing value summary statistics 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. To plot bar graphs of raw data, see plot_bar instead. See this blog post for an introduction to ggplot2.

plot_na(
  data,
  x,
  y = c("p_na", "na", "n"),
  ...,
  width = 0.85,
  position = c("dodge", "fill", "stack"),
  dodge_padding = 0.1,
  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,
  ylim = c(NA, NA),
  ybreaks = ggplot2::waiver(),
  transform_y = FALSE,
  y_transformation = "log10",
  y_var_labs = ggplot2::waiver(),
  x_var_order_by_y = NULL,
  x_var_order = NULL,
  fill_var_order_by_y = NULL,
  fill_var_order = NULL,
  colour_var_order_by_y = NULL,
  colour_var_order = NULL,
  x_var_labs = 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 = 0.9,
  alpha = 0.8,
  greyscale = FALSE,
  line_size = 1,
  coord_flip = FALSE,
  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 at least one categorical variable.
x: A variable you want to check for missing values.
y: Measure to plot on the y-axis. One of "p_na" for the proportion of missing values (default), "na" for the count of missing values, or "n" for the count of non-missing values.
...: graphical parameters (not associated with variables) to be passed to geom_bar, 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.
width: Adjusts the width of the bars (default = 0.85).
position: Determines how bars are arranged relative to one another when a grouping variable is assigned to either fill_var or colour_var. The default, "dodge", uses position_dodge2 to arrange bars side-by-side; "stack" places the bars on top of each other; "fill" also stacks bars but additionally converts y-axis from raw "y"-axis values to proportions. N.B. Stacked bars may be harder to interpret.
dodge_padding: If position = "dodge", this controls the gap width between adjacent bars (default = 0.1). To eliminate the gap, set this to 0. To overlay bars use a negative value e.g. -0.5. See position_dodge2 for details.
fill_var: Use if you want to assign a variable to the 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 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. "bar plots of y for each group 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.
ylim: specify the y-axis limits, e.g. ylim = c(lower_limit, upper_limit). Use NA for the existing minimum or maximum value of y, e.g. the default is ylim = c(NA, NA)
ybreaks: This allows you to change the break points to use for tick marks on the y-axis. seq is particularly useful here. See scale_y_continuous for details. If ybreaks is specified, then ylim should be also.
transform_y: Would you like to transform the y axis? (TRUE or FALSE)
y_transformation: If transform_y = TRUE, this determines the transformation to be applied. Common choices include "log10" (the default), "log2", "sqrt", or "exp". See scale_continuous for details.
y_var_labs: Allows you to modify the labels displayed with the y-axis tick marks. See scale_continuous for details.
x_var_order_by_y: If a variable has been assigned to x, this allows you to sort the bars in order of increasing/ascending ("i" or "a") or decreasing ("d") value of y. If no variable is assigned to y, then the sorting occurs based on relative counts (position = "dodge" or position = "stack") or proportions (position = "fill").
x_var_order: If a variable has been assigned to x, this allows you to manually modify the order of the variable groups, e.g. x = grouping_variable, x_var_order = c("group_2", "group_1"). See fct_relevel for details.
fill_var_order_by_y: If a variable has been assigned to fill_var, this allows you to sort the bars in order of increasing/ascending ("i" or "a") or decreasing ("d") value of y. If no variable is assigned to y, then the sorting occurs based on relative counts (position = "dodge" or position = "stack") or proportions (position = "fill").
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_by_y: If a variable has been assigned to colour_var, this allows you to sort the bars in order of increasing/ascending ("i" or "a") or decreasing ("d") value of y. If no variable is assigned to y, then the sorting occurs based on relative counts (position = "dodge" or position = "stack") or proportions (position = "fill").
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.
x_var_labs: If a variable has been assigned to x, this allows you to modify the labels of the variable groups, e.g. x = grouping_variable, x_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_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 graphical components of the plot, ranging from 0 = 100% transparent to 1 = 100% opaque.
greyscale: Set to TRUE if you want the plot converted to greyscale.
line_size: Controls the thickness of the bar outlines.
coord_flip: Flips the x and y axes. See coord_flip for details.
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.

References

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

Author

Craig P. Hutton, Craig.Hutton@gov.bc.ca

Examples


#simulate missing data
na_cars <- recode_errors(mtcars, errors = c(8, 90:100, 2))

#plot the proportion of missing values for the "cyl" variable
plot_na(na_cars, x = cyl)


#plot the count of missing values for the "carb" variable
plot_na(na_cars, carb, y = "na")


#plot the proportion of missing values for "cyl" split by grouping variable "am"
# assigned to the fill aesthetic via the "fill_var" argument
plot_na(na_cars, x = cyl, fill_var = am)