plot_bars: Plot bar-plots of numerical variables

In konradsemsch/aider: Perform everyday analytical and data science tasks more efficiently

Description

This function creates nicely formatted, standardised bar-plots.

Usage

plot_bars(df, x, y = NULL, y_prop = FALSE, x_type = "num",
  fill = NULL, facet = NULL, binwidth = NULL, position = "stack",
  stat = "count", angle = 0, title = TRUE, subtitle = NULL,
  caption = NULL, lab_x = "Value range", lab_y = "Proportion",
  legend = TRUE, vline = c(NaN), alpha = 1, fct_order = FALSE,
  quantile_low = 0.025, quantile_high = 0.975,
  palette = "cartography", theme_type = "grey")

Arguments

df	A data frame
x	A numeric/ categorical variable for which the bar graph is to be plotted
y	A numeric variable which contains summarised y values, used only with stat ="identity"
y_prop	A logical variable to choose between counts/proportion on y axis, Defaults to FALSE (proportion)
x_type	Character identifier for type of the variable x defined above: "num" for numeric (plots histogram) and "char" for character (plots bar chart). Defauls to "num"
fill	Select an additional grouping variable to be used for plotting. Defaults to NULL
facet	Select an additional faceting variable to create facets. Defaults to NULL
binwidth	Select binwidth, defaults to NULL and let's ggplot select the optimal binwidth
position	Select the position of the barplot from: For numeric variables : "stack" (default), "dodge" or "fill".
stat	Character identifier for whether the data is already grouped ("identity") or if the function needs to aggregate data at the level of x ("count")
angle	Select the rotation angle for the x axis labels. Defaults to 0
title	Should the plot title appear automatically. Defaults to TRUE
subtitle	Text that is displayed on the subtitle. Defaults to NULL
caption	Text that is displayed on the caption. Defaults to NULL
lab_x	Text that is displayed on the x axis. Defaults to "Level"
lab_y	Text that is displayed on the y axis. Defaults to "Value range"
legend	Should the plot legend appear automatically. Defaults to TRUE
vline	Should any horizontal lines be added to the plot. Defaults to c(NaN)
alpha	Select plot fill transparency. Defaults to 1
fct_order	Should the factors be reordered by their frequency? Defaults to FALSE
quantile_low	Select lower percentile for outliers exclusion. Defaults to 2.5%
quantile_high	Select upper percentile for outliers exclusion. Defaults to 97.5%
palette	Select a color palette from colors available in the select_palette function or provide your own as a nammed vector
theme_type	Select a theme type from themes available in the aider_theme function

Examples

data <- recipes::credit_data %>%
 first_to_lower()

df_sum <- data %>%
 group_by(marital) %>%
 summarise(mean_inc = mean(income, na.rm = TRUE))

data %>%
 plot_bars(x = income,
           x_type = "num",
           fill = marital,
           facet = job)
data %>%
 plot_bars(x = income,
           x_type = "num",
           fill = marital,
           facet = job,
           position = "stack",
           binwidth = 50,
           vline = 45,
           angle = 45,
           alpha = .7,
           palette = "berlin")

data %>%
 plot_bars(x = job,
          x_type = "char",
          y_prop = FALSE) # for generating counts

data %>%
 plot_bars(x = job,
          x_type = "char",
          position = "dodge",
          fill = marital,
          facet = status)

data %>%
 plot_bars(x = job,
           x_type = "char",
           y_prop = TRUE,
           position = "fill",
           fill = marital,
           facet = status)  # for generating proportions

df_sum %>%
 plot_bars(x = marital,
           y = mean_inc,
           x_type = "char",
           stat ="identity")

konradsemsch/aider documentation built on May 22, 2019, 2:40 p.m.