R/cor_tables.R
plot_distributions.Rd
Particularly in exploratory data analysis, it can be instructive to see histograms or density charts.
plot_distributions(
data,
var_names = NULL,
plot_type = c("auto", "histogram", "density"),
hist_align_y = FALSE,
plot_theme = NULL
)
A dataframe - if var_names is NULL, all numeric variables in x will be used, otherwise those included in var_names will be selected
A named character vector with new variable names or a tibble as provided by get_rename_tribbles()
If provided, only variables included here will be plotted. Apart from that, this will only determine the names of the list items, so it is most relevant if the output is to be combined with a correlation matrix, e.g., from cor_matrix()
Type of plot that should be produced - histogram
or density
plot. If auto
,
histograms are produced for variables that take fewer than 10 unique values, density plots for others. If a number is provided,
that number is used as the maximum number of unique values for which a histogram is used.
Should histograms use the same y-axis, so that bin heights are comparable? Defaults to FALSE
Additional theme_ commands to be added to each plot
A list of plots
if (FALSE) { # \dontrun{
plot_distributions(mtcars, var_names = c(wt = "Weight", mpg = "Efficiency",
am = "Transmission", gear = "Gears"))
} # }