Skip to contents

Plot an hv_eda object

Source: R/eda-plots.R
plot.hv_eda.Rd

Draws an exploratory data analysis plot for the variable stored in the hv_eda object. Variable type (stored in x$meta$var_type) determines the chart:

Usage

# S3 method for class 'hv_eda'
plot(
  x,
  smooth_method = "loess",
  smooth_span = 0.8,
  smooth_se = FALSE,
  loess_cutoff = 10,
  group_bars = FALSE,
  alpha = 0.4,
  ...
)

Arguments

x

An hv_eda object.

smooth_method

Smoothing method for continuous plots, passed to geom_smooth. Default "loess".

smooth_span

LOESS span. Default 0.8.

smooth_se

Logical; show confidence ribbon around smooth? Default FALSE.

loess_cutoff

Integer, if the y-variable has less unique values than this, the smooth line will not be plotted. Default 10.

group_bars

Logical; Plot as grouped bars instead of stacked? Default FALSE.

alpha

Point transparency for continuous plots. Default 0.4.

...

Ignored; present for S3 consistency.

Value

A bare ggplot object.

Details

Continuous ("Cont")

Scatter plot with a LOESS smoother overlay and a rug on the x-axis for rows where the outcome is missing.

Numeric categorical ("Cat_Num")

Stacked (or filled) bar chart with counts (or proportions) per x level.

Character categorical ("Cat_Char")

Same stacked bar, coloring each string level separately.

See also

hv_eda, theme_hv_manuscript

Examples

dta <- sample_eda_data(n = 300, seed = 42)

# --- Ordinal categorical: percentage barplot ------------------------------
plot(hv_eda(dta, x_col = "year", y_col = "nyha",
              y_label = "Preoperative NYHA Class")) +
  ggplot2::scale_fill_brewer(
    palette = "RdYlGn", direction = -1,
    labels  = c("1" = "I", "2" = "II", "3" = "III", "4" = "IV",
                "(Missing)" = "Missing"),
    name    = "NYHA"
  ) +
  ggplot2::scale_x_discrete(breaks = seq(2005, 2020, 5)) +
  ggplot2::labs(x = "Surgery Year", y = "Count") +
  theme_hv_poster()


# --- Continuous: annotated -----------------------------------------------
plot(hv_eda(dta, x_col = "op_years", y_col = "peak_grad",
              y_label = "Peak Gradient (mmHg)")) +
  ggplot2::scale_color_manual(values = c("steelblue"), guide = "none") +
  ggplot2::scale_x_continuous(breaks = seq(0, 15, 5)) +
  ggplot2::labs(x = "Years from First Surgery Year") +
  ggplot2::annotate("text", x = 12, y = 70,
                    label = "LOESS span = 0.8",
                    size = 3, color = "gray40", fontface = "italic") +
  theme_hv_poster()