This function creates a ggplot2 visualization to show trends in multiple variables over time. It's possible to add vertical lines at significant events. The function now also counts and reports the number of unique participants and observations. It includes options for faceting to avoid overplotting when dealing with multiple variables.
Usage
margot_plot_slope(
data,
y_vars,
event_dates = NULL,
event_names = NULL,
start_date = NULL,
end_date = NULL,
title = NULL,
y_label = NULL,
x_label = NULL,
data_fraction = 1,
seed = NULL,
plot_points = FALSE,
point_alpha = 0.03,
jitter_width = 1,
base_date = as.Date("2009-06-30"),
save_path = NULL,
width = 12,
height = 8,
event_line_color = "darkred",
event_line_alpha = 0.7,
event_line_type = "dashed",
event_line_width = 0.5,
event_label_size = 3,
event_label_color = "darkred",
legend_position = "bottom",
use_title_case = TRUE,
remove_underscores = TRUE,
y_limits = NULL,
color_palette = NULL,
use_facets = TRUE,
facet_scales = "free_y",
facet_ncol = NULL,
facet_nrow = NULL
)Arguments
- data
A data frame containing the variables to be plotted.
- y_vars
A list of variable names or a single variable name to be plotted on the y-axis.
- event_dates
An optional vector of dates representing the events.
- event_names
An optional vector of names for the events. If NULL, events will be labeled "Event 1", "Event 2", etc.
- start_date
An optional start date for the x-axis.
- end_date
An optional end date for the x-axis.
- title
An optional title for the plot. If NULL, an automatic title will be generated including the count of participants and observations.
- y_label
An optional label for the y-axis.
- x_label
An optional label for the x-axis.
- data_fraction
The fraction of data to use. Default is 1 (use all data).
- seed
An optional seed for reproducibility when sampling data.
- plot_points
Logical, whether to plot individual data points. Default is FALSE.
- point_alpha
The alpha (transparency) of the data points. Default is 0.03.
- jitter_width
The width of the jitter for the data points. Default is 1.
- base_date
The base date for the timeline. Default is "2009-06-30".
- save_path
An optional path to save the plot.
- width
The width of the saved plot in inches. Default is 12.
- height
The height of the saved plot in inches. Default is 8.
- event_line_color
The color of the event lines. Default is "darkred".
- event_line_alpha
The alpha of the event lines. Default is 0.7.
- event_line_type
The type of the event lines. Default is "dashed".
- event_line_width
The width of the event lines. Default is 0.5.
- event_label_size
The size of the event labels. Default is 3.
- event_label_color
The color of the event labels. Default is "darkred".
- legend_position
The position of the legend. Default is "bottom".
- use_title_case
Logical, whether to use title case for labels. Default is TRUE.
- remove_underscores
Logical, whether to remove underscores from labels. Default is TRUE.
- y_limits
An optional vector of two numbers specifying the y-axis limits.
- color_palette
An optional custom color palette. If NULL, a default palette will be used.
- use_facets
Logical, whether to use faceting for multiple variables. Default is TRUE.
- facet_scales
The scales parameter for facet_wrap. Default is "free_y".
- facet_ncol
The number of columns for facet_wrap. Default is NULL.
- facet_nrow
The number of rows for facet_wrap. Default is NULL.
Examples
if (FALSE) { # \dontrun{
library(dplyr)
library(ggplot2)
library(tidyr)
library(here)
# Basic usage with a single variable
single_var_plot <- margot_plot_slope(
data = dat,
y_vars = "warm_muslims",
start_date = "2012-06-06",
y_label = "Warmth",
x_label = "NZAVS Time 4 - 14 Cohort (2012-2023)"
)
# Multiple variables with events and custom y-axis limits
multi_var_plot <- margot_plot_slope(
data = dat,
y_vars = list("warm_muslims", "warm_immigrants"),
event_dates = c("2019-03-15", "2021-01-01"),
event_names = c("Christchurch Attack", "COVID-19 Lockdown"),
start_date = "2012-06-06",
y_label = "Warmth",
x_label = "NZAVS Time 4 - 14 Cohort (2012-2023)",
y_limits = c(1, 7),
use_facets = TRUE
)
# Plot with points, using a subset of data and custom facet layout
point_plot <- margot_plot_slope(
data = dat,
y_vars = list("warm_asians", "warm_pacific", "warm_immigrants"),
plot_points = TRUE,
point_alpha = 0.05,
data_fraction = 0.1,
seed = 123,
y_label = "Warmth",
use_facets = TRUE,
facet_ncol = 2
)
# Save the plot
saved_plot <- margot_plot_slope(
data = dat,
y_vars = list("political_orientation", "social_dominance_orientation"),
save_path = here::here("outputs", "plots"),
width = 10,
height = 6,
use_facets = TRUE
)
# Custom styling and color palette
custom_plot <- margot_plot_slope(
data = dat,
y_vars = list("sat_government", "sat_nz_econ_conditions"),
event_dates = "2017-10-26",
event_names = "2017 Election",
y_label = "Satisfaction Level (0-10)",
y_limits = c(0, 10),
event_line_color = "blue",
event_label_color = "blue",
legend_position = "top",
color_palette = c("#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd"),
use_facets = TRUE
)
} # }