Package 'GimmeMyPlot'

Barplot

Description

Display each numerical value separately using a barplot

Usage

plot_bar(
  x = NULL,
  title = NULL,
  width_title = 20,
  colour = c("blue", "gray", "#cd5b45"),
  color_title = "black",
  cex = 1,
  cex_main = cex * 30,
  digits = 0,
  n_max = 100,
  ratio = 5,
  threshold = 2,
  hjust_title = 0
)

Arguments

x	Vector of numerical values visualized on the plot.
title	Character for the title.
width_title	Integer for the maximum length of the title.
colour	Color or vector of colors for the gradient of the bars.
color_title	Color for the title.
cex	Double for the magnification factor for the text relative to the default.
cex_main	Double for the magnification factor for the subtitles relative to the default.
digits	Integer for the number of decimals.
n_max	Integer for the maximum number of bars to show (prioritizing those with the largest value)
ratio	Double for the width scale
threshold	Double for the minimal percentage value before being hidden on the plot.
hjust_title	Double for the horizontal justification of the title (in [0, 1]).

Examples

library(magrittr)

# Default parameters
x <- runif(10, 1, 10) %>%
    set_names(paste("Sample", LETTERS[seq(10)]))
plot_bar(x)

# Advanced parameters
plot_bar(
    x = x,
    title = "Some numerical variable",
    width_title = 30,
    colour = c("yellow", "gray", "red"),
    color_title = "blue",
    cex = 1.2,
    digits = 1,
    n_max = 5,
    ratio = 15,
    hjust_title = 1
)

---

Barplot for categorical variables

Description

Visualize the proportions of multiple categorical variables using a barplot

Usage

plot_bar_mcat(
  x,
  sample_size = NULL,
  title = NULL,
  width_text = 20,
  width_title = width_text,
  colour = c("blue", "gray", "#cd5b45"),
  color_title = "black",
  cex = 10,
  digits = 0,
  collapse = FALSE,
  ratio = 5,
  n_collapse = 5,
  n_max = Inf,
  threshold = 1,
  hjust_title = -0.5,
  hjust_text = -0.1,
  vjust_text = 0.5
)

Arguments

x	Data.frame of character values visualized on the plot.
sample_size	Integer for the sample size of the dataset to calculate percentages (if different from the length of the variable).
title	Character for the title.
width_text	Integer for the maximum length of the subtitle(s).
width_title	Integer for the maximum length of the title.
colour	Color or vector of colors for the violin and boxplot.
color_title	Color for the title.
cex	Double for the magnification factor for the text relative to the default.
digits	Integer for the number of decimals.
collapse	Boolean to merge categories with identical proportions.
ratio	Double for the width scale
n_collapse	Integer for the maximum number of merged categories to show
n_max	Integer for the maximum number of bars to show (prioritizing those with the largest value)
threshold	Double for the minimal percentage value before being hidden on the plot.
hjust_title	Double for the horizontal justification of the title (in [0, 1]).
hjust_text	Double for the horizontal justification of the text (in [0, 1]).
vjust_text	Double for the vertical justification of the text (in [0, 1]).

Value

A ggplot object.

Examples

library(magrittr)
library(RColorBrewer)

# Default parameters
df <- sapply(seq(10), function(x) runif(10) %>% round()) %>% as.data.frame()
colnames(df) <- paste("Level", seq(10))
plot_bar_mcat(df)

# Advanced parameters
plot_bar_mcat(
    df,
    sample_size = 15,
    title = "Some categorical variable",
    width_text = 30,
    width_title = 50,
    colour = brewer.pal(9, "Reds"),
    color_title = "red",
    cex = 8,
    digits = 1,
    collapse = TRUE,
    ratio = 2,
    n_collapse = 3,
    n_max = 4,
    hjust_title = 1
)

---

Plot histogram

Description

Visualize the distribution of single variable using histogram

Usage

plot_histogram(
  x,
  title = NULL,
  width_title = 20,
  color = "red",
  color_title = color,
  color_stats = "black",
  cex = 1,
  cex_axis = 17 * cex,
  cex_main = 21 * cex,
  cex_sub = 15 * cex,
  digits = 0,
  subtitle = TRUE,
  probs = c(0.25, 0.75),
  binwidth = 1.5
)

Arguments

x	Vector of numerical values visualized on the plot
title	Character for the title.
width_title	Integer for the maximum length of the title.
color	Color for the plot
color_title	Color for the title.
color_stats	Color for the median and quantile lines
cex	Double for the magnification factor for the text relative to the default.
cex_axis	Double for the magnification factor for the axis labels relative to the default.
cex_main	Double for the magnification factor for the subtitles relative to the default.
cex_sub	Double for the magnification factor for the main title relative to the default.
digits	Integer for the number of decimals.
subtitle	Boolean to display the subtitle.
probs	Double vector for the probabilities (in [0, 1]).
binwidth	Double for the number of bins

Value

A ggplot object.

Examples

# Default parameters
x <- rnorm(100)
plot_histogram(x)

# Advanced parameters
plot_histogram(
    x,
    title = "Some numerical variable",
    width_title = 15,
    color = "blue",
    color_title = "orange",
    color_stats = "orange",
    cex = 1.2,
    digits = 1,
    binwidth = 0.5
)

---

Piechart

Description

Visualize the proportions of a categorical variable using a piechart

Usage

plot_pie(
  x,
  title = NULL,
  width_text = 5,
  width_title = 20,
  colour = get_colors(),
  digits = 0.1,
  cex = 15,
  cex_main = cex * 1.5,
  hsize = 1.2,
  legend = TRUE,
  sample_size = NULL,
  collapse = FALSE,
  threshold = 5,
  t = -0.5,
  l = -1,
  r = -1,
  b = -1
)

Arguments

x	Vector of character values visualized on the plot.
title	Character for the title.
width_text	Integer for the maximum length of the subtitle(s).
width_title	Integer for the maximum length of the title.
colour	Color or vector of colors for the categories.
digits	Integer for the number of decimals.
cex	Double for the magnification factor for the text relative to the default.
cex_main	Double for the magnification factor for the subtitles relative to the default.
hsize	Double for the size of the central hole in the pie chart (in [1, 2]).
legend	Boolean to toggle the display of the legend.
sample_size	Integer for the sample size of the dataset to calculate percentages (if different from the length of the variable).
collapse	Boolean to merge categories with identical proportions.
threshold	Double for the minimal percentage value before being hidden on the plot.
t, r, b, l	Dimensions of each margin. (To remember order, think trouble).

Value

A ggplot object.

Examples

library(magrittr)
library(RColorBrewer)

# Default parameters
x <- c(rep("A", 5), rep("B", 4))
plot_pie(x)

# Advanced parameters
k <- 10
n <- runif(k, 1, 10) %>% round()
x <- paste("Level", seq(k)) %>%
    mapply(function(x, y) rep(x, y), ., n) %>%
    unlist()
plot_pie(
    x,
    title = "Some categorical variable",
    width_text = 5,
    width_title = 20,
    colour = brewer.pal(9, "Reds"),
    cex = 20,
    digits = 1,
    hsize = 1.5,
    collapse = TRUE,
    b = 3
)

---

Violin plot

Description

Visualize the distribution of single or multiple variables using violin plots, boxplots, and sina plots

Usage

plot_violin(
  x,
  method = "anova",
  method_adjust = "BH",
  title = NULL,
  width_text = 20,
  width_title = 20,
  colour = "red",
  color_title = colour,
  pch_alpha = 1,
  pch_colour = "gray50",
  pch_size = cex,
  cex = 1,
  cex_axis = 17 * cex,
  cex_main = 21 * cex,
  cex_sub = 15 * cex,
  stats = TRUE,
  digits = 0,
  alpha = 0.3,
  coef = 1.5,
  hjust = 0.5,
  lwd = 1,
  probs = c(0.25, 0.75),
  subtitle = FALSE,
  ylab = NULL
)

Arguments

x	Vector or data.frame of numerical values visualized on the plot.
method	Character for the test method ('anova', 'kruskal', or 'wilcox').
method_adjust	Character for the multiple correction test among 'BH', 'BY', 'bonferroni', 'fdr', 'hochberg', 'holm', 'hommel', 'none'
title	Character for the title.
width_text	Integer for the maximum length of the subtitle(s).
width_title	Integer for the maximum length of the title.
colour	Color or vector of colors for the violin and boxplot.
color_title	Color for the title.
pch_alpha	Double for the transparency of the points (ranging from 0 to 1 for maximum opacity).
pch_colour	Color for the sina points.
pch_size	Double for the magnification factor for the points relative to the default.
cex	Double for the magnification factor for the text relative to the default.
cex_axis	Double for the magnification factor for the axis labels relative to the default.
cex_main	Double for the magnification factor for the subtitles relative to the default.
cex_sub	Double for the magnification factor for the main title relative to the default.
stats	Boolean to display the results of statistical tests.
digits	Integer for the number of decimals.
alpha	Double for the transparency of the violin plot (ranging from 0 to 1 for maximum opacity).
coef	Double to multiply the quantiles by.
hjust	Double for the horizontal justification (in [0, 1]).
lwd	Double for the line width.
probs	Double vector for the probabilities (in [0, 1]).
subtitle	Boolean to display the subtitle.
ylab	Character for the title of the Y-axis.

Value

A ggplot object.

Examples

library(RColorBrewer)

# Default parameters
x <- runif(10)
plot_violin(x)

# Advanced parameters
df <- lapply(seq(2), function(x) runif(10))
df <- as.data.frame(df)
df[, 3] <- runif(10, 1, 2)
colnames(df) <- paste0("X", seq(3))
plot_violin(
    df,
    title = "Some numerical variables",
    color_title = brewer.pal(9, "Set1")[5],
    ylab = "Y-values",
    colour = brewer.pal(9, "Set1")[seq(3)],
    method = "kruskal",
    method_adjust = "none",
    cex = 1.2,
    pch_size = 3,
    width_text = 5,
    pch_colour = "gray30",
    pch_alpha = 0.5,
    width_title = 30,
    lwd = 1.25,
    digits = 2
)

---