README.md

In statech/CommonPlots: Create Commonly Used Plots

CommonPlots

Overview

CommonPlots is a package that allows the user to easily create a wide range of plots commonly used in statistical analysis in ggplot2 style.

Installation

# Install from GitHub:
# install.packages("devtools")
devtools::install_github("statech/CommonPlots")

Usage

Most of the plots supported in CommonPlots can be easily created through one function call. The created plot function can be further customized to meet specific needs with ggplot2 functions.

Barplot

library(CommonPlots)
gg_barplot(mpg, var = 'class', group = 'cyl', add_counts = FALSE)

Gantt Chart

test_df <- data.frame(
    project = rep(paste('Project', 1:10), each = 2),
    time = c(rbind(sample(1:5, 10, replace = TRUE),
                   sample(6:8, 10, replace = TRUE))),
    status = factor(c(rbind(rep('start', 10),
                            c(rep('end', 5), rep('ongoing', 5)))),
                    levels = c('start', 'ongoing', 'end'))
)
gg_gantt_chart(test_df, var = 'project', time = 'time',
               status = 'status', grids = 'y')

Time-profiling graphs

Mean + SE plot

data(koopLME)

# Mean + SE plot
data <- koopLME
data$siblings <- factor(with(data, ifelse(SIBLINGS >= 3, '>= 3', SIBLINGS)),
                        levels = c(0, 1, 2, '>= 3'))
mean_se_plot <- gg_time_profiling(
    data, x = 'TIMETRND', y = 'LOGWAGE', group = 'siblings',
    geoms = c('sumline'), avg_method = 'mean',
    var_method = 'se', x_lab = 'Time trend',
    y_lab = 'Log of hourly wage', group_lab = 'Number of siblings',
    title = 'Mean + SE plot'
)

Boxplot

# Box plot over time
data <- koopLME
data$siblings <- factor(with(data, ifelse(SIBLINGS >= 3, '>= 3', SIBLINGS)),
                        levels = c(0, 1, 2, '>= 3'))
sib_labels <- paste('Number of siblings:', levels(data$siblings))
boxplot_time <- gg_time_profiling(
    data, x = 'TIMETRND', y = 'LOGWAGE', facet_r = 'siblings',
    facet_r_levels = setNames(levels(data$siblings), sib_labels),
    geoms = c('boxplot', 'point'), x_lab = 'Time trend',
    y_lab = 'Log of hourly wage', title = 'Box plot',
    sample_size = FALSE, all_xticks = TRUE
)

Spaghetti plot

# Spaghetti plot
data <- koopLME
data <- with(data, data[PERSONID %in% unique(PERSONID)[1:100], ])
spaghetti_plot <- gg_time_profiling(
    data, x = 'TIMETRND', y = 'LOGWAGE', subject = 'PERSONID',
    geoms = c('line'), x_lab = 'Time trend',
    y_lab = 'Log of hourly wage', title = 'Spaghetti plot',
    subject_show = TRUE
)

Box plot

data <- mpg
data$cyl <- factor(data$cyl)

# boxplot with Student's t-Test performed on engine displacement against year
boxplot_ <- gg_boxplot(
    data, x = 'cyl', y = 'displ', group = 'year', test_func = t.test,
    test_result = c('T test p value:' = 'p.value'),
    x_lab = 'Number of cylinders', y_lab = 'Engine displacement (L)',
    group_lab = 'Year', title = ''
)

Getting help

The help page of CommonPlot package can be accessed by help(package = 'CommonPlots'). Most of the functions are documented and examples are provided to ease learning.

Contact

If you have any questions or encounter any bugs, please contact the author (Feiyang Niu, [e-mail])

statech/CommonPlots documentation built on May 6, 2019, 1:32 a.m.