This package allows users to quickly create plots to facilitate exploratory data analysis along with providing additional summary statistics about the data such as mean, median, and correlation.


Install the development version from GitHub with:

# install.packages("devtools")

Package Developers

Package Vignette

Go here to see step by step walk through of package functions.

Package Summary



ggplot2 (v3.2.1 or higher) stats (v3.6.1 or higher) tidyr (v1.0.0) Hmise (v4.3 or higher) forecast (v8.11) rlang (v0.4.5) magrittr (v1.5) tibble (v2.1.3) testthat (v2.3.3) readr (v1.3.1) gapminder (v0.3.0)

How this package fits into the R ecosytem

Code Examples

This is a basic example of how to make an exploratory histogram that displays summary statistics about the variable. You can find the details about iris dataset used in this example here: iris

## basic example code

# Produces a ggplot histogram with mean, median and standard deviation indicated on the plot.
gghist(data = iris, variable = Sepal.Length)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Creates a scatterplot and calculates correlation values for two numeric variables

scatter_express(df = iris, xval = Sepal.Width, yval = Sepal.Length)

Plots a time series and its decomposed components

time <- c("1950 Q1", "1950 Q2", "1950 Q3", "1950 Q4", 
           "1951 Q1", "1951 Q2", "1951 Q3", "1951 Q4",
           "1952 Q1", "1952 Q2", "1952 Q3", "1952 Q4")
earnings <- c(0.71, 0.63, 0.82, 0.21, 
              1.21, 1.03, 2.82, 0.51,
              0.79, 0.92, 1.06, 0.41)
 ts_data <- tibble::tibble(time, earnings)
 ts_plot(data = ts_data, col = "earnings", frequency = 4)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#> zoo

This example displays a fourier transform given some simple input data.

my_data = tibble::tibble(time_series =  c(0, 1, 2, 3), signal = c(2, 3, 4, 6))

fourier_transform(data = my_data,
                  time_col = "time_series",
                  data_col = "signal")

UBC-MDS/ggexpress documentation built on March 29, 2020, 9:13 p.m.