ggformula/lattice Comparison

require(mosaic)   # Load additional packages here 
require(ggformula)

# Some customization.  You can alter or delete as desired (if you know what you are doing).
trellis.par.set(theme = theme.mosaic()) # change default color scheme for lattice
theme_set(theme_bw())                   # change default theme for ggformula
knitr::opts_chunk$set(
  tidy = FALSE,     # display code as typed
  size = "small")   # slightly smaller font for code

Introduction

This document is intended to help users of the mosaic package migrate their lattice package graphics to ggformula. The mosaic package provides a simplified and systematic introduction to the core functionality related to descriptive statistics, visualization, modeling, and simulation-based inference required in first and second courses in statistics. Originally, the mosaic package used lattice graphics but now support is also available for the improved ggformula system. Going forward, ggformula will be the preferred graphics package for Project MOSAIC.

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Histograms

### Histograms (ggformula) wzxhzdk:1 ### Histogram options (ggformula) wzxhzdk:2
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### Histograms (lattice) wzxhzdk:3 ### Histogram options (lattice) wzxhzdk:4

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Density Plots

### Density plots (ggformula) wzxhzdk:5 ### Overlaid density plots (ggformula) wzxhzdk:6
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### Density plots (lattice) wzxhzdk:7 ### Overlaid density plots (lattice) wzxhzdk:8

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### Density over histograms (ggformula) We can use stacked layers to add a density curve based on a maximum likelihood fit or a kernel density estimate (see also `gf_dist()`) wzxhzdk:9
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### Density over histograms (lattice) `mosaic` makes it easy to add a fitted distribution to a histogram. wzxhzdk:10

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Side by side box plots

### Side by side box plots (ggformula) wzxhzdk:11 ### Faceted side by side box plots (ggformula) wzxhzdk:12
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### Side by side plots (lattice) wzxhzdk:13 ### Faceted side by side plots (lattice) wzxhzdk:14

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Scatterplots

### Basic scatterplot (ggformula) wzxhzdk:15 ### Overlaid scatterplot with linear fit (ggformula) wzxhzdk:16 ### Overlaid scatterplot with linear fit (lattice) wzxhzdk:17

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### Faceted scatterplot with smooth fit (ggformula) wzxhzdk:18
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## Faceted scatterplot with smooth fit (lattice) wzxhzdk:19 ## More options for scatterplot with linear fit (lattice) wzxhzdk:20

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Refining graphs

### Log scales (ggformula) wzxhzdk:21 ### Custom Colors (ggformula) wzxhzdk:22
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### Log scales (lattice) wzxhzdk:23 ### Custom Colors (lattice) wzxhzdk:24

Want to explore more?

Within RStudio, after loading the mosaic package, try running the command mplot(ds) where ds is a dataframe. This will open up an interactive visualizer that will output the code to generate the figure (using lattice, ggplot2, or ggformula) when you click on Show Expression.

References

More information about ggformula can be found at https://projectmosaic/github.io/ggformula.

More information regarding Project MOSAIC (Kaplan, Pruim, and Horton) can be found at http://www.mosaic-web.org. Further information regarding the mosaic package can be found at https://projectmosaic.github.io/mosaic and https://journal.r-project.org/archive/2017/RJ-2017-02.

Examples of how to bring multidimensional graphics into day one of an introductory statistics course can be found at http://escholarship.org/uc/item/84v3774z.

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mosaic documentation built on Aug. 11, 2018, 9:04 a.m.