lemon

πŸ‹ Lemon --- Freshing up your ggplots

https://github.com/stefanedwards/lemon

Science Score: 36.0%

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Keywords

axis-lines facets ggplot-extension ggplot2 knitr legend ticks visualization
Last synced: 6 months ago · JSON representation

Repository

πŸ‹ Lemon --- Freshing up your ggplots

Basic Info
Statistics
  • Stars: 194
  • Watchers: 7
  • Forks: 14
  • Open Issues: 6
  • Releases: 6
Topics
axis-lines facets ggplot-extension ggplot2 knitr legend ticks visualization
Created almost 9 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog License

README.Rmd

---
output: github_document
---


```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README/",
  cache.path = "README/cache/",
  cache = TRUE,
  autodep=TRUE,
  cache.rebuild = TRUE
)
```

# Lemon --- Freshing up your ggplots

[![CRAN\_Status\_Badge](https://www.r-pkg.org/badges/version/lemon)](https://cran.r-project.org/package=lemon)
![downloads](http://cranlogs.r-pkg.org/badges/grand-total/lemon)

  [![R-CMD-check](https://github.com/stefanedwards/lemon/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/stefanedwards/lemon/actions/workflows/R-CMD-check.yaml)
  

Just another [ggplot2](http://ggplot2.tidyverse.org) and 
[knitr](https://yihui.name/knitr/) extension package.

This package contains functions primarily in these domains of ggplot2:

```{r domain_axis_lines,include=FALSE,fig.height=0.5,fig.width=0.5}
library(ggplot2)
library(lemon)
ggplot(mtcars, aes(x=cyl, y=mpg)) + 
  geom_point(size=0.1) + 
  coord_capped_cart(bottom=brackets_horisontal(), left='both') +
  theme_light() + 
  theme(panel.border=element_blank(), axis.line = element_line(),
        axis.title=element_blank(), axis.text=element_blank(),
        panel.grid=element_blank(), axis.ticks.x = element_line(colour='black'))
```
```{r domain_facets,include=FALSE,fig.height=0.5, fig.width=0.5}
ggplot(mtcars, aes(x=cyl, y=mpg)) + 
  geom_point(size=0.1) + 
  coord_capped_cart(bottom='both', left='both') +
  facet_rep_wrap(~carb) +
  theme_light() + 
  theme(panel.border=element_blank(), axis.line = element_line(),
        axis.title=element_blank(), axis.text=element_blank(),
        panel.grid=element_blank(), axis.ticks = element_blank(), 
        axis.ticks.length = unit(0, 'npc'), panel.spacing=unit(1, 'mm'),
        strip.background=element_blank(), strip.text=element_blank())
```
```{r domain_pointline,include=FALSE,fig.height=0.5,fig.width=0.5}
ggplot(data.frame(x=1:3, y=c(1,2.4,3.5)), aes(x, y)) +
  geom_pointline(size=0.5) +
  coord_capped_cart(xlim=c(0,4), bottom='both', left='both') +
  theme_light() + 
  theme(panel.border=element_blank(), axis.line = element_line(),
        axis.title=element_blank(), axis.text=element_blank(),
        panel.grid=element_blank(), axis.ticks.x = element_line(colour='black'))
```

-   ![Axis lines miniature](README/domain_axis_lines-1.png) Axis lines.
-   ![Facets miniature](README/domain_facets-1.png) Repeated axis lines on facets.
-   ![geom_pointline](README/domain_pointline-1.png) `geom_pointpath` and `geom_pointline`.
-   Legends

As well as some functions in knitr.

## Installation

```{r, eval = FALSE}
# install.packages("devtools")

# Install release from GitHub:
devtools::install_github("stefanedwards/lemon", ref='v0.4.7')

# Or get the lastest development version from GitHub:
devtools::install_github("stefanedwards/lemon")
```



## Axis lines

We can display a limit on the axes range.
```{r usage1}
library(lemon)
ggplot(mtcars, aes(x=cyl, y=mpg)) + 
  geom_point() + 
  coord_capped_cart(bottom='both', left='none') +
  theme_light() + theme(panel.border=element_blank(), axis.line = element_line())
```

**NB**: Disable `panel.border` and enable `axis.line` in `theme`, otherwise you will not see an effect!

We could also show that the x-axis is categorical (or ordinal):
```{r brackets_demo}
(p <- ggplot(mtcars, aes(x=as.factor(cyl), y=mpg)) + 
  geom_point(position=position_jitter(width=0.1)) + 
  coord_flex_cart(bottom=brackets_horisontal(), left=capped_vertical('both')) +
  theme_light() + theme(panel.border=element_blank(), axis.line = element_line())
)
```

When capping the axis lines, they are never capped further inwards than the ticks!
Look up

* `coord_capped_cart`, `coord_capped_flip`
* `coord_flex_cart`, `coord_flex_flip`, `coord_flex_fixed`
* `brackets_horisontal`, `brackets_vertical`
* `capped_horisontal`, `capped_vertical`

## Facets 

Having produced such wonderous axes, it is a pity they are not plotted around 
all panels when using faceting. 
We have extended both `facet_grid` and `facet_wrap` to produce axis, ticks, and 
labels on _all_ panels:

```{r facets}
p + facet_rep_wrap(~gear, ncol=2, label=label_both)
```

They work just like the normal ones; look up `facet_rep_grid` and `facet_rep_wrap`.

## `geom_pointline`

A geom that combines both points and lines. 
While possible by using both `geom_point` and `geom_line`, position adjustments
are not preserved between the two layers.
`geom_pointline` and `geom_pointpath` combines `geom_point` with 
`geom_line` and `geom_path`, respectively, while preserving position adjustments.


```{r geom_pointline_demo,echo=FALSE}
library(grid)
library(gtable)

p <- ggplot(mtcars, aes(wt, mpg, colour=factor(cyl))) + 
  geom_point(col='grey') +
  theme_light() + theme(panel.border=element_blank(), axis.line = element_line()) +
  theme(legend.position='hidden', plot.title = element_text(size=rel(0.8)))

p1 <- p + geom_point(position=position_jitter(0.1, 0.1)) + geom_line(position=position_jitter(0.1, 0.1)) +
  labs(title='geom_point(position=position_jitter(0.1, 0.1)) + \ngeom_line(position=position_jitter(0.1, 0.1))')
p2 <- p + geom_pointline(position=position_jitter(0.1, 0.1)) +
  labs(title='geom_pointline(position=position_jitter(0.1, 0.1))')

g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
grid.newpage()
grid.draw(cbind(g1, g2, size = 'first'))
```
Left: `geom_point` and `geom_line` as two separate geoms. 
Right: The two geoms combined into `geom_pointline`. 
Both produced with `ggplot(mtcars, aes(wt, mpg, colour=factor(cyl))) + geom_point(col='grey')`, where the grey points indicate the true location of the datapoint.

An added visual effect is seen as the lines do not touch the points, leaving a 
small gap (set by argument `distance`).

## Legends

Reposition the legend onto the plot. Exactly where you want it:
```{r reposition_legend}
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
d <- ggplot(dsamp, aes(carat, price)) +
  geom_point(aes(colour = clarity))
reposition_legend(d, 'top left')
```
The legend repositioned onto the top left corner of the panel.

Scavenging the Internet, we have found some functions that help work with 
legends.

Frequently appearing on [Stack Overflow](https://stackoverflow.com), we bring 
you `g_legend`:
```{r g_legend,fig.height=3,fig.width=2}
library(grid)
legend <- g_legend(d)
grid.newpage()
grid.draw(legend)
```
The legend grob, by itself.


Originally brought to you by
  (Baptiste AuguiΓ©)[http://baptiste.github.io/]
  ()
  and 
  (Shaun Jackman)[http://rpubs.com/sjackman]
  ().
We put it in a package.

```{r grid_arrange_shared_legend}
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
p1 <- qplot(carat, price, data = dsamp, colour = clarity)
p2 <- qplot(cut, price, data = dsamp, colour = clarity)
p3 <- qplot(color, price, data = dsamp, colour = clarity)
p4 <- qplot(depth, price, data = dsamp, colour = clarity)
grid_arrange_shared_legend(p1, p2, p3, p4, ncol = 2, nrow = 2)
```
Four plots that share the same legend.

## Extensions to knitr

`knitr` allows S3 methods for `knit_print` for specialised printing of objects.
We provide `lemon_print` for data frames, dplyr tables, and summary objects, 
that can  be used to render the output, without mucking up the code source.
An added benefit is that we can use RStudio's inline data frame viewer:

![Viewing data frames in R Notebooks in RStudio](vignettes/lemon_print_capture.png)


### Relative file paths made safe

Using `knitr` for computations that use external binaries and/or write temporary
files, setting the root directory for `knitr`'s knitting saves the user from a
file mess. E.g.

```r
knitr::opts_knit$set(root.dir=TMPDIR)
```

But we want to keep our file paths relative for the scripts / document to be 
transferable. We introduce the `.dot` functions:

```r
TMPDIR=tempdir()

.data <- .dot('data')

knitr_opts_knit$set(root.dir=TMPDIR)
```

We can then load our data file using the created `.data` function,
even though the chunk is executed from TMPDIR.

```r
dat <- read.table(.data('mydata.tab'))
```

Owner

  • Name: Stefan McKinnon Edwards
  • Login: stefanedwards
  • Kind: user
  • Location: Silkeborg, Denmark
  • Company: Kamstrup A/S

Data Analyst at Kamstrup A/S, former quantitative geneticist.

GitHub Events

Total
  • Issues event: 1
  • Watch event: 9
  • Issue comment event: 5
  • Push event: 3
  • Pull request event: 3
  • Fork event: 1
Last Year
  • Issues event: 1
  • Watch event: 9
  • Issue comment event: 5
  • Push event: 3
  • Pull request event: 3
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 162
  • Total Committers: 6
  • Avg Commits per committer: 27.0
  • Development Distribution Score (DDS): 0.265
Past Year
  • Commits: 2
  • Committers: 2
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.5
Top Committers
Name Email Commits
stefanedwards s****e@i****m 119
Stefan McKinnon HΓΈj-Edwards s****e@k****m 32
Stefan Hoj-Edwards s****s 7
HOJ-EDWARDS Stefan s****w@e****k 2
Teun van den Brand 4****d 1
Stefan McKinnon Edwards s****h@k****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 29
  • Total pull requests: 9
  • Average time to close issues: 12 months
  • Average time to close pull requests: 24 days
  • Total issue authors: 16
  • Total pull request authors: 3
  • Average comments per issue: 1.93
  • Average comments per pull request: 0.78
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: about 1 month
  • Issue authors: 1
  • Pull request authors: 2
  • Average comments per issue: 0.0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • stefanedwards (11)
  • dylanjm (2)
  • g-pacheco (2)
  • thomasp85 (2)
  • ObGDK (1)
  • msgoussi (1)
  • mdeber (1)
  • teng-gao (1)
  • jdeines (1)
  • ghost (1)
  • bappa10085 (1)
  • lnnrtwttkhn (1)
  • thomas-neitmann (1)
  • gkaramanis (1)
  • sam81 (1)
Pull Request Authors
  • stefanedwards (5)
  • teunbrand (3)
  • mariabnd (2)
Top Labels
Issue Labels
bug (7) enhancement (3)
Pull Request Labels

Packages

  • Total packages: 3
  • Total downloads:
    • cran 5,393 last-month
  • Total docker downloads: 425
  • Total dependent packages: 6
    (may contain duplicates)
  • Total dependent repositories: 15
    (may contain duplicates)
  • Total versions: 23
  • Total maintainers: 1
proxy.golang.org: github.com/stefanedwards/lemon
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 6.5%
Average: 6.7%
Dependent repos count: 6.9%
Last synced: 6 months ago
cran.r-project.org: lemon

Freshing Up your 'ggplot2' Plots

  • Versions: 14
  • Dependent Packages: 6
  • Dependent Repositories: 14
  • Downloads: 5,393 Last month
  • Docker Downloads: 425
Rankings
Stargazers count: 2.4%
Downloads: 6.1%
Dependent packages count: 7.3%
Dependent repos count: 7.7%
Forks count: 7.9%
Average: 8.9%
Docker downloads count: 22.1%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: r-lemon
  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 1
Rankings
Dependent repos count: 24.4%
Stargazers count: 27.9%
Average: 37.8%
Forks count: 47.5%
Dependent packages count: 51.6%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.1.0 depends
  • ggplot2 >= 2.2.0 imports
  • grid * imports
  • gridExtra * imports
  • gtable * imports
  • knitr >= 1.12 imports
  • lattice * imports
  • plyr * imports
  • scales * imports
  • dplyr * suggests
  • rmarkdown * suggests
  • stringr * suggests
  • testthat * suggests