RaukR 2023 • Advanced R for Bioinformatics
27-Jun-2023
Graphing is an essential part of data analyses. Data with same summary statistics can look very different when plotted out.
ggplot2
?
iris
data.frame
objectSepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
---|---|---|---|---|
5.1 | 3.5 | 1.4 | 0.2 | setosa |
4.9 | 3.0 | 1.4 | 0.2 | setosa |
4.7 | 3.2 | 1.3 | 0.2 | setosa |
4.6 | 3.1 | 1.5 | 0.2 | setosa |
5.0 | 3.6 | 1.4 | 0.2 | setosa |
5.4 | 3.9 | 1.7 | 0.4 | setosa |
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
diamonds
carat | cut | color | clarity | depth | table | price | x | y | z |
---|---|---|---|---|---|---|---|---|---|
0.23 | Ideal | E | SI2 | 61.5 | 55 | 326 | 3.95 | 3.98 | 2.43 |
0.21 | Premium | E | SI1 | 59.8 | 61 | 326 | 3.89 | 3.84 | 2.31 |
0.23 | Good | E | VS1 | 56.9 | 65 | 327 | 4.05 | 4.07 | 2.31 |
0.29 | Premium | I | VS2 | 62.4 | 58 | 334 | 4.20 | 4.23 | 2.63 |
0.31 | Good | J | SI2 | 63.3 | 58 | 335 | 4.34 | 4.35 | 2.75 |
0.24 | Very Good | J | VVS2 | 62.8 | 57 | 336 | 3.94 | 3.96 | 2.48 |
tibble [53,940 × 10] (S3: tbl_df/tbl/data.frame)
$ carat : num [1:53940] 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
$ cut : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
$ color : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
$ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
$ depth : num [1:53940] 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
$ table : num [1:53940] 55 61 65 58 58 57 57 55 61 61 ...
$ price : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...
$ x : num [1:53940] 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
$ y : num [1:53940] 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
$ z : num [1:53940] 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...
Wide
Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
---|---|---|---|---|
5.1 | 3.5 | 1.4 | 0.2 | setosa |
4.9 | 3.0 | 1.4 | 0.2 | setosa |
4.7 | 3.2 | 1.3 | 0.2 | setosa |
Long
Species | variable | value |
---|---|---|
setosa | Sepal.Length | 5.1 |
setosa | Sepal.Length | 4.9 |
setosa | Sepal.Length | 4.7 |
plot | stat | geom |
---|---|---|
histogram | bin | bar |
smooth | smooth | line |
boxplot | boxplot | boxplot |
density | density | line |
freqpoly | freqpoly | line |
Use args(geom_bar)
to check arguments.
Just because you can doesn’t mean you should!
scale_<aesthetic>_<type>
scale_
, then press TABscale_<axis>_<type>
facet_wrap
facet_grid
p <- p + theme(
axis.title=element_text(color="#e41a1c"),
axis.text=element_text(color="#377eb8"),
plot.title=element_text(color="#4daf4a"),
plot.subtitle=element_text(color="#984ea3"),
legend.text=element_text(color="#ff7f00"),
legend.title=element_text(color="#ffff33"),
strip.text=element_text(color="#a65628")
)
p <- p + theme(
plot.background=element_rect(fill="#b3e2cd"),
panel.background=element_rect(fill="#fdcdac"),
panel.border=element_rect(fill=NA,color="#cbd5e8",size=3),
legend.background=element_rect(fill="#f4cae4"),
legend.box.background=element_rect(fill="#e6f5c9"),
strip.background=element_rect(fill="#fff2ae")
)
newtheme <- theme_bw() + theme(
axis.ticks=element_blank(), panel.background=element_rect(fill="white"),
panel.grid.minor=element_blank(), panel.grid.major.x=element_blank(),
panel.grid.major.y=element_line(size=0.3,color="grey90"), panel.border=element_blank(),
legend.position="top", legend.justification="right"
)
ggplot2
plots can be saved just like base plotsggplot2
package offers a convenient functionpng
is pixels while in ggsave
it’s inchesRefer to patchwork documentation.
ggplot2
object to interactive HTMLA collection of ggplot extension packages: https://exts.ggplot2.tidyverse.org/.
Curated list of ggplot2 links: https://github.com/erikgahner/awesome-ggplot2.
_
platform x86_64-pc-linux-gnu
os linux-gnu
major 4
minor 2.3
2023 • SciLifeLab • NBIS • RaukR