G RAPHIQUESAVECGGPLOT 2

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G

RAPHIQUES AVEC GGPLOT

2

L3 -R3

Julie Scholler - B246

novembre 2019

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Graphics with ggplot2

Why?

• elegant, polyvalent

• mature and complete graphics system

• very flexible

• default behaviour carefully chosen

• theme system for polishing plot appearance

How?

grammar of graphics(Wilkinson, 2005)

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The Grammar Of Graphics

The basic idea to building plot

• specify blocks/layers

• combine them

• get any kind of graphics Blocks/layers

• data

• aesthetic mapping

• geometric object

• statistical transformations

• scales

• coordinate system

• position adjustments

• faceting

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Syntax

ggplot(data=...) + aes(x=..., y=...) + geom_...()

• Data: what is being visualized

• Aesthetic Mappings: mappings between variables in the data and components of the chart

• Geometric Objects: geometric objects that are used to display the data, such as points, lines, or shapes

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First try

ggplot(data)

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Aesthetic Mapping

In ggplot: aesthetic= “something you can see”

Examples

• position (on the x and y axes)

• color (“outside” color)

• fill (“inside” color)

• shape (of points)

• linetype

• size

Aesthetic mappings are set with the aes()function.

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Second try

ggplot(data) + aes(x = note_totale)

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note_totale

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Geometic Objects (geom)

Examples

• points: geom_point

• lines: geom_line

• bar: geom_bar

• histogram: geom_histogram

• boxplot: geom_boxplot

List of available geometric objects Reference list

help.search("geom_", package = "ggplot2")

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Histogramm

ggplot(data) + aes(x = note_totale) + geom_histogram()

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

0 5 10

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note_totale

count

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Create Good and Effective Graphics

• Labels

+ labs(title=..., subtitle=..., caption=..., x=..., y=..., color=..., etc.)

• Annotations + geom_text()

+ geom_text_repel()

• Coordinate + coord_flip()

• Scales, Guides, Themes

• Interactivity

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ggplot(data = data) + aes(x=note_totale) + geom_histogram(bins = 15, fill="aquamarine3",

col="white") +

labs(title = "Distribution des notes au QCM", x = "Note", y = "Effectif")+

theme_minimal()

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Note

Effectif

Distribution des notes au QCM

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Themes

The ggplot2theme system handles non-data plot elements such as

• Axis labels

• Plot background

• Facet label backround

• Legend appearance Built-in themes include:

• theme_gray() (default)

• theme_bw()

• theme_classic()

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Multivariate

ggplot(data = data) + aes(x=note_totale, fill=annee) + geom_histogram(bins = 15, col="white", alpha=0.6) + labs(title = "Distribution des notes au QCM",

x = "Note", y = "Effectif") + theme_minimal()

0 5 10 15 20 25

25 50 75 100

Note

Effectif

annee

L1 L2 L3

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Faceting

• Creates separate graphs for subsets of data

• Two solutions

1. facet_wrap(): subsets as the levels of a single grouping variable

2. facet_grid(): subsets as the crossing of two grouping variables

• Facilitates comparison among plots

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Syntax

ggplot(data=...) + aes(x=..., y=...,

fill=...,color=...,group=...) + geom_...() + facet_...(...) +

labs(...) + theme_minimal()

• Data: what is being visualized

• Aesthetic Mappings: mappings between variables in the data and components of the chart

• Geometric Objects: geometric objects that are used to display the data, such as points, lines, or shapes

gg + facet_wrap(~annee, ncol=2)

L3

L1 L2

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0.0 2.5 5.0 7.5 10.0 12.5

Note

Effectif

annee

L1 L2 L3

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Use of facet_grid()

gg + facet_grid(annee~sexe)

Un homme Une femme

L1L2L3

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0 2 4 6 8

Note

Effectif

annee

L1 L2 L3

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Density chart

ggplot(data = data) + aes(x=note_totale) +

geom_density(fill="aquamarine3", color="white", alpha = 0.6) +

labs(title = "Distribution des notes au QCM", x = "Note", y = "") + theme_minimal()

0.000 0.005 0.010 0.015 0.020 0.025

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Note Distribution des notes au QCM

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Density charts

ggplot(data = data) +

aes(x=note_totale, fill=annee, color=annee) + geom_density(alpha = 0.6) +

0.00 0.01 0.02 0.03 0.04 0.05

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Note

annee L1 L2 L3

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With ridges lines

library(ggridges) ggplot(data = data) +

aes(x=note_totale, fill=annee, col=annee, y=annee) + geom_density_ridges(alpha = 0.6, scale = 3) +

L1 L2 L3

50 100

Note

annee L1 L2 L3

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Bar charts

ggplot(data) + aes(x=annee) + geom_bar(fill="aquamarine3") + theme_minimal()

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L1 L2 L3

annee

count

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density <- ggplot(data = data) +

aes(x=note_totale, fill=annee, col=annee) + geom_density(alpha = 0.6) +

labs(title = "Notes au QCM",

subtitle = "Les L2 sont très moyens.", x = "Note", y = "")+

theme_minimal()

barplot <- ggplot(data) + aes(x=annee, fill = bac) + geom_bar(width = 0.5) +

labs(title = "Séries de baccalauréat par année de Licence", subtitle = "Les filières ES et S sont très majoritaires.", x = "Note", y = "") +

theme_minimal()

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Draw multiple plots within one figure

library(ggpubr)

ggarrange(density,barplot,align="h")

0.00 0.01 0.02 0.03 0.04 0.05

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Note

annee L1 L2 L3 Les L2 sont très moyens.

Notes au QCM

0 20 40 60

L1 L2 L3

Note

bac Bac ES Bac S Bac L Bac STMG Bac professionnel Les filières ES et S sont très majoritaires.

Séries de baccalauréat par année de Licence