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Create a new ggplot — ggplot • ggplot

# Une ellipse autour de tous les points ggplot(faithful, aes(waiting, eruptions))+ geom_point()+ stat_ellipse() # Ellipses par groupes p - ggplot(faithful, aes(waiting, eruptions, color = eruptions > 3))+ geom_point() p + stat_ellipse() # Changer le type d'ellipses: # Valeurs possibles t, norm, euclid p + stat_ellipse(type = norm Retour sur les bases de ggplot2. L'extension ggplot2 nécessite que les données du graphique soient sous la forme d'un tableau de données (data.frame) avec une ligne par observation et les différentes valeurs à représenter sous forme de variables du tableau.. Tous les graphiques avec ggplot2 suivent une même logique. En premier lieu, on appelera la fonction ggplot en lui passant en.

Introduction à ggplot2, la grammaire des graphique

On créé un objet ggplot et on lui indique quelles données il faut utiliser (data=data_kinetic_01). Puis les paramètres de Aesthetics sont définis (aes(x=Time, y=Abs, colour=Cond, shape=Cond)). Dans cette commande, il est indiqué d'utiliser la colonne Time pour x et la colonne Abs pour y. Pour les couleurs et les formes la colonne Cond sera utilisée. Ce paramètre peut être plus. Cet article fournit une galerie d'exemples de ggplot, notamment : diagrammes de dispersion, diagrammes de densité et histogrammes, diagrammes en barres et en lignes, barres d'erreur, box plot, violin plot et plus

Chapitre 1 Visualisation avec ggplot2 Tutoriel

Partie 8 Visualiser avec ggplot2 Introduction à R et au

modifier - modifier le code - voir Wikidata (aide) ggplot2 est une librairie R de visualisation de données développée par Hadley Wickham . La librairie est développée selon les principes développés par Leland Wilkinson dans son ouvrage The Grammar of Graphics . Sommaire 1 Galerie 2 Bibliographie 3 Notes et références 4 Liens externes Galerie [modifier | modifier le code] Nuage de. A system for 'declaratively' creating graphics, based on The Grammar of Graphics. You provide the data, tell 'ggplot2' how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details Cheatsheet. Usage. It's hard to succinctly describe how ggplot2 works because it embodies a deep philosophy of visualisation. However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()).You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), faceting specifications (like facet_wrap()) and coordinate systems. Éléments graphiques Les Graphiques avec ggplot2 Aide mémoire RStudio® is a trademark of RStudio, Inc. • CC BY RStudio • info@rstudio.com • 844448 1212.

ggplot function R Documentatio

  1. On va plutôt se focaliser sur la grammaire de ggplot. Itération 1 - Ajouter un titre. La première chose qu'on va faire, c'est ajouter un titre. Pour ça, on utilise la fonction labs. Et je vais lui donner la couleur du logo de Pokemon GO : p <-ggplot (pokemon, aes (x = `Max HP`, y = `Max CP`)) + geom_point + # Title labs (title = Relationship between Max CP and Max HP) + # Style bbc.
  2. p4=ggplot(catdata, aes(x=foodtype, y=age)) p4a=p4+geom_violin(fill=powderblue)+xlab(type de nourriture)+ylab(âge) #plot(p4a) Un des aspects les plus intéressants de ggplot2 est la facilité avec laquelle on peut transformer les variables de position x et y. Ici par exemple en travaillant sur une échelle y log (figure 4b; dans ce cas particulier loguer les y n'aide pas franchement à.
  3. While you could set matplotlib's style to ggplot, you cannot implement the grammar of graphics in matplotlib the same way you can in ggplot2. Installation. Before getting started, you have to install plotnine. As always, there are two main options for doing so: pip and conda. Plotting . Having installed plotnine, you can get started plotting using the grammar of graphics. Let us begin by.
  4. Saving ggplot; Cheatsheets: Lookup code to accomplish common tasks from this ggplot2 quickref and this cheatsheet. The distinctive feature of the ggplot2 framework is the way you make plots through adding 'layers'. The process of making any ggplot is as follows. 1. The Setup. First, you need to tell ggplot what dataset to use
  5. In this example, I construct the ggplot from a long data format. That means, the column names and respective values of all the columns are stacked in just 2 variables (variable and value respectively). If you were to convert this data to wide format, it would look like the economics dataset. In below example, the geom_line is drawn for value column and the aes(col) is set to variable. This way.
  6. x =) ) **. ++--| | %% ## ↵ ↵ ↵ ↵
  7. Because ggplot2 isn't part of the standard distribution of R, you have to download the package from CRAN and install it. The Comprehensive R Archive Network (CRAN) is a network of servers around the world that contain the source code, documentation, and add-on packages for R. Each submitted package on CRAN also has a page [

La fonction rapide de carte est qmap (une terminologie qui devrait sonner familière aux adeptes des qplot de ggplot) - le premier argument faisant référence à la requête (ville / département / région) et le second au niveau de zoom de Google map. library (ggmap) map <-qmap ('Bretagne', zoom = 8) Une fois l'objet map créé, il ne vous reste qu'à l'utiliser comme première. library(ggplot2) g <- ggplot(df, aes(x=distanceRemaining, y =position, colour=athlete, group = athlete)) g <- g + geom_point() g <- g + geom_line(size=1.15) g <- g + scale_y_discrete() g To give. Question. How do I reverse the order of the y-axis so that 10 is at the bottom and 1 is at the top? r ggplot2. Share . Improve this question. Follow edited Dec 11 '18 at 13:16. zx8754. 40.9k 10 10. Note that ggplot also separates the lines correctly if only the color mapping is specified (the group parameter is implicitly set).. Exercise: Compare life expectancy. Create a line graph to compare the life expectancy lifeExp in the countries Japan, Brazil and India.. Use the data set gapminder_comparison in your ggplot() function which contains only data for the countries Japan, Brazil and.

ggplot2 is a data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a number of. ggplot(data = diamonds) + geom_bar(mapping = aes(x = 1, fill = cut), position = fill) + coord_polar(theta = y) + facet_wrap( ~ clarity, nrow = 2) + scale_fill_brewer(type = qual, palette = 6) On peut ainsi comparer dans quelle mesure les proportions varient d'une catégorie à l'autre d'une seconde variable. Bonnes pratiques . En introduction j'avais évoqué les reproches qui. b <-ggplot(hour.dataset, aes(x =weathersit,fill =season)) L'axe des x est toujours occupé par la température, mais ce sont les saisons qui créent les barres. C'es ggplot (mpg, aes (displ, hwy)) + geom_point (aes (colour = class)) + scale_x_sqrt + scale_colour_brewer Here scale_x_sqrt() changes the scale for the x axis scale, and scale_colour_brewer() does the same for the colour scale. The scale functions intended for users all follow a common naming scheme. You've probably already figured out the scheme, but to be concrete, it's made up of three.

Line segments and curves — geom_segment • ggplot2

ggplot2 graphique linéaire : Guide de démarrage rapide

  1. Je ne sais pas pour vous, mais moi, à chaque fois que j'assiste à une réunion de labo, il y a quasi systématiquement un graphique d'ACP pour montrer les données. Et à chaque fois, il s'agit d'un graphique de base, généré avec R, avec la fonction plot(), des couleurs qui piquent les yeux et des axes et légendes illisibles. La critique est facile me direz-vous, j'avoue avoir moi aussi.
  2. Normalement, ggplot les supprime automatiquement (avec un message d'erreur du type Warning message: Removed 1 rows containing missing values (geom_path)). PY. Haut. roxanne anckaert Messages : 10 Enregistré le : Lun Juil 17, 2017 11:33 am. Re: ggplot (ajouter plusieurs courbes a un même graphique) Message par roxanne anckaert » Mer Juil 19, 2017 6:11 am . Merci beaucoup ! Oui en effet.
  3. ggplot(data = <DATA>, mapping = aes(<MAPPINGS>)) + <GEOM_FUNCTION>() use the ggplot() function and bind the plot to a specific data frame using the data argument; ggplot (data = surveys_complete) define an aesthetic mapping (using the aesthetic (aes) function), by selecting the variables to be plotted and specifying how to present them in the graph, e.g. as x/y positions or characteristics.
  4. Bonjour. Tu auras un axe secondaire gradué comme tu veux en changeant ta fonction sec_axis. Par contre dans {ggplot2} l'axe secondaire permet juste de présenter les mêmes données que l'axe Y, éventuellement dans des unités différentes (exemple classique : des températures en ° celsius et farenheit) ou juste en miroir, à l'identique
  5. ggplot() helpfully takes care of the remaining five elements by using defaults (default coordinate system, scales, faceting scheme, etc.). There are also a couple of plot elements not technically part of the grammar of graphics. These are: Theme; Labels; You already learned about labels and the labs() function. Themes control components of plots not related to the actually data being plotted.
  6. GGPLOT. ggplot est la seconde fonction du package ggplot2, et va permettre de produire des graphiques plus complexes et élaborés. De plus, alors que la fonction qplot était relativement similaire dans sa syntaxe des fonctions traditionnelles permettant de tracer des graphiques sous R, la syntaxe utilisée par ggplot est totalement différente

I am trying to change the height and width of my plot and while I have changed the plot margins I would like to change the background to be proportionate with my plot. This is what my current plot looks like: And I want it to look more like this: I've added the background to so it's easier to see what I mean. Ultimatley, I just want my plot to be wider than it is tall, and I would like if. A List of ggplot2 extensions. This site tracks and lists ggplot2 extensions developed by R users in the community.; The aim is to make it easy for R users to find developed extensions. New Geom We have only scratched the surface here. To learn more, see the ggplot reference site, and Winston Chang's excellent Cookbook for R site. Though slightly out of date, ggplot2: Elegant Graphics for Data Anaysis. is still the definative book on this subject. To Practice. Try the free first chapter of this interactive tutorial on ggplot2 Using ggplot in Python allows you to build visualizations incrementally, first focusing on your data and then adding and tuning components to improve its graphical representation. In the next section, you'll learn how to use colors and how to export your visualizations. Remove ads. Visualizing Multidimensional Data . As you saw in the section about facets, displaying data with more than two.

Pretty scatter plots with ggplot2

Graphiques univariés et bivariés avec ggplot

library(tidyverse) Nous considérons les données salaires.tex.. salary: salaire brut actuel en $ par an. salbegin: salaire de départ en $ par an. minority: appartenance à une minorité (0 appartient et 1 sinon). jobtime: nombre de mois depuis l'entrée dans l'entreprise. prevexp: nombre de mois de travail avant l'entrée dans l'entreprise. educ: nombre d'années d'étud Files for ggplot, version 0.11.5; Filename, size File type Python version Upload date Hashes; Filename, size ggplot-0.11.5-py2.7.egg (2.3 MB) File type Egg Python version 2.7 Upload date Sep 29, 2016 Hashes Vie Call the ggplot() function which creates a blank canvas; Specify aesthetic mappings, which specifies how you want to map variables to visual aspects. In this case we are simply mapping the displ and hwy variables to the x- and y-axes. You then add new layers that are geometric objects which will show up on the plot. In this case we add geom_point to add a layer with points (dot) elements as. Change Position of ggplot Title; Graphics in R; List of R Commands (+ Examples) The R Programming Language; In this tutorial I explained how to remove legends in ggplot2. The tutorial should include everything you need to know in order to delete a legend properly. However, in case you have any further questions or recommendations for improvements of the tutorial, you can let me know in the. Donc je suis passer loin de ggplot aujourd'hui pour ce projet particulier. =(Cette réponse (à partir du lien wiki) est une excellente suggestion, sauf que les deux parcelles sont tout simplement étiquetés y. On pourrait juste se cacher le nom de l'axe y et l'utilisation de la facette noms pour l'axe des y, mais qui semble comme un sous-par la solution. Tous les conseils sur la façon d.

Shapes and line types

Quand on commence à utiliser le package ggplot2, la question de la gestion des couleurs se pose en général assez rapidement. Cet article a pour but de vous aider dans cette étape, en vous montrant quelques fonctions, outils, et autres ressources utiles.. Les données utilisées dans les exemples sont celle du jeu de données iris.Il est constitué de quatre variables numériques Sepal. Default grouping in ggplot2. ggplot2 can subset all data into groups and give each group its own appearance and transformation. In many cases new users are not aware that default groups have been created, and are surprised when seeing unexpected plots ggplot. What is it? ggplot is a Python implementation of the grammar of graphics. It is not intended to be a feature-for-feature port of ggplot2 for R--though there is much greatness in ggplot2, the Python world could stand to benefit from it.So there will be feature overlap, but not neccessarily mimicry (after all, R is a little weird).. You can do cool things like this

ggplot2 histogramme : Guide de démarrage rapide - Logiciel

# Bars: x and fill both depend on cond2 ggplot (df, aes (x = cond, y = yval, fill = cond)) + geom_bar (stat = identity) # Bars with other dataset; fill depends on cond2 ggplot (df2, aes (x = cond1, y = yval)) + geom_bar (aes (fill = cond2), # fill depends on cond2 stat = identity, colour = black, # Black outline for all position = position_dodge ()) # Put bars side-by-side instead of. ggplot(df, aes(a, b)) + geom_col() En savoir plus : Comment construire un graphique avec ggplot2. 2017-07-25. Article précédent: Comment faire rbind et cbind dans le tidyverse ? bind_rows et bind_cols. Article suivant: Comment détecter si une valeur se situe entre deux autres valeurs ? between() Search . Formation et consultance. Trouvez votre formation R sur-mesure chez ThinkR-- Contactez. Re: Courbe de fréquence cumulée - GGPLOT Message par Mickael Canouil » Ven Avr 10, 2020 3:08 pm SI je peux me permettre, weight n'a jamais été mentionné dans la documentation de stat_ecdf et en particulier dans les aesthetics nécessaires In this case the ggplot_na_intervals plotting function can provide a more condensed overview. See also. ggplot_na_intervals, ggplot_na_gapsize, ggplot_na_imputations. Examples # Example 1: Visualize the missing values in x x <-stats:: ts (c (1: 11, 4: 9, NA, NA, NA, 11: 15, 7: 15, 15: 6, NA, NA, 2: 5, 3: 7)) ggplot_na_distribution (x) # Example 2: Visualize the missing values in tsAirgap time.

Monte Carlo Part Two · R Views

Comment Créer une Carte avec GGPlot2: Meilleure Référence

  1. Introductory video tutorial on using the ggplot2 plotting system in R and RStudio. Please view in HD (cog in bottom right corner).Download the R script here:..
  2. ggplotオブジェクトにtheme(axis.title.x = element_blank())を+で繋ぐと横軸のラベルが表示されなくなります。ggarrange()に入れるオブジェクトに直接アクセスし、それぞれの軸ラベルを消してみましょう 5
  3. ggplot likes data in the 'long' format: i.e., a column for every dimension, and a row for every observation. Well structured data will save you lots of time when making figures with ggplot. ggplot graphics are built step by step by adding new elements. Adding layers in this fashion allows for extensive flexibility and customization of plots. To build a ggplot, we need to: use the ggplot.
  4. To make it easy to get started, the ggplot2 package offers two main functions: quickplot() and ggplot(). The quickplot() function - also known as qplot() - mimics R's traditional plot() function in many ways. It is particularly easy to use for simple plots. Below is an example of the default plots that qplot() makes. The command that created each plot is shown in the title of each graph.
  5. ggplot(data, mapping=aes()) + geometric object arguments: data: Dataset used to plot the graph mapping: Control the x and y-axis geometric object: The type of plot you want to show. The most common object are: - Point: `geom_point()` - Bar: `geom_bar()` - Line: `geom_line()` - Histogram: `geom_histogram()` Scatterplot. Let's see how ggplot works with the mtcars dataset. You start by plotting a.

ggplot likes data in the 'long' format: i.e., a column for every dimension, and a row for every observation. Well structured data will save you lots of time when making figures with ggplot. ggplot graphics are built step by step by adding new elements. Adding layers in this fashion allows for extensive flexibility and customization of plots. 5.5 Data. We are going to use a National Park. The R ggplot2 boxplot is useful for graphically visualizing the numeric data group by specific data. Let us see how to Create an R ggplot2 boxplot, Format the colors, changing labels, drawing horizontal boxplots, and plot multiple boxplots using R ggplot2 with an example The ggplot() function within the ggplot2 package gives us more control over plot appearance. However, to use ggplot we need to learn a slightly different syntax. Three basic elements are needed for ggplot() to work: The data_frame: containing the variables that we wish to plot, aes (aesthetics): which denotes which variables will map to the x-, y- (and other) axes, geom_XXXX (geometry): which. Multiple graphs on one page (ggplot2) Problem. You want to put multiple graphs on one page. Solution. The easy way is to use the multiplot function, defined at the bottom of this page. If it isn't suitable for your needs, you can copy and modify it ggplot(airbnb.summ, aes(x=longitude, y=latitude)) + geom_point() La librairie geojsonio permet de lire et d'écrire des données au format GeoJSON, permettant de réprésenter des objets géoraphiques dans un formalisme issue de JSON. Il est très utilisé pour représenter des zones, telles que des villes, des pays, On importe donc les données des arrondissements. La fonction fortify.

A geom that draws a rectangle.. Default statistic: stat_identity Default position adjustment: position_identity. Parameters. xmin - (required) left edge of rectangle ; xmax - (required) right edge of rectangle ; ymin - (required) bottom edge of rectangle ; ymax - (required) top edge of rectangle ; size - (default: 0.5) line width of the rectangle's outline ; linetype - (default: 1=solid) line. This tutorial explains how to create a heatmap in R using ggplot2 A blog about statistics including research methods, with a focus on data analysis using R and psychology Making Plots With plotnine (aka ggplot) Introduction. Python has a number of powerful plotting libraries to choose from. One of the oldest and most popular is matplotlib - it forms the foundation for many other Python plotting libraries. For this exercise we are going to use plotnine which is a Python implementation of the The Grammar of Graphics, inspired by the interface of the ggplot2.

ggwordcloud provides a word cloud text geom for ggplot2.The placement algorithm implemented in C++ is an hybrid between the one of wordcloud and the one of wordcloud2.js.The cloud can grow according to a shape and stay within a mask While ggplot() allows for maximum features and flexibility, qplot() is a more straightforward but less customizable wrapper around ggplot. Note: in practice, ggplot() is used more often. Step Four. Taking It One Step Further. Now that you know how to make a basic histogram with this R package that is based on the grammar of graphics, it's time to take things up a notch, and adjust the qplot. Mapping via scale_linetype_identity. The scale_linetype_identity scale can be used to pass through any legal linetype value (its mapping is the identity function, and thus it does not change anything) ggedit is aimed to interactively edit ggplot layers, scales and themes aesthetics stop author: yonicd. stop tags: visualization, interactive, shiny, general,themes. stop js libraries: true. gganatogram Star. gganatogram makes it possible to visualise tissues for different organisms or cell compartments. stop author: jespermaag. stop tags: anatograms, tissue, visualization, anatomy, expression.

ggplot2 package R Documentatio

ggplot While qplot is a great way to get off the ground running, it does not provide the same level of customization as ggplot . All the above plots can be reproduced using ggplot as follows ggplot vs base vs lattice vs XYZ R provides many ways to get your data into a plot. Three common ones are, base graphics (plot, hist, etc`) lattice; ggplot2; All of them work! I use base graphics for simple, quick and dirty plots. I use ggplot2 for most everything else. ggplot2 excels at making complicated plots easy and easy plots simple enough. Geoms / Aesthetics. Every graphic you.

r programming language:wow example using ggplot graphics

ggplot2 heatmap - the R Graph Galler

We then instruct ggplot to render this as a boxplot by adding the geom_boxplot() option. p10 <-ggplot (airquality, aes (x = Month, y = Ozone)) + geom_boxplot p10. Customising axis labels. In order to change the axis labels, we have a couple of options. In this case, we have used the scale_x_discrete and scale_y_continuous options, as these have further customisation options for the axes we. A powerful graphics library for great visualizations. Do you wish that Python could emulate the superb visualizations that ggplot gives you in the R language? Well it can. We are going to explore the capabilities of Plotnine, a visualization library for Python that is based on ggplot2.. Being able to visualize your data gives you the ability to better understand it This document is the web-based version of a presentation given through the University of Idaho library workshop series on September 12, 2017. The text is fairly sparse because this is primarily a reference based on workshop slides ggplot is both flexible and powerful, but it's up to you to design a graph that communicates what you want to show. Just because you can do something doesn't mean you should. You should always think about what message you're trying to convey with a graph, then design from those principles. Keep this in mind as we review the next two aesthetics. While these aesthetics absolutely have a place in. gapminder %>% ggplot (aes (x = year, y = lifeExp)) + stat_summary (fun.y = mean, geom = pointrange, fun.ymax = function (x) mean (x) + sd (x), fun.ymin = function (x) mean (x)-sd (x)) Another typical representation are standard errors. I haven't found a function that we can use to calculate standard errors, but the formula is not very complicated and we can use the same logic to represent.

Introduction à la visualisation sous R avec le package

myplot = ggplot (df, aes (x = a, y = b)) + geom_point myplot. theme_bw() will get rid of the background. myplot + theme_bw remove grid (does not remove backgroud colour and border lines) myplot + theme (panel.grid.major = element_blank (), panel.grid.minor = element_blank ()) remove border lines (does not remove backgroud colour and grid lines) myplot + theme (panel.border = element_blank. ggplot() + aes() + geom_*() VizTOC To use the visual table of contents, mouse over to see a preview of what will be covered, then click any link or visual preview to go through to the flipbook (code-movies built with the flipbookr and xaringan packages) that will show you a detailed build of the previewed contents Hom

Data visualization with R and ggplot2 the R Graph Galler

The ggplot() command sets up a general canvas with our full data set. We then plot a geom_histogram() using the background data (d_bg) and fill it grey so as to give it a neutral appearance. It makes use of the aes() command within ggplot(), thus plotting the data we want. On top of this, we plot another geom_histogram() ggplot supports the layering of multiple data objects and graph types. Multilayered charts also present the challenge of managing multiple legends. As before, legend control is tied to use of the appropriate scale function given previously declared aesthetics. For example

Guide de démarrage pour ggplot2, un package graphique pour

La fonction labs(), à insérer pendant la construction de votre ggplot, fournit un raccourci pour intégrer titre, sous-titres, et légendes 7.2 ggplot objects. The first step in creating a ggplot2 graph is to define a ggplot object. We do this with the function ggplot, which initializes the graph. If we read the help file for this function, we see that the first argument is used to specify what data is associated with this object: ggplot (data = murders) We can also pipe the data in as the first argument. So this line of code is.

a ggplot object. width: Width of the plot in pixels (optional, defaults to automatic sizing). height: Height of the plot in pixels (optional, defaults to automatic sizing). tooltip: a character vector specifying which aesthetic mappings to show in the tooltip. The default, all, means show all the aesthetic mappings (including the unofficial text aesthetic). The order of variables here will. Part 1 of 2 of my impromptu beginner/intermediate ggplot2 workshop. It will focus on teaching the underlying theory of ggplot2 and how it is reflected in the.. plotnine.ggplot¶ class plotnine.ggplot (mapping = None, data = None, environment = None) [source] ¶. Create a new ggplot object. Parameters aesthetics aes. Default aesthetics for the plot. These will be used by all layers unless specifically overridden

Transform ggplot2 objects into 3D — plot_gg • rayshaderGGtutorial: Day 3 - Introduction to ColorsPretty scatter plots with ggplot2 | R-bloggersFile:Confidence-interval

Help on all the ggplot functions can be found at the The master ggplot help site. A useful cheat sheet on commonly used functions can be downloaded here. Chang, W (2012) R Graphics cookbook. O'Reilly Media. - a guide to ggplot with quite a bit of help online here . Author: Fiona Robinson Last updated: ## [1] Tue May 24 12:38:12 201 Si vous voulez reprendre des parties de ce site, faites-le, mais n'oubliez pas de donner votre source !. Aide à l'utilisation du logiciel R - site réalisé par Antoine Massé - ingénieur en biotechnologies - enseignant PrAg à l'IUT de Bordeaux - Université de Bordeaux - Site de Périgueux - département Génie Biologique. Commentaire - Problème à signaler - ou dire Merci - Cliquer-ici. Ggplot graduation des axes. L'axe x ou y peut être discret (variable de groupement) ou continu (variable numérique). Dans chacun de ces deux cas, les fonctions à utiliser pour le réglage des graduations des axes sont différentes color name color name gray8 gray9 gray10 gray11 gray12 gray13 gray14 gray15 gray16 gray17 gray18 gray19 gray20 gray21 gray22 gray23 gray24 gray25 gray26 gray27 gray2

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