Solution Finale proposée

module3/exo3/README.txt

+README file for Snow GIS data
+-----------------------------
+
+This zip file contains a number of GIS layers relating to John Snow's 1854 investigation of a
+Cholera outbreak in London - considered by many to be the first use of geographical analysis
+in an epidemiological study. More details on the history are available at
+http://en.wikipedia.org/wiki/1854_Broad_Street_cholera_outbreak
+
+This file contains a number of GIS layers created from Snow's original map which allow analyses to be
+conducted on the data in modern GIS systems. For example, clustering of cases can be analysed and the
+effect of spatial aggregation in modern anonymised health data releases. Of course, it's also just
+interesting to look at the area, and how little it has changed since 1854.
+
+Files included:
+(Many of the items in the list consist of many actual files (for example .shp, .dbf etc)
+
+* OSMap				Raster		Modern OS map of the area of the outbreak (from OS Open Data - contains Ordnance Survey data © Crown copyright and database right 2013)
+* OSMap_Greyscale	Raster		Same as above, but in greyscale for easier visualisation (altered by conversion to greyscale, from OS Open Data - contains Ordnance Survey data © Crown copyright and database right 2013)
+* SnowMap			Raster		Snow's original map, georeferenced and warped so that it accurately overlays the OS map
+* CholeraDeaths		Vector		Points for each location of one or more deaths. Attribute value gives number of deaths at that location
+* Pumps				Vector		Points for each location of a pump
+
+Created and compiled by Robin Wilson (robin@rtwilson.com, www.rtwilson.com/academic) - Jan 2011.
\ No newline at end of file

module3/exo3/exercice_fr.Rmd

 ---
 title: "Evaluation par les pairs"
-author: "Paul Faye"
+author: "Auteur: ea4f5ba1b97cd5a14653d4641234245a"
 date: "05 Juin 2021"
 output: pdf_document
 ---

module3/exo3/exercice_fr.knit.md

+---
+title: "Evaluation par les pairs"
+author: "Auteur: ea4f5ba1b97cd5a14653d4641234245a"
+date: "05 Juin 2021"
+output: pdf_document
+---
+
+# Le pouvoir d'achat des ouvriers anglais du XVIe au XIXe siècle
+
+
+
+### Importation des bibliothèques nécessaires
+
+
+```r
+library(ggplot2)
+library(stringr)
+library(tseries)
+```
+
+```
+## Registered S3 method overwritten by 'quantmod':
+##   method            from
+##   as.zoo.data.frame zoo
+```
+
+### Importation des données nécessaires
+
+
+```r
+# Importation des données
+data = read.csv("Wheat.csv", header=T)
+# Supprimer la colonne d'indexation
+data$X =NULL 
+# Un peu de statistiques descriptives
+summary(data)
+```
+
+```
+##       Year          Wheat           Wages       
+##  Min.   :1565   Min.   :26.00   Min.   : 5.000  
+##  1st Qu.:1630   1st Qu.:33.00   1st Qu.: 6.145  
+##  Median :1695   Median :41.00   Median : 7.800  
+##  Mean   :1695   Mean   :43.26   Mean   :11.582  
+##  3rd Qu.:1760   3rd Qu.:47.00   3rd Qu.:14.875  
+##  Max.   :1821   Max.   :99.00   Max.   :30.000  
+##                                 NA's   :3
+```
+1. Reproduction du graphique de Playfair
+
+
+```r
+ggplot(data = data) + 
+  geom_bar(aes(x = Year, y = Wheat), stat="identity", width=5, fill = "white", color="steelblue") +
+  xlab("Year")+
+  ylab("shillings") +
+  geom_area(aes(x =Year, y = Wages), color="red",fill="lightblue")+
+    theme(
+      axis.title.y = element_text(color = "blue"),
+      axis.title.y.right = element_text(color = "blue"))
+```
+
+![](exercice_fr_files/figure-latex/unnamed-chunk-3-1.pdf)<!-- --> 
+
+2. Amélioration du graphique avec une ordonnée pour chaque variable quantitative
+
+
+
+```r
+ggplot(data= data) + 
+  geom_bar(aes(x = Year, y = Wheat), stat="identity", width=5, fill = "white", color="steelblue") +
+  xlab("Year")+
+  ylab("shillings par quart de boisseau de blé") +
+  geom_area(aes(x =Year, y = Wages), color="red",fill="lightblue")+
+  ggtitle("Evolution du prix du blé et du salaire moyen de 1965 à 1821") +
+  scale_y_continuous(sec.axis = sec_axis(~., name = "shillings par semaine"))+
+    theme(
+      axis.title.y = element_text(color = "blue"),
+      axis.title.y.right = element_text(color = "red"))
+```
+
+![](exercice_fr_files/figure-latex/unnamed-chunk-4-1.pdf)<!-- --> 
+
+```r
+#scale_y_continuous(sec.axis = sec_axis(~.*, name = ""))+
+```
+3. Représentation de l'évolution du pouvoir d'achat
+
+
+```r
+# Le pouvoir d'achat est défini comme la quantité de blé qu'un ouvrier peut acheter avec son salaire hebdomadaire.
+data$PA= data$Wages / data$Wheat 
+
+# Evolution du pouvoir d'achat
+ggplot(data= data) +
+  xlab("Year")+
+  ylab("Pouvoir d'achat (PA)") +
+  geom_area(aes(x =Year, y = PA), color="purple",fill=NA)+
+  ggtitle("Evolution du pouvoir d'achat de 1965 à 1821") +
+    theme(
+      axis.title.y = element_text(color = "purple"))
+```
+
+![](exercice_fr_files/figure-latex/unnamed-chunk-5-1.pdf)<!-- --> 
+
+3. b) Graphique du prix du blé et du salaire : On montre l'augmentation dans le temps du pouvoir d'achat
+
+
+```r
+# On enlève les 3 dernières observations pour lesquelles nous n'avons pas le salaire et par conséquent le pouvoir d'achat
+plot.ts(data[1:50,2:4], main= "Evolution au cours du temps")
+```
+
+![](exercice_fr_files/figure-latex/unnamed-chunk-6-1.pdf)<!-- --> 
+Le pouvoir d'achat a une tendance haussière au cours du temps. Il faut cependant noter quelques périodes d'instabilité, ou elle s'inverse (baisse). 
+