Replace exercice_en.Rmd

module3/exo3/exercice_en.Rmd

@@ -78,7 +78,7 @@ ggplot(df, aes(x=Year)) +
 ## 2. Alternative representation
 First, we represent the data as simple dots for both wages and wheat price.
 
-As it is difficult to see the pattern for the wheat values evolution, we use the `stat_smooth()` function that shows a smoothed mean.
+As it is difficult to see the pattern for the wheat values evolution, we use the `stat_smooth()` function that shows a smoothed mean (with a confidence level of 70%).
 ```{r, message=FALSE}
 # Set color parameters
 wages_color <- "#ff5733"
@@ -91,7 +91,7 @@ ggplot(df, aes(x=Year)) +
   geom_point( aes(y=Wheat/1.5), size = 0.7, color = wheat_color) +
   geom_line( aes(y=Wages), size = 0.3, color = wages_color, linetype="dashed") +
   geom_line( aes(y=Wheat/1.5), size = 0.3, color = wheat_color, linetype="dashed") +
-  stat_smooth(aes(y=Wheat/1.5), level = 0, size=0.6, color=wheat_color_trans) +
+  stat_smooth(aes(y=Wheat/1.5), level = 0.7, size=0.6, color=wheat_color_trans) +
   
 # Custom the Y scales:
   scale_y_continuous(
@@ -108,6 +108,21 @@ ggplot(df, aes(x=Year)) +
 ```
 
 ## 3. Another Representation without an explicit time axis
-TBD
+```{r, message=FALSE}
+ggplot(df, aes(x=Wages, y=Wheat)) + 
+  geom_area( size = 0.5, alpha=0.5, 
+             linetype="dashed",
+             color = "#ff3333", 
+             fill = "#3399e6" ) +
+  geom_point( size = .7, shape = 4 ) +
+
+  xlim(min((na.omit(df))$Wages), max((na.omit(df))$Wages)) +
+  
 
+  labs(title = "Evolution Wheat price with respect to Salary of English workers (16th to 19th century)") +
+  theme(plot.title = element_text(hjust = 0.5))
+```
+
+### Comments
+TBD