Homework assignment No.3

Describe Your Data:

  1. Chose 4 simple visualization methods (boxplot must be included) for your data visualization.
  2. Present and upload your results.

Visualizations

## [1] "LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252"
ggplot(data = data, aes(x = date, y = ValueSum))+
  geom_line(size = 2, color = "lightgreen")+
  theme_light() +
  labs(title = "Revenue accumulation per time", x = "", y = "Sum of revenue (€)")

1. This simple line graph shows how much revenue was accumulated throughout the month.

ggplot(data1, aes(x="", y=prop, fill=Var1)) +
  geom_bar(stat="identity", width=1, color="white") +
  coord_polar("y", start=0) +
  theme_void() + 
  geom_text(aes(y = ypos, label = proc), color = "white", size=6) +
  scale_fill_brewer(palette="Dark2", name = "Terminal in the sender's city") + 
  labs(title = "Percentage of cargo in regards to redirecting each to a terminal")

2. I used a pie chart to compare two binary values. In here, we see that only around a third of all the cargo was redirected to a terminal in the sender’s country.

ggplot(data, aes(x = day, y = Value, fill = day)) +  
  ggtitle("Revenue distribution per day of the week") + 
  geom_boxplot(outlier.colour="black",outlier.shape=16,outlier.size=3, notch=F) + 
  labs(x = "", y = "Revenue (€)", fill = "Day of the week") +
  theme_minimal()

3. In the boxplots, the revenue distribution for each day of the week is presented. It appears, that the median revenue value is almost the same for each day, at around 200.

ggplot(data2, aes(x = Value, y = UnitTypeName, color = UnitTypeName)) +
  ggtitle("Average revenue in different unit types") + 
  geom_point(size = 4) + 
  labs(x = "Revenue (€)", y = "Unit Type") +
  scale_color_brewer(palette = "Dark2", name = "Unit Type Name")

4. Lastly, I used a simple dot plot to represent the average revenue in different unit types.