Data analysis

We provide here some basic elements about the data set and descriptive statistics on some variables of interest.

  • First we load the data
  • second we print a summary

We loaded the data set and compile the report on 2024-10-21

Summary statistics

Here are some summary statistics of the export value (Stat_Value variable), all products combined:

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    98.9   159.6   336.7   303.4   443.6   492.8

The data set contains 88 observations, and 16 variables.

Here is a list of all variables available in the data set:

##  [1] "X"                   "Reg_Date"            "Type"               
##  [4] "CP4"                 "Stat_Value"          "IMPORT_COUNTRY"     
##  [7] "IMPORT_REGION"       "EXPORT_COUNTRY"      "EXPORT_REGION"      
## [10] "Principle_Exports"   "Principle_ReExports" "Principle_Imports"  
## [13] "Year"                "Month"               "Day"                
## [16] "epsilon"

Type of exports

The variable Principle_Export list all the types of goods exported from Vanuatu. There are 10 different goods exported. Let’s have the list of all these goods.

##  [1] "Beef"             "Coffee"           "Vanilla"          "Copra"           
##  [5] "Kava"             "Coconut Oil"      "Cocoa"            "Alcoholic Drinks"
##  [9] "Cowhides"         "Wood"

Main Exports by type of goods

As a table

It could be nicer to have this as a table:

Principle_Exports

total

Alcoholic Drinks

14,908.72

Wood

4,765.27

Kava

2,699.67

Coffee

1,340.77

Coconut Oil

1,051.49

Cocoa

957.56

Beef

409.04

Cowhides

247.46

Vanilla

167.25

Copra

148.90

As a graphic:

Since we have a limited number of goods, a bar chart would probably describe the data in a very good way. We follow here some good practices in terms of data visualization:

  • The bar chart is horizontal to facilitate the reading of the labels for each good
  • The bar chart is ordered to follow the data (largest on top)

Some extensions on this dynamic report

Selection of the Year

The previous analysis was done for all years. Imagine now the same report but for any year in [2000, 2010]. let’s pick a year in the code chunck below!

we have now selected the year 2009, let’s see the new report!

As a table

We use the same table as before. Maybe that could be a function later ;-).

Principle_Exports

total

Alcoholic Drinks

1,264.08

Coconut Oil

404.34

Wood

367.30

Vanilla

167.25

Cowhides

141.75

As expected, the graphic shows the difference with the