Project: Analyze International Debt Statistics

It's not that we humans only take debts to manage our necessities. A country may also take debt to manage its economy. For example, infrastructure spending is one costly ingredient required for a country's citizens to lead comfortable lives. The World Bank is the organization that provides debt to countries.

In this notebook, we are going to analyze international debt data collected by The World Bank. The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories. We are going to find the answers to questions like:

What is the total amount of debt that is owed by the countries listed in the dataset?
Which country owns the maximum amount of debt and what does that amount look like?
What is the average amount of debt owed by countries across different debt indicators?

Below is a snapshot of the database you will be working with:

country_name	country_code	indicator_name	indicator_code	debt
Afghanistan	AFG	"Disbursements on external debt, long-term (DIS, current US$)"	DT.DIS.DLXF.CD	72894453.7
Afghanistan	AFG	"Interest payments on external debt, long-term (INT, current US$)"	DT.INT.DLXF.CD	53239440.1
Afghanistan	AFG	"PPG, bilateral (AMT, current US$)"	DT.AMT.BLAT.CD	61739336.9
Afghanistan	AFG	"PPG, bilateral (DIS, current US$)"	DT.DIS.BLAT.CD	49114729.4
Afghanistan	AFG	"PPG, bilateral (INT, current US$)"	DT.INT.BLAT.CD	39903620.1
Afghanistan	AFG	"PPG, multilateral (AMT, current US$)"	DT.AMT.MLAT.CD	39107845
Afghanistan	AFG	"PPG, multilateral (DIS, current US$)"	DT.DIS.MLAT.CD	23779724.3
Afghanistan	AFG	"PPG, multilateral (INT, current US$)"	DT.INT.MLAT.CD	13335820
Afghanistan	AFG	"PPG, official creditors (AMT, current US$)"	DT.AMT.OFFT.CD	100847181.9
Afghanistan	AFG	"PPG, official creditors (DIS, current US$)"	DT.DIS.OFFT.CD	72894453.7

You will execute SQL queries to answer six questions, as listed in the instructions.

DataFrameas

num_distinct_countries

variable

SELECT COUNT(DISTINCT country_code) AS total_distinct_countries
  FROM international_debt;

DataFrameas

distinct_debt_indicators

variable

SELECT DISTINCT indicator_code AS distinct_debt_indicators
  FROM international_debt
 ORDER BY indicator_code;

DataFrameas

total_debt

variable

SELECT ROUND((SUM(debt)/1000000), 2) AS total_debt
  FROM international_debt;

DataFrameas

highest_debt_country

variable

SELECT country_name,
	   SUM(debt) AS total_debt
  FROM international_debt 
 GROUP BY country_name
 ORDER BY total_debt DESC
 LIMIT 1;

DataFrameas

avg_debt_per_indicator

variable

SELECT indicator_code AS debt_indicator,
	   indicator_name,
	   AVG(debt) AS average_debt
  FROM international_debt 
 GROUP BY indicator_code,
 		  indicator_name
 ORDER BY average_debt DESC
 LIMIT 10;

DataFrameas

highest_principal_repayment

variable

SELECT international_debt.country_name, 
       international_debt.indicator_name
  FROM international_debt
 WHERE debt = (SELECT MAX(debt)
                 FROM international_debt
                WHERE indicator_code='DT.AMT.DLXF.CD');