The Finance Project - SQL
The INTRODUCTION
For this project, I worked with historical data from the International Development Association (IDA). This financial institution provides concessional loans and grants to the world's poorest developing countries so that they can meet their development needs.
The assignment calls for a summary of financial data using fundamental SQL commands. I installed, configured and used Xampp to import the data and I used MySQL to run the queries for the analysis. Alternatively, you can also use the online cloud database: bit.io to upload the data and run the queries.
The DATA
The dataset is available in CSV format from The World Bank's website and consists of 1.12 million rows and 30 columns. Each row represents a credit or a grant provided to a member country.
You can access the data here: IDA Statement Of Credits and Grants - Historical Data.
These focus of this project was to examine the IDA's transactions and provide insights. The main questions posed were:
The ANALYSIS
To answer the first question: show us all transactions from Nicaragua and their status, I wrote the following query:
I used a CTE (common table expression) to be able to perform calculations with the aggregate functions.
Breaking the query down, I displayed the country, the status and the number of transactions for each status as well as the total transactions for Nicaragua and the percentage for each credit status. This is the result:
You will see that there are many different statuses, which gives an insight into the length and kind of relationship that Nicaragua has with the IDA.
Next, I looked into how many transactions per country. I executed the following query:
This query returned a considerable amount of rows. The top portion of the results are shown here:
Because of how many rows returned, I wanted to know exactly how many countries were included in these results. I ran a quick query to find that answer:
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I was surprised to find out that there were 137 countries listed in the results! As a reminder, these are countries that are considered the world's poorest. Knowing this, I wondered how many countries there are in the world. Most people wouldn't know the exact number without looking it up. A quick Google search tells me there are 195 recognized countries. With 137 countries reportedly using the World Bank for assistance, that's 70% of the world - which seems higher than it should be. Diving a bit deeper into the data, I found that there were a lot of entries that listed a Region instead of the Country. Example: Eastern Africa or Central America.
Moving on to the next question, we needed to find out what is the average service charge rate for a loan. This was accomplished by using the AVG and ROUND aggregate functions:
The results show the following:
Next, we needed to have see which country is owing the most to the IDA:
The results of this query showed that India has the largest amount outstanding at $793,256,127.64.
Finally, we needed to know what were the top five projects from Chad. To do this, I created a query that displayed the project name and the original principal amount. Then sorting and grouping by the project name and amounts loaned:
These are the results:
The number one project that Chad borrowed money for was to support their Energy Access Scale Up Project, which aims to increase access to electricity and clean cooking solutions.
The INSIGHTS
THANK YOU!
If you got this far, thank you so much for taking the time and I welcome any and all feedback as I believe the feedback is a gift! Data analysis is a new venture for me, and I'm excited to share what I've been learning - please follow me Lisette Mohammed to stay connected on this data journey!
Nice work Lisette M. . Agree with Ashley, Carbon does make it look really neat!
I like your use of Carbon - made your queries look nice and neat!
I liked you project Lisette! Your images were super clear, and the content was straightforward and easy to read.
Good job Lisette 👏💪👏