SQL - Student mental health - data exploration

Does going to university in a different country affect your mental health? A Japanese international university surveyed its students in 2018 and published a study the following year that was approved by several ethical and regulatory boards.

The study found that international students have a higher risk of mental health difficulties than the general population, and that social connectedness (belonging to a social group) and acculturative stress (stress associated with joining a new culture) are predictive of depression.

Explore the students data using PostgreSQL to find out if you would come to a similar conclusion for international students and see if the length of stay is a contributing factor.

Description of helpful columns.

Field Name	Description
`inter_dom`	Types of students (international or domestic)
`japanese_cate`	Japanese language proficiency
`english_cate`	English language proficiency
`academic`	Current academic level (undergraduate or graduate)
`age`	Current age of student
`stay`	Current length of stay in years
`todep`	Total score of depression (PHQ-9 test)
`tosc`	Total score of social connectedness (SCS test)
`toas`	Total score of acculturative stress (ASISS test)

DataFrameavailable as

students

variable

-- Select all columns from students.csv
SELECT * 
FROM 'students.csv';

DataFrameavailable as

df

variable

-- Check of total number of records
SELECT COUNT(*) AS total_records
FROM students

DataFrameavailable as

df

variable

-- Check how many students are domestic students and how many are international
SELECT inter_dom, COUNT(inter_dom) AS count_inter_dom
FROM students
GROUP BY inter_dom

DataFrameavailable as

df

variable

-- Overview of all columns about International students
SELECT * 
FROM students
WHERE inter_dom LIKE 'Inter';

DataFrameavailable as

df

variable

-- Overview of all columns about International students
SELECT * 
FROM students
WHERE inter_dom LIKE 'Dom';

DataFrameavailable as

df

variable


SELECT 
	MIN(todep) AS min_phq, MAX(todep) AS max_phq, ROUND(AVG(todep), 2) AS avg_phq,
 	MIN(tosc) AS min_scs, MAX(tosc) AS max_scs, ROUND(AVG(tosc), 2) AS avg_scs,
 	MIN(toas) AS min_as, MAX(toas) AS max_as, ROUND(AVG(toas), 2) AS avg_as
FROM students;

DataFrameavailable as

df

variable

SELECT 
	MIN(todep) AS min_phq, MAX(todep) AS max_phq, ROUND(AVG(todep), 2) AS avg_phq,
 	MIN(tosc) AS min_scs, MAX(tosc) AS max_scs, ROUND(AVG(tosc), 2) AS avg_scs,
 	MIN(toas) AS min_as, MAX(toas) AS max_as, ROUND(AVG(toas), 2) AS avg_as
FROM students
WHERE inter_dom LIKE 'Dom';

DataFrameavailable as

df

variable

SELECT 
	MIN(todep) AS min_phq, MAX(todep) AS max_phq, ROUND(AVG(todep), 2) AS avg_phq,
 	MIN(tosc) AS min_scs, MAX(tosc) AS max_scs, ROUND(AVG(tosc), 2) AS avg_scs,
 	MIN(toas) AS min_as, MAX(toas) AS max_as, ROUND(AVG(toas), 2) AS avg_as
FROM students
WHERE inter_dom LIKE 'Inter';

DataFrameavailable as

df

variable

SELECT
	stay,
	ROUND(AVG(todep), 2) AS average_phq,
 	ROUND(AVG(tosc), 2) AS average_scs,
 	ROUND(AVG(toas), 2) AS average_as
FROM students
WHERE inter_dom LIKE 'Inter'
GROUP BY stay,
ORDER BY stay DESC;