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Project: Analyzing Students' Mental Health in SQL

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.

Here is a data description of the columns you may find helpful.

Field NameDescription
inter_domTypes of students (international or domestic)
japanese_cateJapanese language proficiency
english_cateEnglish language proficiency
academicCurrent academic level (undergraduate or graduate)
ageCurrent age of student
stayCurrent length of stay in years
todepTotal score of depression (PHQ-9 test)
toscTotal score of social connectedness (SCS test)
toasTotal score of acculturative stress (ASISS test)
Spinner
DataFrameavailable as
students
variable
-- Run this code to save the CSV file as students
SELECT * 
FROM 'students.csv';
Spinner
DataFrameavailable as
df1
variable
-- Start by counting all of the records in the data,
SELECT COUNT(*) AS number_of_students
FROM students;
Spinner
DataFrameavailable as
df2
variable
-- then all records per student type to see how the records are categorized 
-- and scored.
SELECT *
FROM students
WHERE inter_dom = 'Inter';
Spinner
DataFrameavailable as
df3
variable
-- then all records per student type to see how the records are categorized 
-- and scored.
SELECT *
FROM students
WHERE inter_dom = 'Dom';
Spinner
DataFrameavailable as
df4
variable
-- Find the summary statistics of the diagnostic tests for all students using -- aggregate functions, rounding the test scores to two decimal places,
-- remembering to use aliases.

SELECT ROUND(SUM(todep), 2) AS sum_todep, ROUND(AVG(todep), 2) AS avg_todep, ROUND(MIN(todep), 2) AS min_todep, ROUND(MAX(todep), 2) AS max_todep, ROUND(SUM(tosc), 2) AS sum_tosc, ROUND(AVG(tosc), 2) AS avg_tosc, ROUND(MIN(tosc), 2) AS min_tosc, ROUND(MAX(tosc), 2) AS max_tosc, ROUND(SUM(toas), 2) AS sum_toas, ROUND(AVG(toas), 2) AS avg_toas, ROUND(MIN(toas), 2) AS min_toas, ROUND(MAX(toas), 2) AS max_toas
FROM students;
Spinner
DataFrameavailable as
df5
variable
-- Repeat this to summarize the data for international students only.
SELECT ROUND(SUM(todep), 2) AS sum_todep, ROUND(AVG(todep), 2) AS avg_todep, ROUND(MIN(todep), 2) AS min_todep, ROUND(MAX(todep), 2) AS max_todep, ROUND(SUM(tosc), 2) AS sum_tosc, ROUND(AVG(tosc), 2) AS avg_tosc, ROUND(MIN(tosc), 2) AS min_tosc, ROUND(MAX(tosc), 2) AS max_tosc, ROUND(SUM(toas), 2) AS sum_toas, ROUND(AVG(toas), 2) AS avg_toas, ROUND(MIN(toas), 2) AS min_toas, ROUND(MAX(toas), 2) AS max_toas
FROM students
WHERE inter_dom = 'Inter';
Spinner
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 = 'Inter'
GROUP BY stay
ORDER BY stay DESC;