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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)
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DataFrameas
students
variable
-- Run this code to save the CSV file as students
SELECT * 
FROM 'students.csv';

Start by counting all of the records in the data

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DataFrameas
df
variable
SELECT COUNT(*)
FROM 'students.csv';

Then count all records per student type to see how the records are categorized and scored

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DataFrameas
df1
variable
SELECT inter_dom, COUNT(inter_dom) AS student_type
FROM 'students.csv'
GROUP BY inter_dom;

Filter the data to see how it differs between the student types

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DataFrameas
df2
variable
SELECT academic, age, stay, japanese, todep, tosc, apd, ahome
FROM 'students.csv'
WHERE inter_dom = 'Inter';

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

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DataFrameas
df3
variable
SELECT inter_dom,
	ROUND(AVG(todep),2) AS average_depression, 
	ROUND(AVG(tosc),2) AS average_social_connectedness,
	ROUND(AVG(toas),2) AS average_acculterative_stress
FROM 'students.csv'
GROUP BY inter_dom;

Repeat this to summarize the data for international students only

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DataFrameas
df4
variable
SELECT 
	ROUND(AVG(todep),2) AS average_depression, 
	ROUND(AVG(tosc),2) AS average_social_connectedness,
	ROUND(AVG(toas),2) AS average_acculterative_stress
FROM 'students.csv'
WHERE inter_dom = 'Inter';