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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';
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DataFrameas
df
variable
-- Explore and understand the data
-- #1 count the number of records
SELECT COUNT(*)
FROM students;
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DataFrameas
df1
variable
-- Explore and understand the data
-- #2 Grouping by inter_dom to see how many international and domestic students
SELECT inter_dom, COUNT(inter_dom)
FROM students
GROUP BY inter_dom
ORDER BY 2 desc;
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DataFrameas
df2
variable
-- Filter to undestand the data for each student type
--#1 For internationl students
SELECT *
FROM students
WHERE inter_dom = 'Inter';
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DataFrameas
df3
variable
-- Filter to undestand the data for each student type
--#2 For domestic students
SELECT *
FROM students
WHERE inter_dom = 'Dom';
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DataFrameas
df4
variable
-- Filter to undestand the data for each student type
--#1 For status in null in column inter_dom
SELECT *
FROM students
WHERE inter_dom is null;
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DataFrameas
df5
variable
-- Check the summary statistics of the diagnostics scores for all students
-- todep, tosc, toas

SELECT MIN(todep) AS min_phq, 
MAX(todep) AS max_phq, 
ROUND(AVG(todep)) AS avg_phq,
MIN(tosc) AS min_scs,
MAX(tosc) AS max_scs,
ROUND(AVG(todep)) AS avg_scs,
MIN(toas) AS min_as,
MAX(toas) AS max_as,
ROUND(AVG(toas)) AS avg_as
FROM students;
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DataFrameas
df6
variable
-- Check the summary statistics of the diagnostics scores for internaltional students only
-- todep, tosc, toas

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(todep), 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 = 'Inter';
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DataFrameas
df7
variable
-- See if the impact of length of stay affects the test results for international students

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;