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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
-- Start coding here...
--Explore and understand the data
select count(*) as total_records
from 'students.csv'
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DataFrameas
df
variable
-- Explore data per type of students
select inter_dom, count(*) as count_inter_dom
from 'students.csv'
group by inter_dom
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DataFrameas
df
variable
--Filter to understand the data for each student type
-- explore international students
select *
from 'students.csv'
where inter_dom = 'Inter'
--limit 10
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DataFrameas
df
variable
-- explore domestic students
select *
from 'students.csv'
where inter_dom = 'Dom'
--limit 10
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DataFrameas
df
variable
-- explore students with unknown status
select *
from 'students.csv'
where inter_dom is null

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DataFrameas
df
variable
--Query the summary statistics of the diagnostics scores for all students
-- for phq test
select min(todep) as min_phq, max(todep) as max_phq , round(avg(todep),2) as avg_phq
from 'students.csv'
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DataFrameas
df
variable
-- for scs test
select min(tosc) as min_scs, max(tosc) as max_scs , round(avg(tosc),2) as avg_scs
from 'students.csv'
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DataFrameas
df
variable
-- for as test
select min(toas) as min_as, max(toas) as max_as , round(avg(toas),2) as avg_as
from 'students.csv'
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DataFrameas
df
variable
--Summarize the data for international students only
-- for phq test
select min(todep) as min_phq, max(todep) as max_phq , round(avg(todep),2) as avg_phq
from 'students.csv'
where inter_dom = 'Inter'
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DataFrameas
df
variable
-- for scs test
select min(tosc) as min_scs, max(tosc) as max_scs , round(avg(tosc),2) as avg_scs
from 'students.csv'
where inter_dom = 'Inter'
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DataFrameas
df
variable
-- for as test
select min(toas) as min_as, max(toas) as max_as , round(avg(toas),2) as avg_as
from 'students.csv'
where inter_dom = 'Inter'