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 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)

DataFrameas

students

variable

-- Run this code to save the CSV file as students
SELECT stay_cate , count(*) as NUMBER_OF_STUDENT, avg(todep) as averege_depression
FROM 'students.csv'
where stay_cate is not null
group by stay_cate

DataFrameas

df1

variable

--select  todep as "Total score of depression"   ,round(100/(247/count(*)),2) as "totalNumber"  from 'students.csv' where  inter_dom='Inter' group by  todep   having  todep  order by  todep  desc

--SELECT todep , stay from 'students.csv'  group by todep order by stay desc

select stay_cate , count(*) as number_of_peale_that_stay , avg(todep) as avegr_depres_for_stay
from 'students.csv'
where region != 'JAP'
group by stay_cate
order by stay_cate desc
--select * from 'students.csv' where stay=10

Based on the chart above, the average depression rate for each stay category for international students does not show a significant variance. Therefore, we can conclude that the length of stay is not a primary factor in determining depression levels among students.

DataFrameas

df2

variable

select count(*) as number_of_students from 'students.csv'

DataFrameas

df

variable

select academic as "Current academic level",count(*) as number_of_student , round(avg(todep),2)  as avrege_todepression , round(avg(tosc),2) as "averege  of social connectedness",round(avg(toas),2) as "averege of acculturative stress" from 'students.csv'where inter_dom is not null group by academic order by academic desc

DataFrameas

df3

variable

select academic as type_of_student ,count(*) as number_of_student , round(avg(todep),2)  as avrege_todepression , round(avg(tosc),2) as "averege  of social connectedness",round(avg(toas),2) as "averege of acculturative stress" from 'students.csv' where inter_dom='Inter' group by academic

DataFrameas

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.csv'   WHERE inter_dom = 'Inter' group by stay order by stay desc limit 9

DataFrameas

df4

variable