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In today's fast-paced and competitive educational environment, understanding the factors that influence student success is more important than ever. Just like the transport system in a bustling city like London must adapt to serve its residents, schools and educators must adapt to meet the needs of students. In this project, we will take a deep dive into a dataset containing rich details about various aspects of student life, such as hours studied, sleep patterns, attendance, and more, to uncover what truly impacts exam performance.

The dataset we'll be working with includes a wide range of factors influencing student performance. By analyzing this data, we'll be able to identify key drivers of success and provide insights that could help students, teachers, and policymakers make informed decisions. The table we'll use for this project is called student_performance and includes the following data:

ColumnDefinitionData type
attendancePercentage of classes attendedfloat
extracurricular_activitiesParticipation in extracurricular activitiesvarchar (Yes, No)
sleep_hoursAverage number of hours of sleep per nightfloat
tutoring_sessionsNumber of tutoring sessions attended per monthinteger
teacher_qualityQuality of the teachersvarchar (Low, Medium, High)
exam_scoreFinal exam scorefloat

You will execute SQL queries to answer three questions, as listed in the instructions.

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DataFrameas
df
variable
SELECT *
FROM student_performance
LIMIT 10;
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DataFrameas
avg_exam_score_by_study_and_extracurricular
variable
[38]
-- avg_exam_score_by_study_and_extracurricular
-- Edited query
SELECT hours_studied, AVG(exam_score) as avg_exam_score
FROM student_performance
WHERE hours_studied > 10 AND extracurricular_activities = 'Yes'
GROUP BY hours_studied
ORDER BY hours_studied DESC, avg_exam_score;
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DataFrameas
avg_exam_score_by_hours_studied_range
variable
-- avg_exam_score_by_hours_studied_range
-- Add solution code below 
SELECT AVG(exam_score) as avg_exam_score,
CASE
	When hours_studied <= 5 THEN '1-5 hours'
	When hours_studied > 5 AND hours_studied <= 10 THEN '6-10 hours'
	When hours_studied > 10 AND hours_studied <= 15 THEN '11-15 hours'
	ELSE '16+ hours'
	END AS hours_studied_range
FROM student_performance
GROUP BY hours_studied_range
ORDER BY avg_exam_score DESC;
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DataFrameas
student_exam_ranking
variable
-- student_exam_ranking
-- Add solution code below 
SELECT attendance, hours_studied, sleep_hours, tutoring_sessions, 
DENSE_RANK() Over(ORDER BY exam_score DESC) AS exam_rank
FROM student_performance
ORDER BY exam_rank ASC
Limit 30;