Utilizing research data collected from university students, we performed a data science analysis on the effects on students' mental health based on their CGPA (Cumulative Grade point average).
In this analysis we will identify possible correlations or causations in the dataset regarding the wellness of university students' mental health in correspondance with their CGPA.
In order to make the data compilable by Jupyter Notebook, the datatypes of the dataset were adjusted. The original values were unchanged, only the data types. Below is a key to the values for each of the columns within the Kaggle dataset.
Male = 0
Female = 1
1 = Freshman
2 = Sophomore
3 = Junior
4 = Senior
0 = 0 - 1.99
1 = 2.00 - 2.49
2 = 2.50 - 2.99
3 = 3.00 - 3.49
4 = 3.50 - 4.00
Marital_status, Do_you_have_Depression, Do_you_have_Anxiety, Do_you_have_Panic_attack, Did_you_seek_any_specialist_for_a_treatment
0 = No
1 = Yes
Student Mental Health Dataset provided by Harsh Sharma, MD Shariful Islam, and Marilia Prata
Intro to Machine Learning Course on Kaggle
K-Means Clustering with Python