# Beginners Prediction Task — Data

来源：https://www.kaggle.com/competitions/beginners-prediction-task/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

The Student GPA Prediction Competition dataset contains data on over 400 students. The data set includes information on the students' demographics, academic performance, and other factors. The data set is divided into two parts: a training set and a test set. The training set contains data students and is used to train machine learning models. The test set contains data students and is used to evaluate the performance of the machine learning models.

The data set includes the following features:

Gender: The student's gender.
Ethnicity: The student's ethnicity.
Religion: The student's religion.
State of origin: The student's state of origin.
Age: The student's age.
Hobby: The student's hobby.
School type: The type of school the student attends.
Parental education level: The highest level of education attained by the student's parents.
Extracurricular activity: The student's extracurricular activities.
Learning disability: Whether the student has a learning disability.
School location: The location of the student's school.
Tutoring/mentoring program: Whether the student participates in a tutoring or mentoring program.
Parental involvement level: The level of parental involvement in the student's education.
Bullying experience: Whether the student has been bullied.
Study time: The number of hours per week the student studies.
Attendance percentage: The student's attendance percentage.
Self-motivation level: The student's self-motivation level.
Study environment rating: The student's study environment rating.
Stress level: The student's stress level.
Parental support rating: The student's parental support rating.
Note-taking habits: The student's note-taking habits.
Number of extracurricular activities participated: The number of extracurricular activities the student participates in.
Number of leadership roles held: The number of leadership roles the student holds.
Teacher quality rating: The student's teacher quality rating.
Number of school resources available: The number of school resources available to the student.
Peer interaction level: The student's peer interaction level.
Exam maths: The student's exam maths score.
Exam english: The student's exam english score.
Exam social science: The student's exam social science score.
GPA: The student's GPA.
The data set is available for download from the Kaggle website.

### Data Description

The Data Description file provides more detailed information about the features in the dataset. The file includes the following information for each featurSample Submission
The Sample Submission file provides an example of the format that the submissions should be in.

### Conclusion
The Student GPA Prediction Competition dataset is a valuable resource for learning about the factors that contribute to student success. The data could be used to develop new interventions and programs to help students succeed in school. I hope you will participate in the competition!



## Files

*   **train.csv** - the training set
*   **test.csv** - the test set
*   **sample_submission.csv** - a sample submission file in the correct format
*   **metaData.csv** - supplemental information about the data

## Columns

*   `example_id` - random 8 character
*   `gpa` - float
*   etc.