Datasets:
File size: 2,583 Bytes
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STEP 1: Generate 1,000 Student Records and Insert into MongoDB
==============================================================
This script creates a realistic dataset of 1,000 students and
stores them inside MongoDB using the PyMongo library.
"""
import numpy as np
import pandas as pd
from pymongo import MongoClient
def main():
print("==================================================")
print(" STEP 1: GENERATE DATASET & INSERT TO MONGODB ")
print("==================================================")
# Set seed so dataset values are reproducible
np.random.seed(42)
num_records = 1000
# Generate realistic student attributes
student_ids = [f"STU{1001 + i}" for i in range(num_records)]
study_hours = np.round(np.random.uniform(1.0, 9.5, num_records), 1)
attendance = np.round(np.random.uniform(60.0, 99.0, num_records), 1)
previous_marks = np.round(np.random.uniform(40.0, 95.0, num_records), 1)
assignments_score = np.random.randint(4, 11, num_records)
# Calculate realistic final marks with slight noise
noise = np.random.normal(0, 2.5, num_records)
final_marks = (
0.45 * previous_marks +
3.5 * study_hours +
0.25 * attendance +
1.5 * assignments_score +
noise
)
final_marks = np.round(np.clip(final_marks, 30.0, 100.0), 1)
# Combine into a Pandas DataFrame
df = pd.DataFrame({
"student_id": student_ids,
"study_hours": study_hours,
"attendance": attendance,
"previous_marks": previous_marks,
"assignments_score": assignments_score,
"final_marks": final_marks
})
print(f"[+] Generated {len(df)} realistic records.")
# Save a CSV backup
df.to_csv("student_data.csv", index=False)
print("[+] Saved local CSV backup: 'student_data.csv'")
# Connect to MongoDB
print("[+] Connecting to MongoDB on localhost:27017...")
client = MongoClient("mongodb://localhost:27017/")
db = client["student_performance_db"]
collection = db["students"]
# Clear existing data to avoid duplicate inserts on re-runs
collection.delete_many({})
# Convert DataFrame to list of dictionaries for MongoDB insertion
records = df.to_dict(orient="records")
result = collection.insert_many(records)
print(f"[SUCCESS] Inserted {len(result.inserted_ids)} documents into:")
print(" Database : student_performance_db")
print(" Collection : students")
client.close()
if __name__ == "__main__":
main()
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