Food Allergy & Intolerance Dataset

📂 Dataset for Predicting Food Allergies & Intolerance Effects

📌 Overview

This dataset contains data related to food allergies and intolerances. It includes key features such as age, gender, symptoms, food type consumed, IgE levels, and allergy history, helping in predictive modeling for food allergy detection and reaction severity assessment.

This dataset is designed for Exploratory Data Analysis (EDA), Classification, and Regression to predict:

(1) Whether a person is allergic to a specific food item (Classification)
(2) The severity of allergic reactions (Regression)

📑 Dataset Information

Total Rows: 10,000
Total Columns: 11
Target Variable: Allergic (1 = Yes, 0 = No)

📊 Features & Column Descriptions

Column Name	Data Type	Description
Age	Integer	Age of the individual (5 - 80 years)
Gender	Categorical	Gender of the individual (Male, Female, Other)
Family_History	Categorical	Whether family has a history of allergies (Yes/No)
Previous_Reaction	Categorical	Past allergic reaction severity (None, Mild, Moderate, Severe)
Symptoms	Categorical	Common allergic symptoms (Skin rash, Swelling, Nausea, Breathing issues, No symptoms)
Food_Type	Categorical	Type of food consumed (Dairy, Nuts, Seafood, Gluten, Eggs)
Food_Frequency	Integer	Frequency of food consumption (times per month)
Medical_Conditions	Categorical	Existing conditions (Asthma, Eczema, None)
IgE_Levels	Float	Immunoglobulin E (IgE) levels (higher levels indicate allergic responses)
Severity_Score	Integer	Severity score (0 = no reaction, 10 = extreme reaction)
Allergic	Binary (0/1)	Target variable: 1 = Allergic, 0 = Not Allergic

📌 Potential Use Cases

✔ Exploratory Data Analysis (EDA) – Understanding the relationship between food, allergies, and medical history.
✔ Predictive Modeling – Machine learning models for allergy prediction.
✔ Classification Tasks – Identify allergic individuals based on symptoms and food type.
✔ Regression Tasks – Estimate reaction severity based on IgE levels and past reactions.
✔ Healthcare Insights – Study food allergies in different demographics.

🖥️ How to Use the Dataset

Download the CSV file and load it into Python:

import pandas as pd
df = pd.read_csv("food_allergy_dataset.csv")

Explore the dataset:
```
df.head()
df.info()
df.describe()
```
Perform Feature Engineering (e.g., encoding categorical variables)
Train a Machine Learning Model (e.g., Logistic Regression, Decision Tree, Random Forest, or Neural Networks)
Evaluate Model Performance (Accuracy, Precision, Recall, RMSE)

📂 Download the Dataset

You can access the dataset here

📜 License & Citation

This dataset is synthetically generated for academic and research purposes.
Feel free to use it for your projects, but please cite this repository when using it.