Dataset

This dataset was created by Letitia Clarke

Released under Data files © Original Authors

Contents

Purpose

This data came from a survey of students. The purpose of the survey was to identify attitudes and habits regarding food consumption at school and outside of school.

Description of Variables

• Gender: What gender do you identify as?
• Boarding: Day or Boarding?
• Grade: What grade are you in?
• Athlete: Do you consider yourself an athlete?
• Activities: Are you participating in any of the following activities this season?
• DHBreakfast: How many days a week do you eat breakfast in the dining hall (including brunch on Saturday and Sunday)?
• NDHBreakfast: How many days a week do you eat breakfast but not in the dining hall?
• BClass: Would you be more likely to eat breakfast if you could eat it in class?
• DHBoxes: On average, how many boxes of food do you eat per meal at the dining hall?
• NDHBoxes: How many boxes do you take from the dining hall to eat later?
• NDHMeals: How many meals a week do you eat in the dorm or student center?
• Nutrition: On a scale of 0 to 5, how aware are you of the nutritional values of the food you eat?
• Money: On average, how much money do spend on food outside of the dining hall per week?

The Daily Food & Nutrition Dataset provides a detailed record of everyday food consumption paired with essential nutritional values. It is designed to support data analysis, health monitoring, and machine-learning applications related to diet, wellness, and personalized nutrition.

This dataset captures a variety of food items along with their macronutrient and micronutrient composition, enabling users to explore dietary patterns, build predictive health models, and perform nutritional optimization. It is suitable for projects involving calorie tracking, nutrient recommendation systems, diet classification, or exploratory data analysis within the field of nutrition science.

Key Features

• Food Item & Category Identifies each food entry and its general classification (e.g., fruit, vegetable, grain, beverage, snack, etc.).

• Nutritional Components Includes major nutrients that influence health and energy intake:

  • Calories (kcal)
  • Protein (g)
  • Carbohydrates (g)
  • Fat (g)
  • Fiber (g)
  • Sugars (g)
  • Sodium (mg)
  • Cholesterol (mg)

• Meal Context The Meal_Type column specifies whether the food was consumed during breakfast, lunch, dinner, or as a snack — useful for temporal or behavioral pattern analysis.

• Hydration Tracking Water_Intake (ml) allows hydration monitoring alongside nutritional consumption, enabling more holistic dietary assessments.

Potential Use Cases

• Building ML models for calorie prediction or nutrient estimation
• Designing personalized diet recommendations
• Meal-type classification and consumption pattern analysis
• Nutritional health dashboards or tracking applications
• Correlation studies between nutrient intake and hydration patterns

This dataset aims to serve health researchers, data scientists, nutritionists, and enthusiasts who want to analyze or model dietary behavior in a structured, meaningful way.

This dataset is not to be taken seriously. It has been synthetically generated to simulate real-world dietary records and reflects diverse food intake patterns through a randomized data generation process. It includes food categories, meal types, and nutritional values based on general nutritional guidelines and publicly available food databases.

The mean servings/times sugar-sweetened beverages consumed daily by California residents. These data are from the 2013 California Dietary Practices Surveys (CDPS), 2012 California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and 2013 California Children’s Healthy Eating and Exercise Practices Survey (CalCHEEPS). These surveys are now discontinued. Adults, adolescents, and children (with parental assistance) were asked about the sugar-sweetened beverages they drank over the previous 24 hour period. Child/Adolescent: Fruit and vegetable, beverage, and junk food consumption, along with physical activity, sedentary time, active transport, sport participation, school environment, home neighborhood environment, fruit and vegetable access and availability, household/family rules, weight status, school breakfast/lunch participation, attitudes, and beliefs. Adult: Fruit and vegetable, beverage, and junk food consumption, along with physical activity, sedentary time, worksite environment, school environment, home neighborhood environment, fruit and vegetable access and availability, household/family rules, weight status and weight loss practices, and food security. According to the Dietary Guidelines for Americans, 2010, sugar-sweetened beverages provide excess calories and few essential nutrients to the diet and should only be consumed when nutrient needs have been met and without exceeding daily calorie limits.

Percentage of California residents who consumed five or more servings of fruits and vegetables a day. These data are from the 2013 California Dietary Practices Surveys (CDPS), 2012 California Teen Eating, Exercise and Nutrition Survey (CalTEENS), and 2013 California Children’s Healthy Eating and Exercise Practices Survey (CalCHEEPS). These surveys have been discontinued. Adults, adolescents, and children (with parental assistance) were asked about the serving sizes and types of fruits and vegetables they ate over the previous 24 hour period. Child/Adolescent: Fruit and vegetable, beverage, and junk food consumption, along with physical activity, sedentary time, active transport, sport participation, school environment, home neighborhood environment, fruit and vegetable access and availability, household/family rules, weight status, school breakfast/lunch participation, attitudes, and beliefs. Adult: Fruit and vegetable, beverage, and junk food consumption, along with physical activity, sedentary time, worksite environment, school environment, home neighborhood environment, fruit and vegetable access and availability, household/family rules, weight status and weight loss practices, and food security.

Data collected from a survey-based study of the sleeping habits of individuals within the US. This data was conducted as a pilot study to determine whether or not students were satisfied with the survey.

Here is a description of each of the variables contained within the dataset.

• Enough = Do you think that you get enough sleep?
• Hours = On average, how many hours of sleep do you get on a weeknight?
• PhoneReach = Do you sleep with your phone within arms reach?
• PhoneTime = Do you use your phone within 30 minutes of falling asleep?
• Tired = On a scale from 1 to 5, how tired are you throughout the day? (1 being not tired, 5 being very tired)
• Breakfast = Do you typically eat breakfast?