Exotic Foods Consumption Data

Columns

• Age in years: The respondent's age as a whole number.
• Gender: The self-identified gender of the respondent.
• Race: The respondent's race.
• Home location: The continent where the respondent resides.
• Cockroach: Whether the respondent has consumed a cockroach (True/False).
• Sushi: Whether the respondent has consumed sushi (True/False).
• Rocky Mountain oyster: Whether the respondent has consumed a Rocky Mountain oyster (True/False).
• Spam: Whether the respondent has consumed Spam (True/False).
• Cow urine: Whether the respondent has consumed cow urine (True/False).
• Jalapeño: Whether the respondent has consumed a jalapeño (True/False).
• Alligator meat: Whether the respondent has consumed alligator meat (True/False).
• Paper: Whether the respondent has consumed paper (True/False).
• Hawaiian pizza: Whether the respondent has consumed Hawaiian pizza (True/False).
• Pig's trotters: Whether the respondent has consumed pig's trotters (True/False).
• Durian: Whether the respondent has consumed durian (True/False).
• Monkey brains: Whether the respondent has consumed monkey brains (True/False).
• Frog legs: Whether the respondent has consumed frog legs (True/False).
• Caviar: Whether the respondent has consumed caviar (True/False).
• Fugu: Whether the respondent has consumed fugu (pufferfish) (True/False).
• Balut: Whether the respondent has consumed balut (True/False).
• Lutefisk: Whether the respondent has consumed lutefisk (True/False).
• Century egg: Whether the respondent has consumed a century egg (True/False).
• Salo: Whether the respondent has consumed salo (True/False).
• Locusts: Whether the respondent has consumed a locust (True/False).

Distribution

Usage

• Market Research: Analysing food consumption patterns to identify market opportunities for niche or exotic foods.
• Cultural Studies: Investigating how dietary habits differ across various demographic groups, such as age, gender, and location.
• Survey Analysis: Serving as a practical example for learning and applying statistical analysis techniques to survey data.
• Predictive Modelling: Building models to predict the likelihood of a person trying a specific food based on their demographic profile.

Coverage

• Geographic: The survey has a global reach, with the majority of respondents from North America/Central America and Europe.
• Time Range: This is a snapshot from an ongoing survey. The provided data reflects responses collected up to the point of its publication and is expected to be updated daily.
• Demographic: The dataset includes respondents with ages ranging from 9 to 76 years, covering various genders and racial backgrounds.

License

Who Can Use It

• Data Analysts: Can explore correlations between demographics and food choices.
• Food Industry Professionals: Can gain insights into consumer tastes and willingness to try novel food items.
• Sociologists and Researchers: Can study cultural influences on diet and consumption habits.
• Students and Educators: Can use the dataset for projects and teaching materials related to data science and statistics.

Dataset Name Suggestions

• Global Food Consumption Survey
• Have You Eaten This? Survey Responses
• Demographics and Dietary Experiences
• Exotic Foods Consumption Data

Attributes