Name: Obesity Or CVD Risk (Classify/Regressor/Cluster)
Creator: Kaggle
License: https://creativecommons.org/licenses/by-sa/4.0/

About this Dataset

Obesity Or CVD Risk (Classify/Regressor/Cluster)

The data consist of the estimation of obesity levels in people from the countries of Mexico, Peru and Colombia, with ages between 14 and 61 and diverse eating habits and physical condition , data was collected using a web platform with a survey where anonymous users answered each question, then the information was processed obtaining 17 attributes and 2111 records.
The attributes related with eating habits are: Frequent consumption of high caloric food (FAVC), Frequency of consumption of vegetables (FCVC), Number of main meals (NCP), Consumption of food between meals (CAEC), Consumption of water daily (CH20), and Consumption of alcohol (CALC). The attributes related with the physical condition are: Calories consumption monitoring (SCC), Physical activity frequency (FAF), Time using technology devices (TUE), Transportation used (MTRANS)
variables obtained :
Gender, Age, Height and Weight.

NObesity values are:

•Underweight Less than 18.5
•Normal 18.5 to 24.9
•Overweight 25.0 to 29.9
•Obesity I 30.0 to 34.9
•Obesity II 35.0 to 39.9
•Obesity III Higher than 40

The data contains numerical data and continous data, so it can be used for analysis based on algorithms of classification, prediction, segmentation and association. Data is available in CSV format.

Tables

Obesitydataset

@kaggle.aravindpcoder_obesity_or_cvd_risk_classifyregressorcluster.obesitydataset

106.95 KB
2111 rows
17 columns


CREATE TABLE obesitydataset (
  "gender" VARCHAR,
  "age" DOUBLE,
  "height" DOUBLE,
  "weight" DOUBLE,
  "family_history_with_overweight" VARCHAR,
  "favc" VARCHAR,
  "fcvc" DOUBLE,
  "ncp" DOUBLE,
  "caec" VARCHAR,
  "smoke" VARCHAR,
  "ch2o" DOUBLE,
  "scc" VARCHAR,
  "faf" DOUBLE,
  "tue" DOUBLE,
  "calc" VARCHAR,
  "mtrans" VARCHAR,
  "nobeyesdad" VARCHAR
);