lmizner / codecademy_eda_diabetes

Utilized exploratory data analysis (EDA) to inform data inspection, cleaning, and validation.

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codecademy_eda_diabetes

EDA: Diagnosing Diabetes

In this project, you’ll imagine you are a data scientist interested in exploring data that looks at how certain diagnostic factors affect the diabetes outcome of women patients.

You will use your EDA skills to help inspect, clean, and validate the data.

Note: This dataset is from the National Institute of Diabetes and Digestive and Kidney Diseases. It contains the following columns:

  • Pregnancies: Number of times pregnant
  • Glucose: Plasma glucose concentration at 2 hours in an oral glucose tolerance test
  • BloodPressure: Diastolic blood pressure
  • SkinThickness: Triceps skinfold thickness
  • Insulin: 2-Hour serum insulin
  • BMI: Body mass index
  • DiabetesPedigreeFunction: Diabetes pedigree function
  • Age: Age (years)
  • Outcome: Class variable (0 or 1)

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Utilized exploratory data analysis (EDA) to inform data inspection, cleaning, and validation.


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