npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

@liquid-carrot/data.pima-indians-diabetes

v1.0.2

Published

A dataset template

Downloads

21

Readme

Pima Indians Diabetes Dataset

The Pima Indians Diabetes Dataset involves predicting the onset of diabetes within 5 years in Pima Indians given medical details.

It is a binary (2-class) classification problem. The number of observations for each class is not balanced. There are 768 observations with 8 input variables and 1 output variable. Missing values are believed to be encoded with zero values. The variable names are as follows:

  1. Number of times pregnant.
  2. Plasma glucose concentration a 2 hours in an oral glucose tolerance test.
  3. Diastolic blood pressure (mm Hg).
  4. Triceps skinfold thickness (mm).
  5. 2-Hour serum insulin (mu U/ml).
  6. Body mass index (weight in kg/(height in m)^2).
  7. Diabetes pedigree function.
  8. Age (years).
  9. Class variable (0 or 1).

The baseline performance of predicting the most prevalent class is a classification accuracy of approximately 65%. Top results achieve a classification accuracy of approximately 77%.

A sample of the first 5 rows is listed below.

CSV

6,148,72,35,0,33.6,0.627,50,1
1,85,66,29,0,26.6,0.351,31,0
8,183,64,0,0,23.3,0.672,32,1
1,89,66,23,94,28.1,0.167,21,0
0,137,40,35,168,43.1,2.288,33,1

JSON

[
  {
    "pregnancies": "6",
    "plasma glucose concentration": "148",
    "diastolic blood pressure": "72",
    "triceps skinfold thickness": "35",
    "insulin": "0",
    "body mass index": "33.6",
    "diabetes pedigree function": "0.627",
    "age": "50",
    "diabetic": "1"
  }, {
    "pregnancies": "1",
    "plasma glucose concentration": "85",
    "diastolic blood pressure": "66",
    "triceps skinfold thickness": "29",
    "insulin": "0",
    "body mass index": "26.6",
    "diabetes pedigree function": "0.351",
    "age": "31",
    "diabetic": "0"
  }, {
    "pregnancies": "8",
    "plasma glucose concentration": "183",
    "diastolic blood pressure": "64",
    "triceps skinfold thickness": "0",
    "insulin": "0",
    "body mass index": "23.3",
    "diabetes pedigree function": "0.672",
    "age": "32",
    "diabetic": "1"
  }, {
    "pregnancies": "1",
    "plasma glucose concentration": "89",
    "diastolic blood pressure": "66",
    "triceps skinfold thickness": "23",
    "insulin": "94",
    "body mass index": "28.1",
    "diabetes pedigree function": "0.167",
    "age": "21",
    "diabetic": "0"
  }, {
    "pregnancies": "0",
    "plasma glucose concentration": "137",
    "diastolic blood pressure": "40",
    "triceps skinfold thickness": "35",
    "insulin": "168",
    "body mass index": "43.1",
    "diabetes pedigree function": "2.288",
    "age": "33",
    "diabetic": "1"
  }
]