{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd \n", "import matplotlib.pyplot as plt\n", "import scipy.stats as stats\n", "import numpy as np\n", "data=pd.read_csv('diabetes.csv')\n", "originaldata=data\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | Pregnancies | \n", "Glucose | \n", "BloodPressure | \n", "SkinThickness | \n", "Insulin | \n", "BMI | \n", "DiabetesPedigreeFunction | \n", "Age | \n", "Outcome | \n", "
|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "6 | \n", "148 | \n", "72 | \n", "35 | \n", "0 | \n", "33.6 | \n", "0.627 | \n", "50 | \n", "1 | \n", "
| 1 | \n", "1 | \n", "85 | \n", "66 | \n", "29 | \n", "0 | \n", "26.6 | \n", "0.351 | \n", "31 | \n", "0 | \n", "
| 2 | \n", "8 | \n", "183 | \n", "64 | \n", "0 | \n", "0 | \n", "23.3 | \n", "0.672 | \n", "32 | \n", "1 | \n", "
| 3 | \n", "1 | \n", "89 | \n", "66 | \n", "23 | \n", "94 | \n", "28.1 | \n", "0.167 | \n", "21 | \n", "0 | \n", "
| 4 | \n", "0 | \n", "137 | \n", "40 | \n", "35 | \n", "168 | \n", "43.1 | \n", "2.288 | \n", "33 | \n", "1 | \n", "