{
"cells": [
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"cell_type": "markdown",
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"source": [
"___\n",
"\n",
" 
\n",
"___"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# K Nearest Neighbors Project - Solution\n",
"\n",
"Welcome to the KNN Project! This will be a simple project very similar to the lecture, except you'll be given another data set. Go ahead and just follow the directions below.\n",
"## Import Libraries\n",
"**Import pandas,seaborn, and the usual libraries.**"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get the Data\n",
"** Read the 'KNN_Project_Data csv file into a dataframe **"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"df = pd.read_csv('KNN_Project_Data')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Check the head of the dataframe.**"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [
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