{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"\n",
"
\n",
"___\n",
"Copyright by Pierian Data Inc.\n",
"For more information, visit us at www.pieriandata.com"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Grids"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The Data"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('StudentsPerformance.csv')"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" gender | \n",
" race/ethnicity | \n",
" parental level of education | \n",
" lunch | \n",
" test preparation course | \n",
" math score | \n",
" reading score | \n",
" writing score | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" female | \n",
" group B | \n",
" bachelor's degree | \n",
" standard | \n",
" none | \n",
" 72 | \n",
" 72 | \n",
" 74 | \n",
"
\n",
" \n",
" | 1 | \n",
" female | \n",
" group C | \n",
" some college | \n",
" standard | \n",
" completed | \n",
" 69 | \n",
" 90 | \n",
" 88 | \n",
"
\n",
" \n",
" | 2 | \n",
" female | \n",
" group B | \n",
" master's degree | \n",
" standard | \n",
" none | \n",
" 90 | \n",
" 95 | \n",
" 93 | \n",
"
\n",
" \n",
" | 3 | \n",
" male | \n",
" group A | \n",
" associate's degree | \n",
" free/reduced | \n",
" none | \n",
" 47 | \n",
" 57 | \n",
" 44 | \n",
"
\n",
" \n",
" | 4 | \n",
" male | \n",
" group C | \n",
" some college | \n",
" standard | \n",
" none | \n",
" 76 | \n",
" 78 | \n",
" 75 | \n",
"
\n",
" \n",
"
\n",
"