Facet Jupyter Notebook

facets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "features = [\"Age\", \"Workclass\", \"fnlwgt\", \"Education\", \"Education-Num\", \"Marital Status\",\n",
    "            \"Occupation\", \"Relationship\", \"Race\", \"Sex\", \"Capital Gain\", \"Capital Loss\",\n",
    "            \"Hours per week\", \"Country\", \"Target\"]\n",
    "train_data = pd.read_csv(\n",
    "    \"https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data\",\n",
    "    names=features,\n",
    "    sep=r'\\s*,\\s*',\n",
    "    engine='python',\n",
    "    na_values=\"?\")\n",
    "test_data = pd.read_csv(\n",
    "    \"https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test\",\n",
    "    names=features,\n",
    "    sep=r'\\s*,\\s*',\n",
    "    skiprows=[0],\n",
    "    engine='python',\n",
    "    na_values=\"?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        <facets-dive id=\"elem\" height=\"600\"></facets-dive>\n",
       "        <script>\n",