{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "q3LkhJPJXf_I",
   "metadata": {
    "id": "q3LkhJPJXf_I"
   },
   "source": [
    "# Introduction to Datascience"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "SG-Ms-vcc-c8",
   "metadata": {
    "id": "SG-Ms-vcc-c8"
   },
   "source": [
    "## Goals/Anti-goals"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "WILJ_TMKdDiP",
   "metadata": {
    "id": "WILJ_TMKdDiP"
   },
   "source": [
    "* **Goal**: Provide a tour of several different libraries\n",
    "* **Goal**: Demonstrate the synergy of the \"Python Universe\"\n",
    "* **Goal**: Demonstrate paradigm \"get idea then translate into code\"\n",
    "* **Goal**: Demonstrate paradigm \"write one line, test, then continue\"\n",
    "\n",
    "\n",
    "\n",
    "* **Anti-goal**: Teach specific functions and specific arguments\n",
    "* **Anti-goal**: Confuse you "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "LVwWAoKU9Bej",
   "metadata": {
    "id": "LVwWAoKU9Bej"
   },
   "source": [
    "## Roadmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d14ee735",
   "metadata": {
    "id": "d14ee735"
   },
   "source": [
    "A) Obtain dataset from the internet\n",
    "\n",
    "B) Prepare dataset for analysis with *pandas*\n",
    "\n",
    "C) Cluster dataset with *sklearn*\n",
    "\n",
    "D) Dimensionality reduction with *UMAP*, visualization with *matplotlib*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dxHfLKjM7uWB",
   "metadata": {
    "id": "dxHfLKjM7uWB"
   },
   "source": [
    "## A) Obtain dataset from the internet"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "wwsNF_MA-Vgs",
   "metadata": {
    "id": "wwsNF_MA-Vgs"
   },
   "source": [
    "### Description: "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ZgVpKfcx-Vt7",
   "metadata": {
    "id": "ZgVpKfcx-Vt7"
   },
   "source": [
    "* 23 species\n",
    "\n",
    "* Coincidentally 23 features (columns)\n",
    "\n",
    "* 8124 samples (rows)\n",
    "\n",
    "* 11th column has missing data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "LuKpVG-8-n1T",
   "metadata": {
    "id": "LuKpVG-8-n1T"
   },
   "source": [
    "### Image of dataset:"
   ]
  },
  {
   "attachments": {
    "day_3_lecture_2_image_1.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "31974f1d",
   "metadata": {
    "id": "31974f1d"
   },
   "source": [
    "![day_3_lecture_2_image_1.png](attachment:day_3_lecture_2_image_1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4YawSXAA7yUr",
   "metadata": {
    "id": "4YawSXAA7yUr"
   },
   "source": [
    "## B) Prepare dataset for analysis using pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "NA5HYlwqAg7d",
   "metadata": {
    "id": "NA5HYlwqAg7d"
   },
   "source": [
    "* pandas \n",
    "* library in python\n",
    "* perfect for matrix-like data of mixed types (numbers, strings, etc.)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "Sqk9d-ArAgqt",
   "metadata": {
    "id": "Sqk9d-ArAgqt"
   },
   "source": [
    "### Overall Strategy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "_hrdHELpAgeN",
   "metadata": {
    "id": "_hrdHELpAgeN"
   },
   "source": [
    "0) Get dataset into python\n",
    "\n",
    "1) Deal with missing data (drop column)\n",
    "\n",
    "2) Transform letters into numbers (one-hot encoding)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8zrrcNuBAgP9",
   "metadata": {
    "id": "8zrrcNuBAgP9"
   },
   "source": [
    "### 0) Get dataset into python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "DHa2BsVmAgBt",
   "metadata": {
    "id": "DHa2BsVmAgBt"
   },
   "source": [
    "* get pandas library\n",
    "* get a hard coded address for the file\n",
    "* try a simple usage of read_csv\n",
    "* check our work\n",
    "* update our usage of read_csv and check work again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5f4a863d",
   "metadata": {
    "id": "5f4a863d"
   },
   "outputs": [],
   "source": [
    "# get library\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7fe2177e",
   "metadata": {
    "id": "7fe2177e"
   },
   "outputs": [],
   "source": [
    "# get a hard coded address for the file\n",
    "mushroom_dataset_address='../data/agaricus-lepiota.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c070e60d",
   "metadata": {
    "id": "c070e60d"
   },
   "outputs": [],
   "source": [
    "# try a simple usage of read_csv\n",
    "my_Panda=pd.read_csv(mushroom_dataset_address)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6b527afc",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 417
    },
    "id": "6b527afc",
    "outputId": "6c6e9ebf-905a-4bfd-d22b-90c63211ca04"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p</th>\n",
       "      <th>x</th>\n",
       "      <th>s</th>\n",
       "      <th>n</th>\n",
       "      <th>t</th>\n",
       "      <th>p.1</th>\n",
       "      <th>f</th>\n",
       "      <th>c</th>\n",
       "      <th>n.1</th>\n",
       "      <th>k</th>\n",
       "      <th>...</th>\n",
       "      <th>s.2</th>\n",
       "      <th>w</th>\n",
       "      <th>w.1</th>\n",
       "      <th>p.2</th>\n",
       "      <th>w.2</th>\n",
       "      <th>o</th>\n",
       "      <th>p.3</th>\n",
       "      <th>k.1</th>\n",
       "      <th>s.3</th>\n",
       "      <th>u</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>e</td>\n",
       "      <td>b</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>l</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>g</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>w</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8118</th>\n",
       "      <td>e</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>e</td>\n",
       "      <td>f</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>y</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>b</td>\n",
       "      <td>...</td>\n",
       "      <td>k</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>w</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8123 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      p  x  s  n  t p.1  f  c n.1  k  ... s.2  w w.1 p.2 w.2  o p.3 k.1 s.3  u\n",
       "0     e  x  s  y  t   a  f  c   b  k  ...   s  w   w   p   w  o   p   n   n  g\n",
       "1     e  b  s  w  t   l  f  c   b  n  ...   s  w   w   p   w  o   p   n   n  m\n",
       "2     p  x  y  w  t   p  f  c   n  n  ...   s  w   w   p   w  o   p   k   s  u\n",
       "3     e  x  s  g  f   n  f  w   b  k  ...   s  w   w   p   w  o   e   n   a  g\n",
       "4     e  x  y  y  t   a  f  c   b  n  ...   s  w   w   p   w  o   p   k   n  g\n",
       "...  .. .. .. .. ..  .. .. ..  .. ..  ...  .. ..  ..  ..  .. ..  ..  ..  .. ..\n",
       "8118  e  k  s  n  f   n  a  c   b  y  ...   s  o   o   p   o  o   p   b   c  l\n",
       "8119  e  x  s  n  f   n  a  c   b  y  ...   s  o   o   p   n  o   p   b   v  l\n",
       "8120  e  f  s  n  f   n  a  c   b  n  ...   s  o   o   p   o  o   p   b   c  l\n",
       "8121  p  k  y  n  f   y  f  c   n  b  ...   k  w   w   p   w  o   e   w   v  l\n",
       "8122  e  x  s  n  f   n  a  c   b  y  ...   s  o   o   p   o  o   p   o   c  l\n",
       "\n",
       "[8123 rows x 23 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check our work\n",
    "my_Panda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8b286331",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 417
    },
    "id": "8b286331",
    "outputId": "ce1a27d1-e10e-4468-8ad7-e62d6b81f2c4"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>e</td>\n",
       "      <td>b</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>l</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>g</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>w</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>e</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>e</td>\n",
       "      <td>f</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>y</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>b</td>\n",
       "      <td>...</td>\n",
       "      <td>k</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>w</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8123</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8124 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0  1  2  3  4  5  6  7  8  9   ... 13 14 15 16 17 18 19 20 21 22\n",
       "0     p  x  s  n  t  p  f  c  n  k  ...  s  w  w  p  w  o  p  k  s  u\n",
       "1     e  x  s  y  t  a  f  c  b  k  ...  s  w  w  p  w  o  p  n  n  g\n",
       "2     e  b  s  w  t  l  f  c  b  n  ...  s  w  w  p  w  o  p  n  n  m\n",
       "3     p  x  y  w  t  p  f  c  n  n  ...  s  w  w  p  w  o  p  k  s  u\n",
       "4     e  x  s  g  f  n  f  w  b  k  ...  s  w  w  p  w  o  e  n  a  g\n",
       "...  .. .. .. .. .. .. .. .. .. ..  ... .. .. .. .. .. .. .. .. .. ..\n",
       "8119  e  k  s  n  f  n  a  c  b  y  ...  s  o  o  p  o  o  p  b  c  l\n",
       "8120  e  x  s  n  f  n  a  c  b  y  ...  s  o  o  p  n  o  p  b  v  l\n",
       "8121  e  f  s  n  f  n  a  c  b  n  ...  s  o  o  p  o  o  p  b  c  l\n",
       "8122  p  k  y  n  f  y  f  c  n  b  ...  k  w  w  p  w  o  e  w  v  l\n",
       "8123  e  x  s  n  f  n  a  c  b  y  ...  s  o  o  p  o  o  p  o  c  l\n",
       "\n",
       "[8124 rows x 23 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# update our usage of read_csv and check work again\n",
    "my_Panda=pd.read_csv(mushroom_dataset_address,header=None)\n",
    "my_Panda"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "zLvoSaFoB3KB",
   "metadata": {
    "id": "zLvoSaFoB3KB"
   },
   "source": [
    "### 1) Deal with missing data (drop column)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "975cb3df",
   "metadata": {
    "id": "975cb3df"
   },
   "source": [
    "\n",
    "We need a fast and clear approach\n",
    "\n",
    "*   use the function DataFrame.drop\n",
    "*   check our work\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8704031e",
   "metadata": {
    "id": "8704031e"
   },
   "outputs": [],
   "source": [
    "# use the function DataFrame.drop\n",
    "## labels indicates the \"name\" of the column to drop\n",
    "## axis indicates whether we are dropping from columns or rows (10 exists on both)\n",
    "## inplace means that we are modifying the variable my_Panda instead of getting a result returned\n",
    "my_Panda_column_dropped=my_Panda.drop(labels=11,axis='columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "07463476",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 417
    },
    "id": "07463476",
    "outputId": "921bf7ad-4303-4e09-9403-5d4e2fb74b96"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "      <th>22</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>y</td>\n",
       "      <td>t</td>\n",
       "      <td>a</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>e</td>\n",
       "      <td>b</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>l</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>m</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p</td>\n",
       "      <td>x</td>\n",
       "      <td>y</td>\n",
       "      <td>w</td>\n",
       "      <td>t</td>\n",
       "      <td>p</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>u</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>g</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>w</td>\n",
       "      <td>b</td>\n",
       "      <td>k</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>g</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>e</td>\n",
       "      <td>k</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>n</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>e</td>\n",
       "      <td>f</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>n</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>p</td>\n",
       "      <td>k</td>\n",
       "      <td>y</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>y</td>\n",
       "      <td>f</td>\n",
       "      <td>c</td>\n",
       "      <td>n</td>\n",
       "      <td>b</td>\n",
       "      <td>...</td>\n",
       "      <td>k</td>\n",
       "      <td>w</td>\n",
       "      <td>w</td>\n",
       "      <td>p</td>\n",
       "      <td>w</td>\n",
       "      <td>o</td>\n",
       "      <td>e</td>\n",
       "      <td>w</td>\n",
       "      <td>v</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8123</th>\n",
       "      <td>e</td>\n",
       "      <td>x</td>\n",
       "      <td>s</td>\n",
       "      <td>n</td>\n",
       "      <td>f</td>\n",
       "      <td>n</td>\n",
       "      <td>a</td>\n",
       "      <td>c</td>\n",
       "      <td>b</td>\n",
       "      <td>y</td>\n",
       "      <td>...</td>\n",
       "      <td>s</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>o</td>\n",
       "      <td>p</td>\n",
       "      <td>o</td>\n",
       "      <td>c</td>\n",
       "      <td>l</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8124 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     0  1  2  3  4  5  6  7  8  9   ... 13 14 15 16 17 18 19 20 21 22\n",
       "0     p  x  s  n  t  p  f  c  n  k  ...  s  w  w  p  w  o  p  k  s  u\n",
       "1     e  x  s  y  t  a  f  c  b  k  ...  s  w  w  p  w  o  p  n  n  g\n",
       "2     e  b  s  w  t  l  f  c  b  n  ...  s  w  w  p  w  o  p  n  n  m\n",
       "3     p  x  y  w  t  p  f  c  n  n  ...  s  w  w  p  w  o  p  k  s  u\n",
       "4     e  x  s  g  f  n  f  w  b  k  ...  s  w  w  p  w  o  e  n  a  g\n",
       "...  .. .. .. .. .. .. .. .. .. ..  ... .. .. .. .. .. .. .. .. .. ..\n",
       "8119  e  k  s  n  f  n  a  c  b  y  ...  s  o  o  p  o  o  p  b  c  l\n",
       "8120  e  x  s  n  f  n  a  c  b  y  ...  s  o  o  p  n  o  p  b  v  l\n",
       "8121  e  f  s  n  f  n  a  c  b  n  ...  s  o  o  p  o  o  p  b  c  l\n",
       "8122  p  k  y  n  f  y  f  c  n  b  ...  k  w  w  p  w  o  e  w  v  l\n",
       "8123  e  x  s  n  f  n  a  c  b  y  ...  s  o  o  p  o  o  p  o  c  l\n",
       "\n",
       "[8124 rows x 22 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check our work\n",
    "my_Panda_column_dropped"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "571f60f5",
   "metadata": {
    "id": "571f60f5"
   },
   "source": [
    "### 2) Transform letters into numbers\n",
    "Why?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4Z_zGeHNFclR",
   "metadata": {
    "id": "4Z_zGeHNFclR"
   },
   "source": [
    "#### Background: clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "NhEuktO5FQBR",
   "metadata": {
    "id": "NhEuktO5FQBR"
   },
   "source": [
    "8,124 samples -> which samples come from the same species?\n",
    "\n",
    "Clustering: Group datapoints based on location"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5fs3RjPFRsg",
   "metadata": {
    "id": "e5fs3RjPFRsg"
   },
   "source": [
    "#### Image"
   ]
  },
  {
   "attachments": {
    "day_3_lecture_2_image_2.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "f554839f",
   "metadata": {
    "id": "f554839f"
   },
   "source": [
    "source:: https://miro.medium.com/max/1200/1*rw8IUza1dbffBhiA4i0GNQ.png\n",
    "\n",
    "![day_3_lecture_2_image_2.png](attachment:day_3_lecture_2_image_2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dPmeeKomFmkE",
   "metadata": {
    "id": "dPmeeKomFmkE"
   },
   "source": [
    "#### One-hot encoding"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "slN1DmmEFl-K",
   "metadata": {
    "id": "slN1DmmEFl-K"
   },
   "source": [
    "To cluster, we need to put data points in spatial locations\n",
    "\n",
    "Right now each datapoint has 23 letters\n",
    "\n",
    "We use the strategy of \"one-hot encoding\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01M5UqV5FuVp",
   "metadata": {
    "id": "01M5UqV5FuVp"
   },
   "source": [
    "#### image"
   ]
  },
  {
   "attachments": {
    "day_3_lecture_2_image_3.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "e45e4841",
   "metadata": {
    "id": "e45e4841"
   },
   "source": [
    "source: https://miro.medium.com/max/875/1*ggtP4a5YaRx6l09KQaYOnw.png\n",
    "\n",
    "![day_3_lecture_2_image_3.png](attachment:day_3_lecture_2_image_3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "QyV1HNCrF2Pq",
   "metadata": {
    "id": "QyV1HNCrF2Pq"
   },
   "source": [
    "#### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8e9686e4",
   "metadata": {
    "id": "8e9686e4"
   },
   "outputs": [],
   "source": [
    "# one hot encoding\n",
    "## this time, we got a copy of the dataset back instead of operating on the variable my_Panda directly\n",
    "## we specify what to encode using 'data'\n",
    "## we provide a list of columns using my_Panda.columns - we could have also type the list [0,1,2,...,20,21,22]\n",
    "my_Panda_dummies=pd.get_dummies(data=my_Panda_column_dropped,columns=my_Panda_column_dropped.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7cef832c",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 437
    },
    "id": "7cef832c",
    "outputId": "926cbaac-5b6f-477b-b3c0-9c0a7e60d8cb"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0_e</th>\n",
       "      <th>0_p</th>\n",
       "      <th>1_b</th>\n",
       "      <th>1_c</th>\n",
       "      <th>1_f</th>\n",
       "      <th>1_k</th>\n",
       "      <th>1_s</th>\n",
       "      <th>1_x</th>\n",
       "      <th>2_f</th>\n",
       "      <th>2_g</th>\n",
       "      <th>...</th>\n",
       "      <th>21_s</th>\n",
       "      <th>21_v</th>\n",
       "      <th>21_y</th>\n",
       "      <th>22_d</th>\n",
       "      <th>22_g</th>\n",
       "      <th>22_l</th>\n",
       "      <th>22_m</th>\n",
       "      <th>22_p</th>\n",
       "      <th>22_u</th>\n",
       "      <th>22_w</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8123</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8124 rows × 114 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      0_e  0_p  1_b  1_c  1_f  1_k  1_s  1_x  2_f  2_g  ...  21_s  21_v  21_y  \\\n",
       "0       0    1    0    0    0    0    0    1    0    0  ...     1     0     0   \n",
       "1       1    0    0    0    0    0    0    1    0    0  ...     0     0     0   \n",
       "2       1    0    1    0    0    0    0    0    0    0  ...     0     0     0   \n",
       "3       0    1    0    0    0    0    0    1    0    0  ...     1     0     0   \n",
       "4       1    0    0    0    0    0    0    1    0    0  ...     0     0     0   \n",
       "...   ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...   ...   ...   ...   \n",
       "8119    1    0    0    0    0    1    0    0    0    0  ...     0     0     0   \n",
       "8120    1    0    0    0    0    0    0    1    0    0  ...     0     1     0   \n",
       "8121    1    0    0    0    1    0    0    0    0    0  ...     0     0     0   \n",
       "8122    0    1    0    0    0    1    0    0    0    0  ...     0     1     0   \n",
       "8123    1    0    0    0    0    0    0    1    0    0  ...     0     0     0   \n",
       "\n",
       "      22_d  22_g  22_l  22_m  22_p  22_u  22_w  \n",
       "0        0     0     0     0     0     1     0  \n",
       "1        0     1     0     0     0     0     0  \n",
       "2        0     0     0     1     0     0     0  \n",
       "3        0     0     0     0     0     1     0  \n",
       "4        0     1     0     0     0     0     0  \n",
       "...    ...   ...   ...   ...   ...   ...   ...  \n",
       "8119     0     0     1     0     0     0     0  \n",
       "8120     0     0     1     0     0     0     0  \n",
       "8121     0     0     1     0     0     0     0  \n",
       "8122     0     0     1     0     0     0     0  \n",
       "8123     0     0     1     0     0     0     0  \n",
       "\n",
       "[8124 rows x 114 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check our work\n",
    "my_Panda_dummies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "q4GP2qUu8BBr",
   "metadata": {
    "id": "q4GP2qUu8BBr"
   },
   "source": [
    "## C) Cluster the data with sklearn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "kNUAiEUKZDVb",
   "metadata": {
    "id": "kNUAiEUKZDVb"
   },
   "source": [
    "### Background: "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8kbl2Tcp2vcB",
   "metadata": {
    "id": "8kbl2Tcp2vcB"
   },
   "source": [
    "In the above image, data had 2 dimensions so we could visually assess clustering\n",
    "\n",
    "For n-dimensional case We turn to a clustering algorithm.\n",
    "\n",
    "Within sklearn we choose the algorithm K-means.\n",
    "\n",
    "Because time constraints we treat KMeans like a black box"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "r6nmnsRC2waQ",
   "metadata": {
    "id": "r6nmnsRC2waQ"
   },
   "source": [
    "#### Image: Black box"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "uvacn4Ck2wtp",
   "metadata": {
    "id": "uvacn4Ck2wtp"
   },
   "source": [
    "Black box: give input, get output, dont ask how\n",
    "\n",
    "Step 1) \n",
    "* Parameters: arguments that our chosen algorithm requires\n",
    "\n",
    "Step 2) \n",
    "* Input: my_Panda_dummies\n",
    "* Output: list of labels \n"
   ]
  },
  {
   "attachments": {
    "day_3_lecture_2_image_4.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "88c55435",
   "metadata": {
    "id": "88c55435"
   },
   "source": [
    "![day_3_lecture_2_image_4.png](attachment:day_3_lecture_2_image_4.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9384f3f7",
   "metadata": {
    "id": "9384f3f7"
   },
   "source": [
    "#### Giving parameters to K-means black box\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9533eb26",
   "metadata": {},
   "source": [
    "KMeans *requires* the number of clusters (23)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6546f16b",
   "metadata": {
    "id": "6546f16b"
   },
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "50af6505",
   "metadata": {
    "id": "50af6505"
   },
   "outputs": [],
   "source": [
    "#declare our black box by calling KMeans\n",
    "##we give the black box/calculator the name my_KMeans_tool\n",
    "my_KMeans_tool=KMeans(n_clusters=23)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7a544e76",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7a544e76",
    "outputId": "e34c889d-b7d0-4b97-9c1d-467513a243ba"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KMeans(n_clusters=23)\n"
     ]
    }
   ],
   "source": [
    "print(my_KMeans_tool)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5f490567",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 178
    },
    "id": "5f490567",
    "outputId": "f65b7e4d-2d1c-48e6-9cbb-f187e40f4b9a"
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'KMeans' object has no attribute 'labels_'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-39-9d53e9cea4d7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#we havent told my_KMeans_tool about our data yet, so we expect this to fail\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmy_KMeans_tool\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlabels_\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m: 'KMeans' object has no attribute 'labels_'"
     ]
    }
   ],
   "source": [
    "#we havent told my_KMeans_tool about our data yet, so we expect this to fail\n",
    "print(my_KMeans_tool.labels_)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d3d25c0",
   "metadata": {
    "id": "2d3d25c0"
   },
   "source": [
    "#### Black Box Operation\n",
    "sklearn (often) relies on the function \"fit_transform\" to connect the data with the algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7ba3d4f7",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7ba3d4f7",
    "outputId": "1bd989da-d1d1-44c4-aa44-00da79be6fb3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3.77102947, 4.54519275, 4.26060768, ..., 3.7859389 , 3.64273399,\n",
       "        5.07033858],\n",
       "       [3.58657502, 5.01968512, 3.73980095, ..., 3.05505046, 3.88277768,\n",
       "        4.85197554],\n",
       "       [3.44952673, 5.08565682, 3.87835876, ..., 3.41565026, 3.96295279,\n",
       "        5.11940752],\n",
       "       ...,\n",
       "       [4.51655119, 5.20279094, 4.51386752, ..., 4.65474668, 4.1459457 ,\n",
       "        5.16801058],\n",
       "       [4.4688548 , 2.70655571, 4.72434593, ..., 4.61880215, 3.59594233,\n",
       "        4.76532615],\n",
       "       [4.59105719, 5.20279094, 4.44565956, ..., 4.72581563, 4.1672875 ,\n",
       "        5.26387057]])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#tell my_KMeans_tool about our data\n",
    "## we ignore the output\n",
    "## notice how sklearn's KMeans flawlessly accepts a panda as input\n",
    "my_KMeans_tool.fit_transform(X=my_Panda_dummies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "4216fe7f",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "4216fe7f",
    "outputId": "d0f8b230-5cc0-48b0-833b-8544ea6d6873"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 4 11 11 ... 10  8 10]\n",
      "8124\n"
     ]
    }
   ],
   "source": [
    "#now we see that we have the labels that expected\n",
    "print(my_KMeans_tool.labels_)\n",
    "print(len(my_KMeans_tool.labels_))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a4f7815",
   "metadata": {
    "id": "8a4f7815"
   },
   "source": [
    "#### Done?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "yQ4L6Cu37ytw",
   "metadata": {
    "id": "yQ4L6Cu37ytw"
   },
   "source": [
    "\n",
    "Got a label for every data point.\n",
    "\n",
    "Philosophical viewpoint: We did perfectly, the algorithm worked exactly as intended\n",
    "\n",
    "Are our clusters meaningful?\n",
    "\n",
    "Hard to say. We could try to relate our clusters to some external dataset. We don't have that here.\n",
    "\n",
    "Lets try a visualization.\n",
    "\n",
    "In our case, we are going to:\n",
    "* Take our 114 dimensional dataset (114 columns)\n",
    "* Reduce the dimensionality to 2.\n",
    "* Plot all datapoints, getting (x,y) from dimensionality reduction and colors from clustering label.\n",
    "\n",
    "If each color of datapoints is separated from every other cluster, then we have some assurance that our dataset is \"robustly clusterable\". That's it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0280f3d",
   "metadata": {
    "id": "a0280f3d"
   },
   "source": [
    "## Dimensionality Reduction and Visualization\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "RxsMsdz48-BS",
   "metadata": {
    "id": "RxsMsdz48-BS"
   },
   "source": [
    "### Naive approach:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "GwiSRVLb85TB",
   "metadata": {
    "id": "GwiSRVLb85TB"
   },
   "source": [
    "choose two columns and drop all of the rest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "KhBBD_VQ-07t",
   "metadata": {
    "id": "KhBBD_VQ-07t"
   },
   "source": [
    "### Which algorithm?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "Y1dJ_se9-0w1",
   "metadata": {
    "id": "Y1dJ_se9-0w1"
   },
   "source": [
    "PCA, PLS-DA, t-SNE, UMAP\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "qTGIJ8Qq-0jd",
   "metadata": {
    "id": "qTGIJ8Qq-0jd"
   },
   "source": [
    "demonstrate the bredth/synergy of the python language, so we choose UMAP (not in sklearn)\n",
    "\n",
    "Even though UMAP is not in sklearn, the authors of UMAP wrote it in such a way that it \"works like\" sklearn functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cNqjOULP-0S3",
   "metadata": {
    "id": "cNqjOULP-0S3"
   },
   "source": [
    "### Strategy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98e1c8f2",
   "metadata": {
    "id": "98e1c8f2"
   },
   "source": [
    "* create our UMAP black box\n",
    "* operate that black box on our dataset\n",
    "* obtain a 2-d coordinate pair for every datapoint\n",
    "* plot those pairs, with the color of the datapoint reflecting the clustering label from KMeans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bnr1h1ph_QdX",
   "metadata": {
    "id": "bnr1h1ph_QdX"
   },
   "source": [
    "### Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "8a98590e",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 370
    },
    "id": "8a98590e",
    "outputId": "ef72cc44-8261-479e-a333-cb8f2358a0df"
   },
   "outputs": [],
   "source": [
    "# create our black box\n",
    "## import our library\n",
    "import umap\n",
    "\n",
    "## declare a couple of parameters that we wont get into\n",
    "n_neighbors=10\n",
    "min_dist=0.1\n",
    "n_components=2\n",
    "metric='euclidean'\n",
    "\n",
    "\n",
    "##just like last time, we declare a \"UMAP calculator\" and send a couple of parameters\n",
    "my_UMAP=umap.UMAP(n_neighbors=n_neighbors,min_dist=min_dist,n_components=n_components,metric=metric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c2da8e81",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "c2da8e81",
    "outputId": "828c486d-5b26-434a-e6d9-fa0fea915637"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UMAP(dens_frac=0.0, dens_lambda=0.0, n_neighbors=10)\n"
     ]
    }
   ],
   "source": [
    "print(my_UMAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d857b5dc",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "d857b5dc",
    "outputId": "0122a955-ce4f-4e83-989f-0b6f82008df4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ -7.6440673 , -12.353603  ],\n",
       "       [ -0.26427558,   8.624089  ],\n",
       "       [ -0.47456995,   7.971237  ],\n",
       "       ...,\n",
       "       [ 11.546015  ,  -6.2244453 ],\n",
       "       [ 19.653965  ,   8.905327  ],\n",
       "       [ 11.451685  ,  -6.2179003 ]], dtype=float32)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# again, we use fit transform to inform our calculator of our dataset \n",
    "## again, notice how it flawlessly accepts a panda\n",
    "## this time, we actually want the thing that gets spit back out\n",
    "my_UMAP.fit_transform(my_Panda_dummies)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "969f072e",
   "metadata": {
    "id": "969f072e"
   },
   "source": [
    "We redo to capture the 2D coordinate list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "cd347372",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cd347372",
    "outputId": "8bf8cba3-7627-4cff-cfea-cae17650e342"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8124\n"
     ]
    }
   ],
   "source": [
    "# 2) and 3)\n",
    "my_numpy_2d=my_UMAP.fit_transform(my_Panda_dummies)\n",
    "print(len(my_numpy_2d))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "k6JZWFo1Esrs",
   "metadata": {
    "id": "k6JZWFo1Esrs"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "f80a7b39",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 264
    },
    "id": "f80a7b39",
    "outputId": "39bac2d6-092c-46ee-9237-31ae635d15cc"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#4)\n",
    "#scatter plot takes\n",
    "#list of x coordinates\n",
    "#list of y coordinates\n",
    "plt.scatter(\n",
    "    my_numpy_2d[:,0],\n",
    "    my_numpy_2d[:,1]\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c8f6ea55",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 264
    },
    "id": "c8f6ea55",
    "outputId": "7cf0e5c7-65c6-4388-ce90-b8a41dc2d481"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#4) redo with arguments to make the color in accordance wiht the KMeans cluster labels\n",
    "\n",
    "\n",
    "\n",
    "#an opacity parameter\n",
    "plt.scatter(\n",
    "    my_numpy_2d[:,0],\n",
    "    my_numpy_2d[:,1],\n",
    "    #a label list\n",
    "    c=my_KMeans_tool.labels_,\n",
    "    #a color bar (literally the rainbox)\n",
    "    cmap='gist_rainbow',\n",
    "    #make the points mildly transparent so we can see generalities\n",
    "    alpha=0.2\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81d99400",
   "metadata": {
    "id": "81d99400"
   },
   "source": [
    "#### Observations\n",
    "Our dimensionality reduction technique independently produced 23 visually-discernible clusters, but those clusters only partially agree with the KMeans clustering"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0747962",
   "metadata": {
    "id": "f0747962"
   },
   "source": [
    "#### Bonus: Dim Reduction with PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "55d546a4",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 548
    },
    "id": "55d546a4",
    "outputId": "09d24d87-e69b-400b-f5e9-705c93d1dd7c"
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(8124, 114)\n",
      "(8124,)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from sklearn.decomposition import PCA\n",
    "my_PCA=PCA()\n",
    "my_PCAd_coordinates=my_PCA.fit_transform(my_Panda_dummies)\n",
    "plt.scatter(range(len(my_PCA.explained_variance_ratio_)),my_PCA.explained_variance_ratio_)\n",
    "plt.show()\n",
    "print(my_PCAd_coordinates.shape)\n",
    "print(my_PCAd_coordinates[:,0].shape)\n",
    "plt.scatter(my_PCAd_coordinates[:,0],my_PCAd_coordinates[:,1],c=my_KMeans_tool.labels_,cmap='gist_rainbow',alpha=0.2)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [
    "kNUAiEUKZDVb",
    "r6nmnsRC2waQ",
    "9384f3f7",
    "2d3d25c0",
    "8a4f7815",
    "a0280f3d",
    "RxsMsdz48-BS",
    "KhBBD_VQ-07t",
    "cNqjOULP-0S3",
    "bnr1h1ph_QdX",
    "81d99400",
    "f0747962"
   ],
   "name": "Day3_Lecture.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}