Unsupervised_Machine_Learning_report_UsArrests.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This data set contains statistics, in arrests per 100,000 residents,\n",
    "for assault, murder, and rape in each of the 50 US states in 1973. Also given is the\n",
    "percent of the population living in urban areas\n",
    "To see a breakdown of the data titles: https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/USArrests.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1112,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import relevant libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        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>Murder</th>\n",
       "      <th>Assault</th>\n",
       "      <th>UrbanPop</th>\n",
       "      <th>Rape</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>13.20</td>\n",
       "      <td>236</td>\n",
       "      <td>58</td>\n",
       "      <td>21.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>10.00</td>\n",
       "      <td>263</td>\n",
       "      <td>48</td>\n",
       "      <td>44.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>8.10</td>\n",
       "      <td>294</td>\n",
       "      <td>80</td>\n",
       "      <td>31.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>8.80</td>\n",
       "      <td>190</td>\n",
       "      <td>50</td>\n",
       "      <td>19.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>9.00</td>\n",
       "      <td>276</td>\n",
       "      <td>91</td>\n",
       "      <td>40.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Murder  Assault  UrbanPop  Rape\n",
       "City                                       \n",
       "Alabama      13.20      236        58 21.20\n",
       "Alaska       10.00      263        48 44.50\n",
       "Arizona       8.10      294        80 31.00\n",
       "Arkansas      8.80      190        50 19.50\n",
       "California    9.00      276        91 40.60"
      ]
     },
     "execution_count": 1113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read data from file 'UsArrests.csv'\n",
    "df = pd.read_csv(\"UsArrests.csv\",index_col='City') # Reading data, making 'City' index(as it is the only column with str)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of cases: 50 Number of features: 4\n"
     ]
    }
   ],
   "source": [
    "print('Number of cases: {} Number of features: {}'.format(df.shape[0],df.shape[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Murder</th>\n",
       "      <td>7.79</td>\n",
       "      <td>4.36</td>\n",
       "      <td>0.80</td>\n",
       "      <td>17.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assault</th>\n",
       "      <td>170.76</td>\n",
       "      <td>83.34</td>\n",
       "      <td>45.00</td>\n",
       "      <td>337.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UrbanPop</th>\n",
       "      <td>65.54</td>\n",
       "      <td>14.47</td>\n",
       "      <td>32.00</td>\n",
       "      <td>91.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rape</th>\n",
       "      <td>21.23</td>\n",
       "      <td>9.37</td>\n",
       "      <td>7.30</td>\n",
       "      <td>46.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           mean   std   min    max\n",
       "Murder     7.79  4.36  0.80  17.40\n",
       "Assault  170.76 83.34 45.00 337.00\n",
       "UrbanPop  65.54 14.47 32.00  91.00\n",
       "Rape      21.23  9.37  7.30  46.00"
      ]
     },
     "execution_count": 1115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To set the decimal precision at 2 points in float format\n",
    "pd.set_option('display.float_format', lambda x: '%.2f' % x) \n",
    "\n",
    "#The describe function give us insight into the statistical properties of the columns\n",
    "stats = df.describe()\n",
    "selected_stats = stats.loc[[\"mean\",\"std\",\"min\",\"max\"]].transpose() #select relevant rows\n",
    "selected_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1116,
   "metadata": {},
   "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>missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Murder</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assault</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UrbanPop</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rape</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          missing\n",
       "Murder          0\n",
       "Assault         0\n",
       "UrbanPop        0\n",
       "Rape            0"
      ]
     },
     "execution_count": 1116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count missing values\n",
    "missing = df.isnull().sum()\n",
    "relevant_missing = pd.DataFrame(missing, columns=[\"missing\"])\n",
    "relevant_missing\n",
    "# No values are missing, no action is required"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 50 entries, Alabama to Wyoming\n",
      "Data columns (total 4 columns):\n",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   Murder    50 non-null     float64\n",
      " 1   Assault   50 non-null     int64  \n",
      " 2   UrbanPop  50 non-null     int64  \n",
      " 3   Rape      50 non-null     float64\n",
      "dtypes: float64(2), int64(2)\n",
      "memory usage: 2.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# It is often useful to determine the type of each variable.\n",
    "df.info() # Examines types"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To visualise the distribution of the observations for each feature, we plot a histogram using Pandas's ```.hist()``` function:\n",
    "* Documentation: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.hist.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1118,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histograms will give a general idea on the distribution of crimes/arrests committed throughout the USA\n",
    "# Plot histograms\n",
    "histograms = df.hist(color='black', grid=False, figsize=(15, 10)) #This can also be done for each column individually by calling hist on that column\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1119,
   "metadata": {},
   "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>missing</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Murder</th>\n",
       "      <td>0</td>\n",
       "      <td>7.79</td>\n",
       "      <td>4.36</td>\n",
       "      <td>0.80</td>\n",
       "      <td>17.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Assault</th>\n",
       "      <td>0</td>\n",
       "      <td>170.76</td>\n",
       "      <td>83.34</td>\n",
       "      <td>45.00</td>\n",
       "      <td>337.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UrbanPop</th>\n",
       "      <td>0</td>\n",
       "      <td>65.54</td>\n",
       "      <td>14.47</td>\n",
       "      <td>32.00</td>\n",
       "      <td>91.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rape</th>\n",
       "      <td>0</td>\n",
       "      <td>21.23</td>\n",
       "      <td>9.37</td>\n",
       "      <td>7.30</td>\n",
       "      <td>46.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          missing   mean   std   min    max\n",
       "Murder          0   7.79  4.36  0.80  17.40\n",
       "Assault         0 170.76 83.34 45.00 337.00\n",
       "UrbanPop        0  65.54 14.47 32.00  91.00\n",
       "Rape            0  21.23  9.37  7.30  46.00"
      ]
     },
     "execution_count": 1119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create summary table\n",
    "frames = [relevant_missing,selected_stats]\n",
    "summary = pd.concat(frames, axis=1)\n",
    "summary.rename(columns = {0:\"missing\"}, inplace = True)\n",
    "summary.to_csv('summary.csv', index=True) \n",
    "summary"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean for Assault is much higher than any other category, meaning Assault is much more common than Rape and Murder.\n",
    "Murder has the lowest statistics, meaning it is the least common.\n",
    "UrbanPop is a percentage of the urban population which is hoswn to range from 32% to 91%."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correlation Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1120,
   "metadata": {},
   "outputs": [],
   "source": [
    "cities = df.index\n",
    "corr_df = df.corr()\n",
    "labels =corr_df.columns\n",
    "\n",
    "correlations = corr_df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 1121,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask_ut=np.triu(np.ones(corr_df.shape)).astype(np.bool_)\n",
    "sns.heatmap(corr_df, vmin=-1, vmax=1, annot=True,fmt='.2g', mask=mask_ut, cmap=\"coolwarm\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the plot, there is a linear correlation between strongly correlated variables: those coloured in either dark red or dark blue. Variables which are positively correlated are red: an increase in one corresponds to an increase in the other, while negatively correlated variables are blue: a decrease in one means an increase in the other."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At a glance one can see that all the variables, except one pair (UrbanPop and Murder), have a positive correlation. This suggests that if there is a high rate of one kind of crime in an area the likelihood of other kinds of crime rates being high is expected.\n",
    "Murder and UrbanPop have the weakest correlation (0.07).\n",
    "Assault and Murder have the strongest positive correlation (0.8).\n",
    "The most moderate correlation is between Rape and UrbanPop (0.41).\n",
    "Assault and UrbanPop have a weak positive correlation (0.26).\n",
    "Rape and Murder have a moderately strong positive correlation (0.56).\n",
    "Assault and Rape have a strong positive correlation (0.67).\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overall this shows that this data is a poor candidate for a PCA as there are not many variables that have strong negative and\n",
    "positive correlations with each other."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PCA\n",
    "Principal Components Analysis (PCA) is a method for finding the underlying variables (i.e. principal components) that best differentiate the observations by determining the directions along which your data points are most spread out. Since the determination of the principal components is based on finding the direction that maximises the variance, variables with variance that are much higher than the other variables tend to dominate the analysis purely due to their scale. PCA is a dimensionality reduction techinque which is useful when we have a lot of variables, and need to reduce these. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1122,
   "metadata": {},
   "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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>64.80</td>\n",
       "      <td>11.45</td>\n",
       "      <td>-2.49</td>\n",
       "      <td>2.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>92.83</td>\n",
       "      <td>17.98</td>\n",
       "      <td>20.13</td>\n",
       "      <td>-4.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>124.07</td>\n",
       "      <td>-8.83</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>-4.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>18.34</td>\n",
       "      <td>16.70</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>107.42</td>\n",
       "      <td>-22.52</td>\n",
       "      <td>6.75</td>\n",
       "      <td>-2.81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                0      1     2     3\n",
       "City                                \n",
       "Alabama     64.80  11.45 -2.49  2.41\n",
       "Alaska      92.83  17.98 20.13 -4.09\n",
       "Arizona    124.07  -8.83 -1.69 -4.35\n",
       "Arkansas    18.34  16.70  0.21 -0.52\n",
       "California 107.42 -22.52  6.75 -2.81"
      ]
     },
     "execution_count": 1122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.set_printoptions(precision=2)\n",
    "\n",
    "# select features without standardising\n",
    "X = df.values\n",
    "\n",
    "# create PCA object\n",
    "pca = PCA()\n",
    "\n",
    "# obtain components\n",
    "X_trans = pca.fit_transform(X)\n",
    "\n",
    "# transform the components into a pandas data frame\n",
    "df_pca = pd.DataFrame(X_trans, index=df.index)\n",
    "# This is to include the city name as the rownames in the PC's\n",
    "df_pca.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1123,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Standard deviation: [83.73 14.21  6.49  2.48]\n"
     ]
    }
   ],
   "source": [
    "std = df_pca.describe().transpose()[\"std\"]\n",
    "print(f\"Standard deviation: {std.values}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Proportion of Variance Explained: [9.66e-01 2.78e-02 5.80e-03 8.49e-04]\n"
     ]
    }
   ],
   "source": [
    "print(f\"Proportion of Variance Explained: {pca.explained_variance_ratio_}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1125,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cumulative Proportion: [7011.11 7213.11 7255.22 7261.38]\n"
     ]
    }
   ],
   "source": [
    "print(f\"Cumulative Proportion: {np.cumsum(pca.explained_variance_)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1126,
   "metadata": {},
   "outputs": [],
   "source": [
    "def biplot(score,coeff,labels=None,points=None):\n",
    "    xs = score[:,0]\n",
    "    ys = score[:,1]\n",
    "    n = coeff.shape[0]\n",
    "    scalex = 1.0/(xs.max() - xs.min())\n",
    "    scaley = 1.0/(ys.max() - ys.min())\n",
    "\n",
    "    fig, ax = plt.subplots()    \n",
    "\n",
    "    ax.scatter(xs * scalex,ys * scaley,s=5)\n",
    "\n",
    "    for i in range(0,len(xs)):\n",
    "        txt = cities[i]\n",
    "        ax.annotate(txt, (xs[i]* scalex, ys[i]* scaley))\n",
    "\n",
    "    for i in range(n):\n",
    "        ax.arrow(0, 0, coeff[i,0], coeff[i,1],color = 'r',alpha = 0.5)\n",
    "        if labels is None:\n",
    "            ax.text(coeff[i,0]* 1.15, coeff[i,1] * 1.15, \"Var\"+str(i+1), color = 'green', ha = 'center', va = 'center')\n",
    "        else:\n",
    "            ax.text(coeff[i,0]* 1.15, coeff[i,1] * 1.15, labels[i], color = 'g', ha = 'center', va = 'center')\n",
    " \n",
    "    plt.xlabel(\"PC1\")\n",
    "    plt.ylabel(\"PC2\")\n",
    "    plt.grid()\n",
    "\n",
    "    # Adapted from: https://ostwalprasad.github.io/machine-learning/PCA-using-python.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "biplot(X_trans[:,0:2],np.transpose(pca.components_[0:2, :]),list(labels),list(cities))\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each point on a biplot is the projected observation, transformed from the original data. The importance of each feature is indicated by the length of the arrows on the biplot. This corresponds to the magnitude of the values in the eigenvectors. From this biplot, we see that Assault and UrbanPop are the most important features as the arrows to each of these dominate the biplot.\n",
    "\n",
    "This information can also be quantified as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1128,
   "metadata": {},
   "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>Features</th>\n",
       "      <th>PC1 Importance</th>\n",
       "      <th>PC2 Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Murder</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0.045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Assault</td>\n",
       "      <td>0.995</td>\n",
       "      <td>0.059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>UrbanPop</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rape</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Features  PC1 Importance  PC2 Importance\n",
       "0    Murder           0.042           0.045\n",
       "1   Assault           0.995           0.059\n",
       "2  UrbanPop           0.046           0.977\n",
       "3      Rape           0.075           0.201"
      ]
     },
     "execution_count": 1128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Feature importance\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x) #change precision to see more decimal places\n",
    "\n",
    "pc1 = abs( pca.components_[0] ) #components x features - access at index 0 to get the first component\n",
    "pc2 = abs( pca.components_[1] )\n",
    "\n",
    "feat_df = pd.DataFrame()\n",
    "feat_df[\"Features\"] = list(labels)\n",
    "feat_df[\"PC1 Importance\"] = pc1\n",
    "feat_df[\"PC2 Importance\"] = pc2\n",
    "feat_df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspecting the feature importance now, we see that most of the variables contribute fairly evenly, most with low importance.\n",
    "The most important for PC1 is Assault and for PC2 is UrbanPop, each of which dominate their PC with over 0.9 importance."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standardised Data"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We standardise the data so that some features do not swamp the others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1129,
   "metadata": {},
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.986</td>\n",
       "      <td>1.133</td>\n",
       "      <td>-0.444</td>\n",
       "      <td>0.156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.950</td>\n",
       "      <td>1.073</td>\n",
       "      <td>2.040</td>\n",
       "      <td>-0.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.763</td>\n",
       "      <td>-0.746</td>\n",
       "      <td>0.055</td>\n",
       "      <td>-0.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.141</td>\n",
       "      <td>1.120</td>\n",
       "      <td>0.115</td>\n",
       "      <td>-0.183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.524</td>\n",
       "      <td>-1.543</td>\n",
       "      <td>0.599</td>\n",
       "      <td>-0.342</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0      1      2      3\n",
       "0  0.986  1.133 -0.444  0.156\n",
       "1  1.950  1.073  2.040 -0.439\n",
       "2  1.763 -0.746  0.055 -0.835\n",
       "3 -0.141  1.120  0.115 -0.183\n",
       "4  2.524 -1.543  0.599 -0.342"
      ]
     },
     "execution_count": 1129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_std = StandardScaler().fit_transform(X)\n",
    "\n",
    "std_pca = PCA()\n",
    "X_std_trans = std_pca.fit_transform(X_std)\n",
    "\n",
    "df_std_pca = pd.DataFrame(X_std_trans)\n",
    "df_std_pca.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "biplot(X_std_trans[:,0:2],np.transpose(std_pca.components_[0:2, :]),list(labels))\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the standardised data results in far more variables being utilised to explain the variance, as the large numbers no longer dominate it. We also see that the the different features cluster together in groups.\n",
    "It can be seen that Murder and Assault have the strongest positive correlations for PC1."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "State cities to the right of the plot show a higher correlation to all of the variables, while states to the left show less correlation, thus less crime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1131,
   "metadata": {},
   "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>Features</th>\n",
       "      <th>PC1 Importance</th>\n",
       "      <th>PC2 Importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Murder</td>\n",
       "      <td>0.536</td>\n",
       "      <td>0.418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Assault</td>\n",
       "      <td>0.583</td>\n",
       "      <td>0.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>UrbanPop</td>\n",
       "      <td>0.278</td>\n",
       "      <td>0.873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rape</td>\n",
       "      <td>0.543</td>\n",
       "      <td>0.167</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Features  PC1 Importance  PC2 Importance\n",
       "0    Murder           0.536           0.418\n",
       "1   Assault           0.583           0.188\n",
       "2  UrbanPop           0.278           0.873\n",
       "3      Rape           0.543           0.167"
      ]
     },
     "execution_count": 1131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Feature importance\n",
    "\n",
    "pc1 = abs( std_pca.components_[0] ) #components x features - access at index 0 to get the first component\n",
    "pc2 = abs( std_pca.components_[1] )\n",
    "\n",
    "feat_df = pd.DataFrame()\n",
    "feat_df[\"Features\"] = list(labels)\n",
    "feat_df[\"PC1 Importance\"] = pc1\n",
    "feat_df[\"PC2 Importance\"] = pc2\n",
    "feat_df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PC1 shows that Assault, Rape and Murder have the highest importance scores of about 0.5 each.\n",
    "PC2 shows UrbanPop to be most important at 0.873."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Cumulative Explained Variance')"
      ]
     },
     "execution_count": 1132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cumulative variance plot\n",
    "plt.ylabel('Explained variance')\n",
    "plt.xlabel('Components')\n",
    "plt.plot(range(1,len(std_pca.explained_variance_ratio_ )+1),\n",
    "         np.cumsum(std_pca.explained_variance_ratio_),\n",
    "         c='red')\n",
    "plt.title(\"Cumulative Explained Variance\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The variance reaches over 0.9 between 2 and 3 components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scree plot\n",
    "plt.plot(std_pca.explained_variance_ratio_)\n",
    "plt.xlabel('number of components')\n",
    "plt.ylabel('cumulative explained variance')\n",
    "plt.title(\"Scree plot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1134,
   "metadata": {},
   "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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>City</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>0.986</td>\n",
       "      <td>1.133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>1.950</td>\n",
       "      <td>1.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>1.763</td>\n",
       "      <td>-0.746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>-0.141</td>\n",
       "      <td>1.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>2.524</td>\n",
       "      <td>-1.543</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                0      1\n",
       "City                    \n",
       "Alabama     0.986  1.133\n",
       "Alaska      1.950  1.073\n",
       "Arizona     1.763 -0.746\n",
       "Arkansas   -0.141  1.120\n",
       "California  2.524 -1.543"
      ]
     },
     "execution_count": 1134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''The first 2 principal components together explain around 90% of the variance.\n",
    "We can therefore use them to perform cluster analysis. This is what we refer to as dimensionality reduction.\n",
    "We began with 4 variables and now we have 2 variables explaining most of the variability.'''\n",
    "pca_df = pd.DataFrame(X_std_trans[:,0:2], index = df.index)\n",
    "pca_df.head()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from sklearn.cluster import AgglomerativeClustering\n",
    "\n",
    "model = AgglomerativeClustering(distance_threshold=0, n_clusters=None)\n",
    "model = model.fit(pca_df)\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3)\n",
    "fig.suptitle('Hierarchical Clustering Dendrogram')\n",
    "ax1.set_title(\"Single\")\n",
    "dendrogram(linkage(pca_df, method='single'), labels=pca_df.index, ax=ax1) #change method: eg. single, average, complete...\n",
    "ax2.set_title(\"Average\")\n",
    "dendrogram(linkage(pca_df, method='average'), labels=pca_df.index, ax=ax2)\n",
    "ax3.set_title(\"Complete\")\n",
    "dendrogram(linkage(pca_df, method='complete'), labels=pca_df.index, ax=ax3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title(\"Complete linkage\")\n",
    "dendrogram(linkage(pca_df, method='complete'), labels=pca_df.index)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This complete hierarchical clustering splits the cities 31 to 19. 31 have less crime while 19 have more."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kmeans clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1137,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\super\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\sklearn\\cluster\\_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
      "  warnings.warn(\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e30f28c550>"
      ]
     },
     "execution_count": 1137,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "# We extract the first two components\n",
    "x = X_std_trans[:,0]\n",
    "y = X_std_trans[:,1]\n",
    "\n",
    "# Fit k-means\n",
    "k=2\n",
    "kmeans = KMeans(n_clusters=k, init='k-means++', random_state=42)\n",
    "cluster_labels = kmeans.fit_predict(pca_df)\n",
    "cent = kmeans.cluster_centers_\n",
    "\n",
    "# Plot clusters\n",
    "fig, ax = plt.subplots()\n",
    "colours = 'rbgy'\n",
    "for i in range(0,k):\n",
    "    ax.scatter(x[cluster_labels == i],y[cluster_labels == i],c = colours[i]) \n",
    "\n",
    "for i in range(0,len(x)):\n",
    "        txt = cities[i]\n",
    "        ax.annotate(txt, (x[i], y[i]))\n",
    "ax.set_title(\"K-Means cluster plot\")\n",
    "ax.set_xlabel(\"Dim 2\")\n",
    "ax.set_ylabel(\"Dim 1\")\n",
    "ax.legend()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This Kmeans clustering splits the cities 31 to 19. 31 have less crime while 19 have more."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1138,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Group 0: [50.0, 77.0, 72.0, 83.0, 54.0, 65.0, 57.0, 66.0, 52.0, 51.0, 85.0, 66.0, 53.0, 62.0, 56.0, 89.0, 44.0, 75.0, 68.0, 67.0, 72.0, 87.0, 45.0, 80.0, 32.0, 63.0, 73.0, 39.0, 66.0, 60.0]\n",
      "\n",
      "\n",
      "Group 1: [58.0, 48.0, 80.0, 91.0, 78.0, 80.0, 60.0, 83.0, 66.0, 67.0, 74.0, 44.0, 70.0, 81.0, 70.0, 86.0, 45.0, 48.0, 59.0, 80.0]\n",
      "\n",
      "\n",
      "Group 2: []\n",
      "\n",
      "\n",
      "Group 0: [Murder       8.800\n",
      "Assault    190.000\n",
      "UrbanPop    50.000\n",
      "Rape        19.500\n",
      "Name: Arkansas, dtype: float64, Murder       3.300\n",
      "Assault    110.000\n",
      "UrbanPop    77.000\n",
      "Rape        11.100\n",
      "Name: Connecticut, dtype: float64, Murder       5.900\n",
      "Assault    238.000\n",
      "UrbanPop    72.000\n",
      "Rape        15.800\n",
      "Name: Delaware, dtype: float64, Murder      5.300\n",
      "Assault    46.000\n",
      "UrbanPop   83.000\n",
      "Rape       20.200\n",
      "Name: Hawaii, dtype: float64, Murder       2.600\n",
      "Assault    120.000\n",
      "UrbanPop    54.000\n",
      "Rape        14.200\n",
      "Name: Idaho, dtype: float64, Murder       7.200\n",
      "Assault    113.000\n",
      "UrbanPop    65.000\n",
      "Rape        21.000\n",
      "Name: Indiana, dtype: float64, Murder      2.200\n",
      "Assault    56.000\n",
      "UrbanPop   57.000\n",
      "Rape       11.300\n",
      "Name: Iowa, dtype: float64, Murder       6.000\n",
      "Assault    115.000\n",
      "UrbanPop    66.000\n",
      "Rape        18.000\n",
      "Name: Kansas, dtype: float64, Murder       9.700\n",
      "Assault    109.000\n",
      "UrbanPop    52.000\n",
      "Rape        16.300\n",
      "Name: Kentucky, dtype: float64, Murder      2.100\n",
      "Assault    83.000\n",
      "UrbanPop   51.000\n",
      "Rape        7.800\n",
      "Name: Maine, dtype: float64, Murder       4.400\n",
      "Assault    149.000\n",
      "UrbanPop    85.000\n",
      "Rape        16.300\n",
      "Name: Massachusetts, dtype: float64, Murder      2.700\n",
      "Assault    72.000\n",
      "UrbanPop   66.000\n",
      "Rape       14.900\n",
      "Name: Minnesota, dtype: float64, Murder       6.000\n",
      "Assault    109.000\n",
      "UrbanPop    53.000\n",
      "Rape        16.400\n",
      "Name: Montana, dtype: float64, Murder       4.300\n",
      "Assault    102.000\n",
      "UrbanPop    62.000\n",
      "Rape        16.500\n",
      "Name: Nebraska, dtype: float64, Murder      2.100\n",
      "Assault    57.000\n",
      "UrbanPop   56.000\n",
      "Rape        9.500\n",
      "Name: New Hampshire, dtype: float64, Murder       7.400\n",
      "Assault    159.000\n",
      "UrbanPop    89.000\n",
      "Rape        18.800\n",
      "Name: New Jersey, dtype: float64, Murder      0.800\n",
      "Assault    45.000\n",
      "UrbanPop   44.000\n",
      "Rape        7.300\n",
      "Name: North Dakota, dtype: float64, Murder       7.300\n",
      "Assault    120.000\n",
      "UrbanPop    75.000\n",
      "Rape        21.400\n",
      "Name: Ohio, dtype: float64, Murder       6.600\n",
      "Assault    151.000\n",
      "UrbanPop    68.000\n",
      "Rape        20.000\n",
      "Name: Oklahoma, dtype: float64, Murder       4.900\n",
      "Assault    159.000\n",
      "UrbanPop    67.000\n",
      "Rape        29.300\n",
      "Name: Oregon, dtype: float64, Murder       6.300\n",
      "Assault    106.000\n",
      "UrbanPop    72.000\n",
      "Rape        14.900\n",
      "Name: Pennsylvania, dtype: float64, Murder       3.400\n",
      "Assault    174.000\n",
      "UrbanPop    87.000\n",
      "Rape         8.300\n",
      "Name: Rhode Island, dtype: float64, Murder      3.800\n",
      "Assault    86.000\n",
      "UrbanPop   45.000\n",
      "Rape       12.800\n",
      "Name: South Dakota, dtype: float64, Murder       3.200\n",
      "Assault    120.000\n",
      "UrbanPop    80.000\n",
      "Rape        22.900\n",
      "Name: Utah, dtype: float64, Murder      2.200\n",
      "Assault    48.000\n",
      "UrbanPop   32.000\n",
      "Rape       11.200\n",
      "Name: Vermont, dtype: float64, Murder       8.500\n",
      "Assault    156.000\n",
      "UrbanPop    63.000\n",
      "Rape        20.700\n",
      "Name: Virginia, dtype: float64, Murder       4.000\n",
      "Assault    145.000\n",
      "UrbanPop    73.000\n",
      "Rape        26.200\n",
      "Name: Washington, dtype: float64, Murder      5.700\n",
      "Assault    81.000\n",
      "UrbanPop   39.000\n",
      "Rape        9.300\n",
      "Name: West Virginia, dtype: float64, Murder      2.600\n",
      "Assault    53.000\n",
      "UrbanPop   66.000\n",
      "Rape       10.800\n",
      "Name: Wisconsin, dtype: float64, Murder       6.800\n",
      "Assault    161.000\n",
      "UrbanPop    60.000\n",
      "Rape        15.600\n",
      "Name: Wyoming, dtype: float64]\n",
      "\n",
      "\n",
      "Group 1: [Murder      13.200\n",
      "Assault    236.000\n",
      "UrbanPop    58.000\n",
      "Rape        21.200\n",
      "Name: Alabama, dtype: float64, Murder      10.000\n",
      "Assault    263.000\n",
      "UrbanPop    48.000\n",
      "Rape        44.500\n",
      "Name: Alaska, dtype: float64, Murder       8.100\n",
      "Assault    294.000\n",
      "UrbanPop    80.000\n",
      "Rape        31.000\n",
      "Name: Arizona, dtype: float64, Murder       9.000\n",
      "Assault    276.000\n",
      "UrbanPop    91.000\n",
      "Rape        40.600\n",
      "Name: California, dtype: float64, Murder       7.900\n",
      "Assault    204.000\n",
      "UrbanPop    78.000\n",
      "Rape        38.700\n",
      "Name: Colorado, dtype: float64, Murder      15.400\n",
      "Assault    335.000\n",
      "UrbanPop    80.000\n",
      "Rape        31.900\n",
      "Name: Florida, dtype: float64, Murder      17.400\n",
      "Assault    211.000\n",
      "UrbanPop    60.000\n",
      "Rape        25.800\n",
      "Name: Georgia, dtype: float64, Murder      10.400\n",
      "Assault    249.000\n",
      "UrbanPop    83.000\n",
      "Rape        24.000\n",
      "Name: Illinois, dtype: float64, Murder      15.400\n",
      "Assault    249.000\n",
      "UrbanPop    66.000\n",
      "Rape        22.200\n",
      "Name: Louisiana, dtype: float64, Murder      11.300\n",
      "Assault    300.000\n",
      "UrbanPop    67.000\n",
      "Rape        27.800\n",
      "Name: Maryland, dtype: float64, Murder      12.100\n",
      "Assault    255.000\n",
      "UrbanPop    74.000\n",
      "Rape        35.100\n",
      "Name: Michigan, dtype: float64, Murder      16.100\n",
      "Assault    259.000\n",
      "UrbanPop    44.000\n",
      "Rape        17.100\n",
      "Name: Mississippi, dtype: float64, Murder       9.000\n",
      "Assault    178.000\n",
      "UrbanPop    70.000\n",
      "Rape        28.200\n",
      "Name: Missouri, dtype: float64, Murder      12.200\n",
      "Assault    252.000\n",
      "UrbanPop    81.000\n",
      "Rape        46.000\n",
      "Name: Nevada, dtype: float64, Murder      11.400\n",
      "Assault    285.000\n",
      "UrbanPop    70.000\n",
      "Rape        32.100\n",
      "Name: New Mexico, dtype: float64, Murder      11.100\n",
      "Assault    254.000\n",
      "UrbanPop    86.000\n",
      "Rape        26.100\n",
      "Name: New York, dtype: float64, Murder      13.000\n",
      "Assault    337.000\n",
      "UrbanPop    45.000\n",
      "Rape        16.100\n",
      "Name: North Carolina, dtype: float64, Murder      14.400\n",
      "Assault    279.000\n",
      "UrbanPop    48.000\n",
      "Rape        22.500\n",
      "Name: South Carolina, dtype: float64, Murder      13.200\n",
      "Assault    188.000\n",
      "UrbanPop    59.000\n",
      "Rape        26.900\n",
      "Name: Tennessee, dtype: float64, Murder      12.700\n",
      "Assault    201.000\n",
      "UrbanPop    80.000\n",
      "Rape        25.500\n",
      "Name: Texas, dtype: float64]\n",
      "\n",
      "\n",
      "Group 2: []\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Groups - translate to readable names\n",
    "clusters = pd.DataFrame()\n",
    "\n",
    "group0_indices = np.argwhere(cluster_labels==0).transpose()[0]\n",
    "group1_indices = np.argwhere(cluster_labels==1).transpose()[0]\n",
    "group2_indices = np.argwhere(cluster_labels==2).transpose()[0]\n",
    "\n",
    "group0 = np.array(cities)[group0_indices]\n",
    "group1 = np.array(cities)[group1_indices]\n",
    "group2 = np.array(cities)[group2_indices]\n",
    "\n",
    "# Groups shown by UrbanPop %\n",
    "print(\"Group 0: {}\\n\\n\".format([df.loc[x][\"UrbanPop\"] for x in group0]))\n",
    "print(\"Group 1: {}\\n\\n\".format([df.loc[x][\"UrbanPop\"] for x in group1]))\n",
    "print(\"Group 2: {}\\n\\n\".format([df.loc[x][\"UrbanPop\"] for x in group2]))\n",
    "\n",
    "# Groups shown with all data (open in text editor to see in full)\n",
    "print(\"Group 0: {}\\n\\n\".format([df.loc[x] for x in group0]))\n",
    "print(\"Group 1: {}\\n\\n\".format([df.loc[x] for x in group1]))\n",
    "print(\"Group 2: {}\\n\\n\".format([df.loc[x] for x in group2]))"
   ]
  }
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