{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "collapsed": true
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import cm as cm\n",
        "import seaborn as sns\n",
        "sns.set(font_scale=2)\n",
        "plt.style.use('seaborn-whitegrid')\n",
        "%matplotlib inline\n",
        "\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.preprocessing import scale\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Example from:\n",
        "http://setosa.io/ev/principal-component-analysis/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style>\n",
              "    .dataframe thead tr:only-child th {\n",
              "        text-align: right;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>England</th>\n",
              "      <th>Wales</th>\n",
              "      <th>Scotland</th>\n",
              "      <th>N.Ireland</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Cheese</td>\n",
              "      <td>105</td>\n",
              "      <td>103</td>\n",
              "      <td>103</td>\n",
              "      <td>66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Carcass_meat</td>\n",
              "      <td>245</td>\n",
              "      <td>227</td>\n",
              "      <td>242</td>\n",
              "      <td>267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Other_meat</td>\n",
              "      <td>685</td>\n",
              "      <td>803</td>\n",
              "      <td>750</td>\n",
              "      <td>586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fish</td>\n",
              "      <td>147</td>\n",
              "      <td>160</td>\n",
              "      <td>122</td>\n",
              "      <td>93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Fats_and_oils</td>\n",
              "      <td>193</td>\n",
              "      <td>235</td>\n",
              "      <td>184</td>\n",
              "      <td>209</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Unnamed: 0  England  Wales  Scotland  N.Ireland\n",
              "0          Cheese      105    103       103         66\n",
              "1   Carcass_meat       245    227       242        267\n",
              "2     Other_meat       685    803       750        586\n",
              "3            Fish      147    160       122         93\n",
              "4  Fats_and_oils       193    235       184        209"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data = pd.io.parsers.read_csv(\"UK_foods.csv\")\n",
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['Cheese', 'Carcass_meat ', 'Other_meat ', 'Fish', 'Fats_and_oils ', 'Sugars', 'Fresh_potatoes ', 'Fresh_Veg ', 'Other_Veg ', 'Processed_potatoes ', 'Processed_Veg ', 'Fresh_fruit ', 'Cereals ', 'Beverages', 'Soft_drinks ', 'Alcoholic_drinks ', 'Confectionery ']\n",
            "['England', 'Wales', 'Scotland', 'N.Ireland']\n"
          ]
        }
      ],
      "source": [
        "headers = data['Unnamed: 0'].values.tolist()\n",
        "print(headers)\n",
        "\n",
        "new_data = data.drop(['Unnamed: 0'], axis=1)\n",
        "new_data.head()\n",
        "\n",
        "regions = new_data.columns.values.tolist()\n",
        "print(regions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style>\n",
              "    .dataframe thead tr:only-child th {\n",
              "        text-align: right;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Cheese</th>\n",
              "      <th>Carcass_meat</th>\n",
              "      <th>Other_meat</th>\n",
              "      <th>Fish</th>\n",
              "      <th>Fats_and_oils</th>\n",
              "      <th>Sugars</th>\n",
              "      <th>Fresh_potatoes</th>\n",
              "      <th>Fresh_Veg</th>\n",
              "      <th>Other_Veg</th>\n",
              "      <th>Processed_potatoes</th>\n",
              "      <th>Processed_Veg</th>\n",
              "      <th>Fresh_fruit</th>\n",
              "      <th>Cereals</th>\n",
              "      <th>Beverages</th>\n",
              "      <th>Soft_drinks</th>\n",
              "      <th>Alcoholic_drinks</th>\n",
              "      <th>Confectionery</th>\n",
              "      <th>region</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>105</td>\n",
              "      <td>245</td>\n",
              "      <td>685</td>\n",
              "      <td>147</td>\n",
              "      <td>193</td>\n",
              "      <td>156</td>\n",
              "      <td>720</td>\n",
              "      <td>253</td>\n",
              "      <td>488</td>\n",
              "      <td>198</td>\n",
              "      <td>360</td>\n",
              "      <td>1102</td>\n",
              "      <td>1472</td>\n",
              "      <td>57</td>\n",
              "      <td>1374</td>\n",
              "      <td>375</td>\n",
              "      <td>54</td>\n",
              "      <td>England</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>103</td>\n",
              "      <td>227</td>\n",
              "      <td>803</td>\n",
              "      <td>160</td>\n",
              "      <td>235</td>\n",
              "      <td>175</td>\n",
              "      <td>874</td>\n",
              "      <td>265</td>\n",
              "      <td>570</td>\n",
              "      <td>203</td>\n",
              "      <td>365</td>\n",
              "      <td>1137</td>\n",
              "      <td>1582</td>\n",
              "      <td>73</td>\n",
              "      <td>1256</td>\n",
              "      <td>475</td>\n",
              "      <td>64</td>\n",
              "      <td>Wales</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>103</td>\n",
              "      <td>242</td>\n",
              "      <td>750</td>\n",
              "      <td>122</td>\n",
              "      <td>184</td>\n",
              "      <td>147</td>\n",
              "      <td>566</td>\n",
              "      <td>171</td>\n",
              "      <td>418</td>\n",
              "      <td>220</td>\n",
              "      <td>337</td>\n",
              "      <td>957</td>\n",
              "      <td>1462</td>\n",
              "      <td>53</td>\n",
              "      <td>1572</td>\n",
              "      <td>458</td>\n",
              "      <td>62</td>\n",
              "      <td>Scotland</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>66</td>\n",
              "      <td>267</td>\n",
              "      <td>586</td>\n",
              "      <td>93</td>\n",
              "      <td>209</td>\n",
              "      <td>139</td>\n",
              "      <td>1033</td>\n",
              "      <td>143</td>\n",
              "      <td>355</td>\n",
              "      <td>187</td>\n",
              "      <td>334</td>\n",
              "      <td>674</td>\n",
              "      <td>1494</td>\n",
              "      <td>47</td>\n",
              "      <td>1506</td>\n",
              "      <td>135</td>\n",
              "      <td>41</td>\n",
              "      <td>N.Ireland</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Cheese  Carcass_meat   Other_meat   Fish  Fats_and_oils   Sugars  \\\n",
              "0     105            245          685   147             193     156   \n",
              "1     103            227          803   160             235     175   \n",
              "2     103            242          750   122             184     147   \n",
              "3      66            267          586    93             209     139   \n",
              "\n",
              "   Fresh_potatoes   Fresh_Veg   Other_Veg   Processed_potatoes   \\\n",
              "0              720         253         488                  198   \n",
              "1              874         265         570                  203   \n",
              "2              566         171         418                  220   \n",
              "3             1033         143         355                  187   \n",
              "\n",
              "   Processed_Veg   Fresh_fruit   Cereals   Beverages  Soft_drinks   \\\n",
              "0             360          1102      1472         57          1374   \n",
              "1             365          1137      1582         73          1256   \n",
              "2             337           957      1462         53          1572   \n",
              "3             334           674      1494         47          1506   \n",
              "\n",
              "   Alcoholic_drinks   Confectionery      region  \n",
              "0                375              54    England  \n",
              "1                475              64      Wales  \n",
              "2                458              62   Scotland  \n",
              "3                135              41  N.Ireland  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "food = pd.DataFrame(new_data.values.T,columns=headers)\n",
        "food['region'] = regions\n",
        "food"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### This is when we want to try PCA!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "collapsed": true
      },
      "outputs": [],
      "source": [
        "#Performing PCA without scaling the data (to match the results from the website)\n",
        "X = pd.DataFrame(food[headers], columns=headers)\n",
        "# In general, PCA scales the variables to zero-mean (use line below to scale)\n",
        "# X = pd.DataFrame(scale(food[headers]), columns=headers)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "collapsed": true
      },
      "outputs": [],
      "source": [
        "pca = PCA().fit(X)\n",
        "pca_samples = pca.transform(X)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZgAAAEiCAYAAADEasRGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a0cc41860>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "var_exp = pca.explained_variance_ratio_\n",
        "plt.bar(range(len(var_exp)),var_exp, align='center', label='individual explained variance');\n",
        "plt.ylabel('Explained variance ratio');\n",
        "plt.xlabel('Principal components');"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style>\n",
              "    .dataframe thead tr:only-child th {\n",
              "        text-align: right;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Cheese</th>\n",
              "      <th>Carcass_meat</th>\n",
              "      <th>Other_meat</th>\n",
              "      <th>Fish</th>\n",
              "      <th>Fats_and_oils</th>\n",
              "      <th>Sugars</th>\n",
              "      <th>Fresh_potatoes</th>\n",
              "      <th>Fresh_Veg</th>\n",
              "      <th>Other_Veg</th>\n",
              "      <th>Processed_potatoes</th>\n",
              "      <th>Processed_Veg</th>\n",
              "      <th>Fresh_fruit</th>\n",
              "      <th>Cereals</th>\n",
              "      <th>Beverages</th>\n",
              "      <th>Soft_drinks</th>\n",
              "      <th>Alcoholic_drinks</th>\n",
              "      <th>Confectionery</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.056955</td>\n",
              "      <td>0.047928</td>\n",
              "      <td>-0.258917</td>\n",
              "      <td>-0.084415</td>\n",
              "      <td>-0.005194</td>\n",
              "      <td>-0.037621</td>\n",
              "      <td>0.401402</td>\n",
              "      <td>-0.151850</td>\n",
              "      <td>-0.243594</td>\n",
              "      <td>-0.026886</td>\n",
              "      <td>-0.036488</td>\n",
              "      <td>-0.632641</td>\n",
              "      <td>-0.047703</td>\n",
              "      <td>-0.026188</td>\n",
              "      <td>0.232244</td>\n",
              "      <td>-0.463968</td>\n",
              "      <td>-0.029650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.016013</td>\n",
              "      <td>0.013916</td>\n",
              "      <td>-0.015331</td>\n",
              "      <td>-0.050755</td>\n",
              "      <td>-0.095389</td>\n",
              "      <td>-0.043022</td>\n",
              "      <td>-0.715017</td>\n",
              "      <td>-0.144900</td>\n",
              "      <td>-0.225451</td>\n",
              "      <td>0.042851</td>\n",
              "      <td>-0.045452</td>\n",
              "      <td>-0.177741</td>\n",
              "      <td>-0.212600</td>\n",
              "      <td>-0.030561</td>\n",
              "      <td>0.555124</td>\n",
              "      <td>0.113537</td>\n",
              "      <td>0.005950</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.023943</td>\n",
              "      <td>0.063671</td>\n",
              "      <td>-0.553849</td>\n",
              "      <td>0.039065</td>\n",
              "      <td>-0.125223</td>\n",
              "      <td>-0.036057</td>\n",
              "      <td>-0.206682</td>\n",
              "      <td>0.213822</td>\n",
              "      <td>-0.053328</td>\n",
              "      <td>-0.073649</td>\n",
              "      <td>0.052892</td>\n",
              "      <td>0.400129</td>\n",
              "      <td>-0.358849</td>\n",
              "      <td>-0.041359</td>\n",
              "      <td>-0.169426</td>\n",
              "      <td>-0.498583</td>\n",
              "      <td>-0.052322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.409383</td>\n",
              "      <td>0.729482</td>\n",
              "      <td>0.331001</td>\n",
              "      <td>0.022376</td>\n",
              "      <td>0.034512</td>\n",
              "      <td>0.024943</td>\n",
              "      <td>0.021396</td>\n",
              "      <td>0.001607</td>\n",
              "      <td>0.031153</td>\n",
              "      <td>-0.017380</td>\n",
              "      <td>0.021251</td>\n",
              "      <td>0.227657</td>\n",
              "      <td>0.100043</td>\n",
              "      <td>-0.018382</td>\n",
              "      <td>0.222319</td>\n",
              "      <td>-0.273126</td>\n",
              "      <td>0.001891</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Cheese  Carcass_meat   Other_meat       Fish  Fats_and_oils     Sugars  \\\n",
              "0 -0.056955       0.047928    -0.258917 -0.084415       -0.005194 -0.037621   \n",
              "1  0.016013       0.013916    -0.015331 -0.050755       -0.095389 -0.043022   \n",
              "2  0.023943       0.063671    -0.553849  0.039065       -0.125223 -0.036057   \n",
              "3 -0.409383       0.729482     0.331001  0.022376        0.034512  0.024943   \n",
              "\n",
              "   Fresh_potatoes   Fresh_Veg   Other_Veg   Processed_potatoes   \\\n",
              "0         0.401402   -0.151850   -0.243594            -0.026886   \n",
              "1        -0.715017   -0.144900   -0.225451             0.042851   \n",
              "2        -0.206682    0.213822   -0.053328            -0.073649   \n",
              "3         0.021396    0.001607    0.031153            -0.017380   \n",
              "\n",
              "   Processed_Veg   Fresh_fruit   Cereals   Beverages  Soft_drinks   \\\n",
              "0       -0.036488     -0.632641 -0.047703  -0.026188      0.232244   \n",
              "1       -0.045452     -0.177741 -0.212600  -0.030561      0.555124   \n",
              "2        0.052892      0.400129 -0.358849  -0.041359     -0.169426   \n",
              "3        0.021251      0.227657  0.100043  -0.018382      0.222319   \n",
              "\n",
              "   Alcoholic_drinks   Confectionery   \n",
              "0          -0.463968       -0.029650  \n",
              "1           0.113537        0.005950  \n",
              "2          -0.498583       -0.052322  \n",
              "3          -0.273126        0.001891  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "components = pd.DataFrame(pca.components_, columns = headers) \n",
        "components"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Text(0.5,1,'influence of original variables(food) upon pc2')"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAHCCAYAAAAtjPomAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nM5lMJpPpAbLBzmQymUymB/h/DgpivDtqxyIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a1518eac8>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAHCCAYAAAAtjPomAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a152ae668>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plt.figure()\n",
        "plt.bar(headers,components.values[0])\n",
        "plt.xticks(rotation=90)\n",
        "plt.title('influence of original variables(food) upon pc1')\n",
        "plt.figure()\n",
        "plt.bar(headers,components.values[1])\n",
        "plt.xticks(rotation=90)\n",
        "plt.title('influence of original variables(food) upon pc2')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style>\n",
              "    .dataframe thead tr:only-child th {\n",
              "        text-align: right;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: left;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>pc1</th>\n",
              "      <th>pc2</th>\n",
              "      <th>pc3</th>\n",
              "      <th>pc4</th>\n",
              "      <th>region</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-144.993152</td>\n",
              "      <td>-2.532999</td>\n",
              "      <td>105.768945</td>\n",
              "      <td>-1.699297e-14</td>\n",
              "      <td>England</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-240.529148</td>\n",
              "      <td>-224.646925</td>\n",
              "      <td>-56.475555</td>\n",
              "      <td>5.541582e-13</td>\n",
              "      <td>Wales</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-91.869339</td>\n",
              "      <td>286.081786</td>\n",
              "      <td>-44.415495</td>\n",
              "      <td>-6.694069e-13</td>\n",
              "      <td>Scotland</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>477.391639</td>\n",
              "      <td>-58.901862</td>\n",
              "      <td>-4.877895</td>\n",
              "      <td>1.251362e-13</td>\n",
              "      <td>N.Ireland</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          pc1         pc2         pc3           pc4     region\n",
              "0 -144.993152   -2.532999  105.768945 -1.699297e-14    England\n",
              "1 -240.529148 -224.646925  -56.475555  5.541582e-13      Wales\n",
              "2  -91.869339  286.081786  -44.415495 -6.694069e-13   Scotland\n",
              "3  477.391639  -58.901862   -4.877895  1.251362e-13  N.Ireland"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Xstar = pd.DataFrame(pca_samples,columns=['pc1','pc2','pc3','pc4'])\n",
        "Xstar['region'] = regions\n",
        "Xstar"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1a15330f98>"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAc0AAAEZCAYAAAD16n4kAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a15311a58>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "sns.stripplot(x=\"pc1\",y=\"region\", data=Xstar, jitter=0.05, linewidth=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Text(67.7201,0.5,'pc2')"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a15170a90>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdUAAAFgCAYAAADtvuMxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzt3Xm8XPP9x/FXRCQilQhNgiIEH1sr\nhIg1sVQtVVVbtbUWbYmqXaxBxVKKWmsJLe1P0UUtVVuigkpdoip8qEipSoJEIiRB3N8fn+/EZDJz\n78y9596Zuff9fDzu49z5nu858z1j5HO/e5fGxkZERESk9ZaqdgFEREQ6CgVVERGRjCioioiIZERB\nVUREJCMKqiIiIhlRUM1QQ0NDI6CfVv68+OKLVS+Dfurvp5nvjUi7UFCVmjN//vxqF0HqkL43UgsU\nVEVERDKioCoiIpIRBVUREZGMKKiKiIhkREFVREQkIwqqIiIiGVFQFRERyYiCqoiISEYUVEVERDKi\noCoiIpIRBVUREZGMKKiKiIhkREFVREQkIwqqIiIiGVFQFRERyYiCqoiISEYUVEVERDKioCoiIpIR\nBVUREZGMKKiKiIhkREFVREQkIwqqIiIiGVFQFRERyYiCqoiISEYUVEVERDKioCoiIpIRBVUREZGM\nKKiKiIhkREFVREQkIwqqIiIiGVFQFRERycjS1S5AFszsEuAEYHt3H19w7iDgOGBdYBZwB3CWu88t\ncp/dgTOAjYB5wD3AKHef0aYPICIiHULd11TNbCjwkxLnRgG/Ip7zSuB5IsA+aGbLFOQ9ALgX6Adc\nCzwKHAI8aWZ92qr8IiLScdR1TTUFxpuArkXOrQ6cCzwFDHf3T1L6ucCZwJHAVSmtV/p9CrCJu89J\n6Q+m+58BnNjWzyMiIvWt3muqpxPNug8XOfcD4o+GMbmAmowB5gCH56UdAPQFLssFVAB3Hws4cIiZ\nLRG4RURE8tVtUDWzrwCjgAuAF4tk2S4dH8tPdPf5RO11YzPrXZB3XJH7jAdWJPpZRURESqrLoJpq\njWOBV4maZzGDgOnu/kGRc1PTcd28vBDNv83lFRERKaougyrRv7kJcLi7f1wiz4rA+yXOzU7H3nl5\nF7j7vDLyioiIFFV3A5XMbF1gNHCNuz/VRNZuwIIS53LpPVqQt0kNDQ3lZJNm6HOUlij1vRkyZEg7\nl0Q6q7oKqmbWhRiNO4PoT23KPGCZEue6p+OHLcjbJP3P23oNDQ36HKVi+t5ILai35t+jgW2AHxVb\nvKHALEo32ebSZ+fl7WFm3cvIKyIiUlRd1VSBfdLxPjMrdn5cSl8TeAUYbmbLFukrXRP4jBjoRMq7\nNTCQmEJTmJci6SIiIoupt6B6CzHFpdAuwBbE6klTiQFKE4DtgW2BB3MZzawHMAx4MW9k8ATgUGA4\nSwbPEUQt9aVMnkBERDqsugqq7n5LsfS0jOAWwC25tX/N7DfAacBoM3vM3XMDjk4Dlgeuz7vFn4DL\ngZPN7C53n5nucRgxleZSd/8s+ycSEZGOpK6CaiXc3dNC+6cAz5nZPcCGwO7AE8ANeXlnmtnJxJq/\nk8zsDmBVYD+iabjUXFgREZFF6m2gUqVGASOBRuBYYlWky4Dd82quALj7dcC3gXeIAVHbEc3JI3I1\nVxERkaZ0aWxsrHYZOoyGhoZGDelvPU2NkJZo5nvTpT3LIp1XR6+pioiItBsFVRERkYwoqIqIiGRE\nQVVERCQjCqoiIiIZUVAVERHJiIKqiIhIRhRURUREMqKgKiIikhEFVRERkYwoqIqIiGREQVVERCQj\nCqoiIiIZUVAVERHJiIKqiIhIRhRURUREMqKgKiIikhEFVRERkYwoqIqIiGREQVVERCQjS1e7AFL7\nZj03iRkPP8r86dPp0b8//XbagRU2GVztYomI1BwFVWnSrOcm8Z9bf7vo9by3py16rcAqIrI4Nf9K\nk2Y8/Gjx9EeKp4uIdGYKqtKk+dOnF0+fNqOdSyIiUvsUVKVJPfr3L54+oF87l0REpPYpqEqT+u20\nQ/H0HYuni4h0ZhqoJE3KDUaa8cijzJ82gx4D+tFvR43+FREpRkFVmrXCJoMVREVEyqDmXxERkYwo\nqIqIiGREQVVERCQjCqoiIiIZUVAVERHJiIKqiIhIRhRURUREMqKgKiIikhEFVRERkYwoqIqIiGRE\nQVVERCQjCqoiIiIZUVAVERHJSF3uUmNmA4DRwO5Af2Am8DBwlrtPKch7EHAcsC4wC7gj5Ztb5L67\nA2cAGwHzgHuAUe4+o80eRkREOoy6q6mmgDoR+AHwEnBFev0d4B9mtk5e3lHAr4jnvBJ4ngiwD5rZ\nMgX3PQC4F+gHXAs8ChwCPGlmfdr2qUREpCOox5rqaGA14AR3/3ku0cy+C9wGXAp8w8xWB84FngKG\nu/snKd+5wJnAkcBVKa1X+n0KsIm7z0npDwI3EbXXE9vj4UREpH7VXU0V2At4B7g8P9HdfwO8BnzN\nzJYiarJLA2NyATUZA8wBDs9LOwDoC1yWC6jpnmMBBw4xs65t8CwiItKB1FVQTYFtDDDa3T8rkmUB\nsEz62S6lPZafwd3nE7XXjc2sd0rO5R1X5J7jgRWJflYREZGS6qr5190XEn2oSzCz9YD1gNfcfb6Z\nDQKmu/sHRbJPTcd1gX8Ag9LrKc3kfb5lJRcRkc6grmqqpaTm3quI57k+Ja8IvF/iktnp2Dsv7wJ3\nn1dGXhERkaLqqqZajJl1AX4J7Ag8w+d9rd2I5uBicuk9WpC3SQ0NDeVkk2boc5SWKPW9GTJkSDuX\nRDqrug6qZrY0cAMx9WUKsKe7f5xOzyP6Vovpno4ftiBvk/Q/b+s1NDToc5SK6XsjtaBum3/NrCdw\nNxFQXwW2d/f/5WWZRekm21z67Ly8Pcysexl5RUREiqrLoGpmKxCLM+wGPAds4+5vFGR7BehvZssW\nucWawGdEMM7lBRhYIi/E1BoREZGS6i6omlkPYuWjLYjpMiNKLCM4gXi+bYtcPwx4MW9k8IR0HF7k\nPiOIWupLrS68iIh0aHUXVIl5qlsRc013zV+socBvgIXA6IJm3dOA5fl8lDDAn4APgJPNrG8u0cwO\nI6bS3FhiXqyIiMgidTVQKa37e3R6+RJwipkVy3qhu7uZXQKcAjxnZvcAGxKL8D9BDHACwN1nmtnJ\nxJq/k8zsDmBVYD+iaXhMGz2SiEjVmNl4YLC7a33zjNRVUCWabXOjdA9rIt/lwHxgFPAmcBRwLDAN\nuAw4x90Xm0Lj7teZ2SzgZCJwzyQW4z/d3Wdm+RAiIjXifGCFaheiI+nS2NhY7TJ0GA0NDY0a0t96\nmhohLdHM96ZLe5ZFOq967FMVERGpSfXW/Csi0uGlvs6libn4p6fkHxAzHs4lxoasBLwB3EqMI/k4\n7/qlgVOBQ4nxIQ6cDYwElnb3EXnvs1ifqpmtkt5jt/QebwK3A+e7+0cpz0Dg9VSmvsRWmqumtMvd\n/brsPo36oqAqIlKbBhObfZwFrAw8DkwEegHXEQF1K2KP6S3NbPe8WQq3AN8lZjZcCmwG/J6YHvjP\nUm9oZqsBfyeC6XXAy8DWxKyJHcxs+7TTV85pRNP6NcBHwDHAtWY21d0faN3j1ycFVRGR2rQccKi7\n3wlgZmOJzT82dffcYjTXmdk/gF8Q+0L/xsy2IgLqje5+RO5mZvYScHEz73kBsAqwi7v/NaVda2b/\nBC4igubP8vIvD6zj7u+l93iImJlxINApg6r6VEVEatf9sGgnrm8RNdX3zGyl3A9RG10I7Jmu2Tsd\nLyq41xXEfPyi0n7V3wAm5gXUnMuBOakM+R7KBVQAd3+ZWEt9QHmP1/EoqIqI1Ka57p7byGMlYh3y\nEcA7BT9vAF2BNVLedYFPKNgfOvW5vtbE+60IfIEiq8ela6fw+bKtOdOL3OfjVJ5OSc2/IiK1aWHe\n77kK0ANEH2kxuVpoN2BhiVXgSm1xmf8epeZZdi1yvVaaK6CgKiJS+94htp9czt0fzj9hZssQzbJv\np6RXga+Z2Wru/mZevqWIgU8vNvEec4ENCk+kpV7XBJ5v5XN0eGr+FRGpce6+ELgH2NbMdig4fQzw\nf8Ae6fVdeen5vks0Izf3HkPN7GsFp48jRh3fXXnpOxfVVEVE6sMpwPbA/Wb2S6LGOQQ4nJgmcw2A\nuz9mZrcDJ5nZmsQ2mV8Gvk/0tTa1jN6pwA7An83sWmJ+69ZEQM6NMpYmqKYqIlIH0p7RmxE7cO0L\nXAl8lQh0OxTs2HUwsa7vFsTI3a2BvYD3aKJfNb3H5sBvgW+nazcHzgG2K1wzXZaktX8zpLV/s6G1\nf6UltPZvMLPewMfuPq8gvQvRL3unux9clcJ1Aqqpioh0LHsAH5rZ1wvSvwksCzzd/kXqPNSnKiLS\nsdwPvAvcbGZXE2v3rgf8kOiHHVvFsnV4qqmKiHQgaf/nrYC/EIOTrib6YG8CtilYu1cyppqqiEgH\n4+7/Bg6qdjk6I9VURUREMqKgKiIikhEFVRERkYwoqIqIiGREQVVERCQjCqoiIiIZUVAVERHJiIKq\niIhIRhRURUREMlLRikpmthqwCvBfd3+rmbwG9Hf3v7WifCIiUiYzOwS4uZy87t5mO/eY2UDgdeBu\nd/9mW71PGeWYBGzcls9aqKygambrEv+hhuWlTQROdvfHS1x2BvAdoGtrCykiIhV5DBhf7UJ0Rs0G\nVTNbFXgc+CLwDvHXxwbE5rePmtkod7+kTUspIiKVGO/uo6tdiM6onD7VM4iAejWwqrsPAwYAP03n\nLzKzs9qofCIiInWjnObfXYH/AD9x94UA7v4RcJaZ/R24CzjbzGa5+5VtV1QREcmSmY0AxgGHEpWs\n44B1iP1YbwfOSv/e51/zA2AkMAiYBlyXjr8Ctnf38U283xrAqcDOwKrAp4ADN7j7dXn5DiG6HHcC\nNgF+AKwGvEXsB3thLh6l/MsCZxJdjv2B54GTK/5AMlBOTXVl4Ln8B8hx9/uJffoWApeZ2d4Zl09E\nRNreSCI4/gv4BTAfOCH9voiZXZbyLQvcADwFnA+c3dwbpMFLzwAHp+suA/4ArA9ca2Yji1x2ETCa\n6IK8BuhJtJKOyrvvUsTesaOA6cC1wCfAg8DqzT55xsqpqc4lIn9R7n6fmf0QuBG41cymu/uErAoo\nIlJL9jjh7p2Bw4C1gCnA2Hsu3fPB6pZqCSPMbHQT5x9w97/nvR4MbOvuTwGY2fnAq8B3zexYd//Q\nzDYDjgX+DnzV3eemvL8F7i2jTKcCK6VrH84lmtlVwNNELfOqgmvWBgan/WExs18ArwBH8nkX5MHA\ncKIGe4S7f5byXgycVEa5MlVOTfUZYKiZDS2Vwd3HEn+t9AD+bGZbZVQ+EZGakQLqGOIf+6XScUxK\nryXDidpjqZ9hBfkfywVUAHefDTxJ/Ju+Wko+COgCnJ4LqCnvfcBDZZTpNuD7+QE1XT8RmAf0K3LN\n73MBNeWdCkwGVjOzHin5AKARGJULqMmZwOwyypWpcmqqlwNfBR4ys0uBx919XGEmdz/TzFYm/oIb\nR1TDRUQ6ksNKpB9KNDfWinMqHP37SpG0XEDqno6bp+PEInmfIOJESakFc4KZ9SVqxmsDRgT4HhSf\nftlcueYDGwNvuPuMgvdbYGYNwA5NlStrzdZU3f0vwGlEW/bZwM+byHs4EYS7AV/KqIwiIrVirQrT\n68WCImmN6ZhbOGEl4MP8Wmqe/zX3Bma2gpndQgxqeoTom90LeCm9f7EFGsop1wrAByXedmZz5cpa\nWcsUuvuFwFeITuO7m8l7PLAb8ddMY1N5RUTqzJQK0zuSOUAPM+tW5NzyZVx/G9H/eROwNdDb3ddK\nlbHWmAX0LnGuVyvvXbGylyl095eIGms5eR8AHkjDnEVEOoqxRJ9qobKWBqxzDcCmwBBisFK+LZq6\n0Mz6EJWtZ9z9RwXnBhLNvy1dSrAB2NXMVnf3N/Lu25WYjtOuWrSgvpktY2YnmdklBel7mNkLZnay\nmS3l7vOyKaaISPWlUb6nESNjF6bjaTU4+rct5P5wON/MeuYSzWx7ohm3KR8DnwErmNkyedcuy+cj\nfovVgMtxSzr+vKAWfRJNzFxpKxUtqA9gZr2IDvktiCaPE/NO9wM2BC4AvmZmu7l7sTZxEZG6lAJo\nrQfR5qbUQCzuUDZ3f8rMrgN+CEwys78QQWtv4H2iz3WJ9QzStR+Z2R+AfYCJZvYg0TS7B7FC3yyg\nT6qMfVbsHk2U6w4z24dYM6HBzB4h4tAOxMJFa1Ryv9aqOKgSE4KHAQ+k3xdx95vM7GFiScNdgVOA\nc1tbSBERqcjw9NOUSUQwrMRI4DXgCCK4vkXUCFcmVjD6qPSlfB/4L1GrPQZ4G/gHUQn7DvATYHti\nEFOlDiCmfx4O/IgYNbxXes92DapdGhsrG0tkZv8CvgCs4+4fl8jTA/g3MVLMWl3KOtHQ0NA4ZMiQ\nahej7jU0NKDPUSrVzPem3bb+6qjMbADwsbsvMaLWzH5FzGMd4O6dejplS/pUBwITSwVUAHefT4z+\nbde/ELJgZkub2XFmNtnM5pnZFDM7s8SINxGRzuJ7wHtmdnB+opkNImqFkzt7QIWWNf++T2xU3py+\nlJ47VMuuJpbAmgD8mRj6fS4xwXifKpZLRKSabgdOB643s92J1siVgW8ByxBNw51eS2qqE4BhZlZy\n9Qwz2xbYhljmqm6k5RWPJHbe2c7dTwW2A34N7G1mX69m+UREqsXd/0usqnRbOh5PjJ15ENiq2Ep7\nnVFLaqqXEFX9P6fFje8F3kznvkR8yD8mFn64KItCtqOj0/Ecd28EcPdGMxsFHEh0gpezcLSISIeT\n1uH9frXLUcsqDqru/oyZHU5sw3MSi0+pgRgQsAA40t3rqqZK1Erfdfd/5Se6+//M7BWaH01Xs571\nGTw88Q2mvfchA1Zcjp2Grs6mVmz9ahERaakWLf7g7rcSe+CdSQx/nkwMYf4bsdrIBu5eVyuMmFl3\noqb9WoksU4l5VF9st0Jl5Fmfwa33T+btd+fS2NjI2+/O5db7J/Ps4utPi4hIK7Wk+ReI9vW0X92j\nxMClhUQz8LO5ptM60zcdS83byu2M0Bt4p+2Lk52HJ75RNP2RiW+otioikqEWBdW0juO5wCHAcgWn\n30mbzl7k7p+0rnjtKjdlptQKULn0HiXOAzFXrta89saMojsbvPbmRzVZXqjNz1FqX6nvjeY9S3tp\nyTKFfYDHgI2AT4gm3zeJvtQ1iOULzwG2TcsUFl22qgbl1ilepsT53J6CHzZ1k1r8n3fQ5Gd4+90l\nd2taZaVeNVleLf4gLaHvjdSCltRURwFfBu4HDnX3xZpCzaw/8Ctiw9ofA5e1tpDtZDax4HOpLYR6\n5+WrKzsNXZ1b75+8RPqOQ1evQmlERDqulgxU2odY73HvwoAKkFbU+BYwAzisdcVrP2mFqP8Aa5bI\nsiYxMrjdN71trU2tHwfutgGrrNSLpZbqwior9eLA3TZQf6qISMZaUlNdGbi3qd1n0o4EE4j98+rJ\nBOBAM1vX3V/JJZrZKsA61PEc1U2tn4KoiEgba0lN9TVggzLyrQ4UH3Zau36djmPMbCkAM+tC7KLQ\nBbi+WgUTEZHa15KgegGwgZldWCpDWhxiM+CnLS1YNbj7w8DviP0Bn0rP+Bix+8JdwH1VLJ6ISElm\ndouZNaZ1eYud/0c6/7cS5w9K58dU+L7j03V9WlLujqYlzb9zgXuAk8zsa8CdxMLKC4FViWUKdyY2\nMF/DzE7Lv9jdK/oPVgUHAi8S04V+QtS2zwIurtP5tyLSOYwDDga2pKACYGZ9gU2JwZjDzKyXuxdO\nCdgmHVuyn6kkLQmqfyLW9e1C7NzylYLzuX0LBwHnFaQ3Eisu1aw0t/Y8Fi+7iEityy1oP6zIuR2J\nlsk7gX2BESw5RmQbYD7wRBuVr1NoSVA9F4quJSAiIlXi7m+Y2RRgqJkt5e6f5Z3+KvApUVnYN71e\nFFRTTXY9YFzaD1taqCUL6o9ug3KIiEjrjSemMm4IvJCX/lXgaXd/IQXewq07tyZaExc1/ZrZ1sAJ\nRHPyisTCN88AY8rZ5s3MdiDWNRhKxJp/Ape6+10F+dYmWjC3AAYAbxPrIJzr7tPKeuoa0qIF9UVE\npCblgt2WuYQUtAYCD6ekh4H1zWzVvOsW6081sz2JQZrDgD8Si/g8STQjP2hmg5sqRBqs+jDRPfg7\n4JdAP+DO/HE2aYOSR4DdiT8Ifk6MafkRMM7MulFnWrygvohIZ7Tf7360M1EbXIsYkDn2jv2vfbC6\npVokv181NwUwVyvNBdVHgCNT+i0pbRtgDlEThdgL+31gk7SgDwBmdnI6tx8wqVgBzOxLwFXAy8C2\n7v5eSj89leE8M/tz2mJzf2L65WH5O5ul9eOPJga91tWsC9VURUTKlALqGGBt4t/PtYExKb3q3P0t\n4FXyaqpE8JwLPJ1eP0qMi9kJFm17OQQY7+4L0xz9UcBB+QE1GZ+OTa0k8z1irfSzcgE1lW0ecDbx\nuR2cknMxaJiZdc27x+nAyu5eVwEVVFMVkTrxms9g0sQ3mfXeR6ywYk8GD12NQe2/SlippVcPBWqp\ntnqEma1A1D63Bx7L7Rrm7u+a2fPECGCAzYkg+Eg6/xnR5IuZrUFsnjKIWPRn+3RNfgAslNvVYEcz\n26jgXK90zDUf30VMWTwS+JaZ/RX4C3B/PfangoKqiNSB13wGj97/8qLXM9/9cNHrdg6sa1WYXg3j\niSC1BdGE24cl554+DJxoZoOIQUqw+CClLwO/4PPA+wkwmWgeXpfPp04Wk1sE4odN5OkL4O7/M7PN\ngTOAbwLfTT8fm9ktwLH1NhpZQVVEat6kiW+WTG/noDqFaPItll4rcv2qmxGLPcDn/ak5jwAnAlsR\nQXW6u78IYGZfAB4iduY6Mf3+srt/bGZbAN9p5v1zi0oMcvdmPxd3fx34vpkdmcq8C1HzP5L4o+CU\n5u5RSxRURaTmzXrvo+LpM4unt6GxFF/A5uYiaVXh7tPM7GWiGbY7ETBfKMj2N+BjYgGfYUTgzNkB\n6A9c4u6XFly3fjo2VVP9J1Hr3IyCPzbMbB3gB0Rz9D1m9g0iiJ7q7nOIft+nzWwssZrdtmU8ck3R\nQCURqXkrrNizeHrf4ultJY3yPY0YDLQwHU+rodG/OeOIvtItKbLsoLt/BPwd+DrwxYI8uebW/vnX\nmNnqxEAjgKamutxGfDbnm9mAvOuXBq4k5r6umJLXI6bPFDYVD0zH/zTxPjVJNVURqXmDh662WJ9q\nfnp7SwG01oJooXFEsIIlm37JSz83/Z4fVCcAU4ltMFcCngdWA/YkAm4jnwfFJbj7q2nqzaXAi2Z2\nNzCLWBd+fWIlp9tS9huIZt6LzGwEUcvtR0zZ+ZDYwKWuqKYqIjVvkPVjh93Wo+9Ky9FlqS70XWk5\ndthtvWqM/q0X4/l8OdlSQTUXSKe4+6Iaobt/SEzD+QPRhHwMsRj/bcRiDs8D25pZL0pw958TCzpM\nInb9+gEx2OkEYB93/zTlmwUMB64lBkD9hKg93w9s4e7/rOSha0GXxkYt45uVhoaGxiFDhjSfUZrU\n0NCAPkepVDPfm6b6AEUyo5qqiIhIRhRURUREMqKgKiIikhEFVRERkYwoqIqIiGREQVVERCQjCqoi\nIiIZUVAVERHJiIKqiIhIRhRURUREMqKgKiIikhEFVRERkYwoqIqIiGRE+6mKiHRAZvYNYq/SoUBv\nYCYwEbjJ3f/cDu/fGzjQ3a/KS5sK9HH3Pm39/k2U63LgWGB7dx+f9f1VUxUR6WDM7ErgbmDDdPw5\n8BCwDXC3mV3fDsV4BTi8Hd6npqimKiLSgZjZCGAk8Hvg27kNwdO53sA44Agzu8/d727DovQD3m7D\n+9ck1VRFRDqWr6fjVfkBFcDdZwOnppffatdSdRKqqYqIdCzd0vHLwPgi5x8H9gNezSWYWVein/Fg\nYG2i/3U8cJa7v56XrztwAvA9YBAwF5gAnOfuz6Q8I4jaMMDGZtYInOPuo4sV1sx6AccBe6d7dgPe\nBP6Yrvsw5RsIvA6cAzwLnJGe8QOiiXuUu79bcO/D0nOtA7wFXFKsDFlSTVVEpGN5KB0vMbMrzWzL\nFDQBcPd57n6nu08CMLMuwL3ApURF60bgb8C3gQlmtmrK1wN4GDgf+BS4Nr3X14AnzWzP9BZTicAH\nMD39Pr5YQc1s6XTPc4im4muAscCywEnAr4pctgcRcN8GfkEEy8OB2wvufR5wEzFI6yZgEnA1sH/R\nTy0jqqmKiFTgiT333hk4DFgLmAKM3fru3z9Y3VJ9zt3vNbNrgR8RfasjgTlmNoEIgne5+3/zLjkU\n2AW4E/ieu38MYGb3Ar8FTgF+TAS5bYBbgCNyTctmNoSo/d5iZmu4+1RgtJmdDUwrVUNN9gG2AM53\n9zNyiWZ2ClGT/qaZ9XT3j/Ku2RTYz93vTHnPAJ4DdjSzQe7+mpmtQzRzTyJG+b6f8n4daNORz6qp\nioiUKQXUMUQT6VLpOCal1wx3P4roW30A+ARYHtgNuAyYYmYXmFnu3/8D0vG4XEBNbieedUJ6fQjw\nEfDj/L5ad28gaoB9qLyf9lmilnlZQfk/SOe6An0LrpmSC6gp7ydEbReimRdgX6LSeH4uoKa89wJ/\nrbCMFVFNVUSkfIeVSD8UqJnaKoC73wfcl/ostwN2BL5B/CFwKvFHwSnAxsAb7v5WwfWNwOkAZvYF\nomb+RAp4hSYAJ6Z7VVLGV4BXzKyHmW0BrJvKNwQYkbJ1LbjslSK3mp2O3dMxV45niuR9kqiZtwkF\nVRGR8q1VYXrVuftc4H7gfjM7Efg+cD1wjJmdA6xA9H02Zfl0nF3i/P/SsWclZUu15VHE4KcVUvIM\nIvBNBdYHuhRctqDIrRrTMZc3d69ifwDMrKSMlVLzr4hI+aZUmN6uzGx5M3s19Ycuwd0b3f1Gom91\nWeBLxAjeL5S433Lp11xwWqXEW+eC2HsVFvkE4KfA88CuwMru3t/d9wL+U+G98s1Kx95FzvVqxX2b\npaAqIlK+sSXSb27XUpTg7nOIQLKTmfVvJvtnwDTgBWB1MxtQJM8kM3sl3fd1wMzsi0XybZeOL1ZY\n5O8AC4E93f0Bd58Gi0Ykr5f6rE9SAAAVCUlEQVTyFNZUy9GQjlsXObdZC+5XNgVVEZEypVG+pxEj\nUxem42m1NPoXuIroW7zLzFYuPJnWBN4J+GMKlrcRgeui/Kk3ZrYv0b+ZGwR0C1G7vSxNhcnl2xQ4\nBngfuCfvrT4BlmmmrPOJPtPCQH0GMDD93o3K/S7d+8z8PxbMbFtgz5JXZUB9qiIiFUgBtJaCaKHz\niUUR9gH+bWZ/JQb3dCOmr2wNvExMuYGYw7k3cBDwFTMbB6ya0qaSBisBFxNzUr+b8j0K9Ae+SQTl\n/VOQznkLWC9N77nf3fMDbs5twDDgCTO7A/gY2J6YNjODWOpwxUo/AHf/T+o/vgp4zsz+QNTg9wXe\nIBaZaBOqqYqIdCDuvtDd9yWmtzwAbE6sKnQ40IMYGLSpu7+Ty08sqHAGURM9GtgB+A2wjbvPSvnm\nEzXcs4ga6I9SvnuALYusIzySaDI+jNK1w2uIWu57qXzfIfpvDyB22IGYCtSSz+FqYC8iiB5KNFGf\nRUz/aTNdGhsbm89VQ8xsJ2IY+ObEF2QK8GvgksJ1Ls2sL3AuMV+rH/AScLG7/67IfXsSX7YDiL/S\nXic+/GvS0PJmNTQ0NA4ZMqSFTyY5DQ0N6HOUSjXzvWlJv5xIxeqqpmpm3yOaXYYCfwCuS6cuAH6f\nOrdzeZcjRrgdBfydaAboA9xuZiML7tuVWE3kDMCBK4j+gKuAn7XhI4mISAdSN0HVzJYl1nmcAwx2\n98Pc/SfEJN+/EJOa98q75FiiXf4Yd/+2u58MDCZGp11kZv3y8u5PNDFc4u67u/upxAixR4HjzezL\nbfx4IiLSAdRNUCU6r1cAbszfNSEtUTUmvdw1L/9RxITm6/LyfkB04vck2u5zjiYWiB6Tl/cTouba\nhZgsLSIi0qR6CqpTiaHsfyhyLrfCRi8AMxtE9Is+njrh8+W2JBqe8nYnmpMn5Trk80wk1roc3trC\ni4hIx1c3U2rcfTIwucTpXLNvbuJxbrj0a0XuM83M5hNrTAKsQXwOxfIuNLM38/KKiIiUVE811aLM\nbH2i/3QBn++9l5vX9H7Ri6JftneZeWcDPfMnO4uIiBRT9UBhZlOJ2mJTrnb3kYWJZvYlYqHonsDx\n7v5mOpVbgaPYwsu59J4V5IWYvjO3mXLS0NDQXBYpgz5HaYlS3xtN0ZL2UvWgSuzgXmwtyXwTCxPM\nbG1iysxA4Jfunr8f37x0LLVEVnfgwwryNhJ9q83S/7ytp3mq0hL63kgtqHpQdffjKr3GzDYH7iOC\n8XXESN98Te1QALGN0fQy8/YG5rr7Z5WWU0REOpeqB9VKmdlXidrtcsAYdz+9SLbcJrZrFrl+ZaIp\n11PSVGK9yWJ5uwKrUXqAlIiIyCJ1NVDJzIYBfyL6Q39SIqDi7m8Q6z1ukzbBzTciHZ9KeT8FngY2\nSbvb5xua3uupTB4gz/PTJnP5kzcy6qELufzJG3l+muK2iEi9q5ugama9iO18coOSrmjmkluJDXgX\nDXBKQfN0oh/11ry8vyb6Ts/Jy9sNOC+9vKG15c/3/LTJ/N8/72ba3HdobGxk2tx3+L9/3q3AKiJS\n5+qp+fdIYHVgJtDHzEYXyfOyu9+efr8Y2A+4wsyGE/NQ9wbWIpYufCfvupuJXQyOS0sSNgC7EEsg\nXuLuL2T5IOOmPFk8/fWn2HjABlm+lYiItKN6Cqq5neX7AmeXyHM3cDuAu89JG9KOIbY12oXYQ/CA\nvMBLyrvQzHYhaqr7AdsQQXgkcG3Gz8H0D98tmj5jbvF0EZFypMrG2cB4YIdiO2yZWR9igOZj7j6i\niXsNJHbrajJfK8u5l7v/Kct7V1CGwcBzwK/c/ZCs7ls3QdXdv9mCa6ZT5rq9aV3g49NPm+q/3EpM\nm/vOEun9eq3U1m8tIp3DCGIf05uqXI5Op276VDuS7dfaqnj6mlu2c0lEpAP7mZn1r3YhOpu6qal2\nJLl+03GvP8WMue/Sr9dKbL/mlupPFZGsPAdsQmyXuX+Vy9KpKKhWycYDNlAQFZG2chFpjIiZ3eru\n92ZxUzMbQez0dRQxzuWbxLrp+7j7E2a2DHACcCAxKHQOsfLdme4+pYz7f53YinMzoE+69xPAaHef\nlJdvPLGa3jbEoNSvAcsCzwBnufv4gvt+hZjNsS2xnecfgdsq/wSap+ZfEZGOZwFwBLHE6jVF5uC3\n1tnA5sCVwLPAc2ka4l+IwaEfAFcBDxCzLv5hZhs1dUMzGwncA6wD/B9wObHwzp7A39LCPfl6AY8T\nszR+RaxhsDXw17T9Z+6+g4EJxH7bDwC/BXYGftPCZ2+SaqoiIhU494R7diYGAa0FTAHGnnXpHg9W\nt1RLcvfHzewGYjri+cCPM7z9F4DB7j4tl2BmJwE7EDXHU3Mjj83sF8CTwFhiQZ0lpH2tzydWw9vU\n3T/MO3cN8CNiFsf1eZetSATLfd39k5T3X+k+BwNnpXxXEOsb7Ozuj6Z8o4kR0gNa+gGUopqqiEiZ\nUkAdA6xN/Pu5NjAmpdeik4G3gaPTinRZmZAfUJPvE1tlnpE/lcfdnwHuADY3sw1L3K8rUbM+PD+g\nJuPTsV+R6y7NBdTk/nRcF8DMViGaqR/IBdRUpneAc0uUpVVUUxURKd9hJdIPBWqxtjrbzI4B7gJu\nMLNNM7r11PwXacU7A6YBp5tZYf5cjXAw8GKRcn5EBF7MbF1gA2AQsBGwY8rWtUg5Xil4PTsdu6fj\nxun4TJFri6/C00oKqiIi5VurwvSqc/ffm9ndRN/kycDVGdx2XsHr3C5fAyi9OA/E4j1Fmdl2wGVA\nLvDPB54nVrhbjRhgVKhwH+xcDTmXd4V0/KDItTObKGeLKaiKiJRvCtHkWyy9lh0NbA+cSYzGzdrc\ndHzc3bdrMmcRZrYGMchpPtEHPAF4Ja12tz8xyrglmtras1cL79kk9amKiJRvbIn0m9u1FBVy97eA\nUUSz6HVtcP/ZxM5gG5rZsoXnzewgMxudlj4s5pvEYKKz3P0Gd3/J3Remc+unY7GaanOeI2qvWxc5\nt1kL7tcsBVURkTKlUb6nAa8CC9PxtFoc/VvEtUQ/4iZtdP9biObdC/O33DSzDYjpNcdTusl1fjou\ntgJUml96bHrZrdICpcFUDwA7mNneefddnqabqVtMzb8iIhVIAbQeguhi3L3RzI4gam/L5J8zs0OI\nxRRucfepLXyLC4lFGH4MbJsWaOgD7AssB3zP3eeUuPZeYqGH08xsPWJDk3WAr/P54KMVW1iukcQf\nE3eY2Z+A/xLTcz5r4f2apJqqiEgn4e6TieBX6BCi5jawFfeeR/Tbng30IFZd2p1YEWl7d/9tE9e+\nBewEPEqM9j2KmBbzC2A94D1gFzOruAk4reQ0jNjBbDtiBPdzwDcqvVc5ujQ2LrEzkLRQQ0ND45Ah\nQ6pdjLrX0NCAPkepVDPfm5b0x4lUTDVVERGRjCioioiIZERBVUREJCMKqiIiIhlRUBUREcmIgqqI\niEhGFFRFREQyoqAqIiKSEQVVERGRjCioioiIZERBVUREJCMKqiIiIhlRUBUREcmIgqqIiEhGFFRF\nREQyoqAqIiKSEQVVERGRjCioioiIZERBVUREJCMKqiIiIhlRUBUREcmIgqqIiEhGFFRFREQyoqAq\nIiKSEQVVERGRjCioioiIZERBVUREJCNLV7sArWFmvYAXgC7uPrDI+b7AucDXgX7AS8DF7v67Inl7\nAqOAA4BVgdeBq4Fr3L2xrZ5BREQ6jnqvqV4ADCx2wsyWAx4CjgL+DlwF9AFuN7ORBXm7AncCZwAO\nXAF8kq75WRuVXUREOpi6DapmtjVwdBNZjgU2BY5x92+7+8nAYOBF4CIz65eXd39gN+ASd9/d3U8F\nNgMeBY43sy+3yUOIiEiHUpdB1cx6ADcBTwBzSmQ7CpgOXJdLcPcPgPOBnsB38vIeDXwKjMnL+wlR\nc+0CfD/D4ouISAdVl0EVOIdo9j0CWKK/08wGEf2ij7v7woLT49JxeMrbHRgKTHL3WQV5JwIf5fKK\niIg0pe6CqpkNAU4AfuruL5fINigdXys84e7TgPnAuilpDWLAVrG8C4E38/KKiIiUVFdB1cy6AWOB\nycBFTWRdMR3fL3F+DtC7zLyzgZ5mVtcjpUVEpO1VPVCY2VSittiUq919JDHlZSNgy9TnWUq3dFxQ\n4vwCol+13LwAPYC5zZSThoaG5rJIGfQ5SkuU+t4MGTKknUsinVXVgyrwR+CLzeSZaGYbAqcDV7j7\nxGbyz0vHZUqc7w58WEHeRqJvtVn6n7f1Ghoa9DlKxfS9kVpQ9aDq7sc1lyfNI30S+B9wZhm3zQ04\n6l3i/PLEyOBy8vYG5rr7Z2W8r4iIdGJVD6plWo0YoQsw18wKz/c2s0bgMXcfAbyS0tcszGhmKxNN\nuZ6SpgIfl8jbNb335NYVX0REOoN6CarvE9NoijmVGM17OREgcfc3zOwNYBszW6qgljkiHZ9KeT81\ns6eBoWb2hTSXNWco0ff6VFYPIiIiHVddBFV3fx8YXeycmf0EeN/dC8/fSvTBjgR+kfJ+IaXNS+dz\nfg1sSwTu41PebsB56fwNGTyGiIh0cHURVFvoYmA/4AozG07MQ90bWItYuvCdvLw3A4cCx6UlCRuA\nXYCNiaULX2jXkouISF2qq3mqlXD3OUTtc2w6Hk00Ix/g7lcV5F1IBNHLgPWJdYOXJmq5p7RjsUVE\npI7VfU3V3fs0cW46Za7bm/pSj08/IiIiFeuwNVUREZH2pqAqIiKSEQVVERGRjCioioiIZERBVURE\nJCMKqiIiIhlRUBUREcmIgqqIiEhGFFRFREQyoqAqIiKSEQVVERGRjCioioiIZKRLY2NjtcvQYTQ0\nNOjDFKlRQ4YM6VLtMkjHp6AqIiKSETX/ioiIZERBVUREJCMKqiIiIhlRUBUREcmIgqqIiEhGFFRF\nREQysnS1CyACYGZLA8cARwBrAm8DNwMXuvsn1SybtD8z+ylweonTv3P3b+flPQg4DlgXmAXcAZzl\n7nOL3Hd34AxgI2AecA8wyt1nZPsE0lkpqEqtuBo4EpgA/BnYGjgX2BjYp4rlkur4CrAAuLDIuX/l\nfjGzUcAY4J/AlcCXiQA7zMxGuPvHeXkPAH4LTAGuBVYHDgGGm9lm7v5+2zyKdCZa/EGqzsy2Ap4A\n7gL2c/dGM+sC3AIcBOzh7vdWsYjSzsxsKjDT3TdtIs/qwGvAP4DhuRYNMzsXOBM4xt2vSmm9gP8A\n7wObuPuclH4YcBNwqbuf2GYPJJ2G+lSlFhydjue4eyNAOo4CGoHDq1UwaX9mtjywBlH7bMoPiNa2\nMQVdBGOAOSz+vTkA6AtclguoAO4+FnDgEDPrmkHxpZNTUJVasB3wrrv/Kz/R3f8HvAIMr0qppFq+\nko7NBdXt0vGx/ER3nw88BWxsZr0L8o4rcp/xwIpEP6tIqyioSlWZWXfgS0QzXjFTgT5m9sV2K5RU\nWy6ormRmD5nZrPRzl5lZXr5BwHR3/6DIPaam47p5eSH6U5vLK9JiCqpSbX3TsdQgkdnp2LvEeel4\nckH1JKIZ9wbgaWBv4GkzG5zOr0j535sVgQXuPq+MvCItptG/Um3d0nFBifO59B7tUBapDQuJQUWH\nuPv4XKKZfRe4DRgLbEp8d8r93lSSV6TFFFSl2nI1h2VKnO+ejh+2Q1mkBrj70Xw+eC0//TdmdiSw\nXWoGnkf535tK8oq0mJp/pdpmA59Ruumtd14+kWfTcU1ioYdyvzezgB6pD7+5vCItpqAqVZUm5/+H\n+EeymDWJkcEz269UUi1mtrSZbW5mW5TIsmw6zidGhvc3s2WL5FuT+GPt1fT6lXQcWCIvxNQakVZR\nUJVaMAEYYGaLjb40s1WAdYjpEdI5dCUWAvlL4bzRtCDIVsCnwCTie7MUsG1Bvh7AMODFvJHBE9Kx\n2PSsEUQt9aVsHkE6MwVVqQW/TscxZrYULPoH9AKgC3B9tQom7cvdFxDr8a4AnFpw+gRiGcLfpiUF\nf0MMahpd0Kx7GrA8i39v/gR8AJxsZrkR57kVldYFbnT3zzJ+HOmEtEyh1AQzux3YH5hITNDfiqiB\nLFq6sIrFk3ZkZgOJ1okBwMPA88AQokb5ErCtu7+X8l4InJLS7wE2BHYnars7piCdu+8PiTV/3yQW\n3V8V2A/4N7CluhgkCwqqUhPMrBtRMzmE+MfuDeBW4OL8fxilczCzVYkNFXYj5pj+j/gD6zx3n52X\nrwtwVPoZBEwD/kAsebnEwCMz2x84GdgAmAn8FTjd3d9u0weSTkNBVUREJCPqUxUREcmIgqqIiEhG\nFFRFREQyoqAqIiKSEQVVERGRjCioioiIZERBVUREJCMKqiIZsDDfzM6odllEpHoUVEVaycy+CPyR\nz/flFJFOSkFVpBXMbCNiB5T1q10WEam+patdAJF6ZGY9gROJxdx7Aq9Tek9YEekkFFSlwzKz0cDZ\nwF5E4BsFrA28TSzOfoG7zyq4ZnNii7FtgT7AVOBO4NK8vTkhdjc5h1jA/XvAxum9RKQTU/OvdAaH\nEXtvdgXuI/o+TwL+VrC35oHElmH7E7vkPEDsy3k28FDa/DrnvZS+jrv/sT0eQkRqn2qq0hnsAVwC\nnOzujWa2LFFT3Y3YXmykma1G7LXZCOzq7g8ApED6R2AX4FjgIgB3v4fYv1NEZBHVVKUzeAE4JbfR\nubvPAw4FPgYOMbPuwEHAcsCVuYCa8s4nmoOnAP3bu+AiUl9UU5XO4A53/yw/wd1nmNlTwHBgM2BE\nOrVE7dPdJxMbYIuINEk1VekM/l0i/c10XAVYuSBNRKRiCqrSGSwskd4l77xabUSk1fQPiXQGq5ZI\nXyMd3ySmxhjwJaL/dDFmdjgwA7gn1zcrIlJINVXpDHYtTDCzAcAWwLvAs8RUmlJ51wBuIOa1KqCK\nSEkKqtIZ7GxmR+RemNlywC1AN+Aqd18I3AQsAH5sZtvl5V0WuDq9vK3dSiwidUnNv9IZTAGuT4H1\nDWAbYnrMI8CFAO4+xcyOImqk48xsAjATGEoMZHoM+FkVyi4idUQ1VekMbibmofYGdidWQzqJWORh\nQS6Tu48lptjcD2yU8n5ELBCxq7t/2s7lFpE606WxUV1E0jHlrf17prv/tMrFEZFOQDVVERGRjCio\nioiIZERBVUREJCPqUxUREcmIaqoiIiIZUVAVERHJiIKqiIhIRhRURUREMqKgKiIikpH/ByHqYBts\nWHoBAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a0cc41780>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "ax = plt.figure()\n",
        "ax = sns.lmplot('pc1', 'pc2',Xstar,hue='region', fit_reg=False)\n",
        "plt.axis('equal')\n",
        "plt.xlabel('pc1')\n",
        "plt.ylabel('pc2')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "collapsed": true
      },
      "outputs": [],
      "source": [
        "def plot_arrow(v,scale,text_pos,text_label):\n",
        "    plt.arrow(0, 0, scale*v[0], scale*v[1], head_width=0.2, head_length=0.2, linewidth=2, color='red')\n",
        "    plt.text(v[0]*text_pos, v[1]*text_pos, text_label, color='black', ha='center', va='center', fontsize=18)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a1520dac8>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdUAAAFgCAYAAADtvuMxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRESiRElVREQkSpRURUREouT/Awplm4hdIJSaAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x1a1551dda0>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "ax = plt.figure()\n",
        "ax = sns.lmplot('pc1', 'pc2',Xstar,hue='region', fit_reg=False)\n",
        "plt.axis('equal')\n",
        "plt.xlabel('pc1')\n",
        "plt.ylabel('pc2')\n",
        "\n",
        "lab = ['Fresh_potatoes ',\n",
        " 'Fresh_fruit ',\n",
        " 'Soft_drinks ',\n",
        " 'Alcoholic_drinks ']\n",
        "\n",
        "for i,label in enumerate(lab):\n",
        "    plot_arrow(components[label],500,500,label)"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.6.9"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}