diff --git "a/dev.ipynb" "b/dev.ipynb"
--- "a/dev.ipynb"
+++ "b/dev.ipynb"
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -46,7 +46,7 @@
        "       [ -8.50038027,  -4.54370383]])"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -57,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -66,7 +66,7 @@
        "array([1, 0, 2, 2, 2])"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -77,7 +77,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -87,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -100,7 +100,7 @@
        "       [-1.29924521, -0.87253446]])"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -120,19 +120,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(init=&#x27;random&#x27;, n_clusters=3, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KMeans</label><div class=\"sk-toggleable__content\"><pre>KMeans(init=&#x27;random&#x27;, n_clusters=3, random_state=42)</pre></div></div></div></div></div>"
+       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KMeans(init=&#x27;random&#x27;, n_clusters=3, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KMeans</label><div class=\"sk-toggleable__content\"><pre>KMeans(init=&#x27;random&#x27;, n_clusters=3, random_state=42)</pre></div></div></div></div></div>"
       ],
       "text/plain": [
        "KMeans(init='random', n_clusters=3, random_state=42)"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -143,7 +143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -152,7 +152,7 @@
        "74.57960106819854"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -163,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -174,7 +174,7 @@
        "       [ 1.19539276,  0.13158148]])"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -185,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -194,7 +194,7 @@
        "2"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -205,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -214,7 +214,7 @@
        "array([2, 0, 1, 1, 1], dtype=int32)"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -225,22 +225,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x12d793f40>"
-      ]
-     },
-     "execution_count": 40,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -252,17 +242,18 @@
     }
    ],
    "source": [
-    "plt.scatter(scaled_features[:,0], scaled_features[:,1])"
+    "plt.scatter(scaled_features[:,0], scaled_features[:,1], c=kmeans.labels_, marker=\"o\", label='dataset')\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -276,15 +267,15 @@
    "source": [
     "fig = plt.figure()\n",
     "ax1 = fig.add_subplot(111)\n",
-    "ax1.scatter(scaled_features[:,0], scaled_features[:,1], s=8, c='c', marker=\"o\", label='dataset')\n",
-    "ax1.scatter(kmeans.cluster_centers_[:,0],kmeans.cluster_centers_[:,1], s=40, c='m', marker=\"o\", label='cluster centers')\n",
+    "ax1.scatter(scaled_features[:,0], scaled_features[:,1], c=kmeans.labels_, s=8, marker=\"o\", label='dataset')\n",
+    "ax1.scatter(kmeans.cluster_centers_[:,0],kmeans.cluster_centers_[:,1], s=50, c='r', marker=\"o\", label='cluster centers')\n",
     "plt.legend(loc='upper left')\n",
     "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -294,7 +285,7 @@
        "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }