crypto_clusters.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9914f1c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from pathlib import Path\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51331797",
   "metadata": {},
   "source": [
    "### Data preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0f8227c",
   "metadata": {},
   "source": [
    "* Read `crypto_data.csv` into Pandas. The dataset was obtained from [CryptoCompare](https://min-api.cryptocompare.com/data/all/coinlist)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1989f3bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CoinName</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>IsTrading</th>\n",
       "      <th>ProofType</th>\n",
       "      <th>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42 Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>True</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>365Coin</td>\n",
       "      <td>X11</td>\n",
       "      <td>True</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2300000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>404Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>True</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>SixEleven</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>True</td>\n",
       "      <td>PoW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>611000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>808</th>\n",
       "      <td>808</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>True</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CoinName Algorithm  IsTrading ProofType  TotalCoinsMined TotalCoinSupply\n",
       "42     42 Coin    Scrypt       True   PoW/PoS     4.199995e+01              42\n",
       "365    365Coin       X11       True   PoW/PoS              NaN      2300000000\n",
       "404    404Coin    Scrypt       True   PoW/PoS     1.055185e+09       532000000\n",
       "611  SixEleven   SHA-256       True       PoW              NaN          611000\n",
       "808        808   SHA-256       True   PoW/PoS     0.000000e+00               0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in csv and covert to dataframe\n",
    "file_path = Path(\"data/crypto_data.csv\")\n",
    "crypto_df = pd.read_csv(file_path,index_col = 0)\n",
    "crypto_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e8683cba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1252, 6)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# EDA\n",
    "crypto_df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd0e826e",
   "metadata": {},
   "source": [
    "* Discard all cryptocurrencies that are not being traded. In other words, filter for currencies that are currently being traded. Then, drop the `IsTrading` column from the dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b4696ad3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CoinName</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>ProofType</th>\n",
       "      <th>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42 Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>365Coin</td>\n",
       "      <td>X11</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2300000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>404Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>SixEleven</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>611000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>808</th>\n",
       "      <td>808</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SERO</th>\n",
       "      <td>Super Zero</td>\n",
       "      <td>Ethash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UOS</th>\n",
       "      <td>UOS</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>DPoI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDX</th>\n",
       "      <td>Beldex</td>\n",
       "      <td>CryptoNight</td>\n",
       "      <td>PoW</td>\n",
       "      <td>9.802226e+08</td>\n",
       "      <td>1400222610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>Horizen</td>\n",
       "      <td>Equihash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>7.296538e+06</td>\n",
       "      <td>21000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XBC</th>\n",
       "      <td>BitcoinPlus</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoS</td>\n",
       "      <td>1.283270e+05</td>\n",
       "      <td>1000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1144 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         CoinName    Algorithm ProofType  TotalCoinsMined TotalCoinSupply\n",
       "42        42 Coin       Scrypt   PoW/PoS     4.199995e+01              42\n",
       "365       365Coin          X11   PoW/PoS              NaN      2300000000\n",
       "404       404Coin       Scrypt   PoW/PoS     1.055185e+09       532000000\n",
       "611     SixEleven      SHA-256       PoW              NaN          611000\n",
       "808           808      SHA-256   PoW/PoS     0.000000e+00               0\n",
       "...           ...          ...       ...              ...             ...\n",
       "SERO   Super Zero       Ethash       PoW              NaN      1000000000\n",
       "UOS           UOS      SHA-256      DPoI              NaN      1000000000\n",
       "BDX        Beldex  CryptoNight       PoW     9.802226e+08      1400222610\n",
       "ZEN       Horizen     Equihash       PoW     7.296538e+06        21000000\n",
       "XBC   BitcoinPlus       Scrypt       PoS     1.283270e+05         1000000\n",
       "\n",
       "[1144 rows x 5 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter for currencies that are currently being traded\n",
    "crypto_trading = crypto_df[crypto_df.IsTrading == True]\n",
    "\n",
    "# drop the `IsTrading` column from the dataframe.\n",
    "crypto_trading = crypto_trading.drop(columns=['IsTrading'])\n",
    "crypto_trading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e8faa9ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CoinName</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>ProofType</th>\n",
       "      <th>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42 Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>404Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>808</th>\n",
       "      <td>808</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>EliteCoin</td>\n",
       "      <td>X13</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>2.927942e+10</td>\n",
       "      <td>314159265359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTC</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW</td>\n",
       "      <td>1.792718e+07</td>\n",
       "      <td>21000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEPH</th>\n",
       "      <td>ZEPHYR</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>DPoS</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>2000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAP</th>\n",
       "      <td>Gapcoin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.493105e+07</td>\n",
       "      <td>250000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDX</th>\n",
       "      <td>Beldex</td>\n",
       "      <td>CryptoNight</td>\n",
       "      <td>PoW</td>\n",
       "      <td>9.802226e+08</td>\n",
       "      <td>1400222610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>Horizen</td>\n",
       "      <td>Equihash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>7.296538e+06</td>\n",
       "      <td>21000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XBC</th>\n",
       "      <td>BitcoinPlus</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoS</td>\n",
       "      <td>1.283270e+05</td>\n",
       "      <td>1000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>685 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         CoinName    Algorithm ProofType  TotalCoinsMined TotalCoinSupply\n",
       "42        42 Coin       Scrypt   PoW/PoS     4.199995e+01              42\n",
       "404       404Coin       Scrypt   PoW/PoS     1.055185e+09       532000000\n",
       "808           808      SHA-256   PoW/PoS     0.000000e+00               0\n",
       "1337    EliteCoin          X13   PoW/PoS     2.927942e+10    314159265359\n",
       "BTC       Bitcoin      SHA-256       PoW     1.792718e+07        21000000\n",
       "...           ...          ...       ...              ...             ...\n",
       "ZEPH       ZEPHYR      SHA-256      DPoS     2.000000e+09      2000000000\n",
       "GAP       Gapcoin       Scrypt   PoW/PoS     1.493105e+07       250000000\n",
       "BDX        Beldex  CryptoNight       PoW     9.802226e+08      1400222610\n",
       "ZEN       Horizen     Equihash       PoW     7.296538e+06        21000000\n",
       "XBC   BitcoinPlus       Scrypt       PoS     1.283270e+05         1000000\n",
       "\n",
       "[685 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop NA\n",
    "crypto_trading.dropna(inplace=True)\n",
    "crypto_trading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f9676b36",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CoinName</th>\n",
       "      <th>Algorithm</th>\n",
       "      <th>ProofType</th>\n",
       "      <th>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42 Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>404Coin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>EliteCoin</td>\n",
       "      <td>X13</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>2.927942e+10</td>\n",
       "      <td>314159265359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTC</th>\n",
       "      <td>Bitcoin</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW</td>\n",
       "      <td>1.792718e+07</td>\n",
       "      <td>21000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ETH</th>\n",
       "      <td>Ethereum</td>\n",
       "      <td>Ethash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>1.076842e+08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEPH</th>\n",
       "      <td>ZEPHYR</td>\n",
       "      <td>SHA-256</td>\n",
       "      <td>DPoS</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>2000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAP</th>\n",
       "      <td>Gapcoin</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.493105e+07</td>\n",
       "      <td>250000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDX</th>\n",
       "      <td>Beldex</td>\n",
       "      <td>CryptoNight</td>\n",
       "      <td>PoW</td>\n",
       "      <td>9.802226e+08</td>\n",
       "      <td>1400222610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>Horizen</td>\n",
       "      <td>Equihash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>7.296538e+06</td>\n",
       "      <td>21000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XBC</th>\n",
       "      <td>BitcoinPlus</td>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoS</td>\n",
       "      <td>1.283270e+05</td>\n",
       "      <td>1000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>532 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         CoinName    Algorithm ProofType  TotalCoinsMined TotalCoinSupply\n",
       "42        42 Coin       Scrypt   PoW/PoS     4.199995e+01              42\n",
       "404       404Coin       Scrypt   PoW/PoS     1.055185e+09       532000000\n",
       "1337    EliteCoin          X13   PoW/PoS     2.927942e+10    314159265359\n",
       "BTC       Bitcoin      SHA-256       PoW     1.792718e+07        21000000\n",
       "ETH      Ethereum       Ethash       PoW     1.076842e+08               0\n",
       "...           ...          ...       ...              ...             ...\n",
       "ZEPH       ZEPHYR      SHA-256      DPoS     2.000000e+09      2000000000\n",
       "GAP       Gapcoin       Scrypt   PoW/PoS     1.493105e+07       250000000\n",
       "BDX        Beldex  CryptoNight       PoW     9.802226e+08      1400222610\n",
       "ZEN       Horizen     Equihash       PoW     7.296538e+06        21000000\n",
       "XBC   BitcoinPlus       Scrypt       PoS     1.283270e+05         1000000\n",
       "\n",
       "[532 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter the total coins mined greater than zero\n",
    "crypto_mined = crypto_trading[crypto_trading.TotalCoinsMined > 0]\n",
    "crypto_mined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ed454685",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save Coin Name in a separate table \n",
    "CoinName = crypto_mined.filter(['CoinName'], axis=1)\n",
    "# Drop the CoinName column\n",
    "crypto_mined2 = crypto_mined.drop(['CoinName'], axis=1)\n",
    "labels = crypto_mined['CoinName']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8ec5bf2",
   "metadata": {},
   "source": [
    "* In order for the dataset to be comprehensible to a machine learning algorithm, its data should be numeric. Since the coin names do not contribute to the analysis of the data, delete the `CoinName` from the original dataframe."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c22e594",
   "metadata": {},
   "source": [
    "### Pandas get_dummies\n",
    "* Convert the remaining features with text values, `Algorithm` and `ProofType`, into numerical data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bce77ba9",
   "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>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "      <th>Algorithm_1GB AES Pattern Search</th>\n",
       "      <th>Algorithm_536</th>\n",
       "      <th>Algorithm_Argon2d</th>\n",
       "      <th>Algorithm_BLAKE256</th>\n",
       "      <th>Algorithm_Blake</th>\n",
       "      <th>Algorithm_Blake2S</th>\n",
       "      <th>Algorithm_Blake2b</th>\n",
       "      <th>Algorithm_C11</th>\n",
       "      <th>...</th>\n",
       "      <th>ProofType_PoW/PoS</th>\n",
       "      <th>ProofType_PoW/PoS</th>\n",
       "      <th>ProofType_PoW/PoW</th>\n",
       "      <th>ProofType_PoW/nPoS</th>\n",
       "      <th>ProofType_Pos</th>\n",
       "      <th>ProofType_Proof of Authority</th>\n",
       "      <th>ProofType_Proof of Trust</th>\n",
       "      <th>ProofType_TPoS</th>\n",
       "      <th>ProofType_Zero-Knowledge Proof</th>\n",
       "      <th>ProofType_dPoW/PoW</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>2.927942e+10</td>\n",
       "      <td>314159265359</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTC</th>\n",
       "      <td>1.792718e+07</td>\n",
       "      <td>21000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ETH</th>\n",
       "      <td>1.076842e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEPH</th>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>2000000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAP</th>\n",
       "      <td>1.493105e+07</td>\n",
       "      <td>250000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDX</th>\n",
       "      <td>9.802226e+08</td>\n",
       "      <td>1400222610</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>7.296538e+06</td>\n",
       "      <td>21000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XBC</th>\n",
       "      <td>1.283270e+05</td>\n",
       "      <td>1000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>532 rows × 98 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      TotalCoinsMined TotalCoinSupply  Algorithm_1GB AES Pattern Search  \\\n",
       "42       4.199995e+01              42                                 0   \n",
       "404      1.055185e+09       532000000                                 0   \n",
       "1337     2.927942e+10    314159265359                                 0   \n",
       "BTC      1.792718e+07        21000000                                 0   \n",
       "ETH      1.076842e+08               0                                 0   \n",
       "...               ...             ...                               ...   \n",
       "ZEPH     2.000000e+09      2000000000                                 0   \n",
       "GAP      1.493105e+07       250000000                                 0   \n",
       "BDX      9.802226e+08      1400222610                                 0   \n",
       "ZEN      7.296538e+06        21000000                                 0   \n",
       "XBC      1.283270e+05         1000000                                 0   \n",
       "\n",
       "      Algorithm_536  Algorithm_Argon2d  Algorithm_BLAKE256  Algorithm_Blake  \\\n",
       "42                0                  0                   0                0   \n",
       "404               0                  0                   0                0   \n",
       "1337              0                  0                   0                0   \n",
       "BTC               0                  0                   0                0   \n",
       "ETH               0                  0                   0                0   \n",
       "...             ...                ...                 ...              ...   \n",
       "ZEPH              0                  0                   0                0   \n",
       "GAP               0                  0                   0                0   \n",
       "BDX               0                  0                   0                0   \n",
       "ZEN               0                  0                   0                0   \n",
       "XBC               0                  0                   0                0   \n",
       "\n",
       "      Algorithm_Blake2S  Algorithm_Blake2b  Algorithm_C11  ...  \\\n",
       "42                    0                  0              0  ...   \n",
       "404                   0                  0              0  ...   \n",
       "1337                  0                  0              0  ...   \n",
       "BTC                   0                  0              0  ...   \n",
       "ETH                   0                  0              0  ...   \n",
       "...                 ...                ...            ...  ...   \n",
       "ZEPH                  0                  0              0  ...   \n",
       "GAP                   0                  0              0  ...   \n",
       "BDX                   0                  0              0  ...   \n",
       "ZEN                   0                  0              0  ...   \n",
       "XBC                   0                  0              0  ...   \n",
       "\n",
       "      ProofType_PoW/PoS  ProofType_PoW/PoS   ProofType_PoW/PoW  \\\n",
       "42                    1                   0                  0   \n",
       "404                   1                   0                  0   \n",
       "1337                  1                   0                  0   \n",
       "BTC                   0                   0                  0   \n",
       "ETH                   0                   0                  0   \n",
       "...                 ...                 ...                ...   \n",
       "ZEPH                  0                   0                  0   \n",
       "GAP                   1                   0                  0   \n",
       "BDX                   0                   0                  0   \n",
       "ZEN                   0                   0                  0   \n",
       "XBC                   0                   0                  0   \n",
       "\n",
       "      ProofType_PoW/nPoS  ProofType_Pos  ProofType_Proof of Authority  \\\n",
       "42                     0              0                             0   \n",
       "404                    0              0                             0   \n",
       "1337                   0              0                             0   \n",
       "BTC                    0              0                             0   \n",
       "ETH                    0              0                             0   \n",
       "...                  ...            ...                           ...   \n",
       "ZEPH                   0              0                             0   \n",
       "GAP                    0              0                             0   \n",
       "BDX                    0              0                             0   \n",
       "ZEN                    0              0                             0   \n",
       "XBC                    0              0                             0   \n",
       "\n",
       "      ProofType_Proof of Trust  ProofType_TPoS  \\\n",
       "42                           0               0   \n",
       "404                          0               0   \n",
       "1337                         0               0   \n",
       "BTC                          0               0   \n",
       "ETH                          0               0   \n",
       "...                        ...             ...   \n",
       "ZEPH                         0               0   \n",
       "GAP                          0               0   \n",
       "BDX                          0               0   \n",
       "ZEN                          0               0   \n",
       "XBC                          0               0   \n",
       "\n",
       "      ProofType_Zero-Knowledge Proof  ProofType_dPoW/PoW  \n",
       "42                                 0                   0  \n",
       "404                                0                   0  \n",
       "1337                               0                   0  \n",
       "BTC                                0                   0  \n",
       "ETH                                0                   0  \n",
       "...                              ...                 ...  \n",
       "ZEPH                               0                   0  \n",
       "GAP                                0                   0  \n",
       "BDX                                0                   0  \n",
       "ZEN                                0                   0  \n",
       "XBC                                0                   0  \n",
       "\n",
       "[532 rows x 98 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert Algorithm and ProofType into numerical data\n",
    "crypto_data = pd.get_dummies(crypto_mined2, columns=['Algorithm', 'ProofType'])\n",
    "crypto_data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe67d78a",
   "metadata": {},
   "source": [
    "### StandardScaler\n",
    "* Standardize the dataset so that columns that contain larger values do not unduly influence the outcome."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "29d3599c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.11710817, -0.1528703 , -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ],\n",
       "       [-0.09396955, -0.145009  , -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ],\n",
       "       [ 0.52494561,  4.48942416, -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ],\n",
       "       ...,\n",
       "       [-0.09561336, -0.13217937, -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ],\n",
       "       [-0.11694817, -0.15255998, -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ],\n",
       "       [-0.11710536, -0.15285552, -0.0433963 , ..., -0.0433963 ,\n",
       "        -0.0433963 , -0.0433963 ]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Standardize your dataset \n",
    "scale = StandardScaler()\n",
    "crypto_scaled = scale.fit_transform(crypto_data)\n",
    "crypto_scaled"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01acf9e2",
   "metadata": {},
   "source": [
    "### Dimensionality Reduction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9f16892",
   "metadata": {},
   "source": [
    "### PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1455414d",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-3.35125284e-01,  1.03266037e+00, -5.90248784e-01, ...,\n",
       "        -4.55492260e-07, -3.04115675e-06,  1.22195992e-03],\n",
       "       [-3.18460446e-01,  1.03280102e+00, -5.90662374e-01, ...,\n",
       "        -2.93937207e-07, -1.49619504e-06,  1.22055987e-03],\n",
       "       [ 2.30526357e+00,  1.64964558e+00, -6.87682515e-01, ...,\n",
       "        -5.20661321e-08, -3.70073826e-05,  1.10578916e-02],\n",
       "       ...,\n",
       "       [ 3.24421251e-01, -2.30991644e+00,  4.22794086e-01, ...,\n",
       "        -1.55155417e-06, -9.20268177e-06,  2.43187167e-03],\n",
       "       [-1.49595012e-01, -2.05428579e+00,  4.09091915e-01, ...,\n",
       "        -8.32272780e-08, -2.82260024e-06, -1.80174423e-04],\n",
       "       [-2.89997198e-01,  8.17993972e-01, -2.79796330e-01, ...,\n",
       "        -3.99031651e-07, -3.78969644e-05, -5.04909530e-04]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Using PCA to reduce to 4 dimensions (three principal components)\n",
    "n = 73\n",
    "pca = PCA(n_components = n)\n",
    "\n",
    "crypto_pca = pca.fit_transform(crypto_scaled)\n",
    "crypto_pca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7b35ad24",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The explained variance ratio: [0.0279317  0.02141793 0.02051609 0.02044661 0.02044658 0.02044657\n",
      " 0.02044644 0.02042552 0.01870901 0.01756281 0.01741094 0.01628941\n",
      " 0.01596136 0.01551128 0.01434991 0.0132091  0.0123654  0.01204709\n",
      " 0.01104099 0.01071303 0.01048944 0.01040648 0.01038997 0.01037702\n",
      " 0.01034873 0.01033724 0.01029558 0.0102815  0.01028105 0.01027942\n",
      " 0.01027832 0.0102753  0.01026884 0.01026308 0.01026064 0.0102546\n",
      " 0.0102533  0.01025019 0.01024879 0.01024257 0.01024229 0.01024202\n",
      " 0.01023801 0.01023625 0.01023508 0.01023354 0.01022983 0.01022438\n",
      " 0.0102233  0.0102233  0.0102233  0.0102233  0.0102233  0.0102233\n",
      " 0.0102233  0.0102233  0.0102233  0.0102233  0.0102233  0.0102233\n",
      " 0.0102233  0.0102233  0.0102233  0.0102233  0.0102233  0.0102233\n",
      " 0.0102233  0.0102233  0.0102233  0.0102233  0.0102233  0.0102233\n",
      " 0.01022262]\n"
     ]
    }
   ],
   "source": [
    "# explained_variance_ratio AND explained_variance_\n",
    "print(f'The explained variance ratio: {pca.explained_variance_ratio_}')\n",
    "# print(f'The explained variance : {pca.explained_variance_}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1246ac40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp_var_pca = pca.explained_variance_ratio_\n",
    "# Cumulative sum of eigenvalues; This will be used to create step plot\n",
    "# for visualizing the variance explained by each principal component.\n",
    "#\n",
    "cum_sum_eigenvalues = np.cumsum(exp_var_pca)\n",
    "plt.figure(figsize=(8,6))\n",
    "plt.bar(range(0,len(exp_var_pca)), exp_var_pca, alpha=0.5, align='center', label='Individual explained variance')\n",
    "plt.step(range(0,len(cum_sum_eigenvalues)), cum_sum_eigenvalues, where='mid',label='Cumulative explained variance')\n",
    "\n",
    "\n",
    "plt.ylabel('Explained variance ratio')\n",
    "plt.xlabel('Principal component index')\n",
    "plt.legend(loc='best')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "471fe8fe",
   "metadata": {},
   "source": [
    "**With 73principal component, we are able to preserve 90% of the explained variance in dimensionality reduction.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d56e1b1",
   "metadata": {},
   "source": [
    "### TSNE\n",
    "* Further reduce the dataset dimensions with t-SNE and visually inspect the results.\n",
    "* Run t-SNE on the principal components: the output of the PCA transformation. Then create a scatter plot of the t-SNE output. Observe whether there are distinct clusters or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "45eace31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(532, 2)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tsne = TSNE(n_components=2, random_state=42, n_iter=1000)\n",
    "crypto_TSNE = tsne.fit_transform(crypto_pca)\n",
    "crypto_TSNE.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ea611dd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "crypto_mined2['x'] = crypto_TSNE[:, 0]\n",
    "crypto_mined2['y'] = crypto_TSNE[:, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b6fde75d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "plt.scatter('x', 'y', data=crypto_mined2, alpha=0.5, edgecolor='w',\n",
    "            cmap=plt.cm.get_cmap('nipy_spectral', 10))\n",
    "\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3879515f",
   "metadata": {},
   "source": [
    "### K Means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aac940e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# iterate through k = 1~10, and collect the result in a inertia list\n",
    "kmeans_list = [KMeans(n_clusters=k, random_state=42).fit(crypto_TSNE) for k in range(1, 11)]\n",
    "inertias = [model.inertia_ for model in kmeans_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4c24f7fc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 5))\n",
    "plt.plot(range(1, 11), inertias, \"bo-\")\n",
    "plt.xlabel(\"$k$\", fontsize=14)\n",
    "plt.ylabel(\"Inertia\", fontsize=14)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "29077566",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = KMeans(n_clusters=4, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fb187d45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(n_clusters=4, random_state=42)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fitting model\n",
    "model.fit(crypto_TSNE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0ff23d35",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get predictions\n",
    "predictions = model.predict(crypto_TSNE)\n",
    "predictions = pd.DataFrame(predictions)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "20691f7c",
   "metadata": {
    "scrolled": false
   },
   "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>Algorithm</th>\n",
       "      <th>ProofType</th>\n",
       "      <th>TotalCoinsMined</th>\n",
       "      <th>TotalCoinSupply</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>4.199995e+01</td>\n",
       "      <td>42</td>\n",
       "      <td>20.299915</td>\n",
       "      <td>2.438020</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.055185e+09</td>\n",
       "      <td>532000000</td>\n",
       "      <td>20.806366</td>\n",
       "      <td>7.440047</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>X13</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>2.927942e+10</td>\n",
       "      <td>314159265359</td>\n",
       "      <td>26.672478</td>\n",
       "      <td>15.567253</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BTC</th>\n",
       "      <td>SHA-256</td>\n",
       "      <td>PoW</td>\n",
       "      <td>1.792718e+07</td>\n",
       "      <td>21000000</td>\n",
       "      <td>-29.299261</td>\n",
       "      <td>17.163460</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ETH</th>\n",
       "      <td>Ethash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>1.076842e+08</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.355748</td>\n",
       "      <td>-17.481886</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEPH</th>\n",
       "      <td>SHA-256</td>\n",
       "      <td>DPoS</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>2000000000</td>\n",
       "      <td>-26.364012</td>\n",
       "      <td>15.328937</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GAP</th>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoW/PoS</td>\n",
       "      <td>1.493105e+07</td>\n",
       "      <td>250000000</td>\n",
       "      <td>23.820419</td>\n",
       "      <td>5.403740</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDX</th>\n",
       "      <td>CryptoNight</td>\n",
       "      <td>PoW</td>\n",
       "      <td>9.802226e+08</td>\n",
       "      <td>1400222610</td>\n",
       "      <td>-11.700278</td>\n",
       "      <td>-24.468109</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>Equihash</td>\n",
       "      <td>PoW</td>\n",
       "      <td>7.296538e+06</td>\n",
       "      <td>21000000</td>\n",
       "      <td>-19.422518</td>\n",
       "      <td>-12.575702</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XBC</th>\n",
       "      <td>Scrypt</td>\n",
       "      <td>PoS</td>\n",
       "      <td>1.283270e+05</td>\n",
       "      <td>1000000</td>\n",
       "      <td>-4.569258</td>\n",
       "      <td>5.820891</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>532 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Algorithm ProofType  TotalCoinsMined TotalCoinSupply          x  \\\n",
       "42         Scrypt   PoW/PoS     4.199995e+01              42  20.299915   \n",
       "404        Scrypt   PoW/PoS     1.055185e+09       532000000  20.806366   \n",
       "1337          X13   PoW/PoS     2.927942e+10    314159265359  26.672478   \n",
       "BTC       SHA-256       PoW     1.792718e+07        21000000 -29.299261   \n",
       "ETH        Ethash       PoW     1.076842e+08               0  -5.355748   \n",
       "...           ...       ...              ...             ...        ...   \n",
       "ZEPH      SHA-256      DPoS     2.000000e+09      2000000000 -26.364012   \n",
       "GAP        Scrypt   PoW/PoS     1.493105e+07       250000000  23.820419   \n",
       "BDX   CryptoNight       PoW     9.802226e+08      1400222610 -11.700278   \n",
       "ZEN      Equihash       PoW     7.296538e+06        21000000 -19.422518   \n",
       "XBC        Scrypt       PoS     1.283270e+05         1000000  -4.569258   \n",
       "\n",
       "              y  Class  \n",
       "42     2.438020      1  \n",
       "404    7.440047      1  \n",
       "1337  15.567253      1  \n",
       "BTC   17.163460      2  \n",
       "ETH  -17.481886      0  \n",
       "...         ...    ...  \n",
       "ZEPH  15.328937      2  \n",
       "GAP    5.403740      1  \n",
       "BDX  -24.468109      0  \n",
       "ZEN  -12.575702      0  \n",
       "XBC    5.820891      3  \n",
       "\n",
       "[532 rows x 7 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crypto_mined2['Class'] = model.labels_\n",
    "crypto_mined2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7167085d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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f21zGUFcb9N14zcLe9XFGwS1SJNO+9KVBn1N9wQVjUMkEVVYNLtn7mkt618cZBbdIkcy4+iqmfeUrhCZN6v+gGdUXXMDcu+4c+8Imio9fDThIJiCVvsWlr48vmsctIuPH+JlVMuA8bgW3iMhw9T3t/cilxTpkQQtwRIZi+zevZ+Pxi9m46Fg2Hr+Y7d+83u+SZCDrVsAdR8B3pnq361aMzef2DW3w7v9s9McxNI9bJMv2b15P22NZLaZkkrbHHmM7qH+6GDY/7Z1+vv89mHKkt/XpSDZn8nPudt/QHux6EanFLZKl7YknvG/MDn9lX5fh2fw03D4X/vVz8OfnYf/7sOOP8JtveI8N1wSau51NLW6RbMnk0K6nta5fz74Hf0q8sZFoQwNTL7tUS9szNj8Nj/wtJNp7X4+3QRteC3y4re6uNq+lna3v3O1fXA5v/h9wqfTjIZg8F9r3QXfr4edVTofP/GRMt2cdLrW4RbKFw0O7TmEHJkzok3BeuKd/aGfE27zW93ANNnf7F5fDn/734dAG7/v97/UObYD2vd5vBN+bUVg/+ZF5fjDnu15ECm6RLNXnned949zhr+zrOWQfmGBm3m0sxr4HfwroJBz2vzfw41OOGP57DzR3e/PTXmgPVaIL1t0++CDjFx7rH9LFm1UyIHWViGSZe9edbCfdp51MQjhM9XnnDTgwGW9sJDR5cq9r2QcmBO4knGKbcuTAreqhnM2Ya3Bz6fX9524DPPI3I6v7vfVey3ugQc4xCOlcNI9bZITeW7acRHMzLpEgvmtX/z25zQhNn05sxgwAkm2tJJr34rq6qFyyZPz3h+fr44ahtVA3P+0NZoZiEK2AeAekuvuf75jpHimWM2/yYxGPFuCIFEuuQUiAxq99HdoG2cyospJo3XQSO3fhnMNiMaKzZuG6u5l5yz+M//D+v1dCe7N330Kw+PPw3+4v/D1Wfxpa90Cs8vC17naomQnLf+3dX7cC1n0fKHKu1S2Gq39X3PccmIJbpBgyfdUWi2Hl5bjOTlx3N5M++1k+WLkSUqnB3yQc7plmGJ09m3BNDamODh1nVogffRjKa3umaALeGETnfph85NDmT4djkOwe2ud/+L8P7QfNyGjlpEgx5BuEbFmzprDQBkgmvZZ2OrSBkj5AuKRMOdLrHskW74D2lgJD26B2Psw+CWYcB7NO9N7zrx+FWM3gL//TI8OpelRocFKkQPkGIVOtrXlekVuopobkBx8Q37WLUCyGVVdTNm9eESsdp07/qtfH3c3hPu62PdB9sMA3cNDybv/L/2cZfCI9QLru9oFfv/npkpjnreAWKVC0oYFEczOWnh0CkNj3Qc+UwYLEYiT37vV+3Q+HSXV1QWcnFX/1V6NQ8ehoWrmKljVrSB06RKiqitply5hx9VXDf8NCd/RbeA7wg/Sskve9P/fuIhySED/kBXbfQxhyKXSx0OhtPgWoq0SkYFMvuxTX3U2qowPnHKmODlIt+4f0HqHqasJ10wmVlWGpFKGyMsJ10+l4+eXRKbrImlau4oNVq0i1t0MkQqq9nQ9WraJp5arhvWFmr5Hu9t57jeRbALPwHG8g8to3oOuAN8g5kNAQ2qZ9F/LkUshioTHYfErBLePOuk1NXHL/i3xyxXNccv+LrNvUVJT3rVm6lJm3/AORujpSBw4QqavDqqqwysreA2b5VFaSOnAAi8WIzZtH2cKFxObNIzJ1WmD6uFvWrAEzLBLB0reYedeHYyR7jfQcVZbnz76iDlKJ4dWVTyGLhcZg8yl1lci4sm5TE19Y/UrPZLDGlg5e3PYBP1t+CmcumjHi969ZurTXtL33li2n689/JhmPewOUqVT/rpNQiGhDA+GaGrreeYdkUzORmsOn5LjOTqINDSOubSykDh2CSJ/YCIe968NRyF4j+ZRVey30aDnEO+k1BbBuMTS/ObyaBjKUxUKjSC1uGVf+7l9e6TeD16Wvj4apl11KKBolPHUqVlYG4TBWVsa0r3yFaH09ZccdR/mxx/bMIAnX1eHi8V7dLa67u2c+eKkLVVX133ArmfSuD8dIzonMXu4eLvN+AIQi3oKZ+NAGjAtSWVcSA5Og4JZxJp5nVl6+6yOV6T4pmzePSG0tlR/9KPX//GNmXH0V0YYGXGdnr+eHolFiRx3Vq7slSItvapctA+dwiQQufYtz3vXhGMk5kWfe4C13j1VCKu7dLr3euz6SjatyKZsMn7m3sOeOweZT6ioRGaJcsypyLZ6Zetml7Ln1u6Sg14KdmTfeEJig7isze6Ros0oys0eGe07kmTfkeW4xFhaGoXIqzFg0tAMfvvDYqM8q0cpJGVfm3fh43sf+fMf5I37/XifkZB22MO2qq3KGl/bp9sltsyGeZyvZvv76Ue82M82wrCY91bC1OKf0DM+Ao91qccu40jC5jMYDXTmvj1Tr+vW0/frXhy9ktn0NhWhZsyZncPcdzJQx8olrB1lMkxatOhzKC8/pvZFVea23N8pvvgH8oGT6t0F93DLO/PZbZ/cL6YbJZfz2W2eP+L33PfhTL6j7HGuGc8OfVSGj48wbCuhTtsMrJjNeuMcL7Vh6imes0rv/wj2jVupwlGyL28zOBe4BwsADzrk7fC5JAqIYIZ1LvLHR+8ecCe8M54Y/qyLAWtevp+kH/0T31q2992oJhyk7+mjqvv41f3/b+MJj3kKe3/2of7dJtMoL7b794/vf81ravZ5bUfzBzhEqyeA2szCwEjgHaAReMbO1zrn/9LcymciiDQ0k29tJtbT0C+9hz6ooEf1OtwdCc+bwoeeezf/8X/8693L/ZJKut9+m8fIrqL7gggEPoRh1eQcv85hyZP+tY+MdIzulZxSUalfJqcBW59w251w38DBwkc81yQQ39bJLCVdVEaqt7dXyrr7ggpHt1eGzXKENkNq5k7f/4qx+15tWrvKeX8DEhrbHHmPb35bYD7V1K+COI+A7U73b7OX1p3/VO5yhuz09QNnu3S+RhTcZpRrc9cD2rPuN6Ws9zOxyM9tgZhuam5vHtDiZmDJztssXLiQ6Zw6VH/sYDff9xN8WZRG0PfFE3sdSO3f2uzbU5e1dL79cOuE92N4oC8/xTtSpment810zs/8JOyWgJLtKyD0VptePd+fc/cD94E0HHIuiZGJYt6mJ+9ZvY3tLO3NrK7li6YKe5fJjNUtk+zevp+3xx3v6jkNTpzLnju+Pzmf3XQk5iOEMxHa9/DJNK1f5/5tJ9t4oAES8RT8vrjzcpbLwnJIL6r5KtcXdCMzNut8A9P/RL1KgHz+zmRO+/RRH3fQEJ3z7KX78zOacz1u3qYlb1r5FU2snUyqiNLV2csvat4q2UVUherousgb8Uvv20fjVa0fnZPhwAduZZhnuQOywN6LKNlA3RyF6NqbKUujeKCWkVIP7FeAYM5tvZjHgYmCtzzVJQP34mc3c89xWOuJJIiHoiCe557mtOcP7vvXbiIaNypi3+11lLEI0bNy3ftuQP3f7N69n4/GL2bjoWDYev5jt37y+oNfl7bro6PCmJBZZ9Xnn5X0sNGcO2/52mff/If2VOljowQW9pQY7k3MwQ90CNpeR7I1SQkoyuJ1zCeDLwFPARuAR59xb/lYlQfXAb98lZBAJhQhZKH3rXe9re0s7FdHeLbKKaJjGFm86WaFbxva0mjPdEMkkbY89Vlh4D9B1MRrbv869606qL8ixV3R1NamdO+kq1l7hqRTvLVs+/N8aRrIFbMZI9kYp1Iqj4duTD3+tOLp4751WksEN4Jx7wjm30Dl3lHPuNr/rkeA61J0k1GfUJGTe9b7m1lbSEe99vSOepKG2ckjdKD2t5j6LdQYaCOwxQNfFaG3/OveuOzl208aer2lf+crgp9YPQ6K5mT23fnd44V2Mbo6BNqYqhhVHQ0efyRIdzXDrrOK8f1qpDk7KOPLjZzbzwG/f5VB3kqpYmC9+cj7XnL1wzD6/KhamI947vFPOu953IPK0BVN59NUdNLd20tqZoCuRIhwyLjpxTq9uFIDKWIT27gT3rd/Wf6/vfK3mAgYCq887L+f0PCoqxmz716L0R+cQqqgghbcKdcgDrZn9t7NjazjdHEOd2z0UfUM7I9XhdekU6XNLtsUt40Omf/lgZ4JkynGwM8EPn9nCh27OvxlUIS657wXm3fh4z9cl972Q97lf/OR8Ug4SqRQpl0rfwlmL6vq1oB99dQcfPWIyLe1xOhNJYmFjalWUR1/dweY9B3N2o2zZc7B/90m+VnMBA4E9XRehw/88Q1On0nDPj8ZsJeKQZ44MYYBz2Kfaj0U3x2gaSpfOILQ7oIyqE779FAc7cx8fNa0ywh9u+cshv+cl973A799t6Xf9tPm1PHTF6Tlfk6vV//tt+2hq7expQQO0dydobu2irqas3/Wd+ztwQDLliIVDTK8uoyuRpKU9TkNtBRVRr2UfTzrufueXVP5/T/erw/eVhAV6+9SPFT4IGY1y7J/e6Lm78djj8i7OKT/+eFIdHUTq6nJuhTuoQg8W9su3J+d/zMLwj/sKfSftDij+ydWPnPFB+/DOA8wV2gNdX7epid9v28ekiijHz5ncMy/7kRXPMaWi97FZFdEwh7qT1CZTbGtuozuZIhYOURkL0ZVIETIjZBBPptixvwNwvUI+033yg4/+NXdOKvf6tJNJCIepPu+8QIQ2eEv4P/jnfy7ouWULFvS6H549m2SOhTuEwyM/8Wewbg6/gz0U9frOcynizBUFt4yqqlg4b4t7LGQGFKNh6zWg+LnG/RzsiLP7QCdlkRCVsTDt3Um6EimcczS2dBAJhwiHjETKsbctTjRszJlSQXNrF93JFJGQkXQwrar3boSZWShz77qTdZd9o/dink1NRTn7crTNuPoq2l56afAZJbEYdV//Wq9Ls7/9jzR+7evQ3u7NRU8PzoYmTyZSVzd6e5JnpgtivacLwtiF98UPwb9+LscDoaJ26aiPW0bVFz8539fPzzUvO55MsnLdO1SVhTGgM56kua2bjngSw/sdNem8LhEckL4xoKY8yoK6ahbNmsTRM6oJmRVlFkopWvAva7zZJfmEwzT8j3/uF8I1S5fS8MN/ovKUU4jW11N56qk0/ORePvTC7zhyzerR66cvxnTBkVp4jncww5Qj6entiFbCmTcW9YeHWtwyqq45eyEr/2MLXTl6TKZVDu8/v9Pm1+bt487IzBZ5+c/7KAsbMyaVU1PudYscaI+TTDmmV5dTFgnz/r7DW37W11Z4XSApR8o5kg5i4RBYiESq98GVHfEkC6ZXcag7SXt3olcf9xVLFwxtFkqJmnH1VVR8eDG7brqZVFsbLpHAIhFC1dXMvv22vCHsywESIzkxvpgWngML3xj8eSOgFreMurdvO79fSA93YBLgoStO7xXS0HtgMrulWx4JEU85du7vpLXT63vsSqYoi3j/6deURwmHjLKIEQ4ZNeVRYukuknDIWDRrEgvqqqmtjBIJhWjv9g7Jbe9OsLeti61Nrby/r513mg/x5s6DvNN8iObWTt5o3J9zMU8imeLV91sGXcCTy/ZvXs/GY4/rWcG4+ROfHJ0l8H3ULF3K7Ntvo+LEE4nOnEnFiScOGNq+GSerIguhWSUSeH3nYu9v76Y7maIyFuFgR5ydBzoAiIaM2VMqaGzpoLYySl1NOUCvQcgFddW0dsbTfdzG0XXVPa3oz51cz2/e3M3WpjbiqcH/3UyvjjG5ItrT4j7YEWfH/g4iIePoGYff99YLjx+0BZ5v61WrrKT+R3eXXoj6IbuP28LpEHfFXWAzdgacVaLglkDLHnzMdFX8+YN2GqaUM6kiBniBubeti85EilPnTeW0BVP5ny++R2tngkTKmymSSDkmV0ToiqfoiGd1iRhEzJhcEfEW5CSH9u+lrjrGpIooFdEwW5vbSCQdDbUVPd027d0JZtSU89DlHx/wfTYevzjv4p3Kj31seFPrxiO/Z5UUj6YDyviVqx85Gjb2HOzqCe5JFVEiYesJyHWbmuiMb6M76S3EyewY3JJreqKDuHPsPZRnitcgytKf29jSjnNQP+VwXzv03gdlQGO8f0lgjeaqyBKiPm4JtFz9yDNryoinUr36ozMDhus2NXH5v2ygtStJAb0dI9Z8KM5Dl3+c52/4C04+opZI2Psn19oZZ1tzGxt3H+RAR3zwvm4f9i+R0qXglkDLtSlUJBzimLpqZtSUs/tgJ9s/aOf9fe0sX/0Ky1e/QvdYJHYOVyxdQDzp2NvWyY6WDrqTXjdNZSw86DTBfFuvWmXlmO1fIqVDXSVS0q57+FXWvrGbZMoRDhkXnjCLuy8+uefxK5Yu4Ja1b/WbjvcP5x8HwFceetW3oAZYMN07dCAzgNrenaClPY5LOSpiYaZXlzGpIjroNMG5d93Jduh1QG942jRmf//28T8w+bML4L2s2TNHLvVOcJ/ANDgpJeu6h1/ll6/t6nf9syfN7hXemVBsbGmnIeuosY/e+tSwl9UXgwE/W34KQK8B1I27DxIyY87kCiall9w75zjQEef5G/7Ct3pLUt/Qzhj/4a3BSQmmtW/sBnq2sga8xubaN3Zz98WHr525aEa/lup1D7/qa2gDVMTC3Ld+Gy2HunoNoJZHwnQnU+xt6+oJ7sxqS+kjV2gPdH2CUB+3lKxkni6OfNez/d8cLfXhMrzZIeG+pzEMYGpllAXTq2hq7WRLcxuJ5OEphnU1ZeDo2Rcle/BUpBBqcUvJCocsZ0gXEqAj6QCMhmDW5Ipe3S4Zl9z/Yq+tYPsuqsnM1Z5UET18ZmUoxJ7WLsDY2+ZtUGUGkZBxoCOe83NGomnlKvY98ACuowPMiMyZw6x/vGX894VPIApuKVkXnjCLX762q9/WzheeMLJjoEIG1551DNecvZBz717Hpj29Dw2Ip6AqFupZFNN3/+/KaIijZtQAsLeti5BB0jnMMj9oHO/vayccMmLhEJPKI+w91M2O/R2EzGvBpxxMLovw3YsW9wR2MU4Kalq5ig9Wrjx8QrxzJHbsYMfXv0H9P/0geOF95NL8fdwTmLpKpGTdffHJfPak2T0t7HDI+g1MDkc0HOKEhikA/UI7I3M916EN7fEU7zS1AtCd7gKJpednh81IpLxgzmwJu689TjQcIhIyXPrzG2q9gcnM6fFDOYl+IC1r1vTaSjUzQOAOHRqVE+JH3Rce6x/S439gclBqcUtJu/vik3sNRBYqZORdYJNIpQreoS/f4Qztca9/2oDupCPlvIMXkumWrkHPlrAAyVSKRbMmYVkjrd6+396qyeyT6DP1J1IpHvjtu0Nqdec9ciyVCu4Kywke0rmoxS3j0odm1uS87g00hmhsaee6h18d0WfsPtBByjnCRs+pOPGU9xmxSIikc0TCRv2UcsKhUN59u2FoJ9EPJFRVleeBkFZYjiMKbhmXbjh3EZWx/svEQwaTK6M01Fb2TDfMZdHMPAGY5ZiZkzhyWhUNtZVEwyFc+v0jIZg1qZxYOER3MsWe1i7qqqLEky7nMnzwTgrq+xtC5iT6oahdtsw7ZNi5w1+AVVVpheU4ouCWwLnu4Vc56qYnmHfj4xx10xN5W86VsTCRPs3YSRURouEwVyxdMOC0wrf3HGLBt/KfRF9TFmZ7SzuJ9HzszLaw06qiJFKwY38H8WQKAxJJR1d6W9gZNeUc6Igzo6a813au+U6iH+oJQjOuvoppV1+NVVR4F8yI1NcHc2BS8tLKSSm6vvtjF3OqW6GrKbOn7bV2xmlu7aIzkaQqFuHHF3+EMxfN4KibniCZ8vqph/qvYPXyU7jjNxvZ2nyIsBlmXuM26byl+d7xZ95p8HU1ZYRDNuj2rcWYVSLjhvbjlrGTvT/2O829B8oiBlu/f/6I3r8nbPuspgyHjHduP7wR0yfTJ7hnDwYe7Ohm98Eu6mrKmFtbCS6Vd/BxICGDbd8/n0/9aD1bmtq8oM4Ed/oHwYdm1fQbiNSSdhmCAYNbXSVSVJn9sfuGNkDCwdEDdD8UotDVlH13DfQWynRi0HNw744DXf2OQCtE5qNauxLUTyn3TntPOSIhbyAyFMp/gLBIMWg6oBTVlqZW2rvy7xGSGOEveIWupuy7a+Ce1k4AZk0u71nR2N6dAAtx2oJp/PH9FrqSqZ4T3QcSMq8rprm1C0u/Z/aJNvOnVdIeT+U8QDij7/zw7DMzRQajFrcUzbpNTbR2Jgo6j3G4Mqsm+0ya6Lea8sxFM7j1wuN7BgMHOn3miqULqCmPEKKwvu6ysNHU2smsSWUkUo7Glg4OdnT3zBS58VPH9vrsvgORuRb1/P7dFi6574Vh/7nIxKIWtxTNfeu3UVsZ5YND3aP2Gd4A5MB7dGdk7xqYGazMlum+OHPRDO763ImseHITW5vaSDiv2W19FvGEQ8aU8ghTqmI9e5WAsae1k90Huzj5iNpeA7H5BmTz9asPp79dJiYFtxTN9pZ2pleXURYJ896+3OcoRgrfYC+v4aymzHfgQqb7ItfWsLl8csVzvY5Km1QRpaY8woGO+KAH/ooUi7pKpGgyA4KTKqJ8uH5yv8eLMatkuPp2nfTtvihUrqPSNPAoY00tbimavq3ao+qqiCfdsAKyWPru/rdoZtWIpuQN1nIvxGnza3N2iwxnhotMTGpxS9EUq1VbLLm2bN205xDn3r1u2O9ZjP+PD11xer+Q1qwSGQotwJFxa96N+eeM//kOf7psRAqkBTgiIuOJ+rhFxqlcp9wPNH1SgkMtbhm38m3NWsiWrUGXK7TB2xrgl6/tGvFe5OIvtbhl3HryujNzzip58rozi/YZi2/5DW3dh09wr46FePPWTxXt/YcrV2hnW/vG7mGdLCSlQcEt41oxQ7qvvqEN0Nad4kM3P87bt5X24OdAe5FL6VNXicgw9Q3tjK6kt29LKeu7KZcEi4JbZBRkTm/3y7TKgX+Z7rsplwSLgltkFGROb/fLH275y5zhHQ5Zv9OCJHjUxy0yTNWxUN7uklLYu+QPt/yl3yXIKFGLW2SY3rz1U5TlOIT9iKmVQ9q7RGSofAluM7vLzDaZ2Rtm9kszm5L12LfMbKuZvW1majJISXv7tvNZvfwUTlswjbm1FZy2YJqv+7PIxODLXiVm9l+A55xzCTNbAeCcu8HMjgMeAk4F5gDPAAudc8n876a9SkRk3Cm9vUqcc//unMusEHgRaEh/fxHwsHOuyzn3LrAVL8RFRCStFPq4LwV+k/6+Htie9Vhj+lo/Zna5mW0wsw3Nzc2jXKKISOkYtVklZvYMkGuy6M3OuV+ln3MzkAB+nnlZjufn7Mtxzt0P3A9eV8mIC5Zxa92mJu5bv43tLe3Mra3sdS6kSBCNWnA7584e6HEzWwZ8GjjLHe5obwTmZj2tAdg5OhXKRLBuUxO3rH2LaNiYUhGlqbWTW9a+xa3kP8xXpNT5NavkXOAG4ELnXPZKhbXAxWZWZmbzgWOAl/2oUcaHFU9uoulgJ+/va+fdvYdIphzRsPm+slFkJPxagPM/gDLgaTMDeNE59yXn3Ftm9gjwn3hdKFcPNqNEJJ91m5rY3NRG2LwVg4mUY+f+TmZPLvN9ZaPISPgS3M65owd47DbgtjEsR8ap+9ZvI2wQTzpIOiwd4HsOdvGRI3QwrwSXlrzLuLWlqZVE0vWMbjsHqaQjaUM7lV2k1JTCdECRUdGdSOWcp1QWCWlgUgJNwS3jVlciQa7zApzLvTGUSFAouGVcuuS+F+jKc3pXZwJ+/MzmsS1IpIgU3DLuXPfwq/z+3ZYBn/PDZ7aU/Ck1IvkouGXc+dXruwp6nuZyS1ApuGXcKfQcXM3llqBScMuEVQqn1IgMh4Jbxp3BDsrN0FxuCSoFt4w7//RXHxn0P+yvnX2M5nJLYCm4Zdw5c9EMfrr8FBqmlPd7rGFKOauXn8I1Zy/0oTKR4vDl6LJi09FlIjLOlN7RZSIiMnwKbhGRgFFwi4gEjIJbRCRgFNwiIgGj4BYRCRgFt4hIwCi4RUQCRsEtIhIwCm4RkYAZF0vezawZeK/Ibzsd2Fvk9yymUq8PSr/GUq8PSr/GUq8PSr/GXPXtdc6dm+8F4yK4R4OZbXDOLfG7jnxKvT4o/RpLvT4o/RpLvT4o/RqHU5+6SkREAkbBLSISMAru/O73u4BBlHp9UPo1lnp9UPo1lnp9UPo1Drk+9XGLiASMWtwiIgGj4BYRCRgFdw5m9g0zc2Y2Pevat8xsq5m9bWZ/6WNt3zWzN8zsNTP7dzObU0o1mtldZrYpXeMvzWxKKdWXruPzZvaWmaXMbEmfx0qlxnPTNWw1sxv9qiObmf3UzJrM7M2sa1PN7Gkz25K+rfWxvrlm9h9mtjH99/vVEqyx3MxeNrPX0zV+Z1g1Ouf0lfUFzAWewlvQMz197TjgdaAMmA+8A4R9qm9S1vfXAD8ppRqB/wJE0t+vAFaUUn3pWo4FPgSsA5ZkXS+JGoFw+rMXALF0Tcf58WfVp66lwMnAm1nX7gRuTH9/Y+bv26f6ZgMnp7+vATan/05LqUYDqtPfR4GXgI8PtUa1uPu7G7geyB61vQh42DnX5Zx7F9gKnOpHcc65g1l3qzhcZ0nU6Jz7d+dcIn33RaChlOpL17jROfd2jodKpcZTga3OuW3OuW7g4XRtvnLOrQf29bl8EbAm/f0a4DNjWVM259wu59yr6e9bgY1APaVVo3POtaXvRtNfjiHWqODOYmYXAjucc6/3eage2J51vzF9zRdmdpuZbQf+H+CW9OWSqjHtUuA36e9Lsb6+SqXGUqmjEDOdc7vAC05ghs/1AGBm84CP4LVoS6pGMwub2WtAE/C0c27INUZGvcoSY2bPALNyPHQzcBPer/r9Xpbj2qjNoxyoRufcr5xzNwM3m9m3gC8D/ziWNQ5WX/o5NwMJ4OeZl41VfenPH7TGXC/Lcc2P+bKlUkcgmVk18AvgWufcQbNcf5z+cc4lgZPS4z+/NLPFQ32PCRfczrmzc103sw/j9Wu+nv6LbgBeNbNT8Vo8c7Oe3gDsHOsac/hX4HG84B6zGgerz8yWAZ8GznLpTruxrA+G9GeYbUxrDEAdhdhjZrOdc7vMbDZeK9I3ZhbFC+2fO+f+LX25pGrMcM7tN7N1wLkMsUZ1laQ55/7knJvhnJvnnJuH94/nZOfcbmAtcLGZlZnZfOAY4GU/6jSzY7LuXghsSn9fEjWa2bnADcCFzrn2rIdKor5BlEqNrwDHmNl8M4sBF6drK0VrgWXp75cB+X6bGXXmtbgeBDY6536Y9VAp1ViXmWllZhXA2Xj/hodWo1+jq6X+BfyZ9KyS9P2b8Ub63wY+5WNdvwDeBN4AHgPqS6lGvAG97cBr6a+flFJ96To+i/eDuQvYAzxVgjWehzcr4h287h1f6uhT00PALiCe/vO7DJgGPAtsSd9O9bG+T+J1Kb2R9d/feSVW4wnAH9M1vgnckr4+pBq15F1EJGDUVSIiEjAKbhGRgFFwi4gEjIJbRCRgFNwiIgGj4BYRCRgFt4hIwCi4RQZhZqek9xcvN7Oq9D7KQ95fQqRYtABHpABm9j2gHKgAGp1z3/e5JJnAFNwiBUjvGfIK0Amc7rwd3kR8oa4SkcJMBarxTlYp97kWmeDU4hYpgJmtxTuJZj4w2zn3ZZ9Lkglswu3HLTJUZva3QMI5969mFgZeMLO/cM4953dtMjGpxS0iEjDq4xYRCRgFt4hIwCi4RUQCRsEtIhIwCm4RkYBRcIuIBIyCW0QkYP5/PgEs0RDeis4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('x', 'y', data=crypto_mined2, hue=\"Class\", fit_reg=False, legend=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d745a36",
   "metadata": {},
   "source": [
    "### Recommendation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69d1a7a7",
   "metadata": {},
   "source": [
    "Based on the visualization and analysis above, this cryptocurrencies dataset can be clustered into 4 distinct groups. I would recommand my clients at the investment bank that the cryptocurrencies can be grouped and created a classification system in order to develop a new investment portfolio for their customers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a491032",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.8 64-bit ('base': conda)",
   "language": "python",
   "name": "python388jvsc74a57bd0208876dcf9cc343f9e531c1c515db77d60ee24d4da368526df9d5cfa732951b1"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}