sonar rock vs mine prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "61c73d8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "24ad0636",
   "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>Freq_1</th>\n",
       "      <th>Freq_2</th>\n",
       "      <th>Freq_3</th>\n",
       "      <th>Freq_4</th>\n",
       "      <th>Freq_5</th>\n",
       "      <th>Freq_6</th>\n",
       "      <th>Freq_7</th>\n",
       "      <th>Freq_8</th>\n",
       "      <th>Freq_9</th>\n",
       "      <th>Freq_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Freq_52</th>\n",
       "      <th>Freq_53</th>\n",
       "      <th>Freq_54</th>\n",
       "      <th>Freq_55</th>\n",
       "      <th>Freq_56</th>\n",
       "      <th>Freq_57</th>\n",
       "      <th>Freq_58</th>\n",
       "      <th>Freq_59</th>\n",
       "      <th>Freq_60</th>\n",
       "      <th>Label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.0428</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0954</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.1601</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>0.2111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0453</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>0.0843</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>0.1183</td>\n",
       "      <td>0.2583</td>\n",
       "      <td>0.2156</td>\n",
       "      <td>0.3481</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>0.2872</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0582</td>\n",
       "      <td>0.1099</td>\n",
       "      <td>0.1083</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>0.2431</td>\n",
       "      <td>0.3771</td>\n",
       "      <td>0.5598</td>\n",
       "      <td>0.6194</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0232</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>0.0316</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>0.0623</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.1098</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>0.0598</td>\n",
       "      <td>0.1264</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0762</td>\n",
       "      <td>0.0666</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0590</td>\n",
       "      <td>0.0649</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.2467</td>\n",
       "      <td>0.3564</td>\n",
       "      <td>0.4459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
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      "text/plain": [
       "   Freq_1  Freq_2  Freq_3  Freq_4  Freq_5  Freq_6  Freq_7  Freq_8  Freq_9  \\\n",
       "0  0.0200  0.0371  0.0428  0.0207  0.0954  0.0986  0.1539  0.1601  0.3109   \n",
       "1  0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
       "2  0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
       "3  0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
       "4  0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
       "\n",
       "   Freq_10  ...  Freq_52  Freq_53  Freq_54  Freq_55  Freq_56  Freq_57  \\\n",
       "0   0.2111  ...   0.0027   0.0065   0.0159   0.0072   0.0167   0.0180   \n",
       "1   0.2872  ...   0.0084   0.0089   0.0048   0.0094   0.0191   0.0140   \n",
       "2   0.6194  ...   0.0232   0.0166   0.0095   0.0180   0.0244   0.0316   \n",
       "3   0.1264  ...   0.0121   0.0036   0.0150   0.0085   0.0073   0.0050   \n",
       "4   0.4459  ...   0.0031   0.0054   0.0105   0.0110   0.0015   0.0072   \n",
       "\n",
       "   Freq_58  Freq_59  Freq_60  Label  \n",
       "0   0.0084   0.0090   0.0032      R  \n",
       "1   0.0049   0.0052   0.0044      R  \n",
       "2   0.0164   0.0095   0.0078      R  \n",
       "3   0.0044   0.0040   0.0117      R  \n",
       "4   0.0048   0.0107   0.0094      R  \n",
       "\n",
       "[5 rows x 61 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('sonar.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "69f44b64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(208, 61)"
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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "data.shape"
   ]
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  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6681c935",
   "metadata": {},
   "outputs": [
    {
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 208 entries, 0 to 207\n",
      "Data columns (total 61 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   Freq_1   208 non-null    float64\n",
      " 1   Freq_2   208 non-null    float64\n",
      " 2   Freq_3   208 non-null    float64\n",
      " 3   Freq_4   208 non-null    float64\n",
      " 4   Freq_5   208 non-null    float64\n",
      " 5   Freq_6   208 non-null    float64\n",
      " 6   Freq_7   208 non-null    float64\n",
      " 7   Freq_8   208 non-null    float64\n",
      " 8   Freq_9   208 non-null    float64\n",
      " 9   Freq_10  208 non-null    float64\n",
      " 10  Freq_11  208 non-null    float64\n",
      " 11  Freq_12  208 non-null    float64\n",
      " 12  Freq_13  208 non-null    float64\n",
      " 13  Freq_14  208 non-null    float64\n",
      " 14  Freq_15  208 non-null    float64\n",
      " 15  Freq_16  208 non-null    float64\n",
      " 16  Freq_17  208 non-null    float64\n",
      " 17  Freq_18  208 non-null    float64\n",
      " 18  Freq_19  208 non-null    float64\n",
      " 19  Freq_20  208 non-null    float64\n",
      " 20  Freq_21  208 non-null    float64\n",
      " 21  Freq_22  208 non-null    float64\n",
      " 22  Freq_23  208 non-null    float64\n",
      " 23  Freq_24  208 non-null    float64\n",
      " 24  Freq_25  208 non-null    float64\n",
      " 25  Freq_26  208 non-null    float64\n",
      " 26  Freq_27  208 non-null    float64\n",
      " 27  Freq_28  208 non-null    float64\n",
      " 28  Freq_29  208 non-null    float64\n",
      " 29  Freq_30  208 non-null    float64\n",
      " 30  Freq_31  208 non-null    float64\n",
      " 31  Freq_32  208 non-null    float64\n",
      " 32  Freq_33  208 non-null    float64\n",
      " 33  Freq_34  208 non-null    float64\n",
      " 34  Freq_35  208 non-null    float64\n",
      " 35  Freq_36  208 non-null    float64\n",
      " 36  Freq_37  208 non-null    float64\n",
      " 37  Freq_38  208 non-null    float64\n",
      " 38  Freq_39  208 non-null    float64\n",
      " 39  Freq_40  208 non-null    float64\n",
      " 40  Freq_41  208 non-null    float64\n",
      " 41  Freq_42  208 non-null    float64\n",
      " 42  Freq_43  208 non-null    float64\n",
      " 43  Freq_44  208 non-null    float64\n",
      " 44  Freq_45  208 non-null    float64\n",
      " 45  Freq_46  208 non-null    float64\n",
      " 46  Freq_47  208 non-null    float64\n",
      " 47  Freq_48  208 non-null    float64\n",
      " 48  Freq_49  208 non-null    float64\n",
      " 49  Freq_50  208 non-null    float64\n",
      " 50  Freq_51  208 non-null    float64\n",
      " 51  Freq_52  208 non-null    float64\n",
      " 52  Freq_53  208 non-null    float64\n",
      " 53  Freq_54  208 non-null    float64\n",
      " 54  Freq_55  208 non-null    float64\n",
      " 55  Freq_56  208 non-null    float64\n",
      " 56  Freq_57  208 non-null    float64\n",
      " 57  Freq_58  208 non-null    float64\n",
      " 58  Freq_59  208 non-null    float64\n",
      " 59  Freq_60  208 non-null    float64\n",
      " 60  Label    208 non-null    object \n",
      "dtypes: float64(60), object(1)\n",
      "memory usage: 99.2+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "baf3e4b7",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Freq_1</th>\n",
       "      <th>Freq_2</th>\n",
       "      <th>Freq_3</th>\n",
       "      <th>Freq_4</th>\n",
       "      <th>Freq_5</th>\n",
       "      <th>Freq_6</th>\n",
       "      <th>Freq_7</th>\n",
       "      <th>Freq_8</th>\n",
       "      <th>Freq_9</th>\n",
       "      <th>Freq_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Freq_51</th>\n",
       "      <th>Freq_52</th>\n",
       "      <th>Freq_53</th>\n",
       "      <th>Freq_54</th>\n",
       "      <th>Freq_55</th>\n",
       "      <th>Freq_56</th>\n",
       "      <th>Freq_57</th>\n",
       "      <th>Freq_58</th>\n",
       "      <th>Freq_59</th>\n",
       "      <th>Freq_60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
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       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.029164</td>\n",
       "      <td>0.038437</td>\n",
       "      <td>0.043832</td>\n",
       "      <td>0.053892</td>\n",
       "      <td>0.075202</td>\n",
       "      <td>0.104570</td>\n",
       "      <td>0.121747</td>\n",
       "      <td>0.134799</td>\n",
       "      <td>0.178003</td>\n",
       "      <td>0.208259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016069</td>\n",
       "      <td>0.013420</td>\n",
       "      <td>0.010709</td>\n",
       "      <td>0.010941</td>\n",
       "      <td>0.009290</td>\n",
       "      <td>0.008222</td>\n",
       "      <td>0.007820</td>\n",
       "      <td>0.007949</td>\n",
       "      <td>0.007941</td>\n",
       "      <td>0.006507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.022991</td>\n",
       "      <td>0.032960</td>\n",
       "      <td>0.038428</td>\n",
       "      <td>0.046528</td>\n",
       "      <td>0.055552</td>\n",
       "      <td>0.059105</td>\n",
       "      <td>0.061788</td>\n",
       "      <td>0.085152</td>\n",
       "      <td>0.118387</td>\n",
       "      <td>0.134416</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>0.009634</td>\n",
       "      <td>0.007060</td>\n",
       "      <td>0.007301</td>\n",
       "      <td>0.007088</td>\n",
       "      <td>0.005736</td>\n",
       "      <td>0.005785</td>\n",
       "      <td>0.006470</td>\n",
       "      <td>0.006181</td>\n",
       "      <td>0.005031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>0.005800</td>\n",
       "      <td>0.006700</td>\n",
       "      <td>0.010200</td>\n",
       "      <td>0.003300</td>\n",
       "      <td>0.005500</td>\n",
       "      <td>0.007500</td>\n",
       "      <td>0.011300</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>0.000500</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>0.000100</td>\n",
       "      <td>0.000600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.013350</td>\n",
       "      <td>0.016450</td>\n",
       "      <td>0.018950</td>\n",
       "      <td>0.024375</td>\n",
       "      <td>0.038050</td>\n",
       "      <td>0.067025</td>\n",
       "      <td>0.080900</td>\n",
       "      <td>0.080425</td>\n",
       "      <td>0.097025</td>\n",
       "      <td>0.111275</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008425</td>\n",
       "      <td>0.007275</td>\n",
       "      <td>0.005075</td>\n",
       "      <td>0.005375</td>\n",
       "      <td>0.004150</td>\n",
       "      <td>0.004400</td>\n",
       "      <td>0.003700</td>\n",
       "      <td>0.003600</td>\n",
       "      <td>0.003675</td>\n",
       "      <td>0.003100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.022800</td>\n",
       "      <td>0.030800</td>\n",
       "      <td>0.034300</td>\n",
       "      <td>0.044050</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>0.092150</td>\n",
       "      <td>0.106950</td>\n",
       "      <td>0.112100</td>\n",
       "      <td>0.152250</td>\n",
       "      <td>0.182400</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013900</td>\n",
       "      <td>0.011400</td>\n",
       "      <td>0.009550</td>\n",
       "      <td>0.009300</td>\n",
       "      <td>0.007500</td>\n",
       "      <td>0.006850</td>\n",
       "      <td>0.005950</td>\n",
       "      <td>0.005800</td>\n",
       "      <td>0.006400</td>\n",
       "      <td>0.005300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.035550</td>\n",
       "      <td>0.047950</td>\n",
       "      <td>0.057950</td>\n",
       "      <td>0.064500</td>\n",
       "      <td>0.100275</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.154000</td>\n",
       "      <td>0.169600</td>\n",
       "      <td>0.233425</td>\n",
       "      <td>0.268700</td>\n",
       "      <td>...</td>\n",
       "      <td>0.020825</td>\n",
       "      <td>0.016725</td>\n",
       "      <td>0.014900</td>\n",
       "      <td>0.014500</td>\n",
       "      <td>0.012100</td>\n",
       "      <td>0.010575</td>\n",
       "      <td>0.010425</td>\n",
       "      <td>0.010350</td>\n",
       "      <td>0.010325</td>\n",
       "      <td>0.008525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.137100</td>\n",
       "      <td>0.233900</td>\n",
       "      <td>0.305900</td>\n",
       "      <td>0.426400</td>\n",
       "      <td>0.401000</td>\n",
       "      <td>0.382300</td>\n",
       "      <td>0.372900</td>\n",
       "      <td>0.459000</td>\n",
       "      <td>0.682800</td>\n",
       "      <td>0.710600</td>\n",
       "      <td>...</td>\n",
       "      <td>0.100400</td>\n",
       "      <td>0.070900</td>\n",
       "      <td>0.039000</td>\n",
       "      <td>0.035200</td>\n",
       "      <td>0.044700</td>\n",
       "      <td>0.039400</td>\n",
       "      <td>0.035500</td>\n",
       "      <td>0.044000</td>\n",
       "      <td>0.036400</td>\n",
       "      <td>0.043900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Freq_1      Freq_2      Freq_3      Freq_4      Freq_5      Freq_6  \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
       "mean     0.029164    0.038437    0.043832    0.053892    0.075202    0.104570   \n",
       "std      0.022991    0.032960    0.038428    0.046528    0.055552    0.059105   \n",
       "min      0.001500    0.000600    0.001500    0.005800    0.006700    0.010200   \n",
       "25%      0.013350    0.016450    0.018950    0.024375    0.038050    0.067025   \n",
       "50%      0.022800    0.030800    0.034300    0.044050    0.062500    0.092150   \n",
       "75%      0.035550    0.047950    0.057950    0.064500    0.100275    0.134125   \n",
       "max      0.137100    0.233900    0.305900    0.426400    0.401000    0.382300   \n",
       "\n",
       "           Freq_7      Freq_8      Freq_9     Freq_10  ...     Freq_51  \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  ...  208.000000   \n",
       "mean     0.121747    0.134799    0.178003    0.208259  ...    0.016069   \n",
       "std      0.061788    0.085152    0.118387    0.134416  ...    0.012008   \n",
       "min      0.003300    0.005500    0.007500    0.011300  ...    0.000000   \n",
       "25%      0.080900    0.080425    0.097025    0.111275  ...    0.008425   \n",
       "50%      0.106950    0.112100    0.152250    0.182400  ...    0.013900   \n",
       "75%      0.154000    0.169600    0.233425    0.268700  ...    0.020825   \n",
       "max      0.372900    0.459000    0.682800    0.710600  ...    0.100400   \n",
       "\n",
       "          Freq_52     Freq_53     Freq_54     Freq_55     Freq_56     Freq_57  \\\n",
       "count  208.000000  208.000000  208.000000  208.000000  208.000000  208.000000   \n",
       "mean     0.013420    0.010709    0.010941    0.009290    0.008222    0.007820   \n",
       "std      0.009634    0.007060    0.007301    0.007088    0.005736    0.005785   \n",
       "min      0.000800    0.000500    0.001000    0.000600    0.000400    0.000300   \n",
       "25%      0.007275    0.005075    0.005375    0.004150    0.004400    0.003700   \n",
       "50%      0.011400    0.009550    0.009300    0.007500    0.006850    0.005950   \n",
       "75%      0.016725    0.014900    0.014500    0.012100    0.010575    0.010425   \n",
       "max      0.070900    0.039000    0.035200    0.044700    0.039400    0.035500   \n",
       "\n",
       "          Freq_58     Freq_59     Freq_60  \n",
       "count  208.000000  208.000000  208.000000  \n",
       "mean     0.007949    0.007941    0.006507  \n",
       "std      0.006470    0.006181    0.005031  \n",
       "min      0.000300    0.000100    0.000600  \n",
       "25%      0.003600    0.003675    0.003100  \n",
       "50%      0.005800    0.006400    0.005300  \n",
       "75%      0.010350    0.010325    0.008525  \n",
       "max      0.044000    0.036400    0.043900  \n",
       "\n",
       "[8 rows x 60 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5a3a61c0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "M    111\n",
       "R     97\n",
       "Name: Label, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b819f1ef",
   "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>Freq_1</th>\n",
       "      <th>Freq_2</th>\n",
       "      <th>Freq_3</th>\n",
       "      <th>Freq_4</th>\n",
       "      <th>Freq_5</th>\n",
       "      <th>Freq_6</th>\n",
       "      <th>Freq_7</th>\n",
       "      <th>Freq_8</th>\n",
       "      <th>Freq_9</th>\n",
       "      <th>Freq_10</th>\n",
       "      <th>...</th>\n",
       "      <th>Freq_51</th>\n",
       "      <th>Freq_52</th>\n",
       "      <th>Freq_53</th>\n",
       "      <th>Freq_54</th>\n",
       "      <th>Freq_55</th>\n",
       "      <th>Freq_56</th>\n",
       "      <th>Freq_57</th>\n",
       "      <th>Freq_58</th>\n",
       "      <th>Freq_59</th>\n",
       "      <th>Freq_60</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Label</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>0.034989</td>\n",
       "      <td>0.045544</td>\n",
       "      <td>0.050720</td>\n",
       "      <td>0.064768</td>\n",
       "      <td>0.086715</td>\n",
       "      <td>0.111864</td>\n",
       "      <td>0.128359</td>\n",
       "      <td>0.149832</td>\n",
       "      <td>0.213492</td>\n",
       "      <td>0.251022</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019352</td>\n",
       "      <td>0.016014</td>\n",
       "      <td>0.011643</td>\n",
       "      <td>0.012185</td>\n",
       "      <td>0.009923</td>\n",
       "      <td>0.008914</td>\n",
       "      <td>0.007825</td>\n",
       "      <td>0.009060</td>\n",
       "      <td>0.008695</td>\n",
       "      <td>0.006930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <td>0.022498</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>0.035951</td>\n",
       "      <td>0.041447</td>\n",
       "      <td>0.062028</td>\n",
       "      <td>0.096224</td>\n",
       "      <td>0.114180</td>\n",
       "      <td>0.117596</td>\n",
       "      <td>0.137392</td>\n",
       "      <td>0.159325</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012311</td>\n",
       "      <td>0.010453</td>\n",
       "      <td>0.009640</td>\n",
       "      <td>0.009518</td>\n",
       "      <td>0.008567</td>\n",
       "      <td>0.007430</td>\n",
       "      <td>0.007814</td>\n",
       "      <td>0.006677</td>\n",
       "      <td>0.007078</td>\n",
       "      <td>0.006024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Freq_1    Freq_2    Freq_3    Freq_4    Freq_5    Freq_6    Freq_7  \\\n",
       "Label                                                                         \n",
       "M      0.034989  0.045544  0.050720  0.064768  0.086715  0.111864  0.128359   \n",
       "R      0.022498  0.030303  0.035951  0.041447  0.062028  0.096224  0.114180   \n",
       "\n",
       "         Freq_8    Freq_9   Freq_10  ...   Freq_51   Freq_52   Freq_53  \\\n",
       "Label                                ...                                 \n",
       "M      0.149832  0.213492  0.251022  ...  0.019352  0.016014  0.011643   \n",
       "R      0.117596  0.137392  0.159325  ...  0.012311  0.010453  0.009640   \n",
       "\n",
       "        Freq_54   Freq_55   Freq_56   Freq_57   Freq_58   Freq_59   Freq_60  \n",
       "Label                                                                        \n",
       "M      0.012185  0.009923  0.008914  0.007825  0.009060  0.008695  0.006930  \n",
       "R      0.009518  0.008567  0.007430  0.007814  0.006677  0.007078  0.006024  \n",
       "\n",
       "[2 rows x 60 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Label').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6efca76e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Freq_1  Freq_2  Freq_3  Freq_4  Freq_5  Freq_6  Freq_7  Freq_8  Freq_9  \\\n",
      "0    0.0200  0.0371  0.0428  0.0207  0.0954  0.0986  0.1539  0.1601  0.3109   \n",
      "1    0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
      "2    0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
      "3    0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
      "4    0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
      "..      ...     ...     ...     ...     ...     ...     ...     ...     ...   \n",
      "203  0.0187  0.0346  0.0168  0.0177  0.0393  0.1630  0.2028  0.1694  0.2328   \n",
      "204  0.0323  0.0101  0.0298  0.0564  0.0760  0.0958  0.0990  0.1018  0.1030   \n",
      "205  0.0522  0.0437  0.0180  0.0292  0.0351  0.1171  0.1257  0.1178  0.1258   \n",
      "206  0.0303  0.0353  0.0490  0.0608  0.0167  0.1354  0.1465  0.1123  0.1945   \n",
      "207  0.0260  0.0363  0.0136  0.0272  0.0214  0.0338  0.0655  0.1400  0.1843   \n",
      "\n",
      "     Freq_10  ...  Freq_51  Freq_52  Freq_53  Freq_54  Freq_55  Freq_56  \\\n",
      "0     0.2111  ...   0.0232   0.0027   0.0065   0.0159   0.0072   0.0167   \n",
      "1     0.2872  ...   0.0125   0.0084   0.0089   0.0048   0.0094   0.0191   \n",
      "2     0.6194  ...   0.0033   0.0232   0.0166   0.0095   0.0180   0.0244   \n",
      "3     0.1264  ...   0.0241   0.0121   0.0036   0.0150   0.0085   0.0073   \n",
      "4     0.4459  ...   0.0156   0.0031   0.0054   0.0105   0.0110   0.0015   \n",
      "..       ...  ...      ...      ...      ...      ...      ...      ...   \n",
      "203   0.2684  ...   0.0203   0.0116   0.0098   0.0199   0.0033   0.0101   \n",
      "204   0.2154  ...   0.0051   0.0061   0.0093   0.0135   0.0063   0.0063   \n",
      "205   0.2529  ...   0.0155   0.0160   0.0029   0.0051   0.0062   0.0089   \n",
      "206   0.2354  ...   0.0042   0.0086   0.0046   0.0126   0.0036   0.0035   \n",
      "207   0.2354  ...   0.0181   0.0146   0.0129   0.0047   0.0039   0.0061   \n",
      "\n",
      "     Freq_57  Freq_58  Freq_59  Freq_60  \n",
      "0     0.0180   0.0084   0.0090   0.0032  \n",
      "1     0.0140   0.0049   0.0052   0.0044  \n",
      "2     0.0316   0.0164   0.0095   0.0078  \n",
      "3     0.0050   0.0044   0.0040   0.0117  \n",
      "4     0.0072   0.0048   0.0107   0.0094  \n",
      "..       ...      ...      ...      ...  \n",
      "203   0.0065   0.0115   0.0193   0.0157  \n",
      "204   0.0034   0.0032   0.0062   0.0067  \n",
      "205   0.0140   0.0138   0.0077   0.0031  \n",
      "206   0.0034   0.0079   0.0036   0.0048  \n",
      "207   0.0040   0.0036   0.0061   0.0115  \n",
      "\n",
      "[208 rows x 60 columns]\n",
      "0      R\n",
      "1      R\n",
      "2      R\n",
      "3      R\n",
      "4      R\n",
      "      ..\n",
      "203    M\n",
      "204    M\n",
      "205    M\n",
      "206    M\n",
      "207    M\n",
      "Name: Label, Length: 208, dtype: object\n"
     ]
    }
   ],
   "source": [
    "x = data.drop(['Label'],axis=1)\n",
    "y = data['Label']\n",
    "print(x)\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "14972b9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cdf3492c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = LogisticRegression()\n",
    "clf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "919b32df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "70e228bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8192771084337349"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_pred = clf.predict(x_train)\n",
    "accuracy_score(train_pred,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7b1cb2eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8333333333333334"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_pred = clf.predict(x_test)\n",
    "accuracy_score(test_pred,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4f31a4f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'R'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {\n",
    "    'R' : 'Rock',\n",
    "    'M' : 'Mine'\n",
    "}\n",
    "train_pred[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ea58fc90",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['R', 'M', 'M', 'R', 'R', 'M', 'M', 'M', 'R', 'R', 'M', 'M', 'M', 'M', 'M', 'M', 'R', 'M', 'M', 'M', 'M', 'M', 'R', 'R', 'R', 'M', 'R', 'R', 'R', 'R', 'R', 'R', 'M', 'R', 'M', 'R', 'M', 'M', 'M', 'M', 'R', 'M', 'M', 'M', 'M', 'R', 'M', 'M', 'M', 'M', 'R', 'R', 'R', 'R', 'M', 'M', 'M', 'R', 'R', 'R', 'R', 'M', 'R', 'R', 'M', 'R', 'R', 'R', 'R', 'R', 'M', 'R', 'R', 'R', 'M', 'R', 'M', 'M', 'R', 'M', 'R', 'R', 'M', 'M', 'R', 'M', 'R', 'M', 'M', 'R', 'R', 'M', 'M', 'R', 'R', 'R', 'M', 'M', 'R', 'R', 'R', 'M', 'R', 'M', 'R', 'R', 'R', 'R', 'R', 'M', 'R', 'M', 'M', 'M', 'M', 'R', 'M', 'R', 'R', 'R', 'M', 'M', 'M', 'M', 'M', 'M', 'R', 'R', 'M', 'M', 'R', 'R', 'R', 'M', 'M', 'M', 'M', 'M', 'M', 'R', 'M', 'M', 'M', 'R', 'M', 'M', 'R', 'R', 'R', 'M', 'R', 'M', 'M', 'R', 'R', 'R', 'M', 'R', 'M', 'M', 'R', 'R', 'M', 'M', 'M', 'M']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(166, 60)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_training = []\n",
    "for i in y_train:\n",
    "    y_training.append(i)\n",
    "print(y_training)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7e13520d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Rock Mine diff\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Rock Mine diff\n",
      "Mine Rock diff\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Rock Mine diff\n",
      "Rock Mine diff\n",
      "Mine Mine same\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(train_pred)):\n",
    "    z = train_pred[i]\n",
    "    a = \"\"\n",
    "    if(d[z] == d[y_training[i]]):\n",
    "        a = \"same\"\n",
    "    else:\n",
    "        a = \"diff\"\n",
    "    print(d[z],d[y_training[i]],a)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "1c674cbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['R', 'R', 'R', 'R', 'R', 'R', 'M', 'R', 'M', 'R', 'M', 'R', 'M', 'M', 'M', 'M', 'M', 'M', 'M', 'M', 'M', 'R', 'R', 'M', 'M', 'M', 'R', 'R', 'M', 'R', 'M', 'M', 'M', 'R', 'M', 'R', 'R', 'M', 'M', 'M', 'M', 'R']\n"
     ]
    }
   ],
   "source": [
    "y_testing = []\n",
    "for i in y_test:\n",
    "    y_testing.append(i)\n",
    "print(y_testing)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "66304262",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Rock Mine diff\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Rock diff\n",
      "Rock Rock same\n",
      "Rock Mine diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Mine same\n",
      "Rock Rock same\n",
      "Mine Rock diff\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Mine Mine same\n",
      "Rock Mine diff\n",
      "Rock Rock same\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(test_pred)):\n",
    "    z = test_pred[i]\n",
    "    a = \"\"\n",
    "    if(d[z] == d[y_testing[i]]):\n",
    "        a = \"same\"\n",
    "    else:\n",
    "        a = \"diff\"\n",
    "    print(d[z],d[y_testing[i]],a)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6b275f69",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e365ca2b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "805d10e7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80516e64",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a29ad2ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "674f2984",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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