category_05_finance/01_Company_Bankruptcy_Prediction/Clone_Powerful_Bankrupt_Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5ebea769",
   "metadata": {},
   "source": [
    "## Bankruptcy_Prediction - Clone Project : [Simple, yet, Powerful Bankrupt Prediction Model](https://www.kaggle.com/jaimebecerraguerrero/simple-yet-powerful-bankrupt-prediction-model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32c6c559",
   "metadata": {},
   "source": [
    "### Introduction\n",
    "\n",
    "The data were collected from the Taiwan Economic Journal for the years 1999 to 2009. Company bankruptcy was defined based on the business regulations of the Taiwan Stock Exchange."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a4c0d6a",
   "metadata": {},
   "source": [
    "### Purpose\n",
    "\n",
    "The dataset has lots of features (96) so is an excelent opertunity to put in practice dimensionality reduction techniques, EDA and finally a machine learning prediction model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f04b3af",
   "metadata": {},
   "source": [
    "### Table of contents\n",
    "\n",
    "1. Data Loading and Data Cleaning\n",
    "2. Model Based Feature Selection\n",
    "3. Descriptive Analysis\n",
    "4. Data Analysis\n",
    "5. Predicting bankruptcy\n",
    "6. Conclusions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "45b972ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# runtime\n",
    "import timeit\n",
    "\n",
    "# Data manipulation\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Data visualization\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# preprocessing\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.preprocessing import StandardScaler, RobustScaler, MinMaxScaler, Normalizer\n",
    "\n",
    "# Ml Model\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "\n",
    "np.warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf0b76b2",
   "metadata": {},
   "source": [
    "### 1. Data Loading and Data Cleaning\n",
    "\n",
    "In this step we are just going to see if we have any null's and see the shape of the dataset.\n",
    "Descriptive analytics wouldn't make sense since we are going to drop lot's of features in step number 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e03f984e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "(6819, 96)\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bankrupt?</th>\n",
       "      <th>ROA(C) before interest and depreciation before interest</th>\n",
       "      <th>ROA(A) before interest and % after tax</th>\n",
       "      <th>ROA(B) before interest and depreciation after tax</th>\n",
       "      <th>Operating Gross Margin</th>\n",
       "      <th>Realized Sales Gross Margin</th>\n",
       "      <th>Operating Profit Rate</th>\n",
       "      <th>Pre-tax net Interest Rate</th>\n",
       "      <th>After-tax net Interest Rate</th>\n",
       "      <th>Non-industry income and expenditure/revenue</th>\n",
       "      <th>...</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Total assets to GNP price</th>\n",
       "      <th>No-credit Interval</th>\n",
       "      <th>Gross Profit to Sales</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Liability to Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Interest Coverage Ratio (Interest expense to EBIT)</th>\n",
       "      <th>Net Income Flag</th>\n",
       "      <th>Equity to Liability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.370594</td>\n",
       "      <td>0.424389</td>\n",
       "      <td>0.405750</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.998969</td>\n",
       "      <td>0.796887</td>\n",
       "      <td>0.808809</td>\n",
       "      <td>0.302646</td>\n",
       "      <td>...</td>\n",
       "      <td>0.716845</td>\n",
       "      <td>0.009219</td>\n",
       "      <td>0.622879</td>\n",
       "      <td>0.601453</td>\n",
       "      <td>0.827890</td>\n",
       "      <td>0.290202</td>\n",
       "      <td>0.026601</td>\n",
       "      <td>0.564050</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.464291</td>\n",
       "      <td>0.538214</td>\n",
       "      <td>0.516730</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.998946</td>\n",
       "      <td>0.797380</td>\n",
       "      <td>0.809301</td>\n",
       "      <td>0.303556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795297</td>\n",
       "      <td>0.008323</td>\n",
       "      <td>0.623652</td>\n",
       "      <td>0.610237</td>\n",
       "      <td>0.839969</td>\n",
       "      <td>0.283846</td>\n",
       "      <td>0.264577</td>\n",
       "      <td>0.570175</td>\n",
       "      <td>1</td>\n",
       "      <td>0.020794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0.426071</td>\n",
       "      <td>0.499019</td>\n",
       "      <td>0.472295</td>\n",
       "      <td>0.601450</td>\n",
       "      <td>0.601364</td>\n",
       "      <td>0.998857</td>\n",
       "      <td>0.796403</td>\n",
       "      <td>0.808388</td>\n",
       "      <td>0.302035</td>\n",
       "      <td>...</td>\n",
       "      <td>0.774670</td>\n",
       "      <td>0.040003</td>\n",
       "      <td>0.623841</td>\n",
       "      <td>0.601449</td>\n",
       "      <td>0.836774</td>\n",
       "      <td>0.290189</td>\n",
       "      <td>0.026555</td>\n",
       "      <td>0.563706</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0.399844</td>\n",
       "      <td>0.451265</td>\n",
       "      <td>0.457733</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.998700</td>\n",
       "      <td>0.796967</td>\n",
       "      <td>0.808966</td>\n",
       "      <td>0.303350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.739555</td>\n",
       "      <td>0.003252</td>\n",
       "      <td>0.622929</td>\n",
       "      <td>0.583538</td>\n",
       "      <td>0.834697</td>\n",
       "      <td>0.281721</td>\n",
       "      <td>0.026697</td>\n",
       "      <td>0.564663</td>\n",
       "      <td>1</td>\n",
       "      <td>0.023982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0.465022</td>\n",
       "      <td>0.538432</td>\n",
       "      <td>0.522298</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.998973</td>\n",
       "      <td>0.797366</td>\n",
       "      <td>0.809304</td>\n",
       "      <td>0.303475</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795016</td>\n",
       "      <td>0.003878</td>\n",
       "      <td>0.623521</td>\n",
       "      <td>0.598782</td>\n",
       "      <td>0.839973</td>\n",
       "      <td>0.278514</td>\n",
       "      <td>0.024752</td>\n",
       "      <td>0.575617</td>\n",
       "      <td>1</td>\n",
       "      <td>0.035490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <th>6814</th>\n",
       "      <td>0</td>\n",
       "      <td>0.493687</td>\n",
       "      <td>0.539468</td>\n",
       "      <td>0.543230</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.604462</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797409</td>\n",
       "      <td>0.809331</td>\n",
       "      <td>0.303510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799927</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>0.623620</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.840359</td>\n",
       "      <td>0.279606</td>\n",
       "      <td>0.027064</td>\n",
       "      <td>0.566193</td>\n",
       "      <td>1</td>\n",
       "      <td>0.029890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6815</th>\n",
       "      <td>0</td>\n",
       "      <td>0.475162</td>\n",
       "      <td>0.538269</td>\n",
       "      <td>0.524172</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797414</td>\n",
       "      <td>0.809327</td>\n",
       "      <td>0.303520</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799748</td>\n",
       "      <td>0.001959</td>\n",
       "      <td>0.623931</td>\n",
       "      <td>0.598306</td>\n",
       "      <td>0.840306</td>\n",
       "      <td>0.278132</td>\n",
       "      <td>0.027009</td>\n",
       "      <td>0.566018</td>\n",
       "      <td>1</td>\n",
       "      <td>0.038284</td>\n",
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       "    <tr>\n",
       "      <th>6816</th>\n",
       "      <td>0</td>\n",
       "      <td>0.472725</td>\n",
       "      <td>0.533744</td>\n",
       "      <td>0.520638</td>\n",
       "      <td>0.610444</td>\n",
       "      <td>0.610213</td>\n",
       "      <td>0.998984</td>\n",
       "      <td>0.797401</td>\n",
       "      <td>0.809317</td>\n",
       "      <td>0.303512</td>\n",
       "      <td>...</td>\n",
       "      <td>0.797778</td>\n",
       "      <td>0.002840</td>\n",
       "      <td>0.624156</td>\n",
       "      <td>0.610441</td>\n",
       "      <td>0.840138</td>\n",
       "      <td>0.275789</td>\n",
       "      <td>0.026791</td>\n",
       "      <td>0.565158</td>\n",
       "      <td>1</td>\n",
       "      <td>0.097649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6817</th>\n",
       "      <td>0</td>\n",
       "      <td>0.506264</td>\n",
       "      <td>0.559911</td>\n",
       "      <td>0.554045</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.999074</td>\n",
       "      <td>0.797500</td>\n",
       "      <td>0.809399</td>\n",
       "      <td>0.303498</td>\n",
       "      <td>...</td>\n",
       "      <td>0.811808</td>\n",
       "      <td>0.002837</td>\n",
       "      <td>0.623957</td>\n",
       "      <td>0.607846</td>\n",
       "      <td>0.841084</td>\n",
       "      <td>0.277547</td>\n",
       "      <td>0.026822</td>\n",
       "      <td>0.565302</td>\n",
       "      <td>1</td>\n",
       "      <td>0.044009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6818</th>\n",
       "      <td>0</td>\n",
       "      <td>0.493053</td>\n",
       "      <td>0.570105</td>\n",
       "      <td>0.549548</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.998080</td>\n",
       "      <td>0.801987</td>\n",
       "      <td>0.813800</td>\n",
       "      <td>0.313415</td>\n",
       "      <td>...</td>\n",
       "      <td>0.815956</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>0.626680</td>\n",
       "      <td>0.627408</td>\n",
       "      <td>0.841019</td>\n",
       "      <td>0.275114</td>\n",
       "      <td>0.026793</td>\n",
       "      <td>0.565167</td>\n",
       "      <td>1</td>\n",
       "      <td>0.233902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6819 rows × 96 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Bankrupt?   ROA(C) before interest and depreciation before interest  \\\n",
       "0             1                                           0.370594          \n",
       "1             1                                           0.464291          \n",
       "2             1                                           0.426071          \n",
       "3             1                                           0.399844          \n",
       "4             1                                           0.465022          \n",
       "...         ...                                                ...          \n",
       "6814          0                                           0.493687          \n",
       "6815          0                                           0.475162          \n",
       "6816          0                                           0.472725          \n",
       "6817          0                                           0.506264          \n",
       "6818          0                                           0.493053          \n",
       "\n",
       "       ROA(A) before interest and % after tax  \\\n",
       "0                                    0.424389   \n",
       "1                                    0.538214   \n",
       "2                                    0.499019   \n",
       "3                                    0.451265   \n",
       "4                                    0.538432   \n",
       "...                                       ...   \n",
       "6814                                 0.539468   \n",
       "6815                                 0.538269   \n",
       "6816                                 0.533744   \n",
       "6817                                 0.559911   \n",
       "6818                                 0.570105   \n",
       "\n",
       "       ROA(B) before interest and depreciation after tax  \\\n",
       "0                                              0.405750    \n",
       "1                                              0.516730    \n",
       "2                                              0.472295    \n",
       "3                                              0.457733    \n",
       "4                                              0.522298    \n",
       "...                                                 ...    \n",
       "6814                                           0.543230    \n",
       "6815                                           0.524172    \n",
       "6816                                           0.520638    \n",
       "6817                                           0.554045    \n",
       "6818                                           0.549548    \n",
       "\n",
       "       Operating Gross Margin   Realized Sales Gross Margin  \\\n",
       "0                    0.601457                      0.601457   \n",
       "1                    0.610235                      0.610235   \n",
       "2                    0.601450                      0.601364   \n",
       "3                    0.583541                      0.583541   \n",
       "4                    0.598783                      0.598783   \n",
       "...                       ...                           ...   \n",
       "6814                 0.604455                      0.604462   \n",
       "6815                 0.598308                      0.598308   \n",
       "6816                 0.610444                      0.610213   \n",
       "6817                 0.607850                      0.607850   \n",
       "6818                 0.627409                      0.627409   \n",
       "\n",
       "       Operating Profit Rate   Pre-tax net Interest Rate  \\\n",
       "0                   0.998969                    0.796887   \n",
       "1                   0.998946                    0.797380   \n",
       "2                   0.998857                    0.796403   \n",
       "3                   0.998700                    0.796967   \n",
       "4                   0.998973                    0.797366   \n",
       "...                      ...                         ...   \n",
       "6814                0.998992                    0.797409   \n",
       "6815                0.998992                    0.797414   \n",
       "6816                0.998984                    0.797401   \n",
       "6817                0.999074                    0.797500   \n",
       "6818                0.998080                    0.801987   \n",
       "\n",
       "       After-tax net Interest Rate  \\\n",
       "0                         0.808809   \n",
       "1                         0.809301   \n",
       "2                         0.808388   \n",
       "3                         0.808966   \n",
       "4                         0.809304   \n",
       "...                            ...   \n",
       "6814                      0.809331   \n",
       "6815                      0.809327   \n",
       "6816                      0.809317   \n",
       "6817                      0.809399   \n",
       "6818                      0.813800   \n",
       "\n",
       "       Non-industry income and expenditure/revenue  ...  \\\n",
       "0                                         0.302646  ...   \n",
       "1                                         0.303556  ...   \n",
       "2                                         0.302035  ...   \n",
       "3                                         0.303350  ...   \n",
       "4                                         0.303475  ...   \n",
       "...                                            ...  ...   \n",
       "6814                                      0.303510  ...   \n",
       "6815                                      0.303520  ...   \n",
       "6816                                      0.303512  ...   \n",
       "6817                                      0.303498  ...   \n",
       "6818                                      0.313415  ...   \n",
       "\n",
       "       Net Income to Total Assets   Total assets to GNP price  \\\n",
       "0                        0.716845                    0.009219   \n",
       "1                        0.795297                    0.008323   \n",
       "2                        0.774670                    0.040003   \n",
       "3                        0.739555                    0.003252   \n",
       "4                        0.795016                    0.003878   \n",
       "...                           ...                         ...   \n",
       "6814                     0.799927                    0.000466   \n",
       "6815                     0.799748                    0.001959   \n",
       "6816                     0.797778                    0.002840   \n",
       "6817                     0.811808                    0.002837   \n",
       "6818                     0.815956                    0.000707   \n",
       "\n",
       "       No-credit Interval   Gross Profit to Sales  \\\n",
       "0                0.622879                0.601453   \n",
       "1                0.623652                0.610237   \n",
       "2                0.623841                0.601449   \n",
       "3                0.622929                0.583538   \n",
       "4                0.623521                0.598782   \n",
       "...                   ...                     ...   \n",
       "6814             0.623620                0.604455   \n",
       "6815             0.623931                0.598306   \n",
       "6816             0.624156                0.610441   \n",
       "6817             0.623957                0.607846   \n",
       "6818             0.626680                0.627408   \n",
       "\n",
       "       Net Income to Stockholder's Equity   Liability to Equity  \\\n",
       "0                                0.827890              0.290202   \n",
       "1                                0.839969              0.283846   \n",
       "2                                0.836774              0.290189   \n",
       "3                                0.834697              0.281721   \n",
       "4                                0.839973              0.278514   \n",
       "...                                   ...                   ...   \n",
       "6814                             0.840359              0.279606   \n",
       "6815                             0.840306              0.278132   \n",
       "6816                             0.840138              0.275789   \n",
       "6817                             0.841084              0.277547   \n",
       "6818                             0.841019              0.275114   \n",
       "\n",
       "       Degree of Financial Leverage (DFL)  \\\n",
       "0                                0.026601   \n",
       "1                                0.264577   \n",
       "2                                0.026555   \n",
       "3                                0.026697   \n",
       "4                                0.024752   \n",
       "...                                   ...   \n",
       "6814                             0.027064   \n",
       "6815                             0.027009   \n",
       "6816                             0.026791   \n",
       "6817                             0.026822   \n",
       "6818                             0.026793   \n",
       "\n",
       "       Interest Coverage Ratio (Interest expense to EBIT)   Net Income Flag  \\\n",
       "0                                              0.564050                   1   \n",
       "1                                              0.570175                   1   \n",
       "2                                              0.563706                   1   \n",
       "3                                              0.564663                   1   \n",
       "4                                              0.575617                   1   \n",
       "...                                                 ...                 ...   \n",
       "6814                                           0.566193                   1   \n",
       "6815                                           0.566018                   1   \n",
       "6816                                           0.565158                   1   \n",
       "6817                                           0.565302                   1   \n",
       "6818                                           0.565167                   1   \n",
       "\n",
       "       Equity to Liability  \n",
       "0                 0.016469  \n",
       "1                 0.020794  \n",
       "2                 0.016474  \n",
       "3                 0.023982  \n",
       "4                 0.035490  \n",
       "...                    ...  \n",
       "6814              0.029890  \n",
       "6815              0.038284  \n",
       "6816              0.097649  \n",
       "6817              0.044009  \n",
       "6818              0.233902  \n",
       "\n",
       "[6819 rows x 96 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank = pd.read_csv('./data/data.csv')\n",
    "\n",
    "print(bank.isnull().values.any())\n",
    "print(bank.shape)\n",
    "\n",
    "bank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fe22c286",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank.isnull().values.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1d75cfb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank.isnull().sum().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b5b957e",
   "metadata": {},
   "source": [
    "great! let's start dropping features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0cfcc50",
   "metadata": {},
   "source": [
    "### 2. Model Based Feature Selection\n",
    "Model based feature selection uses a supervised machine learning model to judge the importance of each feature, and keeps only the most important ones. For this case, we are going to use a random forest classifier, since it usually yields good results and because this is a classification task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "21972eed",
   "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>Bankrupt?</th>\n",
       "      <th>ROA(C) before interest and depreciation before interest</th>\n",
       "      <th>ROA(A) before interest and % after tax</th>\n",
       "      <th>ROA(B) before interest and depreciation after tax</th>\n",
       "      <th>Operating Gross Margin</th>\n",
       "      <th>Realized Sales Gross Margin</th>\n",
       "      <th>Operating Profit Rate</th>\n",
       "      <th>Pre-tax net Interest Rate</th>\n",
       "      <th>After-tax net Interest Rate</th>\n",
       "      <th>Non-industry income and expenditure/revenue</th>\n",
       "      <th>...</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Total assets to GNP price</th>\n",
       "      <th>No-credit Interval</th>\n",
       "      <th>Gross Profit to Sales</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Liability to Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Interest Coverage Ratio (Interest expense to EBIT)</th>\n",
       "      <th>Net Income Flag</th>\n",
       "      <th>Equity to Liability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.370594</td>\n",
       "      <td>0.424389</td>\n",
       "      <td>0.405750</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.998969</td>\n",
       "      <td>0.796887</td>\n",
       "      <td>0.808809</td>\n",
       "      <td>0.302646</td>\n",
       "      <td>...</td>\n",
       "      <td>0.716845</td>\n",
       "      <td>0.009219</td>\n",
       "      <td>0.622879</td>\n",
       "      <td>0.601453</td>\n",
       "      <td>0.827890</td>\n",
       "      <td>0.290202</td>\n",
       "      <td>0.026601</td>\n",
       "      <td>0.564050</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.464291</td>\n",
       "      <td>0.538214</td>\n",
       "      <td>0.516730</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.998946</td>\n",
       "      <td>0.797380</td>\n",
       "      <td>0.809301</td>\n",
       "      <td>0.303556</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795297</td>\n",
       "      <td>0.008323</td>\n",
       "      <td>0.623652</td>\n",
       "      <td>0.610237</td>\n",
       "      <td>0.839969</td>\n",
       "      <td>0.283846</td>\n",
       "      <td>0.264577</td>\n",
       "      <td>0.570175</td>\n",
       "      <td>1</td>\n",
       "      <td>0.020794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0.426071</td>\n",
       "      <td>0.499019</td>\n",
       "      <td>0.472295</td>\n",
       "      <td>0.601450</td>\n",
       "      <td>0.601364</td>\n",
       "      <td>0.998857</td>\n",
       "      <td>0.796403</td>\n",
       "      <td>0.808388</td>\n",
       "      <td>0.302035</td>\n",
       "      <td>...</td>\n",
       "      <td>0.774670</td>\n",
       "      <td>0.040003</td>\n",
       "      <td>0.623841</td>\n",
       "      <td>0.601449</td>\n",
       "      <td>0.836774</td>\n",
       "      <td>0.290189</td>\n",
       "      <td>0.026555</td>\n",
       "      <td>0.563706</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0.399844</td>\n",
       "      <td>0.451265</td>\n",
       "      <td>0.457733</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.998700</td>\n",
       "      <td>0.796967</td>\n",
       "      <td>0.808966</td>\n",
       "      <td>0.303350</td>\n",
       "      <td>...</td>\n",
       "      <td>0.739555</td>\n",
       "      <td>0.003252</td>\n",
       "      <td>0.622929</td>\n",
       "      <td>0.583538</td>\n",
       "      <td>0.834697</td>\n",
       "      <td>0.281721</td>\n",
       "      <td>0.026697</td>\n",
       "      <td>0.564663</td>\n",
       "      <td>1</td>\n",
       "      <td>0.023982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0.465022</td>\n",
       "      <td>0.538432</td>\n",
       "      <td>0.522298</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.998973</td>\n",
       "      <td>0.797366</td>\n",
       "      <td>0.809304</td>\n",
       "      <td>0.303475</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795016</td>\n",
       "      <td>0.003878</td>\n",
       "      <td>0.623521</td>\n",
       "      <td>0.598782</td>\n",
       "      <td>0.839973</td>\n",
       "      <td>0.278514</td>\n",
       "      <td>0.024752</td>\n",
       "      <td>0.575617</td>\n",
       "      <td>1</td>\n",
       "      <td>0.035490</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>6814</th>\n",
       "      <td>0</td>\n",
       "      <td>0.493687</td>\n",
       "      <td>0.539468</td>\n",
       "      <td>0.543230</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.604462</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797409</td>\n",
       "      <td>0.809331</td>\n",
       "      <td>0.303510</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799927</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>0.623620</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.840359</td>\n",
       "      <td>0.279606</td>\n",
       "      <td>0.027064</td>\n",
       "      <td>0.566193</td>\n",
       "      <td>1</td>\n",
       "      <td>0.029890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6815</th>\n",
       "      <td>0</td>\n",
       "      <td>0.475162</td>\n",
       "      <td>0.538269</td>\n",
       "      <td>0.524172</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797414</td>\n",
       "      <td>0.809327</td>\n",
       "      <td>0.303520</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799748</td>\n",
       "      <td>0.001959</td>\n",
       "      <td>0.623931</td>\n",
       "      <td>0.598306</td>\n",
       "      <td>0.840306</td>\n",
       "      <td>0.278132</td>\n",
       "      <td>0.027009</td>\n",
       "      <td>0.566018</td>\n",
       "      <td>1</td>\n",
       "      <td>0.038284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6816</th>\n",
       "      <td>0</td>\n",
       "      <td>0.472725</td>\n",
       "      <td>0.533744</td>\n",
       "      <td>0.520638</td>\n",
       "      <td>0.610444</td>\n",
       "      <td>0.610213</td>\n",
       "      <td>0.998984</td>\n",
       "      <td>0.797401</td>\n",
       "      <td>0.809317</td>\n",
       "      <td>0.303512</td>\n",
       "      <td>...</td>\n",
       "      <td>0.797778</td>\n",
       "      <td>0.002840</td>\n",
       "      <td>0.624156</td>\n",
       "      <td>0.610441</td>\n",
       "      <td>0.840138</td>\n",
       "      <td>0.275789</td>\n",
       "      <td>0.026791</td>\n",
       "      <td>0.565158</td>\n",
       "      <td>1</td>\n",
       "      <td>0.097649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6817</th>\n",
       "      <td>0</td>\n",
       "      <td>0.506264</td>\n",
       "      <td>0.559911</td>\n",
       "      <td>0.554045</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.999074</td>\n",
       "      <td>0.797500</td>\n",
       "      <td>0.809399</td>\n",
       "      <td>0.303498</td>\n",
       "      <td>...</td>\n",
       "      <td>0.811808</td>\n",
       "      <td>0.002837</td>\n",
       "      <td>0.623957</td>\n",
       "      <td>0.607846</td>\n",
       "      <td>0.841084</td>\n",
       "      <td>0.277547</td>\n",
       "      <td>0.026822</td>\n",
       "      <td>0.565302</td>\n",
       "      <td>1</td>\n",
       "      <td>0.044009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6818</th>\n",
       "      <td>0</td>\n",
       "      <td>0.493053</td>\n",
       "      <td>0.570105</td>\n",
       "      <td>0.549548</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.998080</td>\n",
       "      <td>0.801987</td>\n",
       "      <td>0.813800</td>\n",
       "      <td>0.313415</td>\n",
       "      <td>...</td>\n",
       "      <td>0.815956</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>0.626680</td>\n",
       "      <td>0.627408</td>\n",
       "      <td>0.841019</td>\n",
       "      <td>0.275114</td>\n",
       "      <td>0.026793</td>\n",
       "      <td>0.565167</td>\n",
       "      <td>1</td>\n",
       "      <td>0.233902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6819 rows × 96 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Bankrupt?   ROA(C) before interest and depreciation before interest  \\\n",
       "0             1                                           0.370594          \n",
       "1             1                                           0.464291          \n",
       "2             1                                           0.426071          \n",
       "3             1                                           0.399844          \n",
       "4             1                                           0.465022          \n",
       "...         ...                                                ...          \n",
       "6814          0                                           0.493687          \n",
       "6815          0                                           0.475162          \n",
       "6816          0                                           0.472725          \n",
       "6817          0                                           0.506264          \n",
       "6818          0                                           0.493053          \n",
       "\n",
       "       ROA(A) before interest and % after tax  \\\n",
       "0                                    0.424389   \n",
       "1                                    0.538214   \n",
       "2                                    0.499019   \n",
       "3                                    0.451265   \n",
       "4                                    0.538432   \n",
       "...                                       ...   \n",
       "6814                                 0.539468   \n",
       "6815                                 0.538269   \n",
       "6816                                 0.533744   \n",
       "6817                                 0.559911   \n",
       "6818                                 0.570105   \n",
       "\n",
       "       ROA(B) before interest and depreciation after tax  \\\n",
       "0                                              0.405750    \n",
       "1                                              0.516730    \n",
       "2                                              0.472295    \n",
       "3                                              0.457733    \n",
       "4                                              0.522298    \n",
       "...                                                 ...    \n",
       "6814                                           0.543230    \n",
       "6815                                           0.524172    \n",
       "6816                                           0.520638    \n",
       "6817                                           0.554045    \n",
       "6818                                           0.549548    \n",
       "\n",
       "       Operating Gross Margin   Realized Sales Gross Margin  \\\n",
       "0                    0.601457                      0.601457   \n",
       "1                    0.610235                      0.610235   \n",
       "2                    0.601450                      0.601364   \n",
       "3                    0.583541                      0.583541   \n",
       "4                    0.598783                      0.598783   \n",
       "...                       ...                           ...   \n",
       "6814                 0.604455                      0.604462   \n",
       "6815                 0.598308                      0.598308   \n",
       "6816                 0.610444                      0.610213   \n",
       "6817                 0.607850                      0.607850   \n",
       "6818                 0.627409                      0.627409   \n",
       "\n",
       "       Operating Profit Rate   Pre-tax net Interest Rate  \\\n",
       "0                   0.998969                    0.796887   \n",
       "1                   0.998946                    0.797380   \n",
       "2                   0.998857                    0.796403   \n",
       "3                   0.998700                    0.796967   \n",
       "4                   0.998973                    0.797366   \n",
       "...                      ...                         ...   \n",
       "6814                0.998992                    0.797409   \n",
       "6815                0.998992                    0.797414   \n",
       "6816                0.998984                    0.797401   \n",
       "6817                0.999074                    0.797500   \n",
       "6818                0.998080                    0.801987   \n",
       "\n",
       "       After-tax net Interest Rate  \\\n",
       "0                         0.808809   \n",
       "1                         0.809301   \n",
       "2                         0.808388   \n",
       "3                         0.808966   \n",
       "4                         0.809304   \n",
       "...                            ...   \n",
       "6814                      0.809331   \n",
       "6815                      0.809327   \n",
       "6816                      0.809317   \n",
       "6817                      0.809399   \n",
       "6818                      0.813800   \n",
       "\n",
       "       Non-industry income and expenditure/revenue  ...  \\\n",
       "0                                         0.302646  ...   \n",
       "1                                         0.303556  ...   \n",
       "2                                         0.302035  ...   \n",
       "3                                         0.303350  ...   \n",
       "4                                         0.303475  ...   \n",
       "...                                            ...  ...   \n",
       "6814                                      0.303510  ...   \n",
       "6815                                      0.303520  ...   \n",
       "6816                                      0.303512  ...   \n",
       "6817                                      0.303498  ...   \n",
       "6818                                      0.313415  ...   \n",
       "\n",
       "       Net Income to Total Assets   Total assets to GNP price  \\\n",
       "0                        0.716845                    0.009219   \n",
       "1                        0.795297                    0.008323   \n",
       "2                        0.774670                    0.040003   \n",
       "3                        0.739555                    0.003252   \n",
       "4                        0.795016                    0.003878   \n",
       "...                           ...                         ...   \n",
       "6814                     0.799927                    0.000466   \n",
       "6815                     0.799748                    0.001959   \n",
       "6816                     0.797778                    0.002840   \n",
       "6817                     0.811808                    0.002837   \n",
       "6818                     0.815956                    0.000707   \n",
       "\n",
       "       No-credit Interval   Gross Profit to Sales  \\\n",
       "0                0.622879                0.601453   \n",
       "1                0.623652                0.610237   \n",
       "2                0.623841                0.601449   \n",
       "3                0.622929                0.583538   \n",
       "4                0.623521                0.598782   \n",
       "...                   ...                     ...   \n",
       "6814             0.623620                0.604455   \n",
       "6815             0.623931                0.598306   \n",
       "6816             0.624156                0.610441   \n",
       "6817             0.623957                0.607846   \n",
       "6818             0.626680                0.627408   \n",
       "\n",
       "       Net Income to Stockholder's Equity   Liability to Equity  \\\n",
       "0                                0.827890              0.290202   \n",
       "1                                0.839969              0.283846   \n",
       "2                                0.836774              0.290189   \n",
       "3                                0.834697              0.281721   \n",
       "4                                0.839973              0.278514   \n",
       "...                                   ...                   ...   \n",
       "6814                             0.840359              0.279606   \n",
       "6815                             0.840306              0.278132   \n",
       "6816                             0.840138              0.275789   \n",
       "6817                             0.841084              0.277547   \n",
       "6818                             0.841019              0.275114   \n",
       "\n",
       "       Degree of Financial Leverage (DFL)  \\\n",
       "0                                0.026601   \n",
       "1                                0.264577   \n",
       "2                                0.026555   \n",
       "3                                0.026697   \n",
       "4                                0.024752   \n",
       "...                                   ...   \n",
       "6814                             0.027064   \n",
       "6815                             0.027009   \n",
       "6816                             0.026791   \n",
       "6817                             0.026822   \n",
       "6818                             0.026793   \n",
       "\n",
       "       Interest Coverage Ratio (Interest expense to EBIT)   Net Income Flag  \\\n",
       "0                                              0.564050                   1   \n",
       "1                                              0.570175                   1   \n",
       "2                                              0.563706                   1   \n",
       "3                                              0.564663                   1   \n",
       "4                                              0.575617                   1   \n",
       "...                                                 ...                 ...   \n",
       "6814                                           0.566193                   1   \n",
       "6815                                           0.566018                   1   \n",
       "6816                                           0.565158                   1   \n",
       "6817                                           0.565302                   1   \n",
       "6818                                           0.565167                   1   \n",
       "\n",
       "       Equity to Liability  \n",
       "0                 0.016469  \n",
       "1                 0.020794  \n",
       "2                 0.016474  \n",
       "3                 0.023982  \n",
       "4                 0.035490  \n",
       "...                    ...  \n",
       "6814              0.029890  \n",
       "6815              0.038284  \n",
       "6816              0.097649  \n",
       "6817              0.044009  \n",
       "6818              0.233902  \n",
       "\n",
       "[6819 rows x 96 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "15922644",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       1\n",
       "2       1\n",
       "3       1\n",
       "4       1\n",
       "       ..\n",
       "6814    0\n",
       "6815    0\n",
       "6816    0\n",
       "6817    0\n",
       "6818    0\n",
       "Name: Bankrupt?, Length: 6819, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# y\n",
    "bank.iloc[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1739c992",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# y\n",
    "bank.iloc[:,0].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1bc0e034",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1],\n",
       "       [1],\n",
       "       [1],\n",
       "       ...,\n",
       "       [0],\n",
       "       [0],\n",
       "       [0]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# y\n",
    "bank.iloc[:,0].values.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "81a4612a",
   "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>ROA(C) before interest and depreciation before interest</th>\n",
       "      <th>ROA(A) before interest and % after tax</th>\n",
       "      <th>ROA(B) before interest and depreciation after tax</th>\n",
       "      <th>Operating Gross Margin</th>\n",
       "      <th>Realized Sales Gross Margin</th>\n",
       "      <th>Operating Profit Rate</th>\n",
       "      <th>Pre-tax net Interest Rate</th>\n",
       "      <th>After-tax net Interest Rate</th>\n",
       "      <th>Non-industry income and expenditure/revenue</th>\n",
       "      <th>Continuous interest rate (after tax)</th>\n",
       "      <th>...</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Total assets to GNP price</th>\n",
       "      <th>No-credit Interval</th>\n",
       "      <th>Gross Profit to Sales</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Liability to Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Interest Coverage Ratio (Interest expense to EBIT)</th>\n",
       "      <th>Net Income Flag</th>\n",
       "      <th>Equity to Liability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.370594</td>\n",
       "      <td>0.424389</td>\n",
       "      <td>0.405750</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.601457</td>\n",
       "      <td>0.998969</td>\n",
       "      <td>0.796887</td>\n",
       "      <td>0.808809</td>\n",
       "      <td>0.302646</td>\n",
       "      <td>0.780985</td>\n",
       "      <td>...</td>\n",
       "      <td>0.716845</td>\n",
       "      <td>0.009219</td>\n",
       "      <td>0.622879</td>\n",
       "      <td>0.601453</td>\n",
       "      <td>0.827890</td>\n",
       "      <td>0.290202</td>\n",
       "      <td>0.026601</td>\n",
       "      <td>0.564050</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.464291</td>\n",
       "      <td>0.538214</td>\n",
       "      <td>0.516730</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.610235</td>\n",
       "      <td>0.998946</td>\n",
       "      <td>0.797380</td>\n",
       "      <td>0.809301</td>\n",
       "      <td>0.303556</td>\n",
       "      <td>0.781506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795297</td>\n",
       "      <td>0.008323</td>\n",
       "      <td>0.623652</td>\n",
       "      <td>0.610237</td>\n",
       "      <td>0.839969</td>\n",
       "      <td>0.283846</td>\n",
       "      <td>0.264577</td>\n",
       "      <td>0.570175</td>\n",
       "      <td>1</td>\n",
       "      <td>0.020794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.426071</td>\n",
       "      <td>0.499019</td>\n",
       "      <td>0.472295</td>\n",
       "      <td>0.601450</td>\n",
       "      <td>0.601364</td>\n",
       "      <td>0.998857</td>\n",
       "      <td>0.796403</td>\n",
       "      <td>0.808388</td>\n",
       "      <td>0.302035</td>\n",
       "      <td>0.780284</td>\n",
       "      <td>...</td>\n",
       "      <td>0.774670</td>\n",
       "      <td>0.040003</td>\n",
       "      <td>0.623841</td>\n",
       "      <td>0.601449</td>\n",
       "      <td>0.836774</td>\n",
       "      <td>0.290189</td>\n",
       "      <td>0.026555</td>\n",
       "      <td>0.563706</td>\n",
       "      <td>1</td>\n",
       "      <td>0.016474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.399844</td>\n",
       "      <td>0.451265</td>\n",
       "      <td>0.457733</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.583541</td>\n",
       "      <td>0.998700</td>\n",
       "      <td>0.796967</td>\n",
       "      <td>0.808966</td>\n",
       "      <td>0.303350</td>\n",
       "      <td>0.781241</td>\n",
       "      <td>...</td>\n",
       "      <td>0.739555</td>\n",
       "      <td>0.003252</td>\n",
       "      <td>0.622929</td>\n",
       "      <td>0.583538</td>\n",
       "      <td>0.834697</td>\n",
       "      <td>0.281721</td>\n",
       "      <td>0.026697</td>\n",
       "      <td>0.564663</td>\n",
       "      <td>1</td>\n",
       "      <td>0.023982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.465022</td>\n",
       "      <td>0.538432</td>\n",
       "      <td>0.522298</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.598783</td>\n",
       "      <td>0.998973</td>\n",
       "      <td>0.797366</td>\n",
       "      <td>0.809304</td>\n",
       "      <td>0.303475</td>\n",
       "      <td>0.781550</td>\n",
       "      <td>...</td>\n",
       "      <td>0.795016</td>\n",
       "      <td>0.003878</td>\n",
       "      <td>0.623521</td>\n",
       "      <td>0.598782</td>\n",
       "      <td>0.839973</td>\n",
       "      <td>0.278514</td>\n",
       "      <td>0.024752</td>\n",
       "      <td>0.575617</td>\n",
       "      <td>1</td>\n",
       "      <td>0.035490</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>6814</th>\n",
       "      <td>0.493687</td>\n",
       "      <td>0.539468</td>\n",
       "      <td>0.543230</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.604462</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797409</td>\n",
       "      <td>0.809331</td>\n",
       "      <td>0.303510</td>\n",
       "      <td>0.781588</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799927</td>\n",
       "      <td>0.000466</td>\n",
       "      <td>0.623620</td>\n",
       "      <td>0.604455</td>\n",
       "      <td>0.840359</td>\n",
       "      <td>0.279606</td>\n",
       "      <td>0.027064</td>\n",
       "      <td>0.566193</td>\n",
       "      <td>1</td>\n",
       "      <td>0.029890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6815</th>\n",
       "      <td>0.475162</td>\n",
       "      <td>0.538269</td>\n",
       "      <td>0.524172</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.598308</td>\n",
       "      <td>0.998992</td>\n",
       "      <td>0.797414</td>\n",
       "      <td>0.809327</td>\n",
       "      <td>0.303520</td>\n",
       "      <td>0.781586</td>\n",
       "      <td>...</td>\n",
       "      <td>0.799748</td>\n",
       "      <td>0.001959</td>\n",
       "      <td>0.623931</td>\n",
       "      <td>0.598306</td>\n",
       "      <td>0.840306</td>\n",
       "      <td>0.278132</td>\n",
       "      <td>0.027009</td>\n",
       "      <td>0.566018</td>\n",
       "      <td>1</td>\n",
       "      <td>0.038284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6816</th>\n",
       "      <td>0.472725</td>\n",
       "      <td>0.533744</td>\n",
       "      <td>0.520638</td>\n",
       "      <td>0.610444</td>\n",
       "      <td>0.610213</td>\n",
       "      <td>0.998984</td>\n",
       "      <td>0.797401</td>\n",
       "      <td>0.809317</td>\n",
       "      <td>0.303512</td>\n",
       "      <td>0.781546</td>\n",
       "      <td>...</td>\n",
       "      <td>0.797778</td>\n",
       "      <td>0.002840</td>\n",
       "      <td>0.624156</td>\n",
       "      <td>0.610441</td>\n",
       "      <td>0.840138</td>\n",
       "      <td>0.275789</td>\n",
       "      <td>0.026791</td>\n",
       "      <td>0.565158</td>\n",
       "      <td>1</td>\n",
       "      <td>0.097649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6817</th>\n",
       "      <td>0.506264</td>\n",
       "      <td>0.559911</td>\n",
       "      <td>0.554045</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.607850</td>\n",
       "      <td>0.999074</td>\n",
       "      <td>0.797500</td>\n",
       "      <td>0.809399</td>\n",
       "      <td>0.303498</td>\n",
       "      <td>0.781663</td>\n",
       "      <td>...</td>\n",
       "      <td>0.811808</td>\n",
       "      <td>0.002837</td>\n",
       "      <td>0.623957</td>\n",
       "      <td>0.607846</td>\n",
       "      <td>0.841084</td>\n",
       "      <td>0.277547</td>\n",
       "      <td>0.026822</td>\n",
       "      <td>0.565302</td>\n",
       "      <td>1</td>\n",
       "      <td>0.044009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6818</th>\n",
       "      <td>0.493053</td>\n",
       "      <td>0.570105</td>\n",
       "      <td>0.549548</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.627409</td>\n",
       "      <td>0.998080</td>\n",
       "      <td>0.801987</td>\n",
       "      <td>0.813800</td>\n",
       "      <td>0.313415</td>\n",
       "      <td>0.786079</td>\n",
       "      <td>...</td>\n",
       "      <td>0.815956</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>0.626680</td>\n",
       "      <td>0.627408</td>\n",
       "      <td>0.841019</td>\n",
       "      <td>0.275114</td>\n",
       "      <td>0.026793</td>\n",
       "      <td>0.565167</td>\n",
       "      <td>1</td>\n",
       "      <td>0.233902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6819 rows × 95 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ROA(C) before interest and depreciation before interest  \\\n",
       "0                                              0.370594          \n",
       "1                                              0.464291          \n",
       "2                                              0.426071          \n",
       "3                                              0.399844          \n",
       "4                                              0.465022          \n",
       "...                                                 ...          \n",
       "6814                                           0.493687          \n",
       "6815                                           0.475162          \n",
       "6816                                           0.472725          \n",
       "6817                                           0.506264          \n",
       "6818                                           0.493053          \n",
       "\n",
       "       ROA(A) before interest and % after tax  \\\n",
       "0                                    0.424389   \n",
       "1                                    0.538214   \n",
       "2                                    0.499019   \n",
       "3                                    0.451265   \n",
       "4                                    0.538432   \n",
       "...                                       ...   \n",
       "6814                                 0.539468   \n",
       "6815                                 0.538269   \n",
       "6816                                 0.533744   \n",
       "6817                                 0.559911   \n",
       "6818                                 0.570105   \n",
       "\n",
       "       ROA(B) before interest and depreciation after tax  \\\n",
       "0                                              0.405750    \n",
       "1                                              0.516730    \n",
       "2                                              0.472295    \n",
       "3                                              0.457733    \n",
       "4                                              0.522298    \n",
       "...                                                 ...    \n",
       "6814                                           0.543230    \n",
       "6815                                           0.524172    \n",
       "6816                                           0.520638    \n",
       "6817                                           0.554045    \n",
       "6818                                           0.549548    \n",
       "\n",
       "       Operating Gross Margin   Realized Sales Gross Margin  \\\n",
       "0                    0.601457                      0.601457   \n",
       "1                    0.610235                      0.610235   \n",
       "2                    0.601450                      0.601364   \n",
       "3                    0.583541                      0.583541   \n",
       "4                    0.598783                      0.598783   \n",
       "...                       ...                           ...   \n",
       "6814                 0.604455                      0.604462   \n",
       "6815                 0.598308                      0.598308   \n",
       "6816                 0.610444                      0.610213   \n",
       "6817                 0.607850                      0.607850   \n",
       "6818                 0.627409                      0.627409   \n",
       "\n",
       "       Operating Profit Rate   Pre-tax net Interest Rate  \\\n",
       "0                   0.998969                    0.796887   \n",
       "1                   0.998946                    0.797380   \n",
       "2                   0.998857                    0.796403   \n",
       "3                   0.998700                    0.796967   \n",
       "4                   0.998973                    0.797366   \n",
       "...                      ...                         ...   \n",
       "6814                0.998992                    0.797409   \n",
       "6815                0.998992                    0.797414   \n",
       "6816                0.998984                    0.797401   \n",
       "6817                0.999074                    0.797500   \n",
       "6818                0.998080                    0.801987   \n",
       "\n",
       "       After-tax net Interest Rate  \\\n",
       "0                         0.808809   \n",
       "1                         0.809301   \n",
       "2                         0.808388   \n",
       "3                         0.808966   \n",
       "4                         0.809304   \n",
       "...                            ...   \n",
       "6814                      0.809331   \n",
       "6815                      0.809327   \n",
       "6816                      0.809317   \n",
       "6817                      0.809399   \n",
       "6818                      0.813800   \n",
       "\n",
       "       Non-industry income and expenditure/revenue  \\\n",
       "0                                         0.302646   \n",
       "1                                         0.303556   \n",
       "2                                         0.302035   \n",
       "3                                         0.303350   \n",
       "4                                         0.303475   \n",
       "...                                            ...   \n",
       "6814                                      0.303510   \n",
       "6815                                      0.303520   \n",
       "6816                                      0.303512   \n",
       "6817                                      0.303498   \n",
       "6818                                      0.313415   \n",
       "\n",
       "       Continuous interest rate (after tax)  ...   Net Income to Total Assets  \\\n",
       "0                                  0.780985  ...                     0.716845   \n",
       "1                                  0.781506  ...                     0.795297   \n",
       "2                                  0.780284  ...                     0.774670   \n",
       "3                                  0.781241  ...                     0.739555   \n",
       "4                                  0.781550  ...                     0.795016   \n",
       "...                                     ...  ...                          ...   \n",
       "6814                               0.781588  ...                     0.799927   \n",
       "6815                               0.781586  ...                     0.799748   \n",
       "6816                               0.781546  ...                     0.797778   \n",
       "6817                               0.781663  ...                     0.811808   \n",
       "6818                               0.786079  ...                     0.815956   \n",
       "\n",
       "       Total assets to GNP price   No-credit Interval   Gross Profit to Sales  \\\n",
       "0                       0.009219             0.622879                0.601453   \n",
       "1                       0.008323             0.623652                0.610237   \n",
       "2                       0.040003             0.623841                0.601449   \n",
       "3                       0.003252             0.622929                0.583538   \n",
       "4                       0.003878             0.623521                0.598782   \n",
       "...                          ...                  ...                     ...   \n",
       "6814                    0.000466             0.623620                0.604455   \n",
       "6815                    0.001959             0.623931                0.598306   \n",
       "6816                    0.002840             0.624156                0.610441   \n",
       "6817                    0.002837             0.623957                0.607846   \n",
       "6818                    0.000707             0.626680                0.627408   \n",
       "\n",
       "       Net Income to Stockholder's Equity   Liability to Equity  \\\n",
       "0                                0.827890              0.290202   \n",
       "1                                0.839969              0.283846   \n",
       "2                                0.836774              0.290189   \n",
       "3                                0.834697              0.281721   \n",
       "4                                0.839973              0.278514   \n",
       "...                                   ...                   ...   \n",
       "6814                             0.840359              0.279606   \n",
       "6815                             0.840306              0.278132   \n",
       "6816                             0.840138              0.275789   \n",
       "6817                             0.841084              0.277547   \n",
       "6818                             0.841019              0.275114   \n",
       "\n",
       "       Degree of Financial Leverage (DFL)  \\\n",
       "0                                0.026601   \n",
       "1                                0.264577   \n",
       "2                                0.026555   \n",
       "3                                0.026697   \n",
       "4                                0.024752   \n",
       "...                                   ...   \n",
       "6814                             0.027064   \n",
       "6815                             0.027009   \n",
       "6816                             0.026791   \n",
       "6817                             0.026822   \n",
       "6818                             0.026793   \n",
       "\n",
       "       Interest Coverage Ratio (Interest expense to EBIT)   Net Income Flag  \\\n",
       "0                                              0.564050                   1   \n",
       "1                                              0.570175                   1   \n",
       "2                                              0.563706                   1   \n",
       "3                                              0.564663                   1   \n",
       "4                                              0.575617                   1   \n",
       "...                                                 ...                 ...   \n",
       "6814                                           0.566193                   1   \n",
       "6815                                           0.566018                   1   \n",
       "6816                                           0.565158                   1   \n",
       "6817                                           0.565302                   1   \n",
       "6818                                           0.565167                   1   \n",
       "\n",
       "       Equity to Liability  \n",
       "0                 0.016469  \n",
       "1                 0.020794  \n",
       "2                 0.016474  \n",
       "3                 0.023982  \n",
       "4                 0.035490  \n",
       "...                    ...  \n",
       "6814              0.029890  \n",
       "6815              0.038284  \n",
       "6816              0.097649  \n",
       "6817              0.044009  \n",
       "6818              0.233902  \n",
       "\n",
       "[6819 rows x 95 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# x\n",
    "bank.iloc[:,1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81b22daa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.37059426, 0.42438945, 0.40574977, ..., 0.56405011, 1.        ,\n",
       "        0.01646874],\n",
       "       [0.46429094, 0.53821413, 0.51673002, ..., 0.57017495, 1.        ,\n",
       "        0.02079431],\n",
       "       [0.42607127, 0.49901875, 0.47229509, ..., 0.56370608, 1.        ,\n",
       "        0.01647411],\n",
       "       ...,\n",
       "       [0.47272461, 0.533744  , 0.52063815, ..., 0.5651584 , 1.        ,\n",
       "        0.09764874],\n",
       "       [0.50626432, 0.5599106 , 0.55404465, ..., 0.56530151, 1.        ,\n",
       "        0.04400945],\n",
       "       [0.49305319, 0.57010467, 0.54954762, ..., 0.56516694, 1.        ,\n",
       "        0.23390224]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank.iloc[:,1:].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "44a11f56",
   "metadata": {},
   "outputs": [],
   "source": [
    "# training set\n",
    "X = bank.iloc[:,1:].values\n",
    "y = bank.iloc[:,0].values.reshape(-1,1)\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X,y, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f4145adb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test score: 0.968  number of features: 5\n",
      "Test score: 0.970  number of features: 10\n",
      "Test score: 0.971  number of features: 15\n",
      "Test score: 0.970  number of features: 20\n",
      "Test score: 0.971  number of features: 25\n",
      "Test score: 0.972  number of features: 30\n",
      "Test score: 0.971  number of features: 35\n",
      "Test score: 0.972  number of features: 40\n"
     ]
    }
   ],
   "source": [
    "# determining optimal number of features\n",
    "n_features = [5, 10, 15, 20, 25, 30, 35, 40]\n",
    "for i in n_features:\n",
    "    # Building the model based feature selection\n",
    "    select = RFE(RandomForestClassifier(n_estimators=100, random_state=42), n_features_to_select=i)\n",
    "    \n",
    "    select.fit(X_train, y_train)\n",
    "    mask = select.get_support()\n",
    "    \n",
    "    X_train_rfe = select.transform(X_train)\n",
    "    X_test_rfe = select.transform(X_test)\n",
    "    \n",
    "    score = RandomForestClassifier().fit(X_train_rfe, y_train).score(X_test_rfe, y_test)\n",
    "    \n",
    "    print(\"Test score: {:.3f}\".format(score), \" number of features: {}\".format(i))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19fe7728",
   "metadata": {},
   "source": [
    "There's not so much difference between the scores with different features. We are going to work with 15 features since is a 'workable' number of features and has a good a score. Let's run the algorithm again and get the features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "59a6b170",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test score: 0.969  number of features: 15\n"
     ]
    }
   ],
   "source": [
    "select = RFE(RandomForestClassifier(n_estimators=100, random_state=42), n_features_to_select=15)\n",
    "\n",
    "# fit - train set\n",
    "select.fit(X_train, y_train)\n",
    "\n",
    "mask = select.get_support()\n",
    "\n",
    "# trainsform - train / test set\n",
    "X_train_rfe = select.transform(X_train)\n",
    "X_test_rfe = select.transform(X_test)\n",
    "\n",
    "score = RandomForestClassifier().fit(X_train_rfe, y_train).score(X_test_rfe, y_test)\n",
    "\n",
    "print(\"Test score: {:.3f}\".format(score), \" number of features: {}\".format(15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "989b6547",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False, False, False, False, False, False, False,  True,\n",
       "       False, False, False, False,  True, False, False,  True, False,\n",
       "        True, False, False, False, False, False, False, False, False,\n",
       "       False, False,  True, False, False, False, False,  True,  True,\n",
       "       False, False, False,  True, False, False,  True, False, False,\n",
       "       False, False, False,  True, False, False, False, False, False,\n",
       "       False, False,  True, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False,  True, False, False, False,  True,\n",
       "       False,  True, False, False,  True])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What is mask? (select.get_support())\n",
    "mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3e2e6c68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>features</th>\n",
       "      <th>select</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ROA(C) before interest and depreciation befor...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ROA(A) before interest and % after tax</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ROA(B) before interest and depreciation after...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Operating Gross Margin</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Realized Sales Gross Margin</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Liability to Equity</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Degree of Financial Leverage (DFL)</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>Interest Coverage Ratio (Interest expense to ...</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Net Income Flag</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Equity to Liability</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>95 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             features  select\n",
       "0    ROA(C) before interest and depreciation befor...   False\n",
       "1              ROA(A) before interest and % after tax   False\n",
       "2    ROA(B) before interest and depreciation after...   False\n",
       "3                              Operating Gross Margin   False\n",
       "4                         Realized Sales Gross Margin   False\n",
       "..                                                ...     ...\n",
       "90                                Liability to Equity   False\n",
       "91                 Degree of Financial Leverage (DFL)    True\n",
       "92   Interest Coverage Ratio (Interest expense to ...   False\n",
       "93                                    Net Income Flag   False\n",
       "94                                Equity to Liability    True\n",
       "\n",
       "[95 rows x 2 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = pd.DataFrame({'features':list(bank.iloc[:,1:].keys()), 'select':list(mask)})\n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "04be0e82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[' Non-industry income and expenditure/revenue',\n",
       " ' Interest-bearing debt interest rate',\n",
       " ' Net Value Per Share (A)',\n",
       " ' Persistent EPS in the Last Four Seasons',\n",
       " ' Net Value Growth Rate',\n",
       " ' Interest Expense Ratio',\n",
       " ' Total debt/Total net worth',\n",
       " ' Borrowing dependency',\n",
       " ' Net profit before tax/Paid-in capital',\n",
       " ' Fixed Assets Turnover Frequency',\n",
       " ' Cash/Total Assets',\n",
       " ' Net Income to Total Assets',\n",
       " \" Net Income to Stockholder's Equity\",\n",
       " ' Degree of Financial Leverage (DFL)',\n",
       " ' Equity to Liability']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = list(features[features['select']==True]['features'])\n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3f4c5030",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[' Non-industry income and expenditure/revenue',\n",
       " ' Interest-bearing debt interest rate',\n",
       " ' Net Value Per Share (A)',\n",
       " ' Persistent EPS in the Last Four Seasons',\n",
       " ' Net Value Growth Rate',\n",
       " ' Interest Expense Ratio',\n",
       " ' Total debt/Total net worth',\n",
       " ' Borrowing dependency',\n",
       " ' Net profit before tax/Paid-in capital',\n",
       " ' Fixed Assets Turnover Frequency',\n",
       " ' Cash/Total Assets',\n",
       " ' Net Income to Total Assets',\n",
       " \" Net Income to Stockholder's Equity\",\n",
       " ' Degree of Financial Leverage (DFL)',\n",
       " ' Equity to Liability',\n",
       " 'Bankrupt?']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features.append('Bankrupt?')\n",
    "features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac6eb5ff",
   "metadata": {},
   "source": [
    "Let's see the DataFrame we are going to work with it's stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "fd07c585",
   "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>Non-industry income and expenditure/revenue</th>\n",
       "      <th>Interest-bearing debt interest rate</th>\n",
       "      <th>Net Value Per Share (A)</th>\n",
       "      <th>Persistent EPS in the Last Four Seasons</th>\n",
       "      <th>Net Value Growth Rate</th>\n",
       "      <th>Interest Expense Ratio</th>\n",
       "      <th>Total debt/Total net worth</th>\n",
       "      <th>Borrowing dependency</th>\n",
       "      <th>Net profit before tax/Paid-in capital</th>\n",
       "      <th>Fixed Assets Turnover Frequency</th>\n",
       "      <th>Cash/Total Assets</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Equity to Liability</th>\n",
       "      <th>Bankrupt?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.302646</td>\n",
       "      <td>7.250725e-04</td>\n",
       "      <td>0.147950</td>\n",
       "      <td>0.169141</td>\n",
       "      <td>0.000327</td>\n",
       "      <td>0.629951</td>\n",
       "      <td>0.021266</td>\n",
       "      <td>0.390284</td>\n",
       "      <td>0.137757</td>\n",
       "      <td>1.165007e-04</td>\n",
       "      <td>0.004094</td>\n",
       "      <td>0.716845</td>\n",
       "      <td>0.827890</td>\n",
       "      <td>0.026601</td>\n",
       "      <td>0.016469</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.303556</td>\n",
       "      <td>6.470647e-04</td>\n",
       "      <td>0.182251</td>\n",
       "      <td>0.208944</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.635172</td>\n",
       "      <td>0.012502</td>\n",
       "      <td>0.376760</td>\n",
       "      <td>0.168962</td>\n",
       "      <td>7.190000e+08</td>\n",
       "      <td>0.014948</td>\n",
       "      <td>0.795297</td>\n",
       "      <td>0.839969</td>\n",
       "      <td>0.264577</td>\n",
       "      <td>0.020794</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.302035</td>\n",
       "      <td>7.900790e-04</td>\n",
       "      <td>0.177911</td>\n",
       "      <td>0.180581</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>0.629631</td>\n",
       "      <td>0.021248</td>\n",
       "      <td>0.379093</td>\n",
       "      <td>0.148036</td>\n",
       "      <td>2.650000e+09</td>\n",
       "      <td>0.000991</td>\n",
       "      <td>0.774670</td>\n",
       "      <td>0.836774</td>\n",
       "      <td>0.026555</td>\n",
       "      <td>0.016474</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.303350</td>\n",
       "      <td>4.490449e-04</td>\n",
       "      <td>0.154187</td>\n",
       "      <td>0.193722</td>\n",
       "      <td>0.000382</td>\n",
       "      <td>0.630228</td>\n",
       "      <td>0.009572</td>\n",
       "      <td>0.379743</td>\n",
       "      <td>0.147561</td>\n",
       "      <td>9.150000e+09</td>\n",
       "      <td>0.018851</td>\n",
       "      <td>0.739555</td>\n",
       "      <td>0.834697</td>\n",
       "      <td>0.026697</td>\n",
       "      <td>0.023982</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.303475</td>\n",
       "      <td>6.860686e-04</td>\n",
       "      <td>0.167502</td>\n",
       "      <td>0.212537</td>\n",
       "      <td>0.000439</td>\n",
       "      <td>0.636055</td>\n",
       "      <td>0.005150</td>\n",
       "      <td>0.375025</td>\n",
       "      <td>0.167461</td>\n",
       "      <td>2.935211e-04</td>\n",
       "      <td>0.014161</td>\n",
       "      <td>0.795016</td>\n",
       "      <td>0.839973</td>\n",
       "      <td>0.024752</td>\n",
       "      <td>0.035490</td>\n",
       "      <td>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6814</th>\n",
       "      <td>0.303510</td>\n",
       "      <td>1.790179e-04</td>\n",
       "      <td>0.175045</td>\n",
       "      <td>0.216602</td>\n",
       "      <td>0.000450</td>\n",
       "      <td>0.631415</td>\n",
       "      <td>0.006655</td>\n",
       "      <td>0.373823</td>\n",
       "      <td>0.171111</td>\n",
       "      <td>1.429781e-04</td>\n",
       "      <td>0.099481</td>\n",
       "      <td>0.799927</td>\n",
       "      <td>0.840359</td>\n",
       "      <td>0.027064</td>\n",
       "      <td>0.029890</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6815</th>\n",
       "      <td>0.303520</td>\n",
       "      <td>2.370237e-04</td>\n",
       "      <td>0.181324</td>\n",
       "      <td>0.216697</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>0.631489</td>\n",
       "      <td>0.004623</td>\n",
       "      <td>0.372505</td>\n",
       "      <td>0.171805</td>\n",
       "      <td>6.051982e-04</td>\n",
       "      <td>0.080337</td>\n",
       "      <td>0.799748</td>\n",
       "      <td>0.840306</td>\n",
       "      <td>0.027009</td>\n",
       "      <td>0.038284</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6816</th>\n",
       "      <td>0.303512</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.269521</td>\n",
       "      <td>0.210929</td>\n",
       "      <td>0.000435</td>\n",
       "      <td>0.630612</td>\n",
       "      <td>0.001392</td>\n",
       "      <td>0.369637</td>\n",
       "      <td>0.172287</td>\n",
       "      <td>1.024298e-03</td>\n",
       "      <td>0.412885</td>\n",
       "      <td>0.797778</td>\n",
       "      <td>0.840138</td>\n",
       "      <td>0.026791</td>\n",
       "      <td>0.097649</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6817</th>\n",
       "      <td>0.303498</td>\n",
       "      <td>2.110211e-04</td>\n",
       "      <td>0.213392</td>\n",
       "      <td>0.228326</td>\n",
       "      <td>0.000529</td>\n",
       "      <td>0.630731</td>\n",
       "      <td>0.003816</td>\n",
       "      <td>0.369649</td>\n",
       "      <td>0.182498</td>\n",
       "      <td>2.330013e-04</td>\n",
       "      <td>0.112238</td>\n",
       "      <td>0.811808</td>\n",
       "      <td>0.841084</td>\n",
       "      <td>0.026822</td>\n",
       "      <td>0.044009</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6818</th>\n",
       "      <td>0.313415</td>\n",
       "      <td>5.900000e+08</td>\n",
       "      <td>0.220766</td>\n",
       "      <td>0.227758</td>\n",
       "      <td>0.000519</td>\n",
       "      <td>0.630618</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>0.370049</td>\n",
       "      <td>0.179911</td>\n",
       "      <td>2.995731e-04</td>\n",
       "      <td>0.238147</td>\n",
       "      <td>0.815956</td>\n",
       "      <td>0.841019</td>\n",
       "      <td>0.026793</td>\n",
       "      <td>0.233902</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6819 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Non-industry income and expenditure/revenue  \\\n",
       "0                                         0.302646   \n",
       "1                                         0.303556   \n",
       "2                                         0.302035   \n",
       "3                                         0.303350   \n",
       "4                                         0.303475   \n",
       "...                                            ...   \n",
       "6814                                      0.303510   \n",
       "6815                                      0.303520   \n",
       "6816                                      0.303512   \n",
       "6817                                      0.303498   \n",
       "6818                                      0.313415   \n",
       "\n",
       "       Interest-bearing debt interest rate   Net Value Per Share (A)  \\\n",
       "0                             7.250725e-04                  0.147950   \n",
       "1                             6.470647e-04                  0.182251   \n",
       "2                             7.900790e-04                  0.177911   \n",
       "3                             4.490449e-04                  0.154187   \n",
       "4                             6.860686e-04                  0.167502   \n",
       "...                                    ...                       ...   \n",
       "6814                          1.790179e-04                  0.175045   \n",
       "6815                          2.370237e-04                  0.181324   \n",
       "6816                          0.000000e+00                  0.269521   \n",
       "6817                          2.110211e-04                  0.213392   \n",
       "6818                          5.900000e+08                  0.220766   \n",
       "\n",
       "       Persistent EPS in the Last Four Seasons   Net Value Growth Rate  \\\n",
       "0                                     0.169141                0.000327   \n",
       "1                                     0.208944                0.000443   \n",
       "2                                     0.180581                0.000396   \n",
       "3                                     0.193722                0.000382   \n",
       "4                                     0.212537                0.000439   \n",
       "...                                        ...                     ...   \n",
       "6814                                  0.216602                0.000450   \n",
       "6815                                  0.216697                0.000445   \n",
       "6816                                  0.210929                0.000435   \n",
       "6817                                  0.228326                0.000529   \n",
       "6818                                  0.227758                0.000519   \n",
       "\n",
       "       Interest Expense Ratio   Total debt/Total net worth  \\\n",
       "0                    0.629951                     0.021266   \n",
       "1                    0.635172                     0.012502   \n",
       "2                    0.629631                     0.021248   \n",
       "3                    0.630228                     0.009572   \n",
       "4                    0.636055                     0.005150   \n",
       "...                       ...                          ...   \n",
       "6814                 0.631415                     0.006655   \n",
       "6815                 0.631489                     0.004623   \n",
       "6816                 0.630612                     0.001392   \n",
       "6817                 0.630731                     0.003816   \n",
       "6818                 0.630618                     0.000461   \n",
       "\n",
       "       Borrowing dependency   Net profit before tax/Paid-in capital  \\\n",
       "0                  0.390284                                0.137757   \n",
       "1                  0.376760                                0.168962   \n",
       "2                  0.379093                                0.148036   \n",
       "3                  0.379743                                0.147561   \n",
       "4                  0.375025                                0.167461   \n",
       "...                     ...                                     ...   \n",
       "6814               0.373823                                0.171111   \n",
       "6815               0.372505                                0.171805   \n",
       "6816               0.369637                                0.172287   \n",
       "6817               0.369649                                0.182498   \n",
       "6818               0.370049                                0.179911   \n",
       "\n",
       "       Fixed Assets Turnover Frequency   Cash/Total Assets  \\\n",
       "0                         1.165007e-04            0.004094   \n",
       "1                         7.190000e+08            0.014948   \n",
       "2                         2.650000e+09            0.000991   \n",
       "3                         9.150000e+09            0.018851   \n",
       "4                         2.935211e-04            0.014161   \n",
       "...                                ...                 ...   \n",
       "6814                      1.429781e-04            0.099481   \n",
       "6815                      6.051982e-04            0.080337   \n",
       "6816                      1.024298e-03            0.412885   \n",
       "6817                      2.330013e-04            0.112238   \n",
       "6818                      2.995731e-04            0.238147   \n",
       "\n",
       "       Net Income to Total Assets   Net Income to Stockholder's Equity  \\\n",
       "0                        0.716845                             0.827890   \n",
       "1                        0.795297                             0.839969   \n",
       "2                        0.774670                             0.836774   \n",
       "3                        0.739555                             0.834697   \n",
       "4                        0.795016                             0.839973   \n",
       "...                           ...                                  ...   \n",
       "6814                     0.799927                             0.840359   \n",
       "6815                     0.799748                             0.840306   \n",
       "6816                     0.797778                             0.840138   \n",
       "6817                     0.811808                             0.841084   \n",
       "6818                     0.815956                             0.841019   \n",
       "\n",
       "       Degree of Financial Leverage (DFL)   Equity to Liability  Bankrupt?  \n",
       "0                                0.026601              0.016469          1  \n",
       "1                                0.264577              0.020794          1  \n",
       "2                                0.026555              0.016474          1  \n",
       "3                                0.026697              0.023982          1  \n",
       "4                                0.024752              0.035490          1  \n",
       "...                                   ...                   ...        ...  \n",
       "6814                             0.027064              0.029890          0  \n",
       "6815                             0.027009              0.038284          0  \n",
       "6816                             0.026791              0.097649          0  \n",
       "6817                             0.026822              0.044009          0  \n",
       "6818                             0.026793              0.233902          0  \n",
       "\n",
       "[6819 rows x 16 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank = bank[features]\n",
    "bank"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41dd3514",
   "metadata": {},
   "source": [
    "### 3. Descriptive Analysis\n",
    "Now that we have a more workable number of features, let's take a look at their stats"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "606eb3e4",
   "metadata": {},
   "source": [
    "**3.1. Target Variable**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "003c0769",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYsAAAEGCAYAAACUzrmNAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAS7UlEQVR4nO3df6zd9X3f8ecLOwGPxivMhnk2qelmtTO0kHHlOY1WNWEqHutq0o7K6TKsDtUTYlVbbZpgf2xpO2/5Y6sWqoDmNQl2mpZ5yTK8FroitzTb6sS9JDRgfggrZGDZxQ5pFCdK3Np974/zsXJiH9/Pgd5z7jX3+ZCOvt/v+3w/3/u+yPaLz/f7Pd+TqkKSpLlcstANSJIWP8NCktRlWEiSugwLSVKXYSFJ6lq+0A1MyqpVq2r9+vUL3YYkXVSeeOKJL1XV6nPrb9iwWL9+PbOzswvdhiRdVJL8v1F1T0NJkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK63rCf4P6LeuSRry90C1qEbr318oVuQVoQziwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkromGhZJvjPJx5M8l+TZJG9PcmWSx5K80JZXDO1/b5LDSZ5PcstQ/aYkT7X37kuSSfYtSfp2k55ZfAD47ar6XuAG4FngHmB/VW0A9rdtkmwEtgHXAVuA+5Msa8d5ANgBbGivLRPuW5I0ZGJhkWQl8IPAhwCq6k+r6ivAVmB32203cFtb3wo8VFWnqupF4DCwKckaYGVVHaiqAvYMjZEkTcEkZxbfDZwAPpLkc0l+NcnlwNVVdQygLa9q+68FXh4af6TV1rb1c+uSpCmZZFgsB/4W8EBVvQ34Ou2U0wWMug5Rc9TPP0CyI8lsktkTJ0681n4lSRcwybA4Ahypqs+07Y8zCI9X2qkl2vL40P7XDI1fBxxt9XUj6uepql1VNVNVM6tXr563X0SSlrqJhUVV/THwcpLvaaWbgWeAfcD2VtsOPNzW9wHbklya5FoGF7IPtlNVJ5NsbndB3TE0RpI0BcsnfPyfAT6W5M3AF4CfYhBQe5PcCbwE3A5QVYeS7GUQKKeBu6vqTDvOXcCDwArg0faSJE3JRMOiqp4EZka8dfMF9t8J7BxRnwWun9fmJElj8xPckqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKlromGR5ItJnkryZJLZVrsyyWNJXmjLK4b2vzfJ4STPJ7llqH5TO87hJPclyST7liR9u2nMLN5ZVTdW1UzbvgfYX1UbgP1tmyQbgW3AdcAW4P4ky9qYB4AdwIb22jKFviVJzUKchtoK7G7ru4HbhuoPVdWpqnoROAxsSrIGWFlVB6qqgD1DYyRJUzDpsCjgd5I8kWRHq11dVccA2vKqVl8LvDw09kirrW3r59bPk2RHktkksydOnJjHX0OSlrblEz7+O6rqaJKrgMeSPDfHvqOuQ9Qc9fOLVbuAXQAzMzMj95EkvXYTnVlU1dG2PA58EtgEvNJOLdGWx9vuR4BrhoavA462+roRdUnSlEwsLJJcnuQtZ9eBHwaeBvYB29tu24GH2/o+YFuSS5Ncy+BC9sF2qupkks3tLqg7hsZIkqZgkqehrgY+2e5yXQ78elX9dpI/BPYmuRN4CbgdoKoOJdkLPAOcBu6uqjPtWHcBDwIrgEfbS5I0JRMLi6r6AnDDiPqrwM0XGLMT2DmiPgtcP989SpLG4ye4JUldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSuiYeFkmWJflckt9s21cmeSzJC215xdC+9yY5nOT5JLcM1W9K8lR7774kmXTfkqRvmcbM4meBZ4e27wH2V9UGYH/bJslGYBtwHbAFuD/JsjbmAWAHsKG9tkyhb0lSM9GwSLIO+PvArw6VtwK72/pu4Lah+kNVdaqqXgQOA5uSrAFWVtWBqipgz9AYSdIUTHpm8Z+Afwn8+VDt6qo6BtCWV7X6WuDlof2OtNratn5u/TxJdiSZTTJ74sSJefkFJEkTDIskPwIcr6onxh0yolZz1M8vVu2qqpmqmlm9evWYP1aS1LN8gsd+B/CjSW4FLgNWJvk14JUka6rqWDvFdLztfwS4Zmj8OuBoq68bUZckTcnEZhZVdW9Vrauq9QwuXP9uVb0X2Adsb7ttBx5u6/uAbUkuTXItgwvZB9upqpNJNre7oO4YGiNJmoJJziwu5P3A3iR3Ai8BtwNU1aEke4FngNPA3VV1po25C3gQWAE82l6SpCmZSlhU1ePA4239VeDmC+y3E9g5oj4LXD+5DiVJcxnrNFSS/ePUJElvTHPOLJJcBvwlYFX7pPXZO5NWAn9twr1JkhaJ3mmofwr8HINgeIJvhcVXgQ9Ori1J0mIyZ1hU1QeADyT5mar6lSn1JElaZMa6wF1Vv5LkB4D1w2Oqas+E+pIkLSJjhUWSjwJ/HXgSOHs769nnNEmS3uDGvXV2BtjYHuQnSVpixv0E99PAX51kI5KkxWvcmcUq4JkkB4FTZ4tV9aMT6UqStKiMGxbvm2QTkqTFbdy7oX5/0o1Ikhavce+GOsm3vkPizcCbgK9X1cpJNSZJWjzGnVm8ZXg7yW3Apkk0JElafF7X91lU1f8A3jW/rUiSFqtxT0P92NDmJQw+d+FnLiRpiRj3bqh/MLR+GvgisHXeu5EkLUrjXrP4qUk3IklavMb98qN1ST6Z5HiSV5J8Ism6STcnSVocxr3A/RFgH4PvtVgL/M9WkyQtAeOGxeqq+khVnW6vB4HVE+xLkrSIjBsWX0ry3iTL2uu9wKuTbEyStHiMGxb/BPgJ4I+BY8A/BLzoLUlLxLhh8UvA9qpaXVVXMQiP9801IMllSQ4m+aMkh5L8QqtfmeSxJC+05RVDY+5NcjjJ80luGarflOSp9t59STLqZ0qSJmPcsPj+qvqTsxtV9WXgbZ0xp4B3VdUNwI3AliSbgXuA/VW1AdjftkmyEdgGXAdsAe5Psqwd6wFgB7ChvbaM2bckaR6MGxaXnDMDuJLOZzRq4Gtt803tVQw+zLe71XcDt7X1rcBDVXWqql4EDgObkqwBVlbVgfZNfXuGxkiSpmDcT3D/R+APknycwT/4PwHs7A1qM4MngL8BfLCqPpPk6qo6BlBVx5Jc1XZfC3x6aPiRVvuztn5uXZI0JeN+gntPklkGDw8M8GNV9cwY484ANyb5TuCTSa6fY/dR1yFqjvr5B0h2MDhdxVvf+tZee5KkMY07s6CFQzcgLjD2K0keZ3Ct4ZUka9qsYg1wvO12BLhmaNg64GirrxtRH/VzdgG7AGZmZnzQoSTNk9f1iPJxJFndZhQkWQH8XeA5Bp8E39522w483Nb3AduSXJrkWgYXsg+2U1Ynk2xud0HdMTRGkjQFY88sXoc1wO523eISYG9V/WaSA8DeJHcCLwG3A1TVoSR7GcxeTgN3t9NYAHcBDwIrgEfbS5I0JRMLi6r6PCNur62qV4GbLzBmJyMunFfVLDDX9Q5J0gRN7DSUJOmNw7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqmlhYJLkmye8leTbJoSQ/2+pXJnksyQttecXQmHuTHE7yfJJbhuo3JXmqvXdfkkyqb0nS+SY5szgN/POq+pvAZuDuJBuBe4D9VbUB2N+2ae9tA64DtgD3J1nWjvUAsAPY0F5bJti3JOkcEwuLqjpWVZ9t6yeBZ4G1wFZgd9ttN3BbW98KPFRVp6rqReAwsCnJGmBlVR2oqgL2DI2RJE3BVK5ZJFkPvA34DHB1VR2DQaAAV7Xd1gIvDw070mpr2/q59VE/Z0eS2SSzJ06cmNffQZKWsomHRZLvAD4B/FxVfXWuXUfUao76+cWqXVU1U1Uzq1evfu3NSpJGmmhYJHkTg6D4WFX991Z+pZ1aoi2Pt/oR4Jqh4euAo62+bkRdkjQlk7wbKsCHgGer6peH3toHbG/r24GHh+rbklya5FoGF7IPtlNVJ5Nsbse8Y2iMJGkKlk/w2O8A/jHwVJInW+1fAe8H9ia5E3gJuB2gqg4l2Qs8w+BOqrur6kwbdxfwILACeLS9JElTMrGwqKr/w+jrDQA3X2DMTmDniPoscP38dSdJei38BLckqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXYaFJKnLsJAkdRkWkqQuw0KS1GVYSJK6DAtJUpdhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVLXxMIiyYeTHE/y9FDtyiSPJXmhLa8Yeu/eJIeTPJ/klqH6TUmeau/dlyST6lmSNNokZxYPAlvOqd0D7K+qDcD+tk2SjcA24Lo25v4ky9qYB4AdwIb2OveYkqQJm1hYVNWngC+fU94K7G7ru4HbhuoPVdWpqnoROAxsSrIGWFlVB6qqgD1DYyRJUzLtaxZXV9UxgLa8qtXXAi8P7Xek1da29XPrIyXZkWQ2yeyJEyfmtXFJWsoWywXuUdchao76SFW1q6pmqmpm9erV89acJC110w6LV9qpJdryeKsfAa4Z2m8dcLTV142oS5KmaNphsQ/Y3ta3Aw8P1bcluTTJtQwuZB9sp6pOJtnc7oK6Y2iMJGlKlk/qwEl+A/ghYFWSI8C/Ad4P7E1yJ/AScDtAVR1Kshd4BjgN3F1VZ9qh7mJwZ9UK4NH2kiRN0cTCoqrec4G3br7A/juBnSPqs8D189iaJOk1WiwXuCVJi5hhIUnqMiwkSV2GhSSpy7CQJHUZFpKkLsNCktRlWEiSugwLSVKXYSFJ6jIsJEldhoUkqcuwkCR1GRaSpC7DQpLUZVhIkroMC0lSl2EhSeoyLCRJXRP7Dm5Jk/P1Rx5Z6Ba0CF1+660TO7YzC0lSl2EhSeoyLCRJXRdNWCTZkuT5JIeT3LPQ/UjSUnJRhEWSZcAHgb8HbATek2TjwnYlSUvHRREWwCbgcFV9oar+FHgI2LrAPUnSknGx3Dq7Fnh5aPsI8LfP3SnJDmBH2/xakuen0NtSsAr40kI3IV2Afz7n13eNKl4sYZERtTqvULUL2DX5dpaWJLNVNbPQfUij+OdzOi6W01BHgGuGttcBRxeoF0laci6WsPhDYEOSa5O8GdgG7FvgniRpybgoTkNV1ekk/wz4X8Ay4MNVdWiB21pKPLWnxcw/n1OQqvNO/UuS9G0ultNQkqQFZFhIkroMC83Jx6xosUry4STHkzy90L0sBYaFLsjHrGiRexDYstBNLBWGhebiY1a0aFXVp4AvL3QfS4VhobmMeszK2gXqRdICMiw0l7EesyLpjc+w0Fx8zIokwLDQ3HzMiiTAsNAcquo0cPYxK88Ce33MihaLJL8BHAC+J8mRJHcudE9vZD7uQ5LU5cxCktRlWEiSugwLSVKXYSFJ6jIsJEldhoV0jiRnkjyZ5I+SfDbJD/wFjvV4kpn57K8dd32SnxzafneSzyd5Lsl/STLq0/fS62ZYSOf7RlXdWFU3APcC/36SP6w93fe1Wg/85ND2q8A7GDwdeGNbl+aNYSHNbSXwJwBJviPJ/jbbeCrJ1lZfn+TZ9n/0h5L8TpIVwwdJckmS3Un+bdv+WpJfTPIZ4O1JvphkVXtvJsnjbf19ST6a5HeTvJDkp9sh3w/8nTYD+vmq+lRVnWTw7K7LgG9O/j+NlpLlC92AtAitSPIkg3901wDvavVvAu+uqq+2f9g/neTs4082AO+pqp9Oshf4ceDX2nvLgY8BT1fVzla7vG3/a4DOWaPvBza3MZ9L8lvAPcC/qKofOWffXwS+UFWzr+P3li7IsJDO942quhEgyduBPUmuZ/AU3n+X5AeBP2fwuPar25gXq+rJtv4Eg9NEZ/1nBo9K2TlUOwN8Ysx+Hq6qbwDfSPJ7DL5n5Cvn7pTkBuDdwLxfI5E8DSXNoaoOAKuA1cA/asubWpi8wmD2AXBqaNgZvv1/xP4AeGeSy4Zq36yqM0Pbp/nW38fh/eD8x8Jf6Bk93wf8flV5CkrzzrCQ5pDke4FlDC4g/2XgeFX9WZJ3At815mE+BDwC/LckF5rNfxG4qa3/+DnvbU1yWZK/AvwQg6cBnwTecs5+/7f9LGneGRbS+Va0C8dPAv8V2N5mAR8DZpLMMphlPDfuAavql4HPAh9NMurv3S8AH0jyvxnMTIYdBH4L+DTwS1V1FPg8cLrd3vvzbb/vA3543J6k18KnzkqLWJL3AV+rqv+w0L1oaXNmIUnqcmYhSepyZiFJ6jIsJEldhoUkqcuwkCR1GRaSpK7/D595CCWhTw0ZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Bankrupt?\n",
       "0    6599\n",
       "1     220\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns.countplot(data=bank, x='Bankrupt?', palette='bwr')\n",
    "plt.show()\n",
    "\n",
    "bank.groupby('Bankrupt?').size()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9f2f433",
   "metadata": {},
   "source": [
    "We have highly unbalanced data, this is a problem since the machine learning algorithm could be making prediction based mainly on data majority, that's the reason we got so good results in section 2. In this case we are going and try oversampling the data: making synthetic data out of the smaller sample(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15a1e567",
   "metadata": {},
   "source": [
    "**3.2 Features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0cf23bb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bank.hist(figsize=(20,20), edgecolor='white')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "750eb227",
   "metadata": {},
   "source": [
    "Most of the data is rich on outliers, and in some other the values are located in just one bin. Let's take a closer look at 'Non-industry income and expenditure/revenue'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2408591b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0.302646\n",
       "1       0.303556\n",
       "2       0.302035\n",
       "3       0.303350\n",
       "4       0.303475\n",
       "          ...   \n",
       "6814    0.303510\n",
       "6815    0.303520\n",
       "6816    0.303512\n",
       "6817    0.303498\n",
       "6818    0.313415\n",
       "Name:  Non-industry income and expenditure/revenue, Length: 6819, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bank[' Non-industry income and expenditure/revenue']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "50a8dffe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       (0.3, 0.4]\n",
       "1       (0.3, 0.4]\n",
       "2       (0.3, 0.4]\n",
       "3       (0.3, 0.4]\n",
       "4       (0.3, 0.4]\n",
       "           ...    \n",
       "6814    (0.3, 0.4]\n",
       "6815    (0.3, 0.4]\n",
       "6816    (0.3, 0.4]\n",
       "6817    (0.3, 0.4]\n",
       "6818    (0.3, 0.4]\n",
       "Name:  Non-industry income and expenditure/revenue, Length: 6819, dtype: category\n",
       "Categories (10, interval[float64]): [(-0.001, 0.1] < (0.1, 0.2] < (0.2, 0.3] < (0.3, 0.4] ... (0.6, 0.7] < (0.7, 0.8] < (0.8, 0.9] < (0.9, 1.0]]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.cut(bank[' Non-industry income and expenditure/revenue'], bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "905ad6d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "bins = pd.cut(bank[' Non-industry income and expenditure/revenue'], bins=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d47e8651",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.3, 0.4]       6794\n",
       "(0.2, 0.3]         20\n",
       "(-0.001, 0.1]       2\n",
       "(0.9, 1.0]          1\n",
       "(0.7, 0.8]          1\n",
       "(0.4, 0.5]          1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(bins.to_numpy().reshape(-1)).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "fe037e9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rows with outliers: 6819\n",
      "Rows without outliers: 6631\n",
      "information lost = 188 rows\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "lower = bank[' Non-industry income and expenditure/revenue'] > 0.3025\n",
    "upper = bank[' Non-industry income and expenditure/revenue'] < 0.3045\n",
    "\n",
    "close = bank[lower & upper]\n",
    "print('Rows with outliers: {}'.format(bank.shape[0]))\n",
    "print('Rows without outliers: {}'.format(close.shape[0]))\n",
    "print('information lost = {} rows'.format(bank.shape[0]-close.shape[0]))\n",
    "close[' Non-industry income and expenditure/revenue'].hist(edgecolor='white')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3913bf6d",
   "metadata": {},
   "source": [
    "The distribution does have a normal distribution but is highly influenced by the outliers.\n",
    "Therefore, when analysing the data, will be better to use the median as our analysis tool for central measures. Additionally, When we are building our model, we could try and take this outliers out just to see if we can get a better result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "048ee0c7",
   "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>Non-industry income and expenditure/revenue</th>\n",
       "      <th>Interest-bearing debt interest rate</th>\n",
       "      <th>Net Value Per Share (A)</th>\n",
       "      <th>Persistent EPS in the Last Four Seasons</th>\n",
       "      <th>Net Value Growth Rate</th>\n",
       "      <th>Interest Expense Ratio</th>\n",
       "      <th>Total debt/Total net worth</th>\n",
       "      <th>Borrowing dependency</th>\n",
       "      <th>Net profit before tax/Paid-in capital</th>\n",
       "      <th>Fixed Assets Turnover Frequency</th>\n",
       "      <th>Cash/Total Assets</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Equity to Liability</th>\n",
       "      <th>Bankrupt?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6.819000e+03</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6.819000e+03</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6.819000e+03</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6.819000e+03</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "      <td>6819.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.303623</td>\n",
       "      <td>1.644801e+07</td>\n",
       "      <td>0.190633</td>\n",
       "      <td>0.228813</td>\n",
       "      <td>1.566212e+06</td>\n",
       "      <td>0.630991</td>\n",
       "      <td>4.416337e+06</td>\n",
       "      <td>0.374654</td>\n",
       "      <td>0.182715</td>\n",
       "      <td>1.008596e+09</td>\n",
       "      <td>0.124095</td>\n",
       "      <td>0.807760</td>\n",
       "      <td>0.840402</td>\n",
       "      <td>0.027541</td>\n",
       "      <td>0.047578</td>\n",
       "      <td>0.032263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.011163</td>\n",
       "      <td>1.082750e+08</td>\n",
       "      <td>0.033474</td>\n",
       "      <td>0.033263</td>\n",
       "      <td>1.141594e+08</td>\n",
       "      <td>0.011238</td>\n",
       "      <td>1.684069e+08</td>\n",
       "      <td>0.016286</td>\n",
       "      <td>0.030785</td>\n",
       "      <td>2.477557e+09</td>\n",
       "      <td>0.139251</td>\n",
       "      <td>0.040332</td>\n",
       "      <td>0.014523</td>\n",
       "      <td>0.015668</td>\n",
       "      <td>0.050014</td>\n",
       "      <td>0.176710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.303466</td>\n",
       "      <td>2.030203e-04</td>\n",
       "      <td>0.173613</td>\n",
       "      <td>0.214711</td>\n",
       "      <td>4.409689e-04</td>\n",
       "      <td>0.630612</td>\n",
       "      <td>3.007049e-03</td>\n",
       "      <td>0.370168</td>\n",
       "      <td>0.169376</td>\n",
       "      <td>2.330013e-04</td>\n",
       "      <td>0.033543</td>\n",
       "      <td>0.796750</td>\n",
       "      <td>0.840115</td>\n",
       "      <td>0.026791</td>\n",
       "      <td>0.024477</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.303525</td>\n",
       "      <td>3.210321e-04</td>\n",
       "      <td>0.184400</td>\n",
       "      <td>0.224544</td>\n",
       "      <td>4.619555e-04</td>\n",
       "      <td>0.630698</td>\n",
       "      <td>5.546284e-03</td>\n",
       "      <td>0.372624</td>\n",
       "      <td>0.178456</td>\n",
       "      <td>5.930942e-04</td>\n",
       "      <td>0.074887</td>\n",
       "      <td>0.810619</td>\n",
       "      <td>0.841179</td>\n",
       "      <td>0.026808</td>\n",
       "      <td>0.033798</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.303585</td>\n",
       "      <td>5.325533e-04</td>\n",
       "      <td>0.199570</td>\n",
       "      <td>0.238820</td>\n",
       "      <td>4.993621e-04</td>\n",
       "      <td>0.631125</td>\n",
       "      <td>9.273293e-03</td>\n",
       "      <td>0.376271</td>\n",
       "      <td>0.191607</td>\n",
       "      <td>3.652371e-03</td>\n",
       "      <td>0.161073</td>\n",
       "      <td>0.826455</td>\n",
       "      <td>0.842357</td>\n",
       "      <td>0.026913</td>\n",
       "      <td>0.052838</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.900000e+08</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.330000e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.940000e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9.990000e+09</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Non-industry income and expenditure/revenue  \\\n",
       "count                                   6819.000000   \n",
       "mean                                       0.303623   \n",
       "std                                        0.011163   \n",
       "min                                        0.000000   \n",
       "25%                                        0.303466   \n",
       "50%                                        0.303525   \n",
       "75%                                        0.303585   \n",
       "max                                        1.000000   \n",
       "\n",
       "        Interest-bearing debt interest rate   Net Value Per Share (A)  \\\n",
       "count                          6.819000e+03               6819.000000   \n",
       "mean                           1.644801e+07                  0.190633   \n",
       "std                            1.082750e+08                  0.033474   \n",
       "min                            0.000000e+00                  0.000000   \n",
       "25%                            2.030203e-04                  0.173613   \n",
       "50%                            3.210321e-04                  0.184400   \n",
       "75%                            5.325533e-04                  0.199570   \n",
       "max                            9.900000e+08                  1.000000   \n",
       "\n",
       "        Persistent EPS in the Last Four Seasons   Net Value Growth Rate  \\\n",
       "count                               6819.000000            6.819000e+03   \n",
       "mean                                   0.228813            1.566212e+06   \n",
       "std                                    0.033263            1.141594e+08   \n",
       "min                                    0.000000            0.000000e+00   \n",
       "25%                                    0.214711            4.409689e-04   \n",
       "50%                                    0.224544            4.619555e-04   \n",
       "75%                                    0.238820            4.993621e-04   \n",
       "max                                    1.000000            9.330000e+09   \n",
       "\n",
       "        Interest Expense Ratio   Total debt/Total net worth  \\\n",
       "count              6819.000000                 6.819000e+03   \n",
       "mean                  0.630991                 4.416337e+06   \n",
       "std                   0.011238                 1.684069e+08   \n",
       "min                   0.000000                 0.000000e+00   \n",
       "25%                   0.630612                 3.007049e-03   \n",
       "50%                   0.630698                 5.546284e-03   \n",
       "75%                   0.631125                 9.273293e-03   \n",
       "max                   1.000000                 9.940000e+09   \n",
       "\n",
       "        Borrowing dependency   Net profit before tax/Paid-in capital  \\\n",
       "count            6819.000000                             6819.000000   \n",
       "mean                0.374654                                0.182715   \n",
       "std                 0.016286                                0.030785   \n",
       "min                 0.000000                                0.000000   \n",
       "25%                 0.370168                                0.169376   \n",
       "50%                 0.372624                                0.178456   \n",
       "75%                 0.376271                                0.191607   \n",
       "max                 1.000000                                1.000000   \n",
       "\n",
       "        Fixed Assets Turnover Frequency   Cash/Total Assets  \\\n",
       "count                      6.819000e+03         6819.000000   \n",
       "mean                       1.008596e+09            0.124095   \n",
       "std                        2.477557e+09            0.139251   \n",
       "min                        0.000000e+00            0.000000   \n",
       "25%                        2.330013e-04            0.033543   \n",
       "50%                        5.930942e-04            0.074887   \n",
       "75%                        3.652371e-03            0.161073   \n",
       "max                        9.990000e+09            1.000000   \n",
       "\n",
       "        Net Income to Total Assets   Net Income to Stockholder's Equity  \\\n",
       "count                  6819.000000                          6819.000000   \n",
       "mean                      0.807760                             0.840402   \n",
       "std                       0.040332                             0.014523   \n",
       "min                       0.000000                             0.000000   \n",
       "25%                       0.796750                             0.840115   \n",
       "50%                       0.810619                             0.841179   \n",
       "75%                       0.826455                             0.842357   \n",
       "max                       1.000000                             1.000000   \n",
       "\n",
       "        Degree of Financial Leverage (DFL)   Equity to Liability    Bankrupt?  \n",
       "count                          6819.000000           6819.000000  6819.000000  \n",
       "mean                              0.027541              0.047578     0.032263  \n",
       "std                               0.015668              0.050014     0.176710  \n",
       "min                               0.000000              0.000000     0.000000  \n",
       "25%                               0.026791              0.024477     0.000000  \n",
       "50%                               0.026808              0.033798     0.000000  \n",
       "75%                               0.026913              0.052838     0.000000  \n",
       "max                               1.000000              1.000000     1.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(6819, 16)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display(bank.describe())\n",
    "bank.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a37572fd",
   "metadata": {},
   "source": [
    "**3. 3 Correlations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5ba9581b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14,12))\n",
    "\n",
    "sns.heatmap(bank.corr(), vmin=-1, vmax=1, cmap=sns.diverging_palette(20,220, as_cmap=True), annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30b098c6",
   "metadata": {},
   "source": [
    "We have some interesting correlations. Let's inspect the top 3 and see if we can find any bankruptcy pattern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "74f520d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel=\" Net Income to Stockholder's Equity\", ylabel=' Borrowing dependency'>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fix, ax = plt.subplots(1, 3, figsize=(20,6))\n",
    "\n",
    "sns.scatterplot(data=bank, x=' Net profit before tax/Paid-in capital', y=' Persistent EPS in the Last Four Seasons', hue='Bankrupt?', ax=ax[0])\n",
    "sns.scatterplot(data=bank, x=' Persistent EPS in the Last Four Seasons', y=' Net Value Per Share (A)', hue='Bankrupt?', ax=ax[1])\n",
    "sns.scatterplot(data=bank, x=\" Net Income to Stockholder's Equity\", y=' Borrowing dependency', hue='Bankrupt?', ax=ax[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ce3f15ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6819 entries, 0 to 6818\n",
      "Data columns (total 16 columns):\n",
      " #   Column                                        Non-Null Count  Dtype  \n",
      "---  ------                                        --------------  -----  \n",
      " 0    Non-industry income and expenditure/revenue  6819 non-null   float64\n",
      " 1    Interest-bearing debt interest rate          6819 non-null   float64\n",
      " 2    Net Value Per Share (A)                      6819 non-null   float64\n",
      " 3    Persistent EPS in the Last Four Seasons      6819 non-null   float64\n",
      " 4    Net Value Growth Rate                        6819 non-null   float64\n",
      " 5    Interest Expense Ratio                       6819 non-null   float64\n",
      " 6    Total debt/Total net worth                   6819 non-null   float64\n",
      " 7    Borrowing dependency                         6819 non-null   float64\n",
      " 8    Net profit before tax/Paid-in capital        6819 non-null   float64\n",
      " 9    Fixed Assets Turnover Frequency              6819 non-null   float64\n",
      " 10   Cash/Total Assets                            6819 non-null   float64\n",
      " 11   Net Income to Total Assets                   6819 non-null   float64\n",
      " 12   Net Income to Stockholder's Equity           6819 non-null   float64\n",
      " 13   Degree of Financial Leverage (DFL)           6819 non-null   float64\n",
      " 14   Equity to Liability                          6819 non-null   float64\n",
      " 15  Bankrupt?                                     6819 non-null   int64  \n",
      "dtypes: float64(15), int64(1)\n",
      "memory usage: 852.5 KB\n"
     ]
    }
   ],
   "source": [
    "bank.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2128eb85",
   "metadata": {},
   "source": [
    "We start to see some patterns\n",
    "- companies with a low 'Net profit before tax/Paid-in capital', 'Persistent EPS in the Last Four Seasons' and 'Net Value Per Share (A)' tend to go bankrupt\n",
    "- 'Borrowing dependency' has bankrupt companies distributed through all it's range. But, around 0.4, are located the companies that do not go bankrupt. Having around 0.4 doesn't guarantee to be bankrupt safe since there are a lot of companies that went bankrupt with this index, but having a higher o lower index seems to be critical since there aren't any companies operating with this kind of index. Same goes to \"Net Income to Stockholder's Equity\" but around 0.8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ad0aeeb",
   "metadata": {},
   "source": [
    "### Descriptive Analysis Conclusions\n",
    "\n",
    "- We have highly unbalanced data. Therefore, we are going to try applying **oversampling**\n",
    "- Most of the features have outliers. Median will be a better analysis method and also, taking some outliers out will be a good idea when building the model\n",
    "- companies with a low 'Net profit before tax/Paid-in capital', 'Persistent EPS in the Last Four Seasons' and 'Net Value Per Share (A)' tend to go bankrupt. **A KNN algorithm would yield good results since the clusters are so evident**\n",
    "- 0.4 'Borrowing dependency' is a good indicator to operate but doesn't completely safe you from bankruptcy\n",
    "- 0.8 \"Net Income to Stockholder's Equity\" is a good indicator to operate but doesn't completely safe you from bankruptcy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "064bd157",
   "metadata": {},
   "source": [
    "### 4. Data Analysis\n",
    "Let's compare the median of bankrupt and not bankrupt companies of each feature to further see if we can find a tendency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "18bc2800",
   "metadata": {},
   "outputs": [],
   "source": [
    "central = bank.groupby('Bankrupt?').median().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "103b609d",
   "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>Bankrupt?</th>\n",
       "      <th>Non-industry income and expenditure/revenue</th>\n",
       "      <th>Interest-bearing debt interest rate</th>\n",
       "      <th>Net Value Per Share (A)</th>\n",
       "      <th>Persistent EPS in the Last Four Seasons</th>\n",
       "      <th>Net Value Growth Rate</th>\n",
       "      <th>Interest Expense Ratio</th>\n",
       "      <th>Total debt/Total net worth</th>\n",
       "      <th>Borrowing dependency</th>\n",
       "      <th>Net profit before tax/Paid-in capital</th>\n",
       "      <th>Fixed Assets Turnover Frequency</th>\n",
       "      <th>Cash/Total Assets</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Equity to Liability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.303527</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.185074</td>\n",
       "      <td>0.225111</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.630703</td>\n",
       "      <td>0.005377</td>\n",
       "      <td>0.372474</td>\n",
       "      <td>0.179021</td>\n",
       "      <td>0.000583</td>\n",
       "      <td>0.077684</td>\n",
       "      <td>0.811492</td>\n",
       "      <td>0.841232</td>\n",
       "      <td>0.026810</td>\n",
       "      <td>0.034486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.303347</td>\n",
       "      <td>0.000499</td>\n",
       "      <td>0.158021</td>\n",
       "      <td>0.195944</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>0.630283</td>\n",
       "      <td>0.015723</td>\n",
       "      <td>0.382655</td>\n",
       "      <td>0.154012</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.023755</td>\n",
       "      <td>0.766297</td>\n",
       "      <td>0.836707</td>\n",
       "      <td>0.026689</td>\n",
       "      <td>0.018662</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bankrupt?   Non-industry income and expenditure/revenue  \\\n",
       "0          0                                      0.303527   \n",
       "1          1                                      0.303347   \n",
       "\n",
       "    Interest-bearing debt interest rate   Net Value Per Share (A)  \\\n",
       "0                              0.000317                  0.185074   \n",
       "1                              0.000499                  0.158021   \n",
       "\n",
       "    Persistent EPS in the Last Four Seasons   Net Value Growth Rate  \\\n",
       "0                                  0.225111                0.000463   \n",
       "1                                  0.195944                0.000396   \n",
       "\n",
       "    Interest Expense Ratio   Total debt/Total net worth  \\\n",
       "0                 0.630703                     0.005377   \n",
       "1                 0.630283                     0.015723   \n",
       "\n",
       "    Borrowing dependency   Net profit before tax/Paid-in capital  \\\n",
       "0               0.372474                                0.179021   \n",
       "1               0.382655                                0.154012   \n",
       "\n",
       "    Fixed Assets Turnover Frequency   Cash/Total Assets  \\\n",
       "0                          0.000583            0.077684   \n",
       "1                          0.001225            0.023755   \n",
       "\n",
       "    Net Income to Total Assets   Net Income to Stockholder's Equity  \\\n",
       "0                     0.811492                             0.841232   \n",
       "1                     0.766297                             0.836707   \n",
       "\n",
       "    Degree of Financial Leverage (DFL)   Equity to Liability  \n",
       "0                             0.026810              0.034486  \n",
       "1                             0.026689              0.018662  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "central"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "2072e04d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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>Bankrupt?</th>\n",
       "      <th>Non-industry income and expenditure/revenue</th>\n",
       "      <th>Interest-bearing debt interest rate</th>\n",
       "      <th>Net Value Per Share (A)</th>\n",
       "      <th>Persistent EPS in the Last Four Seasons</th>\n",
       "      <th>Net Value Growth Rate</th>\n",
       "      <th>Interest Expense Ratio</th>\n",
       "      <th>Total debt/Total net worth</th>\n",
       "      <th>Borrowing dependency</th>\n",
       "      <th>Net profit before tax/Paid-in capital</th>\n",
       "      <th>Fixed Assets Turnover Frequency</th>\n",
       "      <th>Cash/Total Assets</th>\n",
       "      <th>Net Income to Total Assets</th>\n",
       "      <th>Net Income to Stockholder's Equity</th>\n",
       "      <th>Degree of Financial Leverage (DFL)</th>\n",
       "      <th>Equity to Liability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.303527</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.185074</td>\n",
       "      <td>0.225111</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.630703</td>\n",
       "      <td>0.005377</td>\n",
       "      <td>0.372474</td>\n",
       "      <td>0.179021</td>\n",
       "      <td>0.000583</td>\n",
       "      <td>0.077684</td>\n",
       "      <td>0.811492</td>\n",
       "      <td>0.841232</td>\n",
       "      <td>0.026810</td>\n",
       "      <td>0.034486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.303347</td>\n",
       "      <td>0.000499</td>\n",
       "      <td>0.158021</td>\n",
       "      <td>0.195944</td>\n",
       "      <td>0.000396</td>\n",
       "      <td>0.630283</td>\n",
       "      <td>0.015723</td>\n",
       "      <td>0.382655</td>\n",
       "      <td>0.154012</td>\n",
       "      <td>0.001225</td>\n",
       "      <td>0.023755</td>\n",
       "      <td>0.766297</td>\n",
       "      <td>0.836707</td>\n",
       "      <td>0.026689</td>\n",
       "      <td>0.018662</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Bankrupt?   Non-industry income and expenditure/revenue  \\\n",
       "0          0                                      0.303527   \n",
       "1          1                                      0.303347   \n",
       "\n",
       "    Interest-bearing debt interest rate   Net Value Per Share (A)  \\\n",
       "0                              0.000317                  0.185074   \n",
       "1                              0.000499                  0.158021   \n",
       "\n",
       "    Persistent EPS in the Last Four Seasons   Net Value Growth Rate  \\\n",
       "0                                  0.225111                0.000463   \n",
       "1                                  0.195944                0.000396   \n",
       "\n",
       "    Interest Expense Ratio   Total debt/Total net worth  \\\n",
       "0                 0.630703                     0.005377   \n",
       "1                 0.630283                     0.015723   \n",
       "\n",
       "    Borrowing dependency   Net profit before tax/Paid-in capital  \\\n",
       "0               0.372474                                0.179021   \n",
       "1               0.382655                                0.154012   \n",
       "\n",
       "    Fixed Assets Turnover Frequency   Cash/Total Assets  \\\n",
       "0                          0.000583            0.077684   \n",
       "1                          0.001225            0.023755   \n",
       "\n",
       "    Net Income to Total Assets   Net Income to Stockholder's Equity  \\\n",
       "0                     0.811492                             0.841232   \n",
       "1                     0.766297                             0.836707   \n",
       "\n",
       "    Degree of Financial Leverage (DFL)   Equity to Liability  \n",
       "0                             0.026810              0.034486  \n",
       "1                             0.026689              0.018662  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(5,3, figsize=(20,20))\n",
    "features = list(central.keys()[1:])\n",
    "ax = ax.ravel()\n",
    "position = 0\n",
    "\n",
    "for i in features:\n",
    "    sns.barplot(data=central, x='Bankrupt?', y=i, ax=ax[position], palette='bwr')\n",
    "    position += 1\n",
    "\n",
    "plt.show()\n",
    "display(central)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a16cd6b5",
   "metadata": {},
   "source": [
    "### Data Analysis Conclusions\n",
    "Let's mention the most evident tendencies:\n",
    "\n",
    "Companies with:\n",
    "- high \"Interest-bearing debt interest rate\" tend to go bankrupt (≈ 0.000499)\n",
    "- high \"Total debt/Total net worth\" tend to go bankrupt (≈ 0.015723)\n",
    "- high \"Fixed Assets Turnover Frequency\" tend to go bankrupt (≈ 0.001225)\n",
    "- low \"Cash/Total Assets\" tend to go bankrupt (≈ 0.023755)\n",
    "- low \"Equity to Liability\" tend to go bankrupt (≈ 0.018662)\n",
    "\n",
    "Also, These indicators should be enough to build a reliable model since the tend is very clear.\n",
    "Let's build our model!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea9cac7c",
   "metadata": {},
   "source": [
    "### 5. Prediction bankruptcy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfacc137",
   "metadata": {},
   "source": [
    "**5.1 KNN**\n",
    "\n",
    "A KNN if we recall section 3 and 4 conclusions, an KNN algorithm with features 'Net profit before tax/Paid-in capital', 'Persistent EPS in the Last Four Seasons', \"Interest-bearing debt interest rate\", \"Total debt/Total net worth\", \"Fixed Assets Turnover Frequency\", \"Cash/Total Assets\" and \"Equity to Liability\" should do the work. let's go and try."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "65dd4238",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = ['Bankrupt?', ' Net profit before tax/Paid-in capital', ' Persistent EPS in the Last Four Seasons', \" Interest-bearing debt interest rate\", \" Total debt/Total net worth\", \" Fixed Assets Turnover Frequency\", \" Cash/Total Assets\", \" Equity to Liability\"]\n",
    "model = bank[model]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "90ed6aa4",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = model.iloc[:, 1:].values\n",
    "y = model.iloc[:,0].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "c19ae6aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.37757334e-01, 1.69140588e-01, 7.25072507e-04, ...,\n",
       "        1.16500653e-04, 4.09440595e-03, 1.64687409e-02],\n",
       "       [1.68961617e-01, 2.08943935e-01, 6.47064706e-04, ...,\n",
       "        7.19000000e+08, 1.49477270e-02, 2.07943063e-02],\n",
       "       [1.48035593e-01, 1.80580505e-01, 7.90079008e-04, ...,\n",
       "        2.65000000e+09, 9.90944451e-04, 1.64741143e-02],\n",
       "       ...,\n",
       "       [1.72287158e-01, 2.10929375e-01, 0.00000000e+00, ...,\n",
       "        1.02429795e-03, 4.12884904e-01, 9.76487375e-02],\n",
       "       [1.82497549e-01, 2.28325612e-01, 2.11021102e-04, ...,\n",
       "        2.33001306e-04, 1.12238224e-01, 4.40094472e-02],\n",
       "       [1.79911017e-01, 2.27758344e-01, 5.90000000e+08, ...,\n",
       "        2.99573108e-04, 2.38147050e-01, 2.33902238e-01]])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "ff75ccb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, ..., 0, 0, 0])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "d33d0723",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best number of neighbors: 7\n",
      "Best training set score: 0.969691044192413\n",
      "Best test set score: 0.9700879765395894\n"
     ]
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)\n",
    "\n",
    "best_n = 0\n",
    "best_training = 0\n",
    "best_test = 0\n",
    "\n",
    "for i in range(1,20):\n",
    "    knn = KNeighborsClassifier(n_neighbors=i)\n",
    "    knn.fit(X_train, y_train)\n",
    "    \n",
    "    training = knn.score(X_train, y_train)\n",
    "    test = knn.score(X_test, y_test)\n",
    "    \n",
    "    if test > best_test:\n",
    "        best_n = i\n",
    "        best_training = training\n",
    "        best_test = test\n",
    "        \n",
    "print('Best number of neighbors: {}'.format(best_n))\n",
    "print('Best training set score: {}'.format(best_training))\n",
    "print('Best test set score: {}'.format(best_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "943d1453",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training set score: 0.97\n",
      "test set score: 0.97\n",
      "Time:  0.2861250799996924\n"
     ]
    }
   ],
   "source": [
    "start = timeit.default_timer()\n",
    "\n",
    "knn = KNeighborsClassifier(n_neighbors=7)\n",
    "knn.fit(X_train, y_train)\n",
    "print('training set score: {:.2f}'.format(knn.score(X_train, y_train)))\n",
    "print('test set score: {:.2f}'.format(knn.score(X_test, y_test)))\n",
    "\n",
    "stop = timeit.default_timer()\n",
    "print('Time: ', stop - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e45b33fd",
   "metadata": {},
   "source": [
    "**5.2 Gradient Boosting Classifer**\n",
    "\n",
    "Here we are going to first apply a more sophisticated classifier on our reduced data and then on the whole dataset. In the end, we compare the three models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba8bd93f",
   "metadata": {},
   "source": [
    "**5.3 Gradient Boosting Classifier, reduced features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "24b72cb3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training set score : 0.97\n",
      "test set score : 0.97\n",
      "Time:  0.3310780719994\n"
     ]
    }
   ],
   "source": [
    "X = model.iloc[:, 1:].values\n",
    "y = model.iloc[:, 0].values\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)\n",
    "\n",
    "start = timeit.default_timer()\n",
    "gbrt = GradientBoostingClassifier(n_estimators=100, random_state=42, max_depth=1).fit(X_train, y_train)\n",
    "\n",
    "print('training set score : {:.2f}'.format(gbrt.score(X_train, y_train)))\n",
    "print('test set score : {:.2f}'.format(gbrt.score(X_test, y_test)))\n",
    "\n",
    "stop = timeit.default_timer()\n",
    "print('Time: ', stop-start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0678b970",
   "metadata": {},
   "source": [
    "**5.4 Gradient Boosting Classifier, all features**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "7f572918",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "traning set score : 0.97\n",
      "test set score : 0.97\n",
      "Time:  3.0825385830003142\n"
     ]
    }
   ],
   "source": [
    "bank = pd.read_csv('./data/data.csv')\n",
    "X = bank.iloc[:,1:].values\n",
    "y = bank.iloc[:,0].values\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)\n",
    "\n",
    "start = timeit.default_timer()\n",
    "gbrt = GradientBoostingClassifier(n_estimators=100, random_state=42, max_depth=1).fit(X_train, y_train)\n",
    "\n",
    "print('traning set score : {:.2f}'.format(gbrt.score(X_train,y_train)))\n",
    "print('test set score : {:.2f}'.format(gbrt.score(X_test,y_test)))\n",
    "\n",
    "stop = timeit.default_timer()\n",
    "print('Time: ',  stop-start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcd9a030",
   "metadata": {},
   "source": [
    "### 6. Conclusions\n",
    "We were able to build three models with a set accuracy of 0.97, while significantly reducing the number of feautures (just 7). This lead us to save running time (from 5.47 seconds to only 0.5)\n",
    "With the reduced features, we were also able to describe how a company might go bankrupt or not, explaining the model better. The features conclusiones were:\n",
    "\n",
    "Companies with:\n",
    "\n",
    "- high \"Interest-bearing debt interest rate\" tend to go bankrupt (≈ 0.000499)\n",
    "- high \"Total debt/Total net worth\" tend to go bankrupt (≈ 0.015723)\n",
    "- high \"Fixed Assets Turnover Frequency\" tend to go bankrupt (≈ 0.001225)\n",
    "- low \"Cash/Total Assets\" tend to go bankrupt (≈ 0.023755)\n",
    "- low \"Equity to Liability\" tend to go bankrupt (≈ 0.018662)\n",
    "- companies with a low 'Net profit before tax/Paid-in capital', 'Persistent EPS in the Last Four Seasons' and 'Net Value Per Share (A)' tend to go bankrupt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c402c12",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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