Mining-Away/dwarves/Mining_HQ.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Modules\n",
    "The dwarves!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import digger, gunner, scout \n",
    "import pandas as pd\n",
    "import numpy as np\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pre-Processing\n",
    "This segment is a demonstration on how the data cleaning process on the acquired datasets was handled"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Game Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Rank                           Name     Genre ESRB_Rating Platform  \\\n",
      "0   1.0                     Wii Sports    Sports           E      Wii   \n",
      "1   2.0              Super Mario Bros.  Platform         NaN      NES   \n",
      "2   3.0                 Mario Kart Wii    Racing           E      Wii   \n",
      "3   4.0  PlayerUnknown's Battlegrounds   Shooter         NaN       PC   \n",
      "4   5.0              Wii Sports Resort    Sports           E      Wii   \n",
      "\n",
      "          Publisher         Developer  Critic_Score  User_Score  \\\n",
      "0          Nintendo      Nintendo EAD           7.7         NaN   \n",
      "1          Nintendo      Nintendo EAD          10.0         NaN   \n",
      "2          Nintendo      Nintendo EAD           8.2         9.1   \n",
      "3  PUBG Corporation  PUBG Corporation           NaN         NaN   \n",
      "4          Nintendo      Nintendo EAD           8.0         8.8   \n",
      "\n",
      "   Total_Shipped  Global_Sales  NA_Sales  PAL_Sales  JP_Sales  Other_Sales  \\\n",
      "0          82.86           NaN       NaN        NaN       NaN          NaN   \n",
      "1          40.24           NaN       NaN        NaN       NaN          NaN   \n",
      "2          37.14           NaN       NaN        NaN       NaN          NaN   \n",
      "3          36.60           NaN       NaN        NaN       NaN          NaN   \n",
      "4          33.09           NaN       NaN        NaN       NaN          NaN   \n",
      "\n",
      "     Year Console Review  Score GameName  \n",
      "0  2006.0     NaN    NaN    NaN      NaN  \n",
      "1  1985.0     NaN    NaN    NaN      NaN  \n",
      "2  2008.0     NaN    NaN    NaN      NaN  \n",
      "3  2017.0     NaN    NaN    NaN      NaN  \n",
      "4  2009.0     NaN    NaN    NaN      NaN  \n"
     ]
    }
   ],
   "source": [
    "\n",
    "games_review = pd.read_csv(\"../datasets/videogames/Games.xls\")\n",
    "games_sales = pd.read_csv(\"../datasets/videogames/vgsales-12-4-2019-short.csv\")\n",
    "\n",
    "games_review_phase1 = digger.slice_column(games_review, \"GameName\", \"Review\")\n",
    "games_review_final = digger.slice_column(games_review, \"GameName\", \"(Import)\")\n",
    "\n",
    "games_merged_dat = digger.write_joined_df(games_sales, games_review_final)\n",
    "\n",
    "# Acquisition of Merged dataset\n",
    "print(games_merged_dat.head(5))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Crime Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "crime_CA = pd.read_excel(\"../datasets/crime/clean_crime_canada_dataset.xlsx\")\n",
    "\n",
    "crime_US = pd.read_csv(\"../datasets/crime/report.csv\")\n",
    "\n",
    "NA_col_list = [\n",
    "    \"JP_Sales\",\n",
    "    \"Other_Sales\",\n",
    "    \"Global_Sales\",\n",
    "    \"GameName\",\n",
    "    \"Review\",\n",
    "    \"Console\",\n",
    "    \"Score\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "report_year            2829\n",
      "agency_code            2829\n",
      "agency_jurisdiction    2829\n",
      "population             2829\n",
      "violent_crimes         2829\n",
      "homicides              2829\n",
      "rapes                  2829\n",
      "assaults               2829\n",
      "robberies              2829\n",
      "months_reported        2829\n",
      "crimes_percapita       2829\n",
      "homicides_percapita    2829\n",
      "rapes_percapita        2829\n",
      "assaults_percapita     2829\n",
      "robberies_percapita    2829\n",
      "sum_violence           2829\n",
      "dtype: int64\n",
      "year             4664\n",
      "location         4664\n",
      "type_of_crime    4664\n",
      "incidents        4664\n",
      "rate_per_100k    4664\n",
      "incident_sum     4664\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(crime_US.isnull().count())\n",
    "print(crime_CA.isnull().count())\n",
    "\n",
    "year_interval = gunner.year_interval(crime_US, crime_CA, \"report_year\", \"year\")\n",
    "\n",
    "year_max = year_interval[0]\n",
    "year_min = year_interval[1]\n",
    "\n",
    "crime_intersect = gunner.intersect_by_year(crime_US, crime_CA, \"report_year\", \"year\")\n",
    "\n",
    "crime_US_intersect = crime_intersect[0]\n",
    "crime_CA_intersect = crime_intersect[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "games_merged_dat = gunner.drop_kick(NA_col_list, games_merged_dat)\n",
    "games_merged_dat.to_csv(\"../datasets/videogames/games_merged.csv\", index=False)\n",
    "\n",
    "sale_tri_split = gunner.trisect_by_year(games_merged_dat, \"Year\", year_interval)\n",
    "\n",
    "games_sales_split_pre = sale_tri_split[0]\n",
    "games_sales_split_dur = sale_tri_split[1]\n",
    "games_sales_split_pos = sale_tri_split[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acquired Datasets:\n",
      "\n",
      "    Rank                                Name         Genre ESRB_Rating  \\\n",
      "1    2.0                   Super Mario Bros.      Platform         NaN   \n",
      "5    6.0  Pokemon Red / Green / Blue Version  Role-Playing           E   \n",
      "7    8.0                              Tetris        Puzzle           E   \n",
      "10  11.0                           Duck Hunt       Shooter         NaN   \n",
      "18  19.0                   Super Mario World      Platform           E   \n",
      "\n",
      "   Platform Publisher              Developer  Critic_Score  User_Score  \\\n",
      "1       NES  Nintendo           Nintendo EAD          10.0         NaN   \n",
      "5        GB  Nintendo             Game Freak           9.4         NaN   \n",
      "7        GB  Nintendo  Bullet Proof Software           NaN         NaN   \n",
      "10      NES  Nintendo          Nintendo R&D1           NaN         NaN   \n",
      "18     SNES  Nintendo           Nintendo EAD           8.5         NaN   \n",
      "\n",
      "    Total_Shipped  NA_Sales  PAL_Sales    Year  \n",
      "1           40.24       NaN        NaN  1985.0  \n",
      "5           31.38       NaN        NaN  1998.0  \n",
      "7           30.26       NaN        NaN  1989.0  \n",
      "10          28.31       NaN        NaN  1985.0  \n",
      "18          20.61       NaN        NaN  1991.0      Rank                       Name     Genre ESRB_Rating Platform Publisher  \\\n",
      "0   1.0                 Wii Sports    Sports           E      Wii  Nintendo   \n",
      "2   3.0             Mario Kart Wii    Racing           E      Wii  Nintendo   \n",
      "4   5.0          Wii Sports Resort    Sports           E      Wii  Nintendo   \n",
      "6   7.0      New Super Mario Bros.  Platform           E       DS  Nintendo   \n",
      "8   9.0  New Super Mario Bros. Wii  Platform           E      Wii  Nintendo   \n",
      "\n",
      "      Developer  Critic_Score  User_Score  Total_Shipped  NA_Sales  PAL_Sales  \\\n",
      "0  Nintendo EAD           7.7         NaN          82.86       NaN        NaN   \n",
      "2  Nintendo EAD           8.2         9.1          37.14       NaN        NaN   \n",
      "4  Nintendo EAD           8.0         8.8          33.09       NaN        NaN   \n",
      "6  Nintendo EAD           9.1         8.1          30.80       NaN        NaN   \n",
      "8  Nintendo EAD           8.6         9.2          30.22       NaN        NaN   \n",
      "\n",
      "     Year  \n",
      "0  2006.0  \n",
      "2  2008.0  \n",
      "4  2009.0  \n",
      "6  2006.0  \n",
      "8  2009.0       Rank                           Name             Genre ESRB_Rating  \\\n",
      "3    4.0  PlayerUnknown's Battlegrounds           Shooter         NaN   \n",
      "31  32.0               Pokemon Sun/Moon      Role-Playing           E   \n",
      "35  36.0            Mario Kart 8 Deluxe            Racing           E   \n",
      "45  46.0          Red Dead Redemption 2  Action-Adventure           M   \n",
      "48  49.0            Super Mario Odyssey          Platform         E10   \n",
      "\n",
      "   Platform         Publisher         Developer  Critic_Score  User_Score  \\\n",
      "3        PC  PUBG Corporation  PUBG Corporation           NaN         NaN   \n",
      "31      3DS          Nintendo        Game Freak           9.0         NaN   \n",
      "35       NS          Nintendo      Nintendo EPD           9.3         NaN   \n",
      "45      PS4    Rockstar Games    Rockstar Games           9.8         NaN   \n",
      "48       NS          Nintendo      Nintendo EPD           9.9         NaN   \n",
      "\n",
      "    Total_Shipped  NA_Sales  PAL_Sales    Year  \n",
      "3           36.60       NaN        NaN  2017.0  \n",
      "31          16.14       NaN        NaN  2016.0  \n",
      "35          15.02       NaN        NaN  2017.0  \n",
      "45            NaN      5.26       6.21  2018.0  \n",
      "48          13.76       NaN        NaN  2017.0  \n",
      "Dataset Info:\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12445 entries, 1 to 55771\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           12445 non-null  float64\n",
      " 1   Name           12445 non-null  object \n",
      " 2   Genre          12445 non-null  object \n",
      " 3   ESRB_Rating    2704 non-null   object \n",
      " 4   Platform       12445 non-null  object \n",
      " 5   Publisher      12445 non-null  object \n",
      " 6   Developer      12444 non-null  object \n",
      " 7   Critic_Score   493 non-null    float64\n",
      " 8   User_Score     16 non-null     float64\n",
      " 9   Total_Shipped  243 non-null    float64\n",
      " 10  NA_Sales       1047 non-null   float64\n",
      " 11  PAL_Sales      1086 non-null   float64\n",
      " 12  Year           12445 non-null  float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 1.3+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 37102 entries, 0 to 55763\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           37102 non-null  float64\n",
      " 1   Name           37102 non-null  object \n",
      " 2   Genre          37102 non-null  object \n",
      " 3   ESRB_Rating    18606 non-null  object \n",
      " 4   Platform       37102 non-null  object \n",
      " 5   Publisher      37102 non-null  object \n",
      " 6   Developer      37089 non-null  object \n",
      " 7   Critic_Score   5709 non-null   float64\n",
      " 8   User_Score     212 non-null    float64\n",
      " 9   Total_Shipped  1284 non-null   float64\n",
      " 10  NA_Sales       10610 non-null  float64\n",
      " 11  PAL_Sales      11150 non-null  float64\n",
      " 12  Year           37102 non-null  float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 4.0+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 5266 entries, 3 to 55790\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           5266 non-null   float64\n",
      " 1   Name           5266 non-null   object \n",
      " 2   Genre          5266 non-null   object \n",
      " 3   ESRB_Rating    2213 non-null   object \n",
      " 4   Platform       5266 non-null   object \n",
      " 5   Publisher      5266 non-null   object \n",
      " 6   Developer      5266 non-null   object \n",
      " 7   Critic_Score   330 non-null    float64\n",
      " 8   User_Score     100 non-null    float64\n",
      " 9   Total_Shipped  300 non-null    float64\n",
      " 10  NA_Sales       1301 non-null   float64\n",
      " 11  PAL_Sales      929 non-null    float64\n",
      " 12  Year           5266 non-null   float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 576.0+ KB\n",
      "Dataset Info:\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12445 entries, 1 to 55771\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           12445 non-null  float64\n",
      " 1   Name           12445 non-null  object \n",
      " 2   Genre          12445 non-null  object \n",
      " 3   ESRB_Rating    2704 non-null   object \n",
      " 4   Platform       12445 non-null  object \n",
      " 5   Publisher      12445 non-null  object \n",
      " 6   Developer      12444 non-null  object \n",
      " 7   Critic_Score   493 non-null    float64\n",
      " 8   User_Score     16 non-null     float64\n",
      " 9   Total_Shipped  243 non-null    float64\n",
      " 10  NA_Sales       1047 non-null   float64\n",
      " 11  PAL_Sales      1086 non-null   float64\n",
      " 12  Year           12445 non-null  float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 1.3+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 37102 entries, 0 to 55763\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           37102 non-null  float64\n",
      " 1   Name           37102 non-null  object \n",
      " 2   Genre          37102 non-null  object \n",
      " 3   ESRB_Rating    18606 non-null  object \n",
      " 4   Platform       37102 non-null  object \n",
      " 5   Publisher      37102 non-null  object \n",
      " 6   Developer      37089 non-null  object \n",
      " 7   Critic_Score   5709 non-null   float64\n",
      " 8   User_Score     212 non-null    float64\n",
      " 9   Total_Shipped  1284 non-null   float64\n",
      " 10  NA_Sales       10610 non-null  float64\n",
      " 11  PAL_Sales      11150 non-null  float64\n",
      " 12  Year           37102 non-null  float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 4.0+ MB\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 5266 entries, 3 to 55790\n",
      "Data columns (total 13 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Rank           5266 non-null   float64\n",
      " 1   Name           5266 non-null   object \n",
      " 2   Genre          5266 non-null   object \n",
      " 3   ESRB_Rating    2213 non-null   object \n",
      " 4   Platform       5266 non-null   object \n",
      " 5   Publisher      5266 non-null   object \n",
      " 6   Developer      5266 non-null   object \n",
      " 7   Critic_Score   330 non-null    float64\n",
      " 8   User_Score     100 non-null    float64\n",
      " 9   Total_Shipped  300 non-null    float64\n",
      " 10  NA_Sales       1301 non-null   float64\n",
      " 11  PAL_Sales      929 non-null    float64\n",
      " 12  Year           5266 non-null   float64\n",
      "dtypes: float64(7), object(6)\n",
      "memory usage: 576.0+ KB\n",
      "Yer forsaken Statistical Description:\n",
      "                Rank  Critic_Score  User_Score  Total_Shipped      NA_Sales  \\\n",
      "count  37102.000000   5709.000000  212.000000    1284.000000  10610.000000   \n",
      "mean   25036.476282      7.170047    8.369811       1.786597      0.273487   \n",
      "std    15243.705990      1.433885    1.254125       4.209405      0.512590   \n",
      "min        1.000000      1.000000    2.000000       0.030000      0.000000   \n",
      "25%    11755.250000      6.400000    8.000000       0.200000      0.050000   \n",
      "50%    23875.500000      7.400000    8.600000       0.545000      0.120000   \n",
      "75%    38152.750000      8.200000    9.200000       1.680000      0.290000   \n",
      "max    55764.000000     10.000000   10.000000      82.860000      9.760000   \n",
      "\n",
      "          PAL_Sales          Year  \n",
      "count  11150.000000  37102.000000  \n",
      "mean       0.149162   2008.141852  \n",
      "std        0.380365      4.135877  \n",
      "min        0.000000   2000.000000  \n",
      "25%        0.010000   2005.000000  \n",
      "50%        0.040000   2009.000000  \n",
      "75%        0.140000   2011.000000  \n",
      "max        9.850000   2015.000000  \n",
      "    Rank                                Name         Genre ESRB_Rating  \\\n",
      "1    2.0                   Super Mario Bros.      Platform         NaN   \n",
      "5    6.0  Pokemon Red / Green / Blue Version  Role-Playing           E   \n",
      "7    8.0                              Tetris        Puzzle           E   \n",
      "10  11.0                           Duck Hunt       Shooter         NaN   \n",
      "18  19.0                   Super Mario World      Platform           E   \n",
      "\n",
      "   Platform Publisher              Developer  Critic_Score  User_Score  \\\n",
      "1       NES  Nintendo           Nintendo EAD          10.0         NaN   \n",
      "5        GB  Nintendo             Game Freak           9.4         NaN   \n",
      "7        GB  Nintendo  Bullet Proof Software           NaN         NaN   \n",
      "10      NES  Nintendo          Nintendo R&D1           NaN         NaN   \n",
      "18     SNES  Nintendo           Nintendo EAD           8.5         NaN   \n",
      "\n",
      "    Total_Shipped  NA_Sales  PAL_Sales    Year  \n",
      "1           40.24       NaN        NaN  1985.0  \n",
      "5           31.38       NaN        NaN  1998.0  \n",
      "7           30.26       NaN        NaN  1989.0  \n",
      "10          28.31       NaN        NaN  1985.0  \n",
      "18          20.61       NaN        NaN  1991.0      Rank                       Name     Genre ESRB_Rating Platform Publisher  \\\n",
      "0   1.0                 Wii Sports    Sports           E      Wii  Nintendo   \n",
      "2   3.0             Mario Kart Wii    Racing           E      Wii  Nintendo   \n",
      "4   5.0          Wii Sports Resort    Sports           E      Wii  Nintendo   \n",
      "6   7.0      New Super Mario Bros.  Platform           E       DS  Nintendo   \n",
      "8   9.0  New Super Mario Bros. Wii  Platform           E      Wii  Nintendo   \n",
      "\n",
      "      Developer  Critic_Score  User_Score  Total_Shipped  NA_Sales  PAL_Sales  \\\n",
      "0  Nintendo EAD           7.7         NaN          82.86       NaN        NaN   \n",
      "2  Nintendo EAD           8.2         9.1          37.14       NaN        NaN   \n",
      "4  Nintendo EAD           8.0         8.8          33.09       NaN        NaN   \n",
      "6  Nintendo EAD           9.1         8.1          30.80       NaN        NaN   \n",
      "8  Nintendo EAD           8.6         9.2          30.22       NaN        NaN   \n",
      "\n",
      "     Year  \n",
      "0  2006.0  \n",
      "2  2008.0  \n",
      "4  2009.0  \n",
      "6  2006.0  \n",
      "8  2009.0       Rank                           Name             Genre ESRB_Rating  \\\n",
      "3    4.0  PlayerUnknown's Battlegrounds           Shooter         NaN   \n",
      "31  32.0               Pokemon Sun/Moon      Role-Playing           E   \n",
      "35  36.0            Mario Kart 8 Deluxe            Racing           E   \n",
      "45  46.0          Red Dead Redemption 2  Action-Adventure           M   \n",
      "48  49.0            Super Mario Odyssey          Platform         E10   \n",
      "\n",
      "   Platform         Publisher         Developer  Critic_Score  User_Score  \\\n",
      "3        PC  PUBG Corporation  PUBG Corporation           NaN         NaN   \n",
      "31      3DS          Nintendo        Game Freak           9.0         NaN   \n",
      "35       NS          Nintendo      Nintendo EPD           9.3         NaN   \n",
      "45      PS4    Rockstar Games    Rockstar Games           9.8         NaN   \n",
      "48       NS          Nintendo      Nintendo EPD           9.9         NaN   \n",
      "\n",
      "    Total_Shipped  NA_Sales  PAL_Sales    Year  \n",
      "3           36.60       NaN        NaN  2017.0  \n",
      "31          16.14       NaN        NaN  2016.0  \n",
      "35          15.02       NaN        NaN  2017.0  \n",
      "45            NaN      5.26       6.21  2018.0  \n",
      "48          13.76       NaN        NaN  2017.0  \n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"Acquired Datasets:\\n\")\n",
    "print(sale_tri_split[0].head(5), sale_tri_split[1].head(5), sale_tri_split[2].head(5))\n",
    "\n",
    "print(\"Dataset Info:\\n\")\n",
    "sale_tri_split[0].info()\n",
    "sale_tri_split[1].info()\n",
    "sale_tri_split[2].info()\n",
    "\n",
    "\n",
    "print(\"Dataset Info:\\n\")\n",
    "games_sales_split_pre.info()\n",
    "games_sales_split_dur.info()\n",
    "games_sales_split_pos.info()\n",
    "\n",
    "print(\"Yer forsaken Statistical Description:\\n\", games_sales_split_dur.describe())\n",
    "\n",
    "print(\n",
    "    games_sales_split_pre.head(5),\n",
    "    games_sales_split_dur.head(5),\n",
    "    games_sales_split_pos.head(5),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min:  1.0  max:  10.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8738/2916340334.py:4: DtypeWarning: Columns (1,2,3,4,5,6) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  gammas = pd.read_csv(\"../datasets/videogames/games_merged.csv\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    0.399535\n",
      "1    2.335800\n",
      "2    0.820462\n",
      "3    0.736276\n",
      "4    0.652091\n",
      "5    1.830687\n",
      "6    1.578131\n",
      "7    1.367667\n",
      "8    1.157204\n",
      "9    2.335800\n",
      "Name: Critic_Score_Norm, dtype: float64\n",
      "          Rank                       Name         Genre ESRB_Rating Platform  \\\n",
      "1560    1561.0    Sega Genesis Collection          Misc           T      PSP   \n",
      "3834    3835.0  Muramasa: The Demon Blade  Role-Playing           T      Wii   \n",
      "6341    6342.0                  Fable III  Role-Playing           M       PC   \n",
      "20387  20388.0                    Phalanx       Shooter           E      GBA   \n",
      "2401    2402.0              Excitebike 64        Racing           E      N64   \n",
      "\n",
      "                    Publisher               Developer  Critic_Score  \\\n",
      "1560                     Sega                    Sega           8.3   \n",
      "3834   Ignition Entertainment             Vanillaware           8.0   \n",
      "6341   Microsoft Game Studios        Lionhead Studios           7.0   \n",
      "20387                   Kemco               Zoom Inc.           5.0   \n",
      "2401                 Nintendo  Left Field Productions           8.9   \n",
      "\n",
      "       User_Score  Total_Shipped  NA_Sales  PAL_Sales    Year  \\\n",
      "1560     7.245455          1.446      0.53       0.58  2006.0   \n",
      "3834     9.300000          0.600      0.32       0.13  2009.0   \n",
      "6341     7.080214          0.330      0.11       0.17  2011.0   \n",
      "20387    9.658065          0.030      0.00       0.00  2001.0   \n",
      "2401     8.420000          1.000      0.65       0.15  2000.0   \n",
      "\n",
      "      bin_Critic_Score  bin_value  Critic_Score_Norm  \n",
      "1560              larg        8.5           0.904647  \n",
      "3834              larg        8.5           0.652091  \n",
      "6341              epik        5.5          -0.189763  \n",
      "20387             epik        5.5          -1.873472  \n",
      "2401              larg        8.5           1.409760  \n",
      "  Dissim  |  Entry 1 | Entry 2 | Entry 3 | Entry 4 | Entry 5 |\n",
      "Entry  1  |  0.00000 | 3.78646 | 6.20524 | 7.81351 | 6.19620 |\n",
      "\n",
      "Entry  2  |  3.78646 | 0.00000 | 4.44463 | 9.43138 | 9.13388 |\n",
      "\n",
      "Entry  3  |  6.20524 | 4.44463 | 0.00000 | 10.6589 | 11.7773 |\n",
      "\n",
      "Entry  4  |  7.81351 | 9.43138 | 10.6589 | 0.00000 | 6.23765 |\n",
      "\n",
      "Entry  5  |  6.19620 | 9.13388 | 11.7773 | 6.23765 | 0.00000 |\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Load merged gammas\n",
    "\n",
    "# Required to use binning for cleaning\n",
    "gammas = pd.read_csv(\"../datasets/videogames/games_merged.csv\")\n",
    "labels = [\"smol\", \"epik\", \"larg\"]\n",
    "gammas = digger.slam_dunk(gammas, \"Critic_Score\", labels=labels)\n",
    "\n",
    "# Also need to transform using Z-score (normal distr go brrrr lmao), or min-max\n",
    "# ah, scheiße\n",
    "gammas['Critic_Score_Norm'] = scout.scaling_zscore(gammas, 'Critic_Score')\n",
    "print(gammas['Critic_Score_Norm'].head(10))\n",
    "\n",
    "# Saving all into a file\n",
    "gammas = gammas.dropna(how=\"any\", axis=0)  # nuke them empty poopers\n",
    "gammas.to_csv(\"../datasets/videogames/games_cleanish.csv\", index=False)\n",
    "\n",
    "\n",
    "# Need similarity and dissimialrity, scipy time\n",
    "# Selecting 5 random rows\n",
    "chosen_idx = np.random.choice(len(gammas), replace = False, size = 5)\n",
    "sample_rows = gammas.iloc[chosen_idx]\n",
    "print(sample_rows.head())\n",
    "\n",
    "scout.dissimilarity(sample_rows)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting\n",
    "Engineer.py steps up to the job"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing and setting up environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "from numpy import count_nonzero\n",
    "\n",
    "games_pre = games_sales_split_pre\n",
    "games_dur = games_sales_split_dur\n",
    "games_pos = games_sales_split_pos\n",
    "\n",
    "crime_US = crime_US_intersect\n",
    "crime_CA = crime_CA_intersect\n",
    "\n",
    "custom_params = {\"axes.spines.right\": False, \"axes.spines.top\": False}\n",
    "\n",
    "sns.set_theme(style = 'ticks', rc = custom_params)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Game Sales pre 2000s"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### General Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8738/2832375763.py:2: UserWarning: Ignoring `palette` because no `hue` variable has been assigned.\n",
      "  games_fig_pre = sns.histplot(data = games_pre, x = \"Year\", palette = sns.color_palette(\"flare\"), kde = True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "games_fig_pre = sns.histplot(data = games_pre, x = \"Year\", palette = sns.color_palette(\"flare\"), kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### According to Genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "games_fig2_pre = sns.histplot(data = games_pre, x = \"Year\", hue = \"Genre\", multiple = \"stack\", kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Game Sales during 2000s"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### General Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "games_fig_dur = sns.histplot(data = games_dur, x = \"Year\", kde = True)\n",
    "plt.show()\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### According to Genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "games_fig2_dur = sns.histplot(data = games_dur, x = \"Year\", hue = \"Genre\", multiple = \"stack\", kde = True)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Crime in Canada and US"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "crime_CA_fig = sns.histplot(data = crime_CA, x = \"year\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.xticks(rotation = 90)\n",
    "crime_US_fig = sns.histplot(data = crime_US, x = \"report_year\")\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Integrating violence crimes column into Game sales  \n",
    "- Note: multiplying sales by 1000 because they're reduced by default\n",
    "- to plot later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8738/2268265722.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  games_dur['Violent_US'] = crime_US['violent_crimes']\n",
      "/tmp/ipykernel_8738/2268265722.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  games_dur['NA_Sales'] = games_dur['NA_Sales'].multiply(1000)\n"
     ]
    }
   ],
   "source": [
    "games_dur['Violent_US'] = crime_US['violent_crimes']\n",
    "games_dur['NA_Sales'] = games_dur['NA_Sales'].multiply(1000)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting Sales against Crime with Relplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation = 90)\n",
    "games_violence_US = sns.relplot(data = games_dur, x = 'NA_Sales', y = 'Violent_US')\n",
    "plt.close(1)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Joined Plot and Histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.xticks(rotation = 90)\n",
    "games_crime_dur = sns.jointplot(data = games_dur, x = \"Year\", y = 'Violent_US')\n",
    "plt.close(1)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kmeans\n",
    "This executes the kmeans algorithm on the Critic/User scores and total units shipped for video games"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.27944729305334054\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "19       4\n",
       "20       4\n",
       "21       4\n",
       "24       4\n",
       "25       4\n",
       "        ..\n",
       "55090    6\n",
       "55423    8\n",
       "55490    6\n",
       "55528    6\n",
       "55653    6\n",
       "Name: Kmean_Labels, Length: 6116, dtype: int32"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "from sklearn import metrics\n",
    "gammas_train_kmeans = KMeans(n_clusters=10, random_state=420, n_init=\"auto\").fit(\n",
    "    gammas[[\"Critic_Score\", \"User_Score\", \"Total_Shipped\"]]\n",
    ")\n",
    "gammas_labels = gammas_train_kmeans.labels_\n",
    "\n",
    "silh_score = metrics.silhouette_score(\n",
    "    gammas[[\"Critic_Score\", \"User_Score\", \"Total_Shipped\"]],\n",
    "    gammas_labels,\n",
    "    metric=\"euclidean\",\n",
    ")\n",
    "print(silh_score)\n",
    "gammas[\"Kmean_Labels\"] = gammas_labels\n",
    "gammas[\"Kmean_Labels\"]\n",
    "# print(gammas_train.head())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Splitting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "# gammas = pd.read_csv(\"../datasets/videogames/games_cleanish.csv\")\n",
    "gammas_train, gammas_test = train_test_split(gammas, test_size=0.20, random_state=69)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Naive Bayes\n",
    "Using the classifier on the video game data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of mislabeled points out of a total 1224 points : 56\n"
     ]
    }
   ],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "gnb = GaussianNB()\n",
    "silly_columns = [\"Critic_Score\", \"User_Score\", \"Total_Shipped\"]\n",
    "prediction = gnb.fit(X=gammas_train[silly_columns], y=gammas_train[\"Kmean_Labels\"]).predict(gammas_test[silly_columns])\n",
    "len(prediction)\n",
    "y_test = gammas_test[\"Kmean_Labels\"]\n",
    "len(y_test)\n",
    "print(\"Number of mislabeled points out of a total %d points : %d\"\n",
    "   % (gammas_test.shape[0], (y_test != prediction).sum()))\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# L'Arbre De Decisions\n",
    "\n",
    "Making tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor # Import Decision Tree Classifier\n",
    "from sklearn.model_selection import train_test_split # Import train_test_split function\n",
    "from sklearn import metrics #Import scikit-learn metrics module for accuracy calculation\n",
    "from sklearn import preprocessing\n",
    "from sklearn.compose import make_column_transformer\n",
    "from sklearn.model_selection import cross_val_score\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  Genre  ESRB_Rating  Platform  NA_Sales\n",
      "19               Action            3        17       750\n",
      "20               Action            3        18       742\n",
      "21                 Misc            0         2       747\n",
      "24               Racing            0         0       761\n",
      "25         Role-Playing            0         2       764\n",
      "...                 ...          ...       ...       ...\n",
      "55090           Shooter            3        14         0\n",
      "55423             Music            1        12         0\n",
      "55490            Action            3        12         0\n",
      "55528  Action-Adventure            0        12         0\n",
      "55653      Visual Novel            5        18         0\n",
      "\n",
      "[6116 rows x 4 columns]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_8738/1054103916.py:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  to_be_nodes[\"NA_Sales\"] = le.fit_transform(gammas[\"NA_Sales\"])\n",
      "/tmp/ipykernel_8738/1054103916.py:14: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  to_be_nodes[\"ESRB_Rating\"] = le.fit_transform(gammas[\"ESRB_Rating\"])\n",
      "/tmp/ipykernel_8738/1054103916.py:15: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  to_be_nodes[\"Platform\"] = le.fit_transform(gammas[\"Platform\"])\n"
     ]
    }
   ],
   "source": [
    "# Columnising dataset\n",
    "node_cols = [\"Genre\", \"ESRB_Rating\", \"Platform\"]\n",
    "\n",
    "# Columns to be considered as nodes\n",
    "to_be_nodes = gammas[node_cols]\n",
    "\n",
    "\n",
    "le = preprocessing.LabelEncoder()\n",
    "# Attribute to be predicted\n",
    "predikt_col = le.fit_transform(gammas[\"Genre\"])\n",
    "\n",
    "# to_be_nodes[\"Genre\"] = le.fit_transform(gammas[\"Genre\"])\n",
    "to_be_nodes[\"NA_Sales\"] = le.fit_transform(gammas[\"NA_Sales\"])\n",
    "to_be_nodes[\"ESRB_Rating\"] = le.fit_transform(gammas[\"ESRB_Rating\"])\n",
    "to_be_nodes[\"Platform\"] = le.fit_transform(gammas[\"Platform\"])\n",
    "\n",
    "print(to_be_nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1, 13,  0, ..., 15,  0,  5])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Chopping down trees\n",
    "node_train, node_test, predikt_train, predikt_test = train_test_split(to_be_nodes, predikt_col, test_size = 0.2, random_state =69)\n",
    "predikt_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unknown label type: 'continuous'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[48], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m classifier_obj \u001b[39m=\u001b[39m DecisionTreeClassifier()\n\u001b[0;32m----> 3\u001b[0m classifier_obj \u001b[39m=\u001b[39m classifier_obj\u001b[39m.\u001b[39;49mfit(node_train, predikt_train)\n\u001b[1;32m      5\u001b[0m predikt_result \u001b[39m=\u001b[39m classifier_obj\u001b[39m.\u001b[39mpredict(node_test)\n\u001b[1;32m      7\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mACCURACY FOR MODEL PRE: \u001b[39m\u001b[39m\"\u001b[39m, metrics\u001b[39m.\u001b[39maccuracy_score(predikt_test, predikt_result))\n",
      "File \u001b[0;32m~/bin/anaconda3/envs/jewpidor/lib/python3.10/site-packages/sklearn/tree/_classes.py:889\u001b[0m, in \u001b[0;36mDecisionTreeClassifier.fit\u001b[0;34m(self, X, y, sample_weight, check_input)\u001b[0m\n\u001b[1;32m    859\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mfit\u001b[39m(\u001b[39mself\u001b[39m, X, y, sample_weight\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, check_input\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m):\n\u001b[1;32m    860\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Build a decision tree classifier from the training set (X, y).\u001b[39;00m\n\u001b[1;32m    861\u001b[0m \n\u001b[1;32m    862\u001b[0m \u001b[39m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    886\u001b[0m \u001b[39m        Fitted estimator.\u001b[39;00m\n\u001b[1;32m    887\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 889\u001b[0m     \u001b[39msuper\u001b[39;49m()\u001b[39m.\u001b[39;49mfit(\n\u001b[1;32m    890\u001b[0m         X,\n\u001b[1;32m    891\u001b[0m         y,\n\u001b[1;32m    892\u001b[0m         sample_weight\u001b[39m=\u001b[39;49msample_weight,\n\u001b[1;32m    893\u001b[0m         check_input\u001b[39m=\u001b[39;49mcheck_input,\n\u001b[1;32m    894\u001b[0m     )\n\u001b[1;32m    895\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\n",
      "File \u001b[0;32m~/bin/anaconda3/envs/jewpidor/lib/python3.10/site-packages/sklearn/tree/_classes.py:224\u001b[0m, in \u001b[0;36mBaseDecisionTree.fit\u001b[0;34m(self, X, y, sample_weight, check_input)\u001b[0m\n\u001b[1;32m    221\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mn_outputs_ \u001b[39m=\u001b[39m y\u001b[39m.\u001b[39mshape[\u001b[39m1\u001b[39m]\n\u001b[1;32m    223\u001b[0m \u001b[39mif\u001b[39;00m is_classification:\n\u001b[0;32m--> 224\u001b[0m     check_classification_targets(y)\n\u001b[1;32m    225\u001b[0m     y \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mcopy(y)\n\u001b[1;32m    227\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mclasses_ \u001b[39m=\u001b[39m []\n",
      "File \u001b[0;32m~/bin/anaconda3/envs/jewpidor/lib/python3.10/site-packages/sklearn/utils/multiclass.py:207\u001b[0m, in \u001b[0;36mcheck_classification_targets\u001b[0;34m(y)\u001b[0m\n\u001b[1;32m    199\u001b[0m y_type \u001b[39m=\u001b[39m type_of_target(y, input_name\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39my\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m    200\u001b[0m \u001b[39mif\u001b[39;00m y_type \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m [\n\u001b[1;32m    201\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mbinary\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m    202\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mmulticlass\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    205\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mmultilabel-sequences\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m    206\u001b[0m ]:\n\u001b[0;32m--> 207\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mUnknown label type: \u001b[39m\u001b[39m%r\u001b[39;00m\u001b[39m\"\u001b[39m \u001b[39m%\u001b[39m y_type)\n",
      "\u001b[0;31mValueError\u001b[0m: Unknown label type: 'continuous'"
     ]
    }
   ],
   "source": [
    "classifier_obj = DecisionTreeClassifier()\n",
    "\n",
    "classifier_obj = classifier_obj.fit(node_train, predikt_train)\n",
    "\n",
    "predikt_result = classifier_obj.predict(node_test)\n",
    "\n",
    "print(\"ACCURACY FOR MODEL PRE: \", metrics.accuracy_score(predikt_test, predikt_result))"
   ]
  }
 ],
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