.gitignore

@@ -26,3 +26,4 @@ ipython_config.py
 # Built Visual Studio Code Extensions
 *.vsix
 
+laba

lab_1/laba1.ipynb

@@ -0,0 +1,93 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## просто вывод датасета"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<bound method DataFrame.items of              ID  Price  Levy   Manufacturer    Model  Prod. year   Category  \\\n",
+       "0      45654403  13328  1399          LEXUS   RX 450        2010       Jeep   \n",
+       "1      44731507  16621  1018      CHEVROLET  Equinox        2011       Jeep   \n",
+       "2      45774419   8467     -          HONDA      FIT        2006  Hatchback   \n",
+       "3      45769185   3607   862           FORD   Escape        2011       Jeep   \n",
+       "4      45809263  11726   446          HONDA      FIT        2014  Hatchback   \n",
+       "...         ...    ...   ...            ...      ...         ...        ...   \n",
+       "19232  45798355   8467     -  MERCEDES-BENZ  CLK 200        1999      Coupe   \n",
+       "19233  45778856  15681   831        HYUNDAI   Sonata        2011      Sedan   \n",
+       "19234  45804997  26108   836        HYUNDAI   Tucson        2010       Jeep   \n",
+       "19235  45793526   5331  1288      CHEVROLET  Captiva        2007       Jeep   \n",
+       "19236  45813273    470   753        HYUNDAI   Sonata        2012      Sedan   \n",
+       "\n",
+       "      Leather interior Fuel type Engine volume    Mileage  Cylinders  \\\n",
+       "0                  Yes    Hybrid           3.5  186005 km        6.0   \n",
+       "1                   No    Petrol             3  192000 km        6.0   \n",
+       "2                   No    Petrol           1.3  200000 km        4.0   \n",
+       "3                  Yes    Hybrid           2.5  168966 km        4.0   \n",
+       "4                  Yes    Petrol           1.3   91901 km        4.0   \n",
+       "...                ...       ...           ...        ...        ...   \n",
+       "19232              Yes       CNG     2.0 Turbo  300000 km        4.0   \n",
+       "19233              Yes    Petrol           2.4  161600 km        4.0   \n",
+       "19234              Yes    Diesel             2  116365 km        4.0   \n",
+       "19235              Yes    Diesel             2   51258 km        4.0   \n",
+       "19236              Yes    Hybrid           2.4  186923 km        4.0   \n",
+       "\n",
+       "      Gear box type Drive wheels   Doors             Wheel   Color  Airbags  \n",
+       "0         Automatic          4x4  04-May        Left wheel  Silver       12  \n",
+       "1         Tiptronic          4x4  04-May        Left wheel   Black        8  \n",
+       "2          Variator        Front  04-May  Right-hand drive   Black        2  \n",
+       "3         Automatic          4x4  04-May        Left wheel   White        0  \n",
+       "4         Automatic        Front  04-May        Left wheel  Silver        4  \n",
+       "...             ...          ...     ...               ...     ...      ...  \n",
+       "19232        Manual         Rear  02-Mar        Left wheel  Silver        5  \n",
+       "19233     Tiptronic        Front  04-May        Left wheel     Red        8  \n",
+       "19234     Automatic        Front  04-May        Left wheel    Grey        4  \n",
+       "19235     Automatic        Front  04-May        Left wheel   Black        4  \n",
+       "19236     Automatic        Front  04-May        Left wheel   White       12  \n",
+       "\n",
+       "[19237 rows x 18 columns]>"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "df = pd.read_csv(\"..//static//csv//car_price_prediction.csv\", sep=\",\")\n",
+    "df.items"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "laba",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}