Created on Cognitive Class Labs

3.4_notebook_quizz_objects.ipynb

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    "You will need the class Car for the next exercises. The class Car has four data attributes: make, model, colour and number of owners (owner_number). The method <code> car_info() </code>  prints out the data attributes and the method <code>sell()</code> increments the number of owners. "
   ]
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   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Car(object):\n",
    "    def __init__(self,make,model,color):\n",
    "        self.make=make;\n",
    "        self.model=model;\n",
    "        self.color=color;\n",
    "        self.owner_number=0 \n",
    "    def car_info(self):\n",
    "        print(\"make: \",self.make)\n",
    "        print(\"model:\", self.model)\n",
    "        print(\"color:\",self.color)\n",
    "        print(\"number of owners:\",self.owner_number)\n",
    "    def sell(self):\n",
    "        self.owner_number=self.owner_number+1"
   ]
  },
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   "source": [
    "<h3> Create a Car object </h3>"
   ]
  },
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   "source": [
    "Create a <code> Car </code> object my_car with the given data attributes: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_car = Car('BMW','M3','red')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Data Attributes </h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the method car_info() to print out the data attributes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "jupyter": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "make:  BMW\n",
      "model: M3\n",
      "color: red\n",
      "number of owners: 0\n"
     ]
    }
   ],
   "source": [
    "my_car.car_info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Methods  </h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call the method <code> sell() </code> in the loop, then call the method <code> car_info()</code> again "
   ]
  },
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   "execution_count": 12,
   "metadata": {
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   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "sell() takes 1 positional argument but 2 were given",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-12-fcaf42385dd1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0mmy_car\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: sell() takes 1 positional argument but 2 were given"
     ]
    }
   ],
   "source": [
    "for i in range(5):\n",
    "    my_car.sell(i)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<small>Copyright &copy; 2018 IBM Cognitive Class. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license/).</small>"
   ]
  }
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