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Created August 8, 2020 15:55
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Created on Skills Network Labs
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"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. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"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"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h3> Create a Car object </h3>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Create a <code> Car </code> object my_car with the given data attributes: "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"ename": "SyntaxError",
"evalue": "invalid syntax (<ipython-input-5-6367d4704ee2>, line 2)",
"output_type": "error",
"traceback": [
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-5-6367d4704ee2>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m model=\"M3\"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
]
}
],
"source": [
"\n",
"make=\"BMW\"\n",
"model=\"M3\"\n",
"color=\"red\"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"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": 7,
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"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 "
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"make: BMW\n",
"model: M3\n",
"color: red\n",
"number of owners: 1\n",
"make: BMW\n",
"model: M3\n",
"color: red\n",
"number of owners: 2\n",
"make: BMW\n",
"model: M3\n",
"color: red\n",
"number of owners: 3\n",
"make: BMW\n",
"model: M3\n",
"color: red\n",
"number of owners: 4\n",
"make: BMW\n",
"model: M3\n",
"color: red\n",
"number of owners: 5\n"
]
}
],
"source": [
"for i in range(5):\n",
" my_car.sell()\n",
" my_car.car_info()\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>"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"my_car = Car(make=\"Honda\",model=\"Accord\",color=\"blue\") "
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"make: Honda\n",
"model: Accord\n",
"color: blue\n",
"number of owners: 0\n"
]
}
],
"source": [
"my_car.car_info()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"my_car = Car(model=\"Accord\",make=\"Honda\",color=\"blue\") "
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python",
"language": "python",
"name": "conda-env-python-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.11"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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