Lab 2.1 Solutions.ipynb

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   "source": [
    "*Edited: 17th September 2023*"
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   "metadata": {},
   "source": [
    "# CMM201 &mdash; Lab 2.1 &mdash; Solutions"
   ]
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   "source": [
    "Defining data and functions used in the answer below:"
   ]
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   "source": [
    "example = 10, 1000, 42, 'Banana', 3.14\n",
    "\n",
    "powers = 1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024\n",
    "\n",
    "company = 'Alphabet Inc.', 'GOOGL', 1616.11\n",
    "\n",
    "def square(x):\n",
    "    return x ** 2\n",
    "\n",
    "def less_than_four(x):\n",
    "    return x < 4\n",
    "\n",
    "data = 0, 1, 2, 3, 4, 5\n",
    "\n",
    "fruits = 'Cherry', 'Orange', 'Pear', 'Apple', 'Coconut', 'Peach'"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(a)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shopping = 'apples', 'oranges', 'bananas'\n",
    "\n",
    "shopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(shopping)"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(b)**"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "shopping += ('pears', )\n",
    "\n",
    "shopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(shopping)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(c)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example[3]"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(d)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example[-2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(e)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "example.index('Banana')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(f)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "powers[3:7]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(g)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "powers[3::3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(h)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(('hello',))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(i)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "company_name, ticker_symbol, stock_price = company"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(j)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "\n",
    "def roller():\n",
    "    first = random.randint(1, 6)\n",
    "    second = random.randint(1, 6)\n",
    "    return first + second, max((first, second))\n",
    "\n",
    "total, highest = roller()\n",
    "\n",
    "print(f'The total rolled was {total}')\n",
    "print(f'The highest die rolled was {highest}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(k)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for index, fruit in enumerate(sorted(fruits)):\n",
    "    print(index, fruit, sep=' - ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(l)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('lab_text.txt', encoding='utf-8') as file:\n",
    "    for line in file:\n",
    "        line = line.strip()\n",
    "        name, price = line.split(':')\n",
    "        price = float(price[1:]) # removing the £\n",
    "        if price > 0.25:\n",
    "            print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternate solution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('lab_text.txt', encoding='utf-8') as file:\n",
    "    for line in file:\n",
    "        line = line.strip()\n",
    "        name, price = line.split(':')\n",
    "        price = float(price.lstrip('£')) # removing the £\n",
    "        if price > 0.25:\n",
    "            print(name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(m)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for x in map(square, filter(less_than_four, data)):\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(n)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for x in filter(less_than_four, map(square, data)):\n",
    "    print(x)"
   ]
  }
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