Learn Python - List Comprehension

List Comprehension 2023.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# List Comprehension in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83507115",
   "metadata": {},
   "source": [
    "### Archived copy in case you'd like to follow along\n",
    "- [On NBViewer](https://nbviewer.org/gist/pdbartsch/d527e1a0ad9e6c04613f8e355e1de0fa)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4980f7eb",
   "metadata": {},
   "source": [
    "### Jupyter Notebooks:\n",
    "- Create, edit, share and execute live code along with\n",
    "- Narrative text written in Markdown\n",
    "- Can make use of environments\n",
    "\n",
    "#### Options:\n",
    "- Install locally\n",
    "  - `pip install notebook`\n",
    "  - `jupyter notebook` To run the notebook\n",
    "- https://jupyter.org/try\n",
    "- https://colab.research.google.com/\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e75cd566",
   "metadata": {},
   "source": [
    "## List Comprehension\n",
    "- a concise way to create lists\n",
    "- can sometimes be used in place of a for loop\n",
    "- [Python List Comprehensions: Explained Visually](https://treyhunner.com/2015/12/python-list-comprehensions-now-in-color/)\n",
    "- [Python docs - List Comprehensions](https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions)\n",
    "- [Jupyter Notebook Shortcuts](https://towardsdatascience.com/jypyter-notebook-shortcuts-bf0101a98330) \n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cde1f04",
   "metadata": {},
   "source": [
    "### Example from Python docs:\n",
    "##### Regular for loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8cd9bc22",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]\n"
     ]
    }
   ],
   "source": [
    "squares = []\n",
    "for x in range(10):\n",
    "    squares.append(x**2)\n",
    "print(squares)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7628fe9c",
   "metadata": {},
   "source": [
    "##### Equivalent using list comprehension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7f589f34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]\n"
     ]
    }
   ],
   "source": [
    "squares_lc = [x**2 for x in range(10)]\n",
    "print(squares_lc)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eeaa10e",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "771c6c5f",
   "metadata": {},
   "source": [
    "### More examples of list comprehensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4a7f7d18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n"
     ]
    }
   ],
   "source": [
    "first_fifteen_numbers = [i for i in range(1, 16)]\n",
    "print(first_fifteen_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0203edac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 2, 4, 6, 8, 10]\n"
     ]
    }
   ],
   "source": [
    "even_numbers = [i for i in range(11) if i % 2 == 0]\n",
    "print(even_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b1b39ead",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 3, 5, 7, 9]\n"
     ]
    }
   ],
   "source": [
    "odd_numbers = [i for i in range(11) if i % 2 != 0]\n",
    "print(odd_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3afe6a4e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50]\n"
     ]
    }
   ],
   "source": [
    "every_fifth = [i for i in range(0,51,5)]  #range(start, stop, step)\n",
    "print(every_fifth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "91d07c4e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['c', 'f', 'i', 'l', 'o', 'r', 'u', 'x']\n"
     ]
    }
   ],
   "source": [
    "alphabet = 'abcdefghijklmnopqrstuvwxyz'\n",
    "every_third_letter = [alphabet[i] for i in range(2, len(alphabet), 3)]\n",
    "print(every_third_letter)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27bc440f",
   "metadata": {},
   "source": [
    "#### Nested List Comprehension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4259052a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)]\n"
     ]
    }
   ],
   "source": [
    "pairs = [(i, j) for i in range(3) for j in range(3)]\n",
    "print(pairs) #output is a list of tuples"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bebedbd",
   "metadata": {},
   "source": [
    "#### List Comprehension used on Dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e34551a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['apple', 'banana', 'orange']\n"
     ]
    }
   ],
   "source": [
    "prices = {'apple': 0.5, 'banana': 0.25, 'orange': 0.75}\n",
    "\n",
    "# extract all values from the dictionary\n",
    "values = [price for price in prices.values()]\n",
    "\n",
    "# extract all keys from the dictionary\n",
    "keys = [fruit for fruit in prices.keys()]\n",
    "\n",
    "print(keys)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a42c685a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5 apple\n",
      "0.25 banana\n",
      "0.75 orange\n"
     ]
    }
   ],
   "source": [
    "# use the zip() function to create a new iterable that contains pairs of corresponding elements from both lists\n",
    "# for loop to iterate over this iterable and print out each pair of elements side by side\n",
    "for i, j in zip(values, keys):\n",
    "    print(i, j)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb1dfa05",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b8ebc41",
   "metadata": {},
   "source": [
    "#### Some ideas for future python code topics:\n",
    " - zip()\n",
    " - enumerate()"
   ]
  }
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