ch4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "025b4347",
   "metadata": {},
   "source": [
    "# CS 131 - Chapter 4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99a5d271",
   "metadata": {},
   "source": [
    "## Review:\n",
    "- Numbers representation: `11, 0x11, 0o11, 0b11`\n",
    "- Characters representation: Unicode / ASCII .. `ord()`\n",
    "- Arithmatic Operators: `+ - * / // \\% ** += -= *= /=`\n",
    "- Comparison Operators: `== < > <= >= != is in`\n",
    "- Value assignment and Type change"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5deba51",
   "metadata": {},
   "source": [
    "## Lists"
   ]
  },
  {
   "attachments": {
    "image.jpeg": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "d89fcb19",
   "metadata": {},
   "source": [
    "### Real world data\n",
    "#### Weights of each family member:\n",
    "- weight1 = 198 \n",
    "- weight2 = 121 \n",
    "- weight3 = 90 \n",
    "- Weight4 = 63\n",
    "![image.jpeg](attachment:image.jpeg)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3a7cfcd1",
   "metadata": {},
   "source": [
    "### Lists are:\n",
    "- most flexible ordered collection of arbitrary objects (numbers, strings, lists)\n",
    "    - a place to collect other objects\n",
    "    - ordered left- to-right \n",
    "- Accessed by offset\n",
    "    - indexing, slicing and concatenation \n",
    "- Variable length, heterogeneous, arbitrarily nestable\n",
    "    - unlike strings, list can grow and shrink in place (!!)\n",
    "    - lists may contain any type of object\n",
    "    - you can create lists of lists"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "224b20f0",
   "metadata": {},
   "source": [
    "#### More about this later ...\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69e17525",
   "metadata": {},
   "source": [
    "### Lists with data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a452d67e",
   "metadata": {},
   "outputs": [],
   "source": [
    "family_weights = [198, 121, 90, 63]\n",
    "\n",
    "family_weights = [\"dad\", 198, \"mom\", 121, \"liz\", 90, \"emma\", 63]\n",
    "\n",
    "family_weights = [[\"dad\", 198], [\"mom\", 121], [\"liz\", 90], [\"emma\", 63]]\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f29983f8",
   "metadata": {},
   "source": [
    "### Quesiton: \n",
    "A list can contain only integer items.\n",
    "- (A) False\n",
    "- (B) True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fe278e1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[]\n"
     ]
    }
   ],
   "source": [
    "L1=[]              # an empty list\n",
    "print (L1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "451e7440",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['abc', 4]\n"
     ]
    }
   ],
   "source": [
    "L2=['abc',4]       # List with different types \n",
    "print (L2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d5a81041",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, ['abc', 4], []]\n"
     ]
    }
   ],
   "source": [
    "L3=[1,2,L2,L1]     # list of numbers and other lists\n",
    "print (L3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a70d5e4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "L4=list(range(4))  #makes list of integers 0, 1, 2, 3\n",
    "print(L4)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "96c74f24",
   "metadata": {},
   "source": [
    "### Lists' Basic Operations: \n",
    "- Indexing \n",
    "- Slicing \n",
    "- len()\n",
    "- `+`\n",
    "- `*`\n",
    "- `in`\n",
    "- Adding Elements\n",
    "- Updating Elements \n",
    "- Deletion "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33566bff",
   "metadata": {},
   "source": [
    "##### List Indexing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "395ffee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "L0 = [1, 2, 3, 4, 5, 6, 7, 8, 9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "b87ee73a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "577c2c4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "8285d382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "bfbf1a18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[7]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b05a356",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c1edebd",
   "metadata": {},
   "source": [
    "##### List Negative Indexing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "c19bdb02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "25f52707",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[-3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20d93938",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80a52335",
   "metadata": {},
   "source": [
    "#### List Slicing\n",
    "- list_obj[start, end, step]\n",
    "- start inclusive\n",
    "- end exclusive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "468f75ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 4, 5, 6, 7]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[2:7]       # Slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "4671d6bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 5, 7]"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[2:7:2]     # Slicing with intervals (steps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "dac4d92e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 4, 5, 6, 7, 8, 9]"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[2:]        # Slicing without end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "c07d99c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[7, 8]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[-3:-1]    # Slicing from the end of the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "2b43977e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[7, 8, 9]"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[-3:]     # Slicing from the end of the list without end"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5a354ac",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1da499f",
   "metadata": {},
   "source": [
    "#### Reversing List with Slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "dc30ae1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[9, 8, 7, 6, 5, 4, 3, 2, 1]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "7555750c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 3, 4, 5]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "5ed8e01d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[1:5:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "6cceb5a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6, 5, 4, 3]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L0[5:1:-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b2344ad",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8af6a9e",
   "metadata": {},
   "source": [
    "##### List Length: `len()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e524382a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, ['abc', 4], []]\n",
      "4\n"
     ]
    }
   ],
   "source": [
    "print (L3)\n",
    "print (len(L3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3921a139",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d6e344a",
   "metadata": {},
   "source": [
    "##### List Concatenation  : `+`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "d60c4e17",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 'a', 'b', 'c']\n"
     ]
    }
   ],
   "source": [
    "print ([1,2,3] + ['a','b','c'] )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "627816e0",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca49644f",
   "metadata": {},
   "source": [
    "##### Lists' Elements Repeating: `*`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c4702b16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ok', 'ok', 'ok']"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "['ok']*3  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a72e2615",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24a61796",
   "metadata": {},
   "source": [
    "##### Check Element Membership"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ae18ee0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'a' in [1,2,'a']  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65c48e5d",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2939787b",
   "metadata": {},
   "source": [
    "#### Updating Elements is Lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "3502a17a",
   "metadata": {},
   "outputs": [],
   "source": [
    "alist = [1,2,3,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "65bb0f79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 44]"
      ]
     },
     "execution_count": 263,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alist[3] = 44\n",
    "alist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "id": "95779289",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 22, 3, 44]"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alist[1] = 22\n",
    "alist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72f007ac",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b67ca0e",
   "metadata": {},
   "source": [
    "### Lists functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "243d7a23",
   "metadata": {},
   "source": [
    "#### Adding elements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "id": "165dd669",
   "metadata": {},
   "outputs": [],
   "source": [
    "origlist = [45, 32, 88]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "id": "bd5dbe43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 32, 88]"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orig_lst = origlist + [\"dog\"]\n",
    "origlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "id": "b9e1551a",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can only concatenate list (not \"str\") to list",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [297]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m origlist \u001b[38;5;241m=\u001b[39m \u001b[43moriglist\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrabbit\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n",
      "\u001b[0;31mTypeError\u001b[0m: can only concatenate list (not \"str\") to list"
     ]
    }
   ],
   "source": [
    "origlist = origlist + \"rabbit\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "id": "90315eb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 32, 88, 'hameter', 'mouse', 'dog']"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist = origlist + [\"hameter\", \"mouse\", \"dog\"]\n",
    "origlist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a472ec62",
   "metadata": {},
   "source": [
    "### Lists functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b478696",
   "metadata": {},
   "source": [
    "#### Adding elements: `append()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "4a48d401",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 32, 88, 'cat']"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist.append(\"cat\")\n",
    "origlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "b1ee1e9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45,\n",
       " 32,\n",
       " 88,\n",
       " 'cat',\n",
       " 'hameter',\n",
       " 'hameter',\n",
       " 'mouse',\n",
       " 'wolf',\n",
       " 'hameter',\n",
       " 'mouse',\n",
       " 'dog']"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist = origlist + [\"hameter\", \"mouse\", \"dog\"]\n",
    "origlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "b747de75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 32, 88, 'cat', 'hameter', 'mouse', 'hameter', 'mouse', 'wolf']"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist.append(\"wolf\")\n",
    "origlist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f0df460",
   "metadata": {},
   "source": [
    "#### Adding elements: `insert()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "0d40d1b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 'dog', 32, 88, 'cat', 'hameter', 'mouse', 'hameter', 'mouse', 'wolf']"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist.insert(1, \"dog\")\n",
    "origlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "id": "6a9cd902",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45,\n",
       " 32,\n",
       " 88,\n",
       " 'cat',\n",
       " 'hameter',\n",
       " 'hameter',\n",
       " 'mouse',\n",
       " 'wolf',\n",
       " 'hameter',\n",
       " 'mouse',\n",
       " 'dog',\n",
       " 'monkey']"
      ]
     },
     "execution_count": 272,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist.insert(150, \"monkey\")\n",
    "origlist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44a49cad",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c13dea43",
   "metadata": {},
   "source": [
    "#### List deletions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "ebe22902",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 'dog', 32, 88, 'cat', 'hameter', 'mouse', 'hameter', 'mouse', 'wolf']"
      ]
     },
     "execution_count": 255,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "0fa5ecfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[45, 32, 88, 'cat', 'hameter', 'hameter', 'mouse', 'wolf']"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "origlist.remove('dog')\n",
    "origlist"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bc02598",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76713b5a",
   "metadata": {},
   "source": [
    "#### Element Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "id": "36c1af60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 289,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alist = [1,2,3,4]\n",
    "alist.index(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca7e2fe3",
   "metadata": {},
   "source": [
    "---\n",
    "***"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f1b06be4",
   "metadata": {},
   "source": [
    "### Question: \n",
    "- What is printed by the following statements?\n",
    "    - a) 4\n",
    "    - b) 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "27accc6f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "alist = [3, 67, \"cat\", 3.14, False]\n",
    "print(len(alist))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "5c67fd68",
   "metadata": {},
   "source": [
    "### Quesiton\n",
    "- What is printed by the following statements?\n",
    "    - a) 7\n",
    "    - b) 8\n",
    "    - c) 9\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "5be243f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7\n"
     ]
    }
   ],
   "source": [
    "alist = [3, 67, \"cat\", [56, 57, \"dog\"], [ ], 3.14, False]\n",
    "print(len(alist))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "d3e226ab",
   "metadata": {},
   "source": [
    "### Question \n",
    "- What is printed by the following statements?\n",
    "    - a) Error, you cannot use the upper method on a list.\n",
    "    - b) 2\n",
    "    - c) CAT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1ce0f9c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CAT\n"
     ]
    }
   ],
   "source": [
    "alist = [3, 67, \"cat\", [56, 57, \"dog\"], [ ], 3.14, False]\n",
    "print(alist[2].upper())"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f1d590b3",
   "metadata": {},
   "source": [
    "### Question \n",
    "- What is printed by the following statements?\n",
    "\n",
    "    - a) 9\n",
    "    - b) [1, 1, 1, 3, 3, 3, 5, 5, 5]\n",
    "    - c) [1, 3, 5, 1, 3, 5, 1, 3, 5]\n",
    "    - d) [3, 9, 15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "fd829a70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 3, 5, 1, 3, 5, 1, 3, 5]\n"
     ]
    }
   ],
   "source": [
    "alist = [1, 3, 5]\n",
    "print(alist * 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da5988f4",
   "metadata": {},
   "source": [
    "---\n",
    "---\n",
    "### Nested Lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "05aa6eb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['dad', 198], ['mom', 121], ['liz', 90], ['emma', 63]]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "family_weights"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c3ab2db",
   "metadata": {},
   "source": [
    "Lists can contain any kind of Python object... Even non-homgenous ones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "7069d095",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = [1,\"Dave\",3.14, [\"Mark\", 7, 9, [100,101]], 10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ba4dfb7",
   "metadata": {},
   "source": [
    "What would the following statement return:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "c8e9a547",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Dave'"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "dcb6c300",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[3][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "1d6e3bba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[3][3][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7618bb1",
   "metadata": {},
   "source": [
    "### Question\n",
    "- What is printed by the following statements?\n",
    "    - a) 56\n",
    "    - b) c\n",
    "    - c) cat\n",
    "    - d) Error, you cannot have two index values unless you are using slicing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "fcb674c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c\n"
     ]
    }
   ],
   "source": [
    "alist = [3, 67, \"cat\", [56, 57, \"dog\"], [ ], 3.14, False]\n",
    "print(alist[2][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "055b8d87",
   "metadata": {},
   "source": [
    "#### Item in list_object only checks whether the item is in top level of the list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "ba453aa2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "fruit = [\"apple\", \"orange\", \"banana\", \"cherry\"]\n",
    "print(\"apple\" in fruit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "974f2688",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "alist = [3, 67, \"cat\", [56, 57, \"dog\"], [ ],3.14, False]\n",
    "print(3.14 in alist)\n",
    "print(57 in alist)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31a03009",
   "metadata": {},
   "source": [
    "#### Strings are treated by Python like a sequence of charaters (kind of like list BUT NOT LISTS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "d1a616de",
   "metadata": {},
   "outputs": [],
   "source": [
    "string1 = \"This is a one line string for testing\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "2555feb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' is a one line string for '"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "string1[4:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "82556e0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' aentg'"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "string1[4:25:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d74489ba",
   "metadata": {},
   "source": [
    "#### However, you can cast a string to a list of characters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "b139be4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['T',\n",
       " 'h',\n",
       " 'i',\n",
       " 's',\n",
       " ' ',\n",
       " 'i',\n",
       " 's',\n",
       " ' ',\n",
       " 'a',\n",
       " ' ',\n",
       " 'o',\n",
       " 'n',\n",
       " 'e',\n",
       " ' ',\n",
       " 'l',\n",
       " 'i',\n",
       " 'n',\n",
       " 'e',\n",
       " ' ',\n",
       " 's',\n",
       " 't',\n",
       " 'r',\n",
       " 'i',\n",
       " 'n',\n",
       " 'g',\n",
       " ' ',\n",
       " 'f',\n",
       " 'o',\n",
       " 'r',\n",
       " ' ',\n",
       " 't',\n",
       " 'e',\n",
       " 's',\n",
       " 't',\n",
       " 'i',\n",
       " 'n',\n",
       " 'g']"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_string1 = list(string1)\n",
    "list_string1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "04e17cd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[' ', 'a', 'e', 'n', 't', 'g']"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_string1[4:25:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eef91b3c",
   "metadata": {},
   "source": [
    "####  You can then do list operations on the string converted to list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "474d58e1",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "can only concatenate list (not \"str\") to list",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [138]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m list1 \u001b[38;5;241m=\u001b[39m \u001b[43mL0\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mstring1\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m:\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m]\u001b[49m\n",
      "\u001b[0;31mTypeError\u001b[0m: can only concatenate list (not \"str\") to list"
     ]
    }
   ],
   "source": [
    "list1 = L0 + string1[2:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "61cf5e97",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 8, 9, 'i', 's', ' ']"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list1 = L0 + list_string1[2:5]\n",
    "list1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33309e5e",
   "metadata": {},
   "source": [
    "## Tuples\n",
    "Like `list` but they are immutable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "id": "430d4ff6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 2, 3)"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1 = (1, 2, 3)\n",
    "t1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "id": "d149a184",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'a'"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1 = ('a')\n",
    "t1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "dc2cc417",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('a',)"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1 = ('a',)\n",
    "t1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "id": "ad97a0b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "l = [1,2,3]       # list\n",
    "m = [1,2,3]       # same values in l    \n",
    "x = 3             # int\n",
    "y = 3             # same value as x\n",
    "t = (1,2,3)       # tuple\n",
    "u = (1,2,3)       # same values as t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "id": "ffe4867b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 311,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[-1] is x   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 312,
   "id": "556fb761",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 312,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x is y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 332,
   "id": "9d1ae2c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 332,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l is m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 334,
   "id": "c1442f1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 334,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l[2] is x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "129730b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 336,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t is u"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "id": "ceaf7065",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 337,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t[2] is x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "id": "af3818db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4378951984\n",
      "4378952016\n"
     ]
    }
   ],
   "source": [
    "print(id(x))\n",
    "x = 4\n",
    "print(id(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "id": "b7d7183d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4621494592\n",
      "[1, 2, 3]\n",
      "[1, 2, 33]\n",
      "4621494592\n"
     ]
    }
   ],
   "source": [
    "print(id(l))\n",
    "print(l)\n",
    "l[2] = 33\n",
    "print(l)\n",
    "print(id(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "id": "5d739def",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [339]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mt\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m]\u001b[49m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m33\u001b[39m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "t[2] = 33"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66878de2",
   "metadata": {},
   "source": [
    "### Fuctions used with Llists, Tuples, and Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "id": "bc6407cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 346,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "bc8d62fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "id": "fb32e611",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a one line string for testing\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'t'"
      ]
     },
     "execution_count": 351,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(string1)\n",
    "max(string1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "id": "34431aae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 352,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "id": "aff9e050",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "id": "c7596ce4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "' '"
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(string1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "id": "0b39d4a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 355,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "id": "21652ec2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "id": "ec2fa17b",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for +: 'int' and 'str'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [357]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;43msum\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mstring1\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'int' and 'str'"
     ]
    }
   ],
   "source": [
    "sum(string1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbf33e05",
   "metadata": {},
   "source": [
    "### CS Circles\n",
    "\n",
    "- 7A: Strings – 5 questions"
   ]
  }
 ],
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