├── Python Basics 101 - Printing.ipynb ├── Python Basics 101 - Creating, Reading, and Appending Files.ipynb ├── Regex Use Cases.ipynb ├── Python Basics 101 - If - Elif - Else Statements.ipynb ├── Python Project for Beginners - BMI Calculator.ipynb ├── Python Basics 101 - Converting Data Types.ipynb ├── Python Basics 101 - Variables.ipynb ├── Python Basics 101 - List Comprehension.ipynb ├── Inspecting Web Pages with HTML.ipynb ├── Python Basics 101 - Functions.ipynb ├── Python Basics 101 - Data Types.ipynb └── Regex Metacharacters.ipynb /Python Basics 101 - Printing.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "d6a4c505", 6 | "metadata": {}, 7 | "source": [ 8 | "# Printing" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 5, 14 | "id": "e0d4b666", 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "x = 'Hello World!'" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 6, 24 | "id": "ebc240bc", 25 | "metadata": {}, 26 | "outputs": [ 27 | { 28 | "name": "stdout", 29 | "output_type": "stream", 30 | "text": [ 31 | "Hello World!\n" 32 | ] 33 | } 34 | ], 35 | "source": [ 36 | "print(x)" 37 | ] 38 | }, 39 | { 40 | "cell_type": "code", 41 | "execution_count": 10, 42 | "id": "0a2f5aac", 43 | "metadata": {}, 44 | "outputs": [ 45 | { 46 | "name": "stdout", 47 | "output_type": "stream", 48 | "text": [ 49 | "Hello\n", 50 | "World!\n" 51 | ] 52 | } 53 | ], 54 | "source": [ 55 | "print('Hello', 'World!', sep='\\n')" 56 | ] 57 | }, 58 | { 59 | "cell_type": "code", 60 | "execution_count": 17, 61 | "id": "1016495e", 62 | "metadata": {}, 63 | "outputs": [ 64 | { 65 | "name": "stdout", 66 | "output_type": "stream", 67 | "text": [ 68 | "16\n", 69 | "range(0, 5)\n", 70 | "[1, 2, 3]\n" 71 | ] 72 | } 73 | ], 74 | "source": [ 75 | "print(8 + 8)\n", 76 | "\n", 77 | "print(range(5))\n", 78 | "\n", 79 | "print([1,2,3])" 80 | ] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "execution_count": 20, 85 | "id": "c23a38c7", 86 | "metadata": {}, 87 | "outputs": [ 88 | { 89 | "name": "stdout", 90 | "output_type": "stream", 91 | "text": [ 92 | "Mint Chocolate Chip 4\n" 93 | ] 94 | } 95 | ], 96 | "source": [ 97 | "print('Mint Chocolate Chip', 4)" 98 | ] 99 | }, 100 | { 101 | "cell_type": "code", 102 | "execution_count": 22, 103 | "id": "77a2bc47", 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "name": "stdout", 108 | "output_type": "stream", 109 | "text": [ 110 | "I want 3 scoop(s) of MCC ice cream\n" 111 | ] 112 | } 113 | ], 114 | "source": [ 115 | "print('I want {one} scoop(s) of {two} ice cream'.format(one=3, two = 'MCC'))" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 23, 121 | "id": "9ad2ae28", 122 | "metadata": {}, 123 | "outputs": [], 124 | "source": [ 125 | "fav_ice_cream = 'Mint Chocolate Chip'" 126 | ] 127 | }, 128 | { 129 | "cell_type": "code", 130 | "execution_count": 31, 131 | "id": "ef1166c9", 132 | "metadata": {}, 133 | "outputs": [ 134 | { 135 | "name": "stdout", 136 | "output_type": "stream", 137 | "text": [ 138 | " Choco\n" 139 | ] 140 | } 141 | ], 142 | "source": [ 143 | "print(fav_ice_cream[4:10])" 144 | ] 145 | }, 146 | { 147 | "cell_type": "code", 148 | "execution_count": 34, 149 | "id": "8bb0fa55", 150 | "metadata": {}, 151 | "outputs": [ 152 | { 153 | "name": "stdout", 154 | "output_type": "stream", 155 | "text": [ 156 | "I've always liked ice cream\n" 157 | ] 158 | } 159 | ], 160 | "source": [ 161 | "print(\"I've always liked ice cream\")" 162 | ] 163 | } 164 | ], 165 | "metadata": { 166 | "kernelspec": { 167 | "display_name": "Python 3 (ipykernel)", 168 | "language": "python", 169 | "name": "python3" 170 | }, 171 | "language_info": { 172 | "codemirror_mode": { 173 | "name": "ipython", 174 | "version": 3 175 | }, 176 | "file_extension": ".py", 177 | "mimetype": "text/x-python", 178 | "name": "python", 179 | "nbconvert_exporter": "python", 180 | "pygments_lexer": "ipython3", 181 | "version": "3.9.12" 182 | } 183 | }, 184 | "nbformat": 4, 185 | "nbformat_minor": 5 186 | } 187 | -------------------------------------------------------------------------------- /Python Basics 101 - Creating, Reading, and Appending Files.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "9efd109c", 6 | "metadata": {}, 7 | "source": [ 8 | "# Creating, Reading, and Appending Files" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 4, 14 | "id": "10fcb2c9", 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "write_file = open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'w')" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 5, 24 | "id": "f201a07e", 25 | "metadata": {}, 26 | "outputs": [ 27 | { 28 | "data": { 29 | "text/plain": [ 30 | "39" 31 | ] 32 | }, 33 | "execution_count": 5, 34 | "metadata": {}, 35 | "output_type": "execute_result" 36 | } 37 | ], 38 | "source": [ 39 | "write_file.write('This is our first sentence in our file.')" 40 | ] 41 | }, 42 | { 43 | "cell_type": "code", 44 | "execution_count": 6, 45 | "id": "86cf9089", 46 | "metadata": {}, 47 | "outputs": [], 48 | "source": [ 49 | "write_file.close()" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 7, 55 | "id": "41fd7d83", 56 | "metadata": {}, 57 | "outputs": [], 58 | "source": [ 59 | "append_file = open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'a')\n", 60 | "append_file.write(' This is our Second sentence in our file.')\n", 61 | "append_file.close()" 62 | ] 63 | }, 64 | { 65 | "cell_type": "code", 66 | "execution_count": 8, 67 | "id": "c9a799b5", 68 | "metadata": {}, 69 | "outputs": [], 70 | "source": [ 71 | "with open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'a') as append_file:\n", 72 | " append_file.write('\\n This is our Third sentence in our file on a new line.')" 73 | ] 74 | }, 75 | { 76 | "cell_type": "code", 77 | "execution_count": 10, 78 | "id": "65008e57", 79 | "metadata": {}, 80 | "outputs": [ 81 | { 82 | "name": "stdout", 83 | "output_type": "stream", 84 | "text": [ 85 | "This is our first sentence in our file. This is our Second sentence in our file.\n", 86 | " This is our Third sentence in our file on a new line.\n" 87 | ] 88 | } 89 | ], 90 | "source": [ 91 | "with open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'r') as read_file:\n", 92 | " print(read_file.read())" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 12, 98 | "id": "5a943263", 99 | "metadata": {}, 100 | "outputs": [], 101 | "source": [ 102 | "multi_line = \"\"\"\n", 103 | "This is the Fourth sentence.\n", 104 | "This is the Fifth sentence.\n", 105 | "This is the Sixth sentence.\n", 106 | "\"\"\"\n", 107 | "\n", 108 | "with open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'a') as append_file:\n", 109 | " append_file.write(multi_line)" 110 | ] 111 | }, 112 | { 113 | "cell_type": "code", 114 | "execution_count": 13, 115 | "id": "46e3e243", 116 | "metadata": {}, 117 | "outputs": [ 118 | { 119 | "name": "stdout", 120 | "output_type": "stream", 121 | "text": [ 122 | "This is our first sentence in our file. This is our Second sentence in our file.\n", 123 | " This is our Third sentence in our file on a new line.\n", 124 | "This is the Fourth sentence.\n", 125 | "This is the Fifth sentence.\n", 126 | "This is the Sixth sentence.\n", 127 | "\n" 128 | ] 129 | } 130 | ], 131 | "source": [ 132 | "with open(r'C:\\Users\\alexf\\OneDrive\\Documents\\Python Tutorials\\FakeFile.txt', 'r') as read_file:\n", 133 | " print(read_file.read())" 134 | ] 135 | } 136 | ], 137 | "metadata": { 138 | "kernelspec": { 139 | "display_name": "Python 3 (ipykernel)", 140 | "language": "python", 141 | "name": "python3" 142 | }, 143 | "language_info": { 144 | "codemirror_mode": { 145 | "name": "ipython", 146 | "version": 3 147 | }, 148 | "file_extension": ".py", 149 | "mimetype": "text/x-python", 150 | "name": "python", 151 | "nbconvert_exporter": "python", 152 | "pygments_lexer": "ipython3", 153 | "version": "3.9.12" 154 | } 155 | }, 156 | "nbformat": 4, 157 | "nbformat_minor": 5 158 | } 159 | -------------------------------------------------------------------------------- /Regex Use Cases.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "b383356f", 6 | "metadata": {}, 7 | "source": [ 8 | "# Regex Use Cases" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 12, 14 | "id": "af857b00", 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "import re\n", 19 | "\n", 20 | "random_text = '''\n", 21 | "My name is Mr. Neo. My phone number is 123-456-7890. My email is ChosenOne@gmail.com\n", 22 | "My name is Mr. Morphius. My phone number is 413-234-2568. My email is CoolGuy@yahoo.com. \n", 23 | "My name is Mrs. Trinity. My phone number is 285-036-8215. My email is ChosenOnesGirl1@apple.com.\n", 24 | "'''" 25 | ] 26 | }, 27 | { 28 | "cell_type": "code", 29 | "execution_count": 6, 30 | "id": "adfa8b2c", 31 | "metadata": {}, 32 | "outputs": [ 33 | { 34 | "data": { 35 | "text/plain": [ 36 | "['gmail', 'yahoo', 'apple']" 37 | ] 38 | }, 39 | "execution_count": 6, 40 | "metadata": {}, 41 | "output_type": "execute_result" 42 | } 43 | ], 44 | "source": [ 45 | "re.findall('@([a-z]+)',random_text)" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": 10, 51 | "id": "202d1183", 52 | "metadata": {}, 53 | "outputs": [ 54 | { 55 | "data": { 56 | "text/plain": [ 57 | "['gmail.com', 'yahoo.com.', 'apple.com.']" 58 | ] 59 | }, 60 | "execution_count": 10, 61 | "metadata": {}, 62 | "output_type": "execute_result" 63 | } 64 | ], 65 | "source": [ 66 | "re.findall('@([\\w\\.]+)',random_text)" 67 | ] 68 | }, 69 | { 70 | "cell_type": "code", 71 | "execution_count": 15, 72 | "id": "41375adb", 73 | "metadata": {}, 74 | "outputs": [ 75 | { 76 | "data": { 77 | "text/plain": [ 78 | "['ChosenOne@gmail.com', 'CoolGuy@yahoo.com.', 'ChosenOnesGirl1@apple.com.']" 79 | ] 80 | }, 81 | "execution_count": 15, 82 | "metadata": {}, 83 | "output_type": "execute_result" 84 | } 85 | ], 86 | "source": [ 87 | "re.findall('[\\w+]+@[\\w\\.]+',random_text)" 88 | ] 89 | }, 90 | { 91 | "cell_type": "code", 92 | "execution_count": 18, 93 | "id": "56f35608", 94 | "metadata": {}, 95 | "outputs": [ 96 | { 97 | "data": { 98 | "text/plain": [ 99 | "['123-456-7890', '413-234-2568', '285-036-8215']" 100 | ] 101 | }, 102 | "execution_count": 18, 103 | "metadata": {}, 104 | "output_type": "execute_result" 105 | } 106 | ], 107 | "source": [ 108 | "re.findall('\\d{3}-\\d{3}-\\d{4}',random_text)" 109 | ] 110 | }, 111 | { 112 | "cell_type": "code", 113 | "execution_count": 19, 114 | "id": "c8cc1e5e", 115 | "metadata": {}, 116 | "outputs": [], 117 | "source": [ 118 | "my_list = ['ChosenOne@gmail.com', 'CoolGuy@yahoo.com.', 'ChosenOnesGirl1@apple.com.']" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 21, 124 | "id": "5d3e2f33", 125 | "metadata": {}, 126 | "outputs": [ 127 | { 128 | "name": "stdout", 129 | "output_type": "stream", 130 | "text": [ 131 | "['gmail.com']\n", 132 | "['yahoo.com.']\n", 133 | "['apple.com.']\n" 134 | ] 135 | } 136 | ], 137 | "source": [ 138 | "for email in my_list:\n", 139 | " print(re.findall('@([\\w\\.]+)',email))" 140 | ] 141 | }, 142 | { 143 | "cell_type": "code", 144 | "execution_count": 23, 145 | "id": "2b3cd5c7", 146 | "metadata": {}, 147 | "outputs": [ 148 | { 149 | "name": "stdout", 150 | "output_type": "stream", 151 | "text": [ 152 | "['gmail.com', 'yahoo.com.', 'apple.com.']\n" 153 | ] 154 | } 155 | ], 156 | "source": [ 157 | "domain_list = [re.findall('@([\\w\\.]+)',email)[0] for email in my_list]\n", 158 | "\n", 159 | "print(domain_list)" 160 | ] 161 | }, 162 | { 163 | "cell_type": "code", 164 | "execution_count": null, 165 | "id": "62e9a271", 166 | "metadata": {}, 167 | "outputs": [], 168 | "source": [] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": null, 173 | "id": "352953cc", 174 | "metadata": {}, 175 | "outputs": [], 176 | "source": [] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": null, 181 | "id": "40b86e09", 182 | "metadata": {}, 183 | "outputs": [], 184 | "source": [] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "execution_count": null, 189 | "id": "8c8477b5", 190 | "metadata": {}, 191 | "outputs": [], 192 | "source": [] 193 | }, 194 | { 195 | "cell_type": "code", 196 | "execution_count": null, 197 | "id": "919b7814", 198 | "metadata": {}, 199 | "outputs": [], 200 | "source": [] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": null, 205 | "id": "d35fe5e8", 206 | "metadata": {}, 207 | "outputs": [], 208 | "source": [] 209 | }, 210 | { 211 | "cell_type": "code", 212 | "execution_count": null, 213 | "id": "7147efa6", 214 | "metadata": {}, 215 | "outputs": [], 216 | "source": [] 217 | } 218 | ], 219 | "metadata": { 220 | "kernelspec": { 221 | "display_name": "Python 3 (ipykernel)", 222 | "language": "python", 223 | "name": "python3" 224 | }, 225 | "language_info": { 226 | "codemirror_mode": { 227 | "name": "ipython", 228 | "version": 3 229 | }, 230 | "file_extension": ".py", 231 | "mimetype": "text/x-python", 232 | "name": "python", 233 | "nbconvert_exporter": "python", 234 | "pygments_lexer": "ipython3", 235 | "version": "3.9.13" 236 | } 237 | }, 238 | "nbformat": 4, 239 | "nbformat_minor": 5 240 | } 241 | -------------------------------------------------------------------------------- /Python Basics 101 - If - Elif - Else Statements.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "attachments": {}, 5 | "cell_type": "markdown", 6 | "id": "770bcc6d", 7 | "metadata": {}, 8 | "source": [ 9 | "# If - Elif - Else Statements" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 1, 15 | "id": "78e96668", 16 | "metadata": {}, 17 | "outputs": [ 18 | { 19 | "name": "stdout", 20 | "output_type": "stream", 21 | "text": [ 22 | "It worked!\n" 23 | ] 24 | } 25 | ], 26 | "source": [ 27 | "if 25 > 10:\n", 28 | " print('It worked!')" 29 | ] 30 | }, 31 | { 32 | "cell_type": "code", 33 | "execution_count": 4, 34 | "id": "9bb90f9b", 35 | "metadata": {}, 36 | "outputs": [ 37 | { 38 | "name": "stdout", 39 | "output_type": "stream", 40 | "text": [ 41 | "It worked!\n" 42 | ] 43 | } 44 | ], 45 | "source": [ 46 | "if 25 > 10:\n", 47 | " print('It worked!')\n", 48 | "else:\n", 49 | " print('It did not work...')" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 7, 55 | "id": "064e4770", 56 | "metadata": {}, 57 | "outputs": [ 58 | { 59 | "name": "stdout", 60 | "output_type": "stream", 61 | "text": [ 62 | "It worked!\n" 63 | ] 64 | } 65 | ], 66 | "source": [ 67 | "if (25 < 10) or (1 < 3):\n", 68 | " print('It worked!')\n", 69 | "elif 25 < 20:\n", 70 | " print('elif worked!')\n", 71 | "elif 25 < 21:\n", 72 | " print('elif 2 worked!')\n", 73 | "elif 25 < 40:\n", 74 | " print('elif 3 worked!')\n", 75 | "elif 25 < 50:\n", 76 | " print('elif 4 worked!')\n", 77 | "else:\n", 78 | " print('It did not work...')" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 8, 84 | "id": "421a4e09", 85 | "metadata": {}, 86 | "outputs": [ 87 | { 88 | "name": "stdout", 89 | "output_type": "stream", 90 | "text": [ 91 | "It did not work...\n" 92 | ] 93 | } 94 | ], 95 | "source": [ 96 | "print('It worked!') if 10>30 else print('It did not work...')" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 14, 102 | "id": "5a7ba25e", 103 | "metadata": {}, 104 | "outputs": [ 105 | { 106 | "name": "stdout", 107 | "output_type": "stream", 108 | "text": [ 109 | "It worked!\n", 110 | "This nested if statement worked!\n" 111 | ] 112 | } 113 | ], 114 | "source": [ 115 | "if (25 < 10) or (1 < 3):\n", 116 | " print('It worked!')\n", 117 | " if 10 > 5:\n", 118 | " print('This nested if statement worked!')\n", 119 | "elif 25 < 20:\n", 120 | " print('elif worked!')\n", 121 | "elif 25 < 21:\n", 122 | " print('elif 2 worked!')\n", 123 | "elif 25 < 40:\n", 124 | " print('elif 3 worked!')\n", 125 | "elif 25 < 50:\n", 126 | " print('elif 4 worked!')\n", 127 | "else:\n", 128 | " print('It did not work...')" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": null, 134 | "id": "aaed42c5", 135 | "metadata": {}, 136 | "outputs": [], 137 | "source": [] 138 | }, 139 | { 140 | "cell_type": "code", 141 | "execution_count": null, 142 | "id": "b26d5171", 143 | "metadata": {}, 144 | "outputs": [], 145 | "source": [] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "execution_count": null, 150 | "id": "1fa8dbc0", 151 | "metadata": {}, 152 | "outputs": [], 153 | "source": [] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": null, 158 | "id": "e9106ac7", 159 | "metadata": {}, 160 | "outputs": [], 161 | "source": [] 162 | }, 163 | { 164 | "cell_type": "code", 165 | "execution_count": null, 166 | "id": "233f0e99", 167 | "metadata": {}, 168 | "outputs": [], 169 | "source": [] 170 | }, 171 | { 172 | "cell_type": "code", 173 | "execution_count": null, 174 | "id": "f0b889e8", 175 | "metadata": {}, 176 | "outputs": [], 177 | "source": [] 178 | }, 179 | { 180 | "cell_type": "code", 181 | "execution_count": null, 182 | "id": "e490f008", 183 | "metadata": {}, 184 | "outputs": [], 185 | "source": [] 186 | }, 187 | { 188 | "cell_type": "code", 189 | "execution_count": null, 190 | "id": "3146f0ae", 191 | "metadata": {}, 192 | "outputs": [], 193 | "source": [] 194 | }, 195 | { 196 | "cell_type": "code", 197 | "execution_count": null, 198 | "id": "cd77a547", 199 | "metadata": {}, 200 | "outputs": [], 201 | "source": [] 202 | }, 203 | { 204 | "cell_type": "code", 205 | "execution_count": null, 206 | "id": "487556c8", 207 | "metadata": {}, 208 | "outputs": [], 209 | "source": [] 210 | }, 211 | { 212 | "cell_type": "code", 213 | "execution_count": null, 214 | "id": "f2a77e2e", 215 | "metadata": {}, 216 | "outputs": [], 217 | "source": [] 218 | }, 219 | { 220 | "cell_type": "code", 221 | "execution_count": null, 222 | "id": "996d05df", 223 | "metadata": {}, 224 | "outputs": [], 225 | "source": [] 226 | }, 227 | { 228 | "cell_type": "code", 229 | "execution_count": null, 230 | "id": "21458f08", 231 | "metadata": {}, 232 | "outputs": [], 233 | "source": [] 234 | }, 235 | { 236 | "cell_type": "code", 237 | "execution_count": null, 238 | "id": "45967f97", 239 | "metadata": {}, 240 | "outputs": [], 241 | "source": [] 242 | }, 243 | { 244 | "cell_type": "code", 245 | "execution_count": null, 246 | "id": "7895a426", 247 | "metadata": {}, 248 | "outputs": [], 249 | "source": [] 250 | }, 251 | { 252 | "cell_type": "code", 253 | "execution_count": null, 254 | "id": "29f04730", 255 | "metadata": {}, 256 | "outputs": [], 257 | "source": [] 258 | }, 259 | { 260 | "cell_type": "code", 261 | "execution_count": null, 262 | "id": "c41f0531", 263 | "metadata": {}, 264 | "outputs": [], 265 | "source": [] 266 | } 267 | ], 268 | "metadata": { 269 | "kernelspec": { 270 | "display_name": "Python 3 (ipykernel)", 271 | "language": "python", 272 | "name": "python3" 273 | }, 274 | "language_info": { 275 | "codemirror_mode": { 276 | "name": "ipython", 277 | "version": 3 278 | }, 279 | "file_extension": ".py", 280 | "mimetype": "text/x-python", 281 | "name": "python", 282 | "nbconvert_exporter": "python", 283 | "pygments_lexer": "ipython3", 284 | "version": "3.9.12" 285 | } 286 | }, 287 | "nbformat": 4, 288 | "nbformat_minor": 5 289 | } 290 | -------------------------------------------------------------------------------- /Python Project for Beginners - BMI Calculator.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "c131715d", 6 | "metadata": {}, 7 | "source": [ 8 | "# BMI Calculator\n", 9 | "\n", 10 | "https://mercer-health.com/services/weight-management-center/bmi-calculator#:~:text=Body%20Mass%20Index%2C%20or%20BMI,inches%20x%20height%20in%20inches" 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": 21, 16 | "id": "ed4712f7", 17 | "metadata": {}, 18 | "outputs": [ 19 | { 20 | "name": "stdout", 21 | "output_type": "stream", 22 | "text": [ 23 | "Enter you name: Alex\n", 24 | "Enter your weight in pounds: 170\n", 25 | "Enter your height in inches: 69\n", 26 | "25.101869355177485\n", 27 | "Alex, you are overweight. You need to exercise more and stop sitting and writing so many python tutorials\n" 28 | ] 29 | } 30 | ], 31 | "source": [ 32 | "name = input(\"Enter you name: \")\n", 33 | "\n", 34 | "weight = int(input(\"Enter your weight in pounds: \"))\n", 35 | "\n", 36 | "height = int(input(\"Enter your height in inches: \"))\n", 37 | "\n", 38 | "BMI = (weight * 703) / (height * height)\n", 39 | "\n", 40 | "print(BMI)\n", 41 | "\n", 42 | "if BMI>0:\n", 43 | " if(BMI<18.5):\n", 44 | " print(name +\", you are underwight.\")\n", 45 | " elif (BMI<=24.9):\n", 46 | " print(name +\", you are normal weight.\")\n", 47 | " elif (BMI<29.9):\n", 48 | " print(name +\", you are overweight. You need to exercise more and stop sitting and writing so many python tutorials.\")\n", 49 | " elif (BMI<34.9):\n", 50 | " print(name +\", you are obese.\")\n", 51 | " elif (BMI<39.9):\n", 52 | " print(name +\", you are severely obese.\")\n", 53 | " else:\n", 54 | " print(name +\", you are morbidly obese.\")\n", 55 | "else:\n", 56 | " print(\"Enter valid input\")" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": null, 62 | "id": "5cff5811", 63 | "metadata": {}, 64 | "outputs": [], 65 | "source": [] 66 | }, 67 | { 68 | "cell_type": "code", 69 | "execution_count": null, 70 | "id": "cec22d0c", 71 | "metadata": {}, 72 | "outputs": [], 73 | "source": [] 74 | }, 75 | { 76 | "cell_type": "code", 77 | "execution_count": null, 78 | "id": "66be944f", 79 | "metadata": {}, 80 | "outputs": [], 81 | "source": [] 82 | }, 83 | { 84 | "cell_type": "code", 85 | "execution_count": null, 86 | "id": "1ab169ae", 87 | "metadata": {}, 88 | "outputs": [], 89 | "source": [ 90 | "#BMI = (weight in pounds x 703) / (height in inches x height in inches)" 91 | ] 92 | }, 93 | { 94 | "cell_type": "code", 95 | "execution_count": null, 96 | "id": "31a43c55", 97 | "metadata": {}, 98 | "outputs": [], 99 | "source": [ 100 | "print(weight)" 101 | ] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": null, 106 | "id": "81cf54aa", 107 | "metadata": {}, 108 | "outputs": [], 109 | "source": [ 110 | "Under 18.5\tUnderweight\tMinimal\n", 111 | "18.5 - 24.9\tNormal Weight\tMinimal\n", 112 | "25 - 29.9\tOverweight\tIncreased\n", 113 | "30 - 34.9\tObese\tHigh\n", 114 | "35 - 39.9\tSeverely Obese\tVery High\n", 115 | "40 and over\tMorbidly Obese\tExtremely High" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 19, 121 | "id": "3fb8d60a", 122 | "metadata": {}, 123 | "outputs": [ 124 | { 125 | "name": "stdout", 126 | "output_type": "stream", 127 | "text": [ 128 | "Alex, you are overweight.\n" 129 | ] 130 | } 131 | ], 132 | "source": [ 133 | "if BMI>0:\n", 134 | " if(BMI<18.5):\n", 135 | " print(name +\", you are underwight.\")\n", 136 | " elif (BMI<=24.9):\n", 137 | " print(name +\", you are normal weight.\")\n", 138 | " elif (BMI<29.9):\n", 139 | " print(name +\", you are overweight.\")\n", 140 | " elif (BMI<34.9):\n", 141 | " print(name +\", you are obese.\")\n", 142 | " elif (BMI<39.9):\n", 143 | " print(name +\", you are severely obese.\")\n", 144 | " else:\n", 145 | " print(name +\", you are morbidly obese.\")\n", 146 | "else:\n", 147 | " print(\"Enter valid input\")" 148 | ] 149 | }, 150 | { 151 | "cell_type": "code", 152 | "execution_count": null, 153 | "id": "521c5bb8", 154 | "metadata": {}, 155 | "outputs": [], 156 | "source": [] 157 | }, 158 | { 159 | "cell_type": "code", 160 | "execution_count": null, 161 | "id": "bf0ae710", 162 | "metadata": {}, 163 | "outputs": [], 164 | "source": [] 165 | }, 166 | { 167 | "cell_type": "code", 168 | "execution_count": null, 169 | "id": "2026624b", 170 | "metadata": {}, 171 | "outputs": [], 172 | "source": [] 173 | }, 174 | { 175 | "cell_type": "code", 176 | "execution_count": null, 177 | "id": "15b3560f", 178 | "metadata": {}, 179 | "outputs": [], 180 | "source": [] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": null, 185 | "id": "103deb3d", 186 | "metadata": {}, 187 | "outputs": [], 188 | "source": [] 189 | }, 190 | { 191 | "cell_type": "code", 192 | "execution_count": null, 193 | "id": "d72530fb", 194 | "metadata": {}, 195 | "outputs": [], 196 | "source": [] 197 | }, 198 | { 199 | "cell_type": "code", 200 | "execution_count": null, 201 | "id": "a07ad247", 202 | "metadata": {}, 203 | "outputs": [], 204 | "source": [] 205 | }, 206 | { 207 | "cell_type": "code", 208 | "execution_count": null, 209 | "id": "25a3ec13", 210 | "metadata": {}, 211 | "outputs": [], 212 | "source": [] 213 | }, 214 | { 215 | "cell_type": "code", 216 | "execution_count": null, 217 | "id": "10ec78fe", 218 | "metadata": {}, 219 | "outputs": [], 220 | "source": [] 221 | }, 222 | { 223 | "cell_type": "code", 224 | "execution_count": null, 225 | "id": "2cd4c947", 226 | "metadata": {}, 227 | "outputs": [], 228 | "source": [] 229 | }, 230 | { 231 | "cell_type": "code", 232 | "execution_count": null, 233 | "id": "17550312", 234 | "metadata": {}, 235 | "outputs": [], 236 | "source": [] 237 | }, 238 | { 239 | "cell_type": "code", 240 | "execution_count": null, 241 | "id": "ea0f4997", 242 | "metadata": {}, 243 | "outputs": [], 244 | "source": [] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": null, 249 | "id": "76574c3f", 250 | "metadata": {}, 251 | "outputs": [], 252 | "source": [] 253 | } 254 | ], 255 | "metadata": { 256 | "kernelspec": { 257 | "display_name": "Python 3 (ipykernel)", 258 | "language": "python", 259 | "name": "python3" 260 | }, 261 | "language_info": { 262 | "codemirror_mode": { 263 | "name": "ipython", 264 | "version": 3 265 | }, 266 | "file_extension": ".py", 267 | "mimetype": "text/x-python", 268 | "name": "python", 269 | "nbconvert_exporter": "python", 270 | "pygments_lexer": "ipython3", 271 | "version": "3.9.12" 272 | } 273 | }, 274 | "nbformat": 4, 275 | "nbformat_minor": 5 276 | } 277 | -------------------------------------------------------------------------------- /Python Basics 101 - Converting Data Types.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "9d8fd8b3", 6 | "metadata": {}, 7 | "source": [ 8 | "# Converting Data Types" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 8, 14 | "id": "5647de8d", 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "int" 21 | ] 22 | }, 23 | "execution_count": 8, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "num_int = 7\n", 30 | "\n", 31 | "type(num_int)" 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": 9, 37 | "id": "c5aa9dcc", 38 | "metadata": {}, 39 | "outputs": [ 40 | { 41 | "data": { 42 | "text/plain": [ 43 | "str" 44 | ] 45 | }, 46 | "execution_count": 9, 47 | "metadata": {}, 48 | "output_type": "execute_result" 49 | } 50 | ], 51 | "source": [ 52 | "num_str = '7'\n", 53 | "\n", 54 | "type(num_str)" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 11, 60 | "id": "079fc569", 61 | "metadata": {}, 62 | "outputs": [ 63 | { 64 | "data": { 65 | "text/plain": [ 66 | "int" 67 | ] 68 | }, 69 | "execution_count": 11, 70 | "metadata": {}, 71 | "output_type": "execute_result" 72 | } 73 | ], 74 | "source": [ 75 | "nun_str_conv = int(num_str)\n", 76 | "\n", 77 | "type(nun_str_conv)" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": 13, 83 | "id": "3d4d00cb", 84 | "metadata": {}, 85 | "outputs": [ 86 | { 87 | "name": "stdout", 88 | "output_type": "stream", 89 | "text": [ 90 | "14\n" 91 | ] 92 | } 93 | ], 94 | "source": [ 95 | "num_sum = num_int + nun_str_conv\n", 96 | "\n", 97 | "print(num_sum)" 98 | ] 99 | }, 100 | { 101 | "cell_type": "code", 102 | "execution_count": 14, 103 | "id": "e54eac45", 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "data": { 108 | "text/plain": [ 109 | "int" 110 | ] 111 | }, 112 | "execution_count": 14, 113 | "metadata": {}, 114 | "output_type": "execute_result" 115 | } 116 | ], 117 | "source": [ 118 | "type(num_sum)" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 15, 124 | "id": "bc419b2a", 125 | "metadata": {}, 126 | "outputs": [ 127 | { 128 | "data": { 129 | "text/plain": [ 130 | "list" 131 | ] 132 | }, 133 | "execution_count": 15, 134 | "metadata": {}, 135 | "output_type": "execute_result" 136 | } 137 | ], 138 | "source": [ 139 | "list_type = [1,2,3]\n", 140 | "\n", 141 | "type(list_type)" 142 | ] 143 | }, 144 | { 145 | "cell_type": "code", 146 | "execution_count": 17, 147 | "id": "ee48356d", 148 | "metadata": {}, 149 | "outputs": [ 150 | { 151 | "data": { 152 | "text/plain": [ 153 | "tuple" 154 | ] 155 | }, 156 | "execution_count": 17, 157 | "metadata": {}, 158 | "output_type": "execute_result" 159 | } 160 | ], 161 | "source": [ 162 | "type(tuple(list_type))" 163 | ] 164 | }, 165 | { 166 | "cell_type": "code", 167 | "execution_count": 18, 168 | "id": "08e59291", 169 | "metadata": {}, 170 | "outputs": [], 171 | "source": [ 172 | "list_type = [1,2,3,3,2,1,2,3,2,1]" 173 | ] 174 | }, 175 | { 176 | "cell_type": "code", 177 | "execution_count": 20, 178 | "id": "0273ed56", 179 | "metadata": {}, 180 | "outputs": [ 181 | { 182 | "data": { 183 | "text/plain": [ 184 | "set" 185 | ] 186 | }, 187 | "execution_count": 20, 188 | "metadata": {}, 189 | "output_type": "execute_result" 190 | } 191 | ], 192 | "source": [ 193 | "type(set(list_type))" 194 | ] 195 | }, 196 | { 197 | "cell_type": "code", 198 | "execution_count": 21, 199 | "id": "565aaa3e", 200 | "metadata": {}, 201 | "outputs": [ 202 | { 203 | "data": { 204 | "text/plain": [ 205 | "dict" 206 | ] 207 | }, 208 | "execution_count": 21, 209 | "metadata": {}, 210 | "output_type": "execute_result" 211 | } 212 | ], 213 | "source": [ 214 | "dict_type = {'name': 'Alex','age': 28, 'hair': 'N/A'}\n", 215 | "\n", 216 | "type(dict_type)" 217 | ] 218 | }, 219 | { 220 | "cell_type": "code", 221 | "execution_count": 22, 222 | "id": "f1d5d6eb", 223 | "metadata": {}, 224 | "outputs": [ 225 | { 226 | "data": { 227 | "text/plain": [ 228 | "dict_items([('name', 'Alex'), ('age', 28), ('hair', 'N/A')])" 229 | ] 230 | }, 231 | "execution_count": 22, 232 | "metadata": {}, 233 | "output_type": "execute_result" 234 | } 235 | ], 236 | "source": [ 237 | "dict_type.items()" 238 | ] 239 | }, 240 | { 241 | "cell_type": "code", 242 | "execution_count": 23, 243 | "id": "519de227", 244 | "metadata": {}, 245 | "outputs": [ 246 | { 247 | "data": { 248 | "text/plain": [ 249 | "dict_values(['Alex', 28, 'N/A'])" 250 | ] 251 | }, 252 | "execution_count": 23, 253 | "metadata": {}, 254 | "output_type": "execute_result" 255 | } 256 | ], 257 | "source": [ 258 | "dict_type.values()" 259 | ] 260 | }, 261 | { 262 | "cell_type": "code", 263 | "execution_count": 24, 264 | "id": "30d1e55f", 265 | "metadata": {}, 266 | "outputs": [ 267 | { 268 | "data": { 269 | "text/plain": [ 270 | "dict_keys(['name', 'age', 'hair'])" 271 | ] 272 | }, 273 | "execution_count": 24, 274 | "metadata": {}, 275 | "output_type": "execute_result" 276 | } 277 | ], 278 | "source": [ 279 | "dict_type.keys()" 280 | ] 281 | }, 282 | { 283 | "cell_type": "code", 284 | "execution_count": 26, 285 | "id": "9f147d5f", 286 | "metadata": {}, 287 | "outputs": [ 288 | { 289 | "data": { 290 | "text/plain": [ 291 | "list" 292 | ] 293 | }, 294 | "execution_count": 26, 295 | "metadata": {}, 296 | "output_type": "execute_result" 297 | } 298 | ], 299 | "source": [ 300 | "type(list(dict_type.keys()))" 301 | ] 302 | }, 303 | { 304 | "cell_type": "code", 305 | "execution_count": 27, 306 | "id": "727f66de", 307 | "metadata": {}, 308 | "outputs": [ 309 | { 310 | "data": { 311 | "text/plain": [ 312 | "list" 313 | ] 314 | }, 315 | "execution_count": 27, 316 | "metadata": {}, 317 | "output_type": "execute_result" 318 | } 319 | ], 320 | "source": [ 321 | "type(list(dict_type.values()))" 322 | ] 323 | }, 324 | { 325 | "cell_type": "code", 326 | "execution_count": 29, 327 | "id": "f360e2b4", 328 | "metadata": {}, 329 | "outputs": [ 330 | { 331 | "data": { 332 | "text/plain": [ 333 | "{' ', 'I', 'a', 'e', 'i', 'k', 'l', 'o', 'p', 'r', 't', 'y'}" 334 | ] 335 | }, 336 | "execution_count": 29, 337 | "metadata": {}, 338 | "output_type": "execute_result" 339 | } 340 | ], 341 | "source": [ 342 | "long_str = \"I like to party\"\n", 343 | "\n", 344 | "set(long_str)" 345 | ] 346 | } 347 | ], 348 | "metadata": { 349 | "kernelspec": { 350 | "display_name": "Python 3 (ipykernel)", 351 | "language": "python", 352 | "name": "python3" 353 | }, 354 | "language_info": { 355 | "codemirror_mode": { 356 | "name": "ipython", 357 | "version": 3 358 | }, 359 | "file_extension": ".py", 360 | "mimetype": "text/x-python", 361 | "name": "python", 362 | "nbconvert_exporter": "python", 363 | "pygments_lexer": "ipython3", 364 | "version": "3.9.12" 365 | } 366 | }, 367 | "nbformat": 4, 368 | "nbformat_minor": 5 369 | } 370 | -------------------------------------------------------------------------------- /Python Basics 101 - Variables.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "c7bcc89c", 6 | "metadata": {}, 7 | "source": [ 8 | "# Variables in Python" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 1, 14 | "id": "1b508a9f", 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stdout", 19 | "output_type": "stream", 20 | "text": [ 21 | "22\n" 22 | ] 23 | } 24 | ], 25 | "source": [ 26 | "x = 22\n", 27 | "\n", 28 | "print(x)" 29 | ] 30 | }, 31 | { 32 | "cell_type": "code", 33 | "execution_count": 2, 34 | "id": "3efc2c0a", 35 | "metadata": {}, 36 | "outputs": [ 37 | { 38 | "data": { 39 | "text/plain": [ 40 | "int" 41 | ] 42 | }, 43 | "execution_count": 2, 44 | "metadata": {}, 45 | "output_type": "execute_result" 46 | } 47 | ], 48 | "source": [ 49 | "type(x)" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 8, 55 | "id": "49d1a64d", 56 | "metadata": {}, 57 | "outputs": [ 58 | { 59 | "name": "stdout", 60 | "output_type": "stream", 61 | "text": [ 62 | "Mint Chocolate Chip\n" 63 | ] 64 | } 65 | ], 66 | "source": [ 67 | "y = 'Mint Chocolate Chip'\n", 68 | "\n", 69 | "print(y)" 70 | ] 71 | }, 72 | { 73 | "cell_type": "code", 74 | "execution_count": 4, 75 | "id": "af55f52f", 76 | "metadata": {}, 77 | "outputs": [ 78 | { 79 | "data": { 80 | "text/plain": [ 81 | "str" 82 | ] 83 | }, 84 | "execution_count": 4, 85 | "metadata": {}, 86 | "output_type": "execute_result" 87 | } 88 | ], 89 | "source": [ 90 | "type(y)" 91 | ] 92 | }, 93 | { 94 | "cell_type": "code", 95 | "execution_count": 11, 96 | "id": "09a0073a", 97 | "metadata": {}, 98 | "outputs": [ 99 | { 100 | "name": "stdout", 101 | "output_type": "stream", 102 | "text": [ 103 | "Mint Chocolate Chip\n" 104 | ] 105 | } 106 | ], 107 | "source": [ 108 | "# Case Sensitivity\n", 109 | "\n", 110 | "y = 'Chocolate'\n", 111 | "\n", 112 | "Y = 'Mint Chocolate Chip'\n", 113 | "\n", 114 | "print(Y)" 115 | ] 116 | }, 117 | { 118 | "cell_type": "code", 119 | "execution_count": 12, 120 | "id": "b6442032", 121 | "metadata": {}, 122 | "outputs": [ 123 | { 124 | "name": "stdout", 125 | "output_type": "stream", 126 | "text": [ 127 | "Chocolate\n", 128 | "Vanilla\n", 129 | "Rocky Road\n" 130 | ] 131 | } 132 | ], 133 | "source": [ 134 | "#Assign multiple values to multiple variables\n", 135 | "\n", 136 | "x,y,z = 'Chocolate', 'Vanilla', 'Rocky Road'\n", 137 | "\n", 138 | "print(x)\n", 139 | "print(y)\n", 140 | "print(z)\n" 141 | ] 142 | }, 143 | { 144 | "cell_type": "code", 145 | "execution_count": 14, 146 | "id": "599e484b", 147 | "metadata": {}, 148 | "outputs": [ 149 | { 150 | "name": "stdout", 151 | "output_type": "stream", 152 | "text": [ 153 | "Root Beer Float\n", 154 | "Root Beer Float\n", 155 | "Root Beer Float\n" 156 | ] 157 | } 158 | ], 159 | "source": [ 160 | "#Assign one value to multiple variables\n", 161 | "\n", 162 | "x = y = z = 'Root Beer Float'\n", 163 | "\n", 164 | "print(x)\n", 165 | "print(y)\n", 166 | "print(z)" 167 | ] 168 | }, 169 | { 170 | "cell_type": "code", 171 | "execution_count": 15, 172 | "id": "43d4d3d5", 173 | "metadata": {}, 174 | "outputs": [ 175 | { 176 | "name": "stdout", 177 | "output_type": "stream", 178 | "text": [ 179 | "Chocolate\n", 180 | "Vanilla\n", 181 | "Rocky Road\n" 182 | ] 183 | } 184 | ], 185 | "source": [ 186 | "ice_cream = ['Chocolate', 'Vanilla', 'Rocky Road']\n", 187 | "\n", 188 | "x,y,z = ice_cream\n", 189 | "\n", 190 | "print(x)\n", 191 | "print(y)\n", 192 | "print(z)" 193 | ] 194 | }, 195 | { 196 | "cell_type": "code", 197 | "execution_count": null, 198 | "id": "a1788d5e", 199 | "metadata": {}, 200 | "outputs": [], 201 | "source": [ 202 | "# Camel Case\n", 203 | "\n", 204 | "#Test Variable Case\n", 205 | "\n", 206 | "testVariableCase = 'Vanilla Swirl'" 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": null, 212 | "id": "1954effe", 213 | "metadata": {}, 214 | "outputs": [], 215 | "source": [ 216 | "# Pascal Case\n", 217 | "\n", 218 | "#Test Variable Case\n", 219 | "\n", 220 | "TestVariableCase = 'Vanilla Swirl'" 221 | ] 222 | }, 223 | { 224 | "cell_type": "code", 225 | "execution_count": null, 226 | "id": "f79bc1d1", 227 | "metadata": {}, 228 | "outputs": [], 229 | "source": [ 230 | "# Snake Case\n", 231 | "\n", 232 | "#Test Variable Case\n", 233 | "\n", 234 | "test_variable_case = 'Vanilla Swirl'" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": null, 240 | "id": "295aa5c6", 241 | "metadata": {}, 242 | "outputs": [], 243 | "source": [ 244 | "#Good ways to write variables\n", 245 | "\n", 246 | "testvar = 'Vanilla Swirl'\n", 247 | "test_var = 'Vanilla Swirl'\n", 248 | "_test_var = 'Vanilla Swirl'\n", 249 | "testVar = 'Vanilla Swirl'\n", 250 | "TestVar = 'Vanilla Swirl'\n", 251 | "testVar2 = 'Vanilla Swirl'" 252 | ] 253 | }, 254 | { 255 | "cell_type": "code", 256 | "execution_count": 17, 257 | "id": "0e08b4dc", 258 | "metadata": {}, 259 | "outputs": [], 260 | "source": [ 261 | "#Bad ways to write variables\n", 262 | "\n", 263 | "2testVar = 'Vanilla Swirl'\n", 264 | "test-Var2 = 'Vanilla Swirl'\n", 265 | "test Var2 = 'Vanilla Swirl'\n", 266 | "test,Var2 = 'Vanilla Swirl'" 267 | ] 268 | }, 269 | { 270 | "cell_type": "code", 271 | "execution_count": 19, 272 | "id": "a588bcef", 273 | "metadata": {}, 274 | "outputs": [ 275 | { 276 | "ename": "TypeError", 277 | "evalue": "can only concatenate str (not \"int\") to str", 278 | "output_type": "error", 279 | "traceback": [ 280 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", 281 | "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", 282 | "Input \u001b[1;32mIn [19]\u001b[0m, in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mIce Cream is my favorite\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(x)\n", 283 | "\u001b[1;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str" 284 | ] 285 | } 286 | ], 287 | "source": [ 288 | "x = 'Ice Cream is my favorite' + 2\n", 289 | "\n", 290 | "print(x)" 291 | ] 292 | }, 293 | { 294 | "cell_type": "code", 295 | "execution_count": 20, 296 | "id": "922fc0e0", 297 | "metadata": {}, 298 | "outputs": [ 299 | { 300 | "name": "stdout", 301 | "output_type": "stream", 302 | "text": [ 303 | "5\n" 304 | ] 305 | } 306 | ], 307 | "source": [ 308 | "y = 3 + 2\n", 309 | "\n", 310 | "print(y)" 311 | ] 312 | }, 313 | { 314 | "cell_type": "code", 315 | "execution_count": 24, 316 | "id": "b7f10c19", 317 | "metadata": {}, 318 | "outputs": [ 319 | { 320 | "name": "stdout", 321 | "output_type": "stream", 322 | "text": [ 323 | "Ice Cream is my favorite.\n" 324 | ] 325 | } 326 | ], 327 | "source": [ 328 | "x = 'Ice Cream'\n", 329 | "y = ' is'\n", 330 | "z = ' my favorite.'\n", 331 | "\n", 332 | "print(x+y+z)" 333 | ] 334 | }, 335 | { 336 | "cell_type": "code", 337 | "execution_count": 26, 338 | "id": "897fa416", 339 | "metadata": {}, 340 | "outputs": [ 341 | { 342 | "name": "stdout", 343 | "output_type": "stream", 344 | "text": [ 345 | "6\n" 346 | ] 347 | } 348 | ], 349 | "source": [ 350 | "x = 1\n", 351 | "y = 2\n", 352 | "z = 3\n", 353 | "\n", 354 | "print(x+y+z)" 355 | ] 356 | }, 357 | { 358 | "cell_type": "code", 359 | "execution_count": 29, 360 | "id": "b8d95a8d", 361 | "metadata": {}, 362 | "outputs": [ 363 | { 364 | "name": "stdout", 365 | "output_type": "stream", 366 | "text": [ 367 | "Ice Cream 2\n" 368 | ] 369 | } 370 | ], 371 | "source": [ 372 | "x = 'Ice Cream'\n", 373 | "y = 2\n", 374 | "\n", 375 | "\n", 376 | "print(x,y)" 377 | ] 378 | } 379 | ], 380 | "metadata": { 381 | "kernelspec": { 382 | "display_name": "Python 3 (ipykernel)", 383 | "language": "python", 384 | "name": "python3" 385 | }, 386 | "language_info": { 387 | "codemirror_mode": { 388 | "name": "ipython", 389 | "version": 3 390 | }, 391 | "file_extension": ".py", 392 | "mimetype": "text/x-python", 393 | "name": "python", 394 | "nbconvert_exporter": "python", 395 | "pygments_lexer": "ipython3", 396 | "version": "3.9.12" 397 | } 398 | }, 399 | "nbformat": 4, 400 | "nbformat_minor": 5 401 | } 402 | -------------------------------------------------------------------------------- /Python Basics 101 - List Comprehension.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "attachments": {}, 5 | "cell_type": "markdown", 6 | "id": "857a5eac", 7 | "metadata": {}, 8 | "source": [ 9 | "# List Comprehension" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "id": "bd1f6620", 16 | "metadata": {}, 17 | "outputs": [ 18 | { 19 | "name": "stdout", 20 | "output_type": "stream", 21 | "text": [ 22 | "['Chocolate', 'Chocolate Fudge', 'Choco Swirl']\n" 23 | ] 24 | } 25 | ], 26 | "source": [ 27 | "ice_cream = ['Vanilla','Chocolate','Chocolate Fudge','Strawberry','Choco Swirl']\n", 28 | "chocolate_flavors = []\n", 29 | "\n", 30 | "for flavors in ice_cream:\n", 31 | " if 'Choco' in flavors:\n", 32 | " chocolate_flavors.append(flavors)\n", 33 | " \n", 34 | "print(chocolate_flavors)" 35 | ] 36 | }, 37 | { 38 | "cell_type": "code", 39 | "execution_count": 3, 40 | "id": "b1d8652b", 41 | "metadata": {}, 42 | "outputs": [ 43 | { 44 | "name": "stdout", 45 | "output_type": "stream", 46 | "text": [ 47 | "['Chocolate', 'Chocolate Fudge', 'Choco Swirl']\n" 48 | ] 49 | } 50 | ], 51 | "source": [ 52 | "ice_cream = ['Vanilla','Chocolate','Chocolate Fudge','Strawberry','Choco Swirl']\n", 53 | "\n", 54 | "chocolate_flavors = [flavors for flavors in ice_cream if 'Choco' in flavors]\n", 55 | "\n", 56 | "print(chocolate_flavors)" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": 4, 62 | "id": "52751334", 63 | "metadata": {}, 64 | "outputs": [ 65 | { 66 | "name": "stdout", 67 | "output_type": "stream", 68 | "text": [ 69 | "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n" 70 | ] 71 | } 72 | ], 73 | "source": [ 74 | "newlist = [x for x in range(10)]\n", 75 | "\n", 76 | "print(newlist)" 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": 6, 82 | "id": "65e5f737", 83 | "metadata": {}, 84 | "outputs": [ 85 | { 86 | "name": "stdout", 87 | "output_type": "stream", 88 | "text": [ 89 | "[0, 2, 4, 6, 8, 10]\n" 90 | ] 91 | } 92 | ], 93 | "source": [ 94 | "newlist = [x for x in range(11) if x % 2 ==0]\n", 95 | "\n", 96 | "print(newlist)" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": null, 102 | "id": "316736bc", 103 | "metadata": {}, 104 | "outputs": [], 105 | "source": [] 106 | }, 107 | { 108 | "cell_type": "code", 109 | "execution_count": null, 110 | "id": "07dbee5e", 111 | "metadata": {}, 112 | "outputs": [], 113 | "source": [] 114 | }, 115 | { 116 | "cell_type": "code", 117 | "execution_count": null, 118 | "id": "2b9c9f35", 119 | "metadata": {}, 120 | "outputs": [], 121 | "source": [] 122 | }, 123 | { 124 | "attachments": { 125 | "image.png": { 126 | "image/png": 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" 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" 7 | } 8 | }, 9 | "cell_type": "markdown", 10 | "id": "ac662849", 11 | "metadata": {}, 12 | "source": [ 13 | "# HTML and Inspecting a Web Page\n", 14 | "\n", 15 | "\n", 16 | "\n", 17 | "\n", 18 | "![image.png](attachment:image.png)\n", 19 | " \n", 20 | " \n", 21 | "\n", 22 | " \n", 23 | "https://www.scrapethissite.com/pages/forms/" 24 | ] 25 | }, 26 | { 27 | "cell_type": "code", 28 | "execution_count": null, 29 | "id": "c9c27b20", 30 | "metadata": {}, 31 | "outputs": [], 32 | "source": [] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": null, 37 | "id": "7274bc28", 38 | "metadata": {}, 39 | "outputs": [], 40 | "source": [] 41 | }, 42 | { 43 | "cell_type": "code", 44 | "execution_count": null, 45 | "id": "618b818d", 46 | "metadata": {}, 47 | "outputs": [], 48 | "source": [] 49 | }, 50 | { 51 | "cell_type": "code", 52 | "execution_count": null, 53 | "id": "64c12da4", 54 | "metadata": {}, 55 | "outputs": [], 56 | "source": [] 57 | }, 58 | { 59 | "cell_type": "code", 60 | "execution_count": null, 61 | "id": "3e717cc9", 62 | "metadata": {}, 63 | "outputs": [], 64 | "source": [] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": null, 69 | "id": "5248c4d6", 70 | "metadata": {}, 71 | "outputs": [], 72 | "source": [] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": null, 77 | "id": "dc3757ca", 78 | "metadata": {}, 79 | "outputs": [], 80 | "source": [] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "execution_count": null, 85 | "id": "b775e863", 86 | "metadata": {}, 87 | "outputs": [], 88 | "source": [] 89 | }, 90 | { 91 | "cell_type": "code", 92 | "execution_count": null, 93 | "id": "19060c4c", 94 | "metadata": {}, 95 | "outputs": [], 96 | "source": [] 97 | }, 98 | { 99 | "cell_type": "code", 100 | "execution_count": null, 101 | "id": "70963b15", 102 | "metadata": {}, 103 | "outputs": [], 104 | "source": [] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": null, 109 | "id": "a66d6454", 110 | "metadata": {}, 111 | "outputs": [], 112 | "source": [] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": null, 117 | "id": "94f264cb", 118 | "metadata": {}, 119 | "outputs": [], 120 | "source": [] 121 | }, 122 | { 123 | "cell_type": "code", 124 | "execution_count": null, 125 | "id": "07afca82", 126 | "metadata": {}, 127 | "outputs": [], 128 | "source": [] 129 | }, 130 | { 131 | "cell_type": "code", 132 | "execution_count": null, 133 | "id": "a26feb56", 134 | "metadata": {}, 135 | "outputs": [], 136 | "source": [] 137 | }, 138 | { 139 | "cell_type": "code", 140 | "execution_count": null, 141 | "id": "8d037aeb", 142 | "metadata": {}, 143 | "outputs": [], 144 | "source": [] 145 | }, 146 | { 147 | "cell_type": "code", 148 | "execution_count": null, 149 | "id": "47eeaa62", 150 | "metadata": {}, 151 | "outputs": [], 152 | "source": [] 153 | }, 154 | { 155 | "cell_type": "code", 156 | "execution_count": null, 157 | "id": "7674e92d", 158 | "metadata": {}, 159 | "outputs": [], 160 | "source": [] 161 | }, 162 | { 163 | "cell_type": "code", 164 | "execution_count": null, 165 | "id": "a36e5715", 166 | "metadata": {}, 167 | "outputs": [], 168 | "source": [] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": null, 173 | "id": "7f587a85", 174 | "metadata": {}, 175 | "outputs": [], 176 | "source": [] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": null, 181 | "id": "c741bd2b", 182 | "metadata": {}, 183 | "outputs": [], 184 | "source": [] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "execution_count": null, 189 | "id": "74cbef48", 190 | "metadata": {}, 191 | "outputs": [], 192 | "source": [] 193 | }, 194 | { 195 | "cell_type": "code", 196 | "execution_count": null, 197 | "id": "3ebc8540", 198 | "metadata": {}, 199 | "outputs": [], 200 | "source": [] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": null, 205 | "id": "6e592692", 206 | "metadata": {}, 207 | "outputs": [], 208 | "source": [] 209 | } 210 | ], 211 | "metadata": { 212 | "kernelspec": { 213 | "display_name": "Python 3 (ipykernel)", 214 | "language": "python", 215 | "name": "python3" 216 | }, 217 | "language_info": { 218 | "codemirror_mode": { 219 | "name": "ipython", 220 | "version": 3 221 | }, 222 | "file_extension": ".py", 223 | "mimetype": "text/x-python", 224 | "name": "python", 225 | "nbconvert_exporter": "python", 226 | "pygments_lexer": "ipython3", 227 | "version": "3.9.13" 228 | } 229 | }, 230 | "nbformat": 4, 231 | "nbformat_minor": 5 232 | } 233 | -------------------------------------------------------------------------------- /Python Basics 101 - Functions.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "attachments": {}, 5 | "cell_type": "markdown", 6 | "id": "a9534f3a", 7 | "metadata": {}, 8 | "source": [ 9 | "# Functions" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 1, 15 | "id": "1bb8a257", 16 | "metadata": {}, 17 | "outputs": [], 18 | "source": [ 19 | "def first_func():\n", 20 | " print('We did it!')" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 2, 26 | "id": "5f75cf9f", 27 | "metadata": {}, 28 | "outputs": [ 29 | { 30 | "name": "stdout", 31 | "output_type": "stream", 32 | "text": [ 33 | "We did it!\n" 34 | ] 35 | } 36 | ], 37 | "source": [ 38 | "first_func()" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 4, 44 | "id": "375847c2", 45 | "metadata": {}, 46 | "outputs": [], 47 | "source": [ 48 | "def number_squared(number):\n", 49 | " print(number**2)" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 5, 55 | "id": "98255c7b", 56 | "metadata": {}, 57 | "outputs": [ 58 | { 59 | "name": "stdout", 60 | "output_type": "stream", 61 | "text": [ 62 | "25\n" 63 | ] 64 | } 65 | ], 66 | "source": [ 67 | "number_squared(5)" 68 | ] 69 | }, 70 | { 71 | "cell_type": "code", 72 | "execution_count": 6, 73 | "id": "f23de228", 74 | "metadata": {}, 75 | "outputs": [], 76 | "source": [ 77 | "def number_squared_cust(number,power):\n", 78 | " print(number**power)" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 9, 84 | "id": "d956bb39", 85 | "metadata": {}, 86 | "outputs": [ 87 | { 88 | "name": "stdout", 89 | "output_type": "stream", 90 | "text": [ 91 | "125\n" 92 | ] 93 | } 94 | ], 95 | "source": [ 96 | "number_squared_cust(5,3)" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 12, 102 | "id": "ad75e5e6", 103 | "metadata": {}, 104 | "outputs": [], 105 | "source": [ 106 | "\n", 107 | "args_tuple = (5,6,1,2,8)\n", 108 | "\n", 109 | "def number_args(*number):\n", 110 | " print(number[0]*number[1])" 111 | ] 112 | }, 113 | { 114 | "cell_type": "code", 115 | "execution_count": 14, 116 | "id": "8c6f83d0", 117 | "metadata": {}, 118 | "outputs": [ 119 | { 120 | "name": "stdout", 121 | "output_type": "stream", 122 | "text": [ 123 | "30\n" 124 | ] 125 | } 126 | ], 127 | "source": [ 128 | "number_args(*args_tuple)" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": 15, 134 | "id": "7bb8dc07", 135 | "metadata": {}, 136 | "outputs": [], 137 | "source": [ 138 | "def number_squared_cust(number,power):\n", 139 | " print(number**power)" 140 | ] 141 | }, 142 | { 143 | "cell_type": "code", 144 | "execution_count": 18, 145 | "id": "de070529", 146 | "metadata": {}, 147 | "outputs": [ 148 | { 149 | "name": "stdout", 150 | "output_type": "stream", 151 | "text": [ 152 | "243\n" 153 | ] 154 | } 155 | ], 156 | "source": [ 157 | "number_squared_cust(power = 5,number = 3)" 158 | ] 159 | }, 160 | { 161 | "cell_type": "code", 162 | "execution_count": 28, 163 | "id": "af5b85a9", 164 | "metadata": {}, 165 | "outputs": [], 166 | "source": [ 167 | "def number_kwarg(**number):\n", 168 | " print('My number is: ' + number['integer'] + 'My other number: ' + number['integer2'])" 169 | ] 170 | }, 171 | { 172 | "cell_type": "code", 173 | "execution_count": 29, 174 | "id": "7d2bc5e8", 175 | "metadata": {}, 176 | "outputs": [ 177 | { 178 | "name": "stdout", 179 | "output_type": "stream", 180 | "text": [ 181 | "My number is: 2309My other number: 349\n" 182 | ] 183 | } 184 | ], 185 | "source": [ 186 | "number_kwarg(integer = '2309', integer2 = '349')" 187 | ] 188 | }, 189 | { 190 | "cell_type": "code", 191 | "execution_count": null, 192 | "id": "41126532", 193 | "metadata": {}, 194 | "outputs": [], 195 | "source": [] 196 | }, 197 | { 198 | "cell_type": "code", 199 | "execution_count": null, 200 | "id": "11b65aea", 201 | "metadata": {}, 202 | "outputs": [], 203 | "source": [] 204 | }, 205 | { 206 | "cell_type": "code", 207 | "execution_count": null, 208 | "id": "c28bdd56", 209 | "metadata": {}, 210 | "outputs": [], 211 | "source": [] 212 | }, 213 | { 214 | "cell_type": "code", 215 | "execution_count": null, 216 | "id": "f81e1140", 217 | "metadata": {}, 218 | "outputs": [], 219 | "source": [] 220 | }, 221 | { 222 | "attachments": { 223 | "image.png": { 224 | 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" 225 | } 226 | }, 227 | "cell_type": "markdown", 228 | "id": "619887d5", 229 | "metadata": {}, 230 | "source": [ 231 | "![image.png](attachment:image.png)" 232 | ] 233 | } 234 | ], 235 | "metadata": { 236 | "kernelspec": { 237 | "display_name": "Python 3 (ipykernel)", 238 | "language": "python", 239 | "name": "python3" 240 | }, 241 | "language_info": { 242 | "codemirror_mode": { 243 | "name": "ipython", 244 | "version": 3 245 | }, 246 | "file_extension": ".py", 247 | "mimetype": "text/x-python", 248 | "name": "python", 249 | "nbconvert_exporter": "python", 250 | "pygments_lexer": "ipython3", 251 | "version": "3.9.12" 252 | } 253 | }, 254 | "nbformat": 4, 255 | "nbformat_minor": 5 256 | } 257 | -------------------------------------------------------------------------------- /Python Basics 101 - Data Types.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "id": "3403857f", 6 | "metadata": {}, 7 | "source": [ 8 | "# Data Types" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 4, 14 | "id": "d6fde853", 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "int" 21 | ] 22 | }, 23 | "execution_count": 4, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "type(-12 + 100)" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 5, 35 | "id": "1c6ee3b5", 36 | "metadata": {}, 37 | "outputs": [ 38 | { 39 | "data": { 40 | "text/plain": [ 41 | "float" 42 | ] 43 | }, 44 | "execution_count": 5, 45 | "metadata": {}, 46 | "output_type": "execute_result" 47 | } 48 | ], 49 | "source": [ 50 | "type(12 + 10.25)" 51 | ] 52 | }, 53 | { 54 | "cell_type": "code", 55 | "execution_count": 8, 56 | "id": "84a2358e", 57 | "metadata": {}, 58 | "outputs": [ 59 | { 60 | "data": { 61 | "text/plain": [ 62 | "complex" 63 | ] 64 | }, 65 | "execution_count": 8, 66 | "metadata": {}, 67 | "output_type": "execute_result" 68 | } 69 | ], 70 | "source": [ 71 | "type(12 + 3j)" 72 | ] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": 13, 77 | "id": "75dd7320", 78 | "metadata": {}, 79 | "outputs": [ 80 | { 81 | "data": { 82 | "text/plain": [ 83 | "bool" 84 | ] 85 | }, 86 | "execution_count": 13, 87 | "metadata": {}, 88 | "output_type": "execute_result" 89 | } 90 | ], 91 | "source": [ 92 | "#Boolean\n", 93 | "\n", 94 | "type(1 > 5)" 95 | ] 96 | }, 97 | { 98 | "cell_type": "code", 99 | "execution_count": 15, 100 | "id": "a9cb0ff9", 101 | "metadata": {}, 102 | "outputs": [ 103 | { 104 | "data": { 105 | "text/plain": [ 106 | "True" 107 | ] 108 | }, 109 | "execution_count": 15, 110 | "metadata": {}, 111 | "output_type": "execute_result" 112 | } 113 | ], 114 | "source": [ 115 | "1 == 1" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 16, 121 | "id": "00fe9772", 122 | "metadata": {}, 123 | "outputs": [ 124 | { 125 | "data": { 126 | "text/plain": [ 127 | "'Single Quote'" 128 | ] 129 | }, 130 | "execution_count": 16, 131 | "metadata": {}, 132 | "output_type": "execute_result" 133 | } 134 | ], 135 | "source": [ 136 | "# Strings\n", 137 | "\n", 138 | "'Single Quote'" 139 | ] 140 | }, 141 | { 142 | "cell_type": "code", 143 | "execution_count": 17, 144 | "id": "63d73681", 145 | "metadata": {}, 146 | "outputs": [ 147 | { 148 | "data": { 149 | "text/plain": [ 150 | "'Double Quote'" 151 | ] 152 | }, 153 | "execution_count": 17, 154 | "metadata": {}, 155 | "output_type": "execute_result" 156 | } 157 | ], 158 | "source": [ 159 | "\"Double Quote\"" 160 | ] 161 | }, 162 | { 163 | "cell_type": "code", 164 | "execution_count": 23, 165 | "id": "d90a602f", 166 | "metadata": {}, 167 | "outputs": [], 168 | "source": [ 169 | "multiline = \"\"\"\n", 170 | "The ice cream vanquished\n", 171 | "my longing for sweets,\n", 172 | "upon this diet I look away,\n", 173 | "it no longer exists on this day.\n", 174 | "\n", 175 | "\"\"\"" 176 | ] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": 24, 181 | "id": "048c3402", 182 | "metadata": {}, 183 | "outputs": [ 184 | { 185 | "name": "stdout", 186 | "output_type": "stream", 187 | "text": [ 188 | "\n", 189 | "The ice cream vanquished\n", 190 | "my longing for sweets,\n", 191 | "upon this diet I look away,\n", 192 | "it no longer exists on this day.\n", 193 | "\n", 194 | "\n" 195 | ] 196 | } 197 | ], 198 | "source": [ 199 | "print(multiline)" 200 | ] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": null, 205 | "id": "b285e18d", 206 | "metadata": {}, 207 | "outputs": [], 208 | "source": [ 209 | "\"\"\"\n", 210 | "I've always wanted to eat a gallon of \"ice cream.\"\n", 211 | "\"\"\"" 212 | ] 213 | }, 214 | { 215 | "cell_type": "code", 216 | "execution_count": 25, 217 | "id": "f753eb08", 218 | "metadata": {}, 219 | "outputs": [ 220 | { 221 | "data": { 222 | "text/plain": [ 223 | "str" 224 | ] 225 | }, 226 | "execution_count": 25, 227 | "metadata": {}, 228 | "output_type": "execute_result" 229 | } 230 | ], 231 | "source": [ 232 | "type(multiline)" 233 | ] 234 | }, 235 | { 236 | "cell_type": "code", 237 | "execution_count": 26, 238 | "id": "824fea24", 239 | "metadata": {}, 240 | "outputs": [], 241 | "source": [ 242 | "a = 'Hello World!'" 243 | ] 244 | }, 245 | { 246 | "cell_type": "code", 247 | "execution_count": 31, 248 | "id": "7d267a75", 249 | "metadata": {}, 250 | "outputs": [ 251 | { 252 | "name": "stdout", 253 | "output_type": "stream", 254 | "text": [ 255 | "llo\n" 256 | ] 257 | } 258 | ], 259 | "source": [ 260 | "print(a[2:5])" 261 | ] 262 | }, 263 | { 264 | "cell_type": "code", 265 | "execution_count": 32, 266 | "id": "3893bd14", 267 | "metadata": {}, 268 | "outputs": [ 269 | { 270 | "data": { 271 | "text/plain": [ 272 | "'Hello World!Hello World!Hello World!'" 273 | ] 274 | }, 275 | "execution_count": 32, 276 | "metadata": {}, 277 | "output_type": "execute_result" 278 | } 279 | ], 280 | "source": [ 281 | "a*3" 282 | ] 283 | }, 284 | { 285 | "cell_type": "code", 286 | "execution_count": 33, 287 | "id": "b9aa6c3b", 288 | "metadata": {}, 289 | "outputs": [ 290 | { 291 | "data": { 292 | "text/plain": [ 293 | "'Hello World!Hello World!'" 294 | ] 295 | }, 296 | "execution_count": 33, 297 | "metadata": {}, 298 | "output_type": "execute_result" 299 | } 300 | ], 301 | "source": [ 302 | "a + a " 303 | ] 304 | }, 305 | { 306 | "cell_type": "code", 307 | "execution_count": 34, 308 | "id": "4bdb2e80", 309 | "metadata": {}, 310 | "outputs": [ 311 | { 312 | "data": { 313 | "text/plain": [ 314 | "[1, 2, 3]" 315 | ] 316 | }, 317 | "execution_count": 34, 318 | "metadata": {}, 319 | "output_type": "execute_result" 320 | } 321 | ], 322 | "source": [ 323 | "# list\n", 324 | "\n", 325 | "[1,2,3]" 326 | ] 327 | }, 328 | { 329 | "cell_type": "code", 330 | "execution_count": 35, 331 | "id": "3e9e44bd", 332 | "metadata": {}, 333 | "outputs": [ 334 | { 335 | "data": { 336 | "text/plain": [ 337 | "['Cookie Dough', 'Strawberry', 'Chocolate']" 338 | ] 339 | }, 340 | "execution_count": 35, 341 | "metadata": {}, 342 | "output_type": "execute_result" 343 | } 344 | ], 345 | "source": [ 346 | "['Cookie Dough','Strawberry','Chocolate']" 347 | ] 348 | }, 349 | { 350 | "cell_type": "code", 351 | "execution_count": 36, 352 | "id": "fca2cf9c", 353 | "metadata": {}, 354 | "outputs": [ 355 | { 356 | "data": { 357 | "text/plain": [ 358 | "['Vanilla', 3, ['Scoops', 'Spoon'], True]" 359 | ] 360 | }, 361 | "execution_count": 36, 362 | "metadata": {}, 363 | "output_type": "execute_result" 364 | } 365 | ], 366 | "source": [ 367 | "['Vanilla', 3, ['Scoops','Spoon'],True]" 368 | ] 369 | }, 370 | { 371 | "cell_type": "code", 372 | "execution_count": 37, 373 | "id": "d96f89ef", 374 | "metadata": {}, 375 | "outputs": [ 376 | { 377 | "data": { 378 | "text/plain": [ 379 | "['Cookie Dough', 'Strawberry', 'Chocolate', 'Salted Caramel']" 380 | ] 381 | }, 382 | "execution_count": 37, 383 | "metadata": {}, 384 | "output_type": "execute_result" 385 | } 386 | ], 387 | "source": [ 388 | "ice_cream = ['Cookie Dough','Strawberry','Chocolate']\n", 389 | "\n", 390 | "ice_cream.append('Salted Caramel')\n", 391 | "\n", 392 | "ice_cream" 393 | ] 394 | }, 395 | { 396 | "cell_type": "code", 397 | "execution_count": 38, 398 | "id": "7fdd960c", 399 | "metadata": {}, 400 | "outputs": [ 401 | { 402 | "data": { 403 | "text/plain": [ 404 | "['Butter Pecan', 'Strawberry', 'Chocolate', 'Salted Caramel']" 405 | ] 406 | }, 407 | "execution_count": 38, 408 | "metadata": {}, 409 | "output_type": "execute_result" 410 | } 411 | ], 412 | "source": [ 413 | "ice_cream[0] = 'Butter Pecan'\n", 414 | "\n", 415 | "ice_cream" 416 | ] 417 | }, 418 | { 419 | "cell_type": "code", 420 | "execution_count": 39, 421 | "id": "4d9a1834", 422 | "metadata": {}, 423 | "outputs": [], 424 | "source": [ 425 | "nest_list = ['Vanilla', 3, ['Scoops','Spoon'],True]" 426 | ] 427 | }, 428 | { 429 | "cell_type": "code", 430 | "execution_count": 42, 431 | "id": "ceccf35b", 432 | "metadata": {}, 433 | "outputs": [ 434 | { 435 | "data": { 436 | "text/plain": [ 437 | "'Spoon'" 438 | ] 439 | }, 440 | "execution_count": 42, 441 | "metadata": {}, 442 | "output_type": "execute_result" 443 | } 444 | ], 445 | "source": [ 446 | "nest_list[2][1]" 447 | ] 448 | }, 449 | { 450 | "cell_type": "code", 451 | "execution_count": 43, 452 | "id": "c5e0c40e", 453 | "metadata": {}, 454 | "outputs": [], 455 | "source": [ 456 | "#tuple\n", 457 | "\n", 458 | "tuple_scoops = (1,2,3,2,1)" 459 | ] 460 | }, 461 | { 462 | "cell_type": "code", 463 | "execution_count": 44, 464 | "id": "62e9b0b7", 465 | "metadata": {}, 466 | "outputs": [ 467 | { 468 | "data": { 469 | "text/plain": [ 470 | "tuple" 471 | ] 472 | }, 473 | "execution_count": 44, 474 | "metadata": {}, 475 | "output_type": "execute_result" 476 | } 477 | ], 478 | "source": [ 479 | "type(tuple_scoops)" 480 | ] 481 | }, 482 | { 483 | "cell_type": "code", 484 | "execution_count": 45, 485 | "id": "69c86af2", 486 | "metadata": {}, 487 | "outputs": [ 488 | { 489 | "data": { 490 | "text/plain": [ 491 | "1" 492 | ] 493 | }, 494 | "execution_count": 45, 495 | "metadata": {}, 496 | "output_type": "execute_result" 497 | } 498 | ], 499 | "source": [ 500 | "tuple_scoops[0]" 501 | ] 502 | }, 503 | { 504 | "cell_type": "code", 505 | "execution_count": 46, 506 | "id": "0fb925e7", 507 | "metadata": {}, 508 | "outputs": [ 509 | { 510 | "ename": "AttributeError", 511 | "evalue": "'tuple' object has no attribute 'append'", 512 | "output_type": "error", 513 | "traceback": [ 514 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", 515 | "\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)", 516 | "Input \u001b[1;32mIn [46]\u001b[0m, in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mtuple_scoops\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m(\u001b[38;5;241m3\u001b[39m)\n", 517 | "\u001b[1;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'" 518 | ] 519 | } 520 | ], 521 | "source": [ 522 | "tuple_scoops.append(3)" 523 | ] 524 | }, 525 | { 526 | "cell_type": "code", 527 | "execution_count": 47, 528 | "id": "e92ce72c", 529 | "metadata": {}, 530 | "outputs": [], 531 | "source": [ 532 | "# sets\n", 533 | "\n", 534 | "\n", 535 | "daily_pints = {1,2,3}" 536 | ] 537 | }, 538 | { 539 | "cell_type": "code", 540 | "execution_count": 49, 541 | "id": "950beaad", 542 | "metadata": {}, 543 | "outputs": [ 544 | { 545 | "data": { 546 | "text/plain": [ 547 | "set" 548 | ] 549 | }, 550 | "execution_count": 49, 551 | "metadata": {}, 552 | "output_type": "execute_result" 553 | } 554 | ], 555 | "source": [ 556 | "type(daily_pints)" 557 | ] 558 | }, 559 | { 560 | "cell_type": "code", 561 | "execution_count": 50, 562 | "id": "73f55a86", 563 | "metadata": {}, 564 | "outputs": [ 565 | { 566 | "name": "stdout", 567 | "output_type": "stream", 568 | "text": [ 569 | "{1, 2, 3}\n" 570 | ] 571 | } 572 | ], 573 | "source": [ 574 | "print(daily_pints)" 575 | ] 576 | }, 577 | { 578 | "cell_type": "code", 579 | "execution_count": 51, 580 | "id": "9c5810f4", 581 | "metadata": {}, 582 | "outputs": [ 583 | { 584 | "name": "stdout", 585 | "output_type": "stream", 586 | "text": [ 587 | "{1, 2, 3, 4, 5, 6, 31}\n" 588 | ] 589 | } 590 | ], 591 | "source": [ 592 | "daily_pints_log = {1,2,31,2,3,4,1,2,5,6,3,2}\n", 593 | "\n", 594 | "print(daily_pints_log)" 595 | ] 596 | }, 597 | { 598 | "cell_type": "code", 599 | "execution_count": 53, 600 | "id": "67a2f904", 601 | "metadata": {}, 602 | "outputs": [], 603 | "source": [ 604 | "wifes_daily_pints_log = {1,3,5,7,3,24,5,7,3,2,0}" 605 | ] 606 | }, 607 | { 608 | "cell_type": "code", 609 | "execution_count": 54, 610 | "id": "b4956b32", 611 | "metadata": {}, 612 | "outputs": [ 613 | { 614 | "name": "stdout", 615 | "output_type": "stream", 616 | "text": [ 617 | "{0, 1, 2, 3, 4, 5, 6, 7, 24, 31}\n" 618 | ] 619 | } 620 | ], 621 | "source": [ 622 | "print(daily_pints_log | wifes_daily_pints_log)" 623 | ] 624 | }, 625 | { 626 | "cell_type": "code", 627 | "execution_count": 55, 628 | "id": "b4431472", 629 | "metadata": {}, 630 | "outputs": [ 631 | { 632 | "name": "stdout", 633 | "output_type": "stream", 634 | "text": [ 635 | "{1, 2, 3, 5}\n" 636 | ] 637 | } 638 | ], 639 | "source": [ 640 | "print(daily_pints_log & wifes_daily_pints_log)" 641 | ] 642 | }, 643 | { 644 | "cell_type": "code", 645 | "execution_count": 57, 646 | "id": "a141db95", 647 | "metadata": {}, 648 | "outputs": [ 649 | { 650 | "name": "stdout", 651 | "output_type": "stream", 652 | "text": [ 653 | "{0, 24, 7}\n" 654 | ] 655 | } 656 | ], 657 | "source": [ 658 | "print(wifes_daily_pints_log - daily_pints_log )" 659 | ] 660 | }, 661 | { 662 | "cell_type": "code", 663 | "execution_count": 58, 664 | "id": "bb3d7aea", 665 | "metadata": {}, 666 | "outputs": [ 667 | { 668 | "name": "stdout", 669 | "output_type": "stream", 670 | "text": [ 671 | "{0, 4, 6, 7, 24, 31}\n" 672 | ] 673 | } 674 | ], 675 | "source": [ 676 | "print(wifes_daily_pints_log ^ daily_pints_log )" 677 | ] 678 | }, 679 | { 680 | "cell_type": "code", 681 | "execution_count": 59, 682 | "id": "822e9010", 683 | "metadata": {}, 684 | "outputs": [], 685 | "source": [ 686 | "# dictionaries\n", 687 | "# Key/Value Pair\n", 688 | "\n", 689 | "dict_cream = {'name': 'Alex Freberg', 'weekly intake': 5, 'favorite ice creams': ['MCC','Chocolate']}" 690 | ] 691 | }, 692 | { 693 | "cell_type": "code", 694 | "execution_count": 60, 695 | "id": "925daa00", 696 | "metadata": {}, 697 | "outputs": [ 698 | { 699 | "data": { 700 | "text/plain": [ 701 | "dict" 702 | ] 703 | }, 704 | "execution_count": 60, 705 | "metadata": {}, 706 | "output_type": "execute_result" 707 | } 708 | ], 709 | "source": [ 710 | "type(dict_cream)" 711 | ] 712 | }, 713 | { 714 | "cell_type": "code", 715 | "execution_count": 61, 716 | "id": "6bc1cedd", 717 | "metadata": {}, 718 | "outputs": [ 719 | { 720 | "name": "stdout", 721 | "output_type": "stream", 722 | "text": [ 723 | "{'name': 'Alex Freberg', 'weekly intake': 5, 'favorite ice creams': ['MCC', 'Chocolate']}\n" 724 | ] 725 | } 726 | ], 727 | "source": [ 728 | "print(dict_cream)" 729 | ] 730 | }, 731 | { 732 | "cell_type": "code", 733 | "execution_count": 62, 734 | "id": "cf9782cf", 735 | "metadata": {}, 736 | "outputs": [ 737 | { 738 | "data": { 739 | "text/plain": [ 740 | "dict_values(['Alex Freberg', 5, ['MCC', 'Chocolate']])" 741 | ] 742 | }, 743 | "execution_count": 62, 744 | "metadata": {}, 745 | "output_type": "execute_result" 746 | } 747 | ], 748 | "source": [ 749 | "dict_cream.values()" 750 | ] 751 | }, 752 | { 753 | "cell_type": "code", 754 | "execution_count": 64, 755 | "id": "7d77ebf6", 756 | "metadata": {}, 757 | "outputs": [ 758 | { 759 | "data": { 760 | "text/plain": [ 761 | "dict_keys(['name', 'weekly intake', 'favorite ice creams'])" 762 | ] 763 | }, 764 | "execution_count": 64, 765 | "metadata": {}, 766 | "output_type": "execute_result" 767 | } 768 | ], 769 | "source": [ 770 | "dict_cream.keys()" 771 | ] 772 | }, 773 | { 774 | "cell_type": "code", 775 | "execution_count": 65, 776 | "id": "2d1708b5", 777 | "metadata": {}, 778 | "outputs": [ 779 | { 780 | "data": { 781 | "text/plain": [ 782 | "dict_items([('name', 'Alex Freberg'), ('weekly intake', 5), ('favorite ice creams', ['MCC', 'Chocolate'])])" 783 | ] 784 | }, 785 | "execution_count": 65, 786 | "metadata": {}, 787 | "output_type": "execute_result" 788 | } 789 | ], 790 | "source": [ 791 | "dict_cream.items()" 792 | ] 793 | }, 794 | { 795 | "cell_type": "code", 796 | "execution_count": 67, 797 | "id": "4287746f", 798 | "metadata": {}, 799 | "outputs": [ 800 | { 801 | "data": { 802 | "text/plain": [ 803 | "'Alex Freberg'" 804 | ] 805 | }, 806 | "execution_count": 67, 807 | "metadata": {}, 808 | "output_type": "execute_result" 809 | } 810 | ], 811 | "source": [ 812 | "dict_cream['name']" 813 | ] 814 | }, 815 | { 816 | "cell_type": "code", 817 | "execution_count": 68, 818 | "id": "79fab68b", 819 | "metadata": {}, 820 | "outputs": [ 821 | { 822 | "name": "stdout", 823 | "output_type": "stream", 824 | "text": [ 825 | "{'name': 'Christine Freberg', 'weekly intake': 5, 'favorite ice creams': ['MCC', 'Chocolate']}\n" 826 | ] 827 | } 828 | ], 829 | "source": [ 830 | "dict_cream['name'] = 'Christine Freberg'\n", 831 | "\n", 832 | "print(dict_cream)" 833 | ] 834 | }, 835 | { 836 | "cell_type": "code", 837 | "execution_count": 70, 838 | "id": "6ec7c87f", 839 | "metadata": {}, 840 | "outputs": [ 841 | { 842 | "name": "stdout", 843 | "output_type": "stream", 844 | "text": [ 845 | "{'name': 'Christine Freberg', 'weekly intake': 10, 'favorite ice creams': ['MCC', 'Chocolate'], 'weight': 300}\n" 846 | ] 847 | } 848 | ], 849 | "source": [ 850 | "dict_cream.update({'name': 'Christine Freberg', 'weekly intake': 10, 'weight': 300})\n", 851 | "\n", 852 | "print(dict_cream)" 853 | ] 854 | }, 855 | { 856 | "cell_type": "code", 857 | "execution_count": 71, 858 | "id": "70cc2154", 859 | "metadata": {}, 860 | "outputs": [ 861 | { 862 | "name": "stdout", 863 | "output_type": "stream", 864 | "text": [ 865 | "{'name': 'Christine Freberg', 'weekly intake': 10, 'favorite ice creams': ['MCC', 'Chocolate']}\n" 866 | ] 867 | } 868 | ], 869 | "source": [ 870 | "del dict_cream['weight']\n", 871 | "\n", 872 | "print(dict_cream)" 873 | ] 874 | }, 875 | { 876 | "cell_type": "code", 877 | "execution_count": null, 878 | "id": "9a99a17f", 879 | "metadata": {}, 880 | "outputs": [], 881 | "source": [] 882 | }, 883 | { 884 | "cell_type": "code", 885 | "execution_count": null, 886 | "id": "f82ec801", 887 | "metadata": {}, 888 | "outputs": [], 889 | "source": [] 890 | }, 891 | { 892 | "cell_type": "code", 893 | "execution_count": null, 894 | "id": "cb6a2afb", 895 | "metadata": {}, 896 | "outputs": [], 897 | "source": [] 898 | }, 899 | { 900 | "cell_type": "code", 901 | "execution_count": null, 902 | "id": "c04a3cbc", 903 | "metadata": {}, 904 | "outputs": [], 905 | "source": [] 906 | }, 907 | { 908 | "cell_type": "code", 909 | "execution_count": null, 910 | "id": "3e90e3ff", 911 | "metadata": {}, 912 | "outputs": [], 913 | "source": [] 914 | }, 915 | { 916 | "cell_type": "code", 917 | "execution_count": null, 918 | "id": "7a4ea17f", 919 | "metadata": {}, 920 | "outputs": [], 921 | "source": [] 922 | }, 923 | { 924 | "cell_type": "code", 925 | "execution_count": null, 926 | "id": "cb94ee78", 927 | "metadata": {}, 928 | "outputs": [], 929 | "source": [] 930 | } 931 | ], 932 | "metadata": { 933 | "kernelspec": { 934 | "display_name": "Python 3 (ipykernel)", 935 | "language": "python", 936 | "name": "python3" 937 | }, 938 | "language_info": { 939 | "codemirror_mode": { 940 | "name": "ipython", 941 | "version": 3 942 | }, 943 | "file_extension": ".py", 944 | "mimetype": "text/x-python", 945 | "name": "python", 946 | "nbconvert_exporter": "python", 947 | "pygments_lexer": "ipython3", 948 | "version": "3.9.12" 949 | } 950 | }, 951 | "nbformat": 4, 952 | "nbformat_minor": 5 953 | } 954 | -------------------------------------------------------------------------------- /Regex Metacharacters.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "attachments": { 5 | "image.png": { 6 | "image/png": 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" 7 | } 8 | }, 9 | "cell_type": "markdown", 10 | "id": "8c99beea", 11 | "metadata": {}, 12 | "source": [ 13 | "# Regex Meta-characters\n", 14 | "\n", 15 | "![image.png](attachment:image.png)" 16 | ] 17 | }, 18 | { 19 | "cell_type": "code", 20 | "execution_count": 1, 21 | "id": "cf401264", 22 | "metadata": {}, 23 | "outputs": [], 24 | "source": [ 25 | "import re" 26 | ] 27 | }, 28 | { 29 | "cell_type": "code", 30 | "execution_count": 7, 31 | "id": "1e7657e5", 32 | "metadata": {}, 33 | "outputs": [ 34 | { 35 | "data": { 36 | "text/plain": [ 37 | "['I',\n", 38 | " 'l',\n", 39 | " 'i',\n", 40 | " 'k',\n", 41 | " 'e',\n", 42 | " 't',\n", 43 | " 'h',\n", 44 | " 'e',\n", 45 | " 'm',\n", 46 | " 'o',\n", 47 | " 'u',\n", 48 | " 'n',\n", 49 | " 't',\n", 50 | " 'a',\n", 51 | " 'i',\n", 52 | " 'n',\n", 53 | " 's',\n", 54 | " 'i',\n", 55 | " 'n',\n", 56 | " 't',\n", 57 | " 'h',\n", 58 | " 'e',\n", 59 | " 's',\n", 60 | " 'p',\n", 61 | " 'r',\n", 62 | " 'i',\n", 63 | " 'n',\n", 64 | " 'g',\n", 65 | " '2',\n", 66 | " '3',\n", 67 | " '4',\n", 68 | " '0',\n", 69 | " '9',\n", 70 | " '8']" 71 | ] 72 | }, 73 | "execution_count": 7, 74 | "metadata": {}, 75 | "output_type": "execute_result" 76 | } 77 | ], 78 | "source": [ 79 | "string = 'I like the mountains in the spring. 234098'\n", 80 | "\n", 81 | "re.findall('[a-zA-Z0-9]',string)" 82 | ] 83 | }, 84 | { 85 | "cell_type": "code", 86 | "execution_count": 8, 87 | "id": "388fee19", 88 | "metadata": {}, 89 | "outputs": [ 90 | { 91 | "data": { 92 | "text/plain": [ 93 | "['1', '2', '3', '4']" 94 | ] 95 | }, 96 | "execution_count": 8, 97 | "metadata": {}, 98 | "output_type": "execute_result" 99 | } 100 | ], 101 | "source": [ 102 | "string = 'I have 123,456 koalas!'\n", 103 | "\n", 104 | "re.findall('[0-4]', string)" 105 | ] 106 | }, 107 | { 108 | "cell_type": "code", 109 | "execution_count": 12, 110 | "id": "8c010f2e", 111 | "metadata": {}, 112 | "outputs": [ 113 | { 114 | "data": { 115 | "text/plain": [ 116 | "['sea', 'sea', 'sba']" 117 | ] 118 | }, 119 | "execution_count": 12, 120 | "metadata": {}, 121 | "output_type": "execute_result" 122 | } 123 | ], 124 | "source": [ 125 | "string = 'You can see sea shells by the sea shore. sba'\n", 126 | "\n", 127 | "re.findall('s.a', string)" 128 | ] 129 | }, 130 | { 131 | "cell_type": "code", 132 | "execution_count": 13, 133 | "id": "909d1aa3", 134 | "metadata": {}, 135 | "outputs": [ 136 | { 137 | "data": { 138 | "text/plain": [ 139 | "['sea', 'sea', 'sba']" 140 | ] 141 | }, 142 | "execution_count": 13, 143 | "metadata": {}, 144 | "output_type": "execute_result" 145 | } 146 | ], 147 | "source": [ 148 | "string = 'You can see sea shells by the sea shore. sba'\n", 149 | "\n", 150 | "re.findall('s.{}a', string)" 151 | ] 152 | }, 153 | { 154 | "cell_type": "code", 155 | "execution_count": 14, 156 | "id": "f4abbf5f", 157 | "metadata": {}, 158 | "outputs": [ 159 | { 160 | "data": { 161 | "text/plain": [ 162 | "['Well', 'Will']" 163 | ] 164 | }, 165 | "execution_count": 14, 166 | "metadata": {}, 167 | "output_type": "execute_result" 168 | } 169 | ], 170 | "source": [ 171 | "string = \"Well well well... if it isn't Will Wilmer\"\n", 172 | "\n", 173 | "re.findall('W.{2}l', string)" 174 | ] 175 | }, 176 | { 177 | "cell_type": "code", 178 | "execution_count": null, 179 | "id": "adf164e7", 180 | "metadata": {}, 181 | "outputs": [], 182 | "source": [ 183 | "# $ ^" 184 | ] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "execution_count": 17, 189 | "id": "b990f664", 190 | "metadata": {}, 191 | "outputs": [ 192 | { 193 | "data": { 194 | "text/plain": [ 195 | "[]" 196 | ] 197 | }, 198 | "execution_count": 17, 199 | "metadata": {}, 200 | "output_type": "execute_result" 201 | } 202 | ], 203 | "source": [ 204 | "string = 'Happy birthday to you. Happy birthday to you. Happy birthday dear Alex, happy birthday to you.'\n", 205 | "\n", 206 | "re.findall('^you', string)" 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": 19, 212 | "id": "cf7e3dfb", 213 | "metadata": {}, 214 | "outputs": [ 215 | { 216 | "data": { 217 | "text/plain": [ 218 | "['you.']" 219 | ] 220 | }, 221 | "execution_count": 19, 222 | "metadata": {}, 223 | "output_type": "execute_result" 224 | } 225 | ], 226 | "source": [ 227 | "re.findall('you.$', string)" 228 | ] 229 | }, 230 | { 231 | "cell_type": "code", 232 | "execution_count": null, 233 | "id": "6120fd6f", 234 | "metadata": {}, 235 | "outputs": [], 236 | "source": [ 237 | "# * - zero or more\n", 238 | "# + - one or more\n", 239 | "# ? -zero or one" 240 | ] 241 | }, 242 | { 243 | "cell_type": "code", 244 | "execution_count": 27, 245 | "id": "37421cf6", 246 | "metadata": {}, 247 | "outputs": [ 248 | { 249 | "data": { 250 | "text/plain": [ 251 | "['This Thing called a Thimble ha Thrice hurt me']" 252 | ] 253 | }, 254 | "execution_count": 27, 255 | "metadata": {}, 256 | "output_type": "execute_result" 257 | } 258 | ], 259 | "source": [ 260 | "string = 'This Thing called a Thimble ha Thrice hurt me'\n", 261 | "\n", 262 | "re.findall('Thi.*e', string)" 263 | ] 264 | }, 265 | { 266 | "cell_type": "code", 267 | "execution_count": 28, 268 | "id": "6db706d6", 269 | "metadata": {}, 270 | "outputs": [ 271 | { 272 | "data": { 273 | "text/plain": [ 274 | "['This Thing called a Thimble ha Thrice hurt me']" 275 | ] 276 | }, 277 | "execution_count": 28, 278 | "metadata": {}, 279 | "output_type": "execute_result" 280 | } 281 | ], 282 | "source": [ 283 | "string = 'This Thing called a Thimble ha Thrice hurt me'\n", 284 | "\n", 285 | "re.findall('Thi.+e', string)" 286 | ] 287 | }, 288 | { 289 | "cell_type": "code", 290 | "execution_count": 30, 291 | "id": "da223f8e", 292 | "metadata": {}, 293 | "outputs": [ 294 | { 295 | "data": { 296 | "text/plain": [ 297 | "['Thimble']" 298 | ] 299 | }, 300 | "execution_count": 30, 301 | "metadata": {}, 302 | "output_type": "execute_result" 303 | } 304 | ], 305 | "source": [ 306 | "string = 'This Thing called a Thimble ha Thrice hurt me'\n", 307 | "\n", 308 | "re.findall('Thi.{3}?e', string)" 309 | ] 310 | }, 311 | { 312 | "cell_type": "code", 313 | "execution_count": 32, 314 | "id": "2472b636", 315 | "metadata": {}, 316 | "outputs": [ 317 | { 318 | "data": { 319 | "text/plain": [ 320 | "['beautiful']" 321 | ] 322 | }, 323 | "execution_count": 32, 324 | "metadata": {}, 325 | "output_type": "execute_result" 326 | } 327 | ], 328 | "source": [ 329 | "string = 'I hate that I love balloon animals. They are beautiful.'\n", 330 | "\n", 331 | "re.findall('lovely|beautiful', string)" 332 | ] 333 | }, 334 | { 335 | "cell_type": "code", 336 | "execution_count": 36, 337 | "id": "489e656b", 338 | "metadata": {}, 339 | "outputs": [ 340 | { 341 | "data": { 342 | "text/plain": [ 343 | "['?']" 344 | ] 345 | }, 346 | "execution_count": 36, 347 | "metadata": {}, 348 | "output_type": "execute_result" 349 | } 350 | ], 351 | "source": [ 352 | "string = 'I like cats. You like cats? We all like cats.'\n", 353 | "\n", 354 | "re.findall('\\?',string)" 355 | ] 356 | }, 357 | { 358 | "cell_type": "code", 359 | "execution_count": null, 360 | "id": "2c68d922", 361 | "metadata": {}, 362 | "outputs": [], 363 | "source": [] 364 | }, 365 | { 366 | "cell_type": "code", 367 | "execution_count": null, 368 | "id": "e3ee7364", 369 | "metadata": {}, 370 | "outputs": [], 371 | "source": [] 372 | }, 373 | { 374 | "cell_type": "code", 375 | "execution_count": null, 376 | "id": "59c11d92", 377 | "metadata": {}, 378 | "outputs": [], 379 | "source": [] 380 | }, 381 | { 382 | "cell_type": "code", 383 | "execution_count": null, 384 | "id": "d7d64da6", 385 | "metadata": {}, 386 | "outputs": [], 387 | "source": [] 388 | }, 389 | { 390 | "cell_type": "code", 391 | "execution_count": null, 392 | "id": "67d54a26", 393 | "metadata": {}, 394 | "outputs": [], 395 | "source": [] 396 | }, 397 | { 398 | "cell_type": "code", 399 | "execution_count": null, 400 | "id": "e5fae6eb", 401 | "metadata": {}, 402 | "outputs": [], 403 | "source": [] 404 | }, 405 | { 406 | "cell_type": "code", 407 | "execution_count": null, 408 | "id": "5f489040", 409 | "metadata": {}, 410 | "outputs": [], 411 | "source": [] 412 | }, 413 | { 414 | "cell_type": "code", 415 | "execution_count": null, 416 | "id": "d1cf0912", 417 | "metadata": {}, 418 | "outputs": [], 419 | "source": [] 420 | }, 421 | { 422 | "cell_type": "code", 423 | "execution_count": null, 424 | "id": "1a928c3d", 425 | "metadata": {}, 426 | "outputs": [], 427 | "source": [] 428 | }, 429 | { 430 | "cell_type": "code", 431 | "execution_count": null, 432 | "id": "cfc032b4", 433 | "metadata": {}, 434 | "outputs": [], 435 | "source": [] 436 | }, 437 | { 438 | "cell_type": "code", 439 | "execution_count": null, 440 | "id": "95a4e052", 441 | "metadata": {}, 442 | "outputs": [], 443 | "source": [] 444 | }, 445 | { 446 | "cell_type": "code", 447 | "execution_count": null, 448 | "id": "f5045f66", 449 | "metadata": {}, 450 | "outputs": [], 451 | "source": [] 452 | }, 453 | { 454 | "cell_type": "code", 455 | "execution_count": null, 456 | "id": "72648cdb", 457 | "metadata": {}, 458 | "outputs": [], 459 | "source": [] 460 | }, 461 | { 462 | "cell_type": "code", 463 | "execution_count": null, 464 | "id": "a89c61ff", 465 | "metadata": {}, 466 | "outputs": [], 467 | "source": [] 468 | }, 469 | { 470 | "cell_type": "code", 471 | "execution_count": null, 472 | "id": "c78cf1f8", 473 | "metadata": {}, 474 | "outputs": [], 475 | "source": [] 476 | }, 477 | { 478 | "cell_type": "code", 479 | "execution_count": null, 480 | "id": "85109edf", 481 | "metadata": {}, 482 | "outputs": [], 483 | "source": [] 484 | }, 485 | { 486 | "cell_type": "code", 487 | "execution_count": null, 488 | "id": "6e5c52fe", 489 | "metadata": {}, 490 | "outputs": [], 491 | "source": [] 492 | }, 493 | { 494 | "cell_type": "code", 495 | "execution_count": null, 496 | "id": "721ae70c", 497 | "metadata": {}, 498 | "outputs": [], 499 | "source": [] 500 | }, 501 | { 502 | "cell_type": "code", 503 | "execution_count": null, 504 | "id": "d03a5052", 505 | "metadata": {}, 506 | "outputs": [], 507 | "source": [] 508 | }, 509 | { 510 | "cell_type": "code", 511 | "execution_count": null, 512 | "id": "5200ee84", 513 | "metadata": {}, 514 | "outputs": [], 515 | "source": [] 516 | }, 517 | { 518 | "cell_type": "code", 519 | "execution_count": null, 520 | "id": "1cf14886", 521 | "metadata": {}, 522 | "outputs": [], 523 | "source": [] 524 | }, 525 | { 526 | "cell_type": "code", 527 | "execution_count": null, 528 | "id": "3612e894", 529 | "metadata": {}, 530 | "outputs": [], 531 | "source": [] 532 | }, 533 | { 534 | "cell_type": "code", 535 | "execution_count": null, 536 | "id": "81672121", 537 | "metadata": {}, 538 | "outputs": [], 539 | "source": [] 540 | }, 541 | { 542 | "cell_type": "code", 543 | "execution_count": null, 544 | "id": "6048bffd", 545 | "metadata": {}, 546 | "outputs": [], 547 | "source": [] 548 | }, 549 | { 550 | "cell_type": "code", 551 | "execution_count": null, 552 | "id": "9b7f7beb", 553 | "metadata": {}, 554 | "outputs": [], 555 | "source": [] 556 | }, 557 | { 558 | "cell_type": "code", 559 | "execution_count": null, 560 | "id": "927d863f", 561 | "metadata": {}, 562 | "outputs": [], 563 | "source": [] 564 | }, 565 | { 566 | "cell_type": "code", 567 | "execution_count": null, 568 | "id": "02607f80", 569 | "metadata": {}, 570 | "outputs": [], 571 | "source": [] 572 | }, 573 | { 574 | "cell_type": "code", 575 | "execution_count": null, 576 | "id": "f4a45676", 577 | "metadata": {}, 578 | "outputs": [], 579 | "source": [] 580 | }, 581 | { 582 | "cell_type": "code", 583 | "execution_count": null, 584 | "id": "ffd82d72", 585 | "metadata": {}, 586 | "outputs": [], 587 | "source": [] 588 | }, 589 | { 590 | "cell_type": "code", 591 | "execution_count": null, 592 | "id": "66572cd2", 593 | "metadata": {}, 594 | "outputs": [], 595 | "source": [] 596 | }, 597 | { 598 | "cell_type": "code", 599 | "execution_count": null, 600 | "id": "1342bb7c", 601 | "metadata": {}, 602 | "outputs": [], 603 | "source": [] 604 | }, 605 | { 606 | "cell_type": "code", 607 | "execution_count": null, 608 | "id": "8a310f50", 609 | "metadata": {}, 610 | "outputs": [], 611 | "source": [] 612 | }, 613 | { 614 | "cell_type": "code", 615 | "execution_count": null, 616 | "id": "5ffdf47c", 617 | "metadata": {}, 618 | "outputs": [], 619 | "source": [] 620 | }, 621 | { 622 | "cell_type": "code", 623 | "execution_count": null, 624 | "id": "8ef5d84c", 625 | "metadata": {}, 626 | "outputs": [], 627 | "source": [] 628 | }, 629 | { 630 | "cell_type": "code", 631 | "execution_count": null, 632 | "id": "72e7f7d1", 633 | "metadata": {}, 634 | "outputs": [], 635 | "source": [] 636 | }, 637 | { 638 | "cell_type": "code", 639 | "execution_count": null, 640 | "id": "d274e826", 641 | "metadata": {}, 642 | "outputs": [], 643 | "source": [] 644 | } 645 | ], 646 | "metadata": { 647 | "kernelspec": { 648 | "display_name": "Python 3 (ipykernel)", 649 | "language": "python", 650 | "name": "python3" 651 | }, 652 | "language_info": { 653 | "codemirror_mode": { 654 | "name": "ipython", 655 | "version": 3 656 | }, 657 | "file_extension": ".py", 658 | "mimetype": "text/x-python", 659 | "name": "python", 660 | "nbconvert_exporter": "python", 661 | "pygments_lexer": "ipython3", 662 | "version": "3.9.13" 663 | } 664 | }, 665 | "nbformat": 4, 666 | "nbformat_minor": 5 667 | } 668 | --------------------------------------------------------------------------------