|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "metadata": {}, |
| 6 | + "source": [ |
| 7 | + "# 23. List of lists\n", |
| 8 | + "\n", |
| 9 | + "\n", |
| 10 | + "## Slicing, nested for loops, and flattening\n", |
| 11 | + "\n", |
| 12 | + "\n", |
| 13 | + "[Learn Python with Jupyter](https://learnpythonwithjupyter.com/) by [Serena Bonaretti](https://sbonaretti.github.io/) \n", |
| 14 | + "Narrative license: [CC BY-NC-SA](https://creativecommons.org/licenses/by-nc-sa/2.0/). Code license: [GNU-GPL v3](https://www.gnu.org/licenses/gpl-3.0.en.html) \n", |
| 15 | + "\n", |
| 16 | + "---" |
| 17 | + ] |
| 18 | + }, |
| 19 | + { |
| 20 | + "cell_type": "markdown", |
| 21 | + "metadata": {}, |
| 22 | + "source": [ |
| 23 | + "## 1. Slicing" |
| 24 | + ] |
| 25 | + }, |
| 26 | + { |
| 27 | + "cell_type": "markdown", |
| 28 | + "metadata": {}, |
| 29 | + "source": [ |
| 30 | + "- Given the following list of lists: " |
| 31 | + ] |
| 32 | + }, |
| 33 | + { |
| 34 | + "cell_type": "code", |
| 35 | + "execution_count": null, |
| 36 | + "metadata": {}, |
| 37 | + "outputs": [], |
| 38 | + "source": [ |
| 39 | + "animals = [[\"dog\", \"cat\"], [\"cow\", \"sheep\", \"horse\", \"chicken\", \"rabbit\"], [\"panda\", \"elephant\", \"giraffe\", \"penguin\"]]" |
| 40 | + ] |
| 41 | + }, |
| 42 | + { |
| 43 | + "cell_type": "markdown", |
| 44 | + "metadata": {}, |
| 45 | + "source": [ |
| 46 | + "- Print the sub-lists containing pets, farm animals, and wild animals: " |
| 47 | + ] |
| 48 | + }, |
| 49 | + { |
| 50 | + "cell_type": "code", |
| 51 | + "execution_count": null, |
| 52 | + "metadata": {}, |
| 53 | + "outputs": [], |
| 54 | + "source": [ |
| 55 | + "print (animals[0])\n", |
| 56 | + "print (animals[1])\n", |
| 57 | + "print (animals[2])" |
| 58 | + ] |
| 59 | + }, |
| 60 | + { |
| 61 | + "cell_type": "markdown", |
| 62 | + "metadata": {}, |
| 63 | + "source": [ |
| 64 | + "- Print the sub-elements \"cat\", \"rabbit\", and from \"panda\" to \"giraffe\":" |
| 65 | + ] |
| 66 | + }, |
| 67 | + { |
| 68 | + "cell_type": "code", |
| 69 | + "execution_count": null, |
| 70 | + "metadata": {}, |
| 71 | + "outputs": [], |
| 72 | + "source": [ |
| 73 | + "print (animals[0][1])\n", |
| 74 | + "print (animals[1][-1])\n", |
| 75 | + "print (animals[2][:3])" |
| 76 | + ] |
| 77 | + }, |
| 78 | + { |
| 79 | + "cell_type": "markdown", |
| 80 | + "metadata": {}, |
| 81 | + "source": [ |
| 82 | + "--- \n", |
| 83 | + "## 2. Nested for loops" |
| 84 | + ] |
| 85 | + }, |
| 86 | + { |
| 87 | + "cell_type": "markdown", |
| 88 | + "metadata": {}, |
| 89 | + "source": [ |
| 90 | + "- Given the following list of lists: " |
| 91 | + ] |
| 92 | + }, |
| 93 | + { |
| 94 | + "cell_type": "code", |
| 95 | + "execution_count": null, |
| 96 | + "metadata": {}, |
| 97 | + "outputs": [], |
| 98 | + "source": [ |
| 99 | + "sports = [[\"skiing\", \"skating\", \"curling\"], [\"canoeing\", \"cycling\", \"swimming\", \"surfing\"]]" |
| 100 | + ] |
| 101 | + }, |
| 102 | + { |
| 103 | + "cell_type": "markdown", |
| 104 | + "metadata": {}, |
| 105 | + "source": [ |
| 106 | + "- Print the sub-list elements one-by-one using a nested for loops through *indices*:" |
| 107 | + ] |
| 108 | + }, |
| 109 | + { |
| 110 | + "cell_type": "code", |
| 111 | + "execution_count": null, |
| 112 | + "metadata": {}, |
| 113 | + "outputs": [], |
| 114 | + "source": [ |
| 115 | + "for i in range (len(sports)): \n", |
| 116 | + " for j in range (len(sports[i])):\n", |
| 117 | + " print (sports[i][j])" |
| 118 | + ] |
| 119 | + }, |
| 120 | + { |
| 121 | + "cell_type": "markdown", |
| 122 | + "metadata": {}, |
| 123 | + "source": [ |
| 124 | + "- Print the sub-list elements one-by-one using a nested for loops through *values*:" |
| 125 | + ] |
| 126 | + }, |
| 127 | + { |
| 128 | + "cell_type": "code", |
| 129 | + "execution_count": null, |
| 130 | + "metadata": {}, |
| 131 | + "outputs": [], |
| 132 | + "source": [ |
| 133 | + "for seasonal_sports in sports:\n", |
| 134 | + " for sport in seasonal_sports:\n", |
| 135 | + " print (sport)" |
| 136 | + ] |
| 137 | + }, |
| 138 | + { |
| 139 | + "cell_type": "markdown", |
| 140 | + "metadata": {}, |
| 141 | + "source": [ |
| 142 | + "---\n", |
| 143 | + "## Flattening" |
| 144 | + ] |
| 145 | + }, |
| 146 | + { |
| 147 | + "cell_type": "markdown", |
| 148 | + "metadata": {}, |
| 149 | + "source": [ |
| 150 | + "- Given the following list of lists:" |
| 151 | + ] |
| 152 | + }, |
| 153 | + { |
| 154 | + "cell_type": "code", |
| 155 | + "execution_count": null, |
| 156 | + "metadata": {}, |
| 157 | + "outputs": [], |
| 158 | + "source": [ |
| 159 | + "instruments = [[\"contrabass\", \"cello\", \"clarinet\"],[\"gong\", \"guitar\"],[\"tambourine\", \"trumpet\", \"trombone\", \"triangle\"]]" |
| 160 | + ] |
| 161 | + }, |
| 162 | + { |
| 163 | + "cell_type": "markdown", |
| 164 | + "metadata": {}, |
| 165 | + "source": [ |
| 166 | + "- Flatten the list using a nested for loop through *indices*:" |
| 167 | + ] |
| 168 | + }, |
| 169 | + { |
| 170 | + "cell_type": "code", |
| 171 | + "execution_count": null, |
| 172 | + "metadata": {}, |
| 173 | + "outputs": [], |
| 174 | + "source": [ |
| 175 | + "flat_instruments = []\n", |
| 176 | + "for i in range(len(instruments)):\n", |
| 177 | + " for j in range (len(instruments[i])):\n", |
| 178 | + " flat_instruments.append(instruments[i][j])\n", |
| 179 | + "print (flat_instruments)" |
| 180 | + ] |
| 181 | + }, |
| 182 | + { |
| 183 | + "cell_type": "markdown", |
| 184 | + "metadata": {}, |
| 185 | + "source": [ |
| 186 | + "- Flatten the list using a nested for loop through *elements*:" |
| 187 | + ] |
| 188 | + }, |
| 189 | + { |
| 190 | + "cell_type": "code", |
| 191 | + "execution_count": null, |
| 192 | + "metadata": {}, |
| 193 | + "outputs": [], |
| 194 | + "source": [ |
| 195 | + "flat_instruments = []\n", |
| 196 | + "for group in instruments:\n", |
| 197 | + " for instrument in group:\n", |
| 198 | + " flat_instruments.append(instrument)\n", |
| 199 | + "print (flat_instruments)" |
| 200 | + ] |
| 201 | + }, |
| 202 | + { |
| 203 | + "cell_type": "markdown", |
| 204 | + "metadata": {}, |
| 205 | + "source": [ |
| 206 | + "- Flatten the list using a for loop and list concatenation:" |
| 207 | + ] |
| 208 | + }, |
| 209 | + { |
| 210 | + "cell_type": "code", |
| 211 | + "execution_count": null, |
| 212 | + "metadata": {}, |
| 213 | + "outputs": [], |
| 214 | + "source": [ |
| 215 | + "flat_instruments = []\n", |
| 216 | + "for group in instruments:\n", |
| 217 | + " flat_instruments += group\n", |
| 218 | + "print (flat_instruments)" |
| 219 | + ] |
| 220 | + }, |
| 221 | + { |
| 222 | + "cell_type": "markdown", |
| 223 | + "metadata": {}, |
| 224 | + "source": [ |
| 225 | + "- Flatten the list using list comprehension:" |
| 226 | + ] |
| 227 | + }, |
| 228 | + { |
| 229 | + "cell_type": "code", |
| 230 | + "execution_count": null, |
| 231 | + "metadata": {}, |
| 232 | + "outputs": [], |
| 233 | + "source": [ |
| 234 | + "instruments = [instrument for group in instruments for instrument in group]\n", |
| 235 | + "print (instruments)" |
| 236 | + ] |
| 237 | + }, |
| 238 | + { |
| 239 | + "cell_type": "code", |
| 240 | + "execution_count": null, |
| 241 | + "metadata": {}, |
| 242 | + "outputs": [], |
| 243 | + "source": [] |
| 244 | + } |
| 245 | + ], |
| 246 | + "metadata": { |
| 247 | + "kernelspec": { |
| 248 | + "display_name": "Python 3 (ipykernel)", |
| 249 | + "language": "python", |
| 250 | + "name": "python3" |
| 251 | + }, |
| 252 | + "language_info": { |
| 253 | + "codemirror_mode": { |
| 254 | + "name": "ipython", |
| 255 | + "version": 3 |
| 256 | + }, |
| 257 | + "file_extension": ".py", |
| 258 | + "mimetype": "text/x-python", |
| 259 | + "name": "python", |
| 260 | + "nbconvert_exporter": "python", |
| 261 | + "pygments_lexer": "ipython3", |
| 262 | + "version": "3.11.4" |
| 263 | + }, |
| 264 | + "widgets": { |
| 265 | + "application/vnd.jupyter.widget-state+json": { |
| 266 | + "state": {}, |
| 267 | + "version_major": 2, |
| 268 | + "version_minor": 0 |
| 269 | + } |
| 270 | + } |
| 271 | + }, |
| 272 | + "nbformat": 4, |
| 273 | + "nbformat_minor": 4 |
| 274 | +} |
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