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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 13,
  6. "metadata": {
  7. "collapsed": false
  8. },
  9. "outputs": [],
  10. "source": [
  11. "# Dictionary of movies\n",
  12. "\n",
  13. "movies = [\n",
  14. "{\n",
  15. "\"name\": \"Usual Suspects\", \n",
  16. "\"imdb\": 7.0,\n",
  17. "\"category\": \"Thriller\"\n",
  18. "},\n",
  19. "{\n",
  20. "\"name\": \"Hitman\",\n",
  21. "\"imdb\": 6.3,\n",
  22. "\"category\": \"Action\"\n",
  23. "},\n",
  24. "{\n",
  25. "\"name\": \"Dark Knight\",\n",
  26. "\"imdb\": 9.0,\n",
  27. "\"category\": \"Adventure\"\n",
  28. "},\n",
  29. "{\n",
  30. "\"name\": \"The Help\",\n",
  31. "\"imdb\": 8.0,\n",
  32. "\"category\": \"Drama\"\n",
  33. "},\n",
  34. "{\n",
  35. "\"name\": \"The Choice\",\n",
  36. "\"imdb\": 6.2,\n",
  37. "\"category\": \"Romance\"\n",
  38. "},\n",
  39. "{\n",
  40. "\"name\": \"Colonia\",\n",
  41. "\"imdb\": 7.4,\n",
  42. "\"category\": \"Romance\"\n",
  43. "},\n",
  44. "{\n",
  45. "\"name\": \"Love\",\n",
  46. "\"imdb\": 6.0,\n",
  47. "\"category\": \"Romance\"\n",
  48. "},\n",
  49. "{\n",
  50. "\"name\": \"Bride Wars\",\n",
  51. "\"imdb\": 5.4,\n",
  52. "\"category\": \"Romance\"\n",
  53. "},\n",
  54. "{\n",
  55. "\"name\": \"AlphaJet\",\n",
  56. "\"imdb\": 3.2,\n",
  57. "\"category\": \"War\"\n",
  58. "},\n",
  59. "{\n",
  60. "\"name\": \"Ringing Crime\",\n",
  61. "\"imdb\": 4.0,\n",
  62. "\"category\": \"Crime\"\n",
  63. "},\n",
  64. "{\n",
  65. "\"name\": \"Joking muck\",\n",
  66. "\"imdb\": 7.2,\n",
  67. "\"category\": \"Comedy\"\n",
  68. "},\n",
  69. "{\n",
  70. "\"name\": \"What is the name\",\n",
  71. "\"imdb\": 9.2,\n",
  72. "\"category\": \"Suspense\"\n",
  73. "},\n",
  74. "{\n",
  75. "\"name\": \"Detective\",\n",
  76. "\"imdb\": 7.0,\n",
  77. "\"category\": \"Suspense\"\n",
  78. "},\n",
  79. "{\n",
  80. "\"name\": \"Exam\",\n",
  81. "\"imdb\": 4.2,\n",
  82. "\"category\": \"Thriller\"\n",
  83. "},\n",
  84. "{\n",
  85. "\"name\": \"We Two\",\n",
  86. "\"imdb\": 7.2,\n",
  87. "\"category\": \"Romance\"\n",
  88. "}\n",
  89. "]"
  90. ]
  91. },
  92. {
  93. "cell_type": "code",
  94. "execution_count": 14,
  95. "metadata": {
  96. "collapsed": false
  97. },
  98. "outputs": [
  99. {
  100. "name": "stdout",
  101. "output_type": "stream",
  102. "text": [
  103. "\n",
  104. "Checking if Dark Knight is greater than 5.5\n",
  105. "\n",
  106. "True\n"
  107. ]
  108. }
  109. ],
  110. "source": [
  111. "# Write a function that takes a single movie and \n",
  112. "# returns True if its IMDB score is above 5.5\n",
  113. "\n",
  114. "def check_score_greater(movie): \n",
  115. " if(movie['imdb']>5.5):\n",
  116. " return True\n",
  117. " else:\n",
  118. " return False\n",
  119. "\n",
  120. " \n",
  121. "# Could change movie title from Dark Knight to any other\n",
  122. "# and change to the corresponding element # from 2 to \n",
  123. "# whichever movie you want to see is above 5.5 or not\n",
  124. "print ''\n",
  125. "print 'Checking if Dark Knight is greater than 5.5'\n",
  126. "print ''\n",
  127. "isGreater=check_score_greater(movies[2])\n",
  128. "if(isGreater):\n",
  129. " print 'True'\n",
  130. "else :\n",
  131. " print 'False'"
  132. ]
  133. },
  134. {
  135. "cell_type": "code",
  136. "execution_count": 15,
  137. "metadata": {
  138. "collapsed": false
  139. },
  140. "outputs": [
  141. {
  142. "name": "stdout",
  143. "output_type": "stream",
  144. "text": [
  145. "\n",
  146. "List of movies with an IMDB score > 5.5: \n",
  147. "\n",
  148. "[{'category': 'Thriller', 'imdb': 7.0, 'name': 'Usual Suspects'}, {'category': 'Action', 'imdb': 6.3, 'name': 'Hitman'}, {'category': 'Adventure', 'imdb': 9.0, 'name': 'Dark Knight'}, {'category': 'Drama', 'imdb': 8.0, 'name': 'The Help'}, {'category': 'Romance', 'imdb': 6.2, 'name': 'The Choice'}, {'category': 'Romance', 'imdb': 7.4, 'name': 'Colonia'}, {'category': 'Romance', 'imdb': 6.0, 'name': 'Love'}, {'category': 'Comedy', 'imdb': 7.2, 'name': 'Joking muck'}, {'category': 'Suspense', 'imdb': 9.2, 'name': 'What is the name'}, {'category': 'Suspense', 'imdb': 7.0, 'name': 'Detective'}, {'category': 'Romance', 'imdb': 7.2, 'name': 'We Two'}]\n"
  149. ]
  150. }
  151. ],
  152. "source": [
  153. "# Write a function that returns a sublist of movies \n",
  154. "# with an IMDB score above 5.5. \n",
  155. "\n",
  156. "def sublist_movies_high_score(movies): \n",
  157. " out_list=[];\n",
  158. " for i in range(0,len(movies)):\n",
  159. " curr_movie=movies[i];\n",
  160. " if curr_movie['imdb']>5.5:\n",
  161. " out_list.append(curr_movie)\n",
  162. " return out_list\n",
  163. "\n",
  164. "print ''\n",
  165. "print 'List of movies with an IMDB score > 5.5: '\n",
  166. "print ''\n",
  167. "out_list=sublist_movies_high_score(movies)\n",
  168. "print out_list"
  169. ]
  170. },
  171. {
  172. "cell_type": "code",
  173. "execution_count": 16,
  174. "metadata": {
  175. "collapsed": false
  176. },
  177. "outputs": [
  178. {
  179. "name": "stdout",
  180. "output_type": "stream",
  181. "text": [
  182. "\n",
  183. "Movies in the Thriller are: \n",
  184. "\n",
  185. "[{'category': 'Thriller', 'imdb': 7.0, 'name': 'Usual Suspects'}, {'category': 'Thriller', 'imdb': 4.2, 'name': 'Exam'}]\n"
  186. ]
  187. }
  188. ],
  189. "source": [
  190. "# Write a function that takes a category name and returns \n",
  191. "# just those movies under that category.\n",
  192. "\n",
  193. "def return_movie_category(movies,cat_name): \n",
  194. " out_list=[]\n",
  195. " for i in movies:\n",
  196. " curr_cat=i['category']\n",
  197. " if cat_name.lower()==curr_cat.lower():\n",
  198. " out_list.append(i)\n",
  199. " return out_list\n",
  200. "\n",
  201. "# You could change to any category you'd like\n",
  202. "print ''\n",
  203. "print 'Movies in the Thriller are: '\n",
  204. "print ''\n",
  205. "out_list=return_movie_category(movies,'Thriller')\n",
  206. "print out_list"
  207. ]
  208. },
  209. {
  210. "cell_type": "code",
  211. "execution_count": 17,
  212. "metadata": {
  213. "collapsed": false
  214. },
  215. "outputs": [
  216. {
  217. "name": "stdout",
  218. "output_type": "stream",
  219. "text": [
  220. "\n",
  221. "Average IMDB score of all the movies is: \n",
  222. "6.48666666667\n"
  223. ]
  224. }
  225. ],
  226. "source": [
  227. "# Write a function that takes a list of movies and computes \n",
  228. "# the average IMDB score.\n",
  229. "\n",
  230. "def avg_imdb_score(movies): \n",
  231. " avg_score=0\n",
  232. " tot_movies=len(movies)\n",
  233. " for i in movies:\n",
  234. " avg_score=avg_score+i['imdb']\n",
  235. " avg_score=avg_score/tot_movies\n",
  236. " return avg_score\n",
  237. "\n",
  238. "print ''\n",
  239. "print 'Average IMDB score of all the movies is: '\n",
  240. "s1=avg_imdb_score(movies)\n",
  241. "print s1"
  242. ]
  243. },
  244. {
  245. "cell_type": "code",
  246. "execution_count": 18,
  247. "metadata": {
  248. "collapsed": false
  249. },
  250. "outputs": [
  251. {
  252. "name": "stdout",
  253. "output_type": "stream",
  254. "text": [
  255. "\n",
  256. "Average IMDB of movies in the Thriller category is: \n",
  257. "5.6\n"
  258. ]
  259. }
  260. ],
  261. "source": [
  262. "# Write a function that takes a category and computes \n",
  263. "# the average IMDB score (HINT: reuse the function \n",
  264. "# from question 2.)\n",
  265. "\n",
  266. "def avg_imdb_acc_to_cat(movies,cat_name): \n",
  267. " cat_movies=return_movie_category(movies,cat_name)\n",
  268. " avg_score=avg_imdb_score(cat_movies)\n",
  269. " return avg_score\n",
  270. "\n",
  271. "print ''\n",
  272. "print 'Average IMDB of movies in the Thriller category is: '\n",
  273. "s2=avg_imdb_acc_to_cat(movies,'Thriller')\n",
  274. "print s2"
  275. ]
  276. }
  277. ],
  278. "metadata": {
  279. "kernelspec": {
  280. "display_name": "Python 2",
  281. "language": "python",
  282. "name": "python2"
  283. },
  284. "language_info": {
  285. "codemirror_mode": {
  286. "name": "ipython",
  287. "version": 2
  288. },
  289. "file_extension": ".py",
  290. "mimetype": "text/x-python",
  291. "name": "python",
  292. "nbconvert_exporter": "python",
  293. "pygments_lexer": "ipython2",
  294. "version": "2.7.10"
  295. }
  296. },
  297. "nbformat": 4,
  298. "nbformat_minor": 0
  299. }
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