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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 1,
  6. "metadata": {},
  7. "outputs": [],
  8. "source": [
  9. "import cudf as gd\n",
  10. "import pandas as pd\n",
  11. "import time"
  12. ]
  13. },
  14. {
  15. "cell_type": "code",
  16. "execution_count": 2,
  17. "metadata": {},
  18. "outputs": [
  19. {
  20. "name": "stdout",
  21. "output_type": "stream",
  22. "text": [
  23. "(200000, 202)\n",
  24. "CPU times: user 252 ms, sys: 252 ms, total: 504 ms\n",
  25. "Wall time: 509 ms\n"
  26. ]
  27. }
  28. ],
  29. "source": [
  30. "%%time\n",
  31. "PATH = '../input'\n",
  32. "cols = ['ID_code', 'target'] + ['var_%d'%i for i in range(200)]\n",
  33. "dtypes = ['int32', 'int32'] + ['float32' for i in range(200)]\n",
  34. "train_gd = gd.read_csv('%s/train.csv'%PATH,names=cols,dtype=dtypes,skiprows=1)\n",
  35. "print(train_gd.shape)"
  36. ]
  37. },
  38. {
  39. "cell_type": "code",
  40. "execution_count": 3,
  41. "metadata": {},
  42. "outputs": [
  43. {
  44. "name": "stdout",
  45. "output_type": "stream",
  46. "text": [
  47. "(200000, 202)\n",
  48. "CPU times: user 5.08 s, sys: 404 ms, total: 5.48 s\n",
  49. "Wall time: 5.48 s\n"
  50. ]
  51. }
  52. ],
  53. "source": [
  54. "%%time\n",
  55. "train_pd = pd.read_csv('%s/train.csv'%PATH)\n",
  56. "print(train_pd.shape)"
  57. ]
  58. },
  59. {
  60. "cell_type": "code",
  61. "execution_count": 4,
  62. "metadata": {},
  63. "outputs": [
  64. {
  65. "data": {
  66. "text/html": [
  67. "<div>\n",
  68. "<style scoped>\n",
  69. " .dataframe tbody tr th:only-of-type {\n",
  70. " vertical-align: middle;\n",
  71. " }\n",
  72. "\n",
  73. " .dataframe tbody tr th {\n",
  74. " vertical-align: top;\n",
  75. " }\n",
  76. "\n",
  77. " .dataframe thead th {\n",
  78. " text-align: right;\n",
  79. " }\n",
  80. "</style>\n",
  81. "<table border=\"1\" class=\"dataframe\">\n",
  82. " <thead>\n",
  83. " <tr style=\"text-align: right;\">\n",
  84. " <th></th>\n",
  85. " <th>ID_code</th>\n",
  86. " <th>target</th>\n",
  87. " <th>var_0</th>\n",
  88. " <th>var_1</th>\n",
  89. " <th>var_2</th>\n",
  90. " <th>var_3</th>\n",
  91. " <th>var_4</th>\n",
  92. " <th>var_5</th>\n",
  93. " <th>var_6</th>\n",
  94. " <th>var_7</th>\n",
  95. " <th>...</th>\n",
  96. " <th>var_190</th>\n",
  97. " <th>var_191</th>\n",
  98. " <th>var_192</th>\n",
  99. " <th>var_193</th>\n",
  100. " <th>var_194</th>\n",
  101. " <th>var_195</th>\n",
  102. " <th>var_196</th>\n",
  103. " <th>var_197</th>\n",
  104. " <th>var_198</th>\n",
  105. " <th>var_199</th>\n",
  106. " </tr>\n",
  107. " </thead>\n",
  108. " <tbody>\n",
  109. " <tr>\n",
  110. " <th>0</th>\n",
  111. " <td>75153670</td>\n",
  112. " <td>0</td>\n",
  113. " <td>8.925500</td>\n",
  114. " <td>-6.7863</td>\n",
  115. " <td>11.908100</td>\n",
  116. " <td>5.0930</td>\n",
  117. " <td>11.460700</td>\n",
  118. " <td>-9.2834</td>\n",
  119. " <td>5.1187</td>\n",
  120. " <td>18.626602</td>\n",
  121. " <td>...</td>\n",
  122. " <td>4.4354</td>\n",
  123. " <td>3.964200</td>\n",
  124. " <td>3.1364</td>\n",
  125. " <td>1.691000</td>\n",
  126. " <td>18.522701</td>\n",
  127. " <td>-2.3978</td>\n",
  128. " <td>7.8784</td>\n",
  129. " <td>8.5635</td>\n",
  130. " <td>12.780300</td>\n",
  131. " <td>-1.091400</td>\n",
  132. " </tr>\n",
  133. " <tr>\n",
  134. " <th>1</th>\n",
  135. " <td>75153671</td>\n",
  136. " <td>0</td>\n",
  137. " <td>11.500600</td>\n",
  138. " <td>-4.1473</td>\n",
  139. " <td>13.858801</td>\n",
  140. " <td>5.3890</td>\n",
  141. " <td>12.362201</td>\n",
  142. " <td>7.0433</td>\n",
  143. " <td>5.6208</td>\n",
  144. " <td>16.533800</td>\n",
  145. " <td>...</td>\n",
  146. " <td>7.6421</td>\n",
  147. " <td>7.721400</td>\n",
  148. " <td>2.5837</td>\n",
  149. " <td>10.951600</td>\n",
  150. " <td>15.430499</td>\n",
  151. " <td>2.0339</td>\n",
  152. " <td>8.1267</td>\n",
  153. " <td>8.7889</td>\n",
  154. " <td>18.355999</td>\n",
  155. " <td>1.951800</td>\n",
  156. " </tr>\n",
  157. " <tr>\n",
  158. " <th>2</th>\n",
  159. " <td>75153672</td>\n",
  160. " <td>0</td>\n",
  161. " <td>8.609301</td>\n",
  162. " <td>-2.7457</td>\n",
  163. " <td>12.080500</td>\n",
  164. " <td>7.8928</td>\n",
  165. " <td>10.582500</td>\n",
  166. " <td>-9.0837</td>\n",
  167. " <td>6.9427</td>\n",
  168. " <td>14.615500</td>\n",
  169. " <td>...</td>\n",
  170. " <td>2.9057</td>\n",
  171. " <td>9.790500</td>\n",
  172. " <td>1.6704</td>\n",
  173. " <td>1.685800</td>\n",
  174. " <td>21.604200</td>\n",
  175. " <td>3.1417</td>\n",
  176. " <td>-6.5213</td>\n",
  177. " <td>8.2675</td>\n",
  178. " <td>14.722200</td>\n",
  179. " <td>0.396500</td>\n",
  180. " </tr>\n",
  181. " <tr>\n",
  182. " <th>3</th>\n",
  183. " <td>75153673</td>\n",
  184. " <td>0</td>\n",
  185. " <td>11.060400</td>\n",
  186. " <td>-2.1518</td>\n",
  187. " <td>8.952200</td>\n",
  188. " <td>7.1957</td>\n",
  189. " <td>12.584599</td>\n",
  190. " <td>-1.8361</td>\n",
  191. " <td>5.8428</td>\n",
  192. " <td>14.925000</td>\n",
  193. " <td>...</td>\n",
  194. " <td>4.4666</td>\n",
  195. " <td>4.743299</td>\n",
  196. " <td>0.7178</td>\n",
  197. " <td>1.421400</td>\n",
  198. " <td>23.034700</td>\n",
  199. " <td>-1.2706</td>\n",
  200. " <td>-2.9275</td>\n",
  201. " <td>10.2922</td>\n",
  202. " <td>17.969700</td>\n",
  203. " <td>-8.999599</td>\n",
  204. " </tr>\n",
  205. " <tr>\n",
  206. " <th>4</th>\n",
  207. " <td>75153674</td>\n",
  208. " <td>0</td>\n",
  209. " <td>9.836900</td>\n",
  210. " <td>-1.4834</td>\n",
  211. " <td>12.874599</td>\n",
  212. " <td>6.6375</td>\n",
  213. " <td>12.277200</td>\n",
  214. " <td>2.4486</td>\n",
  215. " <td>5.9405</td>\n",
  216. " <td>19.251400</td>\n",
  217. " <td>...</td>\n",
  218. " <td>-1.4905</td>\n",
  219. " <td>9.521400</td>\n",
  220. " <td>-0.1508</td>\n",
  221. " <td>9.194201</td>\n",
  222. " <td>13.287600</td>\n",
  223. " <td>-1.5121</td>\n",
  224. " <td>3.9267</td>\n",
  225. " <td>9.5031</td>\n",
  226. " <td>17.997400</td>\n",
  227. " <td>-8.810400</td>\n",
  228. " </tr>\n",
  229. " </tbody>\n",
  230. "</table>\n",
  231. "<p>5 rows × 202 columns</p>\n",
  232. "</div>"
  233. ],
  234. "text/plain": [
  235. " ID_code target var_0 var_1 var_2 var_3 var_4 var_5 \\\n",
  236. "0 75153670 0 8.925500 -6.7863 11.908100 5.0930 11.460700 -9.2834 \n",
  237. "1 75153671 0 11.500600 -4.1473 13.858801 5.3890 12.362201 7.0433 \n",
  238. "2 75153672 0 8.609301 -2.7457 12.080500 7.8928 10.582500 -9.0837 \n",
  239. "3 75153673 0 11.060400 -2.1518 8.952200 7.1957 12.584599 -1.8361 \n",
  240. "4 75153674 0 9.836900 -1.4834 12.874599 6.6375 12.277200 2.4486 \n",
  241. "\n",
  242. " var_6 var_7 ... var_190 var_191 var_192 var_193 var_194 \\\n",
  243. "0 5.1187 18.626602 ... 4.4354 3.964200 3.1364 1.691000 18.522701 \n",
  244. "1 5.6208 16.533800 ... 7.6421 7.721400 2.5837 10.951600 15.430499 \n",
  245. "2 6.9427 14.615500 ... 2.9057 9.790500 1.6704 1.685800 21.604200 \n",
  246. "3 5.8428 14.925000 ... 4.4666 4.743299 0.7178 1.421400 23.034700 \n",
  247. "4 5.9405 19.251400 ... -1.4905 9.521400 -0.1508 9.194201 13.287600 \n",
  248. "\n",
  249. " var_195 var_196 var_197 var_198 var_199 \n",
  250. "0 -2.3978 7.8784 8.5635 12.780300 -1.091400 \n",
  251. "1 2.0339 8.1267 8.7889 18.355999 1.951800 \n",
  252. "2 3.1417 -6.5213 8.2675 14.722200 0.396500 \n",
  253. "3 -1.2706 -2.9275 10.2922 17.969700 -8.999599 \n",
  254. "4 -1.5121 3.9267 9.5031 17.997400 -8.810400 \n",
  255. "\n",
  256. "[5 rows x 202 columns]"
  257. ]
  258. },
  259. "execution_count": 4,
  260. "metadata": {},
  261. "output_type": "execute_result"
  262. }
  263. ],
  264. "source": [
  265. "train_gd.head().to_pandas()"
  266. ]
  267. }
  268. ],
  269. "metadata": {
  270. "kernelspec": {
  271. "display_name": "Python 3",
  272. "language": "python",
  273. "name": "python3"
  274. },
  275. "language_info": {
  276. "codemirror_mode": {
  277. "name": "ipython",
  278. "version": 3
  279. },
  280. "file_extension": ".py",
  281. "mimetype": "text/x-python",
  282. "name": "python",
  283. "nbconvert_exporter": "python",
  284. "pygments_lexer": "ipython3",
  285. "version": "3.6.8"
  286. }
  287. },
  288. "nbformat": 4,
  289. "nbformat_minor": 2
  290. }
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