API tools faq
paste
Advertisement
Guest User

Untitled

a guest
Feb 24th, 2019
133
0
Never
Add comment
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
text 20.85 KB | None | 0 0
raw download clone embed print report
  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 1,
  6. "metadata": {},
  7. "outputs": [],
  8. "source": [
  9. "import pymapd\n",
  10. "import pandas as pd\n",
  11. "import numpy as np"
  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. "Connection(mapd://mapd:***@localhost:6274/mapd?protocol=binary)\n"
  24. ]
  25. }
  26. ],
  27. "source": [
  28. "conn = pymapd.connect(user=\"mapd\", password=\"HyperInteractive\", \n",
  29. " host=\"localhost\",dbname=\"mapd\", port=6274, protocol=\"binary\")\n",
  30. "print(conn)"
  31. ]
  32. },
  33. {
  34. "cell_type": "code",
  35. "execution_count": 3,
  36. "metadata": {},
  37. "outputs": [
  38. {
  39. "data": {
  40. "text/plain": [
  41. "<pymapd.cursor.Cursor at 0x7fc90814f898>"
  42. ]
  43. },
  44. "execution_count": 3,
  45. "metadata": {},
  46. "output_type": "execute_result"
  47. }
  48. ],
  49. "source": [
  50. "d_query = '''DROP TABLE IF EXISTS wam_ts_precisions'''\n",
  51. "query = '''CREATE TABLE wam_ts_precisions(ts_text text,ts3_text text,ts6_text text,ts9_text text,ts_0 timestamp(0),ts_0_i32 timestamp encoding fixed(32),ts_0_not_null timestamp NOT NULL,ts_3 timestamp(3),ts_3_not_null timestamp(3),ts_6 timestamp(6),ts_6_not_null timestamp(6) NOT NULL,ts_9 timestamp(9),ts_9_not_null timestamp(9) NOT NULL)'''\n",
  52. "\n",
  53. "conn.execute(d_query)\n",
  54. "conn.execute(query)"
  55. ]
  56. },
  57. {
  58. "cell_type": "code",
  59. "execution_count": 4,
  60. "metadata": {},
  61. "outputs": [
  62. {
  63. "data": {
  64. "text/plain": [
  65. "[ColumnDetails(name='ts_text', type='STR', nullable=True, precision=0, scale=0, comp_param=32, encoding='DICT'),\n",
  66. " ColumnDetails(name='ts3_text', type='STR', nullable=True, precision=0, scale=0, comp_param=32, encoding='DICT'),\n",
  67. " ColumnDetails(name='ts6_text', type='STR', nullable=True, precision=0, scale=0, comp_param=32, encoding='DICT'),\n",
  68. " ColumnDetails(name='ts9_text', type='STR', nullable=True, precision=0, scale=0, comp_param=32, encoding='DICT'),\n",
  69. " ColumnDetails(name='ts_0', type='TIMESTAMP', nullable=True, precision=0, scale=0, comp_param=0, encoding='NONE'),\n",
  70. " ColumnDetails(name='ts_0_i32', type='TIMESTAMP', nullable=True, precision=0, scale=0, comp_param=32, encoding='FIXED'),\n",
  71. " ColumnDetails(name='ts_0_not_null', type='TIMESTAMP', nullable=False, precision=0, scale=0, comp_param=0, encoding='NONE'),\n",
  72. " ColumnDetails(name='ts_3', type='TIMESTAMP', nullable=True, precision=3, scale=0, comp_param=0, encoding='NONE'),\n",
  73. " ColumnDetails(name='ts_3_not_null', type='TIMESTAMP', nullable=True, precision=3, scale=0, comp_param=0, encoding='NONE'),\n",
  74. " ColumnDetails(name='ts_6', type='TIMESTAMP', nullable=True, precision=6, scale=0, comp_param=0, encoding='NONE'),\n",
  75. " ColumnDetails(name='ts_6_not_null', type='TIMESTAMP', nullable=False, precision=6, scale=0, comp_param=0, encoding='NONE'),\n",
  76. " ColumnDetails(name='ts_9', type='TIMESTAMP', nullable=True, precision=9, scale=0, comp_param=0, encoding='NONE'),\n",
  77. " ColumnDetails(name='ts_9_not_null', type='TIMESTAMP', nullable=False, precision=9, scale=0, comp_param=0, encoding='NONE')]"
  78. ]
  79. },
  80. "execution_count": 4,
  81. "metadata": {},
  82. "output_type": "execute_result"
  83. }
  84. ],
  85. "source": [
  86. "conn.get_table_details(\"wam_ts_precisions\")"
  87. ]
  88. },
  89. {
  90. "cell_type": "code",
  91. "execution_count": 5,
  92. "metadata": {},
  93. "outputs": [],
  94. "source": [
  95. "df_load = pd.read_csv(\"/home/wamsiv/raidStorage/ipnote/timestamps.csv\")"
  96. ]
  97. },
  98. {
  99. "cell_type": "code",
  100. "execution_count": 6,
  101. "metadata": {},
  102. "outputs": [],
  103. "source": [
  104. "for col in ['ts_0','ts_0_i32','ts_0_not_null','ts_3','ts_3_not_null','ts_6','ts_6_not_null','ts_9','ts_9_not_null']:\n",
  105. " df_load[col] = pd.to_datetime(df_load[col],errors='coerce')"
  106. ]
  107. },
  108. {
  109. "cell_type": "code",
  110. "execution_count": 7,
  111. "metadata": {},
  112. "outputs": [
  113. {
  114. "data": {
  115. "text/html": [
  116. "<div>\n",
  117. "<style scoped>\n",
  118. " .dataframe tbody tr th:only-of-type {\n",
  119. " vertical-align: middle;\n",
  120. " }\n",
  121. "\n",
  122. " .dataframe tbody tr th {\n",
  123. " vertical-align: top;\n",
  124. " }\n",
  125. "\n",
  126. " .dataframe thead th {\n",
  127. " text-align: right;\n",
  128. " }\n",
  129. "</style>\n",
  130. "<table border=\"1\" class=\"dataframe\">\n",
  131. " <thead>\n",
  132. " <tr style=\"text-align: right;\">\n",
  133. " <th></th>\n",
  134. " <th>ts_text</th>\n",
  135. " <th>ts3_text</th>\n",
  136. " <th>ts6_text</th>\n",
  137. " <th>ts9_text</th>\n",
  138. " <th>ts_0</th>\n",
  139. " <th>ts_0_i32</th>\n",
  140. " <th>ts_0_not_null</th>\n",
  141. " <th>ts_3</th>\n",
  142. " <th>ts_3_not_null</th>\n",
  143. " <th>ts_6</th>\n",
  144. " <th>ts_6_not_null</th>\n",
  145. " <th>ts_9</th>\n",
  146. " <th>ts_9_not_null</th>\n",
  147. " </tr>\n",
  148. " </thead>\n",
  149. " <tbody>\n",
  150. " <tr>\n",
  151. " <th>0</th>\n",
  152. " <td>2019-01-07 12:07:31</td>\n",
  153. " <td>2019-01-07 12:07:31.000</td>\n",
  154. " <td>2019-01-07 12:07:31.000000</td>\n",
  155. " <td>2019-01-07 12:07:31.000000000</td>\n",
  156. " <td>2019-01-07 12:07:31</td>\n",
  157. " <td>2019-01-07 12:07:31</td>\n",
  158. " <td>2019-01-07 12:07:31</td>\n",
  159. " <td>2019-01-07 12:07:31.000</td>\n",
  160. " <td>2019-01-07 12:07:31.000</td>\n",
  161. " <td>2019-01-07 12:07:31.000000</td>\n",
  162. " <td>2019-01-07 12:07:31.000000</td>\n",
  163. " <td>2019-01-07 12:07:31.000000000</td>\n",
  164. " <td>2019-01-07 12:07:31.000000000</td>\n",
  165. " </tr>\n",
  166. " <tr>\n",
  167. " <th>1</th>\n",
  168. " <td>2019-01-07 12:07:31</td>\n",
  169. " <td>2019-01-07 12:07:31.123</td>\n",
  170. " <td>2019-01-07 12:07:31.123456</td>\n",
  171. " <td>2019-01-07 12:07:31.123456789</td>\n",
  172. " <td>2019-01-07 12:07:31</td>\n",
  173. " <td>2019-01-07 12:07:31</td>\n",
  174. " <td>2019-01-07 12:07:31</td>\n",
  175. " <td>2019-01-07 12:07:31.123</td>\n",
  176. " <td>2019-01-07 12:07:31.123</td>\n",
  177. " <td>2019-01-07 12:07:31.123456</td>\n",
  178. " <td>2019-01-07 12:07:31.123456</td>\n",
  179. " <td>2019-01-07 12:07:31.123456789</td>\n",
  180. " <td>2019-01-07 12:07:31.123456789</td>\n",
  181. " </tr>\n",
  182. " <tr>\n",
  183. " <th>2</th>\n",
  184. " <td>1947-08-15 00:00:00</td>\n",
  185. " <td>1947-08-15 00:00:00.000</td>\n",
  186. " <td>1947-08-15 00:00:00.000000</td>\n",
  187. " <td>1947-08-15 00:00:00.000000000</td>\n",
  188. " <td>1947-08-15 00:00:00</td>\n",
  189. " <td>1947-08-15 00:00:00</td>\n",
  190. " <td>1947-08-15 00:00:00</td>\n",
  191. " <td>1947-08-15 00:00:00.000</td>\n",
  192. " <td>1947-08-15 00:00:00.000</td>\n",
  193. " <td>1947-08-15 00:00:00.000000</td>\n",
  194. " <td>1947-08-15 00:00:00.000000</td>\n",
  195. " <td>1947-08-15 00:00:00.000000000</td>\n",
  196. " <td>1947-08-15 00:00:00.000000000</td>\n",
  197. " </tr>\n",
  198. " <tr>\n",
  199. " <th>3</th>\n",
  200. " <td>1947-08-15 00:00:00</td>\n",
  201. " <td>1947-08-15 00:00:00.123</td>\n",
  202. " <td>1947-08-15 00:00:00.123456</td>\n",
  203. " <td>1947-08-15 00:00:00.123456000</td>\n",
  204. " <td>1947-08-15 00:00:00</td>\n",
  205. " <td>1947-08-15 00:00:00</td>\n",
  206. " <td>1947-08-15 00:00:00</td>\n",
  207. " <td>1947-08-15 00:00:00.123</td>\n",
  208. " <td>1947-08-15 00:00:00.123</td>\n",
  209. " <td>1947-08-15 00:00:00.123456</td>\n",
  210. " <td>1947-08-15 00:00:00.123456</td>\n",
  211. " <td>1947-08-15 00:00:00.123456000</td>\n",
  212. " <td>1947-08-15 00:00:00.123456000</td>\n",
  213. " </tr>\n",
  214. " <tr>\n",
  215. " <th>4</th>\n",
  216. " <td>2037-11-30 23:22:12</td>\n",
  217. " <td>2037-11-30 23:22:12.123</td>\n",
  218. " <td>2037-11-30 23:22:12.123000</td>\n",
  219. " <td>2037-11-30 23:22:12.123000000</td>\n",
  220. " <td>2037-11-30 23:22:12</td>\n",
  221. " <td>2037-11-30 23:22:12</td>\n",
  222. " <td>2037-11-30 23:22:12</td>\n",
  223. " <td>2037-11-30 23:22:12.123</td>\n",
  224. " <td>2037-11-30 23:22:12.123</td>\n",
  225. " <td>2037-11-30 23:22:12.123000</td>\n",
  226. " <td>2037-11-30 23:22:12.123000</td>\n",
  227. " <td>2037-11-30 23:22:12.123000000</td>\n",
  228. " <td>2037-11-30 23:22:12.123000000</td>\n",
  229. " </tr>\n",
  230. " </tbody>\n",
  231. "</table>\n",
  232. "</div>"
  233. ],
  234. "text/plain": [
  235. " ts_text ts3_text ts6_text \\\n",
  236. "0 2019-01-07 12:07:31 2019-01-07 12:07:31.000 2019-01-07 12:07:31.000000 \n",
  237. "1 2019-01-07 12:07:31 2019-01-07 12:07:31.123 2019-01-07 12:07:31.123456 \n",
  238. "2 1947-08-15 00:00:00 1947-08-15 00:00:00.000 1947-08-15 00:00:00.000000 \n",
  239. "3 1947-08-15 00:00:00 1947-08-15 00:00:00.123 1947-08-15 00:00:00.123456 \n",
  240. "4 2037-11-30 23:22:12 2037-11-30 23:22:12.123 2037-11-30 23:22:12.123000 \n",
  241. "\n",
  242. " ts9_text ts_0 ts_0_i32 \\\n",
  243. "0 2019-01-07 12:07:31.000000000 2019-01-07 12:07:31 2019-01-07 12:07:31 \n",
  244. "1 2019-01-07 12:07:31.123456789 2019-01-07 12:07:31 2019-01-07 12:07:31 \n",
  245. "2 1947-08-15 00:00:00.000000000 1947-08-15 00:00:00 1947-08-15 00:00:00 \n",
  246. "3 1947-08-15 00:00:00.123456000 1947-08-15 00:00:00 1947-08-15 00:00:00 \n",
  247. "4 2037-11-30 23:22:12.123000000 2037-11-30 23:22:12 2037-11-30 23:22:12 \n",
  248. "\n",
  249. " ts_0_not_null ts_3 ts_3_not_null \\\n",
  250. "0 2019-01-07 12:07:31 2019-01-07 12:07:31.000 2019-01-07 12:07:31.000 \n",
  251. "1 2019-01-07 12:07:31 2019-01-07 12:07:31.123 2019-01-07 12:07:31.123 \n",
  252. "2 1947-08-15 00:00:00 1947-08-15 00:00:00.000 1947-08-15 00:00:00.000 \n",
  253. "3 1947-08-15 00:00:00 1947-08-15 00:00:00.123 1947-08-15 00:00:00.123 \n",
  254. "4 2037-11-30 23:22:12 2037-11-30 23:22:12.123 2037-11-30 23:22:12.123 \n",
  255. "\n",
  256. " ts_6 ts_6_not_null \\\n",
  257. "0 2019-01-07 12:07:31.000000 2019-01-07 12:07:31.000000 \n",
  258. "1 2019-01-07 12:07:31.123456 2019-01-07 12:07:31.123456 \n",
  259. "2 1947-08-15 00:00:00.000000 1947-08-15 00:00:00.000000 \n",
  260. "3 1947-08-15 00:00:00.123456 1947-08-15 00:00:00.123456 \n",
  261. "4 2037-11-30 23:22:12.123000 2037-11-30 23:22:12.123000 \n",
  262. "\n",
  263. " ts_9 ts_9_not_null \n",
  264. "0 2019-01-07 12:07:31.000000000 2019-01-07 12:07:31.000000000 \n",
  265. "1 2019-01-07 12:07:31.123456789 2019-01-07 12:07:31.123456789 \n",
  266. "2 1947-08-15 00:00:00.000000000 1947-08-15 00:00:00.000000000 \n",
  267. "3 1947-08-15 00:00:00.123456000 1947-08-15 00:00:00.123456000 \n",
  268. "4 2037-11-30 23:22:12.123000000 2037-11-30 23:22:12.123000000 "
  269. ]
  270. },
  271. "execution_count": 7,
  272. "metadata": {},
  273. "output_type": "execute_result"
  274. }
  275. ],
  276. "source": [
  277. "df_load.head(5)"
  278. ]
  279. },
  280. {
  281. "cell_type": "code",
  282. "execution_count": 8,
  283. "metadata": {},
  284. "outputs": [
  285. {
  286. "data": {
  287. "text/plain": [
  288. "ts_text object\n",
  289. "ts3_text object\n",
  290. "ts6_text object\n",
  291. "ts9_text object\n",
  292. "ts_0 datetime64[ns]\n",
  293. "ts_0_i32 datetime64[ns]\n",
  294. "ts_0_not_null datetime64[ns]\n",
  295. "ts_3 datetime64[ns]\n",
  296. "ts_3_not_null datetime64[ns]\n",
  297. "ts_6 datetime64[ns]\n",
  298. "ts_6_not_null datetime64[ns]\n",
  299. "ts_9 datetime64[ns]\n",
  300. "ts_9_not_null datetime64[ns]\n",
  301. "dtype: object"
  302. ]
  303. },
  304. "execution_count": 8,
  305. "metadata": {},
  306. "output_type": "execute_result"
  307. }
  308. ],
  309. "source": [
  310. "df_load.dtypes"
  311. ]
  312. },
  313. {
  314. "cell_type": "code",
  315. "execution_count": 9,
  316. "metadata": {},
  317. "outputs": [],
  318. "source": [
  319. "conn.load_table(\"wam_ts_precisions\",df_load,preserve_index=False)"
  320. ]
  321. },
  322. {
  323. "cell_type": "code",
  324. "execution_count": 10,
  325. "metadata": {},
  326. "outputs": [],
  327. "source": [
  328. "df = conn.select_ipc(\"Select ts_text,ts3_text,ts6_text,ts9_text,ts_0,ts_0_i32,ts_0_not_null,ts_3,ts_3_not_null,ts_6,ts_6_not_null,ts_9,ts_9_not_null from wam_ts_precisions;\")"
  329. ]
  330. },
  331. {
  332. "cell_type": "code",
  333. "execution_count": 11,
  334. "metadata": {},
  335. "outputs": [
  336. {
  337. "data": {
  338. "text/html": [
  339. "<div>\n",
  340. "<style scoped>\n",
  341. " .dataframe tbody tr th:only-of-type {\n",
  342. " vertical-align: middle;\n",
  343. " }\n",
  344. "\n",
  345. " .dataframe tbody tr th {\n",
  346. " vertical-align: top;\n",
  347. " }\n",
  348. "\n",
  349. " .dataframe thead th {\n",
  350. " text-align: right;\n",
  351. " }\n",
  352. "</style>\n",
  353. "<table border=\"1\" class=\"dataframe\">\n",
  354. " <thead>\n",
  355. " <tr style=\"text-align: right;\">\n",
  356. " <th></th>\n",
  357. " <th>ts_text</th>\n",
  358. " <th>ts3_text</th>\n",
  359. " <th>ts6_text</th>\n",
  360. " <th>ts9_text</th>\n",
  361. " <th>ts_0</th>\n",
  362. " <th>ts_0_i32</th>\n",
  363. " <th>ts_0_not_null</th>\n",
  364. " <th>ts_3</th>\n",
  365. " <th>ts_3_not_null</th>\n",
  366. " <th>ts_6</th>\n",
  367. " <th>ts_6_not_null</th>\n",
  368. " <th>ts_9</th>\n",
  369. " <th>ts_9_not_null</th>\n",
  370. " </tr>\n",
  371. " </thead>\n",
  372. " <tbody>\n",
  373. " <tr>\n",
  374. " <th>0</th>\n",
  375. " <td>2019-01-07 12:07:31</td>\n",
  376. " <td>2019-01-07 12:07:31.000</td>\n",
  377. " <td>2019-01-07 12:07:31.000000</td>\n",
  378. " <td>2019-01-07 12:07:31.000000000</td>\n",
  379. " <td>2019-01-07 12:07:31</td>\n",
  380. " <td>2019-01-07 12:07:31</td>\n",
  381. " <td>2019-01-07 12:07:31</td>\n",
  382. " <td>2019-01-07 12:07:31.000</td>\n",
  383. " <td>2019-01-07 12:07:31.000</td>\n",
  384. " <td>2019-01-07 12:07:31.000000</td>\n",
  385. " <td>2019-01-07 12:07:31.000000</td>\n",
  386. " <td>2019-01-07 12:07:31.000000000</td>\n",
  387. " <td>2019-01-07 12:07:31.000000000</td>\n",
  388. " </tr>\n",
  389. " <tr>\n",
  390. " <th>1</th>\n",
  391. " <td>2019-01-07 12:07:31</td>\n",
  392. " <td>2019-01-07 12:07:31.123</td>\n",
  393. " <td>2019-01-07 12:07:31.123456</td>\n",
  394. " <td>2019-01-07 12:07:31.123456789</td>\n",
  395. " <td>2019-01-07 12:07:31</td>\n",
  396. " <td>2019-01-07 12:07:31</td>\n",
  397. " <td>2019-01-07 12:07:31</td>\n",
  398. " <td>2019-01-07 12:07:31.123</td>\n",
  399. " <td>2019-01-07 12:07:31.123</td>\n",
  400. " <td>2019-01-07 12:07:31.123456</td>\n",
  401. " <td>2019-01-07 12:07:31.123456</td>\n",
  402. " <td>2019-01-07 12:07:31.123456789</td>\n",
  403. " <td>2019-01-07 12:07:31.123456789</td>\n",
  404. " </tr>\n",
  405. " <tr>\n",
  406. " <th>2</th>\n",
  407. " <td>1947-08-15 00:00:00</td>\n",
  408. " <td>1947-08-15 00:00:00.000</td>\n",
  409. " <td>1947-08-15 00:00:00.000000</td>\n",
  410. " <td>1947-08-15 00:00:00.000000000</td>\n",
  411. " <td>1947-08-15 00:00:00</td>\n",
  412. " <td>1947-08-15 00:00:00</td>\n",
  413. " <td>1947-08-15 00:00:00</td>\n",
  414. " <td>1947-08-15 00:00:00.000</td>\n",
  415. " <td>1947-08-15 00:00:00.000</td>\n",
  416. " <td>1947-08-15 00:00:00.000000</td>\n",
  417. " <td>1947-08-15 00:00:00.000000</td>\n",
  418. " <td>1947-08-15 00:00:00.000000000</td>\n",
  419. " <td>1947-08-15 00:00:00.000000000</td>\n",
  420. " </tr>\n",
  421. " <tr>\n",
  422. " <th>3</th>\n",
  423. " <td>1947-08-15 00:00:00</td>\n",
  424. " <td>1947-08-15 00:00:00.123</td>\n",
  425. " <td>1947-08-15 00:00:00.123456</td>\n",
  426. " <td>1947-08-15 00:00:00.123456000</td>\n",
  427. " <td>1947-08-15 00:00:00</td>\n",
  428. " <td>1947-08-15 00:00:00</td>\n",
  429. " <td>1947-08-15 00:00:00</td>\n",
  430. " <td>1947-08-15 00:00:00.123</td>\n",
  431. " <td>1947-08-15 00:00:00.123</td>\n",
  432. " <td>1947-08-15 00:00:00.123456</td>\n",
  433. " <td>1947-08-15 00:00:00.123456</td>\n",
  434. " <td>1947-08-15 00:00:00.123456000</td>\n",
  435. " <td>1947-08-15 00:00:00.123456000</td>\n",
  436. " </tr>\n",
  437. " <tr>\n",
  438. " <th>4</th>\n",
  439. " <td>2037-11-30 23:22:12</td>\n",
  440. " <td>2037-11-30 23:22:12.123</td>\n",
  441. " <td>2037-11-30 23:22:12.123000</td>\n",
  442. " <td>2037-11-30 23:22:12.123000000</td>\n",
  443. " <td>2037-11-30 23:22:12</td>\n",
  444. " <td>2037-11-30 23:22:12</td>\n",
  445. " <td>2037-11-30 23:22:12</td>\n",
  446. " <td>2037-11-30 23:22:12.123</td>\n",
  447. " <td>2037-11-30 23:22:12.123</td>\n",
  448. " <td>2037-11-30 23:22:12.123000</td>\n",
  449. " <td>2037-11-30 23:22:12.123000</td>\n",
  450. " <td>2037-11-30 23:22:12.123000000</td>\n",
  451. " <td>2037-11-30 23:22:12.123000000</td>\n",
  452. " </tr>\n",
  453. " </tbody>\n",
  454. "</table>\n",
  455. "</div>"
  456. ],
  457. "text/plain": [
  458. " ts_text ts3_text ts6_text \\\n",
  459. "0 2019-01-07 12:07:31 2019-01-07 12:07:31.000 2019-01-07 12:07:31.000000 \n",
  460. "1 2019-01-07 12:07:31 2019-01-07 12:07:31.123 2019-01-07 12:07:31.123456 \n",
  461. "2 1947-08-15 00:00:00 1947-08-15 00:00:00.000 1947-08-15 00:00:00.000000 \n",
  462. "3 1947-08-15 00:00:00 1947-08-15 00:00:00.123 1947-08-15 00:00:00.123456 \n",
  463. "4 2037-11-30 23:22:12 2037-11-30 23:22:12.123 2037-11-30 23:22:12.123000 \n",
  464. "\n",
  465. " ts9_text ts_0 ts_0_i32 \\\n",
  466. "0 2019-01-07 12:07:31.000000000 2019-01-07 12:07:31 2019-01-07 12:07:31 \n",
  467. "1 2019-01-07 12:07:31.123456789 2019-01-07 12:07:31 2019-01-07 12:07:31 \n",
  468. "2 1947-08-15 00:00:00.000000000 1947-08-15 00:00:00 1947-08-15 00:00:00 \n",
  469. "3 1947-08-15 00:00:00.123456000 1947-08-15 00:00:00 1947-08-15 00:00:00 \n",
  470. "4 2037-11-30 23:22:12.123000000 2037-11-30 23:22:12 2037-11-30 23:22:12 \n",
  471. "\n",
  472. " ts_0_not_null ts_3 ts_3_not_null \\\n",
  473. "0 2019-01-07 12:07:31 2019-01-07 12:07:31.000 2019-01-07 12:07:31.000 \n",
  474. "1 2019-01-07 12:07:31 2019-01-07 12:07:31.123 2019-01-07 12:07:31.123 \n",
  475. "2 1947-08-15 00:00:00 1947-08-15 00:00:00.000 1947-08-15 00:00:00.000 \n",
  476. "3 1947-08-15 00:00:00 1947-08-15 00:00:00.123 1947-08-15 00:00:00.123 \n",
  477. "4 2037-11-30 23:22:12 2037-11-30 23:22:12.123 2037-11-30 23:22:12.123 \n",
  478. "\n",
  479. " ts_6 ts_6_not_null \\\n",
  480. "0 2019-01-07 12:07:31.000000 2019-01-07 12:07:31.000000 \n",
  481. "1 2019-01-07 12:07:31.123456 2019-01-07 12:07:31.123456 \n",
  482. "2 1947-08-15 00:00:00.000000 1947-08-15 00:00:00.000000 \n",
  483. "3 1947-08-15 00:00:00.123456 1947-08-15 00:00:00.123456 \n",
  484. "4 2037-11-30 23:22:12.123000 2037-11-30 23:22:12.123000 \n",
  485. "\n",
  486. " ts_9 ts_9_not_null \n",
  487. "0 2019-01-07 12:07:31.000000000 2019-01-07 12:07:31.000000000 \n",
  488. "1 2019-01-07 12:07:31.123456789 2019-01-07 12:07:31.123456789 \n",
  489. "2 1947-08-15 00:00:00.000000000 1947-08-15 00:00:00.000000000 \n",
  490. "3 1947-08-15 00:00:00.123456000 1947-08-15 00:00:00.123456000 \n",
  491. "4 2037-11-30 23:22:12.123000000 2037-11-30 23:22:12.123000000 "
  492. ]
  493. },
  494. "execution_count": 11,
  495. "metadata": {},
  496. "output_type": "execute_result"
  497. }
  498. ],
  499. "source": [
  500. "df.head(5)"
  501. ]
  502. },
  503. {
  504. "cell_type": "code",
  505. "execution_count": null,
  506. "metadata": {},
  507. "outputs": [],
  508. "source": []
  509. }
  510. ],
  511. "metadata": {
  512. "kernelspec": {
  513. "display_name": "Python 3",
  514. "language": "python",
  515. "name": "python3"
  516. },
  517. "language_info": {
  518. "codemirror_mode": {
  519. "name": "ipython",
  520. "version": 3
  521. },
  522. "file_extension": ".py",
  523. "mimetype": "text/x-python",
  524. "name": "python",
  525. "nbconvert_exporter": "python",
  526. "pygments_lexer": "ipython3",
  527. "version": "3.7.1"
  528. }
  529. },
  530. "nbformat": 4,
  531. "nbformat_minor": 2
  532. }
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement
Public Pastes
Advertisement
We use cookies for various purposes including analytics. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy.  OK, I Understand
Not a member of Pastebin yet?
Sign Up, it unlocks many cool features!