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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 1,
  6. "metadata": {
  7. "collapsed": true
  8. },
  9. "outputs": [],
  10. "source": [
  11. "from io import StringIO\n",
  12. "\n",
  13. "import pandas\n",
  14. "\n",
  15. "import wqio"
  16. ]
  17. },
  18. {
  19. "cell_type": "code",
  20. "execution_count": 2,
  21. "metadata": {
  22. "collapsed": true
  23. },
  24. "outputs": [],
  25. "source": [
  26. "peters_data = StringIO(\"\"\"\\\n",
  27. "raw\tconc\tcensor\tdate\n",
  28. "81.00000024\t81.00000024\tFALSE\t4/3/1980\n",
  29. "72.99999893\t72.99999893\tFALSE\t5/17/1980\n",
  30. "129.9999952\t129.9999952\tFALSE\t5/28/1980\n",
  31. "10.99999994\t10.99999994\tFALSE\t4/3/1981\n",
  32. "23.00000004\t23.00000004\tFALSE\t4/22/1981\n",
  33. "65.99999964\t65.99999964\tFALSE\t4/28/1981\n",
  34. "24.00000021\t24.00000021\tFALSE\t5/10/1981\n",
  35. "46.00000009\t46.00000009\tFALSE\t5/29/1981\n",
  36. "50.99999905\t50.99999905\tFALSE\t6/8/1981\n",
  37. "23\t23\tFALSE\t5/17/2000\n",
  38. "<20\t20\tTRUE\t5/25/2001\n",
  39. "20\t20\tFALSE\t5/17/2000\n",
  40. "<20\t20\tTRUE\t5/25/2001\n",
  41. "<20\t20\tTRUE\t5/17/2000\n",
  42. "<20\t20\tTRUE\t5/25/2001\n",
  43. "22\t22\tFALSE\t5/17/2000\n",
  44. "<20\t20\tTRUE\t5/25/2001\n",
  45. "31\t31\tFALSE\t5/17/2000\n",
  46. "22\t22\tFALSE\t5/25/2001\n",
  47. "<20\t20\tTRUE\t5/17/2000\n",
  48. "<20\t20\tTRUE\t5/25/2001\n",
  49. "<20\t20\tTRUE\t5/17/2000\n",
  50. "<20\t20\tTRUE\t5/25/2001\n",
  51. "25\t25\tFALSE\t4/17/1992\n",
  52. "12\t12\tFALSE\t6/1/1992\n",
  53. "43\t43\tFALSE\t4/11/1992\n",
  54. "105\t105\tFALSE\t6/1/1992\n",
  55. "92\t92\tFALSE\t4/11/1992\n",
  56. "97\t97\tFALSE\t6/1/1992\n",
  57. "52\t52\tFALSE\t4/17/1992\n",
  58. "50\t50\tFALSE\t6/1/1992\n",
  59. "93\t93\tFALSE\t6/2/2001\n",
  60. "190\t190\tFALSE\t6/11/2001\n",
  61. "2.7\t2.7\tFALSE\t4/11/2003\n",
  62. "3.8\t3.8\tFALSE\t4/22/2003\n",
  63. "3\t3\tFALSE\t4/26/2003\n",
  64. "2\t2\tFALSE\t4/25/2004\n",
  65. "3\t3\tFALSE\t5/3/2004\n",
  66. "<0.8\t0.8\tTRUE\t4/25/2002\n",
  67. "8.15\t8.15\tFALSE\t4/28/2002\n",
  68. "6.9\t6.9\tFALSE\t4/25/2002\n",
  69. "1.3\t1.3\tFALSE\t4/28/2002\n",
  70. "<2\t2\tTRUE\t3/28/2000\n",
  71. "16\t16\tFALSE\t3/26/2002\n",
  72. "13\t13\tFALSE\t6/18/2003\n",
  73. "19\t19\tFALSE\t3/28/2000\n",
  74. "25\t25\tFALSE\t3/26/2002\n",
  75. "5\t5\tFALSE\t6/18/2003\n",
  76. "27.2\t27.2\tFALSE\t3/28/2000\n",
  77. "35\t35\tFALSE\t3/26/2002\n",
  78. "24\t24\tFALSE\t6/18/2003\n",
  79. "14\t14\tFALSE\t3/28/2000\n",
  80. "200\t200\tFALSE\t3/26/2002\n",
  81. "10\t10\tFALSE\t6/18/2003\n",
  82. "32\t32\tFALSE\t3/28/2000\n",
  83. "75\t75\tFALSE\t3/26/2002\n",
  84. "99\t99\tFALSE\t6/18/2003\n",
  85. "120\t120\tFALSE\t3/28/2000\n",
  86. "18\t18\tFALSE\t3/26/2002\n",
  87. "4\t4\tFALSE\t6/18/2003\n",
  88. "41\t41\tFALSE\t3/28/2000\n",
  89. "39\t39\tFALSE\t3/26/2002\n",
  90. "20\t20\tFALSE\t6/18/2003\n",
  91. "45\t45\tFALSE\t4/3/1980\n",
  92. "18\t18\tFALSE\t4/24/1980\n",
  93. "84\t84\tFALSE\t5/30/1980\n",
  94. "18\t18\tFALSE\t6/1/1980\n",
  95. "20\t20\tFALSE\t5/10/1981\n",
  96. "71\t71\tFALSE\t5/30/1980\n",
  97. "24\t24\tFALSE\t6/1/1980\n",
  98. "40\t40\tFALSE\t6/21/1981\n",
  99. "16\t16\tFALSE\t4/3/1980\n",
  100. "15\t15\tFALSE\t4/24/1980\n",
  101. "30\t30\tFALSE\t5/30/1980\n",
  102. "8\t8\tFALSE\t6/1/1980\n",
  103. "12\t12\tFALSE\t6/5/1980\n",
  104. "10\t10\tFALSE\t4/10/1981\n",
  105. "10\t10\tFALSE\t4/11/1981\n",
  106. "10\t10\tFALSE\t4/22/1981\n",
  107. "10\t10\tFALSE\t4/28/1981\n",
  108. "10\t10\tFALSE\t6/21/1981\n",
  109. "21\t21\tFALSE\t4/3/1980\n",
  110. "15\t15\tFALSE\t6/1/1980\n",
  111. "10\t10\tFALSE\t4/11/1981\n",
  112. "10\t10\tFALSE\t4/22/1981\n",
  113. "10\t10\tFALSE\t6/21/1981\n",
  114. "44\t44\tFALSE\t5/30/1980\n",
  115. "16\t16\tFALSE\t6/5/1980\n",
  116. "40\t40\tFALSE\t3/26/1981\n",
  117. "13.4\t13.4\tFALSE\t4/10/2001\n",
  118. "21.6\t21.6\tFALSE\t4/5/2002\n",
  119. "15.4\t15.4\tFALSE\t5/7/2002\n",
  120. "17.1\t17.1\tFALSE\t5/8/2002\n",
  121. "7.37\t7.37\tFALSE\t6/6/2002\n",
  122. "<1.5\t1.5\tTRUE\t5/6/2001\n",
  123. "<1.5\t1.5\tTRUE\t5/10/2001\n",
  124. "29.5\t29.5\tFALSE\t6/11/2001\n",
  125. "3.1\t3.1\tFALSE\t5/6/2001\n",
  126. "7.35\t7.35\tFALSE\t5/20/2001\n",
  127. "7.11\t7.11\tFALSE\t6/5/2001\n",
  128. "7.5\t7.5\tFALSE\t5/20/2001\n",
  129. "21\t21\tFALSE\t5/21/2001\n",
  130. "12.5\t12.5\tFALSE\t6/5/2001\n",
  131. "2\t2\tFALSE\t5/6/2001\n",
  132. "20.3\t20.3\tFALSE\t5/20/2001\n",
  133. "25.2\t25.2\tFALSE\t6/5/2001\n",
  134. "14.5\t14.5\tFALSE\t5/20/2001\n",
  135. "5.7\t5.7\tFALSE\t5/21/2001\n",
  136. "11.1\t11.1\tFALSE\t6/5/2001\n",
  137. "16.4\t16.4\tFALSE\t4/10/2001\n",
  138. "14.5\t14.5\tFALSE\t5/20/2001\n",
  139. "5.7\t5.7\tFALSE\t5/21/2001\n",
  140. "11.1\t11.1\tFALSE\t6/5/2001\n",
  141. "28.5\t28.5\tFALSE\t4/4/2002\n",
  142. "4.91\t4.91\tFALSE\t6/2/2002\n",
  143. "20.9\t20.9\tFALSE\t6/6/2002\n",
  144. "<3\t3\tTRUE\t6/19/2002\n",
  145. "17.1\t17.1\tFALSE\t4/10/2001\n",
  146. "40\t40\tFALSE\t4/5/2002\n",
  147. "68.1\t68.1\tFALSE\t5/5/2002\n",
  148. "753\t753\tFALSE\t5/7/2002\n",
  149. "9.52\t9.52\tFALSE\t6/3/2002\n",
  150. "6.96\t6.96\tFALSE\t4/10/2001\n",
  151. "2.95\t2.95\tFALSE\t5/1/2001\n",
  152. "13.2\t13.2\tFALSE\t4/5/2002\n",
  153. "74.3\t74.3\tFALSE\t5/5/2002\n",
  154. "37.4\t37.4\tFALSE\t5/7/2002\n",
  155. "<3\t3\tTRUE\t6/3/2002\n",
  156. "13\t13\tFALSE\t4/10/2001\n",
  157. "37.1\t37.1\tFALSE\t4/5/2002\n",
  158. "76.6\t76.6\tFALSE\t5/5/2002\n",
  159. "8.14\t8.14\tFALSE\t5/7/2002\n",
  160. "16.4\t16.4\tFALSE\t6/3/2002\n",
  161. "100\t100\tFALSE\t4/23/1981\n",
  162. "200\t200\tFALSE\t4/29/1981\n",
  163. "100\t100\tFALSE\t4/29/1981\n",
  164. "100\t100\tFALSE\t5/5/1981\n",
  165. "100\t100\tFALSE\t5/29/1981\n",
  166. "100\t100\tFALSE\t5/31/1981\n",
  167. "100\t100\tFALSE\t6/4/1981\n",
  168. "100\t100\tFALSE\t6/6/1981\n",
  169. "100\t100\tFALSE\t6/9/1981\n",
  170. "100\t100\tFALSE\t6/20/1981\n",
  171. "100\t100\tFALSE\t6/22/1981\n",
  172. "46\t46\tFALSE\t4/12/1994\n",
  173. "33\t33\tFALSE\t5/11/1994\n",
  174. "24\t24\tFALSE\t5/14/1994\n",
  175. "16\t16\tFALSE\t6/17/1993\n",
  176. "23\t23\tFALSE\t6/17/1993\n",
  177. "37\t37\tFALSE\t4/12/1994\n",
  178. "25\t25\tFALSE\t3/24/1987\n",
  179. "25\t25\tFALSE\t4/13/1987\n",
  180. "25\t25\tFALSE\t4/21/1987\n",
  181. "50\t50\tFALSE\t5/1/1987\n",
  182. "25\t25\tFALSE\t5/25/1987\n",
  183. "25\t25\tFALSE\t5/27/1987\n",
  184. "25\t25\tFALSE\t6/11/1987\n",
  185. "60\t60\tFALSE\t6/21/1987\n",
  186. "130\t130\tFALSE\t3/24/1988\n",
  187. "25\t25\tFALSE\t3/28/1988\n",
  188. "25\t25\tFALSE\t4/2/1988\n",
  189. "25\t25\tFALSE\t4/5/1988\n",
  190. "57\t57\tFALSE\t6/17/1993\n",
  191. "35\t35\tFALSE\t6/17/1993\n",
  192. "38\t38\tFALSE\t4/12/1994\n",
  193. "44\t44\tFALSE\t6/17/1993\n",
  194. "21\t21\tFALSE\t6/17/1993\n",
  195. "26\t26\tFALSE\t5/14/1994\n",
  196. "\"\"\")"
  197. ]
  198. },
  199. {
  200. "cell_type": "code",
  201. "execution_count": 3,
  202. "metadata": {
  203. "collapsed": false
  204. },
  205. "outputs": [
  206. {
  207. "name": "stdout",
  208. "output_type": "stream",
  209. "text": [
  210. "21.3\n"
  211. ]
  212. }
  213. ],
  214. "source": [
  215. "df = pandas.read_csv(peters_data, sep='\\t')\n",
  216. "print(df['conc'].median())"
  217. ]
  218. },
  219. {
  220. "cell_type": "code",
  221. "execution_count": 4,
  222. "metadata": {
  223. "collapsed": false
  224. },
  225. "outputs": [
  226. {
  227. "data": {
  228. "text/plain": [
  229. "final_data 21.3\n",
  230. "conc 21.3\n",
  231. "dtype: float64"
  232. ]
  233. },
  234. "execution_count": 4,
  235. "metadata": {},
  236. "output_type": "execute_result"
  237. }
  238. ],
  239. "source": [
  240. "ros_df = wqio.ros.MR(df, rescol='conc', qualcol='censor', ndsymbol=True)\n",
  241. "ros_df.data.median()"
  242. ]
  243. },
  244. {
  245. "cell_type": "code",
  246. "execution_count": 5,
  247. "metadata": {
  248. "collapsed": false
  249. },
  250. "outputs": [
  251. {
  252. "name": "stdout",
  253. "output_type": "stream",
  254. "text": [
  255. "Total # of observations: 168\n",
  256. "Censored observations: 15\n"
  257. ]
  258. }
  259. ],
  260. "source": [
  261. "print('Total # of observations: {}'.format(df.shape[0]))\n",
  262. "print('Censored observations: {}'.format(df.query(\"censor == True\").shape[0]))\n"
  263. ]
  264. }
  265. ],
  266. "metadata": {
  267. "kernelspec": {
  268. "display_name": "Python 3",
  269. "language": "python",
  270. "name": "python3"
  271. },
  272. "language_info": {
  273. "codemirror_mode": {
  274. "name": "ipython",
  275. "version": 3
  276. },
  277. "file_extension": ".py",
  278. "mimetype": "text/x-python",
  279. "name": "python",
  280. "nbconvert_exporter": "python",
  281. "pygments_lexer": "ipython3",
  282. "version": "3.4.3"
  283. }
  284. },
  285. "nbformat": 4,
  286. "nbformat_minor": 0
  287. }
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