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4_Data_Structure_2.ipynb 26 kB

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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "markdown",
  5. "metadata": {},
  6. "source": [
  7. "# 数据结构 - 2\n",
  8. "\n",
  9. "## 1. 字符串"
  10. ]
  11. },
  12. {
  13. "cell_type": "markdown",
  14. "metadata": {},
  15. "source": [
  16. "字符串是基于文本的有序数据,用单/双/三重引号括起来表示。"
  17. ]
  18. },
  19. {
  20. "cell_type": "code",
  21. "execution_count": 7,
  22. "metadata": {
  23. "collapsed": true
  24. },
  25. "outputs": [],
  26. "source": [
  27. "String0 = 'Taj Mahal is beautiful'\n",
  28. "String1 = \"Taj Mahal is beautiful\"\n",
  29. "String2 = '''Taj Mahal\n",
  30. "is\n",
  31. "beautiful'''\n",
  32. "String3 = \"\"\"Multi-line\n",
  33. "string\"\"\""
  34. ]
  35. },
  36. {
  37. "cell_type": "code",
  38. "execution_count": 8,
  39. "metadata": {},
  40. "outputs": [
  41. {
  42. "name": "stdout",
  43. "output_type": "stream",
  44. "text": [
  45. "Taj Mahal is beautiful <class 'str'>\n",
  46. "Taj Mahal is beautiful <class 'str'>\n",
  47. "Taj Mahal\n",
  48. "is\n",
  49. "beautiful <class 'str'>\n",
  50. "Multi-line\n",
  51. "string <class 'str'>\n"
  52. ]
  53. }
  54. ],
  55. "source": [
  56. "print(String0, type(String0))\n",
  57. "print(String1, type(String1))\n",
  58. "print(String2, type(String2))\n",
  59. "print(String3, type(String3))"
  60. ]
  61. },
  62. {
  63. "cell_type": "markdown",
  64. "metadata": {},
  65. "source": [
  66. "字符串索引和分段类似于前面详细解释过的列表。"
  67. ]
  68. },
  69. {
  70. "cell_type": "code",
  71. "execution_count": 9,
  72. "metadata": {},
  73. "outputs": [
  74. {
  75. "name": "stdout",
  76. "output_type": "stream",
  77. "text": [
  78. "M\n",
  79. "Mahal is beautiful\n",
  80. "l\n"
  81. ]
  82. }
  83. ],
  84. "source": [
  85. "print(String0[4])\n",
  86. "print(String0[4:])\n",
  87. "print(String0[-1])"
  88. ]
  89. },
  90. {
  91. "cell_type": "markdown",
  92. "metadata": {},
  93. "source": [
  94. "### 1.1 内置函数"
  95. ]
  96. },
  97. {
  98. "cell_type": "markdown",
  99. "metadata": {},
  100. "source": [
  101. "**find( )** 函数返回要在字符串中找到的给定数据的索引值。如果没有找到它,它返回 **-1**。请注意不要将返回的-1与反向索引值混淆。"
  102. ]
  103. },
  104. {
  105. "cell_type": "code",
  106. "execution_count": 10,
  107. "metadata": {},
  108. "outputs": [
  109. {
  110. "name": "stdout",
  111. "output_type": "stream",
  112. "text": [
  113. "Taj Mahal is beautiful\n",
  114. "7\n",
  115. "-1\n"
  116. ]
  117. }
  118. ],
  119. "source": [
  120. "print(String0)\n",
  121. "print(String0.find('al'))\n",
  122. "print(String0.find('am'))"
  123. ]
  124. },
  125. {
  126. "cell_type": "markdown",
  127. "metadata": {},
  128. "source": [
  129. "返回的索引值是输入数据中第一个元素的索引。"
  130. ]
  131. },
  132. {
  133. "cell_type": "code",
  134. "execution_count": 6,
  135. "metadata": {},
  136. "outputs": [
  137. {
  138. "name": "stdout",
  139. "output_type": "stream",
  140. "text": [
  141. "a\n"
  142. ]
  143. }
  144. ],
  145. "source": [
  146. "print(String0[7])"
  147. ]
  148. },
  149. {
  150. "cell_type": "markdown",
  151. "metadata": {},
  152. "source": [
  153. "还可以输入**find()** 函数,在它们之间搜索索引值。"
  154. ]
  155. },
  156. {
  157. "cell_type": "code",
  158. "execution_count": 7,
  159. "metadata": {},
  160. "outputs": [
  161. {
  162. "name": "stdout",
  163. "output_type": "stream",
  164. "text": [
  165. "2\n",
  166. "2\n"
  167. ]
  168. }
  169. ],
  170. "source": [
  171. "print(String0.find('j',1))\n",
  172. "print(String0.find('j',1,3))"
  173. ]
  174. },
  175. {
  176. "cell_type": "markdown",
  177. "metadata": {},
  178. "source": [
  179. "**capitalize( )** 用于将字符串中的第一个元素大写。"
  180. ]
  181. },
  182. {
  183. "cell_type": "code",
  184. "execution_count": 11,
  185. "metadata": {},
  186. "outputs": [
  187. {
  188. "name": "stdout",
  189. "output_type": "stream",
  190. "text": [
  191. "Observe the first letter in this sentence. can you change this sentence\n"
  192. ]
  193. }
  194. ],
  195. "source": [
  196. "String3 = 'observe the first letter in this sentence. can you change this sentence'\n",
  197. "print(String3.capitalize())"
  198. ]
  199. },
  200. {
  201. "cell_type": "markdown",
  202. "metadata": {},
  203. "source": [
  204. "**center( )** 用于通过指定字段宽度将字符串居中对齐。"
  205. ]
  206. },
  207. {
  208. "cell_type": "code",
  209. "execution_count": 12,
  210. "metadata": {},
  211. "outputs": [
  212. {
  213. "data": {
  214. "text/plain": [
  215. "' Taj Mahal is beautiful '"
  216. ]
  217. },
  218. "execution_count": 12,
  219. "metadata": {},
  220. "output_type": "execute_result"
  221. }
  222. ],
  223. "source": [
  224. "String0.center(70)"
  225. ]
  226. },
  227. {
  228. "cell_type": "markdown",
  229. "metadata": {},
  230. "source": [
  231. "One can also fill the left out spaces with any other character."
  232. ]
  233. },
  234. {
  235. "cell_type": "code",
  236. "execution_count": 13,
  237. "metadata": {},
  238. "outputs": [
  239. {
  240. "data": {
  241. "text/plain": [
  242. "'------------------------Taj Mahal is beautiful------------------------'"
  243. ]
  244. },
  245. "execution_count": 13,
  246. "metadata": {},
  247. "output_type": "execute_result"
  248. }
  249. ],
  250. "source": [
  251. "String0.center(70,'-')"
  252. ]
  253. },
  254. {
  255. "cell_type": "markdown",
  256. "metadata": {},
  257. "source": [
  258. "**zfill( )** 通过指定字段宽度来填充零。"
  259. ]
  260. },
  261. {
  262. "cell_type": "code",
  263. "execution_count": 14,
  264. "metadata": {},
  265. "outputs": [
  266. {
  267. "data": {
  268. "text/plain": [
  269. "'00000000Taj Mahal is beautiful'"
  270. ]
  271. },
  272. "execution_count": 14,
  273. "metadata": {},
  274. "output_type": "execute_result"
  275. }
  276. ],
  277. "source": [
  278. "String0.zfill(30)"
  279. ]
  280. },
  281. {
  282. "cell_type": "markdown",
  283. "metadata": {},
  284. "source": [
  285. "**expandtabs( )** 允许您更改制表符的间距。`'\\t'`默认设置为8个空格。"
  286. ]
  287. },
  288. {
  289. "cell_type": "code",
  290. "execution_count": 16,
  291. "metadata": {},
  292. "outputs": [
  293. {
  294. "name": "stdout",
  295. "output_type": "stream",
  296. "text": [
  297. "h\te\tl\tl\to\n",
  298. "h e l l o\n",
  299. "h e l l o\n"
  300. ]
  301. }
  302. ],
  303. "source": [
  304. "s = 'h\\te\\tl\\tl\\to'\n",
  305. "print(s)\n",
  306. "print(s.expandtabs(1))\n",
  307. "print(s.expandtabs(4))"
  308. ]
  309. },
  310. {
  311. "cell_type": "markdown",
  312. "metadata": {
  313. "collapsed": true
  314. },
  315. "source": [
  316. "**index( )** 和 **find( )** 函数的工作方式相同,唯一的区别在于 **find( )** 返回 `-1`,当输入元素在字符串中没有找到,但是**index( )** 函数会抛出一个 `ValueError`异常。"
  317. ]
  318. },
  319. {
  320. "cell_type": "code",
  321. "execution_count": 17,
  322. "metadata": {},
  323. "outputs": [
  324. {
  325. "name": "stdout",
  326. "output_type": "stream",
  327. "text": [
  328. "0\n",
  329. "4\n"
  330. ]
  331. },
  332. {
  333. "ename": "ValueError",
  334. "evalue": "substring not found",
  335. "output_type": "error",
  336. "traceback": [
  337. "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
  338. "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
  339. "\u001b[0;32m<ipython-input-17-146ef93bc1cd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Taj'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mString0\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Mahal'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
  340. "\u001b[0;31mValueError\u001b[0m: substring not found"
  341. ]
  342. }
  343. ],
  344. "source": [
  345. "print(String0.index('Taj'))\n",
  346. "print(String0.index('Mahal',0))\n",
  347. "print(String0.index('Mahal',10,20))"
  348. ]
  349. },
  350. {
  351. "cell_type": "markdown",
  352. "metadata": {},
  353. "source": [
  354. "**endswith( )** 函数用于检查给定字符串是否以作为输入的特定字符结尾。"
  355. ]
  356. },
  357. {
  358. "cell_type": "code",
  359. "execution_count": 18,
  360. "metadata": {},
  361. "outputs": [
  362. {
  363. "name": "stdout",
  364. "output_type": "stream",
  365. "text": [
  366. "False\n"
  367. ]
  368. }
  369. ],
  370. "source": [
  371. "print(String0.endswith('y'))"
  372. ]
  373. },
  374. {
  375. "cell_type": "markdown",
  376. "metadata": {},
  377. "source": [
  378. "还可以指定开始和停止索引值。"
  379. ]
  380. },
  381. {
  382. "cell_type": "code",
  383. "execution_count": 19,
  384. "metadata": {},
  385. "outputs": [
  386. {
  387. "name": "stdout",
  388. "output_type": "stream",
  389. "text": [
  390. "True\n",
  391. "True\n"
  392. ]
  393. }
  394. ],
  395. "source": [
  396. "print(String0.endswith('l',0))\n",
  397. "print(String0.endswith('M',0,5))"
  398. ]
  399. },
  400. {
  401. "cell_type": "markdown",
  402. "metadata": {},
  403. "source": [
  404. "**count( )** 函数计算给定字符串中的字符数。也可以指定开始和停止索引或将其留空。(这些是隐式参数,将在函数中处理)"
  405. ]
  406. },
  407. {
  408. "cell_type": "code",
  409. "execution_count": 20,
  410. "metadata": {},
  411. "outputs": [
  412. {
  413. "name": "stdout",
  414. "output_type": "stream",
  415. "text": [
  416. "4\n",
  417. "2\n"
  418. ]
  419. }
  420. ],
  421. "source": [
  422. "print(String0.count('a',0))\n",
  423. "print(String0.count('a',5,10))"
  424. ]
  425. },
  426. {
  427. "cell_type": "markdown",
  428. "metadata": {},
  429. "source": [
  430. "**join( )** 函数在输入字符串的元素之间添加一个字符。"
  431. ]
  432. },
  433. {
  434. "cell_type": "code",
  435. "execution_count": 21,
  436. "metadata": {},
  437. "outputs": [
  438. {
  439. "data": {
  440. "text/plain": [
  441. "'*a_a-'"
  442. ]
  443. },
  444. "execution_count": 21,
  445. "metadata": {},
  446. "output_type": "execute_result"
  447. }
  448. ],
  449. "source": [
  450. "'a'.join('*_-')"
  451. ]
  452. },
  453. {
  454. "cell_type": "code",
  455. "execution_count": 22,
  456. "metadata": {},
  457. "outputs": [
  458. {
  459. "data": {
  460. "text/plain": [
  461. "'1\\n2'"
  462. ]
  463. },
  464. "execution_count": 22,
  465. "metadata": {},
  466. "output_type": "execute_result"
  467. }
  468. ],
  469. "source": [
  470. "'\\n'.join(['1', '2'])"
  471. ]
  472. },
  473. {
  474. "cell_type": "markdown",
  475. "metadata": {},
  476. "source": [
  477. "'*_-' 是输入字符串而字符'a'被添加在每一个元素之间。"
  478. ]
  479. },
  480. {
  481. "cell_type": "markdown",
  482. "metadata": {},
  483. "source": [
  484. "**join( )** 函数也可以被用来将列表转化为字符串。"
  485. ]
  486. },
  487. {
  488. "cell_type": "code",
  489. "execution_count": 25,
  490. "metadata": {},
  491. "outputs": [
  492. {
  493. "name": "stdout",
  494. "output_type": "stream",
  495. "text": [
  496. "['T', 'a', 'j', ' ', 'M', 'a', 'h', 'a', 'l', ' ', 'i', 's', ' ', 'b', 'e', 'a', 'u', 't', 'i', 'f', 'u', 'l']\n",
  497. "Taj Mahal is beautiful\n"
  498. ]
  499. }
  500. ],
  501. "source": [
  502. "a = list(String0)\n",
  503. "print(a)\n",
  504. "b = ''.join(a)\n",
  505. "print(b)"
  506. ]
  507. },
  508. {
  509. "cell_type": "markdown",
  510. "metadata": {},
  511. "source": [
  512. "在将它转化成字符串之前,**join( )** 函数可以被用来在列表元素中插入任意的字符。"
  513. ]
  514. },
  515. {
  516. "cell_type": "code",
  517. "execution_count": 27,
  518. "metadata": {},
  519. "outputs": [
  520. {
  521. "name": "stdout",
  522. "output_type": "stream",
  523. "text": [
  524. " /i/s/ /b/e/a/u/t/i/f/u/l\n"
  525. ]
  526. }
  527. ],
  528. "source": [
  529. "c = '/'.join(a)[18:]\n",
  530. "print(c)"
  531. ]
  532. },
  533. {
  534. "cell_type": "markdown",
  535. "metadata": {},
  536. "source": [
  537. "**split( )** 函数被用来将一个字符串转化为列表。把它想成与**join()** 相反地函数。"
  538. ]
  539. },
  540. {
  541. "cell_type": "code",
  542. "execution_count": 28,
  543. "metadata": {},
  544. "outputs": [
  545. {
  546. "name": "stdout",
  547. "output_type": "stream",
  548. "text": [
  549. "[' ', 'i', 's', ' ', 'b', 'e', 'a', 'u', 't', 'i', 'f', 'u', 'l']\n"
  550. ]
  551. }
  552. ],
  553. "source": [
  554. "d = c.split('/')\n",
  555. "print(d)"
  556. ]
  557. },
  558. {
  559. "cell_type": "markdown",
  560. "metadata": {},
  561. "source": [
  562. "在 **split( )** 函数中,还可以指定分割字符串的次数,或者新返回列表应该包含的元素数量。元素的数量总是比指定的数量多1,这是因为它被分割了指定的次数。"
  563. ]
  564. },
  565. {
  566. "cell_type": "code",
  567. "execution_count": 29,
  568. "metadata": {},
  569. "outputs": [
  570. {
  571. "name": "stdout",
  572. "output_type": "stream",
  573. "text": [
  574. "[' ', 'i', 's', ' /b/e/a/u/t/i/f/u/l']\n",
  575. "4\n"
  576. ]
  577. }
  578. ],
  579. "source": [
  580. "e = c.split('/',3)\n",
  581. "print(e)\n",
  582. "print(len(e))"
  583. ]
  584. },
  585. {
  586. "cell_type": "markdown",
  587. "metadata": {},
  588. "source": [
  589. "**lower( )** 将任何大写字母转换为小写字母。"
  590. ]
  591. },
  592. {
  593. "cell_type": "code",
  594. "execution_count": 30,
  595. "metadata": {},
  596. "outputs": [
  597. {
  598. "name": "stdout",
  599. "output_type": "stream",
  600. "text": [
  601. "Taj Mahal is beautiful\n",
  602. "taj mahal is beautiful\n"
  603. ]
  604. }
  605. ],
  606. "source": [
  607. "print(String0)\n",
  608. "print(String0.lower())"
  609. ]
  610. },
  611. {
  612. "cell_type": "markdown",
  613. "metadata": {},
  614. "source": [
  615. "**upper( )** 将任何小写字母转换为大写字母。"
  616. ]
  617. },
  618. {
  619. "cell_type": "code",
  620. "execution_count": 31,
  621. "metadata": {},
  622. "outputs": [
  623. {
  624. "data": {
  625. "text/plain": [
  626. "'TAJ MAHAL IS BEAUTIFUL'"
  627. ]
  628. },
  629. "execution_count": 31,
  630. "metadata": {},
  631. "output_type": "execute_result"
  632. }
  633. ],
  634. "source": [
  635. "String0.upper()"
  636. ]
  637. },
  638. {
  639. "cell_type": "markdown",
  640. "metadata": {},
  641. "source": [
  642. "**replace( )** 函数将该元素替换为另一个元素。"
  643. ]
  644. },
  645. {
  646. "cell_type": "code",
  647. "execution_count": 32,
  648. "metadata": {},
  649. "outputs": [
  650. {
  651. "data": {
  652. "text/plain": [
  653. "'Bengaluru is beautiful'"
  654. ]
  655. },
  656. "execution_count": 32,
  657. "metadata": {},
  658. "output_type": "execute_result"
  659. }
  660. ],
  661. "source": [
  662. "String0.replace('Taj Mahal','Bengaluru')"
  663. ]
  664. },
  665. {
  666. "cell_type": "markdown",
  667. "metadata": {},
  668. "source": [
  669. "**strip( )** 函数用于从右端和左端删除不需要的元素。"
  670. ]
  671. },
  672. {
  673. "cell_type": "code",
  674. "execution_count": 33,
  675. "metadata": {
  676. "collapsed": true
  677. },
  678. "outputs": [],
  679. "source": [
  680. "f = ' hello '"
  681. ]
  682. },
  683. {
  684. "cell_type": "markdown",
  685. "metadata": {},
  686. "source": [
  687. "如果没有指定字符,那么它将删除数据左边和右边的所有空格。"
  688. ]
  689. },
  690. {
  691. "cell_type": "code",
  692. "execution_count": 34,
  693. "metadata": {},
  694. "outputs": [
  695. {
  696. "data": {
  697. "text/plain": [
  698. "'hello'"
  699. ]
  700. },
  701. "execution_count": 34,
  702. "metadata": {},
  703. "output_type": "execute_result"
  704. }
  705. ],
  706. "source": [
  707. "f.strip()"
  708. ]
  709. },
  710. {
  711. "cell_type": "markdown",
  712. "metadata": {},
  713. "source": [
  714. "**strip( )** 函数,当指定字符时,如果该字符出现在指定字符串的两端,则删除该字符。"
  715. ]
  716. },
  717. {
  718. "cell_type": "code",
  719. "execution_count": 35,
  720. "metadata": {
  721. "collapsed": true
  722. },
  723. "outputs": [],
  724. "source": [
  725. "f = ' ***----hello---******* '"
  726. ]
  727. },
  728. {
  729. "cell_type": "code",
  730. "execution_count": 36,
  731. "metadata": {},
  732. "outputs": [
  733. {
  734. "data": {
  735. "text/plain": [
  736. "'hello'"
  737. ]
  738. },
  739. "execution_count": 36,
  740. "metadata": {},
  741. "output_type": "execute_result"
  742. }
  743. ],
  744. "source": [
  745. "f.strip(' *-')"
  746. ]
  747. },
  748. {
  749. "cell_type": "markdown",
  750. "metadata": {},
  751. "source": [
  752. "必须删除星号,但没有。这是因为在左边和右边都有一个空格。在strip函数中。字符需要按照它们出现的特定顺序输入。"
  753. ]
  754. },
  755. {
  756. "cell_type": "code",
  757. "execution_count": 37,
  758. "metadata": {},
  759. "outputs": [
  760. {
  761. "name": "stdout",
  762. "output_type": "stream",
  763. "text": [
  764. "----hello---\n",
  765. "hello\n"
  766. ]
  767. }
  768. ],
  769. "source": [
  770. "print(f.strip(' *'))\n",
  771. "print(f.strip(' *-'))"
  772. ]
  773. },
  774. {
  775. "cell_type": "markdown",
  776. "metadata": {},
  777. "source": [
  778. "**lstrip( )** 和 **rstrip( )** 函数具有与strip函数相同的功能,但唯一的区别是**lstrip()** 只删除左边的内容,而**rstrip()** 只删除右边的内容。"
  779. ]
  780. },
  781. {
  782. "cell_type": "code",
  783. "execution_count": 38,
  784. "metadata": {},
  785. "outputs": [
  786. {
  787. "name": "stdout",
  788. "output_type": "stream",
  789. "text": [
  790. "----hello---******* \n",
  791. " ***----hello---\n"
  792. ]
  793. }
  794. ],
  795. "source": [
  796. "print(f.lstrip(' *'))\n",
  797. "print(f.rstrip(' *'))"
  798. ]
  799. },
  800. {
  801. "cell_type": "markdown",
  802. "metadata": {},
  803. "source": [
  804. "## 2. 词典"
  805. ]
  806. },
  807. {
  808. "cell_type": "markdown",
  809. "metadata": {},
  810. "source": [
  811. "词典更像数据库,因为在这里你可以用用户定义的字符串索引特定的序列。"
  812. ]
  813. },
  814. {
  815. "cell_type": "markdown",
  816. "metadata": {},
  817. "source": [
  818. "为了定义一个词典,让一个变量赋值为 `{ }`或`dict()`。"
  819. ]
  820. },
  821. {
  822. "cell_type": "code",
  823. "execution_count": 39,
  824. "metadata": {},
  825. "outputs": [
  826. {
  827. "name": "stdout",
  828. "output_type": "stream",
  829. "text": [
  830. "<class 'dict'> <class 'dict'>\n"
  831. ]
  832. }
  833. ],
  834. "source": [
  835. "d0 = {}\n",
  836. "d1 = dict()\n",
  837. "print(type(d0), type(d1))"
  838. ]
  839. },
  840. {
  841. "cell_type": "markdown",
  842. "metadata": {},
  843. "source": [
  844. "词典的工作方式有点像列表,但增加了分配自己索引样式的功能。"
  845. ]
  846. },
  847. {
  848. "cell_type": "code",
  849. "execution_count": 41,
  850. "metadata": {},
  851. "outputs": [
  852. {
  853. "name": "stdout",
  854. "output_type": "stream",
  855. "text": [
  856. "{'One': 1, 'OneTwo': 12}\n"
  857. ]
  858. }
  859. ],
  860. "source": [
  861. "d0['One'] = 1\n",
  862. "d0['OneTwo'] = 12 \n",
  863. "print(d0)"
  864. ]
  865. },
  866. {
  867. "cell_type": "code",
  868. "execution_count": 42,
  869. "metadata": {},
  870. "outputs": [
  871. {
  872. "name": "stdout",
  873. "output_type": "stream",
  874. "text": [
  875. "{'key1': 1, 'key2': [1, 2, 4], 3: (1, 4, 6)}\n"
  876. ]
  877. }
  878. ],
  879. "source": [
  880. "d1 = {\"key1\":1, \"key2\":[1,2,4], 3:(1, 4, 6)}\n",
  881. "print(d1)"
  882. ]
  883. },
  884. {
  885. "cell_type": "markdown",
  886. "metadata": {},
  887. "source": [
  888. "这就是字典的样子。现在你可以通过设为 `'One'` 的索引值来访问 `1` "
  889. ]
  890. },
  891. {
  892. "cell_type": "code",
  893. "execution_count": 43,
  894. "metadata": {},
  895. "outputs": [
  896. {
  897. "name": "stdout",
  898. "output_type": "stream",
  899. "text": [
  900. "1\n"
  901. ]
  902. }
  903. ],
  904. "source": [
  905. "print(d0['One'])"
  906. ]
  907. },
  908. {
  909. "cell_type": "markdown",
  910. "metadata": {},
  911. "source": [
  912. "两个相关的列表可以合并成一个词典。"
  913. ]
  914. },
  915. {
  916. "cell_type": "code",
  917. "execution_count": 44,
  918. "metadata": {
  919. "collapsed": true
  920. },
  921. "outputs": [],
  922. "source": [
  923. "names = ['One', 'Two', 'Three', 'Four', 'Five']\n",
  924. "numbers = [1, 2, 3, 4, 5]"
  925. ]
  926. },
  927. {
  928. "cell_type": "markdown",
  929. "metadata": {},
  930. "source": [
  931. "**zip( )** 函数用来结合两个列表。"
  932. ]
  933. },
  934. {
  935. "cell_type": "code",
  936. "execution_count": 45,
  937. "metadata": {},
  938. "outputs": [
  939. {
  940. "name": "stdout",
  941. "output_type": "stream",
  942. "text": [
  943. "{'One': 1, 'Three': 3, 'Five': 5, 'Four': 4, 'Two': 2}\n"
  944. ]
  945. }
  946. ],
  947. "source": [
  948. "d2 = zip(names,numbers)\n",
  949. "print(dict(d2))"
  950. ]
  951. },
  952. {
  953. "cell_type": "code",
  954. "execution_count": 46,
  955. "metadata": {},
  956. "outputs": [
  957. {
  958. "name": "stdout",
  959. "output_type": "stream",
  960. "text": [
  961. "{'One': 1, 'Three': 3, 'Five': 5, 'Four': 4, 'Two': 2}\n"
  962. ]
  963. }
  964. ],
  965. "source": [
  966. "d3 = {names[i]:numbers[i] for i in range(len(names))}\n",
  967. "print(d3)"
  968. ]
  969. },
  970. {
  971. "cell_type": "markdown",
  972. "metadata": {},
  973. "source": [
  974. "这两个列表组合成一个列表,每个元素都与元组中来自另一个列表的各自元素相连。\n",
  975. "\n",
  976. "进一步地,为了将上面的内容转化为词典。我们可以使用 **dict( )** 函数。"
  977. ]
  978. },
  979. {
  980. "cell_type": "code",
  981. "execution_count": 5,
  982. "metadata": {},
  983. "outputs": [
  984. {
  985. "name": "stdout",
  986. "output_type": "stream",
  987. "text": [
  988. "{'One': 1, 'Four': 4, 'Three': 3, 'Five': 5, 'Two': 2}\n"
  989. ]
  990. }
  991. ],
  992. "source": [
  993. "d2 = zip(names,numbers)\n",
  994. "\n",
  995. "a1 = dict(d2)\n",
  996. "print(a1)"
  997. ]
  998. },
  999. {
  1000. "cell_type": "markdown",
  1001. "metadata": {},
  1002. "source": [
  1003. "### 2.1 内置函数"
  1004. ]
  1005. },
  1006. {
  1007. "cell_type": "markdown",
  1008. "metadata": {},
  1009. "source": [
  1010. "**clear( )** 函数被用于擦除所创建的整个词典。"
  1011. ]
  1012. },
  1013. {
  1014. "cell_type": "code",
  1015. "execution_count": 47,
  1016. "metadata": {},
  1017. "outputs": [
  1018. {
  1019. "name": "stdout",
  1020. "output_type": "stream",
  1021. "text": [
  1022. "{}\n"
  1023. ]
  1024. }
  1025. ],
  1026. "source": [
  1027. "a1 = {1:10, 2:20}\n",
  1028. "a1.clear()\n",
  1029. "print(a1)"
  1030. ]
  1031. },
  1032. {
  1033. "cell_type": "markdown",
  1034. "metadata": {},
  1035. "source": [
  1036. "词典也可以使用循环来构建。"
  1037. ]
  1038. },
  1039. {
  1040. "cell_type": "code",
  1041. "execution_count": 48,
  1042. "metadata": {},
  1043. "outputs": [
  1044. {
  1045. "name": "stdout",
  1046. "output_type": "stream",
  1047. "text": [
  1048. "{'One': 1, 'Three': 3, 'Five': 5, 'Four': 4, 'Two': 2}\n"
  1049. ]
  1050. }
  1051. ],
  1052. "source": [
  1053. "a1 = {names[i]:numbers[i] for i in range(len(names))}\n",
  1054. "print(a1)"
  1055. ]
  1056. },
  1057. {
  1058. "cell_type": "code",
  1059. "execution_count": 49,
  1060. "metadata": {},
  1061. "outputs": [
  1062. {
  1063. "name": "stdout",
  1064. "output_type": "stream",
  1065. "text": [
  1066. "{'One': 1, 'Three': 3, 'Five': 5, 'Four': 4, 'Two': 2}\n"
  1067. ]
  1068. }
  1069. ],
  1070. "source": [
  1071. "for i in range(len(names)):\n",
  1072. " a1[names[i]] = numbers[i]\n",
  1073. "print(a1)"
  1074. ]
  1075. },
  1076. {
  1077. "cell_type": "markdown",
  1078. "metadata": {},
  1079. "source": [
  1080. "**values( )** 函数返回了一个包含词典中所有赋值的列表"
  1081. ]
  1082. },
  1083. {
  1084. "cell_type": "code",
  1085. "execution_count": 50,
  1086. "metadata": {},
  1087. "outputs": [
  1088. {
  1089. "data": {
  1090. "text/plain": [
  1091. "dict_values([1, 3, 5, 4, 2])"
  1092. ]
  1093. },
  1094. "execution_count": 50,
  1095. "metadata": {},
  1096. "output_type": "execute_result"
  1097. }
  1098. ],
  1099. "source": [
  1100. "a1.values()"
  1101. ]
  1102. },
  1103. {
  1104. "cell_type": "markdown",
  1105. "metadata": {},
  1106. "source": [
  1107. "**keys( )** 函数返回包含赋值的所有索引或键。"
  1108. ]
  1109. },
  1110. {
  1111. "cell_type": "code",
  1112. "execution_count": 51,
  1113. "metadata": {},
  1114. "outputs": [
  1115. {
  1116. "data": {
  1117. "text/plain": [
  1118. "dict_keys(['One', 'Three', 'Five', 'Four', 'Two'])"
  1119. ]
  1120. },
  1121. "execution_count": 51,
  1122. "metadata": {},
  1123. "output_type": "execute_result"
  1124. }
  1125. ],
  1126. "source": [
  1127. "a1.keys()"
  1128. ]
  1129. },
  1130. {
  1131. "cell_type": "markdown",
  1132. "metadata": {},
  1133. "source": [
  1134. "**items()** 返回一个列表同时也包含该列表,但是词典中的每个元素都在一个元组中。这与使用zip函数得到的结果相同。"
  1135. ]
  1136. },
  1137. {
  1138. "cell_type": "code",
  1139. "execution_count": 52,
  1140. "metadata": {},
  1141. "outputs": [
  1142. {
  1143. "name": "stdout",
  1144. "output_type": "stream",
  1145. "text": [
  1146. "[ One] 1\n",
  1147. "[ Three] 3\n",
  1148. "[ Five] 5\n",
  1149. "[ Four] 4\n",
  1150. "[ Two] 2\n"
  1151. ]
  1152. }
  1153. ],
  1154. "source": [
  1155. "a1.items()\n",
  1156. "\n",
  1157. "for (k,v) in a1.items():\n",
  1158. " print(\"[%6s] %d\" % (k, v))"
  1159. ]
  1160. },
  1161. {
  1162. "cell_type": "markdown",
  1163. "metadata": {},
  1164. "source": [
  1165. "**pop()** 函数用于删除特定的元素,并且这个删除的元素可以被分配给一个新的变量。但是请记住,只存储值而不存储键,因为它只是一个索引值。"
  1166. ]
  1167. },
  1168. {
  1169. "cell_type": "code",
  1170. "execution_count": 55,
  1171. "metadata": {},
  1172. "outputs": [
  1173. {
  1174. "ename": "KeyError",
  1175. "evalue": "'One'",
  1176. "output_type": "error",
  1177. "traceback": [
  1178. "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
  1179. "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
  1180. "\u001b[0;32m<ipython-input-55-d348bc398654>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0ma1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'One'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
  1181. "\u001b[0;31mKeyError\u001b[0m: 'One'"
  1182. ]
  1183. }
  1184. ],
  1185. "source": [
  1186. "a2 = a1.pop('One')\n",
  1187. "print(a1)\n",
  1188. "print(a2)"
  1189. ]
  1190. }
  1191. ],
  1192. "metadata": {
  1193. "kernelspec": {
  1194. "display_name": "Python 3",
  1195. "language": "python",
  1196. "name": "python3"
  1197. },
  1198. "language_info": {
  1199. "codemirror_mode": {
  1200. "name": "ipython",
  1201. "version": 3
  1202. },
  1203. "file_extension": ".py",
  1204. "mimetype": "text/x-python",
  1205. "name": "python",
  1206. "nbconvert_exporter": "python",
  1207. "pygments_lexer": "ipython3",
  1208. "version": "3.5.4"
  1209. }
  1210. },
  1211. "nbformat": 4,
  1212. "nbformat_minor": 1
  1213. }

机器学习越来越多应用到飞行器、机器人等领域,其目的是利用计算机实现类似人类的智能,从而实现装备的智能化与无人化。本课程旨在引导学生掌握机器学习的基本知识、典型方法与技术,通过具体的应用案例激发学生对该学科的兴趣,鼓励学生能够从人工智能的角度来分析、解决飞行器、机器人所面临的问题和挑战。本课程主要内容包括Python编程基础,机器学习模型,无监督学习、监督学习、深度学习基础知识与实现,并学习如何利用机器学习解决实际问题,从而全面提升自我的《综合能力》。