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1 | 1 | { |
2 | 2 | "metadata": { |
3 | 3 | "name": "", |
4 | | - "signature": "sha256:13c10e46fea51bcbbf203261897bb4d8ea2087e39925e077d452778f78d62b1e" |
| 4 | + "signature": "sha256:7ce6d9e0e1dc3da5c31fc5f3a5ab7687870a76cd4adaedd6da95bc6451755b12" |
5 | 5 | }, |
6 | 6 | "nbformat": 3, |
7 | 7 | "nbformat_minor": 0, |
|
141 | 141 | "language": "python", |
142 | 142 | "metadata": {}, |
143 | 143 | "outputs": [], |
144 | | - "prompt_number": 4 |
| 144 | + "prompt_number": 1 |
145 | 145 | }, |
146 | 146 | { |
147 | 147 | "cell_type": "code", |
|
167 | 167 | ] |
168 | 168 | } |
169 | 169 | ], |
170 | | - "prompt_number": 5 |
| 170 | + "prompt_number": 2 |
171 | 171 | }, |
172 | 172 | { |
173 | 173 | "cell_type": "markdown", |
|
207 | 207 | " \"\"\" Prints CSV file to standard output.\"\"\"\n", |
208 | 208 | " print(50*'-')\n", |
209 | 209 | " for row in csv_content:\n", |
| 210 | + " row = [str(e) for e in row]\n", |
210 | 211 | " print('\\t'.join(row))\n", |
211 | 212 | " print(50*'-')" |
212 | 213 | ], |
213 | 214 | "language": "python", |
214 | 215 | "metadata": {}, |
215 | 216 | "outputs": [], |
216 | | - "prompt_number": 6 |
| 217 | + "prompt_number": 3 |
217 | 218 | }, |
218 | 219 | { |
219 | 220 | "cell_type": "code", |
|
238 | 239 | "name\tcolumn1\tcolumn2\tcolumn3\n", |
239 | 240 | "abc\t1.1\t4.2\t1.2\n", |
240 | 241 | "def\t2.1\t1.4\t5.2\n", |
241 | | - "ghi\t1.5\t1.2\t2.1\n", |
242 | | - "jkl\t1.8\t1.1\t4.2\n", |
| 242 | + "ghi\t1.5\t1.2\t-2.1\n", |
| 243 | + "jkl\t1.8\t-1.1\t4.2\n", |
243 | 244 | "mno\t9.4\t6.6\t6.2\n", |
244 | 245 | "pqr\t1.4\t8.3\t8.4\n", |
245 | 246 | "--------------------------------------------------\n" |
246 | 247 | ] |
247 | 248 | } |
248 | 249 | ], |
249 | | - "prompt_number": 7 |
| 250 | + "prompt_number": 4 |
250 | 251 | }, |
251 | 252 | { |
252 | 253 | "cell_type": "markdown", |
|
291 | 292 | "language": "python", |
292 | 293 | "metadata": {}, |
293 | 294 | "outputs": [], |
294 | | - "prompt_number": 8 |
| 295 | + "prompt_number": 5 |
295 | 296 | }, |
296 | 297 | { |
297 | 298 | "cell_type": "code", |
|
310 | 311 | "text": [ |
311 | 312 | "first 3 rows:\n", |
312 | 313 | "['name', 'column1', 'column2', 'column3']\n", |
313 | | - "['abc', 1.1, 4.2, 1.2]\n", |
314 | | - "['def', 2.1, 1.4, 5.2]\n" |
| 314 | + "['abc', '1.1', '4.2', '1.2']\n", |
| 315 | + "['def', '2.1', '1.4', '5.2']\n" |
315 | 316 | ] |
316 | 317 | } |
317 | 318 | ], |
318 | | - "prompt_number": 9 |
| 319 | + "prompt_number": 6 |
319 | 320 | }, |
320 | 321 | { |
321 | 322 | "cell_type": "markdown", |
|
374 | 375 | "language": "python", |
375 | 376 | "metadata": {}, |
376 | 377 | "outputs": [], |
377 | | - "prompt_number": 10 |
| 378 | + "prompt_number": 7 |
378 | 379 | }, |
379 | 380 | { |
380 | 381 | "cell_type": "markdown", |
|
393 | 394 | "print_csv(csv_cont)\n", |
394 | 395 | "\n", |
395 | 396 | "print('\\n\\nCSV sorted by column \"column3\":')\n", |
| 397 | + "convert_cells_to_floats(csv_cont)\n", |
396 | 398 | "csv_sorted = sort_by_column(csv_cont, 'column3')\n", |
397 | 399 | "print_csv(csv_sorted)" |
398 | 400 | ], |
|
410 | 412 | "name\tcolumn1\tcolumn2\tcolumn3\n", |
411 | 413 | "abc\t1.1\t4.2\t1.2\n", |
412 | 414 | "def\t2.1\t1.4\t5.2\n", |
413 | | - "ghi\t1.5\t1.2\t2.1\n", |
414 | | - "jkl\t1.8\t1.1\t4.2\n", |
| 415 | + "ghi\t1.5\t1.2\t-2.1\n", |
| 416 | + "jkl\t1.8\t-1.1\t4.2\n", |
415 | 417 | "mno\t9.4\t6.6\t6.2\n", |
416 | 418 | "pqr\t1.4\t8.3\t8.4\n", |
417 | 419 | "--------------------------------------------------\n", |
|
420 | 422 | "CSV sorted by column \"column3\":\n", |
421 | 423 | "--------------------------------------------------\n", |
422 | 424 | "name\tcolumn1\tcolumn2\tcolumn3\n", |
| 425 | + "ghi\t1.5\t1.2\t-2.1\n", |
423 | 426 | "abc\t1.1\t4.2\t1.2\n", |
424 | | - "ghi\t1.5\t1.2\t2.1\n", |
425 | | - "jkl\t1.8\t1.1\t4.2\n", |
| 427 | + "jkl\t1.8\t-1.1\t4.2\n", |
426 | 428 | "def\t2.1\t1.4\t5.2\n", |
427 | 429 | "mno\t9.4\t6.6\t6.2\n", |
428 | 430 | "pqr\t1.4\t8.3\t8.4\n", |
429 | 431 | "--------------------------------------------------\n" |
430 | 432 | ] |
431 | 433 | } |
432 | 434 | ], |
433 | | - "prompt_number": 11 |
| 435 | + "prompt_number": 8 |
434 | 436 | }, |
435 | 437 | { |
436 | 438 | "cell_type": "markdown", |
|
489 | 491 | " col_index = sorted_csv[0].index(col)\n", |
490 | 492 | " else:\n", |
491 | 493 | " col_index = col\n", |
492 | | - " sorted_csv[1][col_index] += marker\n", |
| 494 | + " sorted_csv[1][col_index] = str(sorted_csv[1][col_index]) + marker\n", |
493 | 495 | " return None" |
494 | 496 | ], |
495 | 497 | "language": "python", |
496 | 498 | "metadata": {}, |
497 | 499 | "outputs": [], |
498 | | - "prompt_number": 12 |
| 500 | + "prompt_number": 9 |
499 | 501 | }, |
500 | 502 | { |
501 | 503 | "cell_type": "code", |
|
509 | 511 | " (modifies input CSV content list).\n", |
510 | 512 | " \n", |
511 | 513 | " \"\"\"\n", |
512 | | - " for c in csv_cont[0][1:]:\n", |
| 514 | + " for c in range(1, len(csv_cont[0])):\n", |
513 | 515 | " mark_minmax(csv_cont, c, mark_max, marker)\n", |
514 | 516 | " marked_csv = sort_by_column(csv_cont, 0, False)\n", |
515 | 517 | " return marked_csv" |
516 | 518 | ], |
517 | 519 | "language": "python", |
518 | 520 | "metadata": {}, |
519 | 521 | "outputs": [], |
520 | | - "prompt_number": 13 |
| 522 | + "prompt_number": 10 |
521 | 523 | }, |
522 | 524 | { |
523 | 525 | "cell_type": "code", |
524 | 526 | "collapsed": false, |
525 | 527 | "input": [ |
526 | 528 | "import copy\n", |
| 529 | + "\n", |
527 | 530 | "csv_cont = csv_to_list('../Data/test.csv')\n", |
528 | 531 | "\n", |
529 | 532 | "csv_marked = copy.deepcopy(csv_cont)\n", |
530 | | - "mark_all_col(csv_marked, mark_max=True, marker='*')\n", |
531 | | - "mark_all_col(csv_marked, mark_max=False, marker='^')\n", |
| 533 | + "convert_cells_to_floats(csv_marked)\n", |
| 534 | + "mark_all_col(csv_marked, mark_max=False, marker='*')\n", |
532 | 535 | "print_csv(csv_marked)\n", |
533 | | - "\n", |
534 | | - "print('^: min-value\\n*: max-value')" |
| 536 | + "print('*: min-value')" |
535 | 537 | ], |
536 | 538 | "language": "python", |
537 | 539 | "metadata": {}, |
|
542 | 544 | "text": [ |
543 | 545 | "--------------------------------------------------\n", |
544 | 546 | "name\tcolumn1\tcolumn2\tcolumn3\n", |
545 | | - "abc\t1.1^\t4.2\t1.2^\n", |
| 547 | + "abc\t1.1*\t4.2\t1.2\n", |
546 | 548 | "def\t2.1\t1.4\t5.2\n", |
547 | | - "ghi\t1.5\t1.2\t2.1\n", |
548 | | - "jkl\t1.8\t1.1^\t4.2\n", |
549 | | - "mno\t9.4*\t6.6\t6.2\n", |
550 | | - "pqr\t1.4\t8.3*\t8.4*\n", |
| 549 | + "ghi\t1.5\t1.2\t-2.1*\n", |
| 550 | + "jkl\t1.8\t-1.1*\t4.2\n", |
| 551 | + "mno\t9.4\t6.6\t6.2\n", |
| 552 | + "pqr\t1.4\t8.3\t8.4\n", |
551 | 553 | "--------------------------------------------------\n", |
552 | | - "^: min-value\n", |
553 | | - "*: max-value\n" |
| 554 | + "*: min-value\n" |
554 | 555 | ] |
555 | 556 | } |
556 | 557 | ], |
557 | | - "prompt_number": 14 |
| 558 | + "prompt_number": 12 |
558 | 559 | }, |
559 | 560 | { |
560 | 561 | "cell_type": "markdown", |
|
603 | 604 | "language": "python", |
604 | 605 | "metadata": {}, |
605 | 606 | "outputs": [], |
606 | | - "prompt_number": 15 |
| 607 | + "prompt_number": 13 |
607 | 608 | }, |
608 | 609 | { |
609 | 610 | "cell_type": "markdown", |
|
633 | 634 | "Written CSV file:\n", |
634 | 635 | "--------------------------------------------------\n", |
635 | 636 | "name\tcolumn1\tcolumn2\tcolumn3\n", |
636 | | - "abc\t1.1^\t4.2\t1.2^\n", |
| 637 | + "abc\t1.1*\t4.2\t1.2\n", |
637 | 638 | "def\t2.1\t1.4\t5.2\n", |
638 | | - "ghi\t1.5\t1.2\t2.1\n", |
639 | | - "jkl\t1.8\t1.1^\t4.2\n", |
640 | | - "mno\t9.4*\t6.6\t6.2\n", |
641 | | - "pqr\t1.4\t8.3*\t8.4*\n", |
| 639 | + "ghi\t1.5\t1.2\t-2.1*\n", |
| 640 | + "jkl\t1.8\t-1.1*\t4.2\n", |
| 641 | + "mno\t9.4\t6.6\t6.2\n", |
| 642 | + "pqr\t1.4\t8.3\t8.4\n", |
642 | 643 | "--------------------------------------------------\n" |
643 | 644 | ] |
644 | 645 | } |
645 | 646 | ], |
646 | | - "prompt_number": 16 |
| 647 | + "prompt_number": 14 |
647 | 648 | }, |
648 | 649 | { |
649 | 650 | "cell_type": "code", |
|
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