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2 | 2 | "cells": [
|
3 | 3 | {
|
4 | 4 | "cell_type": "code",
|
5 |
| - "execution_count": 10, |
| 5 | + "execution_count": 1, |
6 | 6 | "metadata": {},
|
7 | 7 | "outputs": [
|
8 | 8 | {
|
9 |
| - "name": "stdout", |
| 9 | + "name": "stderr", |
10 | 10 | "output_type": "stream",
|
11 | 11 | "text": [
|
12 |
| - "The rpy2.ipython extension is already loaded. To reload it, use:\n", |
13 |
| - " %reload_ext rpy2.ipython\n" |
| 12 | + "/Users/cc1333/Library/Python/3.9/lib/python/site-packages/rpy2/ipython/rmagic.py:77: UserWarning: The Python package `pandas` is strongly recommended when using `rpy2.ipython`. Unfortunately it could not be loaded (error: No module named 'pandas'), but at least we found `numpy`.\n", |
| 13 | + " warnings.warn('The Python package `pandas` is strongly '\n" |
14 | 14 | ]
|
15 | 15 | }
|
16 | 16 | ],
|
|
20 | 20 | },
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21 | 21 | {
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22 | 22 | "cell_type": "code",
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23 |
| - "execution_count": 11, |
| 23 | + "execution_count": 2, |
24 | 24 | "metadata": {},
|
25 | 25 | "outputs": [],
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26 | 26 | "source": [
|
|
29 | 29 | " suppressMessages({\n",
|
30 | 30 | " library(data.table)\n",
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31 | 31 | " library(dplyr)\n",
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32 |
| - " library(learnr)\n", |
33 |
| - " library(microbenchmark)\n", |
34 |
| - " library(parallel)\n", |
35 |
| - " library(parallelly)\n", |
36 |
| - " library(profvis)\n", |
37 |
| - " library(Rcpp)\n", |
38 |
| - " library(styler)\n", |
39 | 32 | " })\n",
|
40 | 33 | "})"
|
41 | 34 | ]
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|
68 | 61 | },
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69 | 62 | {
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70 | 63 | "cell_type": "code",
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71 |
| - "execution_count": 12, |
| 64 | + "execution_count": 3, |
72 | 65 | "metadata": {},
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73 | 66 | "outputs": [
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74 | 67 | {
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144 | 137 | },
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145 | 138 | {
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146 | 139 | "cell_type": "code",
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147 |
| - "execution_count": 13, |
| 140 | + "execution_count": 4, |
148 | 141 | "metadata": {},
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149 | 142 | "outputs": [],
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150 | 143 | "source": [
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176 | 169 | },
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177 | 170 | {
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178 | 171 | "cell_type": "code",
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179 |
| - "execution_count": 15, |
| 172 | + "execution_count": 5, |
180 | 173 | "metadata": {},
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181 | 174 | "outputs": [
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182 | 175 | {
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|
219 | 212 | },
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220 | 213 | {
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221 | 214 | "cell_type": "code",
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222 |
| - "execution_count": 16, |
| 215 | + "execution_count": 6, |
223 | 216 | "metadata": {},
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224 | 217 | "outputs": [
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225 | 218 | {
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|
257 | 250 | },
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258 | 251 | {
|
259 | 252 | "cell_type": "code",
|
260 |
| - "execution_count": 17, |
| 253 | + "execution_count": 7, |
261 | 254 | "metadata": {},
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262 | 255 | "outputs": [
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263 | 256 | {
|
|
308 | 301 | },
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309 | 302 | {
|
310 | 303 | "cell_type": "code",
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311 |
| - "execution_count": 18, |
| 304 | + "execution_count": 8, |
312 | 305 | "metadata": {},
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313 | 306 | "outputs": [
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314 | 307 | {
|
|
348 | 341 | },
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349 | 342 | {
|
350 | 343 | "cell_type": "code",
|
351 |
| - "execution_count": 19, |
| 344 | + "execution_count": 9, |
352 | 345 | "metadata": {},
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353 | 346 | "outputs": [
|
354 | 347 | {
|
|
376 | 369 | },
|
377 | 370 | {
|
378 | 371 | "cell_type": "code",
|
379 |
| - "execution_count": 20, |
| 372 | + "execution_count": 10, |
380 | 373 | "metadata": {},
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381 | 374 | "outputs": [
|
382 | 375 | {
|
|
411 | 404 | },
|
412 | 405 | {
|
413 | 406 | "cell_type": "code",
|
414 |
| - "execution_count": 22, |
| 407 | + "execution_count": 11, |
415 | 408 | "metadata": {},
|
416 | 409 | "outputs": [
|
417 | 410 | {
|
|
439 | 432 | },
|
440 | 433 | {
|
441 | 434 | "cell_type": "code",
|
442 |
| - "execution_count": 23, |
| 435 | + "execution_count": 12, |
443 | 436 | "metadata": {},
|
444 | 437 | "outputs": [
|
445 | 438 | {
|
|
469 | 462 | },
|
470 | 463 | {
|
471 | 464 | "cell_type": "code",
|
472 |
| - "execution_count": null, |
| 465 | + "execution_count": 13, |
473 | 466 | "metadata": {},
|
474 | 467 | "outputs": [
|
475 | 468 | {
|
476 | 469 | "name": "stdout",
|
477 | 470 | "output_type": "stream",
|
478 | 471 | "text": [
|
479 |
| - "[1] \"<0x119cc0000>\"\n" |
| 472 | + "[1] \"<0x11d9e5800>\"\n" |
480 | 473 | ]
|
481 | 474 | }
|
482 | 475 | ],
|
|
488 | 481 | },
|
489 | 482 | {
|
490 | 483 | "cell_type": "code",
|
491 |
| - "execution_count": 28, |
| 484 | + "execution_count": 14, |
492 | 485 | "metadata": {},
|
493 | 486 | "outputs": [
|
494 | 487 | {
|
495 | 488 | "name": "stdout",
|
496 | 489 | "output_type": "stream",
|
497 | 490 | "text": [
|
498 |
| - "[1] \"<0x119cc0000>\"\n" |
| 491 | + "[1] \"<0x11d9e5800>\"\n" |
499 | 492 | ]
|
500 | 493 | }
|
501 | 494 | ],
|
|
507 | 500 | },
|
508 | 501 | {
|
509 | 502 | "cell_type": "code",
|
510 |
| - "execution_count": 29, |
| 503 | + "execution_count": 15, |
511 | 504 | "metadata": {},
|
512 | 505 | "outputs": [
|
513 | 506 | {
|
514 | 507 | "name": "stdout",
|
515 | 508 | "output_type": "stream",
|
516 | 509 | "text": [
|
517 |
| - "[1] \"<0x11845e698>\"\n" |
| 510 | + "[1] \"<0x11d49cd40>\"\n" |
518 | 511 | ]
|
519 | 512 | }
|
520 | 513 | ],
|
|
526 | 519 | },
|
527 | 520 | {
|
528 | 521 | "cell_type": "code",
|
529 |
| - "execution_count": 30, |
| 522 | + "execution_count": 16, |
530 | 523 | "metadata": {},
|
531 | 524 | "outputs": [
|
532 | 525 | {
|
533 | 526 | "name": "stdout",
|
534 | 527 | "output_type": "stream",
|
535 | 528 | "text": [
|
536 |
| - "tracemem[0x11845e698 -> 0x1184b9680]: initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
537 |
| - "tracemem[0x1184b9680 -> 0x1184b9300]: dplyr_new_list initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
538 |
| - "tracemem[0x1184b9300 -> 0x1184b92c8]: dplyr_new_list initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
539 |
| - "tracemem[0x11845e698 -> 0x1184e40e0]: new_data_frame vec_data as.list dplyr_col_modify.data.frame dplyr_col_modify mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
540 |
| - "tracemem[0x1184e40e0 -> 0x1184e4038]: as.list.data.frame as.list dplyr_col_modify.data.frame dplyr_col_modify mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
541 |
| - "[1] \"<0x1186c3e48>\"\n" |
| 529 | + "tracemem[0x11d49cd40 -> 0x11d3caf38]: initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
| 530 | + "tracemem[0x11d3caf38 -> 0x11d3cb280]: dplyr_new_list initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
| 531 | + "tracemem[0x11d3cb280 -> 0x11d3cb2b8]: dplyr_new_list initialize <Anonymous> mutate_cols mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
| 532 | + "tracemem[0x11d49cd40 -> 0x11d39e090]: new_data_frame vec_data as.list dplyr_col_modify.data.frame dplyr_col_modify mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
| 533 | + "tracemem[0x11d39e090 -> 0x11d39e1a8]: as.list.data.frame as.list dplyr_col_modify.data.frame dplyr_col_modify mutate.data.frame mutate %>% <Anonymous> <Anonymous> <Anonymous> \n", |
| 534 | + "[1] \"<0x14631ea08>\"\n" |
542 | 535 | ]
|
543 | 536 | }
|
544 | 537 | ],
|
|
560 | 553 | },
|
561 | 554 | {
|
562 | 555 | "cell_type": "code",
|
563 |
| - "execution_count": 31, |
| 556 | + "execution_count": 17, |
564 | 557 | "metadata": {},
|
565 | 558 | "outputs": [
|
566 | 559 | {
|
567 | 560 | "name": "stdout",
|
568 | 561 | "output_type": "stream",
|
569 | 562 | "text": [
|
570 |
| - " x\n", |
571 |
| - " <num>\n", |
572 |
| - " 1: 0.08722859\n", |
573 |
| - " 2: 0.31678578\n", |
574 |
| - " 3: 0.71779344\n", |
575 |
| - " 4: -0.79386835\n", |
576 |
| - " 5: 1.30777816\n", |
577 |
| - " --- \n", |
578 |
| - "196: -0.20652236\n", |
579 |
| - "197: -0.14925841\n", |
580 |
| - "198: -0.31833419\n", |
581 |
| - "199: -0.12908298\n", |
582 |
| - "200: -1.27507388\n" |
| 563 | + " x\n", |
| 564 | + " <num>\n", |
| 565 | + " 1: 0.6642543\n", |
| 566 | + " 2: 0.2826647\n", |
| 567 | + " 3: -0.8785894\n", |
| 568 | + " 4: -0.5096216\n", |
| 569 | + " 5: 0.1665126\n", |
| 570 | + " --- \n", |
| 571 | + "196: -1.9311627\n", |
| 572 | + "197: 1.2559794\n", |
| 573 | + "198: -0.3076927\n", |
| 574 | + "199: 0.2261218\n", |
| 575 | + "200: 0.5263950\n" |
583 | 576 | ]
|
584 | 577 | }
|
585 | 578 | ],
|
|
602 | 595 | },
|
603 | 596 | {
|
604 | 597 | "cell_type": "code",
|
605 |
| - "execution_count": 32, |
| 598 | + "execution_count": 18, |
606 | 599 | "metadata": {},
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607 | 600 | "outputs": [
|
608 | 601 | {
|
|
638 | 631 | },
|
639 | 632 | {
|
640 | 633 | "cell_type": "code",
|
641 |
| - "execution_count": 33, |
| 634 | + "execution_count": 19, |
642 | 635 | "metadata": {},
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643 | 636 | "outputs": [
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644 | 637 | {
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|
676 | 669 | },
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677 | 670 | {
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678 | 671 | "cell_type": "code",
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679 |
| - "execution_count": 34, |
| 672 | + "execution_count": 20, |
680 | 673 | "metadata": {},
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681 | 674 | "outputs": [
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682 | 675 | {
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|
719 | 712 | },
|
720 | 713 | {
|
721 | 714 | "cell_type": "code",
|
722 |
| - "execution_count": 37, |
| 715 | + "execution_count": 21, |
723 | 716 | "metadata": {},
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724 | 717 | "outputs": [
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725 | 718 | {
|
|
758 | 751 | },
|
759 | 752 | {
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760 | 753 | "cell_type": "code",
|
761 |
| - "execution_count": 38, |
| 754 | + "execution_count": 22, |
762 | 755 | "metadata": {},
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763 | 756 | "outputs": [
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764 | 757 | {
|
|
784 | 777 | ],
|
785 | 778 | "metadata": {
|
786 | 779 | "kernelspec": {
|
787 |
| - "display_name": "Python 3 (ipykernel)", |
| 780 | + "display_name": "Python 3", |
788 | 781 | "language": "python",
|
789 | 782 | "name": "python3"
|
790 | 783 | },
|
|
798 | 791 | "name": "python",
|
799 | 792 | "nbconvert_exporter": "python",
|
800 | 793 | "pygments_lexer": "ipython3",
|
801 |
| - "version": "3.9.19" |
| 794 | + "version": "3.9.6" |
802 | 795 | }
|
803 | 796 | },
|
804 | 797 | "nbformat": 4,
|
|
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