my_vector <- c(1, 2, 3, 4, 5)
mean_value <- mean(my_vector)
print(mean_value)[1] 3Assignment 1
Let me cook now
1)
Python and R has some differences you know.
R has a unique syntax with a focus on data manipulation and analysis. It uses a vectors for operations on data frames and matrices.
Python has a more general-purpose syntax with a clear, easy-to-read structure. It relies on libraries like NumPy and Pandas for data manipulation.
import numpy as np
my_list = [1, 2, 3, 4, 5]
mean_value = np.mean(my_list)
print(mean_value)3.0R offers unique data structures like data frames, which are well-suited for statistical analysis. It also uses factors for categorical data.
data_frame <- data.frame(
Name = c("Alice", "Bob", "Charlie"),
Age = c(25, 30, 22)
)Python relies on a more extensive set of built-in data structures like lists, dictionaries, and tuples. Libraries like Pandas provide data frames.
import pandas as pd
data_frame = pd.DataFrame({
'Name': ["Alice", "Bob", "Charlie"],
'Age': [25, 30, 22]
})In R, list comprehensions are not a built-in feature of the language. Instead, R typically uses lapply() or sapply() functions to perform operations on lists.
numbers <- c(1, 2, 3, 4, 5)
squared_values <- lapply(numbers, function(x) x^2)
print(squared_values)[[1]]
[1] 1
[[2]]
[1] 4
[[3]]
[1] 9
[[4]]
[1] 16
[[5]]
[1] 25Python supports list comprehensions, which allow you to create lists using a concise and expressive syntax.
numbers = [1, 2, 3, 4, 5]
squared_values = [x**2 for x in numbers]
print(squared_values)[1, 4, 9, 16, 25]2)
I will make all the NAs disappear now. Watch closely.
library(dslabs)
data("na_example")
cat("Original Dataset (na_example) as a Data Frame:\n")Original Dataset (na_example) as a Data Frame:print(as.data.frame(na_example)) na_example
1 2
2 1
3 3
4 2
5 1
6 3
7 1
8 4
9 3
10 2
11 2
12 NA
13 2
14 2
15 1
16 4
17 NA
18 1
19 1
20 2
21 1
22 2
23 2
24 1
25 2
26 5
27 NA
28 2
29 2
30 3
31 1
32 2
33 4
34 1
35 1
36 1
37 4
38 5
39 2
40 3
41 4
42 1
43 2
44 4
45 1
46 1
47 2
48 1
49 5
50 NA
51 NA
52 NA
53 1
54 1
55 5
56 1
57 3
58 1
59 NA
60 4
61 4
62 7
63 3
64 2
65 NA
66 NA
67 1
68 NA
69 4
70 1
71 2
72 2
73 3
74 2
75 1
76 2
77 2
78 4
79 3
80 4
81 2
82 3
83 1
84 3
85 2
86 1
87 1
88 1
89 3
90 1
91 NA
92 3
93 1
94 2
95 2
96 1
97 2
98 2
99 1
100 1
101 4
102 1
103 1
104 2
105 3
106 3
107 2
108 2
109 3
110 3
111 3
112 4
113 1
114 1
115 1
116 2
117 NA
118 4
119 3
120 4
121 3
122 1
123 2
124 1
125 NA
126 NA
127 NA
128 NA
129 1
130 5
131 1
132 2
133 1
134 3
135 5
136 3
137 2
138 2
139 NA
140 NA
141 NA
142 NA
143 3
144 5
145 3
146 1
147 1
148 4
149 2
150 4
151 3
152 3
153 NA
154 2
155 3
156 2
157 6
158 NA
159 1
160 1
161 2
162 2
163 1
164 3
165 1
166 1
167 5
168 NA
169 NA
170 2
171 4
172 NA
173 2
174 5
175 1
176 4
177 3
178 3
179 NA
180 4
181 3
182 1
183 4
184 1
185 1
186 3
187 1
188 1
189 NA
190 NA
191 3
192 5
193 2
194 2
195 2
196 3
197 1
198 2
199 2
200 3
201 2
202 1
203 NA
204 2
205 NA
206 1
207 NA
208 NA
209 2
210 1
211 1
212 NA
213 3
214 NA
215 1
216 2
217 2
218 1
219 3
220 2
221 2
222 1
223 1
224 2
225 3
226 1
227 1
228 1
229 4
230 3
231 4
232 2
233 2
234 1
235 4
236 1
237 NA
238 5
239 1
240 4
241 NA
242 3
243 NA
244 NA
245 1
246 1
247 5
248 2
249 3
250 3
251 2
252 4
253 NA
254 3
255 2
256 5
257 NA
258 2
259 3
260 4
261 6
262 2
263 2
264 2
265 NA
266 2
267 NA
268 2
269 NA
270 3
271 3
272 2
273 2
274 4
275 3
276 1
277 4
278 2
279 NA
280 2
281 4
282 NA
283 6
284 2
285 3
286 1
287 NA
288 2
289 2
290 NA
291 1
292 1
293 3
294 2
295 3
296 3
297 1
298 NA
299 1
300 4
301 2
302 1
303 1
304 3
305 2
306 1
307 2
308 3
309 1
310 NA
311 2
312 3
313 3
314 2
315 1
316 2
317 3
318 5
319 5
320 1
321 2
322 3
323 3
324 1
325 NA
326 NA
327 1
328 2
329 4
330 NA
331 2
332 1
333 1
334 1
335 3
336 2
337 1
338 1
339 3
340 4
341 NA
342 1
343 2
344 1
345 1
346 3
347 3
348 NA
349 1
350 1
351 3
352 5
353 3
354 2
355 3
356 4
357 1
358 4
359 3
360 1
361 NA
362 2
363 1
364 2
365 2
366 1
367 2
368 2
369 6
370 1
371 2
372 4
373 5
374 NA
375 3
376 4
377 2
378 1
379 1
380 4
381 2
382 1
383 1
384 1
385 1
386 2
387 1
388 4
389 4
390 1
391 3
392 NA
393 3
394 3
395 NA
396 2
397 NA
398 1
399 2
400 1
401 1
402 4
403 2
404 1
405 4
406 4
407 NA
408 1
409 2
410 NA
411 3
412 2
413 2
414 2
415 1
416 4
417 3
418 6
419 1
420 2
421 3
422 1
423 3
424 2
425 2
426 2
427 1
428 1
429 3
430 2
431 1
432 1
433 1
434 3
435 2
436 2
437 NA
438 4
439 4
440 4
441 1
442 1
443 NA
444 4
445 3
446 NA
447 1
448 3
449 1
450 3
451 2
452 4
453 2
454 2
455 2
456 3
457 2
458 1
459 4
460 3
461 NA
462 1
463 4
464 3
465 1
466 3
467 2
468 NA
469 3
470 NA
471 1
472 3
473 1
474 4
475 1
476 1
477 1
478 2
479 4
480 3
481 1
482 2
483 2
484 2
485 3
486 2
487 3
488 1
489 1
490 NA
491 3
492 2
493 1
494 1
495 2
496 NA
497 2
498 2
499 2
500 3
501 3
502 1
503 1
504 2
505 NA
506 1
507 2
508 1
509 1
510 3
511 3
512 1
513 3
514 1
515 1
516 1
517 1
518 1
519 2
520 5
521 1
522 1
523 2
524 2
525 1
526 1
527 NA
528 1
529 4
530 1
531 2
532 4
533 1
534 3
535 2
536 NA
537 1
538 1
539 NA
540 2
541 1
542 1
543 4
544 2
545 3
546 3
547 1
548 5
549 3
550 1
551 1
552 2
553 NA
554 1
555 1
556 3
557 1
558 3
559 2
560 4
561 NA
562 2
563 3
564 2
565 1
566 2
567 1
568 1
569 1
570 2
571 2
572 3
573 1
574 5
575 2
576 NA
577 2
578 NA
579 3
580 2
581 2
582 2
583 1
584 5
585 3
586 2
587 3
588 1
589 NA
590 3
591 1
592 2
593 2
594 2
595 1
596 2
597 2
598 4
599 NA
600 6
601 1
602 2
603 NA
604 1
605 1
606 2
607 2
608 3
609 NA
610 3
611 2
612 3
613 3
614 4
615 2
616 NA
617 2
618 NA
619 4
620 NA
621 1
622 1
623 2
624 2
625 3
626 1
627 1
628 1
629 3
630 NA
631 2
632 5
633 NA
634 7
635 1
636 NA
637 4
638 3
639 3
640 1
641 NA
642 1
643 1
644 1
645 1
646 3
647 2
648 4
649 2
650 2
651 3
652 NA
653 NA
654 1
655 4
656 3
657 2
658 2
659 2
660 3
661 2
662 4
663 2
664 2
665 4
666 NA
667 NA
668 NA
669 6
670 3
671 3
672 1
673 4
674 4
675 2
676 1
677 NA
678 1
679 6
680 NA
681 3
682 3
683 2
684 1
685 1
686 6
687 NA
688 1
689 5
690 1
691 NA
692 2
693 6
694 2
695 NA
696 4
697 1
698 3
699 1
700 2
701 NA
702 1
703 1
704 3
705 1
706 2
707 4
708 2
709 1
710 3
711 2
712 4
713 3
714 2
715 2
716 1
717 1
718 5
719 6
720 4
721 2
722 2
723 2
724 2
725 4
726 NA
727 1
728 2
729 2
730 2
731 2
732 4
733 5
734 NA
735 NA
736 NA
737 4
738 3
739 3
740 3
741 2
742 4
743 2
744 4
745 NA
746 NA
747 NA
748 NA
749 2
750 1
751 NA
752 2
753 4
754 3
755 2
756 NA
757 2
758 3
759 1
760 3
761 4
762 NA
763 1
764 2
765 1
766 2
767 NA
768 3
769 1
770 2
771 1
772 2
773 1
774 2
775 1
776 2
777 2
778 2
779 2
780 1
781 1
782 3
783 3
784 1
785 3
786 4
787 3
788 NA
789 NA
790 4
791 2
792 3
793 2
794 1
795 3
796 2
797 4
798 2
799 2
800 3
801 1
802 2
803 4
804 3
805 3
806 4
807 NA
808 1
809 4
810 2
811 1
812 1
813 1
814 3
815 1
816 5
817 2
818 2
819 4
820 2
821 NA
822 1
823 3
824 1
825 2
826 NA
827 1
828 2
829 1
830 2
831 1
832 NA
833 1
834 3
835 2
836 3
837 2
838 NA
839 2
840 1
841 4
842 2
843 NA
844 NA
845 NA
846 2
847 4
848 2
849 NA
850 NA
851 3
852 1
853 NA
854 5
855 5
856 2
857 2
858 2
859 NA
860 2
861 1
862 3
863 1
864 3
865 2
866 4
867 2
868 4
869 NA
870 4
871 1
872 2
873 3
874 2
875 3
876 3
877 2
878 3
879 2
880 2
881 2
882 1
883 3
884 2
885 4
886 2
887 NA
888 3
889 3
890 2
891 2
892 NA
893 NA
894 3
895 2
896 1
897 2
898 4
899 1
900 1
901 1
902 1
903 4
904 3
905 2
906 NA
907 3
908 2
909 NA
910 1
911 NA
912 3
913 2
914 1
915 1
916 1
917 2
918 NA
919 2
920 2
921 3
922 3
923 2
924 NA
925 NA
926 4
927 5
928 2
929 2
930 2
931 1
932 2
933 3
934 1
935 3
936 3
937 4
938 3
939 NA
940 1
941 1
942 1
943 NA
944 4
945 3
946 5
947 1
948 1
949 2
950 NA
951 2
952 2
953 2
954 2
955 5
956 2
957 2
958 3
959 1
960 2
961 3
962 NA
963 1
964 2
965 NA
966 NA
967 2
968 NA
969 3
970 1
971 1
972 2
973 5
974 3
975 5
976 1
977 1
978 4
979 NA
980 2
981 1
982 3
983 1
984 1
985 2
986 4
987 3
988 3
989 3
990 NA
991 1
992 1
993 2
994 2
995 1
996 1
997 2
998 2
999 NA
1000 2na_example_no_na <- na_example
na_example_no_na[is.na(na_example_no_na)] <- 0
cat("\nUpdated Dataset (na_example_no_na, NAs replaced with 0) as a Data Frame:\n")
Updated Dataset (na_example_no_na, NAs replaced with 0) as a Data Frame:print(as.data.frame(na_example_no_na)) na_example_no_na
1 2
2 1
3 3
4 2
5 1
6 3
7 1
8 4
9 3
10 2
11 2
12 0
13 2
14 2
15 1
16 4
17 0
18 1
19 1
20 2
21 1
22 2
23 2
24 1
25 2
26 5
27 0
28 2
29 2
30 3
31 1
32 2
33 4
34 1
35 1
36 1
37 4
38 5
39 2
40 3
41 4
42 1
43 2
44 4
45 1
46 1
47 2
48 1
49 5
50 0
51 0
52 0
53 1
54 1
55 5
56 1
57 3
58 1
59 0
60 4
61 4
62 7
63 3
64 2
65 0
66 0
67 1
68 0
69 4
70 1
71 2
72 2
73 3
74 2
75 1
76 2
77 2
78 4
79 3
80 4
81 2
82 3
83 1
84 3
85 2
86 1
87 1
88 1
89 3
90 1
91 0
92 3
93 1
94 2
95 2
96 1
97 2
98 2
99 1
100 1
101 4
102 1
103 1
104 2
105 3
106 3
107 2
108 2
109 3
110 3
111 3
112 4
113 1
114 1
115 1
116 2
117 0
118 4
119 3
120 4
121 3
122 1
123 2
124 1
125 0
126 0
127 0
128 0
129 1
130 5
131 1
132 2
133 1
134 3
135 5
136 3
137 2
138 2
139 0
140 0
141 0
142 0
143 3
144 5
145 3
146 1
147 1
148 4
149 2
150 4
151 3
152 3
153 0
154 2
155 3
156 2
157 6
158 0
159 1
160 1
161 2
162 2
163 1
164 3
165 1
166 1
167 5
168 0
169 0
170 2
171 4
172 0
173 2
174 5
175 1
176 4
177 3
178 3
179 0
180 4
181 3
182 1
183 4
184 1
185 1
186 3
187 1
188 1
189 0
190 0
191 3
192 5
193 2
194 2
195 2
196 3
197 1
198 2
199 2
200 3
201 2
202 1
203 0
204 2
205 0
206 1
207 0
208 0
209 2
210 1
211 1
212 0
213 3
214 0
215 1
216 2
217 2
218 1
219 3
220 2
221 2
222 1
223 1
224 2
225 3
226 1
227 1
228 1
229 4
230 3
231 4
232 2
233 2
234 1
235 4
236 1
237 0
238 5
239 1
240 4
241 0
242 3
243 0
244 0
245 1
246 1
247 5
248 2
249 3
250 3
251 2
252 4
253 0
254 3
255 2
256 5
257 0
258 2
259 3
260 4
261 6
262 2
263 2
264 2
265 0
266 2
267 0
268 2
269 0
270 3
271 3
272 2
273 2
274 4
275 3
276 1
277 4
278 2
279 0
280 2
281 4
282 0
283 6
284 2
285 3
286 1
287 0
288 2
289 2
290 0
291 1
292 1
293 3
294 2
295 3
296 3
297 1
298 0
299 1
300 4
301 2
302 1
303 1
304 3
305 2
306 1
307 2
308 3
309 1
310 0
311 2
312 3
313 3
314 2
315 1
316 2
317 3
318 5
319 5
320 1
321 2
322 3
323 3
324 1
325 0
326 0
327 1
328 2
329 4
330 0
331 2
332 1
333 1
334 1
335 3
336 2
337 1
338 1
339 3
340 4
341 0
342 1
343 2
344 1
345 1
346 3
347 3
348 0
349 1
350 1
351 3
352 5
353 3
354 2
355 3
356 4
357 1
358 4
359 3
360 1
361 0
362 2
363 1
364 2
365 2
366 1
367 2
368 2
369 6
370 1
371 2
372 4
373 5
374 0
375 3
376 4
377 2
378 1
379 1
380 4
381 2
382 1
383 1
384 1
385 1
386 2
387 1
388 4
389 4
390 1
391 3
392 0
393 3
394 3
395 0
396 2
397 0
398 1
399 2
400 1
401 1
402 4
403 2
404 1
405 4
406 4
407 0
408 1
409 2
410 0
411 3
412 2
413 2
414 2
415 1
416 4
417 3
418 6
419 1
420 2
421 3
422 1
423 3
424 2
425 2
426 2
427 1
428 1
429 3
430 2
431 1
432 1
433 1
434 3
435 2
436 2
437 0
438 4
439 4
440 4
441 1
442 1
443 0
444 4
445 3
446 0
447 1
448 3
449 1
450 3
451 2
452 4
453 2
454 2
455 2
456 3
457 2
458 1
459 4
460 3
461 0
462 1
463 4
464 3
465 1
466 3
467 2
468 0
469 3
470 0
471 1
472 3
473 1
474 4
475 1
476 1
477 1
478 2
479 4
480 3
481 1
482 2
483 2
484 2
485 3
486 2
487 3
488 1
489 1
490 0
491 3
492 2
493 1
494 1
495 2
496 0
497 2
498 2
499 2
500 3
501 3
502 1
503 1
504 2
505 0
506 1
507 2
508 1
509 1
510 3
511 3
512 1
513 3
514 1
515 1
516 1
517 1
518 1
519 2
520 5
521 1
522 1
523 2
524 2
525 1
526 1
527 0
528 1
529 4
530 1
531 2
532 4
533 1
534 3
535 2
536 0
537 1
538 1
539 0
540 2
541 1
542 1
543 4
544 2
545 3
546 3
547 1
548 5
549 3
550 1
551 1
552 2
553 0
554 1
555 1
556 3
557 1
558 3
559 2
560 4
561 0
562 2
563 3
564 2
565 1
566 2
567 1
568 1
569 1
570 2
571 2
572 3
573 1
574 5
575 2
576 0
577 2
578 0
579 3
580 2
581 2
582 2
583 1
584 5
585 3
586 2
587 3
588 1
589 0
590 3
591 1
592 2
593 2
594 2
595 1
596 2
597 2
598 4
599 0
600 6
601 1
602 2
603 0
604 1
605 1
606 2
607 2
608 3
609 0
610 3
611 2
612 3
613 3
614 4
615 2
616 0
617 2
618 0
619 4
620 0
621 1
622 1
623 2
624 2
625 3
626 1
627 1
628 1
629 3
630 0
631 2
632 5
633 0
634 7
635 1
636 0
637 4
638 3
639 3
640 1
641 0
642 1
643 1
644 1
645 1
646 3
647 2
648 4
649 2
650 2
651 3
652 0
653 0
654 1
655 4
656 3
657 2
658 2
659 2
660 3
661 2
662 4
663 2
664 2
665 4
666 0
667 0
668 0
669 6
670 3
671 3
672 1
673 4
674 4
675 2
676 1
677 0
678 1
679 6
680 0
681 3
682 3
683 2
684 1
685 1
686 6
687 0
688 1
689 5
690 1
691 0
692 2
693 6
694 2
695 0
696 4
697 1
698 3
699 1
700 2
701 0
702 1
703 1
704 3
705 1
706 2
707 4
708 2
709 1
710 3
711 2
712 4
713 3
714 2
715 2
716 1
717 1
718 5
719 6
720 4
721 2
722 2
723 2
724 2
725 4
726 0
727 1
728 2
729 2
730 2
731 2
732 4
733 5
734 0
735 0
736 0
737 4
738 3
739 3
740 3
741 2
742 4
743 2
744 4
745 0
746 0
747 0
748 0
749 2
750 1
751 0
752 2
753 4
754 3
755 2
756 0
757 2
758 3
759 1
760 3
761 4
762 0
763 1
764 2
765 1
766 2
767 0
768 3
769 1
770 2
771 1
772 2
773 1
774 2
775 1
776 2
777 2
778 2
779 2
780 1
781 1
782 3
783 3
784 1
785 3
786 4
787 3
788 0
789 0
790 4
791 2
792 3
793 2
794 1
795 3
796 2
797 4
798 2
799 2
800 3
801 1
802 2
803 4
804 3
805 3
806 4
807 0
808 1
809 4
810 2
811 1
812 1
813 1
814 3
815 1
816 5
817 2
818 2
819 4
820 2
821 0
822 1
823 3
824 1
825 2
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1000 23)
Creating basic text-based games in R is a fun way to learn the basics of game development. Here’s a summary of how to make a very simple text-based game in R:
Define the Game Concept: Start by defining the concept of your text-based game. For a basic game, you might create a simple “Guess the Number” game where the player has to guess a random number.
Generate a Random Number: Use R’s sample() function to generate a random number. This number will be the one that the player needs to guess.
Implement Game Logic: Write code that handles the game’s logic. Create a loop that allows the player to enter guesses, compare their guesses to the random number, and provide feedback (e.g., “Too high” or “Too low”). Continue the loop until the player guesses the correct number.
User Input and Output: Use R’s readline() function to get input from the player, and print() or cat() to display messages and feedback. You can also create a simple text-based interface to make the game more interactive.
Win/Lose Conditions: Define win and lose conditions. In the “Guess the Number” game, the player wins if they guess the correct number and loses after a certain number of attempts.