└── Decision Tree classfication-Copy1.ipynb
/Decision Tree classfication-Copy1.ipynb:
--------------------------------------------------------------------------------
1 | {
2 | "cells": [
3 | {
4 | "cell_type": "code",
5 | "execution_count": 2,
6 | "id": "ea84c493",
7 | "metadata": {},
8 | "outputs": [
9 | {
10 | "name": "stdout",
11 | "output_type": "stream",
12 | "text": [
13 | "Requirement already satisfied: pandas in c:\\users\\lenovo\\anaconda3\\lib\\site-packages (1.4.2)\n",
14 | "Requirement already satisfied: pytz>=2020.1 in c:\\users\\lenovo\\anaconda3\\lib\\site-packages (from pandas) (2021.3)\n",
15 | "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\lenovo\\anaconda3\\lib\\site-packages (from pandas) (2.8.2)\n",
16 | "Requirement already satisfied: numpy>=1.18.5 in c:\\users\\lenovo\\anaconda3\\lib\\site-packages (from pandas) (1.21.5)\n",
17 | "Requirement already satisfied: six>=1.5 in c:\\users\\lenovo\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n",
18 | "Note: you may need to restart the kernel to use updated packages.\n"
19 | ]
20 | }
21 | ],
22 | "source": [
23 | "pip install pandas"
24 | ]
25 | },
26 | {
27 | "cell_type": "code",
28 | "execution_count": 20,
29 | "id": "71eb3fc0",
30 | "metadata": {},
31 | "outputs": [],
32 | "source": [
33 | "import pandas as u"
34 | ]
35 | },
36 | {
37 | "cell_type": "code",
38 | "execution_count": 21,
39 | "id": "ff3d30e4",
40 | "metadata": {},
41 | "outputs": [],
42 | "source": [
43 | "import numpy as np"
44 | ]
45 | },
46 | {
47 | "cell_type": "code",
48 | "execution_count": 22,
49 | "id": "128f6994",
50 | "metadata": {},
51 | "outputs": [
52 | {
53 | "data": {
54 | "text/html": [
55 | "
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56 | "\n",
69 | "
\n",
70 | " \n",
71 | " \n",
72 | " | \n",
73 | " rank | \n",
74 | " title | \n",
75 | " total ratings | \n",
76 | " installs | \n",
77 | " average rating | \n",
78 | " growth (30 days) | \n",
79 | " growth (60 days) | \n",
80 | " price | \n",
81 | " category | \n",
82 | " 5 star ratings | \n",
83 | " 4 star ratings | \n",
84 | " 3 star ratings | \n",
85 | " 2 star ratings | \n",
86 | " 1 star ratings | \n",
87 | " paid | \n",
88 | "
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89 | " \n",
90 | " \n",
91 | " \n",
92 | " 0 | \n",
93 | " 1 | \n",
94 | " Garena Free Fire- World Series | \n",
95 | " 86273129 | \n",
96 | " 500.0 M | \n",
97 | " 4 | \n",
98 | " 2.1 | \n",
99 | " 6.9 | \n",
100 | " 0 | \n",
101 | " GAME ACTION | \n",
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103 | " 4949507 | \n",
104 | " 3158756 | \n",
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106 | " 12495915 | \n",
107 | " False | \n",
108 | "
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109 | " \n",
110 | " 1 | \n",
111 | " 2 | \n",
112 | " PUBG MOBILE - Traverse | \n",
113 | " 37276732 | \n",
114 | " 500.0 M | \n",
115 | " 4 | \n",
116 | " 1.8 | \n",
117 | " 3.6 | \n",
118 | " 0 | \n",
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124 | " 4709492 | \n",
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127 | " \n",
128 | " 2 | \n",
129 | " 3 | \n",
130 | " Mobile Legends: Bang Bang | \n",
131 | " 26663595 | \n",
132 | " 100.0 M | \n",
133 | " 4 | \n",
134 | " 1.5 | \n",
135 | " 3.2 | \n",
136 | " 0 | \n",
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139 | " 1812094 | \n",
140 | " 1050600 | \n",
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142 | " 4308998 | \n",
143 | " False | \n",
144 | "
\n",
145 | " \n",
146 | " 3 | \n",
147 | " 4 | \n",
148 | " Brawl Stars | \n",
149 | " 17971552 | \n",
150 | " 100.0 M | \n",
151 | " 4 | \n",
152 | " 1.4 | \n",
153 | " 4.4 | \n",
154 | " 0 | \n",
155 | " GAME ACTION | \n",
156 | " 13018610 | \n",
157 | " 1552950 | \n",
158 | " 774012 | \n",
159 | " 406184 | \n",
160 | " 2219794 | \n",
161 | " False | \n",
162 | "
\n",
163 | " \n",
164 | " 4 | \n",
165 | " 5 | \n",
166 | " Sniper 3D: Fun Free Online FPS Shooting Game | \n",
167 | " 14464235 | \n",
168 | " 500.0 M | \n",
169 | " 4 | \n",
170 | " 0.8 | \n",
171 | " 1.5 | \n",
172 | " 0 | \n",
173 | " GAME ACTION | \n",
174 | " 9827328 | \n",
175 | " 2124154 | \n",
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177 | " 380670 | \n",
178 | " 1084340 | \n",
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184 | " ... | \n",
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186 | " ... | \n",
187 | " ... | \n",
188 | " ... | \n",
189 | " ... | \n",
190 | " ... | \n",
191 | " ... | \n",
192 | " ... | \n",
193 | " ... | \n",
194 | " ... | \n",
195 | " ... | \n",
196 | " ... | \n",
197 | " ... | \n",
198 | "
\n",
199 | " \n",
200 | " 95 | \n",
201 | " 96 | \n",
202 | " Bullet Force | \n",
203 | " 756002 | \n",
204 | " 10.0 M | \n",
205 | " 3 | \n",
206 | " 0.1 | \n",
207 | " 0.1 | \n",
208 | " 0 | \n",
209 | " GAME ACTION | \n",
210 | " 434187 | \n",
211 | " 90078 | \n",
212 | " 58506 | \n",
213 | " 35311 | \n",
214 | " 137917 | \n",
215 | " False | \n",
216 | "
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217 | " \n",
218 | " 96 | \n",
219 | " 97 | \n",
220 | " SHADOWGUN: DEADZONE | \n",
221 | " 748945 | \n",
222 | " 10.0 M | \n",
223 | " 4 | \n",
224 | " 0.1 | \n",
225 | " 0.3 | \n",
226 | " 0 | \n",
227 | " GAME ACTION | \n",
228 | " 554163 | \n",
229 | " 80239 | \n",
230 | " 38183 | \n",
231 | " 14231 | \n",
232 | " 62125 | \n",
233 | " False | \n",
234 | "
\n",
235 | " \n",
236 | " 97 | \n",
237 | " 98 | \n",
238 | " Royal Revolt 2: Tower Defense RTS & Castle Bui... | \n",
239 | " 727627 | \n",
240 | " 10.0 M | \n",
241 | " 4 | \n",
242 | " 0.1 | \n",
243 | " 0.1 | \n",
244 | " 0 | \n",
245 | " GAME ACTION | \n",
246 | " 541833 | \n",
247 | " 91851 | \n",
248 | " 33669 | \n",
249 | " 12216 | \n",
250 | " 48055 | \n",
251 | " False | \n",
252 | "
\n",
253 | " \n",
254 | " 98 | \n",
255 | " 99 | \n",
256 | " Lara Croft: Relic Run | \n",
257 | " 718905 | \n",
258 | " 10.0 M | \n",
259 | " 4 | \n",
260 | " 0.2 | \n",
261 | " 0.5 | \n",
262 | " 0 | \n",
263 | " GAME ACTION | \n",
264 | " 445276 | \n",
265 | " 83143 | \n",
266 | " 55372 | \n",
267 | " 35836 | \n",
268 | " 99275 | \n",
269 | " False | \n",
270 | "
\n",
271 | " \n",
272 | " 99 | \n",
273 | " 100 | \n",
274 | " WWE Mayhem | \n",
275 | " 703514 | \n",
276 | " 10.0 M | \n",
277 | " 4 | \n",
278 | " 0.6 | \n",
279 | " 1.3 | \n",
280 | " 0 | \n",
281 | " GAME ACTION | \n",
282 | " 519090 | \n",
283 | " 68518 | \n",
284 | " 34658 | \n",
285 | " 17634 | \n",
286 | " 63612 | \n",
287 | " False | \n",
288 | "
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289 | " \n",
290 | "
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291 | "
100 rows × 15 columns
\n",
292 | "
"
293 | ],
294 | "text/plain": [
295 | " rank title total ratings \\\n",
296 | "0 1 Garena Free Fire- World Series 86273129 \n",
297 | "1 2 PUBG MOBILE - Traverse 37276732 \n",
298 | "2 3 Mobile Legends: Bang Bang 26663595 \n",
299 | "3 4 Brawl Stars 17971552 \n",
300 | "4 5 Sniper 3D: Fun Free Online FPS Shooting Game 14464235 \n",
301 | ".. ... ... ... \n",
302 | "95 96 Bullet Force 756002 \n",
303 | "96 97 SHADOWGUN: DEADZONE 748945 \n",
304 | "97 98 Royal Revolt 2: Tower Defense RTS & Castle Bui... 727627 \n",
305 | "98 99 Lara Croft: Relic Run 718905 \n",
306 | "99 100 WWE Mayhem 703514 \n",
307 | "\n",
308 | " installs average rating growth (30 days) growth (60 days) price \\\n",
309 | "0 500.0 M 4 2.1 6.9 0 \n",
310 | "1 500.0 M 4 1.8 3.6 0 \n",
311 | "2 100.0 M 4 1.5 3.2 0 \n",
312 | "3 100.0 M 4 1.4 4.4 0 \n",
313 | "4 500.0 M 4 0.8 1.5 0 \n",
314 | ".. ... ... ... ... ... \n",
315 | "95 10.0 M 3 0.1 0.1 0 \n",
316 | "96 10.0 M 4 0.1 0.3 0 \n",
317 | "97 10.0 M 4 0.1 0.1 0 \n",
318 | "98 10.0 M 4 0.2 0.5 0 \n",
319 | "99 10.0 M 4 0.6 1.3 0 \n",
320 | "\n",
321 | " category 5 star ratings 4 star ratings 3 star ratings \\\n",
322 | "0 GAME ACTION 63546766 4949507 3158756 \n",
323 | "1 GAME ACTION 28339753 2164478 1253185 \n",
324 | "2 GAME ACTION 18777988 1812094 1050600 \n",
325 | "3 GAME ACTION 13018610 1552950 774012 \n",
326 | "4 GAME ACTION 9827328 2124154 1047741 \n",
327 | ".. ... ... ... ... \n",
328 | "95 GAME ACTION 434187 90078 58506 \n",
329 | "96 GAME ACTION 554163 80239 38183 \n",
330 | "97 GAME ACTION 541833 91851 33669 \n",
331 | "98 GAME ACTION 445276 83143 55372 \n",
332 | "99 GAME ACTION 519090 68518 34658 \n",
333 | "\n",
334 | " 2 star ratings 1 star ratings paid \n",
335 | "0 2122183 12495915 False \n",
336 | "1 809821 4709492 False \n",
337 | "2 713912 4308998 False \n",
338 | "3 406184 2219794 False \n",
339 | "4 380670 1084340 False \n",
340 | ".. ... ... ... \n",
341 | "95 35311 137917 False \n",
342 | "96 14231 62125 False \n",
343 | "97 12216 48055 False \n",
344 | "98 35836 99275 False \n",
345 | "99 17634 63612 False \n",
346 | "\n",
347 | "[100 rows x 15 columns]"
348 | ]
349 | },
350 | "execution_count": 22,
351 | "metadata": {},
352 | "output_type": "execute_result"
353 | }
354 | ],
355 | "source": [
356 | "data =u.read_csv(\"C:\\\\Users\\\\Lenovo\\\\Downloads\\\\android-games.csv\")\n",
357 | "data"
358 | ]
359 | },
360 | {
361 | "cell_type": "code",
362 | "execution_count": 23,
363 | "id": "754834d4",
364 | "metadata": {},
365 | "outputs": [],
366 | "source": [
367 | "X = data.drop('total ratings', axis=1)\n",
368 | "X"
369 | ]
370 | },
371 | {
372 | "cell_type": "code",
373 | "execution_count": 24,
374 | "id": "67916bc3",
375 | "metadata": {},
376 | "outputs": [
377 | {
378 | "data": {
379 | "text/html": [
380 | "\n",
381 | "\n",
394 | "
\n",
395 | " \n",
396 | " \n",
397 | " | \n",
398 | " rank | \n",
399 | " title | \n",
400 | " installs | \n",
401 | " average rating | \n",
402 | " growth (30 days) | \n",
403 | " growth (60 days) | \n",
404 | " price | \n",
405 | " category | \n",
406 | " 5 star ratings | \n",
407 | " 4 star ratings | \n",
408 | " 3 star ratings | \n",
409 | " 2 star ratings | \n",
410 | " 1 star ratings | \n",
411 | " paid | \n",
412 | "
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413 | " \n",
414 | " \n",
415 | " \n",
416 | " 0 | \n",
417 | " 1 | \n",
418 | " Garena Free Fire- World Series | \n",
419 | " 500.0 M | \n",
420 | " 4 | \n",
421 | " 2.1 | \n",
422 | " 6.9 | \n",
423 | " 0 | \n",
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429 | " 12495915 | \n",
430 | " False | \n",
431 | "
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432 | " \n",
433 | " 1 | \n",
434 | " 2 | \n",
435 | " PUBG MOBILE - Traverse | \n",
436 | " 500.0 M | \n",
437 | " 4 | \n",
438 | " 1.8 | \n",
439 | " 3.6 | \n",
440 | " 0 | \n",
441 | " GAME ACTION | \n",
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446 | " 4709492 | \n",
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448 | "
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449 | " \n",
450 | " 2 | \n",
451 | " 3 | \n",
452 | " Mobile Legends: Bang Bang | \n",
453 | " 100.0 M | \n",
454 | " 4 | \n",
455 | " 1.5 | \n",
456 | " 3.2 | \n",
457 | " 0 | \n",
458 | " GAME ACTION | \n",
459 | " 18777988 | \n",
460 | " 1812094 | \n",
461 | " 1050600 | \n",
462 | " 713912 | \n",
463 | " 4308998 | \n",
464 | " False | \n",
465 | "
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466 | " \n",
467 | " 3 | \n",
468 | " 4 | \n",
469 | " Brawl Stars | \n",
470 | " 100.0 M | \n",
471 | " 4 | \n",
472 | " 1.4 | \n",
473 | " 4.4 | \n",
474 | " 0 | \n",
475 | " GAME ACTION | \n",
476 | " 13018610 | \n",
477 | " 1552950 | \n",
478 | " 774012 | \n",
479 | " 406184 | \n",
480 | " 2219794 | \n",
481 | " False | \n",
482 | "
\n",
483 | " \n",
484 | " 4 | \n",
485 | " 5 | \n",
486 | " Sniper 3D: Fun Free Online FPS Shooting Game | \n",
487 | " 500.0 M | \n",
488 | " 4 | \n",
489 | " 0.8 | \n",
490 | " 1.5 | \n",
491 | " 0 | \n",
492 | " GAME ACTION | \n",
493 | " 9827328 | \n",
494 | " 2124154 | \n",
495 | " 1047741 | \n",
496 | " 380670 | \n",
497 | " 1084340 | \n",
498 | " False | \n",
499 | "
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500 | " \n",
501 | " ... | \n",
502 | " ... | \n",
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505 | " ... | \n",
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507 | " ... | \n",
508 | " ... | \n",
509 | " ... | \n",
510 | " ... | \n",
511 | " ... | \n",
512 | " ... | \n",
513 | " ... | \n",
514 | " ... | \n",
515 | " ... | \n",
516 | "
\n",
517 | " \n",
518 | " 95 | \n",
519 | " 96 | \n",
520 | " Bullet Force | \n",
521 | " 10.0 M | \n",
522 | " 3 | \n",
523 | " 0.1 | \n",
524 | " 0.1 | \n",
525 | " 0 | \n",
526 | " GAME ACTION | \n",
527 | " 434187 | \n",
528 | " 90078 | \n",
529 | " 58506 | \n",
530 | " 35311 | \n",
531 | " 137917 | \n",
532 | " False | \n",
533 | "
\n",
534 | " \n",
535 | " 96 | \n",
536 | " 97 | \n",
537 | " SHADOWGUN: DEADZONE | \n",
538 | " 10.0 M | \n",
539 | " 4 | \n",
540 | " 0.1 | \n",
541 | " 0.3 | \n",
542 | " 0 | \n",
543 | " GAME ACTION | \n",
544 | " 554163 | \n",
545 | " 80239 | \n",
546 | " 38183 | \n",
547 | " 14231 | \n",
548 | " 62125 | \n",
549 | " False | \n",
550 | "
\n",
551 | " \n",
552 | " 97 | \n",
553 | " 98 | \n",
554 | " Royal Revolt 2: Tower Defense RTS & Castle Bui... | \n",
555 | " 10.0 M | \n",
556 | " 4 | \n",
557 | " 0.1 | \n",
558 | " 0.1 | \n",
559 | " 0 | \n",
560 | " GAME ACTION | \n",
561 | " 541833 | \n",
562 | " 91851 | \n",
563 | " 33669 | \n",
564 | " 12216 | \n",
565 | " 48055 | \n",
566 | " False | \n",
567 | "
\n",
568 | " \n",
569 | " 98 | \n",
570 | " 99 | \n",
571 | " Lara Croft: Relic Run | \n",
572 | " 10.0 M | \n",
573 | " 4 | \n",
574 | " 0.2 | \n",
575 | " 0.5 | \n",
576 | " 0 | \n",
577 | " GAME ACTION | \n",
578 | " 445276 | \n",
579 | " 83143 | \n",
580 | " 55372 | \n",
581 | " 35836 | \n",
582 | " 99275 | \n",
583 | " False | \n",
584 | "
\n",
585 | " \n",
586 | " 99 | \n",
587 | " 100 | \n",
588 | " WWE Mayhem | \n",
589 | " 10.0 M | \n",
590 | " 4 | \n",
591 | " 0.6 | \n",
592 | " 1.3 | \n",
593 | " 0 | \n",
594 | " GAME ACTION | \n",
595 | " 519090 | \n",
596 | " 68518 | \n",
597 | " 34658 | \n",
598 | " 17634 | \n",
599 | " 63612 | \n",
600 | " False | \n",
601 | "
\n",
602 | " \n",
603 | "
\n",
604 | "
100 rows × 14 columns
\n",
605 | "
"
606 | ],
607 | "text/plain": [
608 | " rank title installs \\\n",
609 | "0 1 Garena Free Fire- World Series 500.0 M \n",
610 | "1 2 PUBG MOBILE - Traverse 500.0 M \n",
611 | "2 3 Mobile Legends: Bang Bang 100.0 M \n",
612 | "3 4 Brawl Stars 100.0 M \n",
613 | "4 5 Sniper 3D: Fun Free Online FPS Shooting Game 500.0 M \n",
614 | ".. ... ... ... \n",
615 | "95 96 Bullet Force 10.0 M \n",
616 | "96 97 SHADOWGUN: DEADZONE 10.0 M \n",
617 | "97 98 Royal Revolt 2: Tower Defense RTS & Castle Bui... 10.0 M \n",
618 | "98 99 Lara Croft: Relic Run 10.0 M \n",
619 | "99 100 WWE Mayhem 10.0 M \n",
620 | "\n",
621 | " average rating growth (30 days) growth (60 days) price category \\\n",
622 | "0 4 2.1 6.9 0 GAME ACTION \n",
623 | "1 4 1.8 3.6 0 GAME ACTION \n",
624 | "2 4 1.5 3.2 0 GAME ACTION \n",
625 | "3 4 1.4 4.4 0 GAME ACTION \n",
626 | "4 4 0.8 1.5 0 GAME ACTION \n",
627 | ".. ... ... ... ... ... \n",
628 | "95 3 0.1 0.1 0 GAME ACTION \n",
629 | "96 4 0.1 0.3 0 GAME ACTION \n",
630 | "97 4 0.1 0.1 0 GAME ACTION \n",
631 | "98 4 0.2 0.5 0 GAME ACTION \n",
632 | "99 4 0.6 1.3 0 GAME ACTION \n",
633 | "\n",
634 | " 5 star ratings 4 star ratings 3 star ratings 2 star ratings \\\n",
635 | "0 63546766 4949507 3158756 2122183 \n",
636 | "1 28339753 2164478 1253185 809821 \n",
637 | "2 18777988 1812094 1050600 713912 \n",
638 | "3 13018610 1552950 774012 406184 \n",
639 | "4 9827328 2124154 1047741 380670 \n",
640 | ".. ... ... ... ... \n",
641 | "95 434187 90078 58506 35311 \n",
642 | "96 554163 80239 38183 14231 \n",
643 | "97 541833 91851 33669 12216 \n",
644 | "98 445276 83143 55372 35836 \n",
645 | "99 519090 68518 34658 17634 \n",
646 | "\n",
647 | " 1 star ratings paid \n",
648 | "0 12495915 False \n",
649 | "1 4709492 False \n",
650 | "2 4308998 False \n",
651 | "3 2219794 False \n",
652 | "4 1084340 False \n",
653 | ".. ... ... \n",
654 | "95 137917 False \n",
655 | "96 62125 False \n",
656 | "97 48055 False \n",
657 | "98 99275 False \n",
658 | "99 63612 False \n",
659 | "\n",
660 | "[100 rows x 14 columns]"
661 | ]
662 | },
663 | "execution_count": 24,
664 | "metadata": {},
665 | "output_type": "execute_result"
666 | }
667 | ],
668 | "source": [
669 | "X"
670 | ]
671 | },
672 | {
673 | "cell_type": "code",
674 | "execution_count": 25,
675 | "id": "ef6c9d55",
676 | "metadata": {},
677 | "outputs": [],
678 | "source": [
679 | "y = data['total ratings']\n",
680 | "y"
681 | ]
682 | },
683 | {
684 | "cell_type": "code",
685 | "execution_count": 26,
686 | "id": "5066d69f",
687 | "metadata": {},
688 | "outputs": [
689 | {
690 | "data": {
691 | "text/plain": [
692 | "0 86273129\n",
693 | "1 37276732\n",
694 | "2 26663595\n",
695 | "3 17971552\n",
696 | "4 14464235\n",
697 | " ... \n",
698 | "95 756002\n",
699 | "96 748945\n",
700 | "97 727627\n",
701 | "98 718905\n",
702 | "99 703514\n",
703 | "Name: total ratings, Length: 100, dtype: int64"
704 | ]
705 | },
706 | "execution_count": 26,
707 | "metadata": {},
708 | "output_type": "execute_result"
709 | }
710 | ],
711 | "source": [
712 | "y"
713 | ]
714 | },
715 | {
716 | "cell_type": "code",
717 | "execution_count": 27,
718 | "id": "b381de5b",
719 | "metadata": {},
720 | "outputs": [
721 | {
722 | "data": {
723 | "text/html": [
724 | "\n",
725 | "\n",
738 | "
\n",
739 | " \n",
740 | " \n",
741 | " | \n",
742 | " rank | \n",
743 | " total ratings | \n",
744 | " average rating | \n",
745 | " growth (30 days) | \n",
746 | " growth (60 days) | \n",
747 | " price | \n",
748 | " 5 star ratings | \n",
749 | " 4 star ratings | \n",
750 | " 3 star ratings | \n",
751 | " 2 star ratings | \n",
752 | " ... | \n",
753 | " title_Temple Run 2 | \n",
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755 | " title_Vector 2 | \n",
756 | " title_WWE Mayhem | \n",
757 | " title_War Machines: Tank Battle - Army & Military Games | \n",
758 | " title_War Robots. 6v6 Tactical Multiplayer Battles | \n",
759 | " title_Worms Zone .io - Voracious Snake | \n",
760 | " title_Zombie Catchers - love the hunt! | \n",
761 | " title_aquapark.io | \n",
762 | " category_GAME ACTION | \n",
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1031 | "
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1032 | "
100 rows × 113 columns
\n",
1033 | "
"
1034 | ],
1035 | "text/plain": [
1036 | " rank total ratings average rating growth (30 days) growth (60 days) \\\n",
1037 | "0 1 86273129 4 2.1 6.9 \n",
1038 | "1 2 37276732 4 1.8 3.6 \n",
1039 | "2 3 26663595 4 1.5 3.2 \n",
1040 | "3 4 17971552 4 1.4 4.4 \n",
1041 | "4 5 14464235 4 0.8 1.5 \n",
1042 | ".. ... ... ... ... ... \n",
1043 | "95 96 756002 3 0.1 0.1 \n",
1044 | "96 97 748945 4 0.1 0.3 \n",
1045 | "97 98 727627 4 0.1 0.1 \n",
1046 | "98 99 718905 4 0.2 0.5 \n",
1047 | "99 100 703514 4 0.6 1.3 \n",
1048 | "\n",
1049 | " price 5 star ratings 4 star ratings 3 star ratings 2 star ratings \\\n",
1050 | "0 0 63546766 4949507 3158756 2122183 \n",
1051 | "1 0 28339753 2164478 1253185 809821 \n",
1052 | "2 0 18777988 1812094 1050600 713912 \n",
1053 | "3 0 13018610 1552950 774012 406184 \n",
1054 | "4 0 9827328 2124154 1047741 380670 \n",
1055 | ".. ... ... ... ... ... \n",
1056 | "95 0 434187 90078 58506 35311 \n",
1057 | "96 0 554163 80239 38183 14231 \n",
1058 | "97 0 541833 91851 33669 12216 \n",
1059 | "98 0 445276 83143 55372 35836 \n",
1060 | "99 0 519090 68518 34658 17634 \n",
1061 | "\n",
1062 | " ... title_Temple Run 2 title_Tomb of the Mask title_Vector 2 \\\n",
1063 | "0 ... 0 0 0 \n",
1064 | "1 ... 0 0 0 \n",
1065 | "2 ... 0 0 0 \n",
1066 | "3 ... 0 0 0 \n",
1067 | "4 ... 0 0 0 \n",
1068 | ".. ... ... ... ... \n",
1069 | "95 ... 0 0 0 \n",
1070 | "96 ... 0 0 0 \n",
1071 | "97 ... 0 0 0 \n",
1072 | "98 ... 0 0 0 \n",
1073 | "99 ... 0 0 0 \n",
1074 | "\n",
1075 | " title_WWE Mayhem title_War Machines: Tank Battle - Army & Military Games \\\n",
1076 | "0 0 0 \n",
1077 | "1 0 0 \n",
1078 | "2 0 0 \n",
1079 | "3 0 0 \n",
1080 | "4 0 0 \n",
1081 | ".. ... ... \n",
1082 | "95 0 0 \n",
1083 | "96 0 0 \n",
1084 | "97 0 0 \n",
1085 | "98 0 0 \n",
1086 | "99 1 0 \n",
1087 | "\n",
1088 | " title_War Robots. 6v6 Tactical Multiplayer Battles \\\n",
1089 | "0 0 \n",
1090 | "1 0 \n",
1091 | "2 0 \n",
1092 | "3 0 \n",
1093 | "4 0 \n",
1094 | ".. ... \n",
1095 | "95 0 \n",
1096 | "96 0 \n",
1097 | "97 0 \n",
1098 | "98 0 \n",
1099 | "99 0 \n",
1100 | "\n",
1101 | " title_Worms Zone .io - Voracious Snake \\\n",
1102 | "0 0 \n",
1103 | "1 0 \n",
1104 | "2 0 \n",
1105 | "3 0 \n",
1106 | "4 0 \n",
1107 | ".. ... \n",
1108 | "95 0 \n",
1109 | "96 0 \n",
1110 | "97 0 \n",
1111 | "98 0 \n",
1112 | "99 0 \n",
1113 | "\n",
1114 | " title_Zombie Catchers - love the hunt! title_aquapark.io \\\n",
1115 | "0 0 0 \n",
1116 | "1 0 0 \n",
1117 | "2 0 0 \n",
1118 | "3 0 0 \n",
1119 | "4 0 0 \n",
1120 | ".. ... ... \n",
1121 | "95 0 0 \n",
1122 | "96 0 0 \n",
1123 | "97 0 0 \n",
1124 | "98 0 0 \n",
1125 | "99 0 0 \n",
1126 | "\n",
1127 | " category_GAME ACTION \n",
1128 | "0 1 \n",
1129 | "1 1 \n",
1130 | "2 1 \n",
1131 | "3 1 \n",
1132 | "4 1 \n",
1133 | ".. ... \n",
1134 | "95 1 \n",
1135 | "96 1 \n",
1136 | "97 1 \n",
1137 | "98 1 \n",
1138 | "99 1 \n",
1139 | "\n",
1140 | "[100 rows x 113 columns]"
1141 | ]
1142 | },
1143 | "execution_count": 27,
1144 | "metadata": {},
1145 | "output_type": "execute_result"
1146 | }
1147 | ],
1148 | "source": [
1149 | "dummi=u.get_dummies(data.drop(\"installs\", axis=1))\n",
1150 | "dummi"
1151 | ]
1152 | },
1153 | {
1154 | "cell_type": "code",
1155 | "execution_count": 28,
1156 | "id": "4b9b1986",
1157 | "metadata": {},
1158 | "outputs": [],
1159 | "source": [
1160 | "X = u.get_dummies(data.drop(\"installs\", axis=1), drop_first=True)\n",
1161 | "y = data[\"installs\"]"
1162 | ]
1163 | },
1164 | {
1165 | "cell_type": "code",
1166 | "execution_count": 29,
1167 | "id": "32c9c9ab",
1168 | "metadata": {},
1169 | "outputs": [
1170 | {
1171 | "data": {
1172 | "text/plain": [
1173 | "0 500.0 M\n",
1174 | "1 500.0 M\n",
1175 | "2 100.0 M\n",
1176 | "3 100.0 M\n",
1177 | "4 500.0 M\n",
1178 | " ... \n",
1179 | "95 10.0 M\n",
1180 | "96 10.0 M\n",
1181 | "97 10.0 M\n",
1182 | "98 10.0 M\n",
1183 | "99 10.0 M\n",
1184 | "Name: installs, Length: 100, dtype: object"
1185 | ]
1186 | },
1187 | "execution_count": 29,
1188 | "metadata": {},
1189 | "output_type": "execute_result"
1190 | }
1191 | ],
1192 | "source": [
1193 | "y"
1194 | ]
1195 | },
1196 | {
1197 | "cell_type": "code",
1198 | "execution_count": 30,
1199 | "id": "512bdea4",
1200 | "metadata": {},
1201 | "outputs": [],
1202 | "source": [
1203 | "from sklearn.tree import DecisionTreeClassifier\n",
1204 | "model = DecisionTreeClassifier()\n"
1205 | ]
1206 | },
1207 | {
1208 | "cell_type": "code",
1209 | "execution_count": 31,
1210 | "id": "c9c6517a",
1211 | "metadata": {},
1212 | "outputs": [
1213 | {
1214 | "data": {
1215 | "text/plain": [
1216 | "DecisionTreeClassifier()"
1217 | ]
1218 | },
1219 | "execution_count": 31,
1220 | "metadata": {},
1221 | "output_type": "execute_result"
1222 | }
1223 | ],
1224 | "source": [
1225 | "model.fit(X, y)\n"
1226 | ]
1227 | },
1228 | {
1229 | "cell_type": "code",
1230 | "execution_count": 32,
1231 | "id": "97a214d4",
1232 | "metadata": {},
1233 | "outputs": [
1234 | {
1235 | "data": {
1236 | "text/plain": [
1237 | "array(['500.0 M', '500.0 M', '100.0 M', '100.0 M', '500.0 M', '100.0 M',\n",
1238 | " '100.0 M', '500.0 M', '100.0 M', '100.0 M', '100.0 M', '100.0 M',\n",
1239 | " '50.0 M', '100.0 M', '50.0 M', '100.0 M', '100.0 M', '50.0 M',\n",
1240 | " '50.0 M', '50.0 M', '100.0 M', '100.0 M', '100.0 M', '100.0 M',\n",
1241 | " '100.0 M', '50.0 M', '100.0 M', '10.0 M', '50.0 M', '10.0 M',\n",
1242 | " '100.0 M', '50.0 M', '50.0 M', '50.0 M', '10.0 M', '100.0 M',\n",
1243 | " '10.0 M', '100.0 M', '10.0 M', '50.0 M', '50.0 M', '100.0 M',\n",
1244 | " '50.0 M', '100.0 M', '50.0 M', '10.0 M', '50.0 M', '10.0 M',\n",
1245 | " '10.0 M', '100.0 M', '100.0 M', '50.0 M', '50.0 M', '10.0 M',\n",
1246 | " '100.0 M', '100.0 M', '100.0 M', '50.0 M', '50.0 M', '100.0 M',\n",
1247 | " '10.0 M', '100.0 M', '50.0 M', '10.0 M', '50.0 M', '50.0 M',\n",
1248 | " '100.0 M', '10.0 M', '50.0 M', '10.0 M', '100.0 M', '10.0 M',\n",
1249 | " '50.0 M', '10.0 M', '100.0 M', '10.0 M', '100.0 M', '10.0 M',\n",
1250 | " '10.0 M', '10.0 M', '10.0 M', '100.0 M', '100.0 M', '10.0 M',\n",
1251 | " '10.0 M', '10.0 M', '100.0 M', '10.0 M', '10.0 M', '50.0 M',\n",
1252 | " '100.0 M', '50.0 M', '50.0 M', '50.0 M', '10.0 M', '10.0 M',\n",
1253 | " '10.0 M', '10.0 M', '10.0 M', '10.0 M'], dtype=object)"
1254 | ]
1255 | },
1256 | "execution_count": 32,
1257 | "metadata": {},
1258 | "output_type": "execute_result"
1259 | }
1260 | ],
1261 | "source": [
1262 | "pred = model.predict(X)\n",
1263 | "pred"
1264 | ]
1265 | },
1266 | {
1267 | "cell_type": "code",
1268 | "execution_count": 33,
1269 | "id": "3772308f",
1270 | "metadata": {},
1271 | "outputs": [
1272 | {
1273 | "data": {
1274 | "image/png": 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\n",
1275 | "text/plain": [
1276 | ""
1277 | ]
1278 | },
1279 | "metadata": {
1280 | "needs_background": "light"
1281 | },
1282 | "output_type": "display_data"
1283 | }
1284 | ],
1285 | "source": [
1286 | "from sklearn.tree import plot_tree\n",
1287 | "plot_tree(model, feature_names=X.columns, filled=True);"
1288 | ]
1289 | },
1290 | {
1291 | "cell_type": "code",
1292 | "execution_count": 34,
1293 | "id": "1dd1f5c3",
1294 | "metadata": {},
1295 | "outputs": [
1296 | {
1297 | "data": {
1298 | "text/html": [
1299 | "\n",
1300 | "\n",
1313 | "
\n",
1314 | " \n",
1315 | " \n",
1316 | " | \n",
1317 | " Actual | \n",
1318 | " Predicted | \n",
1319 | "
\n",
1320 | " \n",
1321 | " \n",
1322 | " \n",
1323 | " 0 | \n",
1324 | " 500.0 M | \n",
1325 | " 500.0 M | \n",
1326 | "
\n",
1327 | " \n",
1328 | " 1 | \n",
1329 | " 500.0 M | \n",
1330 | " 500.0 M | \n",
1331 | "
\n",
1332 | " \n",
1333 | " 2 | \n",
1334 | " 100.0 M | \n",
1335 | " 100.0 M | \n",
1336 | "
\n",
1337 | " \n",
1338 | " 3 | \n",
1339 | " 100.0 M | \n",
1340 | " 100.0 M | \n",
1341 | "
\n",
1342 | " \n",
1343 | " 4 | \n",
1344 | " 500.0 M | \n",
1345 | " 500.0 M | \n",
1346 | "
\n",
1347 | " \n",
1348 | " ... | \n",
1349 | " ... | \n",
1350 | " ... | \n",
1351 | "
\n",
1352 | " \n",
1353 | " 95 | \n",
1354 | " 10.0 M | \n",
1355 | " 10.0 M | \n",
1356 | "
\n",
1357 | " \n",
1358 | " 96 | \n",
1359 | " 10.0 M | \n",
1360 | " 10.0 M | \n",
1361 | "
\n",
1362 | " \n",
1363 | " 97 | \n",
1364 | " 10.0 M | \n",
1365 | " 10.0 M | \n",
1366 | "
\n",
1367 | " \n",
1368 | " 98 | \n",
1369 | " 10.0 M | \n",
1370 | " 10.0 M | \n",
1371 | "
\n",
1372 | " \n",
1373 | " 99 | \n",
1374 | " 10.0 M | \n",
1375 | " 10.0 M | \n",
1376 | "
\n",
1377 | " \n",
1378 | "
\n",
1379 | "
100 rows × 2 columns
\n",
1380 | "
"
1381 | ],
1382 | "text/plain": [
1383 | " Actual Predicted\n",
1384 | "0 500.0 M 500.0 M\n",
1385 | "1 500.0 M 500.0 M\n",
1386 | "2 100.0 M 100.0 M\n",
1387 | "3 100.0 M 100.0 M\n",
1388 | "4 500.0 M 500.0 M\n",
1389 | ".. ... ...\n",
1390 | "95 10.0 M 10.0 M\n",
1391 | "96 10.0 M 10.0 M\n",
1392 | "97 10.0 M 10.0 M\n",
1393 | "98 10.0 M 10.0 M\n",
1394 | "99 10.0 M 10.0 M\n",
1395 | "\n",
1396 | "[100 rows x 2 columns]"
1397 | ]
1398 | },
1399 | "execution_count": 34,
1400 | "metadata": {},
1401 | "output_type": "execute_result"
1402 | }
1403 | ],
1404 | "source": [
1405 | "pred= model.predict(X)\n",
1406 | "df =u.DataFrame({'Actual': y, 'Predicted':pred})\n",
1407 | "df"
1408 | ]
1409 | },
1410 | {
1411 | "cell_type": "code",
1412 | "execution_count": 35,
1413 | "id": "b18e0b66",
1414 | "metadata": {},
1415 | "outputs": [
1416 | {
1417 | "name": "stdout",
1418 | "output_type": "stream",
1419 | "text": [
1420 | "[[31 0 0 0]\n",
1421 | " [ 0 37 0 0]\n",
1422 | " [ 0 0 28 0]\n",
1423 | " [ 0 0 0 4]]\n"
1424 | ]
1425 | }
1426 | ],
1427 | "source": [
1428 | "from sklearn.metrics import classification_report, confusion_matrix\n",
1429 | "print(confusion_matrix(y, pred))"
1430 | ]
1431 | },
1432 | {
1433 | "cell_type": "code",
1434 | "execution_count": 36,
1435 | "id": "84f0bf7c",
1436 | "metadata": {},
1437 | "outputs": [
1438 | {
1439 | "name": "stdout",
1440 | "output_type": "stream",
1441 | "text": [
1442 | " precision recall f1-score support\n",
1443 | "\n",
1444 | " 10.0 M 1.00 1.00 1.00 31\n",
1445 | " 100.0 M 1.00 1.00 1.00 37\n",
1446 | " 50.0 M 1.00 1.00 1.00 28\n",
1447 | " 500.0 M 1.00 1.00 1.00 4\n",
1448 | "\n",
1449 | " accuracy 1.00 100\n",
1450 | " macro avg 1.00 1.00 1.00 100\n",
1451 | "weighted avg 1.00 1.00 1.00 100\n",
1452 | "\n"
1453 | ]
1454 | }
1455 | ],
1456 | "source": [
1457 | "print(classification_report(y, pred))"
1458 | ]
1459 | }
1460 | ],
1461 | "metadata": {
1462 | "kernelspec": {
1463 | "display_name": "Python 3 (ipykernel)",
1464 | "language": "python",
1465 | "name": "python3"
1466 | },
1467 | "language_info": {
1468 | "codemirror_mode": {
1469 | "name": "ipython",
1470 | "version": 3
1471 | },
1472 | "file_extension": ".py",
1473 | "mimetype": "text/x-python",
1474 | "name": "python",
1475 | "nbconvert_exporter": "python",
1476 | "pygments_lexer": "ipython3",
1477 | "version": "3.9.12"
1478 | }
1479 | },
1480 | "nbformat": 4,
1481 | "nbformat_minor": 5
1482 | }
1483 |
--------------------------------------------------------------------------------