pokemon - A5

sobre o desenho pokemon

importar a base de dados

QE <- load("C:/Users/14086606798/Downloads/df_pokemon.Rdata")

fase 2 - inspecionar a base de dados - saber a altura dos personagens (pokemons)

tail(df$height)

## [1] 20  5 15 30 58 50

summary(df)

##        id          pokemon            species_id        height      
##  Min.   :  1.0   Length:718         Min.   :  1.0   Min.   :  1.00  
##  1st Qu.:180.2   Class :character   1st Qu.:180.2   1st Qu.:  6.00  
##  Median :359.5   Mode  :character   Median :359.5   Median : 10.00  
##  Mean   :359.5                      Mean   :359.5   Mean   : 11.41  
##  3rd Qu.:538.8                      3rd Qu.:538.8   3rd Qu.: 14.00  
##  Max.   :718.0                      Max.   :718.0   Max.   :145.00  
##      weight       base_experience     type_1             type_2         
##  Min.   :   1.0   Min.   : 36.00   Length:718         Length:718        
##  1st Qu.:  95.0   1st Qu.: 65.25   Class :character   Class :character  
##  Median : 280.0   Median :147.00   Mode  :character   Mode  :character  
##  Mean   : 568.2   Mean   :141.55                                        
##  3rd Qu.: 609.5   3rd Qu.:177.00                                        
##  Max.   :9500.0   Max.   :608.00                                        
##      attack          defense             hp         special_attack  
##  Min.   :  5.00   Min.   :  5.00   Min.   :  1.00   Min.   : 10.00  
##  1st Qu.: 53.00   1st Qu.: 50.00   1st Qu.: 50.00   1st Qu.: 45.00  
##  Median : 73.00   Median : 65.00   Median : 65.00   Median : 65.00  
##  Mean   : 74.85   Mean   : 70.67   Mean   : 68.37   Mean   : 68.47  
##  3rd Qu.: 95.00   3rd Qu.: 85.00   3rd Qu.: 80.00   3rd Qu.: 90.00  
##  Max.   :165.00   Max.   :230.00   Max.   :255.00   Max.   :154.00  
##  special_defense      speed          color_1            color_2         
##  Min.   : 20.00   Min.   :  5.00   Length:718         Length:718        
##  1st Qu.: 50.00   1st Qu.: 45.00   Class :character   Class :character  
##  Median : 65.00   Median : 65.00   Mode  :character   Mode  :character  
##  Mean   : 69.09   Mean   : 65.72                                        
##  3rd Qu.: 85.00   3rd Qu.: 85.00                                        
##  Max.   :230.00   Max.   :160.00                                        
##    color_f          egg_group_1        egg_group_2         url_image        
##  Length:718         Length:718         Length:718         Length:718        
##  Class :character   Class :character   Class :character   Class :character  
##  Mode  :character   Mode  :character   Mode  :character   Mode  :character  
##                                                                             
##                                                                             
##                                                                             
##        x                 y          
##  Min.   :-49.152   Min.   :-45.793  
##  1st Qu.:-17.695   1st Qu.:-17.293  
##  Median :  0.705   Median : -0.628  
##  Mean   :  0.000   Mean   :  0.000  
##  3rd Qu.: 15.905   3rd Qu.: 18.155  
##  Max.   : 53.142   Max.   : 46.593

fase 3 - importar as blibliotecas

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.2.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(flextable)

## Warning: package 'flextable' was built under R version 4.2.3

library(janitor)

## Warning: package 'janitor' was built under R version 4.2.3

## 
## Attaching package: 'janitor'

## The following objects are masked from 'package:stats':
## 
##     chisq.test, fisher.test

fase 4 - chamar a tabela da altura e implementar a proporção

tabela = table(df$height)

#proporção dos bichos(para altura)

janitor::tabyl(df, height) %>%
  adorn_percentages("row") %>%
  adorn_pct_formatting(digits = 2) %>%
  adorn_ns %>% flextable() %>% theme_tron()

## Warning in adorn_ns(.): adorn_ns() is meant to be called on a two_way tabyl;
## consider combining columns of a one_way tabyl with tidyr::unite()

height	n	percent
1	1 (2)	0.14% (0.002785515)
2	1 (13)	0.14% (0.018105850)
3	1 (45)	0.14% (0.062674095)
4	1 (56)	0.14% (0.077994429)
5	1 (55)	0.14% (0.076601671)
6	1 (66)	0.14% (0.091922006)
7	1 (33)	0.14% (0.045961003)
8	1 (43)	0.14% (0.059888579)
9	1 (32)	0.14% (0.044568245)
10	1 (58)	0.14% (0.080779944)
11	1 (36)	0.14% (0.050139276)
12	1 (45)	0.14% (0.062674095)
13	1 (27)	0.14% (0.037604457)
14	1 (29)	0.14% (0.040389972)
15	1 (41)	0.14% (0.057103064)
16	1 (23)	0.14% (0.032033426)
17	1 (20)	0.14% (0.027855153)
18	1 (16)	0.14% (0.022284123)
19	1 (11)	0.14% (0.015320334)
20	1 (19)	0.14% (0.026462396)
21	1 (7)	0.14% (0.009749304)
22	1 (6)	0.14% (0.008356546)
23	1 (2)	0.14% (0.002785515)
24	1 (1)	0.14% (0.001392758)
25	1 (4)	0.14% (0.005571031)
26	1 (1)	0.14% (0.001392758)
27	1 (2)	0.14% (0.002785515)
28	1 (1)	0.14% (0.001392758)
29	1 (1)	0.14% (0.001392758)
30	1 (2)	0.14% (0.002785515)
32	1 (2)	0.14% (0.002785515)
33	1 (1)	0.14% (0.001392758)
35	1 (2)	0.14% (0.002785515)
37	1 (1)	0.14% (0.001392758)
38	1 (1)	0.14% (0.001392758)
40	1 (1)	0.14% (0.001392758)
42	1 (1)	0.14% (0.001392758)
45	1 (2)	0.14% (0.002785515)
50	1 (1)	0.14% (0.001392758)
52	1 (1)	0.14% (0.001392758)
54	1 (1)	0.14% (0.001392758)
58	1 (1)	0.14% (0.001392758)
62	1 (1)	0.14% (0.001392758)
65	1 (1)	0.14% (0.001392758)
70	1 (1)	0.14% (0.001392758)
88	1 (1)	0.14% (0.001392758)
92	1 (1)	0.14% (0.001392758)
145	1 (1)	0.14% (0.001392758)

##proporção dos bichos(para peso)

tabela2 = table(df$weight)

janitor::tabyl(df, weight)%>%
  adorn_percentages("row") %>%
  adorn_pct_formatting(digits = 2) %>%
  adorn_ns %>% flextable() %>% theme_tron()

## Warning in adorn_ns(.): adorn_ns() is meant to be called on a two_way tabyl;
## consider combining columns of a one_way tabyl with tidyr::unite()

weight	n	percent
1	1 (3)	0.14% (0.004178273)
3	1 (5)	0.14% (0.006963788)
5	1 (2)	0.14% (0.002785515)
6	1 (3)	0.14% (0.004178273)
8	1 (2)	0.14% (0.002785515)
9	1 (1)	0.14% (0.001392758)
10	1 (7)	0.14% (0.009749304)
11	1 (1)	0.14% (0.001392758)
12	1 (4)	0.14% (0.005571031)
14	1 (1)	0.14% (0.001392758)
15	1 (2)	0.14% (0.002785515)
17	1 (2)	0.14% (0.002785515)
18	1 (2)	0.14% (0.002785515)
19	1 (2)	0.14% (0.002785515)
20	1 (7)	0.14% (0.009749304)
21	1 (4)	0.14% (0.005571031)
22	1 (2)	0.14% (0.002785515)
23	1 (2)	0.14% (0.002785515)
25	1 (4)	0.14% (0.005571031)
26	1 (1)	0.14% (0.001392758)
28	1 (1)	0.14% (0.001392758)
29	1 (1)	0.14% (0.001392758)
30	1 (3)	0.14% (0.004178273)
31	1 (2)	0.14% (0.002785515)
32	1 (2)	0.14% (0.002785515)
33	1 (2)	0.14% (0.002785515)
34	1 (1)	0.14% (0.001392758)
35	1 (4)	0.14% (0.005571031)
36	1 (2)	0.14% (0.002785515)
39	1 (3)	0.14% (0.004178273)
40	1 (6)	0.14% (0.008356546)
41	1 (1)	0.14% (0.001392758)
42	1 (3)	0.14% (0.004178273)
44	1 (1)	0.14% (0.001392758)
45	1 (3)	0.14% (0.004178273)
50	1 (9)	0.14% (0.012534819)
52	1 (1)	0.14% (0.001392758)
53	1 (1)	0.14% (0.001392758)
54	1 (2)	0.14% (0.002785515)
55	1 (5)	0.14% (0.006963788)
57	1 (2)	0.14% (0.002785515)
58	1 (3)	0.14% (0.004178273)
59	1 (2)	0.14% (0.002785515)
60	1 (5)	0.14% (0.006963788)
62	1 (1)	0.14% (0.001392758)
63	1 (1)	0.14% (0.001392758)
64	1 (2)	0.14% (0.002785515)
65	1 (6)	0.14% (0.008356546)
66	1 (3)	0.14% (0.004178273)
69	1 (2)	0.14% (0.002785515)
70	1 (4)	0.14% (0.005571031)
72	1 (1)	0.14% (0.001392758)
73	1 (2)	0.14% (0.002785515)
74	1 (1)	0.14% (0.001392758)
75	1 (4)	0.14% (0.005571031)
76	1 (1)	0.14% (0.001392758)
77	1 (1)	0.14% (0.001392758)
78	1 (2)	0.14% (0.002785515)
79	1 (1)	0.14% (0.001392758)
80	1 (4)	0.14% (0.005571031)
81	1 (1)	0.14% (0.001392758)
83	1 (1)	0.14% (0.001392758)
84	1 (1)	0.14% (0.001392758)
85	1 (8)	0.14% (0.011142061)
86	1 (1)	0.14% (0.001392758)
87	1 (1)	0.14% (0.001392758)
88	1 (1)	0.14% (0.001392758)
90	1 (5)	0.14% (0.006963788)
93	1 (1)	0.14% (0.001392758)
94	1 (1)	0.14% (0.001392758)
95	1 (5)	0.14% (0.006963788)
99	1 (3)	0.14% (0.004178273)
100	1 (4)	0.14% (0.005571031)
101	1 (1)	0.14% (0.001392758)
102	1 (2)	0.14% (0.002785515)
103	1 (1)	0.14% (0.001392758)
104	1 (1)	0.14% (0.001392758)
105	1 (4)	0.14% (0.005571031)
108	1 (2)	0.14% (0.002785515)
109	1 (1)	0.14% (0.001392758)
110	1 (4)	0.14% (0.005571031)
112	1 (1)	0.14% (0.001392758)
115	1 (5)	0.14% (0.006963788)
116	1 (1)	0.14% (0.001392758)
118	1 (1)	0.14% (0.001392758)
120	1 (6)	0.14% (0.008356546)
124	1 (1)	0.14% (0.001392758)
125	1 (6)	0.14% (0.008356546)
130	1 (3)	0.14% (0.004178273)
133	1 (1)	0.14% (0.001392758)
135	1 (2)	0.14% (0.002785515)
136	1 (1)	0.14% (0.001392758)
140	1 (3)	0.14% (0.004178273)
143	1 (1)	0.14% (0.001392758)
145	1 (3)	0.14% (0.004178273)
147	1 (1)	0.14% (0.001392758)
150	1 (8)	0.14% (0.011142061)
152	1 (2)	0.14% (0.002785515)
153	1 (1)	0.14% (0.001392758)
155	1 (3)	0.14% (0.004178273)
158	1 (1)	0.14% (0.001392758)
160	1 (3)	0.14% (0.004178273)
163	1 (2)	0.14% (0.002785515)
165	1 (2)	0.14% (0.002785515)
168	1 (1)	0.14% (0.001392758)
170	1 (2)	0.14% (0.002785515)
173	1 (1)	0.14% (0.001392758)
175	1 (2)	0.14% (0.002785515)
177	1 (2)	0.14% (0.002785515)
180	1 (4)	0.14% (0.005571031)
185	1 (1)	0.14% (0.001392758)
186	1 (1)	0.14% (0.001392758)
188	1 (1)	0.14% (0.001392758)
190	1 (3)	0.14% (0.004178273)
192	1 (1)	0.14% (0.001392758)
195	1 (5)	0.14% (0.006963788)
196	1 (1)	0.14% (0.001392758)
198	1 (1)	0.14% (0.001392758)
199	1 (1)	0.14% (0.001392758)
200	1 (5)	0.14% (0.006963788)
201	1 (1)	0.14% (0.001392758)
202	1 (2)	0.14% (0.002785515)
203	1 (1)	0.14% (0.001392758)
205	1 (3)	0.14% (0.004178273)
206	1 (1)	0.14% (0.001392758)
208	1 (1)	0.14% (0.001392758)
210	1 (3)	0.14% (0.004178273)
212	1 (1)	0.14% (0.001392758)
214	1 (1)	0.14% (0.001392758)
215	1 (2)	0.14% (0.002785515)
216	1 (1)	0.14% (0.001392758)
220	1 (3)	0.14% (0.004178273)
225	1 (2)	0.14% (0.002785515)
226	1 (1)	0.14% (0.001392758)
230	1 (2)	0.14% (0.002785515)
233	1 (2)	0.14% (0.002785515)
234	1 (1)	0.14% (0.001392758)
235	1 (2)	0.14% (0.002785515)
236	1 (1)	0.14% (0.001392758)
238	1 (1)	0.14% (0.001392758)
240	1 (3)	0.14% (0.004178273)
242	1 (1)	0.14% (0.001392758)
244	1 (1)	0.14% (0.001392758)
245	1 (3)	0.14% (0.004178273)
249	1 (1)	0.14% (0.001392758)
250	1 (3)	0.14% (0.004178273)
252	1 (1)	0.14% (0.001392758)
253	1 (1)	0.14% (0.001392758)
255	1 (2)	0.14% (0.002785515)
259	1 (1)	0.14% (0.001392758)
260	1 (1)	0.14% (0.001392758)
265	1 (1)	0.14% (0.001392758)
266	1 (1)	0.14% (0.001392758)
270	1 (4)	0.14% (0.005571031)
273	1 (1)	0.14% (0.001392758)
280	1 (8)	0.14% (0.011142061)
284	1 (1)	0.14% (0.001392758)
285	1 (3)	0.14% (0.004178273)
288	1 (1)	0.14% (0.001392758)
290	1 (4)	0.14% (0.005571031)
295	1 (4)	0.14% (0.005571031)
298	1 (1)	0.14% (0.001392758)
299	1 (1)	0.14% (0.001392758)
300	1 (8)	0.14% (0.011142061)
305	1 (2)	0.14% (0.002785515)
306	1 (2)	0.14% (0.002785515)
310	1 (4)	0.14% (0.005571031)
315	1 (3)	0.14% (0.004178273)
316	1 (2)	0.14% (0.002785515)
320	1 (4)	0.14% (0.005571031)
324	1 (1)	0.14% (0.001392758)
325	1 (4)	0.14% (0.005571031)
326	1 (1)	0.14% (0.001392758)
328	1 (1)	0.14% (0.001392758)
330	1 (3)	0.14% (0.004178273)
333	1 (2)	0.14% (0.002785515)
334	1 (1)	0.14% (0.001392758)
335	1 (3)	0.14% (0.004178273)
339	1 (1)	0.14% (0.001392758)
340	1 (2)	0.14% (0.002785515)
343	1 (1)	0.14% (0.001392758)
345	1 (2)	0.14% (0.002785515)
346	1 (1)	0.14% (0.001392758)
350	1 (4)	0.14% (0.005571031)
353	1 (1)	0.14% (0.001392758)
355	1 (1)	0.14% (0.001392758)
356	1 (1)	0.14% (0.001392758)
360	1 (2)	0.14% (0.002785515)
365	1 (1)	0.14% (0.001392758)
370	1 (1)	0.14% (0.001392758)
375	1 (2)	0.14% (0.002785515)
380	1 (5)	0.14% (0.006963788)
385	1 (1)	0.14% (0.001392758)
390	1 (2)	0.14% (0.002785515)
392	1 (2)	0.14% (0.002785515)
395	1 (3)	0.14% (0.004178273)
400	1 (4)	0.14% (0.005571031)
402	1 (1)	0.14% (0.001392758)
403	1 (1)	0.14% (0.001392758)
404	1 (1)	0.14% (0.001392758)
405	1 (3)	0.14% (0.004178273)
406	1 (1)	0.14% (0.001392758)
408	1 (1)	0.14% (0.001392758)
410	1 (2)	0.14% (0.002785515)
415	1 (1)	0.14% (0.001392758)
420	1 (1)	0.14% (0.001392758)
421	1 (1)	0.14% (0.001392758)
424	1 (1)	0.14% (0.001392758)
425	1 (1)	0.14% (0.001392758)
438	1 (1)	0.14% (0.001392758)
440	1 (1)	0.14% (0.001392758)
444	1 (1)	0.14% (0.001392758)
445	1 (1)	0.14% (0.001392758)
450	1 (1)	0.14% (0.001392758)
455	1 (1)	0.14% (0.001392758)
460	1 (1)	0.14% (0.001392758)
465	1 (1)	0.14% (0.001392758)
468	1 (1)	0.14% (0.001392758)
470	1 (2)	0.14% (0.002785515)
480	1 (2)	0.14% (0.002785515)
484	1 (1)	0.14% (0.001392758)
485	1 (1)	0.14% (0.001392758)
487	1 (1)	0.14% (0.001392758)
495	1 (1)	0.14% (0.001392758)
498	1 (1)	0.14% (0.001392758)
500	1 (1)	0.14% (0.001392758)
502	1 (1)	0.14% (0.001392758)
505	1 (3)	0.14% (0.004178273)
510	1 (2)	0.14% (0.002785515)
513	1 (1)	0.14% (0.001392758)
515	1 (1)	0.14% (0.001392758)
520	1 (2)	0.14% (0.002785515)
522	1 (1)	0.14% (0.001392758)
525	1 (2)	0.14% (0.002785515)
526	1 (1)	0.14% (0.001392758)
530	1 (1)	0.14% (0.001392758)
540	1 (3)	0.14% (0.004178273)
545	1 (1)	0.14% (0.001392758)
550	1 (6)	0.14% (0.008356546)
554	1 (1)	0.14% (0.001392758)
555	1 (2)	0.14% (0.002785515)
558	1 (1)	0.14% (0.001392758)
560	1 (2)	0.14% (0.002785515)
565	1 (1)	0.14% (0.001392758)
570	1 (1)	0.14% (0.001392758)
575	1 (1)	0.14% (0.001392758)
580	1 (2)	0.14% (0.002785515)
585	1 (1)	0.14% (0.001392758)
590	1 (1)	0.14% (0.001392758)
596	1 (1)	0.14% (0.001392758)
600	1 (6)	0.14% (0.008356546)
604	1 (1)	0.14% (0.001392758)
605	1 (2)	0.14% (0.002785515)
608	1 (1)	0.14% (0.001392758)
610	1 (2)	0.14% (0.002785515)
615	1 (2)	0.14% (0.002785515)
620	1 (2)	0.14% (0.002785515)
630	1 (2)	0.14% (0.002785515)
648	1 (1)	0.14% (0.001392758)
650	1 (2)	0.14% (0.002785515)
655	1 (1)	0.14% (0.001392758)
666	1 (1)	0.14% (0.001392758)
680	1 (2)	0.14% (0.002785515)
682	1 (1)	0.14% (0.001392758)
700	1 (1)	0.14% (0.001392758)
705	1 (1)	0.14% (0.001392758)
710	1 (1)	0.14% (0.001392758)
712	1 (1)	0.14% (0.001392758)
715	1 (1)	0.14% (0.001392758)
720	1 (1)	0.14% (0.001392758)
750	1 (2)	0.14% (0.002785515)
755	1 (1)	0.14% (0.001392758)
756	1 (1)	0.14% (0.001392758)
765	1 (1)	0.14% (0.001392758)
766	1 (1)	0.14% (0.001392758)
774	1 (1)	0.14% (0.001392758)
785	1 (1)	0.14% (0.001392758)
795	1 (3)	0.14% (0.004178273)
800	1 (3)	0.14% (0.004178273)
804	1 (1)	0.14% (0.001392758)
805	1 (1)	0.14% (0.001392758)
810	1 (2)	0.14% (0.002785515)
811	1 (1)	0.14% (0.001392758)
815	1 (2)	0.14% (0.002785515)
819	1 (1)	0.14% (0.001392758)
820	1 (1)	0.14% (0.001392758)
825	1 (1)	0.14% (0.001392758)
840	1 (1)	0.14% (0.001392758)
845	1 (1)	0.14% (0.001392758)
850	1 (1)	0.14% (0.001392758)
852	1 (1)	0.14% (0.001392758)
855	1 (1)	0.14% (0.001392758)
856	1 (1)	0.14% (0.001392758)
864	1 (1)	0.14% (0.001392758)
870	1 (1)	0.14% (0.001392758)
876	1 (1)	0.14% (0.001392758)
884	1 (1)	0.14% (0.001392758)
888	1 (2)	0.14% (0.002785515)
900	1 (2)	0.14% (0.002785515)
905	1 (1)	0.14% (0.001392758)
910	1 (1)	0.14% (0.001392758)
920	1 (1)	0.14% (0.001392758)
925	1 (1)	0.14% (0.001392758)
929	1 (1)	0.14% (0.001392758)
946	1 (2)	0.14% (0.002785515)
950	1 (2)	0.14% (0.002785515)
952	1 (1)	0.14% (0.001392758)
960	1 (1)	0.14% (0.001392758)
963	1 (1)	0.14% (0.001392758)
970	1 (2)	0.14% (0.002785515)
995	1 (1)	0.14% (0.001392758)
1,000	1 (2)	0.14% (0.002785515)
1,005	1 (1)	0.14% (0.001392758)
1,020	1 (1)	0.14% (0.001392758)
1,025	1 (1)	0.14% (0.001392758)
1,026	1 (1)	0.14% (0.001392758)
1,050	1 (2)	0.14% (0.002785515)
1,055	1 (1)	0.14% (0.001392758)
1,066	1 (1)	0.14% (0.001392758)
1,073	1 (1)	0.14% (0.001392758)
1,080	1 (2)	0.14% (0.002785515)
1,100	1 (1)	0.14% (0.001392758)
1,105	1 (1)	0.14% (0.001392758)
1,150	1 (1)	0.14% (0.001392758)
1,180	1 (1)	0.14% (0.001392758)
1,200	1 (5)	0.14% (0.006963788)
1,220	1 (1)	0.14% (0.001392758)
1,258	1 (2)	0.14% (0.002785515)
1,286	1 (1)	0.14% (0.001392758)
1,300	1 (2)	0.14% (0.002785515)
1,305	1 (1)	0.14% (0.001392758)
1,325	1 (1)	0.14% (0.001392758)
1,350	1 (1)	0.14% (0.001392758)
1,355	1 (1)	0.14% (0.001392758)
1,360	1 (1)	0.14% (0.001392758)
1,386	1 (1)	0.14% (0.001392758)
1,390	1 (1)	0.14% (0.001392758)
1,400	1 (1)	0.14% (0.001392758)
1,480	1 (1)	0.14% (0.001392758)
1,495	1 (1)	0.14% (0.001392758)
1,500	1 (1)	0.14% (0.001392758)
1,505	1 (1)	0.14% (0.001392758)
1,506	1 (1)	0.14% (0.001392758)
1,520	1 (2)	0.14% (0.002785515)
1,540	1 (1)	0.14% (0.001392758)
1,550	1 (1)	0.14% (0.001392758)
1,600	1 (1)	0.14% (0.001392758)
1,620	1 (1)	0.14% (0.001392758)
1,680	1 (1)	0.14% (0.001392758)
1,750	1 (1)	0.14% (0.001392758)
1,780	1 (1)	0.14% (0.001392758)
1,800	1 (1)	0.14% (0.001392758)
1,870	1 (2)	0.14% (0.002785515)
1,980	1 (1)	0.14% (0.001392758)
1,990	1 (1)	0.14% (0.001392758)
2,000	1 (2)	0.14% (0.002785515)
2,005	1 (1)	0.14% (0.001392758)
2,020	1 (1)	0.14% (0.001392758)
2,025	1 (1)	0.14% (0.001392758)
2,030	1 (1)	0.14% (0.001392758)
2,050	1 (1)	0.14% (0.001392758)
2,065	1 (1)	0.14% (0.001392758)
2,100	1 (2)	0.14% (0.002785515)
2,150	1 (1)	0.14% (0.001392758)
2,160	1 (1)	0.14% (0.001392758)
2,200	1 (3)	0.14% (0.004178273)
2,250	1 (1)	0.14% (0.001392758)
2,300	1 (1)	0.14% (0.001392758)
2,350	1 (1)	0.14% (0.001392758)
2,500	1 (1)	0.14% (0.001392758)
2,538	1 (1)	0.14% (0.001392758)
2,565	1 (1)	0.14% (0.001392758)
2,600	1 (3)	0.14% (0.004178273)
2,700	1 (1)	0.14% (0.001392758)
2,828	1 (1)	0.14% (0.001392758)
2,910	1 (1)	0.14% (0.001392758)
3,000	1 (2)	0.14% (0.002785515)
3,050	1 (1)	0.14% (0.001392758)
3,100	1 (1)	0.14% (0.001392758)
3,200	1 (1)	0.14% (0.001392758)
3,250	1 (1)	0.14% (0.001392758)
3,300	1 (2)	0.14% (0.002785515)
3,360	1 (1)	0.14% (0.001392758)
3,400	1 (1)	0.14% (0.001392758)
3,450	1 (1)	0.14% (0.001392758)
3,520	1 (1)	0.14% (0.001392758)
3,600	1 (1)	0.14% (0.001392758)
3,980	1 (1)	0.14% (0.001392758)
4,000	1 (1)	0.14% (0.001392758)
4,200	1 (1)	0.14% (0.001392758)
4,300	1 (1)	0.14% (0.001392758)
4,600	1 (1)	0.14% (0.001392758)
5,050	1 (1)	0.14% (0.001392758)
5,500	1 (1)	0.14% (0.001392758)
6,830	1 (1)	0.14% (0.001392758)
7,500	1 (1)	0.14% (0.001392758)
9,500	1 (1)	0.14% (0.001392758)

fase 5 - verificar as variaveis para a altura

#media
mean(df$height)

## [1] 11.40669

#mediana
median(df$height)

## [1] 10

#desvio padrão
sd(df$height)

## [1] 10.31993

fase 6 - verificar as variaveis peso

#media
mean(df$weight)

## [1] 568.1657

#mediana
median(df$weight)

## [1] 280

#desvio padrão
sd(df$weight)

## [1] 901.1062

##tabela de barras de altura

tabela = table(df$height)

barplot(tabela, main = "alturas dos pokemons",
        col=c("tan","blue","pink","brown"), beside = TRUE, 
        legend.text = rownames(tabela),
        args.legend = list(x = "topleft"))

devido da grande quantidade de pokemons é observado que as variaveis.

para altura:

media = 11.40669 mediana = 10 desvio padrão = 10.31993

para peso:

media = 568.1657 mediana = 280 desvio padrão = 901.1062

conclusão

existem mais pokemons “baixos” do que “altos”.