##  [1] "version"            "version_name"       "start_date"        
##  [4] "end_date"           "X5_star_characters" "rerun"             
##  [7] "mixed"              "revenue"            "banner_days"       
## [10] "avg_revenue"
## 
## 10,215,165 11,816,107 12,481,634 12,586,764 12,619,390 13,145,115 13,404,072 
##          1          1          1          1          1          1          1 
## 13,443,619 14,333,266 15,110,264 15,669,918 15,681,840 15,731,680 16,264,892 
##          1          1          1          1          1          1          1 
## 16,451,006 16,614,209 16,994,406 17,026,066 19,052,023 19,068,372 22,750,080 
##          1          1          1          1          1          1          1 
## 22,767,455 24,808,479 25,226,952 26,780,298 30,632,752 32,101,943 32,177,144 
##          1          1          1          1          1          1          1 
## 33,020,905 33,560,259 35,939,066  6,965,445  7,006,180  7,020,975  7,785,438 
##          1          1          1          1          1          1          1 
##  8,615,144  9,505,798  9,807,112 
##          1          1          1

La funcion tabyl se encuentra en la paqueteria janitor.

Se trabajará con tabla revenue

##     revenue n    percent
##  10,215,165 1 0.02631579
##  11,816,107 1 0.02631579
##  12,481,634 1 0.02631579
##  12,586,764 1 0.02631579
##  12,619,390 1 0.02631579
##  13,145,115 1 0.02631579
##  13,404,072 1 0.02631579
##  13,443,619 1 0.02631579
##  14,333,266 1 0.02631579
##  15,110,264 1 0.02631579
##  15,669,918 1 0.02631579
##  15,681,840 1 0.02631579
##  15,731,680 1 0.02631579
##  16,264,892 1 0.02631579
##  16,451,006 1 0.02631579
##  16,614,209 1 0.02631579
##  16,994,406 1 0.02631579
##  17,026,066 1 0.02631579
##  19,052,023 1 0.02631579
##  19,068,372 1 0.02631579
##  22,750,080 1 0.02631579
##  22,767,455 1 0.02631579
##  24,808,479 1 0.02631579
##  25,226,952 1 0.02631579
##  26,780,298 1 0.02631579
##  30,632,752 1 0.02631579
##  32,101,943 1 0.02631579
##  32,177,144 1 0.02631579
##  33,020,905 1 0.02631579
##  33,560,259 1 0.02631579
##  35,939,066 1 0.02631579
##   6,965,445 1 0.02631579
##   7,006,180 1 0.02631579
##   7,020,975 1 0.02631579
##   7,785,438 1 0.02631579
##   8,615,144 1 0.02631579
##   9,505,798 1 0.02631579
##   9,807,112 1 0.02631579

Mejorando

revenue

n

percent

10,215,165

1

2.6%

11,816,107

1

2.6%

12,481,634

1

2.6%

12,586,764

1

2.6%

12,619,390

1

2.6%

13,145,115

1

2.6%

13,404,072

1

2.6%

13,443,619

1

2.6%

14,333,266

1

2.6%

15,110,264

1

2.6%

15,669,918

1

2.6%

15,681,840

1

2.6%

15,731,680

1

2.6%

16,264,892

1

2.6%

16,451,006

1

2.6%

16,614,209

1

2.6%

16,994,406

1

2.6%

17,026,066

1

2.6%

19,052,023

1

2.6%

19,068,372

1

2.6%

22,750,080

1

2.6%

22,767,455

1

2.6%

24,808,479

1

2.6%

25,226,952

1

2.6%

26,780,298

1

2.6%

30,632,752

1

2.6%

32,101,943

1

2.6%

32,177,144

1

2.6%

33,020,905

1

2.6%

33,560,259

1

2.6%

35,939,066

1

2.6%

6,965,445

1

2.6%

7,006,180

1

2.6%

7,020,975

1

2.6%

7,785,438

1

2.6%

8,615,144

1

2.6%

9,505,798

1

2.6%

9,807,112

1

2.6%

revenue

n

percent

10,215,165

1

2.6%

11,816,107

1

2.6%

12,481,634

1

2.6%

12,586,764

1

2.6%

12,619,390

1

2.6%

13,145,115

1

2.6%

13,404,072

1

2.6%

13,443,619

1

2.6%

14,333,266

1

2.6%

15,110,264

1

2.6%

15,669,918

1

2.6%

15,681,840

1

2.6%

15,731,680

1

2.6%

16,264,892

1

2.6%

16,451,006

1

2.6%

16,614,209

1

2.6%

16,994,406

1

2.6%

17,026,066

1

2.6%

19,052,023

1

2.6%

19,068,372

1

2.6%

22,750,080

1

2.6%

22,767,455

1

2.6%

24,808,479

1

2.6%

25,226,952

1

2.6%

26,780,298

1

2.6%

30,632,752

1

2.6%

32,101,943

1

2.6%

32,177,144

1

2.6%

33,020,905

1

2.6%

33,560,259

1

2.6%

35,939,066

1

2.6%

6,965,445

1

2.6%

7,006,180

1

2.6%

7,020,975

1

2.6%

7,785,438

1

2.6%

8,615,144

1

2.6%

9,505,798

1

2.6%

9,807,112

1

2.6%

banner_days

n

percent

13

1

2.6%

14

1

2.6%

15

2

5.3%

18

2

5.3%

19

2

5.3%

20

2

5.3%

21

16

42.1%

22

10

26.3%

25

1

2.6%

43

1

2.6%

Total

38

100.0%

df %>% tabyl(rerun) %>%
  ggplot(aes(x=rerun,y=n,fill=rerun)) + 
  geom_col()

df %>% tabyl(rerun) %>%
  ggplot(aes(x=rerun,y=n,fill=rerun)) + 
  geom_col() +
  labs(x="Rerun", y="Frecuencia",title="Cantidad de personajes con rerun")

df %>% tabyl(rerun) %>%
  ggplot(aes(x=rerun,y=n,fill=rerun)) + 
  geom_col() +
  labs(x="Rerun", y="Frecuencia",title="Cantidad de personajes con rerun") +
  geom_text(aes(label=n),vjust=1.5,col="white",fontface="bold")

df %>% tabyl(rerun) %>%
  ggplot(aes(x=rerun,y=n,fill=rerun)) + 
  geom_col() +
  labs(x="Rerun", y="Frecuencia",title="Cantidad de personajes con rerun") +
  geom_text(aes(label= sprintf("%.2f%%",100*percent)  ),vjust=1.5,col="white",fontface="bold")

n=100000
numeros= rnorm(n=n,mean=20,sd=1)
df1=data.frame(numeros)
df1 %>% 
  ggplot(aes(x=numeros)) + geom_histogram(color=600,fill="lightblue") +
  labs(x="Numeros",y="Frecuencia",title = "Campana de gauss experimental")