2019_Cavidades de acceso_Investigacion

Los packages

library("RCurl")

Loading required package: bitops

library("tidyverse")

Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
package 'dplyr' was built under R version 3.4.2Conflicts with tidy packages ------------------------------------------------------------------------
complete(): tidyr, RCurl
filter():   dplyr, stats
lag():      dplyr, stats

library("ggthemes")
library("forcats")

Abro el df de la pag.web, creo objeto df

df <- read.csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vTGWDxQJDcety8tsxTvGQmk8Ul5I4nvpFRLz83DoIeX8h1tEN_Qgk21dvjtwx02xtfBNG8L0n6dlobT/pub?gid=119354125&single=true&output=csv")

Agrupo

df1<- df %>% 
gather(key = "Extensiones", value = "Apreciacion", Extension.V.L:Extension.M.D)

combierto a objeto

df2 <- df1 %>% 
  group_by(Diente,Extensiones,Apreciacion) %>% 
  summarise(suma = n())   

Graficas

df2 %>% 
  ggplot(aes(x=Diente, y=suma, fill=Apreciacion)) +
 geom_boxplot()

diferencias entre dientes ???

aov1 <- aov(df2$suma~df2$Diente)
summary(aov1)

            Df Sum Sq Mean Sq F value   Pr(>F)    
df2$Diente   3  525.8   175.3   13.69 4.39e-05 ***
Residuals   20  256.0    12.8                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

donde ???

TukeyHSD(aov1)

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = df2$suma ~ df2$Diente)

$`df2$Diente`
                       diff        lwr       upr     p adj
incisivo-canino   -2.000000  -7.781458  3.781458 0.7686835
molar-canino      10.333333   4.551876 16.114791 0.0003684
premolar-canino    2.666667  -3.114791  8.448124 0.5789300
molar-incisivo    12.333333   6.551876 18.114791 0.0000427
premolar-incisivo  4.666667  -1.114791 10.448124 0.1416446
premolar-molar    -7.666667 -13.448124 -1.885209 0.0069391

Agrupo para analizar todas las variables

df3 <- df %>% 
gather(key = "total", value = "Apreciacion", Diseno:Cervical)

combierto a objeto

df4 <- df3 %>% 
  group_by(Diente,total,Apreciacion) %>% 
  summarise(suma = n())   

grafico

df4 %>% 
  ggplot(aes(x=total, y=suma, fill=Apreciacion)) +
 geom_boxplot()

diferencias ??

aov2 <- aov(df4$suma~df4$total)
summary(aov2)#NO EXISTEN 

            Df Sum Sq Mean Sq F value Pr(>F)
df4$total    4      0    0.00       0      1
Residuals   55   2175   39.54               

sumo

df1 %>% 
  group_by(Diente, Nfresas,Apreciacion) %>% 
  summarise(suma = n()) 

que pasa con las fresas ??

df5 <- df1 %>% 
  group_by(Diente, Nfresas,Apreciacion) %>% 
  summarise(suma = n())   

grafico

df5 %>% 
  ggplot(aes(x = Diente, y = suma, fill=Apreciacion)) +
  facet_wrap(~Nfresas) +
  geom_col()+
  theme_classic()

df5 %>% 
  ggplot(aes(x = Nfresas, y = suma, color=Apreciacion, group=Apreciacion)) +
  facet_wrap(~Diente) +
  geom_line()+
  theme_classic()

ejemplo para renombrar

df1 %>% 
rename(xxx = Diente)