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library(ggplot2)
# csvs <- list.files(path = "/media/m/MAU DIAZ/Análisis videos/Control", pattern = ".csv", full.names = TRUE)
# 
# 
# out <- lapply(csvs, function(x) {
# 
#   print(x)  
#   dat <- read.table(x, row.names = NULL, header = TRUE, sep = ";")
# 
#   dat$Time <- gsub(",", ".", dat$Time)
#   dat$Time <- as.numeric(dat$Time)
#   dat$file <- basename(x)
#   
#   return(dat)
#   })
# 
# 
# control <- do.call(rbind, out)
# 
# 
## tratamiento

# csvs <- list.files(path = "/media/m/MAU DIAZ/Análisis videos/Tratamiento/", pattern = ".csv", full.names = TRUE)
# 
# 
# out <- lapply(csvs, function(x) {
#   
#   print(x)  
#   dat <- read.table(x, row.names = NULL, header = TRUE, sep = ";")
#   
#   dat$Time <- gsub(",", ".", dat$Time)
#   dat$Time <- as.numeric(dat$Time)
#   dat$file <- basename(x)
#   
#   return(dat)
# })
# 
# 
# tratamiento <- do.call(rbind, out)
# 
# 
# 
# tratamiento$grupo <- "tratamiento"
# control$grupo <- "control"
# 
# datos <- rbind(tratamiento, control)
# names(datos)[1:2] <- c("cuentas","conducta")
# 
# datos$conducta <- gsub("Desplazamiento", "refugio", datos$conducta)
# datos$conducta <- gsub("Rearing", "nado_abierto", datos$conducta)
# datos$conducta <- gsub("Resting", "nado_periferia", datos$conducta)
# datos$conducta <- gsub("Reading", "nado_abierto", datos$conducta)
# datos$grupo <- gsub("tratamiento", "beta estradiol", datos$grupo)
# 
# agg_dat <- aggregate(cuentas ~ conducta + grupo, data = datos, sum)
# 
# agg_dat$tiempo <- agg_dat$cuentas * 0.1
# 
# agg_dat$log_tiempo <- log(agg_dat$tiempo)

agg_dat <- read.csv("~/Downloads/datanueva.csv")

agg_tab <- aggregate(cuentas ~ conducta + grupo, agg_dat, sum)

agg_tab2 <- as.table(rbind(agg_tab$cuentas[1:3], agg_tab$cuentas[4:6]))

chisq.test(agg_tab2)

    Pearson's Chi-squared test

data:  agg_tab2
X-squared = 256.18, df = 2, p-value < 2.2e-16

ggplot(data = agg_tab, aes(x = conducta, y = cuentas,
                          fill = grupo)) + geom_bar(stat = "identity",
                                                            position = position_dodge(0.9))  +
labs(x = "Conducta", y = "Frecuencia", fill = "Tratamiento") +
  scale_fill_viridis_d(begin = 0.2, end = 0.8, alpha = 0.6) +
  theme_classic(base_size = 25)