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Feedback #1
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Feedback #1
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Te hice comentarios. El código está bien así que son más que nada sobre la interpretación de los resultados.
informe.Rmd
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IP <- gsub(".*? ([[:digit:]])", "\\1", system("ipconfig", intern=T)[grep("IPv4", system("ipconfig", intern = T))]) | ||
if (IP == "10.2.29.7") { | ||
Sys.setenv("https_proxy"="proxy.jus.gov.ar:8080/") | ||
Sys.setenv("http_proxy"="proxy.jus.gov.ar:8080/") | ||
options(internet.info = 0) #valor 0 o 1 para ver la comunicación con internet | ||
} |
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Y esto? Si es algo específico de la configuración de tu computadora, quizás no debería estar en el código que voy a correr yo u otres colaboradores.
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Es específico de la pc laboral, pero le puse como condición que verifique que sea mi IP interna laboral que es fija, entonces en otros equipos no debería ejecutarse. No encontré todavía como dejar la variable de entorno del proxy guardada en un .ini para que la ejecute al iniciar rstudio. Probé guardando en file.edit('~/.Renviron') pero no funcionó.
informe.Rmd
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library(DescTools) | ||
library(tidyr) | ||
library(datos) # por si las dudas |
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Estos paquetes no se usan en el código así que podés no cargarlos.
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Sí, gracias, olvidé limpiar el código.
informe.Rmd
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```{r echo=FALSE} | ||
summarise(vinos, puntos_min = min(puntos, na.rm = TRUE), puntos_max = max(puntos, na.rm = TRUE)) | ||
``` |
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¿Qué interpretás de esto?
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Todavía me faltan algunos conceptos de estadística. Solo se me ocurrió, en base al máximo, mínimo y promedio, que los precios altos tienen mucha dispersión, porque se alejan mucho de la media.
informe.Rmd
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``` | ||
También llamó la atención la cantidad de variedades de vinos, ``r variedades``. |
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Por qué?
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Simplemente pensé que eran demasiadas variedades, por lo que supuse que había algunas escritas de diferente forma, pero las listé y ordené alfabéticamente y al parecer no.
informe.Rmd
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p <- vinos |> | ||
filter(precio < 250) |> | ||
ggplot( aes(x=precio, fill=precio)) + | ||
geom_histogram(binwidth=3, show.legend = FALSE, fill=rainbow(83)) |
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Ojo acá que estás hardcodeando el número de barras cuando ponés rainbow(83)
. Lo que en realidad querés hacer acá es mapear el fill al precio del vino y usar una escala de arcoíris.
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Lo que pasa es que intuitivamente entendí que para que el gráfico mostrara información relevante había que desestimar los valores muy altos, entonces con criterio "a ojo" lo acoté a 250. Pero al usar el fill arcoiris me tomaba el rango entero (hasta 3300) y en definitiva quedaba todo en rojo. No encontré otra forma, y las funciones de graficación no terminan de quedarme claras.
informe.Rmd
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prop_no_encontrados <- round(colSums(is.na(vinos))/nrow(vinos),4)*100 | ||
show(prop_no_encontrados) | ||
``` | ||
Podemos encontrar bastantes valores faltantes, pero únicamente en las columnas de nombre (``r prop_no_encontrados[2]``%), region_1 (``r prop_no_encontrados[6]``%) y region_2 (``r prop_no_encontrados[6]``%). |
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Qué interpretás de esto?
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Las columnas región 1 y región 2 contienen información adicional, por lo que es esperable que en muchos casos tengan valores nulos, pero no encontré una explicación para que falten tantos en la columna nombre. Podría haberlo considerado como anomalía.
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