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Feedback #1
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Ahí te hice comentarios en el código.
Además de los comentarios, en términos generales, falta mucho texto. Describir los datos: ¿qué columnas tiene? ¿Cuántos datos? Y sobre los resultados, tablas y gráficos, ¿qué motiva lo que mostrás y qué conclusiones sacás?
informe.Rmd
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```{r} | ||
library(dplyr) | ||
``` |
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No hace falta que cada library()
esté en un bloque separado. Poné todos en el primero (el que dice setup) arriba de este.
informe.Rmd
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## Introducción | ||
```{r} | ||
library(gitcreds) |
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Este paquete no hace falta cargarlo. No usás ninguna función en el código .
informe.Rmd
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```{r} | ||
library(usethis) |
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Este paquete tampoco hace falta cargarlo
informe.Rmd
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## Exploración de los datos | ||
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```{r} | ||
library(readr) |
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El paquete ya lo cargaste arriba, sólo hace falta cargarlo una sola vez.
informe.Rmd
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## Exploración de los datos | ||
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```{r} | ||
library(readr) | ||
captura_puerto_flota_2010_2018 <- read_csv("datos/captura-puerto-flota-2010-2018.csv") |
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Estos datos no están en el repositorio. Tienen que estar para que pueda correr esto.
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Acá también hay un posible probelma de codificación (habrás visto que las tildes se ven mal).
Esto es porque el archivo está con una codificación no estándar. Tenés que definir la codification así:
captura_puerto_flota_2010_2018 <- read_csv("datos/captura-puerto-flota-2010-2018.csv",
locale = locale(encoding = "windows-1252"))
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Gracias! me la pase investigando y no lo pude solucionar
informe.Rmd
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captura_puerto_flota_2010_2018 |> | ||
filter ( fecha %in% c("2010-04", "2010-05", "2010-06")) |> | ||
group_by(puerto) |
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Igual que en bloques anteriores, esto te devuelve el resultado del filtro pero no lo guarda en ningún lado y no es útil para verlo en un informe.
informe.Rmd
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aparece_especie <- captura_puerto_flota_2010_2018 %>% | ||
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filter(fecha=="2010-01") |> | ||
group_by(especie) |> | ||
tally() |
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Este resultado no lo estás mostrando en el informe.
Quizás contar por especie que queda demasiadas especies. Vi que hay una columna llamada especie_agrupada
que tiene menos categorías; quizás podés usar esa para analizar .
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ahora le asigno una variable a cada cosa y saco la media | ||
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```{r} | ||
captura_2010_01_Merluzahubbsi/captura_2010_01_todas |
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Esto no es bueno hacerlo porque en general no tiene sentido dividir una tabla por otra. En este caso en particular funciona porque es un caso muy particular. Está bien lo que hiciste más arriba:
mutate(proporcion = captura[especie = "Merluza hubbsi"]/captura)
informe.Rmd
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especies_repre |> | ||
ggplot(data = especies_repre, mapping = aes(x = fecha, y = captura)) + | ||
geom_line (aes(colour = especie)) |
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Este gráfico te sale mal porque la fecha es una columna de tipo texto. Si la pasás a fecha va a salir bien.
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especies_repre |> | ||
pivot_wider(names_from = especie, values_from = captura, values_fill = 0) |
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Esto está bien el código, pero me parece que el resultado no es muy útil porque, por lo que veo en los datos originales cada fila representa la captura de una especie. Entonces pivot_wider()
te deja ceros en todas las especies salvo una en cada fila.
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