Clima

options(repos = list(CRAN="http://cran.rstudio.com/"))
install.packages("dplyr")

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install.packages('riem')

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library(riem)
install.packages('tidyverse')

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library(tidyverse)

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install.packages('lubridate')

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library(lubridate)
install.packages('ggplot2')

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library(ggplot2)
install.packages('plotly')

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library(plotly)

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# Paso 2 Buscar la red (país).
view(riem_networks())

# Paso 3 Buscar la estación (ciudad) y copiar ID
view(riem_stations('MX__ASOS'))

#Paso 4 Obtener informacion
monterrey<- riem_measures("MMMY")

# Paso 5 Agregar Temperatura en grados centigrados
monterrey$tmpc<- (monterrey$tmpf -32)/1.8

# Paso 6 Filtrar informacion - Ejemplo Enero a Marzo 2023
este_año <- subset(monterrey, valid >= as.POSIXct('2023-01-01 00:00') & valid <= as.POSIXct('2023-03-10 07:00'))

# Paso 7 Graficar temperatura en 2023
plot(este_año$valid,este_año$tmpc)

# Paso 8 Promediar información por día
este_año <- este_año %>%
  mutate(date=ymd_hms(valid), date = as.Date(date)) %>%
  group_by(date) %>%
  summarize_if(is.numeric, ~mean(.,na.rm = TRUE))

# Paso 9 Graficar la temperatura en 2023
plot(este_año$date,este_año$tmpc, type="l", main="Temperatura promedio en monterrey", xlab="Fecha", ylab="´Centigrados")