Administrative area and weather

Source: vignettes/v04_weather.Rmd 
data <- get_lis_geo(rubrik_nr = 3) # weather
colnames(data)
#>  [1] "KENNZIFFER" "EINHEIT"    "2000"       "2001"       "2002"      
#>  [6] "2003"       "2004"       "2005"       "2006"       "2007"      
#> [11] "2008"       "2009"       "2010"       "2011"       "2012"      
#> [16] "2013"       "2014"       "2015"       "2016"       "2017"      
#> [21] "2018"       "2019"       "2020"       "2021"       "2022"      
#> [26] "2023"
data$KENNZIFFER
#>  [1] "Lufttemperatur (Jahresmittel)"                                
#>  [2] "Abweichung der Lufttemperatur vom Normalwert (8,8<U+00B0>C)"  
#>  [3] "Jahresh<U+00F6>chsttemperatur"                                
#>  [4] "Jahrestiefsttemperatur"                                       
#>  [5] "30<U+00B0>C und w<U+00E4>rmer (hei<U+00DF>e Tage)"            
#>  [6] "25<U+00B0>C und w<U+00E4>rmer (warme Tage)"                   
#>  [7] "unter 0<U+00B0>C (Eistage)"                                   
#>  [8] "unter 0<U+00B0>C (Frosttage)"                                 
#>  [9] "Sonnenscheindauer (Jahressumme)"                              
#> [10] "Abweichung der Sonnenscheindauer vom Normalwert (1 494 h)"    
#> [11] "Tage mit mindestens einer Stunde Sonnenschein"                
#> [12] "Niederschlagsh<U+00F6>he (Jahressumme)"                       
#> [13] "Abweichung der Niederschlagsh<U+00F6>he vom Normalwert (511 mm)"
#> [14] "Maximale Tagesh<U+00F6>he der Niederschl<U+00E4>ge"           
#> [15] "Tage im Jahr mit Niederschlagsh<U+00F6>he von mindestens 0,1 mm"
#> [16] "Tage im Jahr mit Niederschlagsh<U+00F6>he von mindestens 10 mm"
#> [17] "Jahresmittel der relativen Luftfeuchte"                       
#> [18] "Maximale Windspitze"
data.sub <- data %>%
  filter(str_detect(KENNZIFFER, "^Lufttemperatur") |
    str_detect(KENNZIFFER, "^Niederschlagsh")) %>%
  mutate(KENNZIFFER = case_when(
    str_detect(KENNZIFFER, "^Lufttemperatur") ~ "Temperature in <U+00B0>C (yearly mean)",
    str_detect(KENNZIFFER, "^Niederschlagsh") ~ "Rain in l (yearly sum)",
    TRUE ~ as.character(NA)
  ))
data.sub <- data.sub %>%
  pivot_longer(
    cols = matches("\\d{4}"),
    names_to = "Year",
    values_to = "Value"
  ) %>%
  mutate(Year = as.numeric(Year))
ggplot(data.sub, aes(
  x = Year,
  y = Value
)) +
  geom_step() +
  geom_point(colour = "red3") +
  scale_x_continuous(breaks = seq(2000, 2024, 2)) +
  geom_smooth(method = "loess") +
  tidyquant::theme_tq() +
  theme(legend.position = "bottom") +
  facet_wrap(. ~ KENNZIFFER, nrow = 2, scales = "free") +
  labs(
    x = NULL,
    y = NULL,
    title = "Temperature and rain in Leipzig",
    subtitle = "2000 to 2023",
    caption = "Source: Leipzig Informationssystem, 2024"
  )