Last updated: 2021-05-12

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File Version Author Date Message
Rmd de8ce5a Darius Görgen 2021-04-05 add content
html de8ce5a Darius Görgen 2021-04-05 add content

1 Loading the data

files = list.files("../data/vector/extraction/", pattern = "_SPEI", full.names = T)

data = lapply(files, function(x){
  filename = str_split(basename(x), "_")[[1]]
  if(length(filename) == 3){
    unit = filename[1]
    buffer = as.numeric(filename[2])
    var = str_remove(filename[3], ".gpkg")
  } else {
    unit = filename[1]
    buffer = 0
    var =  str_remove(filename[2], ".gpkg")
  }
  
  layers = ogrListLayers(x)
  layers = layers[grep("attr_", layers)]
  data = do.call(cbind, lapply(layers, function(l){
    tmp = st_read(x, layer = l, quiet = TRUE)
    lnames = c("SPI1", "SPI3", "SPI6", "SPI12")
    names(tmp) = paste(l, lnames, sep = "-")
    tmp
  }))
  
  data$id = 1:nrow(data)
  data %>%
    as_tibble () %>%
    gather("tmp", "value", -id) %>%
    separate(tmp, into = c("time","SPI"), sep = "-SPI") %>%
    mutate(SPI = as.factor(SPI), 
           time = str_remove(time, "attr_"),
           unit = unit, buffer = buffer, var = var)
})

data = do.call(rbind, data)
str(data)
tibble [7,142,400 × 7] (S3: tbl_df/tbl/data.frame)
 $ id    : int [1:7142400] 1 2 3 4 5 6 7 8 9 10 ...
 $ time  : chr [1:7142400] "2000-02" "2000-02" "2000-02" "2000-02" ...
 $ SPI   : Factor w/ 4 levels "1","12","3","6": 1 1 1 1 1 1 1 1 1 1 ...
 $ value : num [1:7142400] 0.32 0.584 0.771 0.343 0.285 ...
 $ unit  : chr [1:7142400] "basins" "basins" "basins" "basins" ...
 $ buffer: num [1:7142400] 100 100 100 100 100 100 100 100 100 100 ...
 $ var   : chr [1:7142400] "SPEI" "SPEI" "SPEI" "SPEI" ...

2 Missing values

data %>%
  group_by(unit, buffer) %>%
  summarise(N = n(), isna = sum(is.na(value)), isnotna = sum(!is.na(value)), perc = sum(is.na(value)) / n() * 100)
# A tibble: 8 x 6
# Groups:   unit [2]
  unit   buffer      N  isna isnotna  perc
  <chr>   <dbl>  <int> <int>   <int> <dbl>
1 basins      0 972480 23604  948876  2.43
2 basins     50 972480 18280  954200  1.88
3 basins    100 972480 18234  954246  1.88
4 basins    200 972480 18234  954246  1.88
5 states      0 813120 19053  794067  2.34
6 states     50 813120 15246  797874  1.88
7 states    100 813120 15246  797874  1.88
8 states    200 813120 15246  797874  1.88

3 Time Series

data %>%
  filter(buffer==0, unit == "states") %>%
  mutate(time = as.Date(paste0(time, "-01"))) %>%
  group_by(time, unit, SPI) %>%
  summarise(value = median(value, na.rm = T)) %>%
  mutate(sign = if_else(value>0, "pos", "neg"),
         cap = paste0("Scale of ", SPI, " months"),
         scale = as.numeric(as.character(SPI))) %>%
  mutate(cap = fct_reorder(cap, scale, min)) %>%
  ggplot(aes(x=time, y=value, fill = sign)) +
  geom_bar(stat = "identity", show.legend = FALSE) + 
  #scale_x_date(date_breaks = "year", date_labels = "%Y") +
  #scale_y_continuous(breaks = seq(-2, 2, 1)) +
  scale_fill_manual(values = c("#99000d", "#034e7b")) +
  labs(y = "SPI", x = "") +
  theme_classic() +
  facet_wrap(~cap, nrow = 4)

Version Author Date
de8ce5a Darius Görgen 2021-04-05 
data %>%
  filter(buffer==0, unit == "basins") %>%
  mutate(time = as.Date(paste0(time, "-01"))) %>%
  group_by(time, unit, SPI) %>%
  summarise(value = median(value, na.rm = T)) %>%
  mutate(sign = if_else(value>0, "pos", "neg"),
         cap = paste0("Scale of ", SPI, " months"),
         scale = as.numeric(as.character(SPI))) %>%
  mutate(cap = fct_reorder(cap, scale, min)) %>%
  ggplot(aes(x=time, y=value, fill = sign)) +
  geom_bar(stat = "identity", show.legend = FALSE) + 
  #scale_x_date(date_breaks = "year", date_labels = "%Y") +
  #scale_y_continuous(breaks = seq(-2, 2, 1)) +
  scale_fill_manual(values = c("#99000d", "#034e7b")) +
  labs(y = "SPI", x = "") +
  theme_classic() +
  facet_wrap(~cap, nrow = 4)

Version Author Date
de8ce5a Darius Görgen 2021-04-05 

sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 10 (buster)

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.5.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=C             
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] lubridate_1.7.9.2  rgdal_1.5-18       countrycode_1.2.0  welchADF_0.3.2    
 [5] rstatix_0.6.0      ggpubr_0.4.0       scales_1.1.1       RColorBrewer_1.1-2
 [9] latex2exp_0.4.0    cubelyr_1.0.0      gridExtra_2.3      ggtext_0.1.1      
[13] magrittr_2.0.1     tmap_3.2           sf_0.9-7           raster_3.4-5      
[17] sp_1.4-4           forcats_0.5.0      stringr_1.4.0      purrr_0.3.4       
[21] readr_1.4.0        tidyr_1.1.2        tibble_3.0.6       tidyverse_1.3.0   
[25] huwiwidown_0.0.1   kableExtra_1.3.1   knitr_1.31         rmarkdown_2.7.3   
[29] bookdown_0.21      ggplot2_3.3.3      dplyr_1.0.2        devtools_2.3.2    
[33] usethis_2.0.0     

loaded via a namespace (and not attached):
  [1] readxl_1.3.1       backports_1.2.0    workflowr_1.6.2   
  [4] lwgeom_0.2-5       splines_3.6.3      crosstalk_1.1.0.1 
  [7] leaflet_2.0.3      digest_0.6.27      htmltools_0.5.1.1 
 [10] fansi_0.4.2        memoise_1.1.0      openxlsx_4.2.3    
 [13] remotes_2.2.0      modelr_0.1.8       prettyunits_1.1.1 
 [16] colorspace_2.0-0   rvest_0.3.6        haven_2.3.1       
 [19] xfun_0.21          leafem_0.1.3       callr_3.5.1       
 [22] crayon_1.4.0       jsonlite_1.7.2     lme4_1.1-26       
 [25] glue_1.4.2         stars_0.4-3        gtable_0.3.0      
 [28] webshot_0.5.2      car_3.0-10         pkgbuild_1.2.0    
 [31] abind_1.4-5        DBI_1.1.0          Rcpp_1.0.5        
 [34] viridisLite_0.3.0  gridtext_0.1.4     units_0.6-7       
 [37] foreign_0.8-71     htmlwidgets_1.5.3  httr_1.4.2        
 [40] ellipsis_0.3.1     farver_2.0.3       pkgconfig_2.0.3   
 [43] XML_3.99-0.3       dbplyr_2.0.0       utf8_1.1.4        
 [46] labeling_0.4.2     tidyselect_1.1.0   rlang_0.4.10      
 [49] later_1.1.0.1      tmaptools_3.1      munsell_0.5.0     
 [52] cellranger_1.1.0   tools_3.6.3        cli_2.3.0         
 [55] generics_0.1.0     broom_0.7.2        evaluate_0.14     
 [58] yaml_2.2.1         processx_3.4.5     leafsync_0.1.0    
 [61] fs_1.5.0           zip_2.1.1          nlme_3.1-150      
 [64] whisker_0.4        xml2_1.3.2         compiler_3.6.3    
 [67] rstudioapi_0.13    curl_4.3           png_0.1-7         
 [70] e1071_1.7-4        testthat_3.0.1     ggsignif_0.6.0    
 [73] reprex_0.3.0       statmod_1.4.35     stringi_1.5.3     
 [76] highr_0.8          ps_1.5.0           desc_1.2.0        
 [79] lattice_0.20-41    Matrix_1.2-18      nloptr_1.2.2.2    
 [82] classInt_0.4-3     vctrs_0.3.6        pillar_1.4.7      
 [85] lifecycle_0.2.0    data.table_1.13.2  httpuv_1.5.5      
 [88] R6_2.5.0           promises_1.1.1     KernSmooth_2.23-18
 [91] rio_0.5.16         sessioninfo_1.1.1  codetools_0.2-16  
 [94] dichromat_2.0-0    boot_1.3-25        MASS_7.3-53       
 [97] assertthat_0.2.1   pkgload_1.1.0      rprojroot_2.0.2   
[100] withr_2.4.1        parallel_3.6.3     hms_1.0.0         
[103] grid_3.6.3         minqa_1.2.4        class_7.3-17      
[106] carData_3.0-4      git2r_0.27.1       base64enc_0.1-3