National Eutrophication Survey Data Package

# install stable version from CRAN
install.packages("nesRdata")

# install development version from Github
# install devtools if not found - install.packages("devtools")
# devtools::install_github("jsta/nesRdata", update_dependencies = TRUE)

library(nesRdata)

data(nes)
head(nes)
#>   pdf pagenum storet_code     state           name         county lake_type
#> 1 474     100        2709 MINNESOTA      BIG STONE BIG STONE (MN)   NATURAL
#> 2 474     101        2710 MINNESOTA     BIRCH LAKE           CASS   NATURAL
#> 3 474     102        2711 MINNESOTA BLACKDUCK LAKE       BELTRAMI   NATURAL
#> 4 474     103        2712 MINNESOTA BLACKHOOF LAKE      CROW WING   NATURAL
#> 5 474     104        2713 MINNESOTA   BUFFALO LAKE         WRIGHT   NATURAL
#> 6 474     105        2714 MINNESOTA  CARRIGAN LAKE         WRIGHT   NATURAL
#>   drainage_area surface_area mean_depth total_inflow retention_time
#> 1       3004.40        51.03        3.4          3.3            1.7
#> 2            NA         5.19        3.0           NA             NA
#> 3         75.11        11.10        4.5          0.4            4.2
#> 4         20.72         0.74        4.4          0.1          257.0
#> 5        113.96         6.11        4.4          0.6            1.4
#> 6            NA         0.66         NA           NA             NA
#>   retention_time_units alkalinity conductivity secchi    tp   po4   tin tn
#> 1                years        131          800    1.0 0.159 0.126 0.335 NA
#> 2                years        106          210    2.4 0.019 0.009 0.090 NA
#> 3                years        128          243    1.7 0.038 0.019 0.195 NA
#> 4                 days        103          230    1.6 0.043 0.024 0.185 NA
#> 5                years        167          395    1.0 0.209 0.160 0.795 NA
#> 6                years        185          590    0.3 1.215 0.785 0.290 NA
#>   p_pnt_source_muni p_pnt_source_industrial p_pnt_source_septic p_nonpnt_source
#> 1              7696                      23                 213            8014
#> 2                NA                      NA                  NA              NA
#> 3               676                      NA                  NA             916
#> 4               639                      NA                   9             254
#> 5              4821                      NA                  23            1129
#> 6                NA                      NA                  NA              NA
#>   p_total n_pnt_source_muni n_pnt_source_industrial n_pnt_source_septic
#> 1   15946             22599                      NA                8036
#> 2      NA                NA                      NA                  NA
#> 3    1592              2023                      NA                  NA
#> 4     902              1914                      NA                 268
#> 5    5973             10086                      NA                 853
#> 6      NA                NA                      NA                  NA
#>   n_nonpnt_source n_total p_total_out p_percent_retention
#> 1          188812  219447       15846                   1
#> 2              NA      NA          NA                  NA
#> 3           27329   29351         717                  55
#> 4            6522    8703         141                  84
#> 5           18000   28939        3950                  34
#> 6              NA      NA          NA                  NA
#>   p_surface_area_loading n_total_out n_percent_retention n_surface_area_loading
#> 1                   0.31      214068                   2                    4.3
#> 2                     NA          NA                  NA                     NA
#> 3                   0.14       16091                  45                    2.6
#> 4                   1.22        5075                  42                   11.8
#> 5                   0.98       51429                  NA                    4.7
#> 6                     NA          NA                  NA                     NA
#>        lat      long  chl
#> 1 45.30833 -96.45667 16.5
#> 2 46.93333 -94.52500  6.2
#> 3 47.73889 -94.62917 14.5
#> 4 46.47167 -94.01056 12.8
#> 5 45.17083 -93.88000 38.0
#> 6 45.05833 -93.95833 84.3

nes_get(version_id = "5", dest_folder = cache_path())

nes_versions()

dt <- nes_load(version_id = "5", folder = cache_path())
names(dt)
lapply(dt, head)