Functions to work with Wiski raingauge-data
name name_2 elev lat long easting northing par time_res_min start end
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl> <chr> <chr>
1 Melag Melago 1915 46.8 10.7 626323 5188431 N 5 1998-01-0… 2020-11-…
2 St.Valentin a… S.Valentino … 1499 46.8 10.5 616720 5181393 N 5 1981-01-1… 2020-11-…
3 Marienberg Monte Maria 1310 46.7 10.5 616288. 5173583. N 5 2009-07-2… 2020-11-…
4 Taufers Tubre 1235 46.6 10.5 611860 5165895 N 5 1989-05-1… 2020-11-…
5 Madritsch Madriccio 2825 46.5 10.6 623901 5150187. N 5 2008-11-2… 2020-11-…
6 Sulden Solda 1905 46.5 10.6 622375 5152632. N 5 1987-01-0… 2020-11-…
.csv
-files with the name of the station in each filenameAntholz_Obertal.txt
Auer.txt
Bozen.txt
Branzoll.txt
Brixen_Vahrn.txt
Bruneck.txt
Corvara_im_Gadertal.txt
Deutschnofen.txt
Eisack_Sterzing.txt
Eyrs_Laas.txt
Gantkofel.txt
Gargazon.txt
Grasstein.txt
Hintermartell.txt
...
# get the station naames of the files
station_names_files = read_rainfall(only.names = T)
station_names_xl = get_station_information()[["name"]]
This will return the same names as in the second column of the returned dataframe of station_names_files
read_rainfall
and specify the name of the station. It must only match more or less. If it does not match 100 % it will provide a suggestionstation = "bozn"
rain = read_rainfall(station=station)
# Did you meant: Bozen[Yy|Nn]
head(rain)
date hour precip n_measure
1 1981-01-03 01:00:00 NA 12
2 1981-01-03 02:00:00 NA 12
3 1981-01-03 03:00:00 NA 12
4 1981-01-03 04:00:00 NA 12
5 1981-01-03 05:00:00 NA 12
6 1981-01-03 06:00:00 NA 12
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