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tidyhydat
do?hy_*) that access hydrometric data
from the HYDAT database, a national archive of Canadian hydrometric data
and return tidy data.realtime_*) that access Environment
and Climate Change Canada’s real-time hydrometric data source.search_*) that can search through
the approximately 7000 stations in the database and aid in generating
station vectorshy_daily_flows() function queries the database,
tidies the data and returns a tibble of daily flows.You can install tidyhydat from CRAN:
install.packages("tidyhydat")To install the development version of the tidyhydat
package, you can install directly from the rOpenSci development
server:
install.packages("tidyhydat", repos = "https://dev.ropensci.org")More documentation on tidyhydat can found at the
rOpenSci doc page: https://docs.ropensci.org/tidyhydat/
When you install tidyhydat, several other packages will
be installed as well. One of those packages, dplyr, is
useful for data manipulations and is used regularly here. To use
actually use dplyr in a session you must explicitly load
it. A helpful dplyr tutorial can be found here.
library(tidyhydat)
library(dplyr)To use many of the functions in the tidyhydat package
you will need to download a version of the HYDAT database, Environment
and Climate Change Canada’s database of historical hydrometric data then
tell R where to find the database. Conveniently tidyhydat
does all this for you via:
download_hydat()This downloads (with your permission) the most recent version of
HYDAT and then saves it in a location on your computer where
tidyhydat’s function will look for it. Do be patient though
as this can take a long time! To see where HYDAT was saved you can run
hy_default_db(). Now that you have HYDAT downloaded and
ready to go, you are all set to begin looking at Canadian hydrometric
data.
To download real-time data using the datamart we can use
approximately the same conventions discussed above. Using
realtime_dd() we can easily select specific stations by
supplying a station of interest:
realtime_dd(station_number = "08MF005")
#> Queried on: 2024-10-04 21:22:54.830085 (UTC)
#> Date range: 2024-09-04 to 2024-10-04
#> # A tibble: 17,574 × 8
#> STATION_NUMBER PROV_TERR_STATE_LOC Date Parameter Value Grade Symbol Code
#> <chr> <chr> <dttm> <chr> <dbl> <chr> <chr> <chr>
#> 1 08MF005 BC 2024-09-04 08:00:00 Flow 1830 <NA> <NA> 1
#> 2 08MF005 BC 2024-09-04 08:05:00 Flow 1830 <NA> <NA> 1
#> 3 08MF005 BC 2024-09-04 08:10:00 Flow 1830 <NA> <NA> 1
#> 4 08MF005 BC 2024-09-04 08:15:00 Flow 1840 <NA> <NA> 1
#> 5 08MF005 BC 2024-09-04 08:20:00 Flow 1840 <NA> <NA> 1
#> 6 08MF005 BC 2024-09-04 08:25:00 Flow 1830 <NA> <NA> 1
#> 7 08MF005 BC 2024-09-04 08:30:00 Flow 1830 <NA> <NA> 1
#> 8 08MF005 BC 2024-09-04 08:35:00 Flow 1830 <NA> <NA> 1
#> 9 08MF005 BC 2024-09-04 08:40:00 Flow 1830 <NA> <NA> 1
#> 10 08MF005 BC 2024-09-04 08:45:00 Flow 1830 <NA> <NA> 1
#> # ℹ 17,564 more rowsOr we can use realtime_ws:
realtime_ws(
station_number = "08MF005",
parameters = c(46, 5), ## see param_id for a list of codes
start_date = Sys.Date() - 14,
end_date = Sys.Date()
)
#> All station successfully retrieved
#> All parameters successfully retrieved
#> # A tibble: 4,632 × 10
#> STATION_NUMBER Date Name_En Value Unit Grade Symbol Approval Parameter Code
#> <chr> <dttm> <chr> <dbl> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 08MF005 2024-09-20 00:00:00 Water temperature 17.0 °C -1 <NA> Provisional/Provisoire 5 TW
#> 2 08MF005 2024-09-20 01:00:00 Water temperature 17.0 °C -1 <NA> Provisional/Provisoire 5 TW
#> 3 08MF005 2024-09-20 02:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 4 08MF005 2024-09-20 03:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 5 08MF005 2024-09-20 04:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 6 08MF005 2024-09-20 05:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 7 08MF005 2024-09-20 06:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 8 08MF005 2024-09-20 07:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 9 08MF005 2024-09-20 08:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> 10 08MF005 2024-09-20 09:00:00 Water temperature 17.1 °C -1 <NA> Provisional/Provisoire 5 TW
#> # ℹ 4,622 more rowstidyhydat provides two methods to download realtime
data. realtime_dd() provides a function to import .csv
files from here.
realtime_ws() is an client for a web service hosted by
ECCC. realtime_ws() has several difference to
realtime_dd(). These include:
realtime_ws() is much faster for
larger queries (i.e. many stations). For single station queries to
realtime_dd() is more appropriate.realtime_ws() records goes
back further in time.realtime_dd() are
restricted to river flow (either flow and level) data. In contrast
realtime_ws() can download several different parameters
depending on what is available for that station. See
data("param_id") for a list and explanation of the
parameters.realtime_ws() provides
argument to select a date range. Selecting a data range with
realtime_dd() is not possible until after all files have
been downloaded.Plot methods are also provided to quickly visualize realtime data:
realtime_ex <- realtime_dd(station_number = "08MF005")
plot(realtime_ex)
and also historical data:
hy_ex <- hy_daily_flows(station_number = "08MF005", start_date = "2013-01-01")
plot(hy_ex)
To report bugs/issues/feature requests, please file an issue.
These are very welcome!
If you would like to contribute to the package, please see our CONTRIBUTING guidelines.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Get citation information for tidyhydat in R by
running:
To cite package 'tidyhydat' in publications use:
Albers S (2017). "tidyhydat: Extract and Tidy Canadian Hydrometric Data." _The Journal of Open Source Software_, *2*(20). doi:10.21105/joss.00511 <https://doi.org/10.21105/joss.00511>,
<http://dx.doi.org/10.21105/joss.00511>.
A BibTeX entry for LaTeX users is
@Article{,
title = {tidyhydat: Extract and Tidy Canadian Hydrometric Data},
author = {Sam Albers},
doi = {10.21105/joss.00511},
url = {http://dx.doi.org/10.21105/joss.00511},
year = {2017},
publisher = {The Open Journal},
volume = {2},
number = {20},
journal = {The Journal of Open Source Software},
}
Copyright 2017 Province of British Columbia
Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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