# tidyhydat v0.5.0

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## Extract and Tidy Canadian 'Hydrometric' Data

Provides functions to access historical and real-time national 'hydrometric' data from Water Survey of Canada data sources (<http://dd.weather.gc.ca/hydrometric/csv/> and <http://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>) and then applies tidy data principles.

# tidyhydat

## Project Status

This package is maintained by the Data Science and Analytics Branch of the British Columbia Ministry of Citizens’ Services.

## What does tidyhydat do?

• Provides functions (hy_*) that access hydrometric data from the HYDAT database, a national archive of Canadian hydrometric data and return tidy data.
• Provides functions (realtime_*) that access Environment and Climate Change Canada’s real-time hydrometric data source.
• Provides functions (search_*) that can search through the approximately 7000 stations in the database and aid in generating station vectors
• Keep functions as simple as possible. For example, for daily flows, the hy_daily_flows() function queries the database, tidies the data and returns a tibble of daily flows.

## Installation

You can install tidyhydat from CRAN:

install.packages("tidyhydat")


To install the development version of the tidyhydat package, you need to install the remotes package then the tidyhydat package:

if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("ropensci/tidyhydat")


## Usage

A more thorough vignette can be found on the tidyhydat CRAN page.

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.

### Real-time

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 = "08LG006")
#>   Queried on: 2019-12-02 18:59:32 (UTC)
#>   Date range: 2019-11-02 to 2019-12-02
#> # A tibble: 17,482 x 8
#>    STATION_NUMBER PROV_TERR_STATE~ Date                Parameter Value Grade
#>    <chr>          <chr>            <dttm>              <chr>     <dbl> <chr>
#>  1 08LG006        BC               2019-11-02 08:00:00 Flow       13.6 <NA>
#>  2 08LG006        BC               2019-11-02 08:05:00 Flow       13.6 <NA>
#>  3 08LG006        BC               2019-11-02 08:10:00 Flow       13.6 <NA>
#>  4 08LG006        BC               2019-11-02 08:15:00 Flow       13.6 <NA>
#>  5 08LG006        BC               2019-11-02 08:20:00 Flow       13.6 <NA>
#>  6 08LG006        BC               2019-11-02 08:25:00 Flow       13.6 <NA>
#>  7 08LG006        BC               2019-11-02 08:30:00 Flow       13.6 <NA>
#>  8 08LG006        BC               2019-11-02 08:35:00 Flow       13.6 <NA>
#>  9 08LG006        BC               2019-11-02 08:40:00 Flow       13.6 <NA>
#> 10 08LG006        BC               2019-11-02 08:45:00 Flow       13.6 <NA>
#> # ... with 17,472 more rows, and 2 more variables: Symbol <chr>, Code <chr>


### Plotting

Plot methods are also provided to quickly visualize realtime data:

realtime_ex <- realtime_dd(station_number = "08LG006")

plot(realtime_ex)


and also historical data:

hy_ex <- hy_daily_flows(station_number = "08LA001", start_date = "2013-01-01")

plot(hy_ex)


## Getting Help or Reporting an Issue

To report bugs/issues/feature requests, please file an issue.

These are very welcome!

## How to Contribute

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.

## Citation

Get citation information for tidyhydat in R by running:

citation("tidyhydat")


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

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.