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README.Rmd
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README.Rmd
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---
title: README
output: md_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# tidyhydat <img src="man/figures/logo.png" align="right" />
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## 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](https://tibble.tidyverse.org/) of daily flows.
## Installation
You can install `tidyhydat` from CRAN:
```{r, echo=TRUE, eval=FALSE}
install.packages("tidyhydat")
```
To install the development version of the `tidyhydat` package, you can install directly from the rOpenSci development server:
```{r, echo=TRUE, eval=FALSE}
install.packages("tidyhydat", repos = "https://dev.ropensci.org")
```
## Usage
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](https://cran.r-project.org/package=dplyr/vignettes/dplyr.html).
```{r, eval = TRUE, echo=TRUE, message=FALSE, warning=FALSE}
library(tidyhydat)
library(dplyr)
```
### HYDAT download
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:
```{r, eval=FALSE}
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:
```{r}
realtime_dd(station_number = "08MF005")
```
Or we can use `realtime_ws`:
```{r}
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()
)
```
## Compare realtime_ws and realtime_dd
`tidyhydat` provides two methods to download realtime data. `realtime_dd()` provides a function to import .csv files from [here](https://dd.weather.gc.ca/hydrometric/csv/).
`realtime_ws()` is an client for a web service hosted by ECCC. `realtime_ws()` has several difference to `realtime_dd()`. These include:
- *Speed*: The `realtime_ws()` is much faster for larger queries (i.e. many stations). For single station queries to `realtime_dd()` is more appropriate.
- *Length of record*: `realtime_ws()` records goes back further in time.
- *Type of parameters*: `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.
- *Date/Time filtering*: `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.
### Plotting
Plot methods are also provided to quickly visualize realtime data:
```{r}
realtime_ex <- realtime_dd(station_number = "08MF005")
plot(realtime_ex)
```
and also historical data:
```{r, fig.height=7, fig.width=12}
hy_ex <- hy_daily_flows(station_number = "08MF005", start_date = "2013-01-01")
plot(hy_ex)
```
## Getting Help or Reporting an Issue
To report bugs/issues/feature requests, please file an [issue](https://github.com/ropensci/tidyhydat/issues/).
These are very welcome!
## How to Contribute
If you would like to contribute to the package, please see our
[CONTRIBUTING](https://github.com/ropensci/tidyhydat/blob/master/CONTRIBUTING.md) guidelines.
Please note that this project is released with a [Contributor Code of Conduct](https://github.com/ropensci/tidyhydat/blob/master/CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.
## Citation
Get citation information for `tidyhydat` in R by running:
```{r, echo=FALSE, comment=""}
citation("tidyhydat")
```
[![ropensci_footer](https://ropensci.org/public_images/ropensci_footer.png)](https://ropensci.org)
## License
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.