README.md
In rywhale/kiwisR: A Wrapper for Querying KISTERS 'WISKI' Databases via the 'KiWIS' API
kiwisR 
Overview
A wrapper for querying KISTERS WISKI
databases via the KiWIS
API.
Users can toggle between various databases by specifying the hub
argument. Currently, the default hubs are:
- kisters : KISTERS KiWIS Example
Server
- swmc : Ontario Surface Water Monitoring
Centre
- quinte : Quinte Conservation
Authority
All data is returned as tidy
tibbles.
Installation
You can install kiwisR from CRAN:
install.packages('kiwisR')
To install the development version of kiwisR you first need to install
devtools.
if(!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github('rywhale/kiwisR')
Then load the package with
library(kiwisR)
Usage
Get Station Information
By default, ki_station_list() returns a tibble containing information
for all available stations for the selected hub.
# With swmc as the hub
ki_station_list(hub = 'swmc')
#> # A tibble: 3,802 × 5
#> station_name station_no station_id station_latitude station_longitude
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 A SNOW TEMPLATE SNOW-WLF-… 952125 NA NA
#> 2 AA SNOW TEMPLATE SNOW-WLF-… 954599 NA NA
#> 3 ABERDEEN CLIM-MSC-… 121939 45.5 -98.4
#> 4 ABITIBI CANYON ZZSNOW-OP… 148200 49.9 -81.6
#> 5 ABITIBI LAKE CLIM-MNR-… 121135 48.7 -80.1
#> 6 ABITIBI RIVER AT AB… HYDAT-04M… 136328 49.9 -81.6
#> 7 ABITIBI RIVER AT IR… HYDAT-04M… 136304 48.8 -80.7
#> 8 ABITIBI RIVER AT IS… HYDAT-04M… 136324 49.6 -81.4
#> 9 Abitibi River at On… WSC-04ME0… 146775 50.6 -81.4
#> 10 ABITIBI RIVER AT OT… HYDAT-04M… 136332 50.2 -81.6
#> # ℹ 3,792 more rows
Get Time Series Information
You can use the station_id column returned using ki_station_list()
to figure out which time series are available for a given station.
One Station
# Single station_id
available_ts <- ki_timeseries_list(
hub = 'swmc',
station_id = "144659"
)
available_ts
#> # A tibble: 226 × 6
#> station_name station_id ts_id ts_name from to
#> <chr> <chr> <chr> <chr> <dttm> <dttm>
#> 1 Jackson Cre… 144659 1143… 3Month… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 2 Jackson Cre… 144659 1143… 18Mont… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 3 Jackson Cre… 144659 1143… MonthT… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 4 Jackson Cre… 144659 9490… LVL.15… 2005-12-26 05:00:00 2023-07-18 10:00:00
#> 5 Jackson Cre… 144659 9490… LVL.Da… 2005-12-26 05:00:00 2023-07-17 05:00:00
#> 6 Jackson Cre… 144659 9490… LVL.Ye… 2005-01-01 05:00:00 2023-01-01 05:00:00
#> 7 Jackson Cre… 144659 1243… WWP.St… 1985-01-01 05:00:00 2025-01-01 05:00:00
#> 8 Jackson Cre… 144659 1166… Water … 2018-04-23 05:00:00 2023-07-17 05:00:00
#> 9 Jackson Cre… 144659 1184… SoilCo… 2019-01-16 05:00:00 2023-07-17 05:00:00
#> 10 Jackson Cre… 144659 1184… SoilCo… 2019-01-16 14:00:00 2023-07-18 10:00:00
#> # ℹ 216 more rows
Multiple Stations
If you provide a vector to station_id, the returned tibble will have
all the available time series from all stations. They can be
differentiated using the station_name column.
# Vector of station_ids
my_station_ids <- c("144659", "144342")
available_ts <- ki_timeseries_list(
hub = 'swmc',
station_id = my_station_ids
)
available_ts
#> # A tibble: 336 × 6
#> station_name station_id ts_id ts_name from to
#> <chr> <chr> <chr> <chr> <dttm> <dttm>
#> 1 Oshawa Cree… 144342 1143… Precip… 2001-01-01 05:00:00 2023-07-19 05:00:00
#> 2 Oshawa Cree… 144342 1331… Precip… NA NA
#> 3 Oshawa Cree… 144342 9455… Precip… 1990-08-01 05:00:00 2023-07-01 05:00:00
#> 4 Oshawa Cree… 144342 9455… Precip… 1990-01-01 05:00:00 2023-01-01 05:00:00
#> 5 Oshawa Cree… 144342 1143… Precip… 1990-08-01 05:00:00 2023-08-01 05:00:00
#> 6 Oshawa Cree… 144342 9455… Precip… 1990-08-01 05:00:00 2023-07-17 05:00:00
#> 7 Oshawa Cree… 144342 1140… Precip… 2005-01-01 06:00:00 2023-07-18 12:00:00
#> 8 Oshawa Cree… 144342 9455… Precip… 1990-08-01 10:00:00 2023-07-18 10:00:00
#> 9 Oshawa Cree… 144342 1143… Precip… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 10 Oshawa Cree… 144342 1143… Precip… 2000-01-01 05:00:00 2000-12-01 05:00:00
#> # ℹ 326 more rows
Get Time Series Values
You can now use the ts_id column in the tibble produced by
ki_timeseries_list() to query values for chosen time series.
By default this will return values for the past 24 hours. You can
specify the dates you’re interested in by setting start_date and
end_date. These should be set as date strings with the format
‘YYYY-mm-dd’.
You can pass either a single or multiple ts_id(s).
One Time Series
# Past 24 hours
my_values <- ki_timeseries_values(
hub = 'swmc',
ts_id = '966435042'
)
#> No start or end date provided, trying to return data for past 24 hours
my_values
#> # A tibble: 429 × 7
#> Timestamp Value ts_name ts_id Units station_name station_id
#> <dttm> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 2023-07-17 00:00:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 2 2023-07-17 00:05:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 3 2023-07-17 00:10:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 4 2023-07-17 00:15:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 5 2023-07-17 00:20:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 6 2023-07-17 00:25:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 7 2023-07-17 00:30:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 8 2023-07-17 00:35:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 9 2023-07-17 00:40:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 10 2023-07-17 00:45:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> # ℹ 419 more rows
Multiple Time Series
# Specified date, multiple time series
my_ts_ids <- c("1125831042","908195042")
my_values <- ki_timeseries_values(
hub = 'swmc',
ts_id = my_ts_ids,
start_date = "2015-08-28",
end_date = "2018-09-13"
)
my_values
#> # A tibble: 1,264 × 7
#> Timestamp Value ts_name ts_id Units station_name station_id
#> <dttm> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 2015-09-06 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 2 2015-09-17 05:00:00 0.18 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 3 2015-09-26 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 4 2015-09-27 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 5 2015-09-28 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 6 2015-10-03 05:00:00 0.21 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 7 2015-10-08 05:00:00 0.22 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 8 2015-10-12 05:00:00 0.24 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 9 2015-10-24 05:00:00 0.41 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 10 2015-11-11 05:00:00 0.42 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> # ℹ 1,254 more rows
Using Other Hubs
You can use this package for a KiWIS hub not included in this list by
feeding the location of the API service to the hub argument.
For instance: If your URL looks like
specify the hub argument with
http://kiwis.kisters.de/KiWIS/KiWIS?
If you’d like to have a hub added to the defaults, please Submit an
Issue
Contributing
See
here
if you’d like to contribute.
rywhale/kiwisR documentation built on July 20, 2023, 12:37 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
kiwisR
Overview
A wrapper for querying KISTERS WISKI
databases via the KiWIS
API.
Users can toggle between various databases by specifying the hub
argument. Currently, the default hubs are:
- kisters : KISTERS KiWIS Example Server
- swmc : Ontario Surface Water Monitoring Centre
- quinte : Quinte Conservation Authority
All data is returned as tidy tibbles.
Installation
You can install kiwisR from CRAN:
install.packages('kiwisR')
To install the development version of kiwisR you first need to install
devtools.
if(!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github('rywhale/kiwisR')
Then load the package with
library(kiwisR)
Usage
Get Station Information
By default, ki_station_list() returns a tibble containing information
for all available stations for the selected hub.
# With swmc as the hub
ki_station_list(hub = 'swmc')
#> # A tibble: 3,802 × 5
#> station_name station_no station_id station_latitude station_longitude
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 A SNOW TEMPLATE SNOW-WLF-… 952125 NA NA
#> 2 AA SNOW TEMPLATE SNOW-WLF-… 954599 NA NA
#> 3 ABERDEEN CLIM-MSC-… 121939 45.5 -98.4
#> 4 ABITIBI CANYON ZZSNOW-OP… 148200 49.9 -81.6
#> 5 ABITIBI LAKE CLIM-MNR-… 121135 48.7 -80.1
#> 6 ABITIBI RIVER AT AB… HYDAT-04M… 136328 49.9 -81.6
#> 7 ABITIBI RIVER AT IR… HYDAT-04M… 136304 48.8 -80.7
#> 8 ABITIBI RIVER AT IS… HYDAT-04M… 136324 49.6 -81.4
#> 9 Abitibi River at On… WSC-04ME0… 146775 50.6 -81.4
#> 10 ABITIBI RIVER AT OT… HYDAT-04M… 136332 50.2 -81.6
#> # ℹ 3,792 more rows
Get Time Series Information
You can use the station_id column returned using ki_station_list()
to figure out which time series are available for a given station.
One Station
# Single station_id
available_ts <- ki_timeseries_list(
hub = 'swmc',
station_id = "144659"
)
available_ts
#> # A tibble: 226 × 6
#> station_name station_id ts_id ts_name from to
#> <chr> <chr> <chr> <chr> <dttm> <dttm>
#> 1 Jackson Cre… 144659 1143… 3Month… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 2 Jackson Cre… 144659 1143… 18Mont… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 3 Jackson Cre… 144659 1143… MonthT… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 4 Jackson Cre… 144659 9490… LVL.15… 2005-12-26 05:00:00 2023-07-18 10:00:00
#> 5 Jackson Cre… 144659 9490… LVL.Da… 2005-12-26 05:00:00 2023-07-17 05:00:00
#> 6 Jackson Cre… 144659 9490… LVL.Ye… 2005-01-01 05:00:00 2023-01-01 05:00:00
#> 7 Jackson Cre… 144659 1243… WWP.St… 1985-01-01 05:00:00 2025-01-01 05:00:00
#> 8 Jackson Cre… 144659 1166… Water … 2018-04-23 05:00:00 2023-07-17 05:00:00
#> 9 Jackson Cre… 144659 1184… SoilCo… 2019-01-16 05:00:00 2023-07-17 05:00:00
#> 10 Jackson Cre… 144659 1184… SoilCo… 2019-01-16 14:00:00 2023-07-18 10:00:00
#> # ℹ 216 more rows
Multiple Stations
If you provide a vector to station_id, the returned tibble will have
all the available time series from all stations. They can be
differentiated using the station_name column.
# Vector of station_ids
my_station_ids <- c("144659", "144342")
available_ts <- ki_timeseries_list(
hub = 'swmc',
station_id = my_station_ids
)
available_ts
#> # A tibble: 336 × 6
#> station_name station_id ts_id ts_name from to
#> <chr> <chr> <chr> <chr> <dttm> <dttm>
#> 1 Oshawa Cree… 144342 1143… Precip… 2001-01-01 05:00:00 2023-07-19 05:00:00
#> 2 Oshawa Cree… 144342 1331… Precip… NA NA
#> 3 Oshawa Cree… 144342 9455… Precip… 1990-08-01 05:00:00 2023-07-01 05:00:00
#> 4 Oshawa Cree… 144342 9455… Precip… 1990-01-01 05:00:00 2023-01-01 05:00:00
#> 5 Oshawa Cree… 144342 1143… Precip… 1990-08-01 05:00:00 2023-08-01 05:00:00
#> 6 Oshawa Cree… 144342 9455… Precip… 1990-08-01 05:00:00 2023-07-17 05:00:00
#> 7 Oshawa Cree… 144342 1140… Precip… 2005-01-01 06:00:00 2023-07-18 12:00:00
#> 8 Oshawa Cree… 144342 9455… Precip… 1990-08-01 10:00:00 2023-07-18 10:00:00
#> 9 Oshawa Cree… 144342 1143… Precip… 2000-02-01 05:00:00 2035-01-01 05:00:00
#> 10 Oshawa Cree… 144342 1143… Precip… 2000-01-01 05:00:00 2000-12-01 05:00:00
#> # ℹ 326 more rows
Get Time Series Values
You can now use the ts_id column in the tibble produced by
ki_timeseries_list() to query values for chosen time series.
By default this will return values for the past 24 hours. You can
specify the dates you’re interested in by setting start_date and
end_date. These should be set as date strings with the format
‘YYYY-mm-dd’.
You can pass either a single or multiple ts_id(s).
One Time Series
# Past 24 hours
my_values <- ki_timeseries_values(
hub = 'swmc',
ts_id = '966435042'
)
#> No start or end date provided, trying to return data for past 24 hours
my_values
#> # A tibble: 429 × 7
#> Timestamp Value ts_name ts_id Units station_name station_id
#> <dttm> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 2023-07-17 00:00:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 2 2023-07-17 00:05:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 3 2023-07-17 00:10:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 4 2023-07-17 00:15:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 5 2023-07-17 00:20:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 6 2023-07-17 00:25:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 7 2023-07-17 00:30:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 8 2023-07-17 00:35:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 9 2023-07-17 00:40:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> 10 2023-07-17 00:45:00 23.0 LVL.1.O 966435042 m Attawapiskat Ri… 146273
#> # ℹ 419 more rows
Multiple Time Series
# Specified date, multiple time series
my_ts_ids <- c("1125831042","908195042")
my_values <- ki_timeseries_values(
hub = 'swmc',
ts_id = my_ts_ids,
start_date = "2015-08-28",
end_date = "2018-09-13"
)
my_values
#> # A tibble: 1,264 × 7
#> Timestamp Value ts_name ts_id Units station_name station_id
#> <dttm> <dbl> <chr> <chr> <chr> <chr> <chr>
#> 1 2015-09-06 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 2 2015-09-17 05:00:00 0.18 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 3 2015-09-26 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 4 2015-09-27 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 5 2015-09-28 05:00:00 0.19 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 6 2015-10-03 05:00:00 0.21 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 7 2015-10-08 05:00:00 0.22 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 8 2015-10-12 05:00:00 0.24 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 9 2015-10-24 05:00:00 0.41 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> 10 2015-11-11 05:00:00 0.42 Q.DayBaseflow 112583… cumec Chippewa Cr… 140764
#> # ℹ 1,254 more rows
Using Other Hubs
You can use this package for a KiWIS hub not included in this list by
feeding the location of the API service to the hub argument.
For instance: If your URL looks like
specify the hub argument with
http://kiwis.kisters.de/KiWIS/KiWIS?
If you’d like to have a hub added to the defaults, please Submit an Issue
Contributing
See here if you’d like to contribute.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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