Not much.. Just a single function package that wraps the NordPool Spot API.
The package is just a pet project and in early beta. Changes can happen and I'm also very open for suggestions. The project was inspired by the Python library.
Check out how it works below...
# This won't work
# DST ends
np_prices("hourly", "EUR", as.Date("2016-10-30"))
# DST starts
np_prices("hourly", "EUR", as.Date("2017-03-26"))Install the package using Hadley's devtools package.
devtools::install_github("krose/nordpoolspotr")Here are a few examples of how to use the function. All date values are returned with the timezone CET (as they are from the API).
# Load the package.
library(nordpoolspotr)
# Get the prices for tommorow (if they are published).
np_prices("hourly", "EUR")## # A tibble: 24 × 19
## StartTime EndTime Bergen DK1 DK2 EE FI
## * <dttm> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2017-04-19 00:00:00 2017-04-19 01:00:00 30.35 30.35 30.35 30.35 30.35
## 2 2017-04-19 01:00:00 2017-04-19 02:00:00 30.02 30.02 30.02 30.02 30.02
## 3 2017-04-19 02:00:00 2017-04-19 03:00:00 29.94 29.94 29.94 29.94 29.94
## 4 2017-04-19 03:00:00 2017-04-19 04:00:00 30.25 30.25 30.25 30.25 30.25
## 5 2017-04-19 04:00:00 2017-04-19 05:00:00 30.83 30.83 30.83 30.83 30.83
## 6 2017-04-19 05:00:00 2017-04-19 06:00:00 31.80 31.81 31.81 31.81 31.81
## 7 2017-04-19 06:00:00 2017-04-19 07:00:00 34.61 38.90 38.90 38.90 38.90
## 8 2017-04-19 07:00:00 2017-04-19 08:00:00 45.38 46.88 46.88 46.88 46.88
## 9 2017-04-19 08:00:00 2017-04-19 09:00:00 48.38 48.38 48.38 48.38 48.38
## 10 2017-04-19 09:00:00 2017-04-19 10:00:00 43.67 43.67 43.67 43.67 43.67
## # ... with 14 more rows, and 12 more variables: Kr.sand <dbl>, LT <dbl>,
## # LV <dbl>, Molde <dbl>, Oslo <dbl>, SE1 <dbl>, SE2 <dbl>, SE3 <dbl>,
## # SE4 <dbl>, SYS <dbl>, Tr.heim <dbl>, Tromsø <dbl># Get the prices for today
np_prices("hourly", "EUR", Sys.Date())## # A tibble: 24 × 19
## StartTime EndTime Bergen DK1 DK2 EE FI
## * <dttm> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2017-04-18 00:00:00 2017-04-18 01:00:00 29.05 29.05 29.05 29.05 29.05
## 2 2017-04-18 01:00:00 2017-04-18 02:00:00 28.36 28.36 28.36 28.36 28.36
## 3 2017-04-18 02:00:00 2017-04-18 03:00:00 27.77 27.77 27.77 27.77 27.77
## 4 2017-04-18 03:00:00 2017-04-18 04:00:00 27.62 27.26 27.26 27.26 27.26
## 5 2017-04-18 04:00:00 2017-04-18 05:00:00 27.94 26.97 27.94 27.94 27.94
## 6 2017-04-18 05:00:00 2017-04-18 06:00:00 29.94 30.91 29.94 29.94 29.94
## 7 2017-04-18 06:00:00 2017-04-18 07:00:00 33.01 33.01 33.01 39.92 39.92
## 8 2017-04-18 07:00:00 2017-04-18 08:00:00 38.17 42.31 42.31 42.31 42.31
## 9 2017-04-18 08:00:00 2017-04-18 09:00:00 45.39 45.39 45.39 45.39 45.39
## 10 2017-04-18 09:00:00 2017-04-18 10:00:00 41.05 41.05 41.05 41.05 41.05
## # ... with 14 more rows, and 12 more variables: Kr.sand <dbl>, LT <dbl>,
## # LV <dbl>, Molde <dbl>, Oslo <dbl>, SE1 <dbl>, SE2 <dbl>, SE3 <dbl>,
## # SE4 <dbl>, SYS <dbl>, Tr.heim <dbl>, Tromsø <dbl># Get a long data frame
np_prices("hourly", "EUR", long_data = TRUE)## # A tibble: 408 × 4
## StartTime EndTime Areas Value
## <dttm> <dttm> <chr> <dbl>
## 1 2017-04-19 2017-04-19 01:00:00 SYS 29.32
## 2 2017-04-19 2017-04-19 01:00:00 SE1 30.35
## 3 2017-04-19 2017-04-19 01:00:00 SE2 30.35
## 4 2017-04-19 2017-04-19 01:00:00 SE3 30.35
## 5 2017-04-19 2017-04-19 01:00:00 SE4 30.35
## 6 2017-04-19 2017-04-19 01:00:00 FI 30.35
## 7 2017-04-19 2017-04-19 01:00:00 DK1 30.35
## 8 2017-04-19 2017-04-19 01:00:00 DK2 30.35
## 9 2017-04-19 2017-04-19 01:00:00 Oslo 30.35
## 10 2017-04-19 2017-04-19 01:00:00 Kr.sand 30.35
## # ... with 398 more rows# Get only the Danish prices in DKK
np_prices(time_unit = "hourly", currency = "DKK", areas = c("DK1", "DK2"))## Warning in eval(substitute(expr), envir, enclos): NAs introduced by
## coercion
## Warning in eval(substitute(expr), envir, enclos): NAs introduced by
## coercion
## Warning in eval(substitute(expr), envir, enclos): NAs introduced by
## coercion
## # A tibble: 24 × 4
## StartTime EndTime DK1 DK2
## * <dttm> <dttm> <dbl> <dbl>
## 1 2017-04-19 00:00:00 2017-04-19 01:00:00 225.75 225.75
## 2 2017-04-19 01:00:00 2017-04-19 02:00:00 223.30 223.30
## 3 2017-04-19 02:00:00 2017-04-19 03:00:00 222.70 222.70
## 4 2017-04-19 03:00:00 2017-04-19 04:00:00 225.01 225.01
## 5 2017-04-19 04:00:00 2017-04-19 05:00:00 229.32 229.32
## 6 2017-04-19 05:00:00 2017-04-19 06:00:00 236.61 236.61
## 7 2017-04-19 06:00:00 2017-04-19 07:00:00 289.35 289.35
## 8 2017-04-19 07:00:00 2017-04-19 08:00:00 348.71 348.71
## 9 2017-04-19 08:00:00 2017-04-19 09:00:00 359.86 359.86
## 10 2017-04-19 09:00:00 2017-04-19 10:00:00 324.83 324.83
## # ... with 14 more rows