README.md

In krose/nordpoolspotr: An R Wrapper for the NordPool Spot API.

Introduction

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...

Known Issues

• The function doesn't work when DST start or end.

# 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"))

Installation

Install the package using Hadley's devtools package.

devtools::install_github("krose/nordpoolspotr")

Examples

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

krose/nordpoolspotr documentation built on Dec. 11, 2021, 8:09 p.m.