Author: Jonathan Gilligan
Date: 2019-12-21

# Getting Started with the kayadata Package

#### Jonathan Gilligan

#### 2019-12-21

# kayadata

This package loads Kaya-identity data, synthesized from several sources.

To install and load the package, first install either the `pacman` or `devtools` package from CRAN:

    install.packages("devtools")
    devtools::install_github("jonathan-g/kayadata")
    library(kayadata)

or

    install.packages("pacman")
    library(pacman)
    p_load_gh("jonathan-g/kayadata")

Once you’ve installed it, then you just need to use the command `library(kayadata)` to load the package.

Some of the functions the package provides are:

- `kaya_region_list()`: Get a list of available countries and regions.
- `get_kaya_data()`: Get data for a specific country. Example:

    mexico_data = get_kaya_data("Mexico")
    mexico_data %>% filter(year >= 1965) %>%
      select(region:ef) %>%
      head()

    ## # A tibble: 6 × 10
    ##   region  year     P     G     E     F     g     e     f    ef
    ##   <ord>  <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
    ## 1 Mexico  2023 0.128  1.33  8.01  490. 10.3   6.04  61.1  369.
    ## 2 Mexico  2022 0.128  1.29  7.76  469. 10.1   6.04  60.5  365.
    ## 3 Mexico  2021 0.127  1.24  7.42  443.  9.76  6.01  59.6  358.
    ## 4 Mexico  2020 0.126  1.17  6.97  413.  9.28  5.96  59.3  354.
    ## 5 Mexico  2019 0.125  1.28  7.65  481. 10.2   5.98  62.8  376.
    ## 6 Mexico  2018 0.124  1.28  7.73  489. 10.3   6.03  63.3  381.

- `project_top_down()`: Project future population, GDP, energy use, and emissions. Example:

    mexico_2050 = project_top_down("Mexico", 2050)
    mexico_2050

    ## # A tibble: 1 × 10
    ##   region  year     P     G     g     E     F     e     f    ef
    ##   <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
    ## 1 Mexico  2050 0.154  2.51  16.3  10.9  609.  4.36  55.7  243.

- `plot_kaya`: Plot trends in Kaya variables for a given region or country. Example:

    us_kaya = get_kaya_data("United States")
    plot_kaya(us_kaya, "ef", y_lab = "Carbon intensity of economy",
              start_year = 2000, stop_year = 2010, log_scale = TRUE,
              trend_line = TRUE, font_size = 10)

    world_kaya = get_kaya_data("World")
    plot_kaya(world_kaya, "P", start_year = 2000, stop_year = 2010,
              log_scale = FALSE, trend_line = FALSE, font_size = 10)

* `get_fuel_mix`: Get the fuel mix (coal, gas, oil, nuclear, and renewables) for a region or country. Example:

    mexico_mix = get_fuel_mix("Mexico")
    mexico_mix

    ## # A tibble: 5 × 5
    ##   region  year fuel        quads   frac
    ##   <chr>  <int> <ord>       <dbl>  <dbl>
    ## 1 Mexico  2023 Oil         3.64  0.454
    ## 2 Mexico  2023 Natural Gas 3.33  0.416
    ## 3 Mexico  2023 Coal        0.250 0.0312
    ## 4 Mexico  2023 Nuclear     0.105 0.0131
    ## 5 Mexico  2023 Renewables  0.690 0.0861

- `plot_fuel_mix`: Plot the fuel mix in a donut chart

    plot_fuel_mix(mexico_mix, font_size = 10)

After you install the package, you can get more help inside RStudio by typing `help(package="kayadata")` in the R console window.