fix_COL_WRLD_electricity | R Documentation |
The 2022 release of the IEA's WEEB data is different from the 2021 release of the IEA's WEEB data in terms of Colombia's Electricity generation. For example:
2021 release:
Main activity producer electricity plants 34196.4008 TJ
Autoproducer electricity plants: 2671.1993 TJ
2022 release:
Main activity producer electricity plants 31467.5994 TJ
Autoproducer electricity plants: 899.9987 TJ Similar differences appear in all years 1971 - 1977. From 1978 onward, the 2021 and 2022 releases agree. Note that this change leads to overall energy imbalance for Colombia 1971-1977 and World 1971-1977. This function reverts to the values from the 2021 release of the IEA WEEB.
fix_COL_WRLD_electricity(
.tidy_iea_df,
country = IEATools::iea_cols$country,
year = IEATools::iea_cols$year,
e_dot = IEATools::iea_cols$e_dot
)
.tidy_iea_df |
A tidy IEA data frame produced by |
country , year , e_dot |
See |
Similarly, World Electricity is different 2021 release to 2022 release. The 2022 data are unbalanced for 1971 –> 1977. This function reverts to the value from the 2021 release of the IEA WEEB for World Electricity in 1971–1977.
.tidy_iea_df
with improved Ghana Industry Electricity, if warranted.
library(dplyr)
example_tidy_iea_df <- load_tidy_iea_df() %>%
dplyr::filter(Country == "GHA") |>
dplyr::mutate(
# Pretend that GHA is COL.
Country = "COL"
)
example_tidy_iea_df
fixed <- example_tidy_iea_df %>%
fix_COL_WRLD_electricity()
# Compare changed values
example_tidy_iea_df %>%
dplyr::filter(Flow %in% c("Main activity producer electricity plants",
"Autoproducer electricity plants"),
Product == "Electricity") %>%
dplyr::select("Year", "Flow", "Edot", "Unit")
fixed %>%
dplyr::filter(Flow %in% c("Main activity producer electricity plants",
"Autoproducer electricity plants"),
Product == "Electricity") %>%
dplyr::select("Year", "Flow", "Edot", "Unit")
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