packages <- c("tidyverse", "srvyr", "broom","gt", "modelsummary",
"gapminder", "fst", "ggridges", "readxl", "readr")
new_packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new_packages)) install.packages(new_packages)
lapply(packages, library, character.only = TRUE)
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GHG_emissions <- read_excel("co2_data.xlsx")
glimpse(GHG_emissions)
## Rows: 50,191
## Columns: 79
## $ country <chr> "Afghanistan", "Afghanistan"…
## $ year <dbl> 1750, 1751, 1752, 1753, 1754…
## $ iso_code <chr> "AFG", "AFG", "AFG", "AFG", …
## $ population <dbl> 2802560, NA, NA, NA, NA, NA,…
## $ gdp <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cement_co2 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ cement_co2_per_capita <dbl> 0, NA, NA, NA, NA, NA, NA, N…
## $ co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_growth_abs <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_growth_prct <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc_growth_abs <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc_growth_prct <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc_per_gdp <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_including_luc_per_unit_energy <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_per_gdp <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ co2_per_unit_energy <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ coal_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ coal_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ consumption_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ consumption_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ consumption_co2_per_gdp <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_cement_co2 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ cumulative_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_co2_including_luc <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_coal_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_flaring_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_gas_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_luc_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_oil_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ cumulative_other_co2 <lgl> NA, NA, NA, NA, NA, NA, NA, …
## $ energy_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ energy_per_gdp <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ flaring_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ flaring_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ gas_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ gas_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ ghg_excluding_lucf_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ ghg_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ land_use_change_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ land_use_change_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ methane <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ methane_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ nitrous_oxide <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ nitrous_oxide_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ oil_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ oil_co2_per_capita <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ other_co2_per_capita <lgl> NA, NA, NA, NA, NA, NA, NA, …
## $ other_industry_co2 <lgl> NA, NA, NA, NA, NA, NA, NA, …
## $ primary_energy_consumption <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cement_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_co2_including_luc <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_coal_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_cement_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_co2_including_luc <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_coal_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_flaring_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_gas_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_luc_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_oil_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_cumulative_other_co2 <lgl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_flaring_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_gas_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_luc_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_oil_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_global_other_co2 <lgl> NA, NA, NA, NA, NA, NA, NA, …
## $ share_of_temperature_change_from_ghg <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ temperature_change_from_ch4 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ temperature_change_from_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ temperature_change_from_ghg <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ temperature_change_from_n2o <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ total_ghg <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ total_ghg_excluding_lucf <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ trade_co2 <dbl> NA, NA, NA, NA, NA, NA, NA, …
## $ trade_co2_share <dbl> NA, NA, NA, NA, NA, NA, NA, …
year_range <- range(GHG_emissions$year)
print(year_range)
## [1] 1750 2023
co2consumption_by_countries <- GHG_emissions %>%
filter(year >= 1980 & year <= 2023) %>%
filter(!is.na(consumption_co2))%>%
filter(country %in% c("Canada", "Brazil", "Germany")) %>%
select(year, country, consumption_co2) %>%
group_by(country) %>%
arrange(desc(consumption_co2))
print(co2consumption_by_countries)
## # A tibble: 99 × 3
## # Groups: country [3]
## year country consumption_co2
## <dbl> <chr> <dbl>
## 1 1992 Germany 1207.
## 2 1990 Germany 1195.
## 3 1993 Germany 1160.
## 4 1991 Germany 1144.
## 5 1995 Germany 1140.
## 6 1994 Germany 1135.
## 7 1996 Germany 1124.
## 8 1999 Germany 1090.
## 9 2000 Germany 1084.
## 10 2001 Germany 1081.
## # ℹ 89 more rows
ggplot(
co2consumption_by_countries,
aes(x = year, y = consumption_co2,
color = country, fill = country)
) +
geom_line(linewidth = 1.5) +
scale_color_brewer(palette = "Set1") +
theme_minimal() +
theme(
panel.grid = element_blank(),
plot.title = element_text(face = "bold", size = 14),
plot.subtitle = element_text(size = 12),
legend.position = "bottom",
legend.title = element_text(face = "bold", size = 12)
) +
labs(
title = "Consumption-based CO2 emissions",
subtitle = "in Selected Countries",
x = "Year",
y = "CO2 consumption (measured in million tonnes)",
color = "Country",
fill = "Country"
)
co2consumption_by_countries_pc <- GHG_emissions %>%
filter(year >= 1980 & year <= 2023) %>%
filter(!is.na(consumption_co2_per_capita))%>%
filter(country %in% c("Canada", "Brazil", "Germany")) %>%
select(year, country, consumption_co2_per_capita) %>%
group_by(country) %>%
arrange(desc(consumption_co2_per_capita))
print(co2consumption_by_countries_pc)
## # A tibble: 99 × 3
## # Groups: country [3]
## year country consumption_co2_per_capita
## <dbl> <chr> <dbl>
## 1 2000 Canada 18.8
## 2 2005 Canada 18.7
## 3 2002 Canada 18.5
## 4 2004 Canada 18.2
## 5 2003 Canada 18.1
## 6 2007 Canada 18.1
## 7 2001 Canada 17.9
## 8 1997 Canada 17.9
## 9 1998 Canada 17.8
## 10 2010 Canada 17.7
## # ℹ 89 more rows
ggplot(
co2consumption_by_countries_pc,
aes(x = year, y = consumption_co2_per_capita,
color = country, fill = country)
) +
geom_line(linewidth = 1.5) +
scale_color_brewer(palette = "Set1") +
theme_minimal() +
theme(
panel.grid = element_blank(),
plot.title = element_text(face = "bold", size = 14),
plot.subtitle = element_text(size = 12),
legend.position = "bottom",
legend.title = element_text(face = "bold", size = 12)
) +
labs(
title = "Consumption-based CO2 emissions Per Capita",
subtitle = "in Selected Countries",
x = "Year",
y = "CO2 consumption (measured in million tonnes)",
color = "Country",
fill = "Country"
)
