Team RGB, Energy Consumption Trends

Proposal

library(tidyverse)

Dataset

energy <- read_csv("data/owid-energy.csv")
us_china <- energy |>
  filter(country %in% c("United States", "China", "World"))
world_oil <- energy |>
  filter(country == "World", year > 1990) |> select(country, year, contains("share_energy"))
world_oil_regions <- energy |>
  filter(country %in% c("Africa", "Asia", "North America", "South America", "Central America (BP)", "Middle East (BP)", "Europe"), year > 1990) |> select(country, year, oil_share_energy)

We are using the TidyTuesday dataset from 06/06/2023. The data was sourced from Our World In Data, and tracks energy consumption by type (e.g. fossil fuels, solar) for most nations in the world going back to 1900. The full dataset contains 21890 rows and 129 columns, but we will only be analyzing the relationships between the US, China, and global averages. Our subset contains 366 rows and 129 columns.

With US-China relations (especially on climate) being so often discussed in the media right now, we chose this dataset to see if we could add some value to the conversation and cut through some of the political noise to arrive at objective analysis without a political lens.

Questions

  1. How has the proportion of energy being produced by the US and China shifted over time? What about in the years since China has become a world power (1949 Chinese Communist Revolution under Mao)?

  2. How has energy consumption changed since 1995 (when the first UN COP meeting on climate occurred) in the US, China, and globally? Which has made more progress away from harmful energy production since climate change became a global talking point?

Analysis plan

Question 1: How has the proportion of energy being produced by the US and China shifted over time? What about in the years since China has become a world power (1949 Chinese Communist Revolution under Mao)?

Plan: We will animate a bar graph to show temporal changes in energy production since 1900 and since 1949. Bars will be stacked, and fill color will differentiate energy type, while the x-axis contains energy production totals and the y-axis differentiates by country. Our second graph will be a scatter plot of proportions of renewable energy production / total energy production with a geom_path to show the flow of renewable energy production changes. The line will be colored differently for each of the US and China and change line types for before and after 1949.

Question 2: How has energy consumption changed since 1995 (when the first UN COP meeting on climate occurred) in the US, China, and globally? Which has made more progress away from harmful energy production since climate change became a global talking point?

Plan: Using the world_oil dataframe, our first graph would look at world oil consumption as a share of total world energy (utilizing oil_share_energy) for the last four decades (1981-2021) to investigate whether the world has shifted from oil. Prior to these decades, renewable energy was not widely available and was therefore not widely reported, so we will only subset the relevant decades for this analysis. We will use a world map geom to fill in countries with the most oil consumption as a gradient to those with the least oil consumption.

Additionally, we’ll compare the trends in oil by breaking the data into “before 1995” and “after 1995.” We will analyze the changes before and after the Chinese Communist Revolution. That way, if there is a decline post-1995 but also pre-1995, we could hypothesize that the UN pressures weren’t as impactful as a pure analysis of post-1995 would lead us to believe. The x-axis would be years, the y-axis oil consumption, and a line graph with the US before 1995, US after 1995, China before 1995, and China after 1995. Before 1995 would be a different line type than after and the US and China would have different colors.