{ "cells": [ { "cell_type": "code", "execution_count": 3, "id": "5b1b7b3c", "metadata": { "tags": [ "remove_cell" ] }, "outputs": [], "source": [ "# Importing packages\n", "\n", "from datascience import *\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "from matplotlib import patches\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "id": "39a04df2", "metadata": {}, "source": [ "# Environmental Kuznets Curve Hypothesis\n", "\n", "The Environmental Kuznets curve hypothesis that the economic development of a nation is associated with a downward-facing U-shape. The Y-axis is in terms of the level of environmental degradation (e.g pollution, water quality, deforestation. The X-axis would be the GDP/capita. The idea is that the environmental degradation worsens, until a certain level of income, and after which it gets better. In the US this could be seen in terms of air or water quality, where the skies or rivers were very polluted in the 1960s, until the Clean Air Act and Clean Water Act were passed and Air Quality and Water Quality improved. Another motivation for the downward slope would be the idea that at some point a wealthier society demands environmental improvements. \n", "However - could this hold for the potentially most important Pollutant C02, the main driver of anthropogenic climate change. Controversially the impacts of global CO2 pollution are not experienced locally, but are experienced as global effects. So it is not clear whether the Environmental Kuznets hypothesis will hold. \n", "\n", "Today, we'll look to build an C02 Kuznets Curve (as below) for an *association* between the amount of CO2 emitted per capita (t/CO2) and the growing GDP per capita (USD). This dataset is collected from Our World in Data, a great source of all sorts of data types!\n", "\n" ] }, { "cell_type": "markdown", "id": "2c6d3432", "metadata": {}, "source": [ "" ] }, { "cell_type": "markdown", "id": "7252476e", "metadata": {}, "source": [ "## Building our own Environmental Kuznets Curve" ] }, { "cell_type": "markdown", "id": "fd3a8747", "metadata": {}, "source": [ "\n", "We start by importing data on GDP per capita and Per Capita CO2 emissions for every country in the world for as long as it has been recorded." ] }, { "cell_type": "code", "execution_count": 4, "id": "c721e753", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Country | Year | Per capita CO2 emissions | GDP per capita | Continent | \n", "
---|---|---|---|---|
Abkhazia | 2015 | nan | nan | Asia | \n", "
Afghanistan | 1949 | 0.00191237 | nan | nan | \n", "
Afghanistan | 1950 | 0.010871 | 1156 | nan | \n", "
Afghanistan | 1951 | 0.0116837 | 1170 | nan | \n", "
Afghanistan | 1952 | 0.0115423 | 1189 | nan | \n", "
Afghanistan | 1953 | 0.0132159 | 1240 | nan | \n", "
Afghanistan | 1954 | 0.0130359 | 1245 | nan | \n", "
Afghanistan | 1955 | 0.0186057 | 1246 | nan | \n", "
Afghanistan | 1956 | 0.0218121 | 1278 | nan | \n", "
Afghanistan | 1957 | 0.0343433 | 1253 | nan | \n", "
... (53427 rows omitted)
" ], "text/plain": [ "Country | Year | Per capita CO2 emissions | GDP per capita | Continent\n", "Abkhazia | 2015 | nan | nan | Asia\n", "Afghanistan | 1949 | 0.00191237 | nan | nan\n", "Afghanistan | 1950 | 0.010871 | 1156 | nan\n", "Afghanistan | 1951 | 0.0116837 | 1170 | nan\n", "Afghanistan | 1952 | 0.0115423 | 1189 | nan\n", "Afghanistan | 1953 | 0.0132159 | 1240 | nan\n", "Afghanistan | 1954 | 0.0130359 | 1245 | nan\n", "Afghanistan | 1955 | 0.0186057 | 1246 | nan\n", "Afghanistan | 1956 | 0.0218121 | 1278 | nan\n", "Afghanistan | 1957 | 0.0343433 | 1253 | nan\n", "... (53427 rows omitted)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "co2_table = Table.read_table('co2-emissions-vs-gdp.csv').drop('145446-annotations','Total population (Gapminder, HYDE & UN)','Code')\n", "co2_table = co2_table.relabeled('Entity', 'Country')\n", "co2_table" ] }, { "cell_type": "markdown", "id": "9599f38a", "metadata": {}, "source": [ "### Low Income Countries \n", "Let's start by selecting a set of Low Income Countries to graph a scatter plot on the movement of CO2 intensity per capita based on GDP per capita." ] }, { "cell_type": "code", "execution_count": 5, "id": "03dd93b1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "