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+Import libraries¶
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+In [25]:
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+import pandas as pd
+import matplotlib.pyplot as plt
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+User input¶
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+In [26]:
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+year_born = 1987
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+Get the data¶
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+In [27]:
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+# The code below fetches the data from the "Our World in Data" Github page.
+# This is the data behind this graph/table: https://ourworldindata.org/grapher/cumulative-co-emissions
+# If the url does not work you can also use the data provided, by uncommenting the line below.
+df = pd.read_csv('./data/owid-co2-data.csv', header =0)
+# df = pd.read_csv('https://nyc3.digitaloceanspaces.com/owid-public/data/co2/owid-co2-data.csv', header=0)
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+Process the data¶
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+In [28]:
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+# Select only data for World
+df = df[df['country'] == 'World']
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+# Select year and Cumulative CO2
+df = df[['year','cumulative_co2']]
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+# Turn year to integer
+df['year'] = df['year'].astype(int)
+
+# Subtract from every cumulative value what has been emitted until 1750
+df['cumulative_co2']=df['cumulative_co2']-df['cumulative_co2'].iloc[0]
+
+# For every row:
+# 1. Calculate difference between "cumulative CO2 in year i" and "cumulative CO2 in last year"
+# 2. Divide this difference with "cumulative CO2 in last year"
+
+sums = []
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+for i in range(len(df)):
+ share_gen = (df['cumulative_co2'].iloc[-1]-df['cumulative_co2'].iloc[i])/df['cumulative_co2'].iloc[-1]*100
+ sums.append(share_gen)
+
+# Add the new column of sums to the original DataFrame
+df['share_gen'] = sums
+
+# Select every fifth row
+df = df.iloc[::5]
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+# Select data for people who were born in the last 100 years
+scope = int(100/5)
+df = df.tail(scope).reset_index(drop=True)
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+Plotting¶
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+In [29]:
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+# Create a horizontal barplot of year against cumulative_co2
+ax = df.plot.barh(x='year', y='share_gen', color = 'silver', width=0.8, linestyle = "")
+
+# Add rasters to the plot
+ax.grid(axis='x', linestyle='-', alpha=0.5, color = 'white', zorder=1)
+ax.grid(axis='y', linestyle='-', alpha=0.5, color = 'white', zorder=1)
+
+# Add names to axes
+ax.set_ylabel('year of birth')
+ax.set_xlabel('percentage')
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+# Add title
+ax.set_title('Percentage of global CO2 emissions since 1750\n occurring in your lifetime (last updated: %s)' % df['year'].iloc[-1])
+
+# Turn off the legend
+ax.legend().set_visible(False)
+
+# Turn on raster
+ax.set_xticks(range(0, 101, 10));
+
+# Round the year born to intervals of 5
+year_born_round = int(5 * round(float(year_born)/5))
+
+# Find index in df of year born
+year_born_index = df[df['year'] == year_born_round].index.tolist()[0]
+
+# Add explainer to top right
+props = dict(boxstyle='round', facecolor='lightcoral', alpha=0.5)
+ax.text(0.63, 0.975, "If you were born in %s,\n%s%% of the total amount \nof CO2 that has been \nemitted since 1750, has \nbeen emitted in your \nlifetime." %
+(int(df['year'].iloc[year_born_index].item()),
+ int(df['share_gen'].iloc[year_born_index].item())),
+transform=ax.transAxes, fontsize=10,
+verticalalignment='top', bbox=props);
+
+# Give the right bar a different color
+ax.patches[year_born_index].set_facecolor('lightcoral');
+
+# Draw the vertical line towards the red bar
+plt.vlines(x = df['share_gen'].iloc[year_born_index], ymin = -1, ymax = year_born_index, color='lightcoral');
+
+plt.figtext(0.06, 0.02, 'https://git.pub.solar/misha/share_CO2_generation', fontsize = 7)
+plt.figtext(0.97, 0.02, 'Original from https://x.com/neilrkaye', ha='right', fontsize = 7) #
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+plt.tight_layout()
+plt.show()
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