import pandas as pd import numpy as np import matplotlib.pyplot as plt # This makes out plots higher resolution, which makes them easier to see while building plt.rcParams['figure.dpi'] = 100

gdp = pd.read_csv('data/gdp_1960_2020.csv') gdp.head()

gdp['gdp_trillions'] = gdp['gdp'] / 1_000_000_000_000

gdp[gdp['year'] == 2020].sort_values(by='gdp_trillions').tail(9)

# Setup plot size. fig, ax = plt.subplots(figsize=(3,6)) # Create grid # Zorder tells it which layer to put it on. We are setting this to 1 and our data to 2 so the grid is behind the data. ax.grid(which="major", axis='x', color='#758D99', alpha=0.6, zorder=1) # Remove splines. Can be done one at a time or can slice with a list. ax.spines[['top','right','bottom']].set_visible(False) # Make left spine slightly thicker ax.spines['left'].set_linewidth(1.1) # Setup data gdp['country'] = gdp['country'].replace('the United States', 'United States') gdp_bar = gdp[gdp['year'] == 2020].sort_values(by='gdp_trillions')[-9:] # Plot data ax.barh(gdp_bar['country'], gdp_bar['gdp_trillions'], color='#006BA2', zorder=2) # Set custom labels for x-axis ax.set_xticks([0, 5, 10, 15, 20]) ax.set_xticklabels([0, 5, 10, 15, 20]) # Reformat x-axis tick labels ax.xaxis.set_tick_params(labeltop=True, # Put x-axis labels on top labelbottom=False, # Set no x-axis labels on bottom bottom=False, # Set no ticks on bottom labelsize=11, # Set tick label size pad=-1) # Lower tick labels a bit # Reformat y-axis tick labels ax.set_yticklabels(gdp_bar['country'], # Set labels again ha = 'left') # Set horizontal alignment to left ax.yaxis.set_tick_params(pad=100, # Pad tick labels so they don't go over y-axis labelsize=11, # Set label size bottom=False) # Set no ticks on bottom/left # Shrink y-lim to make plot a bit tighter ax.set_ylim(-0.5, 8.5) # Add in line and tag ax.plot([-.35, .87], # Set width of line [1.02, 1.02], # Set height of line transform=fig.transFigure, # Set location relative to plot clip_on=False, color='#E3120B', linewidth=.6) ax.add_patch(plt.Rectangle((-.35,1.02), # Set location of rectangle by lower left corder 0.12, # Width of rectangle -0.02, # Height of rectangle. Negative so it goes down. facecolor='#E3120B', transform=fig.transFigure, clip_on=False, linewidth = 0)) # Add in title and subtitle ax.text(x=-.35, y=.96, s="The big leagues", transform=fig.transFigure, ha='left', fontsize=13, weight='bold', alpha=.8) ax.text(x=-.35, y=.925, s="2020 GDP, trillions of USD", transform=fig.transFigure, ha='left', fontsize=11, alpha=.8) # Set source text ax.text(x=-.35, y=.08, s="""Source: "GDP of all countries(1960-2020)" via Kaggle.com""", transform=fig.transFigure, ha='left', fontsize=9, alpha=.7) # Export plot as high resolution PNG plt.savefig('images/economist_bar.png', # Set path and filename dpi = 300, # Set dots per inch bbox_inches="tight", # Remove extra whitespace around plot facecolor='white') # Set background color to white

countries = gdp[gdp['year'] == 2020].sort_values(by='gdp_trillions')[-9:]['country'].values countries

gdp['date'] = pd.to_datetime(gdp['year'], format='%Y')

# Setup plot size. fig, ax = plt.subplots(figsize=(8,4)) # Create grid # Zorder tells it which layer to put it on. We are setting this to 1 and our data to 2 so the grid is behind the data. ax.grid(which="major", axis='y', color='#758D99', alpha=0.6, zorder=1) # Plot data # Loop through country names and plot each one. for country in countries: ax.plot(gdp[gdp['country'] == country]['date'], gdp[gdp['country'] == country]['gdp_trillions'], color='#758D99', alpha=0.8, linewidth=3) # Plot US and China separately ax.plot(gdp[gdp['country'] == 'United States']['date'], gdp[gdp['country'] == 'United States']['gdp_trillions'], color='#006BA2', linewidth=3) ax.plot(gdp[gdp['country'] == 'China']['date'], gdp[gdp['country'] == 'China']['gdp_trillions'], color='#3EBCD2', linewidth=3) # Remove splines. Can be done one at a time or can slice with a list. ax.spines[['top','right','left']].set_visible(False) # Shrink y-lim to make plot a bit tigheter ax.set_ylim(0, 23) # Set xlim to fit data without going over plot area ax.set_xlim(pd.datetime(1958, 1, 1), pd.datetime(2023, 1, 1)) # Reformat x-axis tick labels ax.xaxis.set_tick_params(labelsize=11) # Set tick label size # Reformat y-axis tick labels ax.set_yticklabels(np.arange(0,25,5), # Set labels again ha = 'right', # Set horizontal alignment to right verticalalignment='bottom') # Set vertical alignment to make labels on top of gridline ax.yaxis.set_tick_params(pad=-2, # Pad tick labels so they don't go over y-axis labeltop=True, # Put y-axis labels on top labelbottom=False, # Set no y-axis labels on bottom bottom=False, # Set no ticks on bottom labelsize=11) # Set tick label size # Add labels for USA and China ax.text(x=.62, y=.68, s='United States', transform=fig.transFigure, size=10, alpha=.9) ax.text(x=.7, y=.4, s='China', transform=fig.transFigure, size=10, alpha=.9) # Add in line and tag ax.plot([0.12, .9], # Set width of line [.98, .98], # Set height of line transform=fig.transFigure, # Set location relative to plot clip_on=False, color='#E3120B', linewidth=.6) ax.add_patch(plt.Rectangle((0.12,.98), # Set location of rectangle by lower left corder 0.04, # Width of rectangle -0.02, # Height of rectangle. Negative so it goes down. facecolor='#E3120B', transform=fig.transFigure, clip_on=False, linewidth = 0)) # Add in title and subtitle ax.text(x=0.12, y=.91, s="Ahead of the pack", transform=fig.transFigure, ha='left', fontsize=13, weight='bold', alpha=.8) ax.text(x=0.12, y=.86, s="Top 9 GDP's by country, in trillions of USD, 1960-2020", transform=fig.transFigure, ha='left', fontsize=11, alpha=.8) # Set source text ax.text(x=0.12, y=0.01, s="""Source: "GDP of all countries(1960-2020)" via Kaggle.com""", transform=fig.transFigure, ha='left', fontsize=9, alpha=.7) # Export plot as high resolution PNG plt.savefig('images/economist_line.png', # Set path and filename dpi = 300, # Set dots per inch bbox_inches="tight", # Remove extra whitespace around plot facecolor='white') # Set background color to white

gdp_dumbbell = gdp[(gdp['country'].isin(countries)) & ((gdp['year'] == 1960) | (gdp['year'] == 2020))].sort_values(by='gdp') gdp_dumbbell.head(5)

# Setup plot size. fig, ax = plt.subplots(figsize=(7,4)) # Create grid # Zorder tells it which layer to put it on. We are setting this to 1 and our data to 2 so the grid is behind the data. ax.grid(which="major", axis='both', color='#758D99', alpha=0.6, zorder=1) # Remove splines. Can be done one at a time or can slice with a list. ax.spines[['top','right','bottom']].set_visible(False) # Setup data gdp_dumbbell = (gdp[(gdp['country'].isin(countries)) & ((gdp['year'] == 2000) | (gdp['year'] == 2020))][['year','gdp_trillions','country']] .pivot(index='country',columns='year', values='gdp_trillions') .sort_values(by=2020)) # Plot data # Plot horizontal lines first ax.hlines(y=gdp_dumbbell.index, xmin=gdp_dumbbell[2000], xmax=gdp_dumbbell[2020], color='#758D99', zorder=2, linewidth=2, label='_nolegend_', alpha=.8) # Plot bubbles next ax.scatter(gdp_dumbbell[2000], gdp_dumbbell.index, label='2000', s=60, color='#DB444B', zorder=3) ax.scatter(gdp_dumbbell[2020], gdp_dumbbell.index, label='2020', s=60, color='#006BA2', zorder=3) # Set xlim ax.set_xlim(0, 25.05) # Reformat x-axis tick labels ax.xaxis.set_tick_params(labeltop=True, # Put x-axis labels on top labelbottom=False, # Set no x-axis labels on bottom bottom=False, # Set no ticks on bottom labelsize=11, # Set tick label size pad=-1) # Lower tick labels a bit # Reformat y-axis tick labels ax.set_yticklabels(gdp_dumbbell.index, # Set labels again ha = 'left') # Set horizontal alignment to left ax.yaxis.set_tick_params(pad=100, # Pad tick labels so they don't go over y-axis labelsize=11, # Set label size bottom=False) # Set no ticks on bottom/left # Set Legend ax.legend(['2000', '2020'], loc=(-.29,1.09), ncol=2, frameon=False, handletextpad=-.1, handleheight=1) # Add in line and tag ax.plot([-0.08, .9], # Set width of line [1.17, 1.17], # Set height of line transform=fig.transFigure, # Set location relative to plot clip_on=False, color='#E3120B', linewidth=.6) ax.add_patch(plt.Rectangle((-0.08,1.17), # Set location of rectangle by lower left corder 0.05, # Width of rectangle -0.025, # Height of rectangle. Negative so it goes down. facecolor='#E3120B', transform=fig.transFigure, clip_on=False, linewidth = 0)) # Add in title and subtitle ax.text(x=-0.08, y=1.09, s="Great expectations", transform=fig.transFigure, ha='left', fontsize=13, weight='bold', alpha=.8) ax.text(x=-0.08, y=1.04, s="Top 9 countries by GDP, in trillions of USD", transform=fig.transFigure, ha='left', fontsize=11, alpha=.8) # Set source text ax.text(x=-0.08, y=0.04, s="""Source: "GDP of all countries(1960-2020)" via Kaggle.com""", transform=fig.transFigure, ha='left', fontsize=9, alpha=.7) # Export plot as high resolution PNG plt.savefig('images/economist_dumbbell.png', # Set path and filename dpi = 300, # Set dots per inch bbox_inches="tight", # Remove extra whitespace around plot facecolor='white') # Set background color to white