gcj_country_performance_chart.py

# import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
import matplotlib.pyplot as plt

data = [
    ['India', 16],
    ['United States', 56],
    ['Bangladesh', 57],
    ['France', 71],
    ['Brazil', 83],
    ['Indonesia', 90],
    ['Romania', 92],
    ['Germany', 94],
    ['Australia', 97],
    ['Canada', 98],
    ['Thailand', 113],
    ['Hungary', 137],
    ['Hong Kong', 143],
    ['Netherlands', 169],
    ['Vietnam', 177],
    ['Poland', 180],
    ['Taiwan', 194],
    ['Iran', 207],
    ['Ukraine', 214],
    ['China', 224],
    ['Belarus', 241],
    ['Slovakia', 252],
    ['Japan', 263],
    ['Russia', 279],
]

c = ['China', 'Taiwan', 'Singapore', 'Macau', 'Hong Kong']
cjk = c + ['Japan'] + ['South Korea'] + ['Vietnam']

slavs = ['Russia', 'Poland', 'Ukraine', 'Serbia', 'Czech Republic', 'Bulgaria', 'Belarus', 'Croatia', 'Slovakia', 'Bosnia', 'Slovenia', 'Macedonia', 'Montenegro']

west = ['United States', 'Canada', 'Australia', 'New Zealand', 'Germany', 'France', 'Spain', 'Italy', 'United Kingdom', 'Portugal', 'Austria', 'Switzerland', 'Netherlands', 'Belgium', 'Luxembourg', 'Denmark', 'Norway', 'Sweden', 'Finland']
    # plus some microstates, whatever

def get_color(c):
    if c in cjk:
        return ['Sinosphere', 'gold']
    if c in slavs:
        return ['Slavic countries', 'lightskyblue']
    if c in west:
        return ['Western countries', 'lightcoral']
    # return 'white'
    return ['Other countries', 'black']

data_x = [d[0] for d in data]
data_y = [d[1]/10 for d in data]

colors = [get_color(d[0]) for d in data]
y_pos = np.arange(len(data))

fig = plt.gcf()
# fig.set_size_inches(18.5, 10.5)
# fig.set_size_inches(10, 4)

# fix ugly default layout
ax = plt.axes()
ax.xaxis.tick_top()
ax.xaxis.set_ticks_position('none')
ax.yaxis.set_ticks_position('none')
ax.xaxis.set_label_position('top')
ax.spines['top'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)

pos1 = ax.get_position() # get the original position
pos2 = [pos1.x0, pos1.y0 + .07,  pos1.width, pos1.height]
ax.set_position(pos2)

# plt.barh(y_pos, data_y, color=colors, align='center', label=colors, linewidth=0, alpha=0.5)
for i in range(len(data)):
    if data_x[i] in ['Netherlands', 'Vietnam', 'Poland', 'Iran']:
        # dum stupid hack for legend
        # there seems to be no way to set it manually :/
        plt.barh(i, data_y[i], color=colors[i][1], align='center', label=colors[i][0], linewidth=0, alpha=0.5)
    else:
        plt.barh(i, data_y[i], color=colors[i][1], align='center', linewidth=0, alpha=0.5)
plt.yticks(y_pos, data_x)
# plt.xlabel('percentage of qualification round participants advancing to round 2')
plt.xlabel('percentage of round 2 participants vs qualification round participants')

FIGURE_TITLE = '2015 Google Code Jam Round 2 advancement*, by country'

# plt.title(FIGURE_TITLE)


plt.text(1.4, 29.3, FIGURE_TITLE,
         # horizontalalignment='center',
         fontsize=14)
         # fontsize=20,
         # transform = ax2.transAxes)

# plt.show()

# problems
# 1. unable to get the xticks (0,5,..) close to the data !
# 2. HUGE white space below india => hide by moving xticks to top,
#       hiding opposite axis
# 3. ugly legend hack
# 4. maybe use flags? probably won't be able to get it to work in matplotlib..
# 5. data old and not nicely collected, better use pure advancement rate
# workaround: manually move in inkscape

plt.legend(loc="lower right", frameon=False)


plt.tight_layout()

# plt.savefig('out.svg', bbox_inches='tight')
plt.savefig('out.svg')