File:IPhO participants graph.svg

#! /usr/bin/env python
# -*- coding:utf8 -*-

import matplotlib.pyplot as plt

# data source: https://web.archive.org/web/*/http://ipho.org/statictics.pdf
data = [
{'y':1967, 'cc':'pl', 'teams':5,  'stud':15,  'g':7,  's':0,  'b':0},
{'y':1968, 'cc':'hu', 'teams':8,  'stud':24,  'g':2,  's':1,  'b':3},
{'y':1969, 'cc':'cs', 'teams':8,  'stud':40,  'g':13, 's':10, 'b':9},
{'y':1970, 'cc':'su', 'teams':8,  'stud':48,  'g':4,  's':7,  'b':10},
{'y':1971, 'cc':'bg', 'teams':7,  'stud':35,  'g':5,  's':6,  'b':12},
{'y':1972, 'cc':'ro', 'teams':9,  'stud':45,  'g':2,  's':3,  'b':14},
{'y':1974, 'cc':'pl', 'teams':8,  'stud':40,  'g':3,  's':0,  'b':8},
{'y':1975, 'cc':'de', 'teams':9,  'stud':45,  'g':7,  's':9,  'b':12},
{'y':1976, 'cc':'hu', 'teams':10, 'stud':50,  'g':7,  's':7,  'b':12},
{'y':1977, 'cc':'cs', 'teams':12, 'stud':60,  'g':7,  's':16, 'b':16},
{'y':1979, 'cc':'su', 'teams':11, 'stud':55,  'g':8,  's':5,  'b':13},
{'y':1981, 'cc':'bg', 'teams':14, 'stud':70,  'g':7,  's':19, 'b':18},
{'y':1982, 'cc':'de', 'teams':17, 'stud':84,  'g':14, 's':19, 'b':23},
{'y':1983, 'cc':'ro', 'teams':16, 'stud':80,  'g':7,  's':9,  'b':16},
{'y':1984, 'cc':'se', 'teams':18, 'stud':83,  'g':9,  's':5,  'b':16},
{'y':1985, 'cc':'yu', 'teams':20, 'stud':99,  'g':5,  's':6,  'b':17},
{'y':1986, 'cc':'uk', 'teams':21, 'stud':105, 'g':4,  's':5,  'b':22},
{'y':1987, 'cc':'de', 'teams':25, 'stud':125, 'g':3,  's':10, 'b':29},
{'y':1988, 'cc':'at', 'teams':27, 'stud':132, 'g':7,  's':23, 'b':29},
{'y':1989, 'cc':'pl', 'teams':30, 'stud':150, 'g':10, 's':26, 'b':31},
{'y':1990, 'cc':'nl', 'teams':32, 'stud':160, 'g':6,  's':12, 'b':25},
{'y':1991, 'cc':'cu', 'teams':31, 'stud':149, 'g':13, 's':10, 'b':31},
{'y':1992, 'cc':'fi', 'teams':38, 'stud':177, 'g':13, 's':20, 'b':24},
{'y':1993, 'cc':'us', 'teams':42, 'stud':201, 'g':18, 's':16, 'b':33},
{'y':1994, 'cc':'cn', 'teams':46, 'stud':229, 'g':6,  's':5,  'b':22},
{'y':1995, 'cc':'au', 'teams':51, 'stud':255, 'g':25, 's':29, 'b':43},
{'y':1996, 'cc':'no', 'teams':55, 'stud':260, 'g':20, 's':25, 'b':47},
{'y':1997, 'cc':'ca', 'teams':56, 'stud':265, 'g':18, 's':33, 'b':54},
{'y':1998, 'cc':'is', 'teams':56, 'stud':266, 'g':11, 's':15, 'b':43},
{'y':1999, 'cc':'it', 'teams':62, 'stud':291, 'g':30, 's':71, 'b':54},
{'y':2000, 'cc':'uk', 'teams':63, 'stud':296, 'g':15, 's':11, 'b':42},
{'y':2001, 'cc':'tr', 'teams':65, 'stud':306, 'g':22, 's':40, 'b':53},
{'y':2002, 'cc':'id', 'teams':66, 'stud':296, 'g':42, 's':37, 'b':58},
{'y':2003, 'cc':'tw', 'teams':54, 'stud':238, 'g':20, 's':39, 'b':38},
{'y':2004, 'cc':'kr', 'teams':71, 'stud':328, 'g':31, 's':35, 'b':68},
{'y':2005, 'cc':'es', 'teams':72, 'stud':352, 'g':46, 's':26, 'b':63},
{'y':2006, 'cc':'sg', 'teams':82, 'stud':388, 'g':37, 's':49, 'b':82},
{'y':2007, 'cc':'ir', 'teams':69, 'stud':327, 'g':37, 's':46, 'b':51},
{'y':2008, 'cc':'vn', 'teams':82, 'stud':376, 'g':46, 's':47, 'b':78},
{'y':2009, 'cc':'mx', 'teams':68, 'stud':316, 'g':41, 's':70, 'b':79},
{'y':2010, 'cc':'hr', 'teams':79, 'stud':367, 'g':35, 's':66, 'b':97},
{'y':2011, 'cc':'th', 'teams':83, 'stud':393, 'g':54, 's':68, 'b':93},
{'y':2012, 'cc':'ee', 'teams':80, 'stud':378, 'g':45, 's':71, 'b':92},
{'y':2013, 'cc':'dk', 'teams':82, 'stud':374, 'g':41, 's':64, 'b':101},
{'y':2014, 'cc':'kz', 'teams':85, 'stud':383, 'g':44, 's':82, 'b':86},
{'y':2015, 'cc':'in', 'teams':83, 'stud':382, 'g':38, 's':64, 'b':88},
{'y':2016, 'cc':'ch', 'teams':84, 'stud':398, 'g':47, 's':74, 'b':95},
{'y':2017, 'cc':'id', 'teams':84, 'stud':395, 'g':64, 's':72, 'b':102},
{'y':2018, 'cc':'pt', 'teams':86, 'stud':396, 'g':42, 's':69, 'b':99}]

fig = plt.figure(figsize=(600 / 90.0, 400 / 90.0), dpi=72)
ax1 = plt.gca()
ax2 = ax1.twinx()

ax1.plot([i['y'] for i in data], [i['teams'] for i in data],
    'bo-', linewidth=1, markersize=5)
ax2.plot([], [], 'bo-', linewidth=1, markersize=5, label='teams')
ax2.plot([i['y'] for i in data], [i['stud'] for i in data],
    'ko-', linewidth=1, markersize=5, label='students')
ax2.plot([i['y'] for i in data], [i['g'] for i in data],
    'o-', linewidth=1, markersize=5, mew=1,
    c='#ffcd00', mec='#d39a00', label='gold', zorder=-1)
ax2.plot([i['y'] for i in data], [i['s'] for i in data],
    'o-', linewidth=1, markersize=5, mew=1,
    c='#a9a9a9', mec='#808080', label='silver', zorder=-2)
ax2.plot([i['y'] for i in data], [i['b'] for i in data],
    'o-', linewidth=1, markersize=5, mew=1,
    c='#cd7f32', mec='#905923', label='bronze', zorder=-3)
plt.xlim(1965)
ax1.set_ylim(0, 90)
ax2.set_ylim(0, 5 * ax1.get_ylim()[1])
ax1.set_ylabel('national teams', color='b')
ax2.set_ylabel('students, medals')
ax1.tick_params('y', colors='b')
ax1.grid(True)
plt.title('IPhO participants')
plt.legend(loc='upper left', borderaxespad=1.5)
plt.tight_layout()
plt.savefig('IPhO_participants_graph.svg')