"""
Data from Paul Bairoch, "International Industrialization Levels from 1750 to 1980," Journal of European Economic History (1982) v. 11.
"""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

palette_colors = ["#1b9e77", "#d95f02", "#7570b3", "#e7298a", "#66a61e",
                  "#e6ab02", "#a6761d", "#666666"]
palette = sns.color_palette(palette_colors, 8)
sns.set_style("white")
years = [1750, 1800, 1830, 1860, 1880, 1900, 1913]
countries = ["United Kingdom", "Germany", "France", "Austria-Hungary",
             "Russia", "Italy", "United States", "Japan"]
data = np.array([
       [  10.,   16.,   25.,   64.,   87.,  100.,  115.],
       [   8.,    8.,    9.,   15.,   25.,   52.,   85.],
       [   9.,    9.,   12.,   20.,   28.,   39.,   59.],
       [   7.,    7.,    8.,   11.,   15.,   23.,   32.],
       [   6.,    6.,    7.,    8.,   10.,   15.,   20.],
       [   8.,    8.,    8.,   10.,   12.,   17.,   26.],
       [   4.,    9.,   14.,   21.,   38.,   69.,  126.],
       [   7.,    7.,    7.,    7.,    9.,   12.,   20.]])
plt.figure(figsize=(6, 4))
for k in range(8):
    plt.plot(years, data[k, :], lw=2, color=palette[k], label=countries[k])
plt.legend(loc="best")
plt.xlabel("Year")
plt.ylabel("Relative per capita industrialization level")
plt.xlim([1750, 1913])
plt.savefig("Industrialization_per_capita_1750-1900.svg", bbox_inches="tight")
plt.show()