File:Industrialization per capita 1750-1900.svg
Summary
| Description |
English: Relative per capita levels of industrialization in developed countries. United Kingdom has the value of 100 at 1900. Values are triennial annual averages, except for 1913.
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| Date | |
| Source | Own work |
| Author | Nicoguaro |
| SVG development | |
| Source code | Python code"""
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()
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