import matplotlib.pyplot as plt
# 创建图形和坐标轴对象，指定尺寸和DPI
fig, ax = plt.subplots(figsize=(13.33,7.5), dpi = 96)
# 绘制折线
for country in top_20_countries:
    data = df[df['Country Name'] == country]
    line = ax.plot(data['Year'], data['GDP'], label=country)
# 添加图例
ax.legend(loc="best", fontsize=8)
# 创建网格
ax.grid(which="major", axis='x', color='#DAD8D7', alpha=0.5, zorder=1)
ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1)
# 重新格式化x轴标签和刻度线标签
ax.set_xlabel('', fontsize=12, labelpad=10)
# 不需要轴标签
ax.xaxis.set_label_position("bottom")
ax.xaxis.set_major_formatter(lambda s, i : f'{s:,.0f}')
#以防万一我们需要额外的格式设置
ax.xaxis.set_major_locator(MaxNLocator(integer=True))
#以防我们需要额外的格式化
ax.xaxis.set_tick_params(pad=2, labelbottom=True, bottom=True, labelsize=12, labelrotation=0)
# 重新格式化y轴
ax.set_ylabel('GDP (Billions USD)', fontsize=12, labelpad=10)
ax.yaxis.set_label_position("left")
ax.yaxis.set_major_formatter(lambda s, i : f'{s*10**-9:,.0f}')
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
#以防我们需要额外的格式化
ax.yaxis.set_tick_params(pad=2, labeltop=False, labelbottom=True, bottom=False, labelsize=12)

# 颜色和线条样式
colors_dict = {'United States': '#014f86', 'China': '#DC0000', 'Japan': '#ff4d6d', 'Germany': '#403d39', 'India': '#6a994e'}

line_styles_dict = {'United States': '-', 'China': '-', 'Japan': '-', 'Germany': '-', 'India': '-'}
# 绘制前5条线
for country in top_20_countries[:5]:
    color = colors_dict.get(country, 'grey')
    # 从字典中获取颜色，如果找不到，默认为灰色
    line_style = line_styles_dict.get(country, '-')
    # 从字典中获取线条样式，如果未找到，默认为实线
    data = df[df['Country Name'] == country]
    line = ax.plot(data['Year'], data['GDP'], color=color, linestyle=line_style, zorder=2, label=country)
    # 添加图例
    ax.legend(loc="best", fontsize=8)
    # 绘制剩余部分
    for country in top_20_countries[5:]:
        data = df[df['Country Name'] == country]
        line = ax.plot(data['Year'], data['GDP'], color='grey', linestyle=':', linewidth=0.5, zorder=2)
# 移除边框
ax.spines[['top','right','bottom']].set_visible(False)
# 加粗左侧边框
ax.spines['left'].set_linewidth(1.1)
# 在顶部添加红线和矩形
ax.plot([0.05, .9], [.98, .98], transform=fig.transFigure, clip_on=False, color='#E3120B', linewidth=.6)
ax.add_patch(plt.Rectangle((0.05,.98), 0.04, -0.02, facecolor='#E3120B', transform=fig.transFigure, clip_on=False, linewidth = 0))
# 添加标题和副标题
ax.text(x=0.05, y=.93, s="Evolution of the 20 Richest Countries GDP over the Past 50 Years", transform=fig.transFigure, ha='left', fontsize=14, weight='bold', alpha=.8)
ax.text(x=0.05, y=.90, s="Focus on the current 5 richest countries from 1973 to 2022", transform=fig.transFigure, ha='left', fontsize=12, alpha=.8)
# 设置来源文本
ax.text(x=0.05, y=0.12, s="Source: World Bank - https://databank.worldbank.org/", transform=fig.transFigure, ha='left', fontsize=10, alpha=.7)
# 调整绘图区域周围的边距
plt.subplots_adjust(left=None, bottom=0.2, right=None, top=0.85, wspace=None, hspace=None)
# 设置白色背景
fig.patch.set_facecolor('white')
# 绘制前5条线
for country in top_20_countries[:5]:
    color = colors_dict.get(country, 'grey')
    # 从字典中获取颜色，如果找不到，默认为黑色
    line_style = line_styles_dict.get(country, '-')
    # 从字典中获取线条样式，如果找不到，默认为实线
    data = df[df['Country Name'] == country]
    line = ax.plot(data['Year'], data['GDP'], color=color, linestyle=line_style, zorder=2, label = country)
    ax.plot(data['Year'].iloc[-1], data['GDP'].iloc[-1], 'o', color=color, markersize=10, alpha=0.3)
    ax.plot(data['Year'].iloc[-1], data['GDP'].iloc[-1], 'o', color=color, markersize=5)
    # 在图表上添加一些文字
    ax.annotate('During the 2000s,\nChina began experiencing rapid economic growth,\noutpacing all other countries.',               (data['Year'].iloc[-18], 2000000000000),              xytext=(data['Year'].iloc[-28]-timedelta(days=500), 18000000000000),              ha='left', fontsize=9, arrowprops=dict(arrowstyle='-|>', facecolor='k', connectionstyle="arc3,rad=-0.15"))