Matplotlib
效果图如下
主要使用matplotlib.animation.FuncAnimation
,上核心代码,
# 定义静态绘图函数 def draw_barchart(year): dff = df[df['year'].eq(year)].sort_values(by='value', ascending=True).tail(10) ax.clear() ax.barh(dff['name'], dff['value'], color=[colors[group_lk[x]] for x in dff['name']]) dx = dff['value'].max() / 200 for i, (value, name) in enumerate(zip(dff['value'], dff['name'])): ax.text(value - dx, i, name, size=14, weight=600, ha='right', va='bottom') ax.text(value - dx, i - .25, group_lk[name], size=10, color='#444444', ha='right', va='baseline') ax.text(value + dx, i, f'{value:,.0f}', size=14, ha='left', va='center') # 注释文本 ax.text(1, 0.4, year, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800) ax.text(0, 1.06, '单位 (每1000)', transform=ax.transAxes, size=12, color='#777777') ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}')) ax.xaxis.set_ticks_position('top') ax.tick_params(axis='x', colors='#777777', labelsize=12) ax.set_yticks([]) ax.margins(0, 0.01) ax.grid(which='major', axis='x', linestyle='-') ax.set_axisbelow(True) ax.text(0, 1.12, '1500~2018年世界人口最多城市', transform=ax.transAxes, size=24, weight=600, ha='left') plt.box(False) # 调用matplotlib.animation.FuncAnimation让静态图动起来 animator = animation.FuncAnimation(fig, draw_barchart, frames=range(1968, 2019)) # Jupyter Notebook里展示动图animation HTML(animator.to_jshtml())
在绘图数据部分改自己的数据既可为所欲为的使用了~
Seaborn
效果图如下
代码
import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation import seaborn as sns import numpy as np import palettable def get_data(i=0): x, y = np.random.normal(loc=i, scale=3, size=(2, 260)) return x, y x, y = get_data() g = sns.JointGrid(x=x, y=y, size=4) g.fig.set_size_inches(10, 8) lim = (-10, 10) def prep_axes(g, xlim, ylim): g.ax_joint.clear() g.ax_joint.set_xlim(xlim) g.ax_joint.set_ylim(ylim) g.ax_marg_x.clear() g.ax_marg_x.set_xlim(xlim) g.ax_marg_y.clear() g.ax_marg_y.set_ylim(ylim) plt.setp(g.ax_marg_x.get_xticklabels(), visible=False) plt.setp(g.ax_marg_y.get_yticklabels(), visible=False) plt.setp(g.ax_marg_x.yaxis.get_majorticklines(), visible=False) plt.setp(g.ax_marg_x.yaxis.get_minorticklines(), visible=False) plt.setp(g.ax_marg_y.xaxis.get_majorticklines(), visible=False) plt.setp(g.ax_marg_y.xaxis.get_minorticklines(), visible=False) plt.setp(g.ax_marg_x.get_yticklabels(), visible=False) plt.setp(g.ax_marg_y.get_xticklabels(), visible=False) def animate(i): g.x, g.y = get_data(i) prep_axes(g, lim, lim) g.plot_joint(sns.kdeplot, cmap='Paired') g.plot_marginals(sns.kdeplot, color='blue', shade=True) frames = np.sin(np.linspace(0, 2 * np.pi, 17)) * 5 ani = matplotlib.animation.FuncAnimation(g.fig, animate, frames=frames, repeat=True) HTML(ani.to_jshtml())
和Matplotlib代码类似,不过多解释。
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