axis('off') 3. 添加双y轴:使用Axes.twinx()方法绘制:重点 代码语言:javascript 代码运行次数:0 运行 AI代码解释 #添加双y轴:使用Axes.twinx()方法绘制 second_plot = ax.twinx() second_plot.set_ylim(bottom=-3,top=43) second_plot.set_yticks(np.arange
second_plot.set_xticks(np.arange(-.5, 8, step=.5)) second_plot.tick_params(left=False,bottom=False,labelbottom=False,labelsize=10,colors='k') second_plot.grid(color="none",zorder=0) second_plot.set_axisbelow(True) for spine in ['top','bottom','left','right']: second_plot.spine...
#add y-axis label ax.set_ylabel('Sales', color=col1, fontsize=16) #define second y-axis that shares x-axis with current plot ax2 = ax.twinx() #add second line to plot ax2.plot(df2.year, df2.leads, color=col2, marker='o', linewidth=3) #add second y-axis label ax2.set_...
(bottom=-3,top=43) second_plot.set_yticks(np.arange(0, 50, step=10)) second_plot.set_xticks(np.arange(-.5, 8, step=.5)) second_plot.tick_params(left=False,bottom=False,labelbottom=False,labelsize=10,colors='k') second_plot.grid(color="none",zorder=0) second_plot.set_axis...
# Plot Line2 (Right Y Axis)ax2 = ax1.twinx() # instantiate a second axes that shares the...
['十字星信号'].values ax2.plot(range(len(signal_data)), signal_data, color='orange', linewidth=2, label=get_label('signal')) ax2.fill_between(range(len(signal_data)), signal_data, alpha=0.3, color='orange') ax2.set_ylabel(get_label('signal'), fontsize=12) ax2.set_ylim(-0.1...
pl.plot(x, y)# use pylab to plot x and y 1 1 2 pl.title(’Plot of y vs. x’)# give plot a title 1 2 pl.xlabel(’x axis’)# make axis labels 1 2 pl.ylabel(’y axis’) 1 1 2 pl.xlim(0.0,7.0)# set axis limits ...
plt.plot(cc,cc ** 3,label ='cubic') plt.xlabel('x label') plt.ylabel('y label') 结果显示,如下: 注意为了显示中文,我们plt.rcParams属性设置了中文字体,不然不能正确显示中文title的。 2.散点图 散点图和折线图的原理差不多;如果使用直线连接散点图中的点,得到的就是折线图。所以你只需要设置线型...
import matplotlib.pyplot as pltimport numpy as np# 生成数据x = np.random.randn(1000)# 绘图plt.boxplot(x)# 添加网格plt.grid(axis='y', ls=':', lw=1, color='gray', alpha=0.4)plt.show() 8. 误差棒图 —— errorbar() 此函数用于绘制y轴方向或者x轴方向的误差范围: import matplotlib.py...
= plt.subplot(221) ax2.margins(2, 2) # Values >0.0 zoom out ax2.plot(t1, f(t1)) ...