6))plt.plot(x,y,label='sin(x)')# 设置x轴刻度plt.xticks(np.arange(0,11,2))# 设置y轴刻度plt.yticks(np.arange(-1,1.1,0.5))plt.title('How to change axis interval - how2matplotlib.com')plt.xlabel('X axis')plt.ylabel('Y axis')plt.legend...
ax=plt.subplots()# 绘制数据ax.plot(x,y,label='sin(x)')# 设置自定义的视图限制ax.set_xlim(2,8)ax.set_ylim(-0.5,0.5)# 重置为默认间隔ax.xaxis.set_default_intervals()ax.yaxis.set_default_intervals()plt.title('How2matplotlib.com: Default Intervals Example')...
x = np.linspace(0, 10, 100) y = np.sin(x) # 创建图形和坐标轴 fig, ax = plt.subplots() # 绘制曲线 ax.plot(x, y) # 设置标题和轴标签 ax.set_title('Smooth Curve') ax.set_xlabel('X Axis') ax.set_ylabel('Y Axis') # 显示图形 plt.show() 在这个例子中,我们使用np.linspace函...
fig, ax = plt.subplots() hours = mdates.HourLocator(interval=2) d_fmt = mdates.DateFormatter('%H:%M') ax.xaxis.set_minor_locator(mdates.HourLocator(interval=1)) ax.xaxis.set_major_locator(hours) ax.xaxis.set_major_formatter(d_fmt) ax.fill(dates, values) ax.plot(dates, values, ...
# Define the upper limit, lower limit, interval of Y axis and colors y_LL = 100 y_UL = int(df.iloc[:, 1:].max().max()*1.1) y_interval = 400 mycolors = ['tab:red', 'tab:blue', 'tab:green', 'tab:orange'] # Draw Plot and Annotate ...
Axis.get_ticklines():获取刻度线列表(一个Line2D实例的列表)。 可以通过minor=True|False关键字参数控制输出minor还是major的tick line。 Axis.get_scale():获取坐标轴的缩放属性,如'log'或者'linear' Axis.get_view_interval():获取内部的axis view limits实例 ...
ax.xaxis.set_ticks_position('bottom') # 使用.spines选择底部边框(x轴),使用.set_position设置边框(x轴)位置在y=0处 # 位置属性可选(outward,axes,data) ax.spines['bottom'].set_position(('data',0)) # 设置y轴刻度数字/名称的位置为left ...
# Import Data df = pd.read_csv('https://github.com/selva86/datasets/raw/master/mortality.csv') # Define the upper limit, lower limit, interval of Y axis and colors y_LL = 100 y_UL = int(df.iloc[:, 1:].max().max()*1.1) y_interval = 400 mycolors = ['tab:red', 'tab:bl...
[np.nan]*len(x))# 初始状态下隐藏线条returnline,# 动画函数defanimate(i):line.set_ydata(np.sin(x+i/10.0))# 更新 y 数据returnline,# 创建动画对象ani=FuncAnimation(fig,animate,init_func=init,frames=200,interval=20,blit=True)# 显示动画plt.show()参数详解fig:图形对象,通过plt.subplots()创建...
# `NullFormatter`, to avoid cumbering the axis with too many labels. plt.gca().yaxis.set_minor_formatter(NullFormatter()) # Adjust the subplot layout, because the logit one may take more space # than usual, due to y-tick labels like "1 - 10^{-3}" ...