【matplotlib】【绘制股票数据】子图的绘制、子图标签设置、双y轴

【matplotlib】【绘制股票数据】子图的绘制、子图标签设置、双y轴最近在使用matplotlib,把我自己遇到过的问题总结一下叭~绘图步骤效果图设置画布画图画线展示各条线的情况legentx轴标签旋转x轴标签(间隔)选取画网格对图像设置数字标签存储完整代码效果图设置画布fig=plt

最近在使用matplotlib,把我自己遇到过的问题总结一下叭~

效果图

在这里插入图片描述

设置画布

fig = plt.figure(figsize=(30,15))

画图

我要画的是3行,1列共三个图
第一个子图(双y轴子图)

host = fig.add_subplot(311) #311表示3行1列里的第一个图
host.set_title(title)
host.set_xlabel("timestamp",fontsize =12)
host.set_ylabel("totle asset",fontsize =12)

如果第一个图是 双y轴,则:

par = host.twinx()
par.set_ylabel("cur Price",fontsize =12) #设置x、y标签的操作和主轴一样

第二个子图

ax2 = fig.add_subplot(312)
ax2.set_xlabel("timestamp",fontsize =12)
ax2.set_ylabel("amount",fontsize =12)

第三个子图

    ax3 = fig.add_subplot(313)
    ax3.set_xlabel("timestamp",fontsize =12)
    ax3.set_ylabel("amount",fontsize =12)
    par_3 = ax3.twinx()
    par_3.set_ylabel("transaction Price",fontsize =12)

画线

    asset_line_1, = host.plot(x,y1,label='asset_line')
    price_line_1, = par.plot(x,y2, color='red',label='price_line')
    host.legend(handles=[asset_line_1,price_line_1], labels=['asset_line','price_line'], loc=2)
    
    amount_line_2, = ax2.plot(x,amount,'co-',label='amount_line')

    asset_line_3, = ax3.plot(timestamp_3,asset_list_3,label='asset_line')
    amount_line_3, = ax3.plot(timestamp_3,amount_3,'co-',label='amount_line')
    price_line_3, = par_3.plot(timestamp_3,price_3, color='red',label='price_line')

展示各条线的情况legent

host.legend(handles=[asset_line_1,price_line_1], labels=['asset_line','price_line'], loc=2)
ax3.legend(handles=[asset_line_3, amount_line_3,price_line_3], labels=['asset_line','amount_line','price_line'], loc=2)

x轴标签旋转

for xtick in ax3.get_xticklabels():
    xtick.set_rotation(-45)

x轴标签(间隔)选取

host.xaxis.set_major_locator(plt.MultipleLocator(10))
ax2.xaxis.set_major_locator(plt.MultipleLocator(10))

画网格

plt.tight_layout()#紧凑布局
host.grid(which='major',axis="both",linewidth=0.75,linestyle='-',color='orange')
host.grid(which='minor',axis="both",linewidth=0.25,linestyle='-',color='orange')

ax3.grid(which='major',axis="both",linewidth=0.75,linestyle='-',color='orange')
ax3.grid(which='minor',axis="both",linewidth=0.25,linestyle='-',color='orange') 

对图像设置数字标签

设置数字标签
for a, b in zip(x, y1):
    host.text(a, b, "%.5f" % b, ha='center', va='bottom', fontsize=10)
for a, b in zip(x, y2):
    par.text(a, b, "%.5f" % b, ha='center', va='bottom', fontsize=10)
for a, b in zip(x, amount):
    host.text(a, b, b, ha='center', va='bottom', fontsize=10)

存储

plt.savefig(output_name)

完整代码

    #图片窗口
    fig = plt.figure(figsize=(30,15))

    host = fig.add_subplot(311)
    host.set_title(title)
    host.set_xlabel("timestamp",fontsize =12)
    host.set_ylabel("totle asset",fontsize =12)
    par = host.twinx()
    par.set_ylabel("cur Price",fontsize =12)

    ax2 = fig.add_subplot(312)
    ax2.set_xlabel("timestamp",fontsize =12)
    ax2.set_ylabel("amount",fontsize =12)

    ax3 = fig.add_subplot(313)
    ax3.set_xlabel("timestamp",fontsize =12)
    ax3.set_ylabel("amount",fontsize =12)
    par_3 = ax3.twinx()
    par_3.set_ylabel("transaction Price",fontsize =12)

    #画线
    asset_line_1, = host.plot(x,y1,label='asset_line')
    price_line_1, = par.plot(x,y2, color='red',label='price_line')
    host.legend(handles=[asset_line_1,price_line_1], labels=['asset_line','price_line'], loc=2)
    
    amount_line_2, = ax2.plot(x,amount,'co-',label='amount_line')

    asset_line_3, = ax3.plot(timestamp_3,asset_list_3,label='asset_line')
    amount_line_3, = ax3.plot(timestamp_3,amount_3,'co-',label='amount_line')
    price_line_3, = par_3.plot(timestamp_3,price_3, color='red',label='price_line')
    ax3.legend(handles=[asset_line_3, amount_line_3,price_line_3], labels=['asset_line','amount_line','price_line'], loc=2)
       
    # #设置坐标轴
    # host.set_xticklabels(labels=trade_date, fontsize=10,rotation=-90)
    for xtick in ax3.get_xticklabels():
        xtick.set_rotation(-45)

    #画网格
    # ax = plt.gca()
    host.xaxis.set_major_locator(plt.MultipleLocator(10))
    ax2.xaxis.set_major_locator(plt.MultipleLocator(10))
    # ax.xaxis.set_major_locator(ticker.MultipleLocator(2))
    # ax.xaxis.set_minor_locator(plt.MultipleLocator(.1))
    # ax.yaxis.set_major_locator(plt.MultipleLocator(1.0))
    # ax.yaxis.set_minor_locator(plt.MultipleLocator(.1))
    plt.tight_layout()#紧凑布局
    host.grid(which='major',axis="both",linewidth=0.75,linestyle='-',color='orange')
    host.grid(which='minor',axis="both",linewidth=0.25,linestyle='-',color='orange')

    ax3.grid(which='major',axis="both",linewidth=0.75,linestyle='-',color='orange')
    ax3.grid(which='minor',axis="both",linewidth=0.25,linestyle='-',color='orange') 

  
    # # 设置数字标签
    # for a, b in zip(x, y1):
    # host.text(a, b, "%.5f" % b, ha='center', va='bottom', fontsize=10)
    # for a, b in zip(x, y2):
    # par.text(a, b, "%.5f" % b, ha='center', va='bottom', fontsize=10)
    # for a, b in zip(x, amount):
    # host.text(a, b, b, ha='center', va='bottom', fontsize=10)
    # a = ScrollableWindow(fig)
    plt.savefig(output_name)

今天的文章【matplotlib】【绘制股票数据】子图的绘制、子图标签设置、双y轴分享到此就结束了,感谢您的阅读。

版权声明:本文内容由互联网用户自发贡献,该文观点仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 举报,一经查实,本站将立刻删除。
如需转载请保留出处:https://bianchenghao.cn/87761.html

(0)
编程小号编程小号

相关推荐

发表回复

您的电子邮箱地址不会被公开。 必填项已用 * 标注