8天Python从入门到精通第十章 Python基础综合案例数据可视化 - 折线图可视化 10.6 创建折线图

我就是我 2024-03-27 13:40 23阅读 0赞

#### 8天Python从入门到精通 ####

[【黑马程序员python教程，8天python从入门到精通，学python看这套就够了】][python_8_python_python]

#### 文章目录 ####

*   *   *  8天Python从入门到精通
         *  第十章 Python基础综合案例 数据可视化 - 折线图可视化
         *   *  10.6 创建折线图
             *   *  10.6.1 导入模块
                 *  10.6.2 折线图相关配置项
                 *  10.6.3 全局配置选项

#### 第十章 Python基础综合案例 数据可视化 - 折线图可视化 ####

##### 10.6 创建折线图 #####

###### 10.6.1 导入模块 ######

导入模块：

![在这里插入图片描述][d6ebfae1a5fa464cbfc079c6d7961265.png_pic_center]

![在这里插入图片描述][266d49cb0fc6424ca1d4a763eb32f38d.png_pic_center]

###### 10.6.2 折线图相关配置项 ######

折线图相关配置项

<table> 
 <thead> 
  <tr> 
   <th><strong>配置项</strong></th> 
   <th><strong>作用</strong></th> 
   <th><strong>代码实例</strong></th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>init_opts</td> 
   <td>对折线图初始化设置宽高</td> 
   <td>init_opts=opts.InitOpts(width=“1600px”, height=“800px”)</td> 
  </tr> 
  <tr> 
   <td>.add_xaxis</td> 
   <td>添加x轴数据</td> 
   <td>.add_xaxis(列表)</td> 
  </tr> 
  <tr> 
   <td>.add_yaxis</td> 
   <td>添加y轴数据</td> 
   <td></td> 
  </tr> 
 </tbody> 
</table>

![在这里插入图片描述][154647ba278c42f5846c0750cfac2622.png_pic_center]

创建折线图

![在这里插入图片描述][c7b06faf877d4282be2b7351c186fae2.png_pic_center]

这里的Line()是构建类对象，我们先不必理解是什么意思，后续在Python高阶中进行详细讲解。

目前我们简单的会用即可

添加数据

![在这里插入图片描述][dba78f91476d4264b88015f14f46b44b.png_pic_center]

.add\_yaxis相关配置选项:

<table> 
 <thead> 
  <tr> 
   <th><strong>配置项</strong></th> 
   <th><strong>作用</strong></th> 
   <th><strong>代码实例</strong></th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>series_name</td> 
   <td>设置图例名称</td> 
   <td>series_name=“美国确诊人数”</td> 
  </tr> 
  <tr> 
   <td>y_axis</td> 
   <td>输入y轴数据</td> 
   <td>y_axis=[“列表”]</td> 
  </tr> 
  <tr> 
   <td>symbol_size</td> 
   <td>设置点的大小</td> 
   <td>symbol_size=10</td> 
  </tr> 
  <tr> 
   <td>label_opts</td> 
   <td>标签设置项：不显示标签</td> 
   <td>label_opts=opts.LabelOpts(is_show=False)</td> 
  </tr> 
  <tr> 
   <td>linestyle_opts</td> 
   <td>线条宽度和样式</td> 
   <td>linestyle_opts=opts.LineStyleOpts(width=2)</td> 
  </tr> 
 </tbody> 
</table>

![在这里插入图片描述][65d853b6efb6436eaf3718ef7a93f9cf.png_pic_center]

![在这里插入图片描述][4283d1eda8614aeb99c8948337eda099.png_pic_center]

![在这里插入图片描述][328d02c3bc6e4a5eaf6bd164e3936c91.png_pic_center]

###### 10.6.3 全局配置选项 ######

.set\_global\_opts全局配置选项:

<table> 
 <thead> 
  <tr> 
   <th><strong>配置项</strong></th> 
   <th><strong>作用</strong></th> 
   <th><strong>代码实例</strong></th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>title_opts</td> 
   <td>设置图标题和位置</td> 
   <td>title_opts=opts.TitleOpts(title=“标题”, pos_left=“center”)</td> 
  </tr> 
  <tr> 
   <td>yaxis_opts</td> 
   <td>y轴配置项</td> 
   <td>yaxis_opts=opts.AxisOpts(name=“累计确诊人数”)</td> 
  </tr> 
  <tr> 
   <td>xaxis_opts</td> 
   <td>x轴配置项</td> 
   <td>xaxis_opts=opts.AxisOpts(name=“时间”)</td> 
  </tr> 
  <tr> 
   <td>legend_opts</td> 
   <td>图例配置项</td> 
   <td>legend_opts=opts.LegendOpts(pos_left=‘70%’)</td> 
  </tr> 
 </tbody> 
</table>

![在这里插入图片描述][8696788fac234d028fc07728a5bdce1f.png_pic_center]

![在这里插入图片描述][e8bc36d18e9743fc8ab4f03d9345c819.png_pic_center]

![在这里插入图片描述][2d88ff837ce8433b9150f92574c2e46b.png_pic_center]

import json
    from pyecharts.charts import Line
    from pyecharts.options import *
    
    f_us = open("美国.txt", 'r', encoding="UTF-8")
    us_data = f_us.read()
    us_data = us_data.replace("jsonp_1629344292311_69436(", "")
    us_data = us_data[:-2]
    us_dict = json.loads(us_data)
    us_trend_data = us_dict["data"][0]["trend"]
    us_x_data = us_trend_data['updateDate'][:314]
    us_y_data = us_trend_data['list'][0]['data'][:314]
    
    f_jp = open("日本.txt", 'r', encoding="UTF-8")
    jp_data = f_jp.read()
    jp_data = jp_data.replace("jsonp_1629350871167_29498(", "")
    jp_data = jp_data[:-2]
    jp_dict = json.loads(jp_data)
    jp_trend_data = jp_dict["data"][0]["trend"]
    jp_x_data = jp_trend_data['updateDate'][:314]
    jp_y_data = jp_trend_data['list'][0]['data'][:314]
    
    f_in = open("印度.txt", 'r', encoding="UTF-8")
    in_data = f_in.read()
    in_data = in_data.replace("jsonp_1629350745930_63180(", "")
    in_data = in_data[:-2]
    in_dict = json.loads(in_data)
    in_trend_data = in_dict["data"][0]["trend"]
    in_x_data = in_trend_data['updateDate'][:314]
    in_y_data = in_trend_data['list'][0]['data'][:314]
    
    line = Line()
    line.add_xaxis(us_x_data)
    line.add_yaxis("美国确诊人数", us_y_data, label_opts=LabelOpts(is_show=False))
    line.add_yaxis("日本确诊人数", jp_y_data, label_opts=LabelOpts(is_show=False))
    line.add_yaxis("印度确诊人数", in_y_data, label_opts=LabelOpts(is_show=False))
    
    line.set_global_opts(
        title_opts=TitleOpts(title="2020年美日印三国新冠确诊人数对比折线图", pos_left='center', pos_bottom='1%'),
    
    )
    
    line.render()
    f_us.close()
    f_jp.close()
    f_in.close()

运行结果

![在这里插入图片描述][eb597e4a4ccb48c0988f66b07e91e83a.png_pic_center]

[python_8_python_python]: https://www.bilibili.com/video/BV1qW4y1a7fU
[d6ebfae1a5fa464cbfc079c6d7961265.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/52f52595e7734c20ac7df11f40101320.png
[266d49cb0fc6424ca1d4a763eb32f38d.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/22438e0d65ee4223bab1d37c36930196.png
[154647ba278c42f5846c0750cfac2622.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/5c59cc3cecb2456b80c7f171b2b05ee0.png
[c7b06faf877d4282be2b7351c186fae2.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/eaaa5a4fce6d4c06be98430130ce9924.png
[dba78f91476d4264b88015f14f46b44b.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/666791ccab32429a939725f7fb5af8c3.png
[65d853b6efb6436eaf3718ef7a93f9cf.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/892022deb032471682e1794ddaa7157d.png
[4283d1eda8614aeb99c8948337eda099.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/f3d27f38f4f244d4b4205c36d3d5ea9c.png
[328d02c3bc6e4a5eaf6bd164e3936c91.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/290de1eb527d4f82841156316ac88052.png
[8696788fac234d028fc07728a5bdce1f.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/4fd0b7b443e94a30a92512e37f2a2996.png
[e8bc36d18e9743fc8ab4f03d9345c819.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/f626cac52d254007a7ab29bfc2bb6251.png
[2d88ff837ce8433b9150f92574c2e46b.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/cfda2f30f1dd4f57bf421bf74824ec05.png
[eb597e4a4ccb48c0988f66b07e91e83a.png_pic_center]: https://image.dandelioncloud.cn/pgy_files/images/2024/03/27/bc8a4851e6ea4fb793d3c4b252eba41b.png