【python】使用plotly生成图表数据

安装

在 ubuntu 环境下，安装 plotly 很简单
python 版本2.7+

pip install plotly

绘图

在 plotly 网站注册后，可以直接将生成的图片保存到网站上，便于共享保存。
这里使用离线的接口，生成的 html 保存在本地文件

绘制直线图

先随便搞一组数据用来绘制图表

1 lcd@ubuntu:~/$ cat gen_log.sh 
2 #!/bin/bash
3 count=$1
4 while [ $count -gt 0 ]
5 do
6   sar -n DEV 1 1 | grep "Average:" | grep "eth0" | awk \'{print $4,$5,$6}\'
7   count=$(($count-1))
8 done
9 lcd@ubuntu:~/$ sh gen_log.sh 1000 > log.txt

通过上述脚本，获取每秒钟网卡的3个数据，记录文本，利用 ploty 按时间绘制成直线图，实现如下：

 1 #!/usr/bin/env python
 2 import plotly.offline as pltoff
 3 import plotly.graph_objs as go
 4  
 5 def line_plots(name="line_plots.html"):
 6   dataset = {
 7     \'time\': [],
 8     \'rx\': [],
 9     \'tx\': [],
10     \'util\': []
11   }
12   with open("./log.txt") as f:
13     i = 0
14     for line in f:
15       items = line.split()
16       dataset[\'time\'].append(i)
17       dataset[\'rx\'].append(items[0])
18       dataset[\'tx\'].append(items[1])
19       dataset[\'util\'].append(items[2])
20       i += 1
21        
22   data_g = []
23   # 构建 time - rx 数据关系，折线图
24   tr_rx = go.Scatter(
25     x = dataset[\'time\'],
26     y = dataset[\'rx\'],
27     name = \'rx\')
28   data_g.append(tr_rx)
29  
30   tr_tx = go.Scatter(
31     x = dataset[\'time\'],
32     y = dataset[\'tx\'],
33     name = \'tx\')
34   data_g.append(tr_tx)
35  
36   tr_util = go.Scatter(
37     x = dataset[\'time\'],
38     y = dataset[\'util\'],
39     name = \'util\')
40   data_g.append(tr_util)
41  
42   # 设置图表布局
43   layout = go.Layout(title="Line plots",
44     xaxis={\'title\':\'time\'}, yaxis={\'title\':\'value\'})
45   fig = go.Figure(data=data_g, layout=layout)
46   # 生成离线html
47   pltoff.plot(fig, filename=name)
48  
49 if __name__==\'__main__\':
50   line_plots()

生成图表如下所示：

柱形图

 1 #!/usr/bin/env python
 2 import plotly.offline as pltoff
 3 import plotly.graph_objs as go
 4  
 5 def bar_charts(name="bar_charts.html"):
 6   dataset = {\'x\':[\'man\', \'woman\'],
 7         \'y1\':[35, 26],
 8         \'y2\':[33, 30]}
 9   data_g = []
10   tr_y1 = go.Bar(
11     x = dataset[\'x\'],
12     y = dataset[\'y1\'],
13     name = \'2016\'
14  
15   )
16   data_g.append(tr_y1)
17  
18   tr_y2 = go.Bar(
19   x = dataset[\'x\'],
20   y = dataset[\'y2\'],
21   name = \'2017\'
22  
23   )
24   data_g.append(tr_y2)
25   layout = go.Layout(title="bar charts",
26     xaxis={\'title\':\'x\'}, yaxis={\'title\':\'value\'})
27   fig = go.Figure(data=data_g, layout=layout)
28   pltoff.plot(fig, filename=name)
29  
30 if __name__==\'__main__\':
31   bar_charts()

饼状图

 1 #!/usr/bin/env python
 2 import plotly.offline as pltoff
 3 import plotly.graph_objs as go
 4  
 5 def pie_charts(name=\'pie_chart.html\'):
 6   dataset = {
 7     \'labels\':[\'Windows\', \'Linux\', \'MacOS\'],
 8     \'values\':[280, 10, 30]}
 9   data_g = []
10   tr_p = go.Pie(
11   labels = dataset[\'labels\'],
12   values = dataset[\'values\']
13  
14   )
15   data_g.append(tr_p)
16   layout = go.Layout(title="pie charts")
17   fig = go.Figure(data=data_g, layout=layout)
18   pltoff.plot(fig, filename=name)
19  
20 if __name__==\'__main__\':
21   pie_charts()

原文链接：http://www.jianshu.com/p/c2997494085b