python實現(xiàn)數(shù)據(jù)圖表

2020-01-04 17:05:41

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來源：轉(zhuǎn)載

供稿：網(wǎng)友

平時壓力測試，生成一些數(shù)據(jù)后分析，直接看 log 不是很直觀，前段時間看到公司同事分享了一個繪制圖表python/142942.html">python 模塊 : plotly，覺得很實用，利用周末時間熟悉下。

python,數(shù)據(jù)圖表,plotly,python繪制圖表
plotly

plotly 主頁： https://plot.ly/python/

安裝

在 ubuntu 環(huán)境下，安裝 plotly 很簡單
python 版本2.7+

$ sudo pip install plotly

繪圖

在 plotly 網(wǎng)站注冊后，可以直接將生成的圖片保存到網(wǎng)站上，便于共享保存。
這里使用離線的接口，生成的 html 保存在本地文件

繪制直線圖

先隨便搞一組數(shù)據(jù)用來繪制圖表

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

通過上述腳本，獲取每秒鐘網(wǎng)卡的3個數(shù)據(jù)，記錄文本，利用 ploty 按時間繪制成直線圖，實現(xiàn)如下：

#!/usr/bin/env pythonimport plotly.offline as pltoffimport plotly.graph_objs as godef line_plots(name="line_plots.html"):  dataset = {    'time': [],    'rx': [],    'tx': [],    'util': []  }  with open("./log.txt") as f:    i = 0    for line in f:      items = line.split()      dataset['time'].append(i)      dataset['rx'].append(items[0])      dataset['tx'].append(items[1])      dataset['util'].append(items[2])      i += 1        data_g = []  # 構(gòu)建 time - rx 數(shù)據(jù)關(guān)系，折線圖  tr_rx = go.Scatter(    x = dataset['time'],    y = dataset['rx'],    name = 'rx')  data_g.append(tr_rx)  tr_tx = go.Scatter(    x = dataset['time'],    y = dataset['tx'],    name = 'tx')  data_g.append(tr_tx)  tr_util = go.Scatter(    x = dataset['time'],    y = dataset['util'],    name = 'util')  data_g.append(tr_util)  # 設(shè)置圖表布局  layout = go.Layout(title="Line plots",    xaxis={'title':'time'}, yaxis={'title':'value'})  fig = go.Figure(data=data_g, layout=layout)  # 生成離線html  pltoff.plot(fig, filename=name)if __name__=='__main__':  line_plots()

生成圖表如下所示：

python,數(shù)據(jù)圖表,plotly,python繪制圖表
line_plot

柱形圖

#!/usr/bin/env pythonimport plotly.offline as pltoffimport plotly.graph_objs as godef bar_charts(name="bar_charts.html"):  dataset = {'x':['man', 'woman'],        'y1':[35, 26],        'y2':[33, 30]}  data_g = []  tr_y1 = go.Bar(    x = dataset['x'],    y = dataset['y1'],    name = '2016'  )  data_g.append(tr_y1)  tr_y2 = go.Bar(  x = dataset['x'],  y = dataset['y2'],  name = '2017'  )  data_g.append(tr_y2)  layout = go.Layout(title="bar charts",    xaxis={'title':'x'}, yaxis={'title':'value'})  fig = go.Figure(data=data_g, layout=layout)  pltoff.plot(fig, filename=name)if __name__=='__main__':  bar_charts()

python,數(shù)據(jù)圖表,plotly,python繪制圖表

bar char

餅狀圖

#!/usr/bin/env pythonimport plotly.offline as pltoffimport plotly.graph_objs as godef pie_charts(name='pie_chart.html'):  dataset = {    'labels':['Windows', 'Linux', 'MacOS'],    'values':[280, 10, 30]}  data_g = []  tr_p = go.Pie(  labels = dataset['labels'],  values = dataset['values']  )  data_g.append(tr_p)  layout = go.Layout(title="pie charts")  fig = go.Figure(data=data_g, layout=layout)  pltoff.plot(fig, filename=name)if __name__=='__main__':  pie_charts()

python,數(shù)據(jù)圖表,plotly,python繪制圖表