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Python基于plotly模塊實(shí)現(xiàn)的畫圖操作示例

 更新時(shí)間：2019年01月23日 10:53:16   作者：云金杞  
這篇文章主要介紹了Python基于plotly模塊實(shí)現(xiàn)的畫圖操作,涉及Python基于plotly模塊的數(shù)值運(yùn)算與圖形操作相關(guān)實(shí)現(xiàn)技巧,需要的朋友可以參考下

本文實(shí)例講述了Python基于plotly模塊實(shí)現(xiàn)的畫圖操作。分享給大家供大家參考，具體如下：

import plotly
plotly.tools.set_credentials_file(username='tianjixuetu', api_key='xxxxxxxx')#此處要去官網(wǎng)申請(qǐng)自己的api，#https://plot.ly/ssu/


#案例1
import plotly.plotly as py
from plotly.graph_objs import *
trace0 = Scatter(
  x=[1, 2, 3, 4],
  y=[10, 15, 13, 17]
)
trace1 = Scatter(
  x=[1, 2, 3, 4],
  y=[16, 5, 11, 9]
)
data = Data([trace0, trace1])
py.plot(data, filename = 'basic-line')


#案例2
import plotly.graph_objs as go
import plotly.plotly as py
import numpy as np
colorscale = [[0, '#FAEE1C'], [0.33, '#F3558E'], [0.66, '#9C1DE7'], [1, '#581B98']]
trace1 = go.Scatter(
  y = np.random.randn(500),
  mode='markers',
  marker=dict(
    size='16',
    color = np.random.randn(500),
    colorscale=colorscale,
    showscale=True
  )
)
data = [trace1]
url_1 = py.plot(data, filename='scatter-for-dashboard', auto_open=False)
py.iplot(data, filename='scatter-for-dashboard')
url_1


#案例3
import plotly.plotly as py
import plotly.graph_objs as go
import numpy as np
x0 = np.random.randn(50)
x1 = np.random.randn(50) + 2
x2 = np.random.randn(50) + 4
x3 = np.random.randn(50) + 6
colors = ['#FAEE1C', '#F3558E', '#9C1DE7', '#581B98']
trace0 = go.Box(x=x0, marker={'color': colors[0]})
trace1 = go.Box(x=x1, marker={'color': colors[1]})
trace2 = go.Box(x=x2, marker={'color': colors[2]})
trace3 = go.Box(x=x3, marker={'color': colors[3]})
data = [trace0, trace1, trace2, trace3]
url_2 = py.plot(data, filename='box-plots-for-dashboard', sharing='public', auto_open=True,world_readable=True)
py.iplot(data, filename='box-plots-for-dashboard')
url_2

更多關(guān)于Python相關(guān)內(nèi)容感興趣的讀者可查看本站專題：《Python數(shù)學(xué)運(yùn)算技巧總結(jié)》、《Python數(shù)據(jù)結(jié)構(gòu)與算法教程》、《Python函數(shù)使用技巧總結(jié)》、《Python字符串操作技巧匯總》及《Python入門與進(jìn)階經(jīng)典教程》

希望本文所述對(duì)大家Python程序設(shè)計(jì)有所幫助。

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