Creating Scatter and Line Charts with Python Plotly: A Step-by-Step Tutorial

I spent two hours troubleshooting while learning Python and Plotly for data processing, eventually completing examples of a scatter plot and a line chart.

Because the official example uses online storage, it requires Jupyter (iPython) notebooks to handle generated files; initially I confused iplot with plot, which caused wasted time.

Important note: the latest Jupyter does not support Python 3.2 and earlier versions.

To work around the issue I switched to using local files. Below is the test code I used (the official code and offline storage code are commented out). This solution is suitable for the newest Python versions.

#!/usr/bin/python
# coding=utf-8

import plotly.plotly
import random
from plotly.graph_objs import *
import plotly.graph_objs as abc  # 必须
import numpy as np

def sayHello():
    N=100
    xx = []
    for i in range(20):
        xx.append(i)
    y0 = []
    for i in range(20):
        y0.append(random.randint(0, 10))
    y1 = []
    for i in range(20):
        y1.append(random.randint(10, 20))
    y2 = []
    for i in range(20):
        y2.append(random.randint(20, 30))
    data_1 = abc.Scatter(
        x=xx,
        y=y0,
        name='test1',
        mode='markers'
    )
    date_2 = abc.Scatter(
        x=xx,
        y=y1,
        name='test2',
        mode="lines"
    )
    date_3 = abc.Scatter(
        x=xx,
        y=y2,
        name='test3',
        mode="lines+markers"
    )
    data1 = Data([data_1, date_2, date_3])
    plotly.offline.plot(data1)
    #plotly.offline.iplot(data1,filename='test01')

if __name__ == "__main__":
    sayHello()

The final result is shown in the screenshot below.