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Introduction to Plotly-online using Python
  • Difficulty Level : Basic
  • Last Updated : 02 Feb, 2021

The plotly library is an interactive open-source library. This can be a very helpful tool for data visualization and understanding the data simply and easily. Plotly graph objects are a high-level interface to plotly which are easy to use. It can plot various types of graphs and charts like scatter plots, line charts, bar charts, box plots, histograms, pie charts, etc. 

Python is also capable of uploading created graph online for use in websites. In this article, a simple scatter plot is created to be used in websites and this graph is working on the particular website that is the beauty of plotly and chart-studio.

Installation:

pip install plotly
pip install chart-studio             

Approach:

Part A: Creating a graph 

  • Import module
  • Create data
  • Create plot
  • Display graph

Part B: Taking the graph online

  • Login/Signup in Chart Studio.
  • After signing in find your username and API key in the settings section. (go to profile > settings > regenerate key)
  • Now in your python script
    • Again import module
    • Pass API keys and username
    • Pass all the necessary information to plot() function
  • The output returned is a link, where the graph can be seen live.

Below is the implementation.



Python3




# importing required libraries
import numpy as np
import plotly
import chart_studio
import plotly.express as px
  
# assigning values to x and y
x = np.random.randint(low=1, high=50, size=50)
y = np.random.randint(low=51, high=100, size=50)
  
# creating and displaying graph
fig = px.scatter(x=x, y=y)
fig.show()

 Output:

Graph Between X and Y generated in Plotly

              

                      

Now as our graph is created. It’s time to use it online on websites. 

Python3




import chart_studio
username =  # 'your username'
api_key =  # 'your api key'
  
chart_studio.tools.set_credentials_file(username=username, api_key=api_key)
  
py.plot(fig, filename='your filename', auto_open=False, sharing='public')

Output:

‘https://plotly.com/~username/graph number/’

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