Data Visualization Using Plotly 

What type of projects or assignments help looking for?​

  • Assignment or Project Help

  • Online Training and Mentorship

  • New Idea or project

  • Existing project that need more resources

What is Plotly?

The Plotly visualization tool was built around 2013 using Python and the Django framework, with a front end using JavaScript and the visualization library D3.js, HTML, and CSS.

We are creating Beautiful and Insight chart

If you are looking beautiful and insight chart then our Codersarts team fulfill your need and do better than then other services.

In reallife it is used to create the dashboards which is used in different industries

Installing Plotly Using pip

To install the Plotly library using the "pip" utility, you need to execute the following command:


>>pip install plotly

We can create different types of visualization using plotly

If you are looking help in different types of visualization like: Line Plot, Bar Plot, Box Plot, etc. here you better scratch code to create these visualization using plotly.

Advantages Of Plotly?

  • It lets you create interactive visualizations built using D3.js without even having to know D3.js.

  • It provides compatibility with number of different languages/ tools like R, Python, MATLAB, Perl, Julia, Arduino.

  • Using plotly, interactive plots can easily be shared online with multiple people.

  • Plotly can also be used by people with no technical background for creating interactive plots by uploading the data and using plotly GUI.

  • Plotly is compatible with ggplots in R and Python.

  • It allows to embed interactive plots in  projects or websites using iframes or html.

  • The syntax for creating interactive plots using plotly is very simple as well.

Steps for creating plots in Plotly

  • Getting the data to be used for creating visualization and preprocesisng it to convert it into the desired format.

  • Calling the plotly API in the language/ tool of your choice.

  • Creating the plot by specifying objectives like the data that is to be represented at each axis of the plot, most appropriate plot type (like histogram, boxplots, 3D surfaces), color of data points or line in the plot and other features. Here’s a generalized format for basic plotting in R and Python:

In R:

>> plot_ly( x , y ,type,mode,color ,size )

In Python:

>> plotly.plotly( [plotly.graph_objs .type(x ,y ,mode , marker = dict(color ,size ))]