{"id":3115,"date":"2020-02-08T08:32:44","date_gmt":"2020-02-08T08:32:44","guid":{"rendered":"https:\/\/www.askpython.com\/?p=3115"},"modified":"2023-02-16T19:57:16","modified_gmt":"2023-02-16T19:57:16","slug":"python-plotly-tutorial","status":"publish","type":"post","link":"https:\/\/www.askpython.com\/python-modules\/python-plotly-tutorial","title":{"rendered":"Python Plotly Tutorial"},"content":{"rendered":"\n

Python Plotly library<\/code> serves the purpose of Data Visualization<\/strong>. It helps in creating interactive, best-quality graphs online and can save them offline as well.<\/p>\n\n\n\n

Need for Plotly in Python<\/h2>\n\n\n\n

Plotly is useful in the field of statistical analysis, data visualization, etc. The outcome of the analysis and predictions can be presented in vivid forms using Plotly.<\/p>\n\n\n\n

Getting started with Python Plotly<\/h2>\n\n\n\n

In order to utilize the Plotly library, we first need to install it using the pip<\/code> command.<\/p>\n\n\n\n

Installation<\/h3>\n\n\n
\npip install plotly==4.5.0\n<\/pre><\/div>\n\n\n
\"Installation
Installation Of Plotly<\/figcaption><\/figure>\n\n\n\n
\n\n\n\n
Basic Charts in Python Plotly<\/h2>\n\n\n\n
Let’s dive into the functionalities served by the Plotly library of Python. This section covers some of the Basic Plotting techniques to serve the purpose of Data Visualization.<\/p>\n\n\n\n
1. Scatter plot<\/h3>\n\n\n\n
As the name suggests, it represents the data in a scattered format.<\/p>\n\n\n\n
We have used NumPy<\/a> to generate random values to be passed as input to the graph.<\/p>\n\n\n\n
Example:<\/strong><\/p>\n\n\n
\nimport plotly\nimport plotly.graph_objs as G\n\n\nimport numpy\n\nnum = 15\nx = numpy.random.randn(num)\ny = numpy.random.randn(num)\n\n# Create a trace\nfollow = G.Scatter(\n    x = random_x,\n    y = random_y,\n    mode = 'markers'\n)\noutput = [follow]\n\n\nplotly.offline.plot(output, filename='basic-scatter.html')\n\n<\/pre><\/div>\n\n\n
The plotly.graph<\/code> contains JSON object<\/code> which is a dict <\/code>like structure. By updating values of few keywords of this object, vivid kinds of graphs can be plotted.<\/p>\n\n\n\n
In the above snippet, plotly.graph’s JSON object is represented as G. Further,  we have used NumPy<\/code> to generate random values for the sake of providing input and plotting of data.<\/p>\n\n\n\n
object.Scatter()<\/code> is used to provide dimensional values i.e. create a trace and is useful to set other attributes that we feel like adding to the graph. <\/p>\n\n\n\n
The x and y parameters<\/strong> contain the values to be plotted on the x and y-axis.<\/p>\n\n\n\n
The parameter mode<\/code> determines the mode of representation<\/strong> of Scatter Plot. It can have any of the following values:<\/p>\n\n\n\n