Why this course?

Description

                                                         Data Visualization using python (Telugu)

 

 

Description:

Data visualization in Python is commonly achieved using libraries such as Matplotlib, Seaborn, Plotly, and Bokeh. These libraries provide a range of tools for creating static and interactive visualizations, allowing users to represent data in meaningful and insightful ways. Matplotlib is a versatile 2D plotting library, Seaborn is built for statistical graphics, Plotly enables interactive visualizations, and Bokeh is designed for interactive plots and dashboards. These libraries empower users to create a variety of charts, graphs, and plots to better understand patterns, trends, and relationships within their data.

 

Introduction Data Visualization using python:

Data visualization is a crucial aspect of the data analysis process, allowing individuals to communicate insights, patterns, and trends in a visually compelling way. Python, as a versatile and widely-used programming language, offers several powerful libraries for creating diverse and informative visualizations. In this introduction, we'll explore the fundamentals of data visualization in Python and highlight key libraries used for this purpose.

 

Data Visualization using python basis

Python offers a variety of libraries, such as Matplotlib, Seaborn, Plotly, and Bokeh, each with its strengths. This versatility allows users to create a wide range of static and interactive visualizations.

Libraries like Plotly and Bokeh enable the creation of interactive visualizations, allowing users to explore and interact with data dynamically. This feature is particularly valuable for building dashboards and conveying complex information effectively.

Creating a correlation matrix and visualizing it is a common task in data analysis and data visualization. In Python, you can use libraries such Seaborn

Modules of  Data Visualization using python:

Module: 1. Introduction of Data Visualization

Module: 2. Matplotlib libraries for visualization

Module: 3. Seaborn libraries for visualization