Data Visualization using Python

Data Visualization is a representation of information in graphs, charts, maps, etc. It has made Visualizing complex data more straightforward and allows many to get a better idea of what is to be done for the improvements in their works. Python is one of the popular and powerful programming languages which has extensive library support. Thus, developers prefer Data Visualization using Python. Due to its flexible frameworks and libraries, Python is highly utilized for the development of many products. 

Data Visualization helps businesses to get meaningful insights. It allows them to understand various strategies very clearly. It converts a large amount of data or information into smaller visuals which saves time and provides a brief report that is easy to understand. It allows them to have a crisp report of what is required and what is done. Many technical works need data representation. Data Science sometimes requires data representation, and this can be achieved using Python. A large quantity of information and data can be analyzed with Data Visualization using Python. 

Exploratory Data Analysis (EDA) is one of the ideal methods in Data Science that allows you to better look at your data by visualizing them. It will enable you to see through your data and help you ensure there are no outliers or any missing values. EDA lets you reach your analysis more correctly and strategically. Python is the most preferred programming language as it has the two most valuable libraries called Matplotlib and Seaborn that allow you to visualize the data.

Matplotlib is considered one of the easy-to-use visualizing libraries in Python. It has many beneficial features that allow you to achieve Data Visualization successfully. NumPy arrays support Matplotlib. It can work on a broader SciPy stack and supports various plots like line, scatter, bar, histogram, and more. Pyplot, a sub-module of Matplotlib, also plays a crucial role in achieving Data Visualization using Python. Pyplot provides an interface like MATLAB and also functions that are easier to interact with the figure. 

The pyplot functions allow you to create a figure, mention the labels concerning the plot, and provide you with the plotting area in a figure. Matplotlib automatically takes care of the inbuilt default features. For example, it automatically gives you Figures and Axes. The Figure is a top-level container class that helps you with all the plots. It is a window on which everything is drawn. Figure object can be considered a box-like container that is capable of holding one or more axes. Axes are regarded as a basic class that allows one to create sub-plots with the help of flexible components. 

Matplotlib allows you to represent your data in a chart that helps you understand your data better and enables you to find errors, if any, and solve complex queries. Matplotlib can create animated, static, and interactive plots. In businesses, you will be surrounded by many data to sort and understand, which becomes slightly annoying with the default methods. With the help of Data Visualization, you will understand the data present better with lesser space and time. As Python has vast library support, you can now make use of Data Visualization using Python.

You can now access the Data Visualization tool Matplotlib through Jupyter Notebook. You can also access it through Python with the help of the Anaconda prompt. Another handy tool for Data Visualization using Python is Seaborn. Seaborn is a Python library. Matplotlib is an open-source library that provides you with a high-level API for Data Visualization using Python programming language. Seaborn will allow you to understand, grasp, and explore your data through Data Visualization using Python. Visualizing your data will enable you to get better insights and help you pop up with new ideas for your work. Representation lets you understand things better than the default state. 

Data Visualization also helps you focus on important key elements that are essential for good growth. Seaborn helps you with styling Matplotlib graphics and also allows you to visualize the univariate and bivariate data. It is also helpful in analyzing the linear regression models. You can now plot statistical time-series data with the help of Seaborn. Seaborn can work well with NumPy and Pandas data structures. If you know how Matplotlib works and are familiar with its features, it becomes easier for you to explore Seaborn more. 

DataFrames in Seaborn allows you to store data in the form of rectangular grids through which the data can be easily overviewed. Rows of the rectangular grid contain instance values, and columns are the vectors that contain the data for the specific variable. Thus, Rows of the DataFrame can include various data type values like numeric, logical, character, etc. These DataFrames can be accessed through the Pandas library. They are seen as two labeled data structures with potentially various types of columns.

Now you are aware that you can visualize your data easily with the help of tools like Matplotlib and Seaborn. These tools have their own advantages like Seaborn has better default color themes, and Matplotlib is more accessible for customization. It is easier to visualize the data but to make it presentable and easier to understand, you need additional features to make your data pleasant and straightforward. Visualization is known for its quantitative insights and communicating these insights to grab the audience’s attention. 

Effective Data Visualization is achieved through communication, design collide, and Data Science. Data Visualization is proved to be effective in simplifying the complex data sets into simple visualization and highlighting the right key insights. Data Visualization using Python has made it more accessible as many data scientists find it helpful to bring impactful insights and results. In this data-driven world, Data Visualization has proved to be very impactful. 

To understand Data Visualization using Python in-depth, enroll in Great Learning Academy’s Data Visualization using Python free course. Through this free course, you will get the theoretical knowledge and implement it through tools like Matplotlib and Seaborn. Hence, this free course is beneficial for those who are enthusiastic about learning Data Visualization using Python. Complete this free course and get the free certification today!