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What is Seaborn and why should we use seaborn?
There are many libraries in the Python programming language. Among them one of the libraries is the seaborn library. It is an open source library. Seaborn library is used to create the visualization of plots. This library uses the matplotlib library to visualize the plots. It has high visualization API. It is mainly used to work with the Data Analysis.
In the Seaborn library there are many default plots and styles to beautify the plot. It is collaborated with the features of the matplotlib library of python. It is also integrated with the pandas library data structures. The aim of the seaborn library is to understand and explore the data in a better way through the plots.
Types of plots in seaborn
It has different dataset API’s, so that we can change from one visualization to another with the same variables to have more understandability of the data. The seaborn library is used to plot the 2−d as well as 3− plots. All the Data Analyzing techniques and Machine learning algorithms easily plotted using the seaborn library plots.
It works very perfectly with data structures of Numpy and pandas libraries. There are multiple themes in the seaborn library and different category plots. They are as follows:
Relational plots − This plot is used to understand the relation between two variables
Categorical plots − This plot works with the categorical variable
Distribution plots − This plot is used to understand the univariate and bivariate distributions.
Regression plots − This plot is used to work with the regression variables
Matrix plots − This plot is with the array of scatterplots.
Multi −plot grid plots − This plot is used to work with multiple subsets of plots in the same plot.
We can easily customize the plots plotted using the seaborn library. We can plot very beautiful and understandable plots. We can use the seaborn in any operating system like windows, Linux, Mac OS etc.
To work with the seaborn library we should have the knowledge on the python programming language, basic understanding of data analysis, some experience with the matplotlib library and also knowledge on the pandas library.
For working with the seaborn library there are some dependencies. The main dependencies of the seaborn library are as follows.
Matplotlib
Numpy
Pandas
Scipy
Python
Reasons to use seaborn
The following are the reasons why we are going to use seaborn library when we have matplotlib library.
In seaborn there are wide varieties of themes available to plot, whereas in the matplotlib library we have the basic themes.
In Matplotlib library we have more numbers of plots like bar, scatter, pie, histogram etc., to visualize the data, in seaborn we have only limited plots.
To use more plots in seaborn we can combined and use the matplotlib library along with the seaborn library.
Seaborn takes care of the visualization of the data frames in pandas whereas the matplotlib library is mainly linked with the pandas and Numpy library and uses the graphic packages in data visualization.
Seaborn uses the default themes whereas the matplotlib library themes can be robust and customized.
Matplotlib is not that much organized and functional compared to the seaborn library.
The Seaborn library can be used effectively even for huge Data Frames whereas the matplotlib only works with the arrays and pandas.
Seaborn library is the Application Programming Interface used for plotting.
The knowledge of matplotlib is used to work with the seaborn library in an easier way.
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