seaborn library python|Data Visualization in Python Using Seaborn(PART-1)|CodeWithTuqi
This video on 'Python #Seaborn Tutorial' is to educate you about data visualizations using Seaborn in #Python. Below are the topics covered in this video:
Introduction to Seaborn
Seaborn vs #Matplotlib
How to install Seaborn
Installing dependencies
Seaborn Plotting functions
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Seaborn is an amazing visualization library for statistical graphics plotting in Python. It provides beautiful default styles and color palettes to make statistical plots more attractive. It is built on the top of matplotlib library and is also closely integrated into the data structures from pandas.
Seaborn aims to make visualization the central part of exploring and understanding data. It provides dataset-oriented APIs so that we can switch between different visual representations for the same variables for a better understanding of the dataset.
Seaborn divides plot into the below categories
Relational plots: This plot is used to understand the relation between two variables.
Categorical plots: This plot deals with categorical variables and how they can be visualized.
Distribution plots: This plot is used for examining univariate and bivariate distributions
Regression plots: The regression plots in seaborn are primarily intended to add a visual guide that helps to emphasize patterns in a dataset during exploratory data analyses.
Matrix plots: A matrix plot is an array of scatterplots.
Multi-plot grids: It is a useful approach is to draw multiple instances of the same plot on different subsets of the dataset.
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Installation
For python environment :
!pip install seaborn
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