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Python Seaborn
4.45
Beginner level
1.5 learning hrs
Instructor:
Mr. Bharani Akella
Modules updated 07/2025
About this course
Data Visualization makes it so easy to work on abundant data. It presents the data in a simplified and easy-to-understand manner. Data visualization is useful for data cleaning, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modeling output, and presenting results. Libraries like Seaborn and Matplotlib do the same for us and it makes it easier to draw insights from abundant data and work accordingly on it. Seaborn being a top data visualization library, is a very important skill to have as an analyst. This course covers a variety of practical demonstrations of various plots in Python to help concrete your understanding on the same.
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Course outline
Introduction to Seaborn and Line Plot
Bar Plot in Seaborn
Scatterplot using Seaborn
Histograms and Jointplot
Working with Boxplots
Get access to the complete curriculum once you enroll in the course
4.45
What our learners enjoyed the most
Skill & tools
60% of learners found all the desired skills & tools
Our course instructor
Mr. Bharani Akella
Data Scientist
Machine Learning Expert
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What is Seaborn in Python used for?
Seaborn is a matplotlib-based open-source Python package. It is used for exploratory data analysis and data visualization. Data frames and the Pandas library are simple to deal with in Seaborn. The graphs that have been made can be readily altered.
Is Seaborn better than matplotlib?
Matplotlib is a graphical tool for data visualization in Python that works well with NumPy and Pandas. Pyplot has many of the same capabilities and syntax as MATLAB. As a result, it is simple to study for MATLAB users. Seaborn is better accustomed to working with Pandas data frames.
How do I get Seaborn in Python?
To install the latest release of seaborn, you can practice pip:
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pip installs seaborn.
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conda install seaborn.
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pip install.
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