Data Visualization makes it so easy to work on abundant data. Seaborn is a Python library which is used for making statistical graphics in Python. Seaborn is a Python data visualization library based on Matplotlib. Seaborn helps you explore and understand your data. It provides a high-level interface for drawing attractive and informative statistical graphics.

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.

- 00:00 - SeaBorn Python Tutorial
- 00:40 - SeaBorn Line Plot
- 09:00 - SeaBorn Bar Plot
- 16:47 - SeaBorn Scatterplot
- 22:02 - SeaBorn Histogram/Distplot
- 28:28 - SeaBorn JointPlot
- 31:58 - SeaBorn BoxPlot

Seaborn is a Python library which is used for making statistical graphics in Python. It is built on top of Matplotlib and integrates closely with pandas data structures. Seaborn is a Python data visualization library based on Matplotlib. Seaborn helps you explore and understand your data. It provides a high-level interface for drawing attractive and informative statistical graphics.

Seaborn is a library that uses Matplotlib underneath to plot graphs. It is used to visualize random distributions. Seaborn is one of the most amazing Python libraries. Want to know more about this interesting library? Then do watch the python tutorial till the end.

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

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This Data Science with Python Tutorial will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python.