abkedar/seaborn_project

Introduction to Seaborn Visualization Project

Welcome to Seaborn visualization project , This project challenges you to understand and analyze data through visualization. One principal truth in the science of data is that breakthroughs are difficult if you don't intuitively "understand" the data. Visualization is important because it helps us to gain insights before making any assumptions or taking on false biases. We will see in the future how this also helps us in feature-selection.

What have we learnt so far?

• Data Visualization
• Various Libraries for data visualization
• Distribution Plots
• Scatter Plot
• Box Plot
• Factor plot
• Violin plot
• Count plot
• Swarm plot
• Bar plot

What are we going to do in the project?

• This project challenges you to manipulate large datasets without using conventional programming techniques to extract business insights.

How will completing this project help you ?

• Learn how to observe different pattern and draw conclusions over it.
• Learn to discover hidden insights.
• Learn feature importance that drives the target variable the most.

About the dataset

For this exercise, we will use the House Prices dataset, which we have already discussed in the session. The dataset contains SalePrice of around 1400 houses. The dataset is a part of a larger dataset. You can read about the dataset description .

Note :- include the line plt.switch_backend('agg') in every build.py