Explain how to Box plot using seaborn?
This recipe explains how to Box plot using seaborn
Recipe Objective
Box plot using seaborn.
Box plot are the plot which is a visual representation of depicting groups of numerical data through their quartiles. Box plot summarizes the data using the 25th, 50th, and 75th percentiles. The plot is mainly used for detecting outliers.
Step 1 - Import the necessary library
import seaborn as sns
Step 2 - load the sample dataset
tips_data = sns.load_dataset('tips')
tips_data.head()
Step 3 - Plot the graph
sns.boxplot(x='size', y='total_bill', data=tips_data)
Here from the above figure: x - denotes which variable to be plot on x-axis y - denotes which variable to be plot on y-axis data - denotes the Sample data name that we have taken.
What Users are saying..
Gautam Vermani
Data Consultant at Confidential
Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic... Read More
Relevant Projects
Machine Learning Projects
Data Science Projects
Python Projects for Data Science
Data Science Projects in R
Machine Learning Projects for Beginners
Deep Learning Projects
Neural Network Projects
Tensorflow Projects
NLP Projects
Kaggle Projects
IoT Projects
Big Data Projects
Hadoop Real-Time Projects Examples
Spark Projects
Data Analytics Projects for Students
You might also like
Data Science Tutorial
Data Scientist Salary
How to Become a Data Scientist
Data Analyst vs Data Scientist
Data Scientist Resume
Data Science Projects for Beginners
Machine Learning Engineer
Machine Learning Projects for Beginners
Datasets
Pandas Dataframe
Machine Learning Algorithms
Regression Analysis
MNIST Dataset
Data Science Interview Questions
Python Data Science Interview Questions
Spark Interview Questions
Hadoop Interview Questions
Data Analyst Interview Questions
Machine Learning Interview Questions
AWS vs Azure
Hadoop Architecture
Spark Architecture
Relevant Projects
Build a Multi-Class Classification Model in Python on Saturn Cloud
In this machine learning classification project, you will build a multi-class classification model in Python on Saturn Cloud to predict the license status of a business.
Stock Price Prediction Project using LSTM and RNN
Learn how to predict stock prices using RNN and LSTM models. Understand deep learning concepts and apply them to real-world financial data for accurate forecasting.
Forecasting Business KPI's with Tensorflow and Python
In this machine learning project, you will use the video clip of an IPL match played between CSK and RCB to forecast key performance indicators like the number of appearances of a brand logo, the frames, and the shortest and longest area percentage in the video.
Build a Text Classification Model with Attention Mechanism NLP
In this NLP Project, you will learn to build a multi class text classification model with attention mechanism.
MLOps using Azure Devops to Deploy a Classification Model
In this MLOps Azure project, you will learn how to deploy a classification machine learning model to predict the customer's license status on Azure through scalable CI/CD ML pipelines.
Build Real Estate Price Prediction Model with NLP and FastAPI
In this Real Estate Price Prediction Project, you will learn to build a real estate price prediction machine learning model and deploy it on Heroku using FastAPI Framework.
Langchain Project for Customer Support App in Python
In this LLM Project, you will learn how to enhance customer support interactions through Large Language Models (LLMs), enabling intelligent, context-aware responses. This Langchain project aims to seamlessly integrate LLM technology with databases, PDF knowledge bases, and audio processing agents to create a comprehensive customer support application.
Build Deep Autoencoders Model for Anomaly Detection in Python
In this deep learning project , you will build and deploy a deep autoencoders model using Flask.
Learn How to Build a Linear Regression Model in PyTorch
In this Machine Learning Project, you will learn how to build a simple linear regression model in PyTorch to predict the number of days subscribed.
Learn to Build a Siamese Neural Network for Image Similarity
In this Deep Learning Project, you will learn how to build a siamese neural network with Keras and Tensorflow for Image Similarity.