How to create a kernel density plots using lattice package in R?

This recipe helps you create a kernel density plots using lattice package in R

Recipe Objective

How to create a kernel density using a lattice package in R? Kernel density plots are nothing but smoothed histogram plots. It is a data visualization tool used for plotting continuous variables. These plots help with visualizing the shape of the data properly i.e whether they are symmetric or skewed in nature. Lattice is a data visualization and graphics package in R. This recipe demonstrates an example on Kernel -Density plots.

Step 1 - Install necessary package and library

install.packages("lattice") library(lattice)

Step 2 - Generate random data for input vector

set.seed(1) x <- rnorm(100)

Step 3 - Plot a kernel density plot

Syntax - densityplot( ~ x, main , xlab) where, ~x - the formula for plotting density main - title for the graph xlab - tilte of the x axis ylab - default label - Density

densityplot(~ x, main = "Density plot", xlab = " x _values")
 " Output of the code is :"

What Users are saying..

profile image

Abhinav Agarwal

Graduate Student at Northwestern University
linkedin profile url

I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More

Relevant Projects

Text Classification with Transformers-RoBERTa and XLNet Model
In this machine learning project, you will learn how to load, fine tune and evaluate various transformer models for text classification tasks.

Image Segmentation using Mask R-CNN with Tensorflow
In this Deep Learning Project on Image Segmentation Python, you will learn how to implement the Mask R-CNN model for early fire detection.

MLOps Project on GCP using Kubeflow for Model Deployment
MLOps using Kubeflow on GCP - Build and deploy a deep learning model on Google Cloud Platform using Kubeflow pipelines in Python

MLOps Project for a Mask R-CNN on GCP using uWSGI Flask
MLOps on GCP - Solved end-to-end MLOps Project to deploy a Mask RCNN Model for Image Segmentation as a Web Application using uWSGI Flask, Docker, and TensorFlow.

Model Deployment on GCP using Streamlit for Resume Parsing
Perform model deployment on GCP for resume parsing model using Streamlit App.

Hands-On Approach to Causal Inference in Machine Learning
In this Machine Learning Project, you will learn to implement various causal inference techniques in Python to determine, how effective the sprinkler is in making the grass wet.

End-to-End Snowflake Healthcare Analytics Project on AWS-2
In this AWS Snowflake project, you will build an end to end retraining pipeline by checking Data and Model Drift and learn how to redeploy the model if needed

AWS MLOps Project to Deploy Multiple Linear Regression Model
Build and Deploy a Multiple Linear Regression Model in Python on AWS

Hands-On Approach to Master PyTorch Tensors with Examples
In this deep learning project, you will learn how to perform various operations on the building block of PyTorch : Tensors.

OpenCV Project to Master Advanced Computer Vision Concepts
In this OpenCV project, you will learn to implement advanced computer vision concepts and algorithms in OpenCV library using Python.

OSZAR »