How to create a strip chart using lattice package in R?

How to create a strip chart using lattice package in R?

How to create a strip chart using lattice package in R?

This recipe helps you create a strip chart using lattice package in R

Recipe Objective

How to create a strip chart using lattice package in R ? A strip chart is a variant of scatter plot where the categorical data is plotted on the X axis Strip charts are useful for plotting small data sets. It shows the variability of the data , whether they are spread or gathered. A term called jitter is used in the syntax which spreads out the data points gathered at a place for better visualization Lattice is a data visualization and graphics package in R - graph_type(formula, data) This recipe demonstrates an example on strip chart.

Step 1 - Install necessary package and library

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

Step 2 - Create a random data

set.seed(1) x <- round(runif(100)) y <- x + rnorm(100) print(x) print(y)

Step 3 - Plot a strip plot

syntax - stripplot(y ~ x,data,main,xlab,ylab) x,y - input variables. data - the input data main - the title of the chart xlab - the title of the x axis ylab - the title of the y axis

stripplot(x ~ y ,main = "Strip chart", xlab = "x_value", ylab = "y_value") # without jitter stripplot(x ~ y , = TRUE ,main = "Strip chart", xlab = "x_value", ylab = "y_value") # with jitter

Relevant Projects

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.

Topic modelling using Kmeans clustering to group customer reviews
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.

Ola Bike Rides Request Demand Forecast
Given big data at taxi service (ride-hailing) i.e. OLA, you will learn multi-step time series forecasting and clustering with Mini-Batch K-means Algorithm on geospatial data to predict future ride requests for a particular region at a given time.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

NLP and Deep Learning For Fake News Classification in Python
In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.

Customer Market Basket Analysis using Apriori and Fpgrowth algorithms
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.

Expedia Hotel Recommendations Data Science Project
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.

Abstractive Text Summarization using Transformers-BART Model
Deep Learning Project to implement an Abstractive Text Summarizer using Google's Transformers-BART Model to generate news article headlines.

Predict Credit Default | Give Me Some Credit Kaggle
In this data science project, you will predict borrowers chance of defaulting on credit loans by building a credit score prediction model.

Machine learning for Retail Price Recommendation with Python
Use the Mercari Dataset with dynamic pricing to build a price recommendation algorithm using machine learning in Python to automatically suggest the right product prices.