How to do annotation with ggplot2?
MACHINE LEARNING RECIPES DATA CLEANING PYTHON DATA MUNGING PANDAS CHEATSHEET     ALL TAGS

How to do annotation with ggplot2?

How to do annotation with ggplot2?

This recipe helps you do annotation with ggplot2

0

Recipe Objective

How to do annotation with ggplot2? An annotation is a note/ text written to provide information about particular data in any given plot i.e it provides metadata for the plots. In data visualization, metadata is very important as it provides us with additional important information for the plots. geom_text () and geom_line () are used for adding annotations over any plot using ggplot. This recipe demonstrates an example of annotations with ggplot2.

Step 1 - Install necessary library

library(ggplot2)

Step 2 - Define a dataframe

# time series graph of random numbers over a period of 12 time units. data <- data.frame(x_value = c(2,3,5,6,3), y_value = c(8,7,2,6,4), labels = c("pt-A","pt-B","pt-C","pt-D","pt-E") ) print(data)

Step 3 - Plot a graph with annotations

Using the geom_text and geom_label to add annotations to our plot. Here the ggplot **syntax is — ggplot (data, aes (x,y) + geom_point ()+ geom_text ()+ geom_label)** where, data — input data aes (x,y) — the aes function — creates mapping from data to geom geom_point — geometric object for plotting points geom_text — for writing text in the plot geom_label — for giving labels to the data points

ggplot(data, aes(x_value,y_value)) + geom_point() + geom_text(aes(label = paste0("(", x_value,y_value, ")")), nudge_y = -0.25) + xlim(1, 10)+ geom_label(data = data, aes(label = labels))

Relevant Projects

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.

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.

Mercari Price Suggestion Challenge Data Science Project
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.

Customer Churn Prediction Analysis using Ensemble Techniques
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.

Predict Employee Computer Access Needs in Python
Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

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.

Machine Learning project for Retail Price Optimization
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

Predict Macro Economic Trends using Kaggle Financial Dataset
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.

Data Science Project-TalkingData AdTracking Fraud Detection
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.