How to define raw vectors in R?

How to define raw vectors in R?

How to define raw vectors in R?

This recipe helps you define raw vectors in R


Recipe Objective:

Vector is a type of object or data structure in R-language. They are designed to store multiple values of same data-type. For example: if you want to store different 50 food items for each cuisine, you don't need to create 50 variables for each cuisine but just a vector of length 50 of datatype character.

Note: It can not have a combination of any two datatype. It has to be homogeneous in nature.

This recipe demonstrates how to create a raw vector

Step 1: Creating a vector

We use combine function "c()" to create a vector

Case 1: Vector food_items with data of 3 different cuisine of character datatype

food_items = c("pasta", "burrito", "butter chicken") class(food_items)

Case 2: Vector no_of_children with data of 3 different people of numeric datatype

no_of_children = c(0,2,3) class(no_of_children)

Case 3: Vector that has both character and numeric values

mixed_values = c(1,3,'red') class(mixed_values)

We can see that the numeric values are type casted to character in this case and the homogeinity is maintained

Relevant Projects

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.

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.

German Credit Dataset Analysis to Classify Loan Applications
In this data science project, you will work with German credit dataset using classification techniques like Decision Tree, Neural Networks etc to classify loan applications using R.

Predict Churn for a Telecom company using Logistic Regression
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

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.

Zillow’s Home Value Prediction (Zestimate)
Data Science Project in R -Build a machine learning algorithm to predict the future sale prices of homes.

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.

Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Loan Eligibility Prediction using Gradient Boosting Classifier
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.