What is knitR?

This recipe explains what is knitR

Recipe Objective

What is knitR ? A knitR function takes an input file, extracts the R code from it and returns an output file. It is a dynamic report generalization package. Knitr integrates R code in various documents like the HTML files, Markdown, Latex etc. An example of kable() is taken, which uses the knitr package in R. This recipe demonstrates an example on knitr package.

Access Retail Price Recommendation ML Project with Source Code

Step 1 - Install necessary library

install.packages('knitr') library("knitr")

Step 2 - kable() in R

kable() is a function of knitr package, used for generating tables in R.

data = dimnames(iris3) # using the iris dataset head(data)

Step 3 - Converting into html format

html_file = kable(data,format="html") html_file # converting into html format

Step 4 - Converting into table format

tab = kable(head(data), format = "simple", row.names = TRUE) # converting to simple table format tab

What Users are saying..

profile image

Anand Kumpatla

Sr Data Scientist @ Doubleslash Software Solutions Pvt Ltd
linkedin profile url

ProjectPro is a unique platform and helps many people in the industry to solve real-life problems with a step-by-step walkthrough of projects. A platform with some fantastic resources to gain... Read More

Relevant Projects

Build a Logistic Regression Model in Python from Scratch
Regression project to implement logistic regression in python from scratch on streaming app data.

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.

Llama2 Project for MetaData Generation using FAISS and RAGs
In this LLM Llama2 Project, you will automate metadata generation using Llama2, RAGs, and AWS to reduce manual efforts.

Locality Sensitive Hashing Python Code for Look-Alike Modelling
In this deep learning project, you will find similar images (lookalikes) using deep learning and locality sensitive hashing to find customers who are most likely to click on an ad.

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.

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.

Time Series Forecasting with LSTM Neural Network Python
Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

Build a Autoregressive and Moving Average Time Series Model
In this time series project, you will learn to build Autoregressive and Moving Average Time Series Models to forecast future readings, optimize performance, and harness the power of predictive analytics for sensor data.

AWS MLOps Project to Deploy a Classification Model [Banking]
In this AWS MLOps project, you will learn how to deploy a classification model using Flask on AWS.

Build a Review Classification Model using Gated Recurrent Unit
In this Machine Learning project, you will build a classification model in python to classify the reviews of an app on a scale of 1 to 5 using Gated Recurrent Unit.