Top 20 R Libraries for Data Science in 2018

LIBRARIES FOR DATA SCIENCE IN R
COMMITS CONTRIBUTORS FEATURES

Dplyr

powerful library for data wrangling
D ply r’  works with local data frames and remote database tables
precise and simple command syntax

Data.table

qurck aggregation of large data
data .tab’Le  laconic flexible syntax and a wide suite of useful functions
friendly file reader and parallel file writer

Lubridate

Set of functions to work with date and time format
lllhl datl easy and fast parsing of date-time data
expanded mathematical operations on time data

Jsonlite

robust and quick parsing JSON objects in R
Jsonllte   great tool for interacting with web APls and building pipelines
functions to stream, validate, and prettify JSON data
powerful implementation of the grammar of graphics visualization
developed static graphics system
m . takes care of plot specifications

Corrplot 

Abilities to visualize correlation matrices and confidence intervals
corrplot . contains algorithms to do matrix reordering
flexible appearance details settings

Ggvis

high-level visualization system
lattice – emphasis on multivariate data
efficiently copes with nonstandard requirements
rich features and plenty of available charts
web-based toolbox for building visualizations
plotly – abilities to make ggplot2 graphics interactive
implementation of an interactive grammar of graphic
E ggvrs – incorporates shiny reactive programming model and dplyr grammar of data transformation

DataTabIes

Displays R matrices and data frames as interactive HTML tables
DataTabIes – creates sortable tables with a minimum of code
many useful features and styling options for tables

rcharts

r 5 – interactive JS charts from R
rcharts- tools for creation, customization, and sharing

Knitr

transparent tool for easy dynamic report generation in R
enables integration of R code into LaTeX, LyX, HTML, Markdown, AsciiDoc, and
reStructuredText documents

Markdown

next generation implementation ofR Markdown based on pandoc
many static and dynamic output formats
abilities to define new formats for custom publishing requirements

Slidify

generates reproducible htmlS slides from r markdown
g snappy – allows embedded code chunks and mathematical formulas
rich sharing and customizing opportunities

Mlr

mlr – extensible framework for classification, regression, survival analysis, and clustering
easy extension mechanism through 53 inheritance

Xgboost

dm/c – implementation of the Gradient Boosted Decision Trees algorithm
XGBOOSt – reach tools for regression, classification, and ranking problems
high speed and performance

Caret

many mo es or c assi cation an regression
é caret – powerful tools and algorithms for creating predictive models

Gbm

3 ~ represents Generalized Boosted Regression Models
5 gbm ‘ includes plenty of regression methods
tools variable selection and final stage precision modeling

Prophet

high-quality forecasts for time series data
Prophet ° manages data that has multiple seasonality with linear or non-linear growth
robust to missing data, shifts in the trend, and large outliers

Randomforest

implements Breiman’s random forest algorithm for classification and regression
builds multiple decision trees and gives back the mean prediction ofthe individual trees

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