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Most popular R Packages Every Analytics Career Enthusiasts Should Be Aware Of

Most Widely Used Tools In Hadoop Ecosystem For Crunching Big Data

The prominence of R programming language is well known by every analytics professional. R programming is one among the most extensively used programming languages in Data Science & Machine Learning applications.

Most of the budding analytics career enthusiasts are planning to learn R among the other programming languages for Data Science & Machine Learning. The main reason for this is that by mastering the skills in R it would become a bit easier towards understanding the core concepts of Data Science, Data Manipulation, Data Visualization & as well as Machine Learning. Learning R programming will take the analytics aspirants a step closer to their dream job of becoming Data Scientists or Machine Learning experts.

Here below is the list of most popular R packages which every analytics career enthusiast should be aware of


Lattice can be interpreted as a powerful and elegant high-level data visualization package for R. It has mainly been designed with the ability to display multivariate relationships and in particular allows easy conditioning to produce “small multiple” plots. Lattice is sufficient for typical graphics needs & also handling most of the nonstandard requirements have become quite effective with Lattice.


Exploratory Data Analysis (EDA) is the initial & foremost important process in data analysis & or predictive modeling phase. Automated data exploration helps the data modelers to set their focus on understanding data and extracting insights & helps them in generating relevant hypotheses. This package is very much capable of scanning & analyzing each variable & can visualize them with easily visible graphical techniques. It aims at automating the regular tasks like data handling & visualization so that data modelers could focus on studying the data and extracting insights.

Dalex (Descriptive mAchine Learning EXplanations)

In most of the complex data analysis applications data modelers must need to understand or prove how input variables could be used in the model & how would they impact on the overall final model prediction. DALEX comprises a set of complex tools in R programming that helps to understand how complex models are working.


dplyr is a is one among the most efficiently used R-package that helps in transforming & summarizing tabular data with rows and columns. dplyr functions can perform data manipulation operations such as filtering for rows, selecting specific columns, re-ordering rows, adding new columns and summarizing data. It is performs several other advanced functions.


With the aid of Esquisse, exploring vast amount of data to extract information can be done precisely & swiftly. This R package helps the modelers to draw bar graphs, curves, scatter plots, histograms, then export the graph or retrieves the code generating the graph.

Apart from these other set of most extensively used packages in the R programming are caret, janitor, rpart, Matrix, prophet, plyr, plotly, gimnet & many more.

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