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Introducing xda: R package for exploratory data analysis

June 17, 2016
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Introducing xda: R package for exploratory data analysis

This R package contains several tools to perform initial exploratory analysis on any input dataset. It includes custom functions for plotting the data as well as performing different kinds of analyses such as univariate, bivariate and multivariate investigation which is the first step of any predictive modeling pipeline. This package can be used to get

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Curated list of R tutorials for Data Science

June 3, 2016
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Curated list of R tutorials for Data Science

Here is topic wise list of R tutorials for Data Science, Time Series Analysis, Natural Language Processing and Machine Learning. This list also serves as a reference guide for several common data analysis tasks. The R Language Awesome-R Repository on GitHub R Reference Card: Cheatsheet R bloggers: blog aggregator R Resources on GitHub Awesome R

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Introduction to k-Means clustering in R

May 29, 2016
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Introduction to k-Means clustering in R

k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. I have provided below the R code to get started with k-means clustering in R. The dataset can be downloaded from here.    

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End to end Logistic Regression in R

May 29, 2016
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End to end Logistic Regression in R

Logistic regression, or logit regression is a regression model where the dependent variable is categorical. I have provided code below to perform end-to-end logistic regression in R including data preprocessing, training and evaluation. The dataset used can be downloaded from here.

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Codes for common Data Frame operations in R

May 29, 2016
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Codes for common Data Frame operations in R

Listed below are codes for some data frame operations that are good to have at your fingertips: Create an empty data.frame Sort a dataframe by column(s) Merge/Join data frames (inner, outer, left, right) Drop data frame columns by name Remove rows with NAs in data.frame Quickly reading very large tables as dataframes in R Drop

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Useful functions in R!

May 29, 2016
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Useful functions in R!

I have listed some useful functions below: with() The with( ) function applys an expression to a dataset. It is similar to DATA= in SAS. # with(data, expression) # example applying a t-test to a data frame mydata with(mydata, t.test(y ~ group)) Please look at other examples here and here. by() The by( ) function

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Some useful R cheatsheets

May 29, 2016
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Some useful R cheatsheets

Given below is a list of useful cheatsheets for R: Data Wrangling in R ggplot2 Cheatsheet Shiny Cheatsheet devtools Cheatsheet markdown Cheatsheet,  reference Data Exploration Cheatsheet  

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ggplot2 Version of Figures in “Lattice: Multivariate Data Visualization with R” (Part 1)

October 16, 2014
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ggplot2 Version of Figures in “Lattice: Multivariate Data Visualization with R” (Part 1)

Originally posted on Learning R: The data visualization package lattice is part of the base R distribution, and like ggplot2 is built on Grid graphics engine. Deepayan Sarkar’s (the developer of lattice) book Lattice: Multivariate Data Visualization with R gives a detailed overview of how the package works. All the figures and code used to…

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