Ivy Jun 01, 2018 No Comments

Have an interview tomorrow? Facing last moment preparation issues? Well, we bring to you this Base R Cheat Sheet to ace up your chances of getting employed.

As Data Exploration and Data Manipulation takes most of the time, chances of being questioned as to how shall you deal with an unstructured data and manipulate them are high.

**Getting Started with Libraries**

*install.packages(“dplyr”) *

Allows download and install packages from the CRAN repository.

*library(dplyr) :*

Loads the package in the session in order to allow the use of the functions.

**Working Directory**

*getwd()*

To get the current location of the directory.

*setwd(“file path”)*

To change the current working directory.

**Reading and Writing Data**

*data <- read.csv(“file.csv”)*

To read or import data as a CSV file.

*write.csv(data, “file.csv”) *

To write or export data.

**Converting Data Types**

*as.logical*

To convert into the Boolean form

*as.numeric*

To convert to numeric

*as.factor*

To convert into factors

**Mathematical Functions**

*log(x)*

To calculate natural log.

*exp(x)*

To calculate exponential

*round(x,n)*

To round a number to n decimal places

*corr(x,y)*

To find a correlation between 2 variables

**Dealing with Data Frames**

*df <- data.frame(x = 6:10, y = c( ‘ a’, ‘b’, ‘c’)*

Creating a data frame

*df$x*

Accessing a column of a data frame

*view(df)*

To look at the whole data set

*dim(df)*

number of rows and columns in a data frame

*rbind*

binding rows

*cbind*

binding columns

**Dealing with strings**

*paste(x, y, sep =’ ‘)*

To join multiple vectors together

*grep(pattern, x)*

To find regular expression matches in x

*gsub(pattern, replace, x)*

To replace matches in x with a string

*toupper(x)*

To convert a string to upper case

*nchar(x)*

To find the number of characters in the string

**Plotting data**

*plot(x, y)*

Bivariate plot

*hist(x)*

Plotting a histogram

*barplot(x)*

Plotting bar plots

*pie(x)*

Plotting a piechart

*stripplot(x)*

Plotting values of x on a line (an alternative to boxplot for small values)

**Statistics**

*lm(formula, data=)*

Fitting a linear regression model

*glm(formula, data=, family=)*

Fitting a generalized linear model

*predict(fit)*

To predict on the fitted model

*fitted(fit)*

To obtain fitted values

Team Ivy

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