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Learning Objectives

  • Sort/Select Data in R
  • Logical Statements in R
  • cbind & rbind functions in R

Introduction

  • When working with a large data set, you might only be interested in a small portion of it. How do you sort through all the variables and observations and extract only the data that you need? R has several ways of sorting and selecting data in a process called "subsetting." Brackets in R lets you select or subset data from a vector, matrix, array, list, or data frame.
  • R's operators can be summarized as:
    • [ for subsets,
    • [[ for extracting items, and
    • $ for extracting by name.

Selecting a Subset From Dataset

We already have our dataset LungCapData loaded in the R environment. Let's say we want to see the details of male patients. We can select the required data, as shown in the screenshot.

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  • In the video coming up in the next slide, the tutor will discuss
    • Subsetting data from a vector and matrix in R
    • Subsetting data from a dataset with given conditions

True / False Indicator for Observations

Let's say we want to check if the observations satisfy the given conditions as TRUE or FALSE indicator. Suppose we want to create a TRUE/FALSE indicator vector for those who are female and they smoke. So if both the conditions satisfy, then return TRUE else FALSE.

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cbind

We can attach vectors or matrices in a column-wise fashion using the cbind command and in a row-wise fashion using the rbind command. Don't worry; you will get more clarity by seeing an example.

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rbind

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  • In the video coming up in the next slide, the tutor will discuss the following topics:
    • how to create a logical vector or variable in R Statistical Software
    • how to turn True or False indicators into 0's and 1's in R using the "as.numeric" function
    • how to use multiple logical statements within an R command/function to have a logical vector answering multiple questions (step-by-step example)
    • how to attach vectors or matrices in a column-wise fashion using the "cbind" function or in a row-wise fashion using the "rbind" function in R
    • two different ways of cleaning R's workspace: using RStudio's menu or "rm" command/function