#3using the diamonds dataset, write in the line below the code necessary to keep all columns that contain the letter "c" in column name
#3using the diamonds dataset, write in the line below the code necessary to keep all columns that contain the letter "c" in column name
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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RStudio.
Task 5. See picture
![### R Programming Task: Diamonds Dataset
In this exercise, you will learn how to manipulate the `diamonds` dataset using R. The aim is to filter specific columns and create a new object for further analysis.
1. **Filter Columns by Name:**
- **Objective:** Write a line of code to select all columns containing the letter "c" in their column name.
- **Example Code Snippet:**
```r
diamonds_c <- diamonds[, grepl("c", names(diamonds))]
```
- **Explanation:** This line uses the `grepl` function to search for the letter "c" within the column names of the dataset and subsets those columns.
2. **Create a New Object:**
- **Task:** Assign the result of the above operation to a new object named `diamonds_c`. Ensure that this new object appears in your environment for further manipulation.
- **Example Code Snippet:**
```r
diamonds_c <- diamonds[, grepl("c", names(diamonds))]
```
#### Console Output:
- **R Version:** R 4.1.2
- **File Path:** ~/Desktop/omis665_rstudio/
- **Displayed Variables:**
- `x`, `y`, `z` are numeric vectors each containing 53,940 elements representing dimensions.
- **Example Content:**
- `x`: 3.95, 3.89, 4.05, 4.2, 4.34...
- `y`: 3.98, 3.84, 4.07, 4.23, 4.35...
- `z`: 2.43, 2.31, 2.31, 2.63, 2.75...
- **Error Message:**
- "Error: attempt to use zero-length variable name" indicates that you need to ensure that variable names are correctly assigned and exist within the dataset.
This guide will help you to efficiently work with the `diamonds` dataset, focusing on filtering and creating objects in R.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff353bebd-f6de-41dd-be51-0148c18c3381%2Fdd1696e9-eb14-4436-8f0c-3862bf9b7ec7%2Fn0psyr6_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### R Programming Task: Diamonds Dataset
In this exercise, you will learn how to manipulate the `diamonds` dataset using R. The aim is to filter specific columns and create a new object for further analysis.
1. **Filter Columns by Name:**
- **Objective:** Write a line of code to select all columns containing the letter "c" in their column name.
- **Example Code Snippet:**
```r
diamonds_c <- diamonds[, grepl("c", names(diamonds))]
```
- **Explanation:** This line uses the `grepl` function to search for the letter "c" within the column names of the dataset and subsets those columns.
2. **Create a New Object:**
- **Task:** Assign the result of the above operation to a new object named `diamonds_c`. Ensure that this new object appears in your environment for further manipulation.
- **Example Code Snippet:**
```r
diamonds_c <- diamonds[, grepl("c", names(diamonds))]
```
#### Console Output:
- **R Version:** R 4.1.2
- **File Path:** ~/Desktop/omis665_rstudio/
- **Displayed Variables:**
- `x`, `y`, `z` are numeric vectors each containing 53,940 elements representing dimensions.
- **Example Content:**
- `x`: 3.95, 3.89, 4.05, 4.2, 4.34...
- `y`: 3.98, 3.84, 4.07, 4.23, 4.35...
- `z`: 2.43, 2.31, 2.31, 2.63, 2.75...
- **Error Message:**
- "Error: attempt to use zero-length variable name" indicates that you need to ensure that variable names are correctly assigned and exist within the dataset.
This guide will help you to efficiently work with the `diamonds` dataset, focusing on filtering and creating objects in R.
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