Type the following solution in R-Code: The numbers below show the amount of snowfall for 10 days in 2010. 0.8, NA, 1.2, 12.9, 7.1, 0.7, 0.0, 3.3, 4.4, 10.8 Return a logical vector showing which elements are NA
Type the following solution in R-Code: The numbers below show the amount of snowfall for 10 days in 2010. 0.8, NA, 1.2, 12.9, 7.1, 0.7, 0.0, 3.3, 4.4, 10.8 Return a logical vector showing which elements are NA
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
YOU MUST SHOW A LOGICAL VECTOR FOR THIS QUESTION
R-PROGRAMMING

Transcribed Image Text:### R-Coding Exercise: Snowfall Data Analysis
**Objective:** Learn how to manipulate data and identify missing values using R.
**Task:** Type the following solution in R code.
#### Problem Description
The numbers below represent the amount of snowfall recorded over 10 days in the year 2010:
`0.8, NA, 1.2, 12.9, 7.1, 0.7, 0.0, 3.3, 4.4, 10.8`
**Your goal is to return a logical vector that identifies which elements are `NA` (missing values).**
#### Instructions
1. Create a numeric vector in R using the snowfall data provided.
2. Write a command to check for `NA` values within the vector.
3. Return the resulting logical vector.
This exercise will help you understand how to work with missing data in R, a critical skill in data analysis and statistical computing.
### Example Code
```r
# Step 1: Create a vector with the snowfall data
snowfall <- c(0.8, NA, 1.2, 12.9, 7.1, 0.7, 0.0, 3.3, 4.4, 10.8)
# Step 2: Identify NA values
na_vector <- is.na(snowfall)
# Step 3: Print the logical vector
print(na_vector)
```
This code will output a logical vector corresponding to each element in the original vector, indicating `TRUE` for `NA` values and `FALSE` for non-missing values.
Expert Solution

Step 1
Solution:
Given,
- Write R code for given amount of snow fall of 10 days
- Return a logical vector with position of elements which have "NA" elements
Step by step
Solved in 3 steps with 1 images
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