Interested to Buy Any Domain ? << Click Here >> for more details...
How would you find the number of missing values in a dataset and remove all of them?
- 1 Answers
- 86 Views
- I also Faced
- E-Mail Answers
Answer / Sumit Srivastava
In R, you can use the `is.na()` function to find missing values, and then use the `na.omit()` function to remove them. Here's an example: nn```rndata <- data.frame(a = c(1, 2, NA, 4), b = c(NA, 5, 6, 7))n# Find number of missing valuesnn_miss <- sum(is.na(data))nprint(n_miss)nn# Remove rows with missing valuesndata_clean <- na.omit(data)n```
| Is This Answer Correct ? | 0 Yes | 0 No |
Why the function anova()?
Mention what does not ‘R’ language do?
What is the apply() family in r?
How can you simulate noise model using r?
How do you build and evaluate a random forest in r?
Explain what is t-tests in r?
What is mean in r?
How many tools for debugging present in r?
Why is clustering required in data analysis?
What are the different data structures in r? Briefly explain about them.
What is R lists?
What is the regular expression in R string manipulation?
C 
