R Language Questions et reponses d'entretien
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Question 6. Explain the use of the 'apply()' function in R.
The apply() function is used to apply a function to the rows or columns of a matrix or array.
Example:
apply(matrix, 1, sum)
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Question 7. What is the purpose of the 'merge()' function in R?
The merge() function is used to merge two or more data frames based on a common column.
Example:
merged_data <- merge(df1, df2, by='common_column')
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Question 8. Explain the concept of factor variables in R.
Factor variables are used to represent categorical data in R. They can have levels, which represent the categories.
Example:
gender <- factor(c('Male', 'Female', 'Male'), levels=c('Male', 'Female'))
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Question 9. How do you handle missing values in a data frame in R?
You can use the na.omit() function to remove rows with missing values, or use functions like is.na() to identify missing values.
Example:
cleaned_data <- na.omit(df)
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Question 10. Explain the purpose of the 'dplyr' package in R.
The 'dplyr' package provides a grammar of data manipulation, with functions like filter(), select(), and mutate(), making data manipulation tasks more intuitive.
Example:
library(dplyr)
filtered_data <- filter(df, Age > 25)
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