You may use str() in order to check the data type of each DataFrame column in R:
str(dataframe name)
Next, I’ll review a simple example with the steps to:
- Create a DataFrame in R; and
- Check the data type of each column in the DataFrame
Steps to Check the Data Type of each DataFrame Column in R
Step 1: Create a DataFrame
To begin, create your DataFrame in R.
For example, I created the following DataFrame about 5 individuals:
df <- data.frame(name = c("Jon", "Bill", "Maria", "Ben", "Emma"),
age = c(23, 41, 32, 57, 38),
date_of_birth = as.Date(c("1997-05-21","1979-03-15","1988-11-08","1963-02-23","1982-09-12")),
employed = c(TRUE, FALSE, TRUE, TRUE, FALSE)
)
print(df)
This is how the DataFrame would look like once you run the code in R:
Step 2: Check the Data Type of each Column
Recall that you may use str() in order to check the data type of each column in your DataFrame:
str(dataframe name)
In our example, the DataFrame name is df.
Therefore, the complete code to check the data type for each column is:
df <- data.frame(name = c("Jon", "Bill", "Maria", "Ben", "Emma"),
age = c(23, 41, 32, 57, 38),
date_of_birth = as.Date(c("1997-05-21","1979-03-15","1988-11-08","1963-02-23","1982-09-12")),
employed = c(TRUE, FALSE, TRUE, TRUE, FALSE)
)
str(df)
You’ll now see the data type that corresponds to each column in the DataFrame:
Notice that the ‘name‘ column is represented as a Factor. You may then add the syntax of stringsAsFactors = FALSE to the DataFrame in order to represent that column as a character:
So the complete R code would look like this:
df <- data.frame(name = c("Jon", "Bill", "Maria", "Ben", "Emma"),
age = c(23, 41, 32, 57, 38),
date_of_birth = as.Date(c("1997-05-21","1979-03-15","1988-11-08","1963-02-23","1982-09-12")),
employed = c(TRUE, FALSE, TRUE, TRUE, FALSE), stringsAsFactors = FALSE
)
str(df)
You’ll now notice that the name column is represented as a character:
