How Do I See the Structure of a Data Frame in R?


Angela Bailey

Are you working with data frames in R and want to get a better understanding of their structure? Well, you’re in luck! In this tutorial, we will delve into various methods to help you see the structure of a data frame in R. Let’s get started!

Using the str() Function

If you want a quick overview of your data frame, the str() function is your go-to tool. It stands for “structure” and provides valuable information about the variables contained within your data frame.

To use the str() function, simply pass your data frame as an argument:


This will display a compact summary of your data frame’s structure, including the variable names, their data types, and sample values. It’s a great way to get a high-level understanding of your dataset.

Viewing the Head and Tail

If you want to see a glimpse of what your data frame looks like, you can use the head() and tail() functions. These functions allow you to view the first few rows (head) or last few rows (tail) of your data frame.

To display the first six rows of your data frame, simply call:


If you’d rather see the last six rows instead, use:


List All Variables with names()

In some cases, you may want to extract just the names of the variables in your data frame. For this, you can use the names() function.

To get a list of all the variable names in your data frame, simply call:


This will return a character vector containing the names of all the variables in your data frame.

Inspecting Variable Types with typeof()

If you’re specifically interested in knowing the data types of each variable within your data frame, you can use the typeof() function.

To inspect the data types of all variables within your data frame, use:

sapply(your_data_frame, typeof)

This will provide you with a vector that displays the data type for each variable in your data frame.

Summary Statistics with summary()

If you want to obtain summary statistics for each variable in your data frame, the summary() function is here to help. It provides useful information such as minimum and maximum values, quartiles, and mean values.

To generate summary statistics for all variables within your data frame, simply call:


This will give you an overview of key statistics for each variable in your dataset.

In Conclusion

In this tutorial, we explored various methods to see the structure of a data frame in R. We learned about using functions like str(), head(), tail(), names(), typeof(), and summary() to obtain valuable insights into our data frames.

By employing these techniques, you can better understand the structure of your data frames and gain deeper insights into your datasets. Happy coding!

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