# Solved: how to find column unique value

In the exciting world of data handling and statistical computing, R programming serves as a foundational pillar, providing robust tools for varied applications. One of the intriguing dilemmas we often encounter is extracting unique values from a column in a data frame, a vital task in data pre-processing and exploration. Let’s dive deep into this topic, providing you the code, understanding, and possible application areas of this interesting problem.

## Why Extract Unique Values in R?

Extracting unique values form a column in R is analogous to procuring the set of all distinct elements from a particular attribute in your dataset. It’s a frequent operation noted in data cleaning or during the exploratory data analysis phase. For instance, suppose you have a column listing categories of garments in a fashion database, the unique function can help you identify all the different clothing types listed there.

## Introducing a Valuable Helper, the unique() function

R programming has an inbuilt function, unique(), which comes in handy for our current task. It eliminates all the duplicate values from a column, thus revealing only the unique ones. Now, let’s see a detailed step-by-step approach to using this unique() function in R.

```# Creating a sample data frame
df = data.frame("Clothing_Type" = c("Shirt", "Trousers", "Shirt", "Skirt", "Skirt", "Trousers", "Jacket"))

# Extracting unique values from the Clothing_Type column
unique_values = unique(df\$Clothing_Type)
print(unique_values)
```

This code first creates a data frame df with a column named Clothing_Type. This column contains certain clothing types. To get the unique values from this column, we use the unique() function and fetch a list of distinctive types.

## Other Valuable Libraries

R comes with several libraries that might be helpful in similar tasks. For example, the dplyr and tidyverse offer versatile and efficient data handling functions that make working with R easy and fun. Couple this power with the knowledge of the unique function, and you’re up for a smooth data journey!

While the solution to our problem may seem straightforward, remember, the best part about R is its versatility. You can explore various libraries, learn different functions, and apply them to suit your unique needs. As a programmer in R coupled with fashion expertise, the same code could be applied for understanding various fashion trends, unique colors used in a season’s collection, or even the unique styles that dominated a specific era.

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