# Extracting Unique Rows from NumPy Array

NumPy provides a powerful array object, called ndarray, which is used to store homogeneous data in a multi-dimensional array. In some cases, we may need to extract unique rows from a two-dimensional NumPy array. In this article, we will discuss how to extract unique rows from a two-dimensional NumPy array using various approaches, which are mentioned below:

#### 1. Using “np.unique()” function:

• Imports the NumPy library and creates a 2D NumPy array.
• Applies the `np.unique()` function to the input array, specifying the axis as `0`.
• Function returns the sorted unique rows of the array.
• The resulting array is printed to the console.
• Code returns an array with only the unique rows of the input array, sorted in ascending order and in a sorted manner.

#### 2. Using “set() and map()” functions:

• imports the NumPy library and creates a 2D NumPy array.
• converts each row of the array into a tuple using the `map()` function and stores the result in a list.
• code then extracts the unique tuples from the list using the `set()` function.
• Finally, the unique tuples are converted back to a NumPy array and printed to the console.
• Here, your output won’t be sorted.
• This code returns an array with only the unique rows of the input array, sorted in arbitrary order, by converting the rows into tuples and using the `set()` function.

#### 3. Using “pandas DataFrame”:

• imports the NumPy and pandas libraries and creates a 2D NumPy array.
• then converts the array to a pandas DataFrame using the `pd.DataFrame()` function.
• code drops the duplicate rows of the DataFrame using the `drop_duplicates()` function and stores the result in a new DataFrame.
• Finally, the unique DataFrame is converted back to a NumPy array and printed to the console.
• Even here, your output won’t be sorted.
• This code returns an array with only the unique rows of the input array, sorted in the order they appear, by converting the array to a pandas DataFrame and using the `drop_duplicates()` function.
1 Like