In this article, we will be understanding 3 ways to get unique values from a Python list. While dealing with a huge amount of raw data, we often come across situations wherein we need to fetch out the unique and non-repeated set of data from the raw input data-set.
The methods listed below will help you solve this problem. Let’s get right into it!
Either of the following ways can be used to get unique values from a list in Python:
As seen in our previous tutorial on Python Set, we know that Set stores a single copy of the duplicate values into it. This property of set can be used to get unique values from a list in Python.
Syntax:
set(input_list_name)
Syntax:
list(set-name)
Example:
list_inp = [100, 75, 100, 20, 75, 12, 75, 25]
set_res = set(list_inp)
print("The unique elements of the input list using set():\n")
list_res = (list(set_res))
for item in list_res:
print(item)
Output:
The unique elements of the input list using set():
25
75
100
20
12
In order to find the unique elements, we can apply a Python for loop along with list.append() function to achieve the same.
Syntax:
list.append(value)
Example:
list_inp = [100, 75, 100, 20, 75, 12, 75, 25]
res_list = []
for item in list_inp:
if item not in res_list:
res_list.append(item)
print("Unique elements of the list using append():\n")
for item in res_list:
print(item)
Output:
Unique elements of the list using append():
100
75
20
12
25
Python NumPy module has a built-in function named, numpy.unique to fetch unique data items from a numpy array.
Syntax:
numpy.array(list-name)
Syntax:
numpy.unique(numpy-array-name)
Example:
import numpy as N
list_inp = [100, 75, 100, 20, 75, 12, 75, 25]
res = N.array(list_inp)
unique_res = N.unique(res)
print("Unique elements of the list using numpy.unique():\n")
print(unique_res)
Output:
Unique elements of the list using numpy.unique():
[12 20 25 75 100]
In this article, we have unveiled various ways to fetch the unique values from a set of data items in a Python list.
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