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# just turn it into a set and then convert again into a list
res = list(set(lst1)))
# now check the lengths of the two lists
print(len(res))
print(len(lst1))
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import numpy as np
def unique(list1):
npArray1 = np.array(list1)
uniqueNpArray1 = np.unique(npArray1)
return uniqueNpArray.tolist()
list1 = [10, 20, 10, 30, 40, 40]
unique(list1) # [10, 20, 30, 40]
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from collections import Counter
words = ['a', 'b', 'c', 'a']
Counter(words).keys() # equals to list(set(words))
Counter(words).values() # counts the elements' frequency
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df.groupby('param')['column'].nunique().sort_values(ascending=False).unique().tolist()
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# Approach 1: Using set
original_list = [1, 2, 3, 2, 4, 5, 1, 3, 3, 4, 5]
unique_list = list(set(original_list))
print(unique_list)
# Approach 2: Using a loop
original_list = [1, 2, 3, 2, 4, 5, 1, 3, 3, 4, 5]
unique_list = []
for element in original_list:
if element not in unique_list:
unique_list.append(element)
print(unique_list)
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mylist = ['nowplaying', 'PBS', 'PBS', 'nowplaying', 'job', 'debate', 'thenandnow']
myset = set(mylist)
print(myset)
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len(set(["word1", "word1", "word2", "word3"]))
# set is like a list but it removes duplicates
# len counts the number of things inside the set