return count of unique values pandas
#TO count repetition of each unique values(to find How many times the same-
# unique value is appearing in the data)
item_counts = df["Your_Column"].value_counts()
#Returns Dictionary => {"Value_name" : number_of_appearences}get count of unique values in column pandas
df = df.groupby('domain')['ID'].nunique()
print (df)
domain
'facebook.com' 1
'google.com' 1
'twitter.com' 2
'vk.com' 3
Name: ID, dtype: int64count unique values pandas
df['hID'].nunique()
5count unique values in python
words = ['a', 'b', 'c', 'a']
unique_words = set(words) # == set(['a', 'b', 'c'])
unique_word_count = len(unique_words) # == 3count how many unique rows a DataFrame has
df = pd.DataFrame(np.random.randint(0,2,size = (10,3)))
df
0 1 2
0 1 1 1
1 1 0 1
2 1 1 1
3 1 0 0
4 1 1 1
5 1 0 1
6 0 0 1
7 0 1 1
8 0 1 0
9 0 0 1
# the only unique rows are : 3, 7 and 8
df.duplicated(keep = False) == False
0 False
1 False
2 False
3 True
4 False
5 False
6 False
7 True
8 True
9 False
dtype: bool
# so to count how many unique rows we have:
sum(df.duplicated(keep = False) = False)
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