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}unique values in dataframe column count
df.groupby('mID').agg(['count', 'size', 'nunique']).stack()
dID hID uID
mID
A count 5 5 5
size 5 5 5
nunique 3 5 5
B count 2 2 2
size 2 2 2
nunique 2 2 2
C count 1 1 1
size 1 1 1
nunique 1 1 1count 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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