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 rows in dataframe
In [33]: df[df.columns[df.apply(lambda s: len(s.unique()) > 1)]]
Out[33]:
A B
0 0 a
1 1 b
2 2 c
3 3 d
4 4 ecount 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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