Boolean for unique value in a column

Question

For my dataframe, e.g.

df = pd.DataFrame([1, 3, 7, 1], columns=['data'])

I want to know for each index if the value is unique in the column data.

So the resulting dataframe should be

    data    is_unique
0   1       False
1   3       True
2   7       True
3   1       False

Is there a convenient approach with pandas?

Asked By: Michael Dorner

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Source

Answer 1

Use duplicated with invert mask by ~:

df['is_unique'] = ~df['data'].duplicated(keep=False)
print (df)

   data  is_unique
0     1      False
1     3       True
2     7       True
3     1      False

Answered By: jezrael

Answer 2

By using value_counts + map

df.assign(BOOL=df.data.map(df.data.value_counts()>1))
Out[437]: 
   data   BOOL
0     1   True
1     3  False
2     7  False
3     1   True

By using drop_duplicate

df.assign(BOOL=df.index.isin(df.drop_duplicates('data',keep =False).index))

Out[440]: 
   data   BOOL
0     1  False
1     3   True
2     7   True
3     1  False

Answered By: BENY

Answer 3

from collections import Counter

c = Counter(df.client.to_list())

df["new_col"] = df.client.apply(lambda x:not(c[x] >1) )

Answered By: Vishesh Mangla

Answer 4

One can use pandas.Series.map and pandas.Series.value_counts as follows

df['is_unique'] = df['data'].map(df['data'].value_counts() == 1)

[Out]:

   data  is_unique
0     1      False
1     3       True
2     7       True
3     1      False

Answered By: Gonçalo Peres

Boolean for unique value in a column

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