CODEWITHSUNDEEP
pythonpandas
AJG519
AJG519

Reputation: 3379

Check if values within a group are equal in Pandas

I have something like the following 'DataFrame`:

>>> df=pd.DataFrame(index=['A','A','A','B','B','C','C','C'])
>>> df['Value1']=[1,1,1,2,1,4,4,4]
>>> df['Value2']=[1,2,3,4,5,6,7,8]
>>> df
   Value1  Value2
A       1       1
A       1       2
A       1       3
B       2       4
B       1       5
C       4       6
C       4       7
C       4       8
>>>

The index of the DataFrame represents 3 different groups. I want to check whether or not the column values within a group are all equal. My current methodology and desired output are the following:

>>> result_list=[]
>>> for Col in df.columns:
...     result=df.groupby(level=0)[Col].apply(lambda x: len(set(x))==1)
...     result_list.append(result)
... 
>>> 
>>> final=pd.concat(result_list,1)
>>> final
  Value1 Value2
A   True  False
B  False  False
C   True  False
>>>

Is this the best approach to take? I'm wondering if it's possible to do this without having to loop through the columns in my DataFrame.

Additionally is using len(set(x)==1) the best way to determine if all items in the group are equal?

Upvotes: 3

Views: 5922

Answers (2)

RootTwo
RootTwo

Reputation: 4418

SImilar to Jansen's answer, but doesn't build the set.

df.groupby(level=0).agg(lambda s:np.unique(s).size==1)

    Value1  Value2
A   True    False
B   False   False
C   True    False

Upvotes: 3

Stefan
Stefan

Reputation: 42885

df.groupby(level=0).agg(lambda x: len(set(x)) == 1)

  Value1 Value2
A   True  False
B  False  False
C   True  False

Upvotes: 5

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