I have two columns in my pandas DataFrame.
A B
0 1 5
1 2 3
2 3 2
3 4 0
4 5 1
I need the value in A where the value of B is minimum. In the above case my answer would be 4 since the minimum B value is 0.
Can anyone help me with it?
To find the minimum in column B, you can use df.B.min(). For your DataFrame this returns 0.
To find values at particular locations in a DataFrame, you can use loc:
>>> df.loc[(df.B == df.B.min()), 'A']
3 4
Name: A, dtype: int64
So here, loc picks out all of the rows where column B is equal to its minimum value (df.B == df.B.min()) and selects the corresponding values in column A.
This method returns all values in A corresponding to the minimum value in B. If you only need to find one of the values, the better way is to use idxmin as @aus_lacy suggests.
Here's one way:
b_min = df.B.idxmin()
a_val = df.A[b_min]
idxmin() returns the index of the minimum value within column B. You then locate the value at that same index in column A.
or if you want a single, albeit less readable, line you can do it like:
a_val = df.A[df.B.idxmin()]
Also, as a disclaimer this solution assumes that the minimum value in column B is unique. For example if you were to have a data set that looked like this:
A B
1 2
2 5
3 0
4 3
5 0
My solution would return the first instance where B's minimum value is located which in this case is in the third row and has a corresponding A value of 3. If you believe that the minimum value of B is not unique then you should go with @ajcr's solution.
