I have a pandas dataframe of multiple minimum values but the min functions picks only one on the column.
ABCD 0.000000
JKLM 0.016535
CAN1 0.381729
MET2 0.275013
INDI 0.149280
MAN3 0.000000
temp2.ix[temp2.idxmin()] only picks one value that is ABCD with 0.0
I would like to fetch both ABCD and MAN3 as minimum ??
You could use following:
df[df == df.min()].dropna()
In [49]: df[df == df.min()].dropna()
Out[49]:
1
0
ABCD 0
MAN3 0
Next solution is:
df.where(df == df.min()).dropna()
And df.idxmin() return only one value, because:
This method is the DataFrame version of ndarray.argmin.
And ndarray.argmin explain this situation in doc:
In case of multiple occurrences of the minimum values, the indices corresponding to the first occurrence are returned.
df2 = df[df.groupby('A')['C'].transform('min') == df['C']]Compare the minimum value for Boolean indexing
df
Out[42]:
b
a
ABCD 0.000000
JKLM 0.016535
CAN1 0.381729
MET2 0.275013
INDI 0.149280
MAN3 0.000000
df[df.b == df.b.min()]
Out[43]:
b
a
ABCD 0
MAN3 0
