I have a dataframe like this
A B
25 0.5
21 0.6
17 0.7
14 0.7 <--- this is the row I want
12 0.3
I'd like to select the maximum B with minimum A.
Is there a pandas easy trick to do this?
First compare column B by max values and then get index of minimal A by idxmin, last select by loc:
a = df.loc[df['B'] == df['B'].max(), 'A'].idxmin()
print (a)
3
#for one row DataFrame use [[]]
df = df.loc[[a]]
print (df)
A B
3 14 0.7
#for Series use []
s = df.loc[a]
print (s)
A 14.0
B 0.7
Name: 3, dtype: float64
Detail:
print (df.loc[df['B'] == df['B'].max(), 'A'])
2 17
3 14
Name: A, dtype: int64
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