Return List Of Indices/index Where A Min/max Value Occurs In A Pandas Dataframe

I'd like to search a pandas DataFrame for minimum values. I need the min in the entire dataframe (across all values) analogous to df.min().min(). However I also need the know the i

Solution 1:

Based on your revised update:

In [209]:
keys = ['x', 'y', 'z'] 
vals = [[1,2,-1], [3,5,-1], [4,2,3]] 
data = dict(zip(keys,vals)) 
df = pd.DataFrame(data)
df

Out[209]:
   x  y  z
013412522-1-13

Then the following would work:

In [211]:
df[df==df.min().min()].dropna(axis=1, thresh=1).dropna()

Out[211]:
     x    y
2 -1.0 -1.0

So this uses the boolean mask on the df:

In [212]:
df[df==df.min().min()]

Out[212]:
     x    y   z
0NaNNaNNaN1NaNNaNNaN2-1.0-1.0NaN

and we call dropna with param thresh=1 this drops columns that don't have at least 1 non-NaN value:

In [213]:
df[df==df.min().min()].dropna(axis=1, thresh=1)

Out[213]:
     x    y
0  NaN  NaN
1  NaN  NaN
2 -1.0 -1.0

Probably safer to call again with thresh=1:

In [214]:
df[df==df.min().min()].dropna(axis=1, thresh=1).dropna(thresh=1)

Out[214]:
     x    y
2 -1.0 -1.0