CODEWITHSUNDEEP
pythonindexingpandasdataframe
JNevens
JNevens

Reputation: 11982

Pandas Dataframe: get index of max element

I am looking for a way to get both the index and the column of the maximum element in a Pandas DataFrame. Thus far, this is my code:

idx = range(0, 50, 5)
col = range(0, 50, 5)
scores = pd.DataFrame(np.zeros((len(idx), len(col))), index=idx, columns=col, dtype=float)
scores.loc[11, 16] = 5 #Assign a random element

This gives me the following DataFrame:

  | 1   6   11  16  21  26  31  36  41  46
------------------------------------------
1 | 0   0   0   0   0   0   0   0   0   0
6 | 0   0   0   0   0   0   0   0   0   0
11| 0   0   0   5   0   0   0   0   0   0
16| 0   0   0   0   0   0   0   0   0   0
21| 0   0   0   0   0   0   0   0   0   0
26| 0   0   0   0   0   0   0   0   0   0
31| 0   0   0   0   0   0   0   0   0   0
36| 0   0   0   0   0   0   0   0   0   0
41| 0   0   0   0   0   0   0   0   0   0
46| 0   0   0   0   0   0   0   0   0   0

After that, I use the unstack method:

unstacked = scores.unstack().copy()
unstacked.sort(ascending=False)

This gives me:

16  11    5
46  46    0
16  31    0
11  31    0
    36    0
...

How can I get the index and column of the maximum value? I would like to get something along the lines of an array or tuple containing (16, 11).

Upvotes: 5

Views: 19242

Answers (2)

mik
mik

Reputation: 110

x.max()[x.max() == x.max(axis=1).max()].index

This works to get the column but max(x.idxmax()) only returns the numerical maximum of the indices themselves, not the index of the maximum value in the table (just got lucky in this example because everything else is 0's). An alternative is:

s = x.max()[x.max() == x.max(index=1).max()].index
s = str(s[0])
max_index = x.idxmax()[s]

Upvotes: 2

fixxxer
fixxxer

Reputation: 16134

You are looking for idxmax :

In [1332]: x
Out[1332]: 
   1  6  11  16  21  26  31  36  41  46
0  0  0   0   0   0   0   0   0   0   0
1  0  0   0   0   0   0   0   0   0   0
2  0  0   5   0   0   0   0   0   0   0
3  0  0   0   0   0   0   0   0   0   0
4  0  0   0   0   0   0   0   0   0   0
5  0  0   0   0   0   0   0   0   0   0
6  0  0   0   0   0   0   0   0   0   0
7  0  0   0   0   0   0   0   0   0   0
8  0  0   0   0   0   0   0   0   0   0
9  0  0   0   0   0   0   0   0   0   0

Row of the max value: 

In [1337]: max(x.idxmax())
Out[1337]: 2

Column of the max value (too many maxs):

In [1359]: x.max()[x.max() == x.max(axis=1).max()].index
Out[1359]: Index([u'11'], dtype='object')

Upvotes: 9

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