CODEWITHSUNDEEP
pythonindexingmax
jpcgandre
jpcgandre

Reputation: 1505

Index of row where maximum value is located

I have this list:

dCF3v=[[(1.90689635276794, -44704.76171875)],
       [(1.90689635276794, -44705.76171875)],
       [(1.90689635276794, -44706.76171875)],
       [(1.90689635276794, -44707.76171875)]
      ]

I'd like to know the index of the row where the maximum value is. In the example above: row index 3.

I already have a code for finding the maximum value:

CF3a = (abs(x[0][1]) for x in dCF3v)
CF3 = max(CF3a)

If possible I'd like to adapt this code and not have to do the classic for and if loops.

Upvotes: 0

Views: 79

Answers (2)

Jochen Ritzel
Jochen Ritzel

Reputation: 107608

You can use enumerate to keep the indices and the key argument for max to look for the right value:

dCF3v=[[(1.90689635276794, -44704.76171875)],
       [(1.90689635276794, -44705.76171875)],
       [(1.90689635276794, -44706.76171875)],
       [(1.90689635276794, -44707.76171875)]
      ]

CF3a = (abs(x[0][1]) for x in dCF3v)
index, value = max(enumerate(CF3a), key=lambda (index, value): value)
print index,value

Upvotes: 2

Martinis Group
Martinis Group

Reputation: 213

Since your data appears to numerical in nature I would strongly recommend using the numpy module as it is designed in part to do what you're asking.

You can convert your data to a numpy array

import numpy as np
data = np.array(dCF3v)

and then use np.argmax to find the index of the largest value

idx = np.argmax(data)

This gives you an index into the flattened array. If you know the shape of your array this flattened index is easily converted into a row number using modular arithmetic. You can get the number of rows and columns like this

rows,cols = data.shape

and then the row number with modular division

maxRow = idx%cols

numpy also has a function called unravel_index which does the modular arithmetic for you,

row, col = np.unravel_index(idx, data.shape)

Upvotes: 1

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