Category : max

I would like to find the max in columns in pairs of two I have the following columns: user_id’, ‘fullname’, ’email’, ‘handle’, ‘audience_ethnicities_code0’, ‘audience_ethnicities_weight0’, ‘audience_ethnicities_code1’, ‘audience_ethnicities_weight1’, ‘audience_ethnicities_code2’, ‘audience_ethnicities_weight2’, ‘audience_ethnicities_code3’, ‘audience_ethnicities_weight3′ where code and weigh are related, for example: ==> user_id = ABCD ‘audience_ethnicities_code0’ = asian; ‘audience_ethnicities_weight0’ = 0.4 ‘audience_ethnicities_code1’ = african; ‘audience_ethnicities_weight1’ = 0.2 ‘audience_ethnicities_code2’ ..

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Given: a=np.array([[-0.00365169, -1.96455717, 1.44163783, 0.52460176, 2.21493637], [-1.05303533, -0.7106505, 0.47988974, 0.73436447, -0.87708389], [-0.76841759, 0.8405524, 0.91184575, -0.70652033, 0.37646991]]) I would like to get the maximum subset (in this case, the first row): [-0.00365169, -1.96455717, 1.44163783, 0.52460176, 2.21493637] By using print(np.amax(a, axis=0)), I’m getting the wrong result: [-0.00365169 0.8405524 1.44163783 0.73436447 2.21493637] How can we get the correct ..

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