pandas get the row-wise minimum value of two or more columns

Question

How can I reference the minimum value of two dataframes as part of a pandas dataframe equation? I tried using the python min() function which did not work. I'm sorry if this is well-documented somewhere but I have not been able to find a working solution for this problem. I am looking for something along the lines of this:

data['eff'] = pd.DataFrame([data['flow_h'], data['flow_c']]).min() *Cp* (data[' Thi'] - data[' Tci']) 

I also tried to use pandas min() function, which is also not working.

min_flow = pd.DataFrame([data['flow_h'], data['flow_c']]).min()  InvalidIndexError: Reindexing only valid with uniquely valued Index objects 

I was confused by this error. The data columns are just numbers and a name, I wasn't sure where the index comes into play.

import pandas as pd import numpy as np  np.random.seed(365) rows = 10 flow = {'flow_c': [np.random.randint(100) for _ in range(rows)],         'flow_d': [np.random.randint(100) for _ in range(rows)],         'flow_h': [np.random.randint(100) for _ in range(rows)]} data = pd.DataFrame(flow)  # display(data)    flow_c  flow_d  flow_h 0      82      36      43 1      52      48      12 2      33      28      77 3      91      99      11 4      44      95      27 5       5      94      64 6      98       3      88 7      73      39      92 8      26      39      62 9      56      74      50 

Answer 1

If you are trying to get the row-wise mininum of two or more columns, use pandas.DataFrame.min and specify axis=1.

data['min_c_h'] = data[['flow_h','flow_c']].min(axis=1)  # display(data)    flow_c  flow_d  flow_h  min_c_h 0      82      36      43       43 1      52      48      12       12 2      33      28      77       33 3      91      99      11       11 4      44      95      27       27 5       5      94      64        5 6      98       3      88       88 7      73      39      92       73 8      26      39      62       26 9      56      74      50       50