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 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

score 201 · Accepted Answer · edited Oct 13 '22 at 03:10

201

If you are trying to get the row-wise mininum of two or more columns, use pandas.DataFrame.min. Note that by default axis=0; specifying axis=1 is necessary.

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

edited Oct 13 '22 at 03:10

Asclepius

57,944
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167
143

answered Nov 28 '15 at 19:18

Happy001

6,103
2
23
16

Is it possible to add a shift(1) in here or would I need to add a temporary column (e.g. data["flow_c_1"] = data["flow_c_1"].shift(1)) ? Thx – user27074 Jul 17 '23 at 09:14

score 19 · Answer 2 · answered Apr 20 '20 at 05:25

19

If you like to get a single minimum value of multiple columns:

data[['flow_h','flow_c']].min().min()

the first "min()" calculates the minimum per column and returns a pandas series. The second "min" returns the minimum of the minimums per column.

answered Apr 20 '20 at 05:25

b0lle

732
6
19

and if one would want to get the index of the min of min? – Geosphere Jun 07 '22 at 11:20

score 1 · Answer 3 · answered Mar 16 '23 at 22:55

One may also transpose and call min().

data['min_flow'] = data[['flow_h','flow_c']].T.min()

or call min(axis=1) on the underlying numpy array.

data['min_flow'] = data[['flow_h','flow_c']].values.min(axis=1)

If no axis is passed, ndarray.min is evaluated on the entire array, so for a single minimum value of multiple columns (i.e. minimum of minimums), accessing the underlying numpy array could be useful too:

minimum = data[['flow_h','flow_c']].values.min()

score 0 · Answer 4 · answered Aug 13 '23 at 23:42

0

You could also use numpy to reference or get the row-wise mininum of two (or more) columns in another one. Important to specify axis=1.

import numpy as np
...
data['min_c_h']= np.min(data[['flow_h','flow_c']],axis=1)

answered Aug 13 '23 at 23:42

Marc Steffen

113
1
7

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

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