I am using pandas to check user input in multiple columns, i want output as entire row which matches input

Question

below is my code:

for r in cols:
    full_row_of_matched = cols[cols.isin([input_ip]).any(axis=1)]
    exact_column = list(cols.columns[cols.eq(input_ip).any(0)])
    res = full_row_of_matched.iloc[:, 1]

Below is the DF

eth0      eth1        eth2         server_group  vars
10.1.0.1  172.10.1.3  172.10.11.3  A             xyz
10.1.0.2  172.10.1.3  172.10.11.9  B             abc
10.1.0.7  172.10.1.9  172.10.1.3   V             qwe

in the above Df you can see ip 172.10.1.3 has duplicates, so if i provide input as 172.10.1.3 i need below output

IP provided 172.10.1.3 has been assigned to host xyz and mapped to interface eth1
IP provided 172.10.1.3 has been assigned to host abc and mapped to interface eth1
IP provided 172.10.1.3 has been assigned to host qwe and mapped to interface eth2

Answer 1

fetching matching rows (option1)

inp = '172.10.1.3'
(df
 .melt(id_vars=['server_group', 'vars'], value_name='IP', var_name='interface')
 .loc[lambda d: d['IP'].eq(inp)]
)

output:

  server_group vars interface          IP
3            A  xyz      eth1  172.10.1.3
4            B  abc      eth1  172.10.1.3
8            V  qwe      eth2  172.10.1.3

fetching matching rows (option2)

inp = '172.10.1.3'
df[df.eq(inp).any(1)]

or, to limit to the "eth" columns:

inp = '172.10.1.3'
df[df.filter(like='eth').eq(inp).any(1)]

output:

        eth0        eth1         eth2. server_group. vars
0  10.1.0.1.  172.10.1.3  172.10.11.3.             A  xyz

older answer

Your question is unclear, but assuming you have inp as input, you could use:

inp = '172.10.1.3'

cols = list(df.columns[df.eq(inp).any(0)])

cols
# ['eth1']

If you want all combinations of matching row/col indices:

inp = '172.10.1.3'

import numpy as np
rows, cols = np.where(df.eq(inp))
indices = list(zip(df.index[rows], df.columns[cols]))

output: [(0, 'eth1')]