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You could use the python statsmodels.tsa.vector_ar.vecm.JohansenTestResult by importing it through EmbedPy and passing the data as a dataframe using mltab2df.
Below is an example based of a similar python version: http://web.pdx.edu/~crkl/ceR/Python/example14_3.py
$pip install statsmodels q)l p.q q)l ml/ml.q q).ml.loadfile`:init.q q)data:flip `YEAR`Y`C!"IFF"$flip 1_-12_{{x where not ""~/:x}" " vs x} each "rn" vs .Q.hg "http://web.pdx.edu/~crkl/ceR/data/usyc87.txt" q)coint_johansen:.p.import[`statsmodels.tsa.vector_ar.vecm;`:coint_johansen] q)pd:.ml.tab2df[data][`:set_index;"YEAR"] q)res:coint_johansen[pd;0;2] q)res[`:lr1]` 31.78169 12.17119 -1.566747e-012 q)res[`:lr2]` 19.6105 12.17119 -1.566747e-012 q)res[`:cvm]` 18.8928 21.1314 25.865 12.2971 14.2639 18.52 2.7055 3.8415 6.6349 q)res[`:cvt]` 27.0669 29.7961 35.4628 13.4294 15.4943 19.9349 2.7055 3.8415 6.6349 q){flip y!(x@/:hsym y)@:`}[res;`lr1`lr2`cvm`cvt] lr1 lr2 cvm cvt ---------------------------------------------------------------------------- 31.78169 19.6105 18.8928 21.1314 25.865 27.0669 29.7961 35.4628 12.17119 12.17119 12.2971 14.2639 18.52 13.4294 15.4943 19.9349 -1.566747e-012 -1.566747e-012 2.7055 3.8415 6.6349 2.7055 3.8415 6.6349