<pre><code>import pandas as pd
data = [
[ 123, 1, 23.34, 12.23, 54.56, 12.22 ],
[ 123, 1, 22.32, 11.32, 7.89, 3.45 ],
[ 123, 1, 21.22, 19.93, 5.54, 5.66 ],
[ 123, 1, 21.34, 12.23, 54.56, 22.22 ],
[ 123, 1, 32.32, 13.32, 4.89, 32.45 ],
[ 123, 1, 32.22, 29.93, 23.54, 23.66 ],
[ 123, 2, 23.34, 12.23, 54.56, 12.22 ],
[ 123, 2, 22.32, 11.32, 7.89, 3.45 ],
[ 123, 2, 21.22, 19.93, 5.54, 5.66 ],
[ 123, 2, 21.34, 12.23, 54.56, 22.22 ],
[ 123, 2, 32.32, 13.32, 4.89, 32.45 ],
[ 123, 2, 32.22, 29.93, 23.54, 23.66 ]
]
columns = ['code', 'tank', 'var', 'nozzle_1', 'nozzle_2', 'nozzle_3']
df = pd.DataFrame(data=data, columns=columns)
print(df[['tank', 'var', 'nozzle_1', 'nozzle_2', 'nozzle_3']].groupby(['tank']).corr())
#
# RESULT:
# var nozzle_1 nozzle_2 nozzle_3
# tank
# 1 var 1.000000 0.501164 -0.309435 0.761017
# nozzle_1 0.501164 1.000000 -0.214982 0.168518
# nozzle_2 -0.309435 -0.214982 1.000000 0.107815
# nozzle_3 0.761017 0.168518 0.107815 1.000000
# 2 var 1.000000 0.501164 -0.309435 0.761017
# nozzle_1 0.501164 1.000000 -0.214982 0.168518
# nozzle_2 -0.309435 -0.214982 1.000000 0.107815
# nozzle_3 0.761017 0.168518 0.107815 1.000000
</code></pre>