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What is the best way to apply a row-wise function and create multiple new columns?

I have two dataframes and a working code, but it's most likely not optimal

df1 (dataframe has thousands of rows and xx number of columns)

sic data1 data2 data3 data4 data5 5 0.90783598 0.84722083 0.47149924 0.98724123 0.50654476 6 0.53442684 0.59730371 0.92486887 0.61531646 0.62784041 3 0.56806423 0.09619383 0.33846097 0.71878313 0.96316724 8 0.86933042 0.64965755 0.94549745 0.08866519 0.92156389 12 0.651328 0.37193774 0.9679044 0.36898991 0.15161838 6 0.24555531 0.50195983 0.79114578 0.9290596 0.10672607

df2 (column header maps to the sic-code in df1. There are in total 12 sic-codes and the dataframe is thousands of rows long)

1 2 3 4 5 6 7 8 9 10 11 12 c_bar 0.4955329 0.92970292 0.68049726 0.91325006 0.55578465 0.78056519 0.53954711 0.90335326 0.93986402 0.0204794 0.51575764 0.61144255 a1_bar 0.75781444 0.81052669 0.99910449 0.62181902 0.11797144 0.40031316 0.08561665 0.35296894 0.14445697 0.93799762 0.80641802 0.31379671 a2_bar 0.41432552 0.36313911 0.13091618 0.39251953 0.66249636 0.31221897 0.15988528 0.1620938 0.55143589 0.66571044 0.68198944 0.23806947 a3_bar 0.38918855 0.83689178 0.15838139 0.39943204 0.48615188 0.06299899 0.86343819 0.47975619 0.05300611 0.15080875 0.73088725 0.3500239 a4_bar 0.47201384 0.90874121 0.50417142 0.70047698 0.24820601 0.34302454 0.4650635 0.0992668 0.55142391 0.82947194 0.28251699 0.53170308

I achieved the result I need with the following code:

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