Predict numeric outcomes from user's input values trained using pandas excel datafram

I have a dataset in excel file as bellow:

HeatZone_1 HeatZone_2 HeatZone_3 HeatZone_4 HeatZone_5 Fan Dryer exhaust Exit_Gate Push Burner_1 Burner_2 Burner_3
516 561 671 742 843 15.5 25.52 24.5 Closed FALSE X 45 45
515 560 668 741 845 15.5 25 24.5 Closed FALSE X 45 45
515 559 665 740 822 15.5 25 24.5 Open FALSE X 45 45
513 558 664 739 841 15.5 25 25.5 open FALSE X 37 45
520 569 686 790 884 17.24 25 25.5 open FALSE X 45 45
522 571 692 802 891 19.26 25.50 25.5 open FALSE X 45 45
530 581 710 821 881 19.50 258.50 25.50 open FALSE X 45 45
532 583 714 826 884 19.50 25.50 25.50 open FALSE X 37 45
539 594 740 852 876 17.56 25.50 25.50 open FALSE X 45 45
536 593 740 851 897 15.08 25.50 25.50 open FALSE X 45 45
536 592 736 845 907 14.50 22.67 25.50 Closed TRUE X 45 45
537 593 735 840 914 14.50 22.67 25.50 open FALSE X 45 45
521 579 652 802 868 19.23 22.67 25.50 open FALSE X 45 45
526 589 663 846 875 19.23 22.67 25.50 open FALSE X 45 45
530 595 670 862 892 19.23 22.67 25.50 open FALSE X 45 45
532 597 671 843 897 19.23 21.32 25.50 Closed FALSE X 45 45
540 607 685 870 910 19.23 21.32 25.50 open FALSE X 45 45
541 609 687 885 924 19.23 21.32 25.50 open FALSE X 45 45
549 617 696 900 919 19.23 21.32 25.50 open FALSE X 45 45
551 620 698 900 926 19.23 21.32 25.50 Closed TRUE X 45 45
536 605 675 808 934 19.23 21.32 25.50 open TRUE X 37 45
541 613 687 846 917 19.57 21.34 25.50 open FALSE X 45 25
544 617 696 849 907 19.57 21.34 25.50 open FALSE X 45 25

It’s just a sample. I have a large data set to be used.

Based on user inputs of |HeatZone_1|HeatZone_2|HeatZone_3|HeatZone_4|HeatZone_5|

st.number_field()

i want the values of parameters
|Fan|Dryer|exhaust|Exit_Gate|Push|Burner_1|Burner_2|Burner_3| to be predicted faster method.

Can someone help me with the code to solve this? Thanks in advance!

Hello welcome to streamlit discussion.

Do you have issues with streamlit ui or issues doing some regression analysis of your data?

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