TeX - LaTeX Asked by oceanbeach96 on July 23, 2021
I am wondering if the following wide table can be stretched out to fit a larger portion of the page. The size of the table is okay, but it would be ideal to be a little larger. Any suggestions would be super!
documentclass{article}
begin{landscape}
begin{table}
caption {label{tab:Table 4 - MDI recursive prediction} This table demonstrates the MDI classification report for the individual corporate credit rating classes for an ET. Based on the balance between number of features and predictive performance in Table 3, precision, recall, F1 score and support are evaluated on 20 features for U.S. and global NonESG and ESG samples.}
resizebox{columnwidth}{!}
{begin{tabular}{ccccccccccccccccc}
toprule
{} & {thead{U.S. NonESG precision}} & {thead{U.S. NonESG recall}} & {thead{U.S. NonESG F1 score}} & {thead{U.S. NonESG support}} & {thead{U.S ESG precision}} & {thead{U.S ESG recall}} & {thead{U.S ESG F1 score}} & {thead{U.S ESG support}} & {thead{GL NonESG precision}} & {thead{GL NonESG recall}} & {thead{GL NonESG F1 score}} & {thead{GL NonESG support}} & {thead{GL ESG precision}} & {thead{GL ESG recall}} & {thead{GL ESG F1 score}} & {thead{GL ESG support}}
midruleaddlinespace
AAA & 0.9766 & 0.9843 & 0.9804 & 127 & 1 & 1 & 1 & 55 & 1 & 1 & 1 & 34 & 1 & 1 & 1 & 27
AA+ & 0.9844 & 0.9403 & 0.9618 & 67 & 0 & 0 & 0 & 0 & 0.9167 & 0.9565 & 0.9362 & 23 & 0.9333 & 0.7778 & 0.8485 & 18
AA & 0.9703 & 0.9729 & 0.9716 & 369 & 1 & 1 & 1 & 148 & 0.9254 & 0.9688 & 0.9466 & 64 & 0.9219 & 0.9833 & 0.9516 & 60
AA- & 0.9543 & 0.9730 & 0.9636 & 408 & 1 & 1 & 1 & 96 & 0.9815 & 0.9578 & 0.9695 & 166 & 1 & 0.9645 & 0.9819 & 169
A+ & 0.9700 & 0.9739 & 0.9719 & 995 & 0.9968 & 1 & 0.9984 & 309 & 0.9804 & 0.9709 & 0.9756 & 309 & 0.9619 & 0.9806 & 0.9712 & 309
A & 0.9696 & 0.9639 & 0.9667 & 1357 & 0.9684 & 0.9629 & 0.9656 & 350 & 0.9463 & 0.9559 & 0.9511 & 295 & 0.9353 & 0.9455 & 0.9403 & 275
A- & 0.9577 & 0.9583 & 0.9580 & 1464 & 0.9790 & 0.9689 & 0.9739 & 482 & 0.9618 & 0.9658 & 0.9638 & 730 & 0.9772 & 0.9646 & 0.9709 & 622
BBB+ & 0.9558 & 0.9663 & 0.9610 & 1901 & 0.9724 & 0.9830 & 0.9776 & 823 & 0.9716 & 0.9716 & 0.9716 & 1090 & 0.9748 & 0.9737 & 0.9743 & 914
BBB & 0.9613 & 0.9582 & 0.9597 & 2438 & 0.9758 & 0.9697 & 0.9727 & 956 & 0.9537 & 0.9683 & 0.9609 & 914 & 0.9674 & 0.9744 & 0.9709 & 821
BBB- & 0.9541 & 0.9508 & 0.9524 & 2031 & 0.9701 & 0.9726 & 0.9714 & 802 & 0.9592 & 0.9613 & 0.9603 & 930 & 0.9708 & 0.9708 & 0.9708 & 754
BB+ & 0.9347 & 0.9474 & 0.9410 & 1406 & 0.9560 & 0.9613 & 0.9587 & 543 & 0.9434 & 0.9488 & 0.9461 & 527 & 0.9504 & 0.9637 & 0.9570 & 358
BB & 0.9597 & 0.9413 & 0.9504 & 1721 & 0.9415 & 0.9489 & 0.9452 & 509 & 0.9667 & 0.8906 & 0.9271 & 521 & 0.9474 & 0.9375 & 0.9424 & 288
BB- & 0.9467 & 0.9554 & 0.9510 & 2397 & 0.9712 & 0.9637 & 0.9674 & 524 & 0.9268 & 0.9552 & 0.9408 & 424 & 0.9474 & 0.9083 & 0.9274 & 218
B+ & 0.9351 & 0.9496 & 0.9423 & 2261 & 0.9728 & 0.9831 & 0.9779 & 473 & 0.9250 & 0.9250 & 0.9250 & 320 & 0.9106 & 0.9412 & 0.9256 & 119
B & 0.9423 & 0.9262 & 0.9342 & 1341 & 0.9490 & 0.9442 & 0.9466 & 197 & 0.9157 & 0.9373 & 0.9264 & 255 & 0.8830 & 0.8925 & 0.8877 & 93
B- & 0.9010 & 0.9151 & 0.9080 & 577 & 0.9655 & 0.8889 & 0.9256 & 63 & 0.9409 & 0.8925 & 0.9161 & 214 & 0.9833 & 0.9365 & 0.9593 & 63
CCC+ & 0.9136 & 0.8627 & 0.8874 & 233 & 0.9730 & 0.9730 & 0.9730 & 37 & 0.7843 & 0.8333 & 0.8081 & 48 & 0.8235 & 0.9333 & 0.8750 & 30
CCC & 0.8701 & 0.7976 & 0.8323 & 84 & 1 & 1 & 1 & 9 & 0.7857 & 0.9429 & 0.8571 & 35 & 0.8235 & 1 & 0.9032 & 14
CCC- & 0.8864 & 0.7800 & 0.8298 & 50 & 1 & 0.9412 & 0.9697 & 17 & 0.9231 & 1 & 0.9600 & 36 & 1 & 1 & 1 & 6
CC & 0.9762 & 0.8200 & 0.8913 & 50 & 1 & 1 & 1 & 11 & 0.9130 & 0.7 & 0.7925 & 30 & 0.875 & 0.7 & 0.7778 & 10
SD & 0.5556 & 0.7143 & 0.6250 & 7 & 0 & 0 & 0 & 0 & 0.9231 & 1 & 0.9600 & 12 & 0.5 & 0.3333 & 0.4 & 3
D & 0.9485 & 0.8846 & 0.9154 & 104 & 1 & 1 & 1 & 4 & 0.8889 & 1 & 0.9412 & 32 & 0.8333 & 0.8333 & 0.8333 & 6
accuracy & 0.9506 & 0.9506 & 0.9506 & 0.9506 & 0.9708 & 0.9708 & 0.9708 & 0.9708 & 0.9518 & 0.9518 & 0.9518 & 0.9518 & 0.9612 & 0.9612 & 0.9612 & 0.9612
macro avg & 0.9284 & 0.9153 & 0.9207 & 21388 & 0.9796 & 0.9731 & 0.9762 & 6408 & 0.9288 & 0.9410 & 0.9334 & 7009 & 0.9145 & 0.9052 & 0.9077 & 5177
weighted avg & 0.9507 & 0.9506 & 0.9506 & 21388 & 0.9708 & 0.9708 & 0.9708 & 6408 & 0.9522 & 0.9518 & 0.9517 & 7009 & 0.9614 & 0.9612 & 0.9611 & 5177
bottomrule
end{tabular}}
end{table}
end{landscape}
end{document}
S
column type (defined in siunitx
packageresizebox{...}{...}
, it make table almost unreadable,
instead use tabular*
with linewidth
(which is in landscape equal to textheight
) width and reduce font size to small
Based on guessing (in lack of information about your document preamble) see, if the following solution is what you looking for:
documentclass{article}
usepackage[margin=25mm]{geometry}
usepackage{pdflscape}
usepackage{booktabs, makecell}
usepackage{siunitx}
begin{document}
begin{landscape}
begin{table}
caption {label{tab:Table 4 - MDI recursive prediction} This table demonstrates the MDI classification report for the individual corporate credit rating classes for an ET. Based on the balance between number of features and predictive performance in Table 3, precision, recall, F1 score and support are evaluated on 20 features for U.S. and global NonESG and ESG samples.}
small
setlengthtabcolsep{0pt}
begin{tabular*}{linewidth}{@{extracolsep{fill}}l
*{4}{*{3}{S[table-format=1.4]}S[table-format=4.0]}
}
toprule
& multicolumn{4}{c}{thead{U.S. NonESG}}
& multicolumn{4}{c}{thead{U.S. NonESG}}
& multicolumn{4}{c}{thead{GL NonESG}}
& multicolumn{4}{c}{thead{GL ESG}}
cmidrule(l){2-5}
cmidrule(l){6-9}
cmidrule(l){10-13}
cmidrule(l){14-17}
& {thead{precision}} & {thead{recall}} & {thead{F1 score}} & {thead{support}}
& {thead{precision}} & {thead{recall}} & {thead{F1 score}} & {thead{support}}
& {thead{precision}} & {thead{recall}} & {thead{F1 score}} & {thead{support}}
& {thead{precision}} & {thead{recall}} & {thead{F1 score}} & {thead{support}}
midrule
AAA & 0.9766 & 0.9843 & 0.9804 & 127
& 1 & 1 & 1 & 55
& 1 & 1 & 1 & 34
& 1 & 1 & 1 & 27
AA+ & 0.9844 & 0.9403 & 0.9618 & 67
& 0 & 0 & 0 & 0
& 0.9167 & 0.9565 & 0.9362 & 23
& 0.9333 & 0.7778 & 0.8485 & 18
AA & 0.9703 & 0.9729 & 0.9716 & 369
& 1 & 1 & 1 & 148
& 0.9254 & 0.9688 & 0.9466 & 64
& 0.9219 & 0.9833 & 0.9516 & 60
AA- & 0.9543 & 0.9730 & 0.9636 & 408
& 1 & 1 & 1 & 96
& 0.9815 & 0.9578 & 0.9695 & 166
& 1 & 0.9645 & 0.9819 & 169
A+ & 0.9700 & 0.9739 & 0.9719 & 995
& 0.9968 & 1 & 0.9984 & 309
& 0.9804 & 0.9709 & 0.9756 & 309
& 0.9619 & 0.9806 & 0.9712 & 309
A & 0.9696 & 0.9639 & 0.9667 & 1357
& 0.9684 & 0.9629 & 0.9656 & 350
& 0.9463 & 0.9559 & 0.9511 & 295
& 0.9353 & 0.9455 & 0.9403 & 275
A- & 0.9577 & 0.9583 & 0.9580 & 1464
& 0.9790 & 0.9689 & 0.9739 & 482
& 0.9618 & 0.9658 & 0.9638 & 730
& 0.9772 & 0.9646 & 0.9709 & 622
addlinespace
BBB+
& 0.9558 & 0.9663 & 0.9610 & 1901
& 0.9724 & 0.9830 & 0.9776 & 823
& 0.9716 & 0.9716 & 0.9716 & 1090
& 0.9748 & 0.9737 & 0.9743 & 914
BBB & 0.9613 & 0.9582 & 0.9597 & 2438
& 0.9758 & 0.9697 & 0.9727 & 956
& 0.9537 & 0.9683 & 0.9609 & 914
& 0.9674 & 0.9744 & 0.9709 & 821
BBB-
& 0.9541 & 0.9508 & 0.9524 & 2031
& 0.9701 & 0.9726 & 0.9714 & 802
& 0.9592 & 0.9613 & 0.9603 & 930
& 0.9708 & 0.9708 & 0.9708 & 754
BB+ & 0.9347 & 0.9474 & 0.9410 & 1406
& 0.9560 & 0.9613 & 0.9587 & 543
& 0.9434 & 0.9488 & 0.9461 & 527
& 0.9504 & 0.9637 & 0.9570 & 358
BB & 0.9597 & 0.9413 & 0.9504 & 1721
& 0.9415 & 0.9489 & 0.9452 & 509
& 0.9667 & 0.8906 & 0.9271 & 521
& 0.9474 & 0.9375 & 0.9424 & 288
BB- & 0.9467 & 0.9554 & 0.9510 & 2397
& 0.9712 & 0.9637 & 0.9674 & 524
& 0.9268 & 0.9552 & 0.9408 & 424
& 0.9474 & 0.9083 & 0.9274 & 218
B+ & 0.9351 & 0.9496 & 0.9423 & 2261
& 0.9728 & 0.9831 & 0.9779 & 473
& 0.9250 & 0.9250 & 0.9250 & 320
& 0.9106 & 0.9412 & 0.9256 & 119
B & 0.9423 & 0.9262 & 0.9342 & 1341
& 0.9490 & 0.9442 & 0.9466 & 197
& 0.9157 & 0.9373 & 0.9264 & 255
& 0.8830 & 0.8925 & 0.8877 & 93
B- & 0.9010 & 0.9151 & 0.9080 & 577
& 0.9655 & 0.8889 & 0.9256 & 63
& 0.9409 & 0.8925 & 0.9161 & 214
& 0.9833 & 0.9365 & 0.9593 & 63
addlinespace
CCC+
& 0.9136 & 0.8627 & 0.8874 & 233
& 0.9730 & 0.9730 & 0.9730 & 37
& 0.7843 & 0.8333 & 0.8081 & 48
& 0.8235 & 0.9333 & 0.8750 & 30
CCC & 0.8701 & 0.7976 & 0.8323 & 84
& 1 & 1 & 1 & 9
& 0.7857 & 0.9429 & 0.8571 & 35
& 0.8235 & 1 & 0.9032 & 14
CCC-
& 0.8864 & 0.7800 & 0.8298 & 50
& 1 & 0.9412 & 0.9697 & 17
& 0.9231 & 1 & 0.9600 & 36
& 1 & 1 & 1 & 6
CC & 0.9762 & 0.8200 & 0.8913 & 50
& 1 & 1 & 1 & 11
& 0.9130 & 0.7 & 0.7925 & 30
& 0.875 & 0.7 & 0.7778 & 10
addlinespace
SD & 0.5556 & 0.7143 & 0.6250 & 7
& 0 & 0 & 0 & 0
& 0.9231 & 1 & 0.9600 & 12
& 0.5 & 0.3333 & 0.4 & 3
D & 0.9485 & 0.8846 & 0.9154 & 104
& 1 & 1 & 1 & 4
& 0.8889 & 1 & 0.9412 & 32
& 0.8333 & 0.8333 & 0.8333 & 6
midrule
accuracy
& 0.9506 & 0.9506 & 0.9506 & {0.9506}
& 0.9708 & 0.9708 & 0.9708 & {0.9708}
& 0.9518 & 0.9518 & 0.9518 & {0.9518}
& 0.9612 & 0.9612 & 0.9612 & {0.9612}
macro avg
& 0.9284 & 0.9153 & 0.9207 & {21388}
& 0.9796 & 0.9731 & 0.9762 & {6408}
& 0.9288 & 0.9410 & 0.9334 & {7009}
& 0.9145 & 0.9052 & 0.9077 & {5177}
weighted avg
& 0.9507 & 0.9506 & 0.9506 & {21388}
& 0.9708 & 0.9708 & 0.9708 & {6408}
& 0.9522 & 0.9518 & 0.9517 & {7009}
& 0.9614 & 0.9612 & 0.9611 & {5177}
bottomrule
end{tabular*}
end{table}
end{landscape}
end{document}
Correct answer by Zarko on July 23, 2021
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