Mdthbs

I am new to tables in latex. I know that I can do this with p{width} but when I try it the table gets all unformated. How do I do it so that the Approach column gets smaller so that the table can fit inside the page?

Thanks.

documentclass{article}

usepackage[utf8]{inputenc}

usepackage[english]{babel}



begin{document}

begin{table}

centering

label{tabelaSemEval}

begin{tabular}{llc|llc|llc} 

hline

multicolumn{3}{c}{ textbf{Sub-task A}} & multicolumn{3}{c}{textbf{Sub-task B}} & multicolumn{3}{c}{textbf{Sub-task C }} \

multicolumn{1}{c|}{textbf{Team Ranks}} & multicolumn{1}{p{3cm}|}{textbf{Approach}} & multicolumn{1}{l|}{textbf{F1 score} } & multicolumn{1}{c|}{textbf{Team Ranks}} & multicolumn{1}{p{3cm}|}{textbf{Approach}} & multicolumn{1}{l|}{textbf{F1 score} } & multicolumn{1}{c|}{textbf{Team Ranks}} & multicolumn{1}{p{3cm}|}{textbf{Approach}} & multicolumn{1}{l}{textbf{F1 score} } \ 

hline

NULI & BERT & 0.829 & jhan014 & MSOC & 0.755 & vradivchev anikolov & BERT+GloVe & 0.660 \

vradivchev anikolov & BERT+GloVe & 0.815 & Amobee & CNN+token embedding & 0.739 & NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM, Transformer,SVM and Random Forest & 0.628 \

UM-IU@LING & BERT & 0.814 & HHU & LSTM & 0.719 & Fermi & ELMo embeddings+ SVM & 0.626 \

Embeddia & BERT & 0.808 & NULI & BERT & 0.716 & YNU-HPCC &  & 0.621 \

MIDAS & CNN+LSTM+GRU and word embeddings & 0.807 & NIT Agartala & Logistic regression+ Linear SVC+SGD+PA & 0.708 & Embeddia & BOW+GloVe-LSTM+POS-LSTM & 0.613 \

BNU-HKBU & BERT & 0.806 & UBC NLP & Emsemble of XGBoost+AdaBoost+logistic regression & 0.706 & NoOffense & - & 0.613 \

SentiBERT & BERT & 0.804 & Pardeep & GRU & 0.700 & Amobee & CNN+token embedding & 0.591 \

NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM,Transformer,SVM and Random Forest & 0.803 & MIDAS & model based on heuristics & 0.695 & orabia & - & 0.588 \

YNUWB & CNN+word embeddings & 0.802 & NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM, Transformer,SVM and Random Forest & 0.692 & UBC NLP & Ensemble of logistic regression+AdaBoost+XGBoost & 0.586 \

LTL-UDE & BERT & 0.802 & Vadym & - & 0.692 & na14 & - & 0.586

end{tabular}

end{table}

end{document}

Here is my suggestion on how to restructure your table. As the table was too wide to fit into the margins (even on a landscape page) I decided to put the three sub-tasks below each other instead of next to each other. I have also used the horizontal lines from the booktabs package and the tabularx package for a table that automatically is as wide as the textwidth.

documentclass{article}

usepackage{tabularx}

usepackage{booktabs}

usepackage{ragged2e}



begin{document}



begin{table}

centering

label{tabelaSemEval}

begin{tabularx}{linewidth}{@{quadquad}l>{RaggedRight}Xc} 

toprule

Team ranks & Approach & F1 score \

midrule

multicolumn{3}{l}{textit{Sub-task A}}\

NULI & BERT & 0.829   \

vradivchev anikolov & BERT+GloVe & 0.815 \

UM-IU@LING & BERT & 0.814   \

Embeddia & BERT & 0.808  \

MIDAS & CNN+LSTM+GRU and word embeddings & 0.807 \

BNU-HKBU & BERT & 0.806  \

SentiBERT & BERT & 0.804 \

NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM,Transformer,SVM and Random Forest & 0.803  \

YNUWB & CNN+word embeddings & 0.802 \

LTL-UDE & BERT & 0.802  \

midrule

multicolumn{3}{l}{textit{Sub-task B}}\

jhan014 & MSOC & 0.755 \

Amobee & CNN+token embedding & 0.739 \

HHU & LSTM & 0.719\

NULI & BERT & 0.716 \

NIT Agartala & Logistic regression+ Linear SVC+SGD+PA & 0.708 \

UBC NLP & Emsemble of XGBoost+AdaBoost+logistic regression & 0.706 \

Pardeep & GRU & 0.700 \

MIDAS & model based on heuristics & 0.695 \

NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM, Transformer,SVM and Random Forest & 0.692\

Vadym & - & 0.692 \

midrule

multicolumn{3}{l}{textit{Sub-task C}}\

vradivchev anikolov & BERT+GloVe & 0.660\

NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM, Transformer,SVM and Random Forest & 0.628 \

Fermi & ELMo embeddings+ SVM & 0.626 \

YNU-HPCC &  & 0.621 \

Embeddia & BOW+GloVe-LSTM+POS-LSTM & 0.613 \

NoOffense & - & 0.613 \

Amobee & CNN+token embedding & 0.591 \

orabia & - & 0.588 \

UBC NLP & Ensemble of logistic regression+AdaBoost+XGBoost & 0.586 \

na14 & - & 0.586 \

bottomrule

end{tabularx}

end{table}



end{document}

Another possibility: a table in landscape format, playing with the margins, the font size and the separating space between columns. I removed all vertical rules, replaced the hyphens with the more appropriate endashes, and added spaces around the + signs, to make line breaking easier:

documentclass{article}

usepackage[utf8]{inputenc}

usepackage[english]{babel}

usepackage{ragged2e}

usepackage[margin=2cm]{geometry}

usepackage{lscape}

usepackage{tabularx, booktabs, makecell}

renewcommand{theadfont}{bfseries}



begin{document}



begin{landscape}

setlength{tabcolsep}{4pt}

footnotesize

begin{table}

centering

label{tabelaSemEval}

    begin{tabularx}{linewidth}{*{2}{l>{RaggedRight}X@{}c}l>{RaggedRight}X@{}c}

    toprule

    multicolumn{3}{c}{textbf{Sub-task A}} & multicolumn{3}{c}{textbf{Sub-task B}} & multicolumn{3}{c}{textbf{Sub-task C }} \[1ex]

    thead[l]{Team Ranks} &thead[l]{Approach}& thead{F1 score,}& thead[l]{Team Ranks} &thead[l]{Approach}& thead{F1 score,} & thead[l]{Team Ranks} &thead[lc]{Approach}& thead{F1 score,}\[1ex]

    cmidrule(lr){1-3}cmidrule(lr){4-6}cmidrule(lr){7-9}

    addlinespace[2ex]

    NULI & BERT & 0.829 & jhan014 & MSOC & 0.755 & vradivchev anikolov & BERT + GloVe & 0.660 \

    vradivchev anikolov & BERT + GloVe & 0.815 & Amobee & CNN + token embedding & 0.739 & NLPR@SRPOL & ensemble of OpenAI,Finetune, LSTM, Transformer,SVM and Random Forest & 0.628 \

    UM-IU@LING & BERT & 0.814 & HHU & LSTM & 0.719 & Fermi & ELMo embeddings + SVM & 0.626 \

    Embeddia & BERT & 0.808 & NULI & BERT & 0.716 & YNU-HPCC & & 0.621 \

    MIDAS & CNN + LSTM + GRU and word embeddings & 0.807 & NIT Agartala & Logistic regression + Linear SVC + SGD + PA & 0.708 & Embeddia & BOW + GloVe-LSTM + POS-LSTM & 0.613 \

    BNU-HKBU & BERT & 0.806 & UBC NLP & Ensemble of XGBoost + AdaBoost + logistic regression & 0.706 & NoOffense & -- & 0.613 \

    SentiBERT & BERT & 0.804 & Pardeep & GRU & 0.700 & Amobee & CNN + token embedding & 0.591 \

    NLPR@SRPOL & ensemble of OpenAI, Finetune, LSTM, Transformer, SVM and Random Forest & 0.803 & MIDAS & model based on heuristics & 0.695 & orabia & -- & 0.588 \

    YNUWB & CNN + word embeddings & 0.802 & NLPR@SRPOL & ensemble of OpenAI, Finetune, LSTM, Transformer, SVM and Random Forest & 0.692 & UBC NLP & Ensemble of logistic regression + AdaBoost + XGBoost & 0.586 \

    LTL-UDE & BERT & 0.802 & Vadym & -- & 0.692 & na14 & -- & 0.586 \

    addlinespace[2ex]

    bottomrule

    end{tabularx}

end{table}

end{landscape}



end{document}