Mdthbs

I am trying to align the right arrows in my table. Can anyone tell me how to do that? Preferably keeping the structure of my table. (see example below)

documentclass[a4paper, 12pt]{article}

    usepackage{threeparttable}

    usepackage{longtable, booktabs, tabularx}

    begin{document}  







begin{table}[h]

      centering

      caption{Transfer Entropy Results}

      label{tab1:correlation}

      begin{threeparttable}

      begin{tabular*}{textwidth}{l@{extracolsep{fill}}*{5}{c}}

      toprule

        multicolumn{1}{l}{Direction} &  multicolumn{1}{c}{TE} & multicolumn{1}{c}{ETE} &  multicolumn{1}{c}{STD} &  multicolumn{1}{c}{P-value} \



    midrule

    Bitcoin $rightarrow$ IPImicro & 0.015 & 0.000 & 0.023 & 0.473 \

    addlinespace

    IPImicro $rightarrow$ Bitcoin & 0.091 & 0.066 & 0.025 & 0.027**  \

    addlinespace

    Bitcoin $rightarrow$ IPImacro & 0.007 & 0.000 & 0.028 & 0.650  \

    addlinespace

    IPImacro $rightarrow$ Bitcoin & 0.073 & 0.044 & 0.027 & 0.066**  \

    bottomrule

  end{tabular*}

  begin{tablenotes}[para,flushleft]

  footnotesize

  itemhspace{-2.5pt}noindenttextit{Note:} This table presents the Transfer Entropy estimation results. H0: No information flow. Statistical significance is based on a bootstrapped Markov chain of the transfer entropy estimates with 300 bootstrap replications. Note that the sign and the numerical value of the transfer Entropy cannot be compared, i.e. determining the magnitude and dominant direction of the information flow is not possible (cite{behrendt2019rtransferentropy}). We also test a vector autoregressive (VAR) model and test for Granger causality (Table ref{tab1:var} and ref{tab1:granger} in the Appendix). However, because it is limited to linear relationships, the VAR model could not reveal any relationship between IPImicro, IPImacro and Bitcoin. Standard deviation in parentheses; *** p < 0.01; ** p < 0.05; * p < 0.10.

  end{tablenotes}

  end{threeparttable}

end{table}



end{document}

I propose to put what's before arrows in an eqmakebox– and added various improvement, via siunitx and caption:

documentclass{article}

usepackage{array, threeparttable, booktabs}

usepackage{eqparbox, siunitx}

usepackage[skip =6pt]{caption}



begin{document}



begin{table}[h]

      centering

sisetup{table-format=1.3, table-number-alignment=center, table-space-text-post=**, table-align-text-post=false}

  begin{threeparttable}

  caption{Transfer Entropy Results}

  label{tab1:correlation}

  begin{tabular*}{textwidth}{@{}l@{extracolsep{fill}}*{4}{S}}

  toprule

    Direction & {TE} & {ETE} & {STD} & {P-value} \



    midrule

    eqmakebox[D][l]{Bitcoin} $rightarrow$ IPImicro & 0.015 & 0.000 & 0.023 & 0.473 \

    addlinespace

    eqmakebox[D][l]{IPImicro} $rightarrow$ Bitcoin & 0.091 & 0.066 & 0.025 & 0.027** \

    addlinespace

    eqmakebox[D][l]{Bitcoin} $rightarrow$ IPImacro & 0.007 & 0.000 & 0.028 & 0.650 \

    addlinespace

   eqmakebox[D][l]{IPImacro} $rightarrow$ Bitcoin & 0.073 & 0.044 & 0.027 & 0.066** \

    bottomrule

  end{tabular*}

  begin{tablenotes}[para,flushleft]

  footnotesizesmallskip

  itemhspace{-2.5pt}noindenttextit{Note:} This table presents the Transfer Entropy estimation results. H0: No information flow. Statistical significance is based on a bootstrapped Markov chain of the transfer entropy estimates with 300 bootstrap replications. Note that the sign and the numerical value of the transfer Entropy cannot be compared, i.e. determining the magnitude and dominant direction of the information flow is not possible (cite{behrendt2019rtransferentropy}). We also test a vector autoregressive (VAR) model and test for Granger causality (Table ref{tab1:var} and ref{tab1:granger} in the Appendix). However, because it is limited to linear relationships, the VAR model could not reveal any relationship between IPImicro, IPImacro and Bitcoin. Standard deviation in parentheses; *** $ p < 0.01 $; ** $p < 0.05 $; * $ p < 0.10 $.

  end{tablenotes}

  end{threeparttable}

end{table}



end{document}

Some suggestions and comments:

• As @daleif has already suggested in a comment, set up a dedicated column for the rightarrow symbols.




• Your code has way too many multicolumn wrappers; cull them ruthlessly.




• The centering directive is not needed since the width of the tabular* environment is set to textwidth.




• The tabular* environment should have 4, not 5, columns of type c.




• The caption statement should be inside, not outside the threeparttable environment. (The three formal parts of a threepartable environment are the caption, the tabular-like environment, and the tablenotes environment.




• There seems to be no compelling need for the threeparttable machiner since there are no tnote directives in your code.

documentclass[a4paper, 12pt]{article}

usepackage[T1]{fontenc}

%usepackage{threeparttable}

usepackage{%longtable, 

             booktabs, %tabularx

             array}

newcolumntype{C}{>{${}}c<{{}$}} % for math symbols such as "to"

begin{document}



begin{table}[h]

    setlengthtabcolsep{0pt}

      %begin{threeparttable}

      %%centering % is redundant

    caption{Transfer Entropy Results}

    label{tab1:correlation}

    begin{tabular*}{textwidth}{ lCl @{extracolsep{fill}} *{4}{c}}

    toprule

    multicolumn{3}{l}{Direction} &  TE & ETE & STD & P-value \



    midrule

    Bitcoin  &to& IPImicro & 0.015 & 0.000 & 0.023 & 0.473 \

    addlinespace

    IPImicro &to& Bitcoin  & 0.091 & 0.066 & 0.025 & 0.027**  \

    addlinespace

    Bitcoin  &to& IPImacro & 0.007 & 0.000 & 0.028 & 0.650  \

    addlinespace

    IPImacro &to& Bitcoin  & 0.073 & 0.044 & 0.027 & 0.066**  \

    bottomrule

    end{tabular*}

%begin{tablenotes}[para,flushleft]



    medskip

    footnotesize

    textit{Note:} This table presents the Transfer Entropy estimation results. H0: No information flow. Statistical significance is based on a bootstrapped Markov chain of the transfer entropy estimates with 300 bootstrap replications. Note that the sign and the numerical value of the transfer Entropy cannot be compared, i.e. determining the magnitude and dominant direction of the information flow is not possible (cite{behrendt2019rtransferentropy}). We also estimate a vector autoregressive (VAR) model and test for Granger causality (Table ref{tab1:var} and ref{tab1:granger} in the Appendix). However, because it is limited to linear relationships, the VAR model could not reveal any relationship between IPImicro, IPImacro and Bitcoin. Standard deviations in parentheses; *** p < 0.01; ** p < 0.05; * p < 0.10.

%  end{tablenotes}

%  end{threeparttable}

end{table}



end{document} 

one more example, with use of siunitx and threeparttablex packages:

documentclass{article}

usepackage{booktabs}

usepackage[referable]{threeparttablex}

usepackage{siunitx}

usepackage[skip =6pt]{caption}



begin{document}

    begin{table}[ht]

      centering

sisetup{table-format=1.3, 

         table-space-text-post=**}

setlengthtabcolsep{0pt}

begin{threeparttable}

caption{Transfer Entropy Results}

label{tab1:correlation}

    begin{tabular*}{linewidth}{l>{ $rightarrow$ }l

                                 @{extracolsep{fill}} *{4}{S}}

  toprule

multicolumn{2}{c}{Direction}           & {TE}  & {ETE} & {STD} & {P-value} \

    midrule

Bitcoin     & IPImicro    & 0.015 & 0.000 & 0.023 & 0.473     \

    addlinespace

IPImicro    & Bitcoin     & 0.091 & 0.066 & 0.025 & 0.027**   \

    addlinespace

Bitcoin     & IPImacro    & 0.007 & 0.000 & 0.028 & 0.650     \

    addlinespace

IPImacro    & Bitcoin     & 0.073 & 0.044 & 0.027 & 0.066**   \

    bottomrule

  end{tabular*}

  begin{tablenotes}[para,flushleft]footnotesizesmallskip

note This table presents the Transfer Entropy estimation results. H0: No information flow. Statistical significance is based on a bootstrapped Markov chain of the transfer entropy estimates with 300 bootstrap replications. Note that the sign and the numerical value of the transfer Entropy cannot be compared, i.e. determining the magnitude and dominant direction of the information flow is not possible (cite{behrendt2019rtransferentropy}). We also test a vector autoregressive (VAR) model and test for Granger causality (Table ref{tab1:var} and ref{tab1:granger} in the Appendix). However, because it is limited to linear relationships, the VAR model could not reveal any relationship between IPImicro, IPImacro and Bitcoin. 

    item[***]  $p < 0.01 $; 

    item[**]   $p < 0.05 $; 

    item[*]    $p < 0.10 $.

  end{tablenotes}

end{threeparttable}

    end{table}

end{document}