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對齊表格中的右箭頭

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對齊表格中的右箭頭

我正在嘗試對齊表格中的右箭頭。誰能告訴我該怎麼做？最好保持我的桌子的結構。 （見下面的例子）

\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
  \item\hspace{-2.5pt}\noindent\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 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}

答案1

我建議將箭頭之前的內容放在 – 中，並通過和\eqmakebox添加各種改進：siunitxcaption

\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]
  \footnotesize\smallskip
  \item\hspace{-2.5pt}\noindent\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 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}

在此輸入影像描述

答案2

再舉一個例子，使用siunitx和threeparttablex包：

在此輸入影像描述

\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=**}
\setlength\tabcolsep{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]\footnotesize\smallskip
\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}

答案3

一些建議和意見：

  • 正如 @daleif 在評論中已經建議的那樣，為符號設定一個專用列\rightarrow。

  • 你的程式碼有太多的\multicolumn包裝器；無情地剔除他們。

  • \centering不需要該語句之前的指令，\caption因為環境的寬度tabular*設定為\textwidth。

  • 該tabular*環境有 4 個（而不是 5 個）資料列。

  • 考慮左對齊而不是將資料列中的數字居中。

  • 該\caption聲明應該在threeparttable環境內部，而不是外部。 （環境的三個正式部分threepartable是標題、表格環境和tablenotes環境。

  • 由於程式碼中threeparttable沒有指令，因此似乎對機器沒有迫切的需求。\tnote

  • 可選：刪除圖例中的「括號中的標準差」句子，因為括號中沒有任何材質。

在此輸入影像描述

\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]
    \setlength\tabcolsep{0pt}
      %\begin{threeparttable}
      %%\centering % is redundant
    \caption{Transfer Entropy Results}
    \label{tab1:correlation}
    \begin{tabular*}{\textwidth}{ lCl @{\extracolsep{\fill}} *{4}{l}}
    \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}

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