我尝试旋转一个大表格以及相应的标题。我想在这个旋转的图形周围换行。我有这个 MWE，但在这个 MWE 中，标题没有旋转，因此需要大量空间，所以表格不再可读。我想给表格尽可能多的空间。
\documentclass[]{scrbook}
\usepackage{wrapfig}
\usepackage{rotating}
\begin{document}
\subsubsection{QuarterlyTouristsIndia}
\begin{wraptable}{r}{0.25\textwidth}
\centering
\caption{Excerpt of the QuaterlyTouristsIndia dataset.}
\begin{sideways}
\resizebox{\textheight}{!}{%
{\begin{tabular}{lrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr}
index & \multicolumn{1}{l}{f1} & \multicolumn{1}{l}{f2} & \multicolumn{1}{l}{f3} & \multicolumn{1}{l}{f4} & \multicolumn{1}{l}{f5} & \multicolumn{1}{l}{f6} & \multicolumn{1}{l}{f7} & \multicolumn{1}{l}{f8} & \multicolumn{1}{l}{f9} & \multicolumn{1}{l}{f10} & \multicolumn{1}{l}{f11} & \multicolumn{1}{l}{f12} & \multicolumn{1}{l}{f13} & \multicolumn{1}{l}{f14} & \multicolumn{1}{l}{f15} & \multicolumn{1}{l}{f16} & \multicolumn{1}{l}{f17} & \multicolumn{1}{l}{f18} & \multicolumn{1}{l}{f19} & \multicolumn{1}{l}{f20} & \multicolumn{1}{l}{f21} & \multicolumn{1}{l}{f22} & \multicolumn{1}{l}{f23} & \multicolumn{1}{l}{f24} & \multicolumn{1}{l}{f25} & \multicolumn{1}{l}{f26} & \multicolumn{1}{l}{f27} & \multicolumn{1}{l}{f28} & \multicolumn{1}{l}{f29} & \multicolumn{1}{l}{f30} & \multicolumn{1}{l}{f31} & \multicolumn{1}{l}{f32} & \multicolumn{1}{l}{f33} & \multicolumn{1}{l}{f34} & \multicolumn{1}{l}{f35} & \multicolumn{1}{l}{f36} & \multicolumn{1}{l}{f37} & \multicolumn{1}{l}{f38} & \multicolumn{1}{l}{f39} & \multicolumn{1}{l}{f40} & \multicolumn{1}{l}{f41} & \multicolumn{1}{l}{TouristsIndia} \\
01.01.2005 & 8338 & 7933 & 1463 & 1932 & 1426 & 676 & 3600 & 1375 & 1287 & 937 & 8738 & 7933 & 1462 & 2004 & 1477 & 689 & 3771 & 1444 & 1287 & 1040 & 13068 & 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824 & 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393 & 1108967 \\
01.04.2005 & 8641 & 7608 & 1517 & 1994 & 1480 & 699 & 3669 & 1424 & 1289 & 957 & 8224 & 7608 & 1450 & 1960 & 1460 & 694 & 3537 & 1372 & 1289 & 876 & 13455 & 11852 & 2901 & 2861 & 2073 & 1139 & 5588 & 2048 & 1900 & 1639 & 12816 & 11852 & 2778 & 2797 & 2017 & 1126 & 5375 & 1971 & 1900 & 1503 & 6257 & 721024 \\
01.07.2005 & 8861 & 7670 & 1582 & 2030 & 1516 & 725 & 3787 & 1469 & 1331 & 987 & 8404 & 7670 & 1232 & 1997 & 1498 & 707 & 3739 & 1429 & 1331 & 979 & 13644 & 11730 & 2943 & 2891 & 2110 & 1166 & 5699 & 2091 & 1934 & 1673 & 12861 & 11730 & 2253 & 2827 & 2077 & 1130 & 5608 & 2023 & 1934 & 1650 & 6964 & 838583 \\
01.10.2005 & 9206 & 8840 & 1654 & 2116 & 1589 & 776 & 3930 & 1533 & 1379 & 1019 & 9592 & 8840 & 2060 & 2104 & 1568 & 782 & 3916 & 1546 & 1379 & 991 & 13990 & 13350 & 2997 & 2970 & 2177 & 1232 & 5843 & 2152 & 1990 & 1701 & 14497 & 13350 & 3702 & 2969 & 2172 & 1238 & 5809 & 2170 & 1990 & 1649 & 10509 & 1250037 \\
01.01.2006 & 9582 & 9107 & 1699 & 2182 & 1634 & 804 & 4106 & 1594 & 1468 & 1044 & 10069 & 9107 & 1710 & 2262 & 1693 & 821 & 4301 & 1672 & 1468 & 1161 & 14341 & 13793 & 3007 & 3042 & 2230 & 1254 & 6062 & 2222 & 2123 & 1717 & 15256 & 13793 & 3115 & 3170 & 2324 & 1297 & 6399 & 2349 & 2123 & 1927 & 11910 & 1267443 \\
01.04.2006 & 9877 & 8812 & 1721 & 2320 & 1740 & 837 & 4235 & 1645 & 1521 & 1069 & 9356 & 8812 & 1633 & 2285 & 1720 & 835 & 4107 & 1593 & 1521 & 992 & 14531 & 12956 & 3034 & 3169 & 2326 & 1267 & 6126 & 2252 & 2155 & 1719 & 13765 & 12956 & 2886 & 3106 & 2272 & 1253 & 5928 & 2174 & 2155 & 1599 & 7566 & 853856 \\
01.07.2006 & 10411 & 8965 & 1788 & 2427 & 1845 & 871 & 4419 & 1745 & 1587 & 1087 & 9866 & 8965 & 1381 & 2380 & 1821 & 851 & 4369 & 1698 & 1587 & 1083 & 14995 & 12877 & 3067 & 3267 & 2411 & 1286 & 6262 & 2343 & 2201 & 1718 & 14178 & 12877 & 2331 & 3185 & 2369 & 1247 & 6173 & 2268 & 2201 & 1704 & 8970 & 929458 \\
\end{tabular}}}
\end{sideways}
\end{wraptable}
This is a multivariate dataset consisting of different configurations of Gross Domestic Product across multiple sectors and Foreign Exchange Earnings as determinants of Foreign Tourism Demand and the number of Foreign Tourist Arrivals in India.
The Foreign Tourist Arrivals are acquired from Indian Tourism Statistics for the duration of 2015-2016.
The Foreign Exchange Earnings are collected from Various Issues of Indian Tourism Statistics, M/o Tourism, Market Research Division in Indian Rupee Crores. One Crore is equal to the number 10,000,000.
The different GDP values are extracted from the Organisation for Economic Co-Operation and Development in Indian Rupee Billions.
The data contains 41 features which are determinants of Foreign Tourist Arrivals and corresponding Foreign Tourist Arrivals for January-March from 2005 to 2016.
The first 40 features contain information regarding different GDP configurations (in India Rupee Billions), which are further classified in the following categories:
\begin{itemize}
\item CQRSA: National currency, current prices, quarterly levels, seasonally adjusted.
\item CQR: National currency, current prices, quarterly levels.
\item VNBQRSA: National currency, constant prices, national base year, quarterly levels, seasonally adjusted.
\item VNBQR: National currency, constant prices, national base year, quarterly levels.
\end{itemize}
Each of the configurations or GDP categories have their share in multiple sectors and can therefore be divided in sub-categories:
\begin{itemize}
\item gross domestic product at market prices - output approach
\item gross value added at basic prices
\item total activity
\item agriculture
\item forestry and fishing
\item industry
\item including energy
\item manufacturing
\item construction
\item services
\item distribution trade, repairs, transport, accommodation, food service
\item real estate activities
\item public administration, education, human health
\end{itemize}
The second to last or 41st feature is the total Foreign Exchange Earnings (in Indian Rupee Crores). The 42nd feature are the foreign tourist arrivals in India.
The dataset therefore contains 42 columns and 48 rows.
An explanation to each column is shown in table \ref{tab:india}.
\end{document}
答案1
尝试这个解决方案：
\documentclass[]{scrbook}
\usepackage{wrapfig}
%\usepackage{rotating}
\usepackage{adjustbox}
\begin{document}
\subsubsection{QuarterlyTouristsIndia}
{\noindent \begin{wraptable}{r}{0.25\textwidth}
\centering
\begin{adjustbox}{addcode={\begin{minipage}{\width}}{%
\caption{\footnotesize Excerpt of the QuaterlyTouristsIndia dataset.}\label{tab:india}
\end{minipage}},rotate=90,center}
\resizebox{\textheight}{!}{%
{\begin{tabular}{lrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr}
index & \multicolumn{1}{l}{f1} & \multicolumn{1}{l}{f2} & \multicolumn{1}{l}{f3} & \multicolumn{1}{l}{f4} & \multicolumn{1}{l}{f5} & \multicolumn{1}{l}{f6} & \multicolumn{1}{l}{f7} & \multicolumn{1}{l}{f8} & \multicolumn{1}{l}{f9} & \multicolumn{1}{l}{f10} & \multicolumn{1}{l}{f11} & \multicolumn{1}{l}{f12} & \multicolumn{1}{l}{f13} & \multicolumn{1}{l}{f14} & \multicolumn{1}{l}{f15} & \multicolumn{1}{l}{f16} & \multicolumn{1}{l}{f17} & \multicolumn{1}{l}{f18} & \multicolumn{1}{l}{f19} & \multicolumn{1}{l}{f20} & \multicolumn{1}{l}{f21} & \multicolumn{1}{l}{f22} & \multicolumn{1}{l}{f23} & \multicolumn{1}{l}{f24} & \multicolumn{1}{l}{f25} & \multicolumn{1}{l}{f26} & \multicolumn{1}{l}{f27} & \multicolumn{1}{l}{f28} & \multicolumn{1}{l}{f29} & \multicolumn{1}{l}{f30} & \multicolumn{1}{l}{f31} & \multicolumn{1}{l}{f32} & \multicolumn{1}{l}{f33} & \multicolumn{1}{l}{f34} & \multicolumn{1}{l}{f35} & \multicolumn{1}{l}{f36} & \multicolumn{1}{l}{f37} & \multicolumn{1}{l}{f38} & \multicolumn{1}{l}{f39} & \multicolumn{1}{l}{f40} & \multicolumn{1}{l}{f41} & \multicolumn{1}{l}{TouristsIndia} \\
01.01.2005 & 8338 & 7933 & 1463 & 1932 & 1426 & 676 & 3600 & 1375 & 1287 & 937 & 8738 & 7933 & 1462 & 2004 & 1477 & 689 & 3771 & 1444 & 1287 & 1040 & 13068 & 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824 & 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393 & 1108967 \\
01.04.2005 & 8641 & 7608 & 1517 & 1994 & 1480 & 699 & 3669 & 1424 & 1289 & 957 & 8224 & 7608 & 1450 & 1960 & 1460 & 694 & 3537 & 1372 & 1289 & 876 & 13455 & 11852 & 2901 & 2861 & 2073 & 1139 & 5588 & 2048 & 1900 & 1639 & 12816 & 11852 & 2778 & 2797 & 2017 & 1126 & 5375 & 1971 & 1900 & 1503 & 6257 & 721024 \\
01.07.2005 & 8861 & 7670 & 1582 & 2030 & 1516 & 725 & 3787 & 1469 & 1331 & 987 & 8404 & 7670 & 1232 & 1997 & 1498 & 707 & 3739 & 1429 & 1331 & 979 & 13644 & 11730 & 2943 & 2891 & 2110 & 1166 & 5699 & 2091 & 1934 & 1673 & 12861 & 11730 & 2253 & 2827 & 2077 & 1130 & 5608 & 2023 & 1934 & 1650 & 6964 & 838583 \\
01.10.2005 & 9206 & 8840 & 1654 & 2116 & 1589 & 776 & 3930 & 1533 & 1379 & 1019 & 9592 & 8840 & 2060 & 2104 & 1568 & 782 & 3916 & 1546 & 1379 & 991 & 13990 & 13350 & 2997 & 2970 & 2177 & 1232 & 5843 & 2152 & 1990 & 1701 & 14497 & 13350 & 3702 & 2969 & 2172 & 1238 & 5809 & 2170 & 1990 & 1649 & 10509 & 1250037 \\
01.01.2006 & 9582 & 9107 & 1699 & 2182 & 1634 & 804 & 4106 & 1594 & 1468 & 1044 & 10069 & 9107 & 1710 & 2262 & 1693 & 821 & 4301 & 1672 & 1468 & 1161 & 14341 & 13793 & 3007 & 3042 & 2230 & 1254 & 6062 & 2222 & 2123 & 1717 & 15256 & 13793 & 3115 & 3170 & 2324 & 1297 & 6399 & 2349 & 2123 & 1927 & 11910 & 1267443 \\
01.04.2006 & 9877 & 8812 & 1721 & 2320 & 1740 & 837 & 4235 & 1645 & 1521 & 1069 & 9356 & 8812 & 1633 & 2285 & 1720 & 835 & 4107 & 1593 & 1521 & 992 & 14531 & 12956 & 3034 & 3169 & 2326 & 1267 & 6126 & 2252 & 2155 & 1719 & 13765 & 12956 & 2886 & 3106 & 2272 & 1253 & 5928 & 2174 & 2155 & 1599 & 7566 & 853856 \\
01.07.2006 & 10411 & 8965 & 1788 & 2427 & 1845 & 871 & 4419 & 1745 & 1587 & 1087 & 9866 & 8965 & 1381 & 2380 & 1821 & 851 & 4369 & 1698 & 1587 & 1083 & 14995 & 12877 & 3067 & 3267 & 2411 & 1286 & 6262 & 2343 & 2201 & 1718 & 14178 & 12877 & 2331 & 3185 & 2369 & 1247 & 6173 & 2268 & 2201 & 1704 & 8970 & 929458 \\
\end{tabular}}}
\end{adjustbox}
\end{wraptable}
This is a multivariate dataset consisting of different configurations of Gross Domestic Product across multiple sectors and Foreign Exchange Earnings as determinants of Foreign Tourism Demand and the number of Foreign Tourist Arrivals in India.
The Foreign Tourist Arrivals are acquired from Indian Tourism Statistics for the duration of 2015-2016.
The Foreign Exchange Earnings are collected from Various Issues of Indian Tourism Statistics, M/o Tourism, Market Research Division in Indian Rupee Crores. One Crore is equal to the number 10,000,000.
The different GDP values are extracted from the Organisation for Economic Co-Operation and Development in Indian Rupee Billions.
The data contains 41 features which are determinants of Foreign Tourist Arrivals and corresponding Foreign Tourist Arrivals for January-March from 2005 to 2016.
The first 40 features contain information regarding different GDP configurations (in India Rupee Billions), which are further classified in the following categories:
\begin{itemize}
\item CQRSA: National currency, current prices, quarterly levels, seasonally adjusted.
\item CQR: National currency, current prices, quarterly levels.
\item VNBQRSA: National currency, constant prices, national base year, quarterly levels, seasonally adjusted.
\item VNBQR: National currency, constant prices, national base year, quarterly levels.
\end{itemize}
Each of the configurations or GDP categories have their share in multiple sectors and can therefore be divided in sub-categories:
\begin{itemize}
\item gross domestic product at market prices - output approach
\item gross value added at basic prices
\item total activity
\item agriculture
\item forestry and fishing
\item industry
\item including energy
\item manufacturing
\item construction
\item services
\item distribution trade, repairs, transport, accommodation, food service
\item real estate activities
\item public administration, education, human health
\end{itemize}
} % end wrap <<<<<<<<<
The second to last or 41st feature is the total Foreign Exchange Earnings (in Indian Rupee Crores). The 42nd feature are the foreign tourist arrivals in India.
The dataset therefore contains 42 columns and 48 rows.
An explanation to each column is shown in table \ref{tab:india}.
\end{document}
更新
要使标题位于表格上方，请使用
{\noindent \begin{wraptable}{r}{0.20\textwidth}
\centering
\begin{adjustbox}{addcode={\begin{minipage}{\width}\caption{\footnotesize Excerpt of the QuaterlyTouristsIndia dataset.}\label{tab:india}}{\end{minipage}},rotate=90,center}
\resizebox{\textheight}{!}{%
答案2
这显示了如何使用 paracol 执行此操作。缺点是您必须手动拆分 itemize。优点是您可以重叠\subsection。
可能有办法消除悬挂缩进。可惜的是，KOMA 与 caption 包不兼容。请参阅包“caption”可以与 KOMAScript 类一起使用吗？
如果不将该表格拆分成几部分，就很难使它变得可读。
\documentclass[]{scrbook}
\usepackage{adjustbox}
\usepackage{paracol}
\globalcounter*
\newlength{\tempdima}% reserve global name
\begin{document}
\setcolumnwidth{\dimexpr 0.75\textwidth-\columnsep}
\begin{paracol}{2}
\subsubsection{QuarterlyTouristsIndia}
This is a multivariate dataset consisting of different configurations of Gross Domestic Product across multiple sectors and Foreign Exchange Earnings as determinants of Foreign Tourism Demand and the number of Foreign Tourist Arrivals in India.
The Foreign Tourist Arrivals are acquired from Indian Tourism Statistics for the duration of 2015-2016.
The Foreign Exchange Earnings are collected from Various Issues of Indian Tourism Statistics, M/o Tourism, Market Research Division in Indian Rupee Crores. One Crore is equal to the number 10,000,000.
The different GDP values are extracted from the Organisation for Economic Co-Operation and Development in Indian Rupee Billions.
The data contains 41 features which are determinants of Foreign Tourist Arrivals and corresponding Foreign Tourist Arrivals for January-March from 2005 to 2016.
The first 40 features contain information regarding different GDP configurations (in India Rupee Billions), which are further classified in the following categories:
\begin{itemize}
\item CQRSA: National currency, current prices, quarterly levels, seasonally adjusted.
\item CQR: National currency, current prices, quarterly levels.
\item VNBQRSA: National currency, constant prices, national base year, quarterly levels, seasonally adjusted.
\item VNBQR: National currency, constant prices, national base year, quarterly levels.
\end{itemize}
Each of the configurations or GDP categories have their share in multiple sectors and can therefore be divided in sub-categories:
\begin{itemize}
\item gross domestic product at market prices - output approach
\item gross value added at basic prices
\item total activity
\item agriculture
\item forestry and fishing
\item industry
\item including energy
\item manufacturing
\end{itemize}% manually break itemize
\switchcolumn
\begin{table}[h]
\setbox0=\vbox{\caption{Excerpt of the QuaterlyTouristsIndia dataset.}}% measure height of caption
\global\tempdima=\dimexpr \ht0+\dp0\relax
\unvbox0
\end{table}% [h] tables will not span entire page
\centering
\rotatebox{90}{\resizebox{\dimexpr \textheight-\tempdima-\intextsep}{!}{%
\begin{tabular}{lrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr}
index & \multicolumn{1}{l}{f1} & \multicolumn{1}{l}{f2} & \multicolumn{1}{l}{f3} & \multicolumn{1}{l}{f4} & \multicolumn{1}{l}{f5} & \multicolumn{1}{l}{f6} & \multicolumn{1}{l}{f7} & \multicolumn{1}{l}{f8} & \multicolumn{1}{l}{f9} & \multicolumn{1}{l}{f10} & \multicolumn{1}{l}{f11} & \multicolumn{1}{l}{f12} & \multicolumn{1}{l}{f13} & \multicolumn{1}{l}{f14} & \multicolumn{1}{l}{f15} & \multicolumn{1}{l}{f16} & \multicolumn{1}{l}{f17} & \multicolumn{1}{l}{f18} & \multicolumn{1}{l}{f19} & \multicolumn{1}{l}{f20} & \multicolumn{1}{l}{f21} & \multicolumn{1}{l}{f22} & \multicolumn{1}{l}{f23} & \multicolumn{1}{l}{f24} & \multicolumn{1}{l}{f25} & \multicolumn{1}{l}{f26} & \multicolumn{1}{l}{f27} & \multicolumn{1}{l}{f28} & \multicolumn{1}{l}{f29} & \multicolumn{1}{l}{f30} & \multicolumn{1}{l}{f31} & \multicolumn{1}{l}{f32} & \multicolumn{1}{l}{f33} & \multicolumn{1}{l}{f34} & \multicolumn{1}{l}{f35} & \multicolumn{1}{l}{f36} & \multicolumn{1}{l}{f37} & \multicolumn{1}{l}{f38} & \multicolumn{1}{l}{f39} & \multicolumn{1}{l}{f40} & \multicolumn{1}{l}{f41} & \multicolumn{1}{l}{TouristsIndia} \\
01.01.2005 & 8338 & 7933 & 1463 & 1932 & 1426 & 676 & 3600 & 1375 & 1287 & 937 & 8738 & 7933 & 1462 & 2004 & 1477 & 689 & 3771 & 1444 & 1287 & 1040 & 13068 & 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824 & 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393 & 1108967 \\
01.04.2005 & 8641 & 7608 & 1517 & 1994 & 1480 & 699 & 3669 & 1424 & 1289 & 957 & 8224 & 7608 & 1450 & 1960 & 1460 & 694 & 3537 & 1372 & 1289 & 876 & 13455 & 11852 & 2901 & 2861 & 2073 & 1139 & 5588 & 2048 & 1900 & 1639 & 12816 & 11852 & 2778 & 2797 & 2017 & 1126 & 5375 & 1971 & 1900 & 1503 & 6257 & 721024 \\
01.07.2005 & 8861 & 7670 & 1582 & 2030 & 1516 & 725 & 3787 & 1469 & 1331 & 987 & 8404 & 7670 & 1232 & 1997 & 1498 & 707 & 3739 & 1429 & 1331 & 979 & 13644 & 11730 & 2943 & 2891 & 2110 & 1166 & 5699 & 2091 & 1934 & 1673 & 12861 & 11730 & 2253 & 2827 & 2077 & 1130 & 5608 & 2023 & 1934 & 1650 & 6964 & 838583 \\
01.10.2005 & 9206 & 8840 & 1654 & 2116 & 1589 & 776 & 3930 & 1533 & 1379 & 1019 & 9592 & 8840 & 2060 & 2104 & 1568 & 782 & 3916 & 1546 & 1379 & 991 & 13990 & 13350 & 2997 & 2970 & 2177 & 1232 & 5843 & 2152 & 1990 & 1701 & 14497 & 13350 & 3702 & 2969 & 2172 & 1238 & 5809 & 2170 & 1990 & 1649 & 10509 & 1250037 \\
01.01.2006 & 9582 & 9107 & 1699 & 2182 & 1634 & 804 & 4106 & 1594 & 1468 & 1044 & 10069 & 9107 & 1710 & 2262 & 1693 & 821 & 4301 & 1672 & 1468 & 1161 & 14341 & 13793 & 3007 & 3042 & 2230 & 1254 & 6062 & 2222 & 2123 & 1717 & 15256 & 13793 & 3115 & 3170 & 2324 & 1297 & 6399 & 2349 & 2123 & 1927 & 11910 & 1267443 \\
01.04.2006 & 9877 & 8812 & 1721 & 2320 & 1740 & 837 & 4235 & 1645 & 1521 & 1069 & 9356 & 8812 & 1633 & 2285 & 1720 & 835 & 4107 & 1593 & 1521 & 992 & 14531 & 12956 & 3034 & 3169 & 2326 & 1267 & 6126 & 2252 & 2155 & 1719 & 13765 & 12956 & 2886 & 3106 & 2272 & 1253 & 5928 & 2174 & 2155 & 1599 & 7566 & 853856 \\
01.07.2006 & 10411 & 8965 & 1788 & 2427 & 1845 & 871 & 4419 & 1745 & 1587 & 1087 & 9866 & 8965 & 1381 & 2380 & 1821 & 851 & 4369 & 1698 & 1587 & 1083 & 14995 & 12877 & 3067 & 3267 & 2411 & 1286 & 6262 & 2343 & 2201 & 1718 & 14178 & 12877 & 2331 & 3185 & 2369 & 1247 & 6173 & 2268 & 2201 & 1704 & 8970 & 929458 \\
\end{tabular}}}
\end{paracol}
\begin{itemize}
\item construction
\item services
\item distribution trade, repairs, transport, accommodation, food service
\item real estate activities
\item public administration, education, human health
\end{itemize}
The second to last or 41st feature is the total Foreign Exchange Earnings (in Indian Rupee Crores). The 42nd feature are the foreign tourist arrivals in India.
The dataset therefore contains 42 columns and 48 rows.
An explanation to each column is shown in table \ref{tab:india}.
\end{document}
答案3
好吧，为了阅读您的 MWE 中的表格以及其他答案中的表格，我需要放大镜...所以我考虑将表格分成两部分并将文档扩展为两页的可能性。这样表格中的\footnotesize字体大小就可以使用，并且变得更易读。
既然你旋转了桌子，我想知道如果我也旋转桌子描述会是什么样子。嗯，这似乎有点不寻常，但无论如何，让我们来看看这种可能性：
\documentclass[]{scrbook}
\usepackage{pdflscape}
\usepackage{multicol}
\usepackage{enumitem}
\usepackage{caption}
\usepackage{tabularray}
\UseTblrLibrary{booktabs, siunitx, varwidth}
\ExplSyntaxOn
\NewChildSelector{eachtwo}
{
\int_step_inline:nnnn {2}{2}{\l_tblr_childs_total_tl}
{ \clist_put_right:Nn \l_tblr_childs_clist {##1} }
}
\ExplSyntaxOff
\begin{document}
\begin{landscape}
\subsubsection{Quarterly Tourists India}
\begin{multicols}{2}\noindent%
This is a multivariate dataset consisting of different configurations of Gross Domestic Product across multiple sectors and Foreign Exchange Earnings as determinants of Foreign Tourism Demand and the number of Foreign Tourist Arrivals in India.
The Foreign Tourist Arrivals are acquired from Indian Tourism Statistics for the duration of 2015-2016.
The Foreign Exchange Earnings are collected from Various Issues of Indian Tourism Statistics, M/o Tourism, Market Research Division in Indian Rupee Crores. One Crore is equal to the number 10,000,000.
The different GDP values are extracted from the Organisation for Economic Co-Operation and Development in Indian Rupee Billions.
The data contains 41 features which are determinants of Foreign Tourist Arrivals and corresponding Foreign Tourist Arrivals for January-March from 2005 to 2016.
The first 40 features contain information regarding different GDP configurations (in India Rupee Billions), which are further classified in the following categories:
\begin{itemize}[parsep=0pt]
\item CQRSA: National currency, current prices, quarterly levels, seasonally adjusted.
\item CQR: National currency, current prices, quarterly levels.
\item VNBQRSA: National currency, constant prices, national base year, quarterly levels, seasonally adjusted.
\item VNBQR: National currency, constant prices, national base year, quarterly levels.
\end{itemize}
Each of the configurations or GDP categories have their share in multiple sectors and can therefore be divided in sub-categories:
\end{multicols}
\begin{table}[!b]
\caption{Excerpt of the Quarterly TouristsIndia dataset (first part)}
\label{tab:india}
\begin{tblr}{colsep=3pt,
colspec = {@{} r Q[c,si={table-format=5.0}]
*{8}{Q[c,si={table-format=4.0}]}
*{2}{Q[c,si={table-format=5.0}]}
*{8}{Q[c,si={table-format=4.0}]}
Q[c,m,si={table-format=5.0}]
Q[c,m,si={table-format=7.0}] @{}},
rows = {font=\footnotesize},
row{2-Z} = {rowsep=-3pt},
row{eachtwo} = {abovesep=1ex},
row{2} = {abovesep=0pt},
row{Z} = {belowsep=0pt},
measure = vbox
}
\toprule
\SetCell{c} index
& {{{f1}}} & {{{f2}}} & {{{f3}}} & {{{f4}}} & {{{f5}}} & {{{f6}}} & {{{f7}}} & {{{f8}}} & {{{f9}}} & {{{f10}}}
& {{{f11}}} & {{{f12}}} & {{{f13}}} & {{{f14}}} & {{{f15}}} & {{{f16}}} & {{{f17}}} & {{{f18}}} & {{{f19}}} & {{{f20}}}
& {{{Tourists\\India}}} \\
\midrule
01.01.2005
& 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824
& 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393
& 1108967 \\
01.04.2005
& 8641 & 7608 & 1517 & 1994 & 1480 & 699 & 3669 & 1424 & 1289 & 957
& 8224 & 7608 & 1450 & 1960 & 1460 & 694 & 3537 & 1372 & 1289 & 876
& 13455 \\
01.07.2005
& 8861 & 7670 & 1582 & 2030 & 1516 & 725 & 3787 & 1469 & 1331 & 987
& 8404 & 7670 & 1232 & 1997 & 1498 & 707 & 3739 & 1429 & 1331 & 979
& 13644 \\
01.10.2005
& 9206 & 8840 & 1654 & 2116 & 1589 & 776 & 3930 & 1533 & 1379 & 1019
& 9592 & 8840 & 2060 & 2104 & 1568 & 782 & 3916 & 1546 & 1379 & 991
& 13990 \\
01.01.2006
& 9582 & 9107 & 1699 & 2182 & 1634 & 804 & 4106 & 1594 & 1468 & 1044
& 10069 & 9107 & 1710 & 2262 & 1693 & 821 & 4301 & 1672 & 1468 & 1161
& 14341 \\
01.04.2006
& 9877 & 8812 & 1721 & 2320 & 1740 & 837 & 4235 & 1645 & 1521 & 1069
& 9356 & 8812 & 1633 & 2285 & 1720 & 835 & 4107 & 1593 & 1521 & 992
& 14531 \\
01.07.2006
& 10411 & 8965 & 1788 & 2427 & 1845 & 871 & 4419 & 1745 & 1587 & 1087
& 9866 & 8965 & 1381 & 2380 & 1821 & 851 & 4369 & 1698 & 1587 & 1083
& 14995 \\
\bottomrule
\end{tblr}
\end{table}
\begin{table}[!ht]
\ContinuedFloat
\caption{Excerpt of the Quarterly TouristsIndia dataset (second part)}
\begin{tblr}{colsep=3pt,
colspec = {@{} r Q[c,si={table-format=5.0}]
*{8}{Q[c,si={table-format=4.0}]}
*{2}{Q[c,si={table-format=5.0}]}
*{8}{Q[c,si={table-format=4.0}]}
Q[c,m,si={table-format=5.0}]
Q[c,m,si={table-format=7.0}] @{}},
rows = {font=\footnotesize},
row{2-Z} = {rowsep=-3pt},
row{eachtwo} = {abovesep=1ex},
row{2} = {abovesep=0pt},
row{Z} = {belowsep=0pt},
measure = vbox
}
\toprule
\SetCell{c} index
& {{{f21}}} & {{{f22}}} & {{{f23}}} & {{{f24}}} & {{{f25}}} & {{{f26}}} & {{{f27}}} & {{{f28}}} & {{{f29}}} & {{{f30}}}
& {{{f31}}} & {{{f32}}} & {{{f33}}} & {{{f34}}} & {{{f35}}} & {{{f36}}} & {{{f37}}} & {{{f38}}} & {{{f39}}} & {{{f40}}}
& {{{Tourists\\India}}} \\
\midrule
01.01.2005
& 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824
& 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393
& 1108967 \\
01.04.2005
& 11852 & 2901 & 2861 & 2073 & 1139 & 5588 & 2048 & 1900 & 1639 & 12816
& 11852 & 2778 & 2797 & 2017 & 1126 & 5375 & 1971 & 1900 & 1503 & 6257
& 721024 \\
01.07.2005
& 11730 & 2943 & 2891 & 2110 & 1166 & 5699 & 2091 & 1934 & 1673 & 12861
& 11730 & 2253 & 2827 & 2077 & 1130 & 5608 & 2023 & 1934 & 1650 & 6964
& 838583 \\
01.10.2005
& 13350 & 2997 & 2970 & 2177 & 1232 & 5843 & 2152 & 1990 & 1701 & 14497
& 13350 & 3702 & 2969 & 2172 & 1238 & 5809 & 2170 & 1990 & 1649 & 10509
& 1250037 \\
01.01.2006
& 13793 & 3007 & 3042 & 2230 & 1254 & 6062 & 2222 & 2123 & 1717 & 15256
& 13793 & 3115 & 3170 & 2324 & 1297 & 6399 & 2349 & 2123 & 1927 & 11910
& 1267443 \\
01.04.2006
& 12956 & 3034 & 3169 & 2326 & 1267 & 6126 & 2252 & 2155 & 1719 & 13765
& 12956 & 2886 & 3106 & 2272 & 1253 & 5928 & 2174 & 2155 & 1599 & 7566
& 853856 \\
01.07.2006
& 12877 & 3067 & 3267 & 2411 & 1286 & 6262 & 2343 & 2201 & 1718 & 14178
& 12877 & 2331 & 3185 & 2369 & 1247 & 6173 & 2268 & 2201 & 1704 & 8970
& 929458 \\
\bottomrule
\end{tblr}
\end{table}
\begin{multicols}{2}
\begin{itemize}[parsep=0pt]
\item gross domestic product at market prices - output approach
\item gross value added at basic prices
\item total activity
\item agriculture
\item forestry and fishing
\item industry
\item including energy
\item manufacturing
\item construction
\item services
\item distribution trade, repairs, transport, accommodation, food service
\item real estate activities
\item public administration, education, human health
\end{itemize}
The second to last or 41st feature is the total Foreign Exchange Earnings (in Indian Rupee Crores). The 42nd feature are the foreign tourist arrivals in India.
The dataset therefore contains 42 columns and 48 rows.
An explanation to each column is shown in table \ref{tab:india}.
\end{multicols}
\end{landscape}
\end{document}
更好的办法是，表格位于自己的横向页面上，并且文本正常设置：
\documentclass[]{scrbook}
\usepackage{lscape, afterpage}
\usepackage{multicol}
\usepackage{enumitem}
\usepackage{caption}
\usepackage{tabularray}
\UseTblrLibrary{booktabs, siunitx, varwidth}
\ExplSyntaxOn
\NewChildSelector{eachtwo}
{
\int_step_inline:nnnn {2}{2}{\l_tblr_childs_total_tl}
{ \clist_put_right:Nn \l_tblr_childs_clist {##1} }
}
\ExplSyntaxOff
\begin{document}
\subsubsection{Quarterly Tourists India}
This is a multivariate dataset consisting of different configurations of Gross Domestic Product across multiple sectors and Foreign Exchange Earnings as determinants of Foreign Tourism Demand and the number of Foreign Tourist Arrivals in India.
The Foreign Tourist Arrivals are acquired from Indian Tourism Statistics for the duration of 2015-2016.
The Foreign Exchange Earnings are collected from Various Issues of Indian Tourism Statistics, M/o Tourism, Market Research Division in Indian Rupee Crores. One Crore is equal to the number 10,000,000.
The different GDP values are extracted from the Organisation for Economic Co-Operation and Development in Indian Rupee Billions.
The data contains 41 features which are determinants of Foreign Tourist Arrivals and corresponding Foreign Tourist Arrivals for January-March from 2005 to 2016.
The first 40 features contain information regarding different GDP configurations (in India Rupee Billions), which are further classified in the following categories:
\begin{itemize}[parsep=0pt]
\item CQRSA: National currency, current prices, quarterly levels, seasonally adjusted.
\item CQR: National currency, current prices, quarterly levels.
\item VNBQRSA: National currency, constant prices, national base year, quarterly levels, seasonally adjusted.
\item VNBQR: National currency, constant prices, national base year, quarterly levels.
\end{itemize}
Each of the configurations or GDP categories have their share in multiple sectors and can therefore be divided in sub-categories:
\afterpage{\clearpage
\begin{landscape}
\begin{table}[!ht]
\caption{Excerpt of the Quarterly TouristsIndia dataset (first part)}
\label{tab:india}
\begin{tblr}{colsep=3pt,
colspec = {@{} r Q[c,si={table-format=5.0}]
*{8}{Q[c,si={table-format=4.0}]}
*{2}{Q[c,si={table-format=5.0}]}
*{8}{Q[c,si={table-format=4.0}]}
Q[c,m,si={table-format=5.0}]
Q[c,m,si={table-format=7.0}] @{}},
rows = {font=\footnotesize},
row{2-Z} = {rowsep=-3pt},
row{eachtwo} = {abovesep=1ex},
row{2} = {abovesep=0pt},
row{Z} = {belowsep=0pt},
measure = vbox
}
\toprule
\SetCell{c} index
& {{{f1}}} & {{{f2}}} & {{{f3}}} & {{{f4}}} & {{{f5}}} & {{{f6}}} & {{{f7}}} & {{{f8}}} & {{{f9}}} & {{{f10}}}
& {{{f11}}} & {{{f12}}} & {{{f13}}} & {{{f14}}} & {{{f15}}} & {{{f16}}} & {{{f17}}} & {{{f18}}} & {{{f19}}} & {{{f20}}}
& {{{Tourists\\India}}} \\
\midrule
01.01.2005
& 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824
& 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393
& 1108967 \\
01.04.2005
& 8641 & 7608 & 1517 & 1994 & 1480 & 699 & 3669 & 1424 & 1289 & 957
& 8224 & 7608 & 1450 & 1960 & 1460 & 694 & 3537 & 1372 & 1289 & 876
& 13455 \\\
01.07.2005
& 8861 & 7670 & 1582 & 2030 & 1516 & 725 & 3787 & 1469 & 1331 & 987
& 8404 & 7670 & 1232 & 1997 & 1498 & 707 & 3739 & 1429 & 1331 & 979
& 13644 \\
01.10.2005
& 9206 & 8840 & 1654 & 2116 & 1589 & 776 & 3930 & 1533 & 1379 & 1019
& 9592 & 8840 & 2060 & 2104 & 1568 & 782 & 3916 & 1546 & 1379 & 991
& 13990 \\
01.01.2006
& 9582 & 9107 & 1699 & 2182 & 1634 & 804 & 4106 & 1594 & 1468 & 1044
& 10069 & 9107 & 1710 & 2262 & 1693 & 821 & 4301 & 1672 & 1468 & 1161
& 14341 \\
01.04.2006
& 9877 & 8812 & 1721 & 2320 & 1740 & 837 & 4235 & 1645 & 1521 & 1069
& 9356 & 8812 & 1633 & 2285 & 1720 & 835 & 4107 & 1593 & 1521 & 992
& 14531 \\
01.07.2006
& 10411 & 8965 & 1788 & 2427 & 1845 & 871 & 4419 & 1745 & 1587 & 1087
& 9866 & 8965 & 1381 & 2380 & 1821 & 851 & 4369 & 1698 & 1587 & 1083
& 14995 \\
\bottomrule
\end{tblr}
\end{table}
\begin{table}[!hb]
\ContinuedFloat
\caption{Excerpt of the Quarterly TouristsIndia dataset (second part)}
\begin{tblr}{colsep=3pt,
colspec = {@{} r Q[c,si={table-format=5.0}]
*{8}{Q[c,si={table-format=4.0}]}
*{2}{Q[c,si={table-format=5.0}]}
*{8}{Q[c,si={table-format=4.0}]}
Q[c,m,si={table-format=5.0}]
Q[c,m,si={table-format=7.0}] @{}},
rows = {font=\footnotesize},
row{2-Z} = {rowsep=-3pt},
row{eachtwo} = {abovesep=1ex},
row{2} = {abovesep=0pt},
row{Z} = {belowsep=0pt},
measure = vbox
}
\toprule
\SetCell{c} index
& {{{f21}}} & {{{f22}}} & {{{f23}}} & {{{f24}}} & {{{f25}}} & {{{f26}}} & {{{f27}}} & {{{f28}}} & {{{f29}}} & {{{f30}}}
& {{{f31}}} & {{{f32}}} & {{{f33}}} & {{{f34}}} & {{{f35}}} & {{{f36}}} & {{{f37}}} & {{{f38}}} & {{{f39}}} & {{{f40}}}
& {{{Tourists\\India}}} \\
\midrule
01.01.2005
& 12547 & 2861 & 2800 & 2030 & 1095 & 5449 & 1984 & 1854 & 1610 & 13824
& 12547 & 2958 & 2913 & 2112 & 1132 & 5754 & 2099 & 1854 & 1801 & 9393
& 1108967 \\
01.04.2005
& 11852 & 2901 & 2861 & 2073 & 1139 & 5588 & 2048 & 1900 & 1639 & 12816
& 11852 & 2778 & 2797 & 2017 & 1126 & 5375 & 1971 & 1900 & 1503 & 6257
& 721024 \\
01.07.2005
& 11730 & 2943 & 2891 & 2110 & 1166 & 5699 & 2091 & 1934 & 1673 & 12861
& 11730 & 2253 & 2827 & 2077 & 1130 & 5608 & 2023 & 1934 & 1650 & 6964
& 838583 \\
01.10.2005
& 13350 & 2997 & 2970 & 2177 & 1232 & 5843 & 2152 & 1990 & 1701 & 14497
& 13350 & 3702 & 2969 & 2172 & 1238 & 5809 & 2170 & 1990 & 1649 & 10509
& 1250037 \\
01.01.2006
& 13793 & 3007 & 3042 & 2230 & 1254 & 6062 & 2222 & 2123 & 1717 & 15256
& 13793 & 3115 & 3170 & 2324 & 1297 & 6399 & 2349 & 2123 & 1927 & 11910
& 1267443 \\
01.04.2006
& 12956 & 3034 & 3169 & 2326 & 1267 & 6126 & 2252 & 2155 & 1719 & 13765
& 12956 & 2886 & 3106 & 2272 & 1253 & 5928 & 2174 & 2155 & 1599 & 7566
& 853856 \\
01.07.2006
& 12877 & 3067 & 3267 & 2411 & 1286 & 6262 & 2343 & 2201 & 1718 & 14178
& 12877 & 2331 & 3185 & 2369 & 1247 & 6173 & 2268 & 2201 & 1704 & 8970
& 929458 \\
\bottomrule
\end{tblr}
\end{table}
\end{landscape}
}
\begin{itemize}[parsep=0pt]
\item gross domestic product at market prices - output approach
\item gross value added at basic prices
\item total activity
\item agriculture
\item forestry and fishing
\item industry
\item including energy
\item manufacturing
\item construction
\item services
\item distribution trade, repairs, transport, accommodation, food service
\item real estate activities
\item public administration, education, human health
\end{itemize}
The second to last or 41st feature is the total Foreign Exchange Earnings (in Indian Rupee Crores). The 42nd feature are the foreign tourist arrivals in India.
The dataset therefore contains 42 columns and 48 rows.
An explanation to each column is shown in table \ref{tab:india}.
\end{document}
