4

I try to rotate a large table and also the corresponding caption. Around this rotated figure I want to wrap text. I have this MWE, but in this MWE the caption is not rotated and therefore needs a lot of space, so the table isn't readable anymore. I want to give the table as much space as possible.

\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}
3
  • 1
    What makes your table's contents illegibly small is not the caption but the fact that you used \resizebox. You're probably better off transposing or splitting the table in order to increase its readability.
    – leandriis
    Dec 19, 2021 at 14:17
  • Hi @leandriis, thanks for the answer. But I want the table to fit on one page. Maybe I have to make the table incomplete with some "..." instead of columns...
    – Zepp
    Dec 19, 2021 at 14:24
  • You can definitely make the table fit onto a single page, for example if you transpose it (switching columns annd rows). A transposed table would not need to be rotated. As an alternative, you could split your extremely wide table into parts. The first part could for example show the first 11 columns, the second part column 12 to 22 and so on. Since the table only contains 7 rows, you should be able to fit all four parts on a single page.
    – leandriis
    Dec 19, 2021 at 14:31

3 Answers 3

4

Try this solution:

a

\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}

From rotate floats with captions

UPDATE

To have the caption above the table use

{\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}{!}{%

b

2
  • Thanks! That's how I imagined it to look like! Right now I'm just about figuring out how to place the caption above the table...
    – Zepp
    Dec 19, 2021 at 15:10
  • 1
    @Zepp I updated the answer. Dec 19, 2021 at 17:56
3

This shows how to do it using paracol. The downside is that you have to manually break the itemize. The upside is that you can overlap the \subsection.

There may be a way to get rid of the hanging indentation. Alas, KOMA is incompatible with the caption package. See Can the package "caption" be used with KOMAScript classes?

It is extremely unlikely that you will ever make this tabular readable without splitting it into pieces.

\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}
0
0

Well, for reading table in your MWE as well in other answers, I need magnifying glass ... so I thought about the possibility of splitting the table into two parts and expanding the document to two pages. By this in table can be used \footnotesize font size and become more readable.

Since you rotate table I wondered what it would look like if I also rotated the table description. Hm, it may seems a bit unusual but anyway let's examine this possibility:

\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}

enter image description here

A bit better would be, that tables are on own landscape oriented page and text is set normally:

\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}

enter image description here

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