From mboxrd@z Thu Jan 1 00:00:00 1970 From: Suvayu Ali Subject: Tables with multicolumn in LaTeX export Date: Tue, 25 Aug 2015 16:38:43 +0200 Message-ID: <20150825143843.GJ31789@chitra.no-ip.org> Mime-Version: 1.0 Content-Type: multipart/mixed; boundary="ADZbWkCsHQ7r3kzd" Content-Transfer-Encoding: 8bit Return-path: Received: from eggs.gnu.org ([2001:4830:134:3::10]:54344) by lists.gnu.org with esmtp (Exim 4.71) (envelope-from ) id 1ZUFND-0001TD-Nb for emacs-orgmode@gnu.org; Tue, 25 Aug 2015 10:38:52 -0400 Received: from Debian-exim by eggs.gnu.org with spam-scanned (Exim 4.71) (envelope-from ) id 1ZUFN9-0003I7-M3 for emacs-orgmode@gnu.org; Tue, 25 Aug 2015 10:38:51 -0400 Received: from mail-wi0-x22a.google.com ([2a00:1450:400c:c05::22a]:37344) by eggs.gnu.org with esmtp (Exim 4.71) (envelope-from ) id 1ZUFN9-0003I2-Av for emacs-orgmode@gnu.org; Tue, 25 Aug 2015 10:38:47 -0400 Received: by widdq5 with SMTP id dq5so17125721wid.0 for ; Tue, 25 Aug 2015 07:38:46 -0700 (PDT) Received: from chitra.no-ip.org ([2001:610:120:3001:2ad2:44ff:fe4a:b029]) by smtp.gmail.com with ESMTPSA id op6sm2954780wic.12.2015.08.25.07.38.45 for (version=TLSv1.2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Tue, 25 Aug 2015 07:38:45 -0700 (PDT) Content-Disposition: inline List-Id: "General discussions about Org-mode." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Errors-To: emacs-orgmode-bounces+geo-emacs-orgmode=m.gmane.org@gnu.org Sender: emacs-orgmode-bounces+geo-emacs-orgmode=m.gmane.org@gnu.org To: Emacs Org mode --ADZbWkCsHQ7r3kzd Content-Type: text/plain; charset=utf-8 Content-Disposition: inline Content-Transfer-Encoding: 8bit Hi, I was wondering if it is possible to have multicolumn when exporting tables to LaTeX. Something like the following: | | | ∈ (5300,5800) | | ∈ (5320,5420) | <- row with multicolumn | classifier | signal | combi. | signal | combi. | |----------------+--------+---------------+--------+---------------| | old BDT > 0.3 | 70347 | 10885 | 68502 | 4021 | | BDT v1 > -0.08 | 68458 | 20310 | 66683 | 5853 | | BDT v1 > -0.09 | 69418 | 22329 | 67617 | 6431 | | BDT v1 > -0.12 | 71336 | 28674 | 69479 | 8160 | to \begin{tabular}{lrrrr} & \multicolumn{2}{c}{∈ (5300,5800)} & \multicolumn{2}{c}{∈ (5320,5420)}\\ classifier & signal & combi. & signal & combi.\\ \hline old BDT > 0.3 & 70347 & 10885 & 68502 & 4021\\ BDT v1 > -0.08 & 68458 & 20310 & 66683 & 5853\\ BDT v1 > -0.09 & 69418 & 22329 & 67617 & 6431\\ BDT v1 > -0.12 & 71336 & 28674 & 69479 & 8160\\ \end{tabular} I am not too keen on using table.el as it uses too many lines, I would like it to be minimal (tiny screenshot attached). Maybe there is a hack? I'm not familiar with all the possibilities available via #+attr_latex properties. Thanks for any ideas. Cheers, -- Suvayu Open source is the future. It sets us free. --ADZbWkCsHQ7r3kzd Content-Type: image/png Content-Disposition: attachment; filename="table.png" Content-Transfer-Encoding: base64 iVBORw0KGgoAAAANSUhEUgAAAbQAAACHCAAAAABbxvMtAAAABGdBTUEAALGPC/xhBQAAACBj SFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAAAmJLR0QA/4ePzL8A AAAJb0ZGcwAAASwAAAFwACLOa/YAAAAJdnBBZwAADwAAAAQ4APMM2ccAABWMSURBVHja7Z15 nFXFlceLbrRZREOzL9LQ0DKAQtQJYBIVEAZZFARlkUlYRISJS2IUlEzoKMQ4okSUsDnCfESB uIDgqKiggHzYFSJLGEGaQADZpaFput9y5t6qOlV173vv3lu3F7q1zh+33n331Klf1el33+t+ 3z5FwFilM2KWwCTNmEmaMZM0kzRjJmnGvr9JWzOnxCGe/ltFk6SpqLIlbXvzY3Bq577tq/dZ JwWbdsWtJr7jKL2GLUiPws3bowkee5oeKitJXBEUf/lF1KFISoKL6xQP5qKpqDIkLf7BxMGD n6EPozfMAJhBLJtvtR1+Wb97BM53vaPFk9Y1bEF6bGjZv9uPTyZ4PN699BQ5JHFFsPnGwe3a HVIVCUkA97cC4YEueooqQdKO964/5NHfzqWP59Y4DzB+9JdrvyiAzeRrmE3Wwv3d45vJehAt CA+4dixEak1O8NjP3UpDkSoJFUUaPwv5lw9VFQlJsIy0BeGBLnqKKn7S4r26nBYnHQdZh8HT 6eMDf4jD1LRjxzJeAmg2ALAF6QFZfWMH0+YlevzkrlJTpEriiuD8tUsAGnRQFQlJ317bqR2g h5SkpajiJ+1/qxwUjw+Q56xj5z73PpFnnxbOq70QlpPlADdliRYUjxfI4J+NjSV6jK0RKSVF LklUEbWjZKyqCD3ifZb0aSc8pCQtRRU/aRPq/dm21fbjj8gb1nHYU1Ovu2qv9WBAFul+cjqx LvVPK8IWVI/R5KplkOgxhWwvJUUuSVQRfTUOaX1KVYQes4YCT5rtIaTpKar4Sbu/xs9se9F+ /Ar5lD35DRlO28/JyOnE+jR22+VRbEHxeDFn9S1VFiZ6zCMrSklRgiRLkd1MabYfXIpsjz0t TmLSbA/poqWo4idtTo0L4vF8+25CrVYn1mblfGQ/d10bwBakx9fpq6CwQ7tEj+lkaykpSpSU lWMdnm/1D0hQZHk8VjMrq1rVrNXcQ7poKar4STvdeIJ4vJnMYg+K03/J7jGZvY+kvwLQcCRg C9JjMbE+ro3PTPR4nJwoJUUJkixFAKsaHYKiwS5Ftkdkx44dN7e0fpdjHlKSlqJK8JF/Va1B S9Zv2G0/LKphLdc/2y6HBelfwO5h/4D3q3wMD/aKf1XVej/h7ane76PHnrQVEO/+kNsD4O52 8VJS5JCEiorr91+06MHeiiIh2rIe2SA8hCQtRZXhl+u8Yc0J6UkfPmj9jlM4rPatzZdZT9/U qGuO9cn5VKe2raxTbPPq34ge8Gpm55zRBW4PKLzyuVJTpEpCRV/av0iTRxRFQrT1WbEK+Tfh gS56iirZn7H2p22zF/0A+7E8e4S28YPFoLR7O0uP4v2FSTzern+6jCRxRWiKIiGpIBK5kOCi p6iy/e1xYm8/j409t/l4FLddWK6SSl1RZUtapP8CH4+CqF+MSb8rX0mlrqjSfTVTdKDEIfLi FU2SpiLzJWglNJM0kzRjJmnGTNJ+EElbl3tvzONydMaAUZ9U6tm/8ZsplVGTZ9Leupqk+Cy6 7LbzEO91186JZEbpyR3aPDvrX7pMOhfIs3lOh9HLSjriM/i3KHs+FU1TalHet8cRaSkuzGl+ HD4iG6Go/aOll7TYOPJX2N2wazyI5yvx/IVXDz5TwiHr95bzqWiaUovyTtoD6amuWJPIJedo W3r2F2LdbX9Njgf0hEN1B5Zw/Kw+cj4VTlNKUamS9u38mV+zpMU/n7bUfmeLLZ/27kF+PPfZ 8/k7bq+6dOnS+TOtSydff9Oa1NkP50aWbC6J3Fn2tB9qkep9dOYKp6f9c/Mmf+L8yqW2fRBP ORc4tnj2Tkvr8tfjW2YfhAPzF0TtBdoyfTXQ+VxCTU5RXJOHqBRJW5k1dXja+3bSYvfcNTPb /npv4M9ntPgVP87/ETnw59ZpDzww+opsgLWtJw+vtwtmXZVxd/VmJUvaM8ufrbcm1eWttda5 FmgvGcbXoDn9rqPqQ/GUc/m4+eQnMn4PU2o0HtW5SZ0pbbpWecZKWo3bR1dl87mEmpyiuCYP UcmTdrLeNPiu9gw7aXvICphGzsBJ8t/w9svsCPCf5DDcl2F53noNnGk8A2I1RwI8RsYf2lay pN09rgvprXyHGz2n2qNVX444Fqi4Sg47/8Nzvx56Yugd51PPJb+B9aHsRbIGhpC58AEZchHa /txKWkeAZ61Y9nwuoSaHKNSUWlTypC2wPmNAhN4e44cjy+4kWyDWKjM3nx8B/kSOsqTd1hoW k8ZNG1QfbN8Y8kp2N6fTfpcoX3XsIC4b7ligaMY17HxT7PFH4BeDPObyLllqveGQMXDfZXH4 ymYEbm3H3j92kyfofC6hJoco1JRaVPKkTbKyZJv9nvZa24d/SzZYr/YhpMkGfnQkbRLZwXrl Wi/IkicNOlQ5B5smzaI/oZETqv2OPJHvWKB9ZCC6jsuFoUM85jLdpqYiVfpR2TvUpB0kT/sl TVcT9w2sySEKNekmbZ51F7RtTBq8R96HRVbSdq+DdZk/ZUf7l4kjMOpyy6PbNTCTvIRSSviF 8EzysXXsklG8JntL4yMJl/9efbH0pAv0LFmJrl2XwqB7PebyIbHu6vlkIpX9FbE+P93SliVt NVlJ51N6moD7BtbkEIWaUotKnrTTdVrsLZw6AwaQ07lka3QM+aTgnZvjcFtPdgT4Dfkb9CNn Adpnwrc1rlofWzvNel2SXSVL2gTyPwAbM56EzRlz9id+czj7PcXzHYDCOZflctfil6ofgxF9 9r2Qci7RDq3PwptXHIQ7yHlYS/4EcF0jgGY3x6P9+8bpfIr6vVpKmpivhiaHKNRERWkkDTbm kBr3Fo5LI422XF2t9fjql7+5Ir3jze3/zo4w5TJSZ1AaaXxsGCHtYWVzckWvEzC+Kqm9siQ5 +0VVkn5t+47zYhB/vcH1Rd6e1a5pnXPPVuCui9KsCS8kV69JORc43L1utzYfw2Np5MdH65Dq n48hpC80adupzYh8Op/dx2uNKCVNzDe4JqcoromJ0kkaxI9Y9+SLxdEL8eJ9BXD2LMTjRw/E +REuFkULC4qiF2KFloflfdS+2dtPlgSRh8KiWOQi/Xw8Zf35Kz718SxirA5zjVEW+1A09Vws y7epG3tOsQvRi5GLxZFC+C6Wh9Kj1kkpaWK+wTU5RXFNXJRO0i6t/b7l0D7nS9213DSVtaiK mbR44Xdl4FpumspalPk+rRKaSZpJmrHyTlouMVZRLde80szt0VjFSpoge76cMvj0D2E5vg9J E2TPqnaE1pSRnIvCsfSsltkkO7tpZvUkfwZSi9ZgOZtwFv9sf17e/30eExFluIvr5FUPO6wK 4rV8sJUFdbQtT4YRUVAj1uXxNFbCJ6HL4ZBJk2TPRPYXZ8m5KBxL/af3flsv4+Cmwd0SA6hl dHg5m5B2ir4hN4pgRCXc/a3E1dT9d93TVBHEa/mIVhbU0bTNvfoWiDAYBTViXR5voyV83F24 3DBJE2TPZP7djuRcBMdy3v56vUMTgONJyCxZtAbL2YS1L2ou27Chx5MYUQln18DBqynt5WaZ zRVBvJaPaEVBHU17O5MyczwMRuGDiLo8nkZL+Li7oFytpHHihCXt+OK/jOBJk5yLk2O5MSt5 GFm0BsvZhLUdcwHO1NyLEWU4WgOHX03dvTDer6UiiNXyAdFiQR1dUemLaMvD8Cg4CNbl8TRW wsfdhcvVShoSJzRpn9R/ckpNkTTkXJwci5K0P07YKR47itbIcjZhbfqtSkQeTtbAsa56GV0F 7M5q+YBoRRUgLYt3/dedu+y/7PMwPIo6a7suj2cIJj+xi3bSBHFiJ+27hk8BPCyShpyLk2NR krbrwbrXT+OfPhxFa0Q5m7AWb/2aEpGHEzVw7Ku+SRPdaS0fAGxFjR8t20+yRrbK2irC8CjK rGldHi/j8hO7aCdNECd20pbaJMNk9fZIORcnx+K4PRYvvzvt9ossaY6iNbycTVhbVavAEdEO J2vg2FcDJI11Z7V8sKYPvY5VgDRsCVkB+fVvUMPYURSNtC6Ph6H8xC7aSRPEiZ20/7KxHkfS KOeiciyupF34a9/L+tNXl7toTVZOSZI2cLgrohVO1sAZ6LPmdBV4d17LB2v6MAesAhTc3rDX 6c70mBrGiiI1sro8HobyE7toJ00QJ2Osj/yvEevN9inO4AnOReVYLLtBUqrbRl3501n8nuAq WkPL2YS2f6avcEa0w4kaOPSql92ZLQXxWj5Y04fdH3gVIA3bRhYDdGuphrGjCI28Lo+HofzE LlSuTtIEcTKAnIaTtW4q2N+GPE3/c0RwLirHYi1f7aqF2HnqU9/ISLwiTVG/V7GcTXjLrVss I6rh7Bo4/KqHda4WEd2xlg+2SkEdHSvuMCheVPt5DCOicI2iLo+3UfkJXZhcjaQhcWKTPWfg vR9Va//ClUPtXxIl56JyLPBpQ0LqLUkWiFekOV5rBJazCW3FjcYqEZVwtAYOv5r6zaMpIQ13 ie68lg+2sqCOnu1u3/GGcVEMI6LwQURdHk+j8t1dUK5O0hQKxmoih+Ix9v255FxUjgUiFyLR wuQ/6LxojQ3NuMrZ6Fp00yk1ogxHa+Dg1ZS9bYlR2Z3X8hEtFtTRtFjeOTUMRkGNQYyX8HF2 EXK1kmas4ppJmkmaMZM0YyZpJmnGTNKMmaT9AJOmiYIc9hhAYUTceEYIy3N0p3AFchl+UR3b KKmEyeEEnfqalDZPnWIALMal370/VPCkaaEgXjSDY2MjF56hb5THULpTuIJzGX5RXdsoCcLE iY6E1CRbBzISCItx6XftD6Vze9RAQTxpBsfGRi48Q9sYjyG7M7iCcxk+UV3bKAnCxIWOhNQk WicyEgiLcel37g+llTR/FGT5O2/thc/eeavYk2ZQNzZy4xm6xnkM0Z3BFchl+ER1baMkCBMX OhJSE7YuZCQQFuPS79wfSjNpfijIYyRzvfUyvKdI/bpOxUNYahX0wY1naBryGNgd2RDOZQSI 6thGSQArDnQkpCbeupGRQFiMS3/i/lAaSfNFQfpXz4eNXcW02dubgodQUxmRBDxDzwSPwbsj G4J0h29U5zZKAlhxoiPhNPHWjYwEwmJc+hP2h9K8PXqjIJ+QeTDqPWfSVDxkfZ06dTq9qBAd bjxD05DH4N2V/ZEol+Ef1bmNkgBWHOhISE28TYKMBMJiXPqd+0NpJs0bBYm1uuV0u6g7aRIP ObZo0aKtKtHhwjN0jfMYe3h3yYaAzWX4R3VtowQIrKjoSEhNMd4uSIKMBMJiXPrV/aE0khYA BYGp5JGp9IGkGVQ8hJpKdLjwDF3jPAZ2F2wIUC7DN6p7GyUBrKjoSEhN2CZBRgJhMS796v5Q OkkLgILAiYwaLD+SZnDgIdQkI+LGM3SN8xhqdxuu4FyGX1TXNkoKYaKiIyE1YetCRiAIFuPS 79ofSidpwVCQ+/7DPnrSDAojkoBn6BrnMWR3Clcgl+ET1bWNkiBMXOhISE3YOpERCILFuPS7 9ofSSVowFKSIvnd50gwORsSNZ+ga5zFEdw5XcC4jaFQughMmbnQkpCZsXchIICzGpT/5/lBB bo/GKrKZpJmkGTNJM2aSZpJmzCTNmEmaSZqxypC0sgV7Ytt3hv33mTxH94vrlPGDgj28RXAG nw4vKk8pTAOC77E1BalIA7IPm44genSLv5Qp2PNNm3+/sUuoyqOUmlG6U7CHjx8U7OEtgjP4 dGhRVJMsPcP5HqbJvyKNDIHTQWEhir+UIdgT/8nDUNxsTIj1odSM0p2BPXz8gGAPbxGcwadD i2Ikjyg9w8Eersm3Io0Sgk8HhYUp/lKGYM92sgBgZF399WHUjOzOwR4+fkCwh7cIzuDTYUUh 0MNLzyDYwzX5VqRRQvDpoLAwxV/KEOz5wN7oYUKQDcmcxqkZ0V0WfaHjBwR7RCvBGfs0pChB 8gAtPaOcijXxqUgj2SCcDgoLk7QyA3sOVO8Zg1+la387w6mZI9hdFH3h4wcDe0QrwBl6eiSc KEny0NIzyimuiV9FGtFHTAeFhUla2YE9Sxq06nH5ddp3IgHRsO4K2EPHDwj2KC0HZ9hpOFGC 5GGlZ5RTXBO/ijTYR+WUmLCQSSsbsMf66Tu8q8ps7aQhRMO7K2CPPX5QsEetx0LBGTwNJUpo YqVnlFNcE7+KNNjnUZVTosL0k1aGYI+9QP066P8HBlIzvLsC9tjjBwV7lHosFJxRTkOIkppo 6Rl5imviW5EG+6icEiN6tIu/lCXYY70aR1x/WDtnAqJRuvfIFuMHBXt4i+CMrLUSSpTQxErP yFNcE9+KNGofezqS6NEu/lKmYM/m63PPQQjj1Izszqqm8PEDgj28RXBG8D4hRSHJw0vP4Cmu iV9FGrUPmw4KC1H8pUzBnoJwWA9SM7I7A3twfE1cyAXOhBXFSR4sPYOnXJNfRRq1D3JKTJgp /vJ9M5M0kzRjJmnGTNJM0oyZpBkzSfsBJq2MGBHuGWjXnMRAErhg4yFMIcuk5Hn1x1ElS5Ln pDiQONE1OqpATOwoMmoQ8kQIOqxG9CpGU56MCPcMtmtOggnggo+HMIUok4KoRXLDUQVL4oI7 kDjRNTaqREzsKCJqEPIEBYllpBE9i9GUJyPCPIPtmpNoCFzw8RCmEGVSELVIbmJUZElccAcS J7rGwkjEhEbBqIHIEy5ILCOL6FmMphwZEc49BNo1J4khcMHHQ5gCW0QtUr3icVTOkrjgDkGc 6IpiYQRiwqJg1EDkCReEy8giehejKUdGBKSn3645qYwBFzwKwhS0VWmNVEZHZSyJC+5QtxnS MQyDiIkSxY4aiDwRcAudFo/oXYymHBkR6em7a06qNWLABY+CMAVtFTwjZW82KmVJXHCHss2Q lmEYRExkFBo1GHmCcAudFo/oXYymHBkR6em3a04q48CFGA/Lo1itgmekMjYqY0lccIejlIyG iTAMMVGiMKlByBMBt9Bp8YjexWjKkRERnr675qQyDlzI8bA8SlaOgmekMDYqZ0lccIezlExw k2EoYqJE4VL9yRMJt9Bp8YgfehajKUdGBD39d81JYQhciPGwPIrVKnhGilcpG5WzJC64w1FK RsOUUW3EREYRbIgveSLhFjotHtG7GE15MiLMM+CuOUkMgQs6HsIUvFVQi6SGo3KWxAV3UOuR ra1IhhGICYuCUf3JEwm30GlhRM9iNOXJiDDPYLvmJFshBlzw8RCmwFagFslNjMpZEhfcAUic aBqGEYgJi4JRg5AnXBAuI4/oWYymPBkRH08/48CFiIKUB28RtfDNPWNJXHCHQDQ0jYcRiAnn VnjUQOQJEySmxSN6FaMxfzCuhGaSZpJmzCTNmEmaSZoxkzRjJmkmacZM0oyZpJmkGasE9v84 uJ3Da6mtiAAAAABJRU5ErkJggg== --ADZbWkCsHQ7r3kzd--