TeX - LaTeX Asked on February 4, 2021
I need to import a .csv
table into LaTeX
, which has 280 rows and will be spread out over multiple pages.
I tried pgfplotstable
and my code looks like this:
begin{table}[!h]
caption{RegressionResults for Apartment Rent}label{RegAR}small
pgfplotstabletypeset[
multicolumn names,
col sep=comma,
string replace*={"}{},
columns = {"term", "estimate", "std.error", "statistic", "p.value"},
columns/""/.style={
column name=Coefficient,
column type={S},string type},
columns/"term"/.style={
column name=Variables,
verb string type, column type=l},
columns/"estimate"/.style={
column name=Coefficient,
column type={S},string type},
columns/"std.error"/.style={
column name=Std. Error,
column type={S},string type},
columns/"statistic"/.style={
column name=t-value,
column type={S},string type},
columns/"p.value"/.style={
column name=p-value,
column type={S},string type},
every head row/.style={
before row={toprule}, % have a rule at top
after row={midrule} % rule under units
},
every last row/.style={after row=bottomrule}, % rule at bottom
]{04_Reg/reg_AR_coefs_copy3.csv} % filename/path to file
begin{tabularx}{linewidth}{X}
This table shows the regression results for the data subset apartment rent.
end{tabularx}
end{table}
Unfortunately, the table is just displayed on one page and cuts off most of the rows. (Note that I don’t want to display the first column.)
My csv is the following:
"","term","estimate","std.error","statistic","p.value"
"1","(Intercept)",3.7,0.005,685.68,0
"2","log_m2_living",0.779,0.001,1291.798,0
"3","b_0",-0.001,0.001,-1.204,0.229
"4","b_2",0.003,0.002,1.38,0.168
"5","b_3",0.012,0.001,15.478,0
"6","b_4",0.094,0.001,120.918,0
"7","b_5",0.105,0.002,63.347,0
"8","b_6",0.167,0.035,4.717,0
"9","y_unknown",0.039,0.001,45.106,0
"10","y_0",0.294,0.016,17.853,0
"11","y_1400",0.116,0.004,30.914,0
"12","y_1800",0.107,0.002,47.573,0
"13","y_1900",0.08,0.002,46.152,0
"14","y_1925",0.029,0.002,18.172,0
"15","y_1950",-0.002,0.001,-1.228,0.219
"16","y_1960",0,0.001,0.092,0.927
"17","y_1970",-0.023,0.001,-19.074,0
"18","y_1990",0.038,0.001,28.279,0
"19","y_1995",0.059,0.001,42.989,0
"20","y_2000",0.104,0.001,74.26,0
"21","y_2005",0.12,0.001,100.682,0
"22","y_2010",0.151,0.002,99.272,0
"23","y_2015",0.151,0.004,42.265,0
"24","f_basement",-0.032,0.004,-8.52,0
"25","f_sout",0.11,0.04,2.752,0.006
"26","f_0",-0.003,0.001,-3.719,0
"27","f_hochp",-0.022,0.002,-9.542,0
"28","f_2",-0.003,0.001,-5.3,0
"29","f_3",0,0.001,0.181,0.857
"30","f_4",0.008,0.001,8.64,0
"31","f_5",0.021,0.001,15.495,0
"32","f_6",0.02,0.002,9.808,0
"33","f_7",0.007,0.003,2.494,0.013
"34","f_8",-0.017,0.004,-4.718,0
"35","f_9",-0.019,0.005,-3.906,0
"36","f_10",-0.02,0.003,-6.263,0
"37","f_penthouse",0.114,0.022,5.209,0
"38","f_attic",0.035,0.012,2.988,0.003
"39","f_unknown_floor",0.013,0.001,17.996,0
"40","l_unknown",0.017,0.001,11.646,0
"41","l_1",0.061,0.001,41.826,0
"42","z_10",0.148,0.002,76.416,0
"43","z_11",0.194,0.003,71.668,0
"44","z_12",0.384,0.002,192.552,0
"45","z_13",-0.118,0.004,-30.395,0
"46","z_14",-0.134,0.003,-45.04,0
"47","z_15",-0.187,0.004,-49.776,0
"48","z_16",-0.204,0.003,-73.056,0
"49","z_17",-0.146,0.002,-65.825,0
"50","z_19",-0.222,0.003,-70.33,0
"51","z_20",-0.175,0.002,-71.575,0
"52","z_21",-0.587,0.009,-66.336,0
"53","z_22",-0.337,0.015,-22.905,0
"54","z_23",-0.506,0.003,-163.399,0
"55","z_24",-0.557,0.005,-102.375,0
"56","z_25",-0.257,0.002,-117.594,0
"57","z_26",-0.516,0.008,-66.31,0
"58","z_27",-0.542,0.006,-84.737,0
"59","z_28",-0.33,0.005,-69.316,0
"60","z_29",-0.321,0.006,-55.903,0
"61","z_30",-0.016,0.002,-8.765,0
"62","z_31",-0.15,0.003,-57.184,0
"63","z_32",-0.182,0.003,-60.981,0
"64","z_33",-0.179,0.003,-56.292,0
"65","z_34",-0.22,0.003,-67.883,0
"66","z_35",-0.204,0.005,-38.11,0
"67","z_36",-0.102,0.003,-37.629,0
"68","z_37",-0.152,0.006,-25.534,0
"69","z_38",-0.124,0.006,-21.154,0
"70","z_39",-0.288,0.005,-56.695,0
"71","z_40",-0.033,0.002,-18.109,0
"72","z_41",0.027,0.002,14.341,0
"73","z_42",-0.164,0.004,-43.705,0
"74","z_43",-0.093,0.003,-32.526,0
"75","z_44",-0.093,0.002,-37.804,0
"76","z_45",-0.23,0.003,-91.765,0
"77","z_46",-0.249,0.002,-105.381,0
"78","z_47",-0.257,0.005,-52.366,0
"79","z_48",-0.202,0.003,-61.229,0
"80","z_49",-0.308,0.004,-84.396,0
"81","z_50",-0.154,0.002,-67.096,0
"82","z_51",-0.188,0.006,-33.883,0
"83","z_52",-0.139,0.003,-42.178,0
"84","z_53",-0.206,0.004,-54.567,0
"85","z_54",-0.053,0.002,-24.002,0
"86","z_55",-0.156,0.004,-39.078,0
"87","z_56",-0.153,0.002,-63.455,0
"88","z_57",-0.251,0.003,-80.702,0
"89","z_60",-0.034,0.002,-17.143,0
"90","z_61",-0.276,0.005,-60.971,0
"91","z_62",-0.191,0.003,-70.437,0
"92","z_63",0.185,0.002,84.482,0
"93","z_64",-0.071,0.003,-23.651,0
"94","z_65",-0.254,0.004,-59.618,0
"95","z_66",-0.096,0.004,-22.487,0
"96","z_67",-0.457,0.016,-27.75,0
"97","z_68",-0.271,0.004,-62.117,0
"98","z_69",0.004,0.003,1.343,0.179
"99","z_70",-0.075,0.003,-25.503,0
"100","z_71",-0.286,0.009,-32.463,0
"101","z_72",-0.099,0.004,-22.218,0
"102","z_73",-0.166,0.005,-33.346,0
"103","z_74",-0.242,0.006,-37.342,0
"104","z_75",0.186,0.006,29.359,0
"105","z_76",-0.402,0.083,-4.856,0
"106","z_77",-0.714,0.061,-11.659,0
"107","z_80",0.313,0.002,175.956,0
"108","z_81",0.045,0.002,23.819,0
"109","z_82",-0.24,0.002,-107.356,0
"110","z_83",-0.008,0.002,-3.769,0
"111","z_84",-0.025,0.002,-12.312,0
"112","z_85",-0.24,0.002,-107.156,0
"113","z_86",0.018,0.002,9.098,0
"114","z_87",0.201,0.002,91.947,0
"115","z_88",0.133,0.002,66.825,0
"116","z_89",0.013,0.002,6.244,0
"117","z_90",-0.197,0.002,-97.511,0
"118","z_91",-0.282,0.004,-77.388,0
"119","z_92",-0.284,0.003,-101.655,0
"120","z_93",-0.279,0.003,-92.741,0
"121","z_94",-0.247,0.002,-110.189,0
"122","z_95",-0.223,0.003,-84.622,0
"123","z_96",-0.382,0.005,-83.947,0
"124","g_1",0.056,0.001,59.354,0
"125","g_2",-0.002,0.006,-0.273,0.784
"126","g_3",0.026,0.001,24.041,0
"127","c_0",0.045,0.006,7.425,0
"128","c_2",0.022,0.001,22.194,0
"129","c_3",0.126,0.001,105.119,0
"130","c_4",0.008,0.001,7.751,0
"131","c_5",0.094,0.003,29.038,0
"132","c_6",0.018,0.015,1.253,0.21
"133","c_7",0.232,0.002,142.634,0
"134","c_8",0.144,0.004,34.768,0
"135","c_9",0.047,0.008,6.262,0
"136","c_10",0.023,0.002,11.576,0
"137","p_2004_02",0.012,0.006,1.88,0.06
"138","p_2004_03",0.013,0.005,2.329,0.02
"139","p_2004_04",0.01,0.006,1.806,0.071
"140","p_2004_05",0.012,0.005,2.293,0.022
"141","p_2004_06",0.008,0.005,1.366,0.172
"142","p_2004_07",0.009,0.005,1.676,0.094
"143","p_2004_08",0.001,0.005,0.212,0.832
"144","p_2004_09",0.005,0.005,1.014,0.31
"145","p_2004_10",0.006,0.005,1.061,0.289
"146","p_2004_11",0.011,0.006,1.886,0.059
"147","p_2004_12",0.014,0.005,2.654,0.008
"148","p_2005_01",0.009,0.005,1.773,0.076
"149","p_2005_02",0.009,0.005,1.746,0.081
"150","p_2005_03",0.02,0.005,3.767,0
"151","p_2005_04",0.01,0.005,2.004,0.045
"152","p_2005_05",0.013,0.005,2.508,0.012
"153","p_2005_06",0.005,0.005,1.018,0.309
"154","p_2005_07",0.011,0.005,2.243,0.025
"155","p_2005_08",0.002,0.005,0.392,0.695
"156","p_2005_09",0.008,0.005,1.593,0.111
"157","p_2005_10",0.006,0.005,1.247,0.213
"158","p_2005_11",0.014,0.005,2.703,0.007
"159","p_2005_12",0.013,0.005,2.474,0.013
"160","p_2006_01",0.013,0.005,2.835,0.005
"161","p_2006_02",0.014,0.005,2.732,0.006
"162","p_2006_03",0.017,0.005,3.404,0.001
"163","p_2006_04",0.013,0.005,2.535,0.011
"164","p_2006_05",0.013,0.005,2.636,0.008
"165","p_2006_06",0.02,0.005,3.797,0
"166","p_2006_07",0.007,0.005,1.456,0.145
"167","p_2006_08",0.003,0.005,0.611,0.541
"168","p_2006_09",0.01,0.005,2.123,0.034
"169","p_2006_10",0.011,0.005,2.309,0.021
"170","p_2006_11",0.014,0.005,3.06,0.002
"171","p_2006_12",0.021,0.005,4.187,0
"172","p_2007_01",0.011,0.005,2.209,0.027
"173","p_2007_02",0.015,0.005,3.226,0.001
"174","p_2007_03",0.02,0.005,4.188,0
"175","p_2007_04",0.014,0.005,2.891,0.004
"176","p_2007_05",0.015,0.005,3.077,0.002
"177","p_2007_06",0.019,0.005,3.985,0
"178","p_2007_07",0.016,0.005,3.369,0.001
"179","p_2007_08",0.02,0.005,4.236,0
"180","p_2007_09",0.026,0.005,5.394,0
"181","p_2007_10",0.023,0.005,4.742,0
"182","p_2007_11",0.021,0.005,4.196,0
"183","p_2007_12",0.035,0.005,7.193,0
"184","p_2008_01",0.033,0.005,7.075,0
"185","p_2008_02",0.037,0.005,7.814,0
"186","p_2008_03",0.042,0.005,8.902,0
"187","p_2008_04",0.049,0.005,10.681,0
"188","p_2008_05",0.049,0.005,10.382,0
"189","p_2008_06",0.043,0.005,9.112,0
"190","p_2008_07",0.047,0.005,9.995,0
"191","p_2008_08",0.052,0.005,11.277,0
"192","p_2008_09",0.058,0.005,11.89,0
"193","p_2008_10",0.06,0.005,12.719,0
"194","p_2008_11",0.07,0.005,15.101,0
"195","p_2008_12",0.069,0.005,14.103,0
"196","p_2009_01",0.056,0.005,12.182,0
"197","p_2009_02",0.059,0.005,12.723,0
"198","p_2009_03",0.066,0.005,14.303,0
"199","p_2009_04",0.053,0.005,11.352,0
"200","p_2009_05",0.066,0.005,13.935,0
"201","p_2009_06",0.076,0.005,15.967,0
"202","p_2009_07",0.071,0.005,14.92,0
"203","p_2009_08",0.063,0.005,13.205,0
"204","p_2009_09",0.069,0.005,14.51,0
"205","p_2009_10",0.07,0.005,14.599,0
"206","p_2009_11",0.071,0.005,14.751,0
"207","p_2009_12",0.073,0.005,14.897,0
"208","p_2010_01",0.068,0.005,14.41,0
"209","p_2010_02",0.072,0.005,15.425,0
"210","p_2010_03",0.08,0.005,17.209,0
"211","p_2010_04",0.079,0.005,16.84,0
"212","p_2010_05",0.074,0.005,15.828,0
"213","p_2010_06",0.077,0.005,16.607,0
"214","p_2010_07",0.078,0.005,16.692,0
"215","p_2010_08",0.07,0.005,15.119,0
"216","p_2010_09",0.077,0.005,16.604,0
"217","p_2010_10",0.076,0.005,16.149,0
"218","p_2010_11",0.086,0.005,18.317,0
"219","p_2010_12",0.085,0.005,17.668,0
"220","p_2011_01",0.09,0.005,19.98,0
"221","p_2011_02",0.089,0.005,19.042,0
"222","p_2011_03",0.09,0.005,19.959,0
"223","p_2011_04",0.094,0.005,20.61,0
"224","p_2011_05",0.098,0.005,21.438,0
"225","p_2011_06",0.087,0.005,18.358,0
"226","p_2011_07",0.089,0.005,19.436,0
"227","p_2011_08",0.094,0.005,20.411,0
"228","p_2011_09",0.099,0.005,21.301,0
"229","p_2011_10",0.102,0.005,22.434,0
"230","p_2011_11",0.106,0.005,22.264,0
"231","p_2011_12",0.104,0.005,21.845,0
"232","p_2012_01",0.1,0.005,21.872,0
"233","p_2012_02",0.106,0.005,23.183,0
"234","p_2012_03",0.115,0.004,25.693,0
"235","p_2012_04",0.125,0.005,26.703,0
"236","p_2012_05",0.118,0.005,26.045,0
"237","p_2012_06",0.123,0.005,26.901,0
"238","p_2012_07",0.123,0.005,27.348,0
"239","p_2012_08",0.124,0.005,27.155,0
"240","p_2012_09",0.13,0.005,28.424,0
"241","p_2012_10",0.129,0.005,28.491,0
"242","p_2012_11",0.13,0.005,28.69,0
"243","p_2012_12",0.138,0.005,29.875,0
"244","p_2013_01",0.13,0.004,28.857,0
"245","p_2013_02",0.129,0.004,28.859,0
"246","p_2013_03",0.154,0.005,33.764,0
"247","p_2013_04",0.13,0.005,28.229,0
"248","p_2013_05",0.126,0.005,27.936,0
"249","p_2013_06",0.144,0.004,32.471,0
"250","p_2013_07",0.137,0.005,30.251,0
"251","p_2013_08",0.136,0.005,29.985,0
"252","p_2013_09",0.138,0.004,30.83,0
"253","p_2013_10",0.147,0.005,31.62,0
"254","p_2013_11",0.135,0.005,29.478,0
"255","p_2013_12",0.128,0.005,27.823,0
"256","p_2014_01",0.125,0.005,27.48,0
"257","p_2014_02",0.115,0.005,24.666,0
"258","p_2014_03",0.119,0.005,25.52,0
"259","p_2014_04",0.128,0.005,27.005,0
"260","p_2014_05",0.119,0.005,25.159,0
"261","p_2014_06",0.121,0.005,25.751,0
"262","p_2014_07",0.117,0.005,25.048,0
"263","p_2014_08",0.127,0.005,26.89,0
"264","p_2014_09",0.125,0.005,26.456,0
"265","p_2014_10",0.122,0.005,26.008,0
"266","p_2014_11",0.123,0.005,26.166,0
"267","p_2014_12",0.122,0.005,23.756,0
"268","p_2015_01",0.125,0.005,25.181,0
"269","p_2015_02",0.131,0.005,25.873,0
"270","p_2015_03",0.134,0.005,27.19,0
"271","p_2015_04",0.124,0.005,24.539,0
"272","p_2015_05",0.123,0.005,24.466,0
"273","p_2015_06",0.124,0.005,24.976,0
"274","p_2015_07",0.12,0.005,24.302,0
"275","p_2015_08",0.111,0.005,22.778,0
"276","p_2015_09",0.119,0.005,24.846,0
"277","p_2015_10",0.127,0.005,26.846,0
"278","p_2015_11",0.119,0.005,24.063,0
"279","p_2015_12",0.125,0.005,24.922,0
"280","p_2016_01",0.151,0.004,34.106,0
Welcome to TeX.SE. Please provide a minimal working example (MWE) next time (I had to add a preamble, find the packages needed by your code...). In order to solve your problem, you can tell pgfplotstable
to build a longtable
. This is explained in section Customizing and Getting the Tabular Code of the pgfplotstable
manual.
begin{filecontents*}{data.csv}
"","term","estimate","std.error","statistic","p.value"
"1","(Intercept)",3.7,0.005,685.68,0
"2","log_m2_living",0.779,0.001,1291.798,0
"3","b_0",-0.001,0.001,-1.204,0.229
"4","b_2",0.003,0.002,1.38,0.168
"5","b_3",0.012,0.001,15.478,0
"6","b_4",0.094,0.001,120.918,0
"7","b_5",0.105,0.002,63.347,0
"8","b_6",0.167,0.035,4.717,0
"9","y_unknown",0.039,0.001,45.106,0
"10","y_0",0.294,0.016,17.853,0
"11","y_1400",0.116,0.004,30.914,0
"12","y_1800",0.107,0.002,47.573,0
"13","y_1900",0.08,0.002,46.152,0
"14","y_1925",0.029,0.002,18.172,0
"15","y_1950",-0.002,0.001,-1.228,0.219
"16","y_1960",0,0.001,0.092,0.927
"17","y_1970",-0.023,0.001,-19.074,0
"18","y_1990",0.038,0.001,28.279,0
"19","y_1995",0.059,0.001,42.989,0
"20","y_2000",0.104,0.001,74.26,0
"21","y_2005",0.12,0.001,100.682,0
"22","y_2010",0.151,0.002,99.272,0
"23","y_2015",0.151,0.004,42.265,0
"24","f_basement",-0.032,0.004,-8.52,0
"25","f_sout",0.11,0.04,2.752,0.006
"26","f_0",-0.003,0.001,-3.719,0
"27","f_hochp",-0.022,0.002,-9.542,0
"28","f_2",-0.003,0.001,-5.3,0
"29","f_3",0,0.001,0.181,0.857
"30","f_4",0.008,0.001,8.64,0
"31","f_5",0.021,0.001,15.495,0
"32","f_6",0.02,0.002,9.808,0
"33","f_7",0.007,0.003,2.494,0.013
"34","f_8",-0.017,0.004,-4.718,0
"35","f_9",-0.019,0.005,-3.906,0
"36","f_10",-0.02,0.003,-6.263,0
"37","f_penthouse",0.114,0.022,5.209,0
"38","f_attic",0.035,0.012,2.988,0.003
"39","f_unknown_floor",0.013,0.001,17.996,0
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"268","p_2015_01",0.125,0.005,25.181,0
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"278","p_2015_11",0.119,0.005,24.063,0
"279","p_2015_12",0.125,0.005,24.922,0
"280","p_2016_01",0.151,0.004,34.106,0
end{filecontents*}
documentclass{article}
usepackage{pgfplotstable}
pgfplotsset{compat=1.17}
usepackage{longtable}
usepackage{booktabs}
usepackage{siunitx}
usepackage{capt-of} % for captionof
begin{document}
captionof{table}{Regression Results for Apartment Rent}label{RegAR}nobreak
pgfplotstabletypeset[
multicolumn names,
col sep=comma,
string replace*={"}{},
columns = {"term", "estimate", "std.error", "statistic", "p.value"},
columns/""/.style={
column name=Coefficient,
column type={S},string type},
columns/"term"/.style={
column name=Variables,
verb string type, column type=l},
columns/"estimate"/.style={
column name=Coefficient,
column type={S},string type},
columns/"std.error"/.style={
column name=Std. Error,
column type={S},string type},
columns/"statistic"/.style={
column name=t-value,
column type={S},string type},
columns/"p.value"/.style={
column name=p-value,
column type={S},string type},
every head row/.style={
before row={toprule}, % have a rule at top
after row={midrule} % rule under units
},
begin table=begin{longtable},
end table=end{longtable},
every head row/.append style={
% Uncomment this if you want the caption repeated on each page
% before row={caption{Regression Results for Apartment Rent}},
after row={%
midruleendhead
bottomruleendfoot
},
},
]{data.csv}
end{document}
First two pages of the output:
Last page:
Answered by frougon on February 4, 2021
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