У меня проблемы с определенным набором данных следующим образом:
1) Я загружаю таблицу:
Regression_990_DT<-fread("DATASET FINALE PER REGRESSIONE 990.R")
2) Я использую его для назначения pdata.frame:
mypanel<- pdata.frame(Regression_990_DT, index = c("Individual","Year"), drop.index = FALSE)
Когда я пытаюсь просмотреть «mypanel» из среды, я получаю
View(mypanel)
Error in View : cannot coerce class ""pseries"" to a data.frame
Как ни странно, если я использую функцию head , я вижу "mypanel":
head(mypanel)
Individual Year Durata Project_number Expenditure SUD_DUMMY_1ifSUD PIL_ProCapite_euro Emp
1-2007 1 2007 315.2321 280 454408824 1 16017.20 33.00737
1-2008 1 2008 315.2321 387 1051968083 1 14895.19 32.96581
1-2009 1 2009 315.2321 330 1121238394 1 14816.81 32.90641
1-2010 1 2010 315.2321 430 1184709708 1 14722.75 31.42855
1-2011 1 2011 315.2321 615 1484840551 1 14828.00 33.02960
1-2012 1 2012 315.2321 243 2672475087 1 14982.53 32.38563
Tonns.inhabitant Diploma_percentage Degree_percentage Reati.Associativi.per.100000.abitanti PA.payment.delays
1-2007 3.196138 0.0001685805 6.130319e-05 3.196138 -4.93
1-2008 2.727606 0.0001714428 6.379166e-05 2.727606 -4.93
1-2009 2.803359 0.0001787922 6.747277e-05 2.803359 -4.93
1-2010 2.219315 0.0001835938 6.743277e-05 2.219315 -4.93
1-2011 2.418667 0.0001899075 6.597913e-05 2.418667 -4.93
1-2012 3.000064 0.0001914966 7.117328e-05 3.000064 -4.93
Percentage.mistrust
1-2007 0.066392
1-2008 0.118608
1-2009 0.099814
1-2010 0.090391
1-2011 0.100016
1-2012 0.093328
Но если я затем использую "mypanel" внутри функции plm , я снова получаю похожую ошибку.
linear_model <- Durata ~ SUD_DUMMY_1ifSUD + PIL_ProCapite_euro + Emp + `Tonns/inhabitant` + Diploma_percentage + Degree_percentage + Reati.Associativi.per.100000.abitanti + PA.payment.delays + `Percentage mistrust` + Project_number + Expenditure + SUD_DUMMY_1ifSUD*(PIL_ProCapite_euro + Emp + `Tonns/inhabitant` + Diploma_percentage + Degree_percentage + Reati.Associativi.per.100000.abitanti + PA.payment.delays + `Percentage mistrust` + Project_number + Expenditure)
fixed__time_effects_fit <- plm(linear_model, pdata.frame(Regression_990_DT, index = c("Individual","Year"), drop.index = FALSE), model = "within", effect = "time", index = c("Individual","Year") )
Error in as.data.frame.default(x, ...) :
cannot coerce class ""pseries"" to a data.frame
Если я работаю с данными о преступности из пакета «foregin», все работает правильно. Единственное различие, которое я заметил между двумя наборами данных (помимо того факта, что я подготовил первый), заключается в следующем:
class(Regression_990_DT)
[1] "data.table" "data.frame"
Пока
data(Crime)
class(Crime)
[1] "data.frame"
Преобразование "Regression_990_DT" в data.frame не помогло решить мою проблему. В чем причина проблемы и как я могу ее решить? Дайте мне знать, если я предоставлю дополнительную информацию, пожалуйста.
-edit: в соответствии с запросом, вот более короткая версия Regression_990_DT, полученная
smallRegression_DT<-Regression_990_DT[c(1:150),]
mypanel<-pdata.frame(smallRegression_DT,index=c("Individual","Year"),drop.index = FALSE)
dput(smallRegression_DT,file="Small Regression 990 _DT.txt")
View(mypanel)
Error in View : cannot coerce class ""pseries"" to a data.frame
structure(list(Individual = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
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13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 17L),
Year = c(2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L),
Durata = c(315.23214, 315.23214, 315.23214, 315.23214, 315.23214,
315.23214, 315.23214, 315.23214, 315.23214, 222.51546, 222.51546,
222.51546, 222.51546, 222.51546, 222.51546, 222.51546, 222.51546,
222.51546, 397.27027, 397.27027, 397.27027, 397.27027, 397.27027,
397.27027, 397.27027, 397.27027, 397.27027, 703.625, 703.625,
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909.4, 909.4, 909.4, 909.4, 909.4, 909.4, 909.4, 909.4, 909.4,
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781.09052, 781.09052, 781.09052, 781.09052, 781.09052, 781.09052,
781.09052, 781.09052, 454.65979, 454.65979, 454.65979, 454.65979,
454.65979, 454.65979, 454.65979, 454.65979, 454.65979, 286.8,
286.8, 286.8, 286.8, 286.8, 286.8, 286.8, 286.8, 286.8, 755.79573,
755.79573, 755.79573, 755.79573, 755.79573, 755.79573, 755.79573,
755.79573, 755.79573, 722, 722, 722, 722, 722, 722, 722,
722, 722, 219.65, 219.65, 219.65, 219.65, 219.65, 219.65,
219.65, 219.65, 219.65, 10.685, 10.685, 10.685, 10.685, 10.685,
10.685, 10.685, 10.685, 10.685, 94.71429, 94.71429, 94.71429,
94.71429, 94.71429, 94.71429, 94.71429, 94.71429, 94.71429,
833, 833, 833, 833, 833, 833), Project_number = c(280L, 387L,
330L, 430L, 615L, 243L, 286L, 170L, 107L, 97L, 211L, 301L,
462L, 460L, 256L, 282L, 130L, 61L, 37L, 197L, 927L, 1315L,
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627L, 204L, 53L, 132L, 155L, 328L, 276L, 200L, 247L, 131L,
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728L, 1139L, 674L, 38L, 7L, 53L, 38L, 11L, 20L, 24L, 19L,
9L, 6L, 2L, 316L, 11657L, 18206L, 5603L, 5313L), Expenditure = structure(c(2.24507789105521e-315,
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2.98218576689234e-315, 2.3086077322002e-315), class = "integer64"),
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0L, 0L, 0L, 0L, 0L, 0L), PIL_ProCapite_euro = c(16017.2,
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57.15862, 57.77888, 57.57656, 57.73713, 57.31809, 57.87199,
57.36274, 56.98581, 56.88521, 51.68247, 51.99544, 51.61008,
50.59364, 48.84598, 48.88933), `Tonns/inhabitant` = c(3.1961383,
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4.1259857, 4.8171136, 4.4487863, 3.2626923, 3.486474, 3.5893337,
2.7663908, 3.0175185, 3.3127343, 2.2049477, 1.9048913, 1.7301393,
2.0736453, 1.5795176, 2.1479161, 1.8670767, 5.1097927, 2.0814786,
2.2049477, 1.9048913, 1.7301393, 2.0736453, 1.5795176, 2.1479161,
1.8670767, 5.1097927, 2.0814786, 1.32461, 1.3734346, 1.3237428,
1.4029454, 1.0303314, 0.5957631, 1.2234194, 0.9741827, 1.3004537,
4.1259857, 4.8171136, 4.4487863, 3.2626923, 3.486474, 3.5893337,
2.7663908, 3.0175185, 3.3127343, 1.0708336, 1.0202281, 1.2012661,
1.4845711, 1.3426456, 1.2105416, 1.0825619, 0.9811768, 1.0993973,
1.4157181, 1.2660572, 1.3993453, 0.7104918, 1.3758356, 1.0536304,
0.8625729, 1.0833668, 1.1779746, 1.0524552, 1.0870344, 1.099711,
0.6714496, 1.1069367, 1.0093217, 1.3372861, 0.6968749, 0.7192099,
1.5101398, 1.5931621, 0.7895187, 0.5878284, 0.7790111, 0.9664081,
1.1472906, 3.3208643, 5.0117066, 1.0708336, 1.0202281, 1.2012661,
1.4845711, 1.3426456, 1.2105416), Diploma_percentage = c(0.0001685805,
0.0001714428, 0.0001787922, 0.0001835938, 0.0001899075, 0.0001914966,
0.0001888013, 0.0001949259, 0.0001983538, 0.0002224064, 0.0002237536,
0.0002294661, 0.0002376372, 0.0002408855, 0.0002346469, 0.000237483,
0.0002419359, 0.0002416174, 0.0002211421, 0.0002281085, 0.0002308735,
0.0002258536, 0.0002319775, 0.0002342337, 0.0002335658, 0.0002378574,
0.0002441675, 0.0002049992, 0.0002040436, 0.0002178408, 0.0002215369,
0.0002225399, 0.0002194361, 0.0002170905, 0.0002249092, 0.0002254857,
0.0001956611, 0.0002031769, 0.000218449, 0.0002193913, 0.0002172489,
0.0002177178, 0.0002255263, 0.0002329892, 0.0002345239, 0.0002211421,
0.0002281085, 0.0002308735, 0.0002258536, 0.0002319775, 0.0002342337,
0.0002335658, 0.0002378574, 0.0002441675, 0.0002224064, 0.0002237536,
0.0002294661, 0.0002376372, 0.0002408855, 0.0002346469, 0.000237483,
0.0002419359, 0.0002416174, 0.0001721867, 0.0001705109, 0.0001773556,
0.0001811312, 0.0001909625, 0.0001967905, 0.000200789, 0.0002038329,
0.0001999294, 0.0001762201, 0.000173649, 0.0001738305, 0.0001797104,
0.0001903682, 0.0001861347, 0.0001853483, 0.0001881858, 0.0001891495,
0.0001762201, 0.000173649, 0.0001738305, 0.0001797104, 0.0001903682,
0.0001861347, 0.0001853483, 0.0001881858, 0.0001891495, 0.000223488,
0.0002306453, 0.0002370594, 0.0002449644, 0.0002433402, 0.0002491851,
0.0002492638, 0.0002544098, 0.000252495, 0.0001721867, 0.0001705109,
0.0001773556, 0.0001811312, 0.0001909625, 0.0001967905, 0.000200789,
0.0002038329, 0.0001999294, 0.0002265142, 0.0002280823, 0.0002302713,
0.0002340262, 0.0002393325, 0.0002434788, 0.0002473161, 0.0002480673,
0.0002453857, 0.0002224064, 0.0002237536, 0.0002294661, 0.0002376372,
0.0002408855, 0.0002346469, 0.000237483, 0.0002419359, 0.0002416174,
0.0002241009, 0.0002277676, 0.0002348658, 0.000242902, 0.0002423722,
0.0002454686, 0.0002528271, 0.000254094, 0.0002495213, 0.0002246225,
0.0002309484, 0.0002373578, 0.0002397655, 0.000246238, 0.0002491149,
0.0002549095, 0.0002667609, 0.0002648261, 0.0002265142, 0.0002280823,
0.0002302713, 0.0002340262, 0.0002393325, 0.0002434788),
Degree_percentage = c(6.130319e-05, 6.379166e-05, 6.747277e-05,
6.743277e-05, 6.597913e-05, 7.117328e-05, 7.367855e-05, 7.302673e-05,
7.229071e-05, 7.158837e-05, 7.662479e-05, 7.662272e-05, 7.859236e-05,
7.819857e-05, 8.407029e-05, 8.802172e-05, 8.891417e-05, 9.012124e-05,
7.531376e-05, 7.581808e-05, 8.432531e-05, 8.783673e-05, 8.449147e-05,
9.177848e-05, 9.965288e-05, 0.0001009108, 0.0001000585, 6.421576e-05,
6.667193e-05, 6.081188e-05, 6.17438e-05, 6.833044e-05, 8.125888e-05,
8.989891e-05, 8.448902e-05, 8.521561e-05, 8.03137e-05, 8.551822e-05,
8.277732e-05, 8.529328e-05, 9.045635e-05, 9.40858e-05, 9.396692e-05,
9.570612e-05, 0.000105987, 7.531376e-05, 7.581808e-05, 8.432531e-05,
8.783673e-05, 8.449147e-05, 9.177848e-05, 9.965288e-05, 0.0001009108,
0.0001000585, 7.158837e-05, 7.662479e-05, 7.662272e-05, 7.859236e-05,
7.819857e-05, 8.407029e-05, 8.802172e-05, 8.891417e-05, 9.012124e-05,
6.088015e-05, 6.442274e-05, 6.859315e-05, 7.105602e-05, 6.887158e-05,
7.621768e-05, 7.955348e-05, 7.986245e-05, 8.298539e-05, 6.081867e-05,
6.540378e-05, 6.140755e-05, 6.400306e-05, 6.44149e-05, 6.851434e-05,
7.261599e-05, 7.663e-05, 7.278414e-05, 6.081867e-05, 6.540378e-05,
6.140755e-05, 6.400306e-05, 6.44149e-05, 6.851434e-05, 7.261599e-05,
7.663e-05, 7.278414e-05, 6.837772e-05, 7.285187e-05, 7.411649e-05,
7.841716e-05, 7.929979e-05, 7.743996e-05, 8.357224e-05, 8.623972e-05,
8.860659e-05, 6.088015e-05, 6.442274e-05, 6.859315e-05, 7.105602e-05,
6.887158e-05, 7.621768e-05, 7.955348e-05, 7.986245e-05, 8.298539e-05,
7.87614e-05, 8.481446e-05, 8.671614e-05, 8.923952e-05, 8.981926e-05,
9.295857e-05, 9.718942e-05, 0.0001013284, 0.0001091616, 7.158837e-05,
7.662479e-05, 7.662272e-05, 7.859236e-05, 7.819857e-05, 8.407029e-05,
8.802172e-05, 8.891417e-05, 9.012124e-05, 7.986197e-05, 8.699749e-05,
9.059117e-05, 8.982733e-05, 9.694028e-05, 9.999793e-05, 9.965632e-05,
0.0001045577, 0.0001130813, 6.609168e-05, 6.881413e-05, 7.229612e-05,
7.773812e-05, 8.005653e-05, 8.300723e-05, 8.606477e-05, 9.501401e-05,
9.612805e-05, 7.87614e-05, 8.481446e-05, 8.671614e-05, 8.923952e-05,
8.981926e-05, 9.295857e-05), Reati.Associativi.per.100000.abitanti = c(3.1961383,
2.7276062, 2.8033593, 2.2193151, 2.4186671, 3.0000642, 2.8925586,
4.4959187, 2.5377862, 1.4157181, 1.2660572, 1.3993453, 0.7104918,
1.3758356, 1.0536304, 0.8625729, 1.0833668, 1.1779746, 2.8737565,
2.5857834, 1.7990829, 1.1031003, 1.5571079, 2.2684239, 2.3238603,
2.1907682, 1.6803746, 2.3980432, 2.3817179, NA, 1.5782392,
NA, 1.5719316, 1.5598495, NA, NA, 1.6673366, 1.8190397, 1.6715239,
1.4741435, 1.8536874, 1.7118151, 1.6390494, 1.0928721, 1.3071805,
2.8737565, 2.5857834, 1.7990829, 1.1031003, 1.5571079, 2.2684239,
2.3238603, 2.1907682, 1.6803746, 1.4157181, 1.2660572, 1.3993453,
0.7104918, 1.3758356, 1.0536304, 0.8625729, 1.0833668, 1.1779746,
4.1259857, 4.8171136, 4.4487863, 3.2626923, 3.486474, 3.5893337,
2.7663908, 3.0175185, 3.3127343, 2.2049477, 1.9048913, 1.7301393,
2.0736453, 1.5795176, 2.1479161, 1.8670767, 5.1097927, 2.0814786,
2.2049477, 1.9048913, 1.7301393, 2.0736453, 1.5795176, 2.1479161,
1.8670767, 5.1097927, 2.0814786, 1.32461, 1.3734346, 1.3237428,
1.4029454, 1.0303314, 0.5957631, 1.2234194, 0.9741827, 1.3004537,
4.1259857, 4.8171136, 4.4487863, 3.2626923, 3.486474, 3.5893337,
2.7663908, 3.0175185, 3.3127343, 1.0708336, 1.0202281, 1.2012661,
1.4845711, 1.3426456, 1.2105416, 1.0825619, 0.9811768, 1.0993973,
1.4157181, 1.2660572, 1.3993453, 0.7104918, 1.3758356, 1.0536304,
0.8625729, 1.0833668, 1.1779746, 1.0524552, 1.0870344, 1.099711,
0.6714496, 1.1069367, 1.0093217, 1.3372861, 0.6968749, 0.7192099,
1.5101398, 1.5931621, 0.7895187, 0.5878284, 0.7790111, 0.9664081,
1.1472906, 3.3208643, 5.0117066, 1.0708336, 1.0202281, 1.2012661,
1.4845711, 1.3426456, 1.2105416), PA.payment.delays = c(-4.93,
-4.93, -4.93, -4.93, -4.93, -4.93, -4.93, -4.93, -4.93, 53.48,
53.48, 53.48, 53.48, 53.48, 53.48, 53.48, 53.48, 53.48, 18.34,
18.34, 18.34, 18.34, 18.34, 18.34, 18.34, 18.34, 18.34, 39.39,
39.39, 39.39, 39.39, 39.39, 39.39, 39.39, 39.39, 39.39, -12.31,
-12.31, -12.31, -12.31, -12.31, -12.31, -12.31, -12.31, -12.31,
172, 172, 172, 172, 172, 172, 172, 172, 172, 21.59, 21.59,
21.59, 21.59, 21.59, 21.59, 21.59, 21.59, 21.59, 10, 10,
10, 10, 10, 10, 10, 10, 10, 43.28, 43.28, 43.28, 43.28, 43.28,
43.28, 43.28, 43.28, 43.28, 43, 43, 43, 43, 43, 43, 43, 43,
43, -14.28, -14.28, -14.28, -14.28, -14.28, -14.28, -14.28,
-14.28, -14.28, 39.79, 39.79, 39.79, 39.79, 39.79, 39.79,
39.79, 39.79, 39.79, -12.21, -12.21, -12.21, -12.21, -12.21,
-12.21, -12.21, -12.21, -12.21, -5.14, -5.14, -5.14, -5.14,
-5.14, -5.14, -5.14, -5.14, -5.14, 4.81, 4.81, 4.81, 4.81,
4.81, 4.81, 4.81, 4.81, 4.81, -6.79, -6.79, -6.79, -6.79,
-6.79, -6.79, -6.79, -6.79, -6.79, -1, -1, -1, -1, -1, -1
), `Percentage mistrust` = c(0.066392, 0.118608, 0.099814,
0.090391, 0.100016, 0.093328, 0.102955, 0.116963, 0.122902,
0.041415, 0.065325, 0.045325, 0.04775, 0.047288, 0.05539,
0.048018, 0.067868, 0.052026, 0.04836, 0.055536, 0.04646,
0.049234, 0.045954, 0.052704, 0.053452, 0.064068, 0.066778,
0.041496, 0.060602, 0.036616, 0.050505, 0.039996, 0.076824,
0.0424, 0.048068, 0.061934, 0.03069, 0.049518, 0.04074, 0.057855,
0.041447, 0.045368, 0.041664, 0.04816, 0.055755, 0.04836,
0.055536, 0.04646, 0.049234, 0.045954, 0.052704, 0.053452,
0.064068, 0.066778, 0.041415, 0.065325, 0.045325, 0.04775,
0.047288, 0.05539, 0.048018, 0.067868, 0.052026, 0.09423,
0.115431, 0.079182, 0.085852, 0.085224, 0.084152, 0.106984,
0.10304, 0.120408, 0.066528, 0.099268, 0.09515, 0.087904,
0.079156, 0.095011, 0.093009, 0.10336, 0.087327, 0.066528,
0.099268, 0.09515, 0.087904, 0.079156, 0.095011, 0.093009,
0.10336, 0.087327, 0.035096, 0.04176, 0.048841, 0.039935,
0.041241, 0.051086, 0.039798, 0.059856, 0.051129, 0.09423,
0.115431, 0.079182, 0.085852, 0.085224, 0.084152, 0.106984,
0.10304, 0.120408, 0.042921, 0.052559, 0.049245, 0.041108,
0.043434, 0.03798, 0.04895, 0.050778, 0.04888, 0.041415,
0.065325, 0.045325, 0.04775, 0.047288, 0.05539, 0.048018,
0.067868, 0.052026, 0.03444, 0.03937, 0.043326, 0.035475,
0.034344, 0.05133, 0.029575, 0.036494, 0.046816, 0.033485,
0.038304, 0.02325, 0.042488, 0.027666, 0.031842, 0.034048,
0.046208, 0.041905, 0.042921, 0.052559, 0.049245, 0.041108,
0.043434, 0.03798)), .Names = c("Individual", "Year", "Durata",
"Project_number", "Expenditure", "SUD_DUMMY_1ifSUD", "PIL_ProCapite_euro",
"Emp", "Tonns/inhabitant", "Diploma_percentage", "Degree_percentage",
"Reati.Associativi.per.100000.abitanti", "PA.payment.delays",
"Percentage mistrust"), class = c("data.table", "data.frame"), row.names = c(NA,
-150L), .internal.selfref = <pointer: 0x00000000001d0788>)