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Encuesta Nacional Agropecuaria 2017

Peru, 2017
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Reference ID
PER_2017_ENA_v01_M
Producer(s)
Instituto Nacional de Estadística e Informática, Dirección Nacional de Censos y Encuestas
Metadata
DDI/XML JSON
Created on
Jan 16, 2021
Last modified
Jan 16, 2021
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Nombre de la provincia (NOMBREPV)

Data file: 17_Cap1000

Overview

Valid: 28804
Invalid: 0
Type: Discrete
Start: 22
End: 46
Width: 25
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
ABANCAY 166
0.6%
ACOBAMBA 163
0.6%
ACOMAYO 30
0.1%
AIJA 12
0%
ALTO AMAZONAS 157
0.5%
AMBO 99
0.3%
ANDAHUAYLAS 453
1.6%
ANGARAES 158
0.5%
ANTA 141
0.5%
ANTABAMBA 38
0.1%
ANTONIO RAYMONDI 27
0.1%
AREQUIPA 315
1.1%
ASCOPE 62
0.2%
ASUNCION 14
0%
ATALAYA 184
0.6%
AYABACA 271
0.9%
AYMARAES 111
0.4%
AZANGARO 213
0.7%
BAGUA 149
0.5%
BARRANCA 99
0.3%
BELLAVISTA 103
0.4%
BOLIVAR 39
0.1%
BOLOGNESI 15
0.1%
BONGARA 86
0.3%
CAJABAMBA 95
0.3%
CAJAMARCA 178
0.6%
CAJATAMBO 42
0.1%
CALCA 101
0.4%
CALLAO 10
0%
CAMANA 74
0.3%
CANAS 56
0.2%
CANCHIS 118
0.4%
CANDARAVE 169
0.6%
CANGALLO 121
0.4%
CANTA 41
0.1%
CARABAYA 69
0.2%
CARAVELI 58
0.2%
CARHUAZ 180
0.6%
CARLOS FERMIN FITZCARRALD 64
0.2%
CASMA 66
0.2%
CASTILLA 141
0.5%
CASTROVIRREYNA 53
0.2%
CAYLLOMA 368
1.3%
CAÑETE 301
1%
CELENDIN 91
0.3%
CHACHAPOYAS 256
0.9%
CHANCHAMAYO 120
0.4%
CHEPEN 50
0.2%
CHICLAYO 219
0.8%
CHINCHA 295
1%
CHINCHEROS 201
0.7%
CHOTA 179
0.6%
CHUCUITO 165
0.6%
CHUMBIVILCAS 133
0.5%
CHUPACA 157
0.5%
CHURCAMPA 158
0.5%
CONCEPCION 140
0.5%
CONDESUYOS 96
0.3%
CONDORCANQUI 80
0.3%
CONTRALMIRANTE VILLAR 84
0.3%
CONTUMAZA 40
0.1%
CORONEL PORTILLO 453
1.6%
CORONGO 14
0%
COTABAMBAS 142
0.5%
CUSCO 21
0.1%
CUTERVO 163
0.6%
DANIEL ALCIDES CARRION 245
0.9%
DATEM DEL MARAÑÓN 151
0.5%
DOS DE MAYO 109
0.4%
EL COLLAO 122
0.4%
EL DORADO 56
0.2%
ESPINAR 43
0.1%
FERREÑAFE 381
1.3%
GENERAL SANCHEZ CERRO 544
1.9%
GRAN CHIMU 94
0.3%
GRAU 89
0.3%
HUACAYBAMBA 66
0.2%
HUALGAYOC 55
0.2%
HUALLAGA 65
0.2%
HUAMALIES 154
0.5%
HUAMANGA 242
0.8%
HUANCA SANCOS 29
0.1%
HUANCABAMBA 391
1.4%
HUANCANE 165
0.6%
HUANCAVELICA 281
1%
HUANCAYO 226
0.8%
HUANTA 223
0.8%
HUANUCO 286
1%
HUARAL 228
0.8%
HUARAZ 202
0.7%
HUARI 150
0.5%
HUARMEY 17
0.1%
HUAROCHIRI 150
0.5%
HUAURA 163
0.6%
HUAYLAS 99
0.3%
HUAYTARA 117
0.4%
ICA 572
2%
ILO 14
0%
ISLAY 62
0.2%
JAEN 73
0.3%
JAUJA 242
0.8%
JORGE BASADRE 115
0.4%
JULCAN 81
0.3%
JUNIN 54
0.2%
LA CONVENCIÓN 248
0.9%
LA MAR 178
0.6%
LA UNION 109
0.4%
LAMAS 153
0.5%
LAMBAYEQUE 601
2.1%
LAMPA 27
0.1%
LAURICOCHA 64
0.2%
LEONCIO PRADO 64
0.2%
LIMA 132
0.5%
LORETO 106
0.4%
LUCANAS 136
0.5%
LUYA 397
1.4%
MANU 123
0.4%
MARAÑON 91
0.3%
MARISCAL CACERES 84
0.3%
MARISCAL LUZURIAGA 41
0.1%
MARISCAL NIETO 594
2.1%
MARISCAL RAMÓN CASTILLA 93
0.3%
MAYNAS 301
1%
MELGAR 50
0.2%
MOHO 28
0.1%
MORROPON 170
0.6%
MOYOBAMBA 219
0.8%
NAZCA 84
0.3%
OCROS 1
0%
OTUZCO 288
1%
OXAPAMPA 372
1.3%
OYON 14
0%
PACASMAYO 88
0.3%
PACHITEA 120
0.4%
PADRE ABAD 377
1.3%
PAITA 30
0.1%
PALLASCA 38
0.1%
PALPA 41
0.1%
PARINACOCHAS 93
0.3%
PARURO 108
0.4%
PASCO 554
1.9%
PATAZ 97
0.3%
PAUCAR DEL SARA SARA 42
0.1%
PAUCARTAMBO 92
0.3%
PICOTA 133
0.5%
PISCO 190
0.7%
PIURA 275
1%
POMABAMBA 53
0.2%
PUERTO INCA 149
0.5%
PUNO 239
0.8%
PURÚS 13
0%
QUISPICANCHI 136
0.5%
RECUAY 47
0.2%
REQUENA 99
0.3%
RIOJA 106
0.4%
RODRIGUEZ DE MENDOZA 75
0.3%
SAN ANTONIO DE PUTINA 28
0.1%
SAN IGNACIO 151
0.5%
SAN MARCOS 65
0.2%
SAN MARTIN 103
0.4%
SAN MIGUEL 92
0.3%
SAN PABLO 41
0.1%
SAN ROMAN 70
0.2%
SANCHEZ CARRION 337
1.2%
SANDIA 195
0.7%
SANTA 186
0.6%
SANTA CRUZ 74
0.3%
SANTIAGO DE CHUCO 124
0.4%
SATIPO 135
0.5%
SECHURA 54
0.2%
SIHUAS 52
0.2%
SUCRE 14
0%
SULLANA 162
0.6%
TACNA 661
2.3%
TAHUAMANU 200
0.7%
TALARA 14
0%
TAMBOPATA 457
1.6%
TARATA 171
0.6%
TARMA 117
0.4%
TAYACAJA 250
0.9%
TOCACHE 153
0.5%
TRUJILLO 70
0.2%
TUMBES 569
2%
UCAYALI 124
0.4%
URUBAMBA 67
0.2%
UTCUBAMBA 205
0.7%
VICTOR FAJARDO 123
0.4%
VILCAS HUAMAN 25
0.1%
VIRU 94
0.3%
YAROWILCA 91
0.3%
YAULI 17
0.1%
YAUYOS 132
0.5%
YUNGAY 135
0.5%
YUNGUYO 51
0.2%
ZARUMILLA 209
0.7%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.

Description

Definition
La variable permite conocer el nombre de la provincia donde se ubica la unidad agropecuaria.
Universe
La encuesta cubre a todas las unidades agropecuarias del país con menos de 50 ha y las unidades agropecuarias que son empresas agrícolas o agropecuarios.
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