NPL_2015_FS_v01_EN_M_v01_A_OCS DDI_NPL_2015_FS_v01_EN_M_v01_A_OCS_FAO Office of Chief Statistician Central Bureau of Statistics Nesstar Publisher NPL_2015_FS_v01_EN_M_v01_A_OCS_v01 Fishery Survey 2015 FS 2015 NPL_2015_FS_v01_EN_M_v01_A_OCS Central Bureau of Statistics (c) 2015, Central Bureau of Statistics, Government of Nepal Nesstar Publisher Government of Nepal Director of Publication, Dissemination and Library Section Agricultural Survey [ag/oth] This is the first ever survey of this type conducted in the country. v1: Final Data for internal use only. Fishery survey Fish kind Reservoir Agriculture and Rural Development The Nepal Fishery survey 2015 is an adhoc survey conducted by the Central Bureau of Statistics, Nepal in 2015. This was conducted for the first time in Nepal. The survey was designed with the following objectives: 1. To identify the district-wise number of fish ponds, area of reservoirs, fish production and thier cost estimation. 2. Estimate the contribution made by the fishing business to the economy. 3. Providing necessary fishery statistics for planning and policy making. Nepal National Coverage Entreprises Total number of fishing ponds of Nepal Sample survey data [ssd] This report includes the information on number, area, water surface area and average depth of pond, median age, sex and fishery training status of fish farmer, education status of fish farmer, major selling place of fish, type of employment, wages and salaries, species of fingerlings (Bhura) and its cost, current expenditure of fish farming, number of pond, water surface area, fish production, value of production and yield rate, value of fixed assets formation during the reference period, input and output of integrated fish farming, percentage of farmers facing problem, percentage of farmers reporting loan, average interest rate, percentage of farmer that need loan/additional loan and purpose of loan and principal indicator of fish farming. The reference period for the 2015 Fishery Survey (FS) was from 17/07/2015 to 15/07/2016. Central Bureau of Statistics Most important initiation of the survey was preparing a survey frame. A total of 24,559 fish ponds were collected in 2014/15. The enumerators of the SOs were directly involved for the listing purpose using paper listing form. Theoretically, the listing of the farms was based on primary source of data collection. The listing forms collected from districts were edited and coded and finally, the survey frame was prepared. After preparing the survey frame, the list was prepared on the basis of area of fish ponds in descending order. The samples were drawn according to systematic sampling. Face-to-face paper [f2f] There was no non-response case as additional samples were drawn to address the non response as well as missing cases. Confidentiality of the respondents is guaranteed by article 8 of Statistics Act 1958. Restriction on publication of information and details. Any information or details relating to any person, family, firm or company, which have been supplied, obtained or prepared pursuant to Section 3 or Section 4 or Section 5 or Section 6 or Section 7 or any part of such information or details, shall not be disclosed or published directly except to the Director General or to any other officer of the Bureau without the written permission of the person or of his or her authorized representative supplying such information or details. Director General Central Bureau of Statistics (CBS), Nepal Fishery Survey 2015. Data and information obtained from National Data Archive (NADA): http://cbs.gov.np/nada/index.php/catalog on [date]. The dataset has been anonymized and is available for internal use only, i.e. not access to public use. The Central Bureau of Statistics, Nepal bears no responsibility for any outcomes or for interpretations or inferences arising from the use of the dataset, or use of the information provided on the study AGGREGATED.NSDstat This data set is related to aggregated expenditure and productions section of the questionnaire. 0 35 Nesstar 200801 BURA_TYPE.NSDstat This data set is related to Current expenditure section of the questionnaire. 0 30 Nesstar 200801 CAPITAL_EXP.NSDstat This data set is related to Capital expenditure section of the questionnaire. 0 21 Nesstar 200801 EMPLOYEE.NSDstat This data set is related to Employment section of the questionnaire. 0 27 Nesstar 200801 F_PROBLEMS.NSDstat This data set is related to Major problem section of the questionnaire. 0 20 Nesstar 200801 F_PRODUCTION final.NSDstat This data set is related to Production of fish section of the questionnaire. 0 28 Nesstar 200801 FISH1_REC.NSDstat This data set is related to information about pond section of the questionnaire. 0 40 Nesstar 200801 INSTITUTIONAL.NSDstat This data set is related to institution fishery section of the questionnaire. 0 22 Nesstar 200801 LOAN_INSURENCE.NSDstat This data set is related to Loan and insurance section of the questionnaire. 0 26 Nesstar 200801 O_INCOME.NSDstat This data set is related to Income section of the questionnaire. 0 22 Nesstar 200801 OTHER_EXP.NSDstat This data set is related to other expenditure section of the questionnaire. 0 25 Nesstar 200801 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE What is the caste of fish farmer ? 0 0 Sex Sex Sex Sex Sex What is the sex of fish farmer ? 0 0 1 Male 2 Female AGE AGE AGE AGE AGE What is the age of fish farmer ? 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION What is the oppupation of fish farmer ? 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION What is the education of fish farmer ? 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING Have <Name> taken any kind of fishery training ? 0 0 1 Having traning 2 No Training IN01_SNO IN01_SNO IN01_SNO IN01_SNO IN01_SNO 0 0 1 Pig 2 Duck 3 Banana 4 Vegitable 5 Others 9 not app IN03_NUMBER IN03_NUMBER IN03_NUMBER IN03_NUMBER IN03_NUMBER 0 0 IN04_KG IN04_KG IN04_KG IN04_KG IN04_KG Weight of goat/chikens/ 0 0 IN05_PRICE IN05_PRICE IN05_PRICE IN05_PRICE IN05_PRICE 0 0 IN06_FEEDKG IN06_FEEDKG IN06_FEEDKG IN06_FEEDKG IN06_FEEDKG 0 0 IN07_FEEDPRICE IN07_FEEDPRICE IN07_FEEDPRICE IN07_FEEDPRICE IN07_FEEDPRICE 0 0 IN08_FERTKG IN08_FERTKG IN08_FERTKG IN08_FERTKG IN08_FERTKG 0 0 IN09_FERTPRICE IN09_FERTPRICE IN09_FERTPRICE IN09_FERTPRICE IN09_FERTPRICE 0 0 IN10_MEDICINE EXP IN10_MEDICINE EXP IN10_MEDICINE EXP IN10_MEDICINE EXP IN10_MEDICINE EXP 0 0 IN11_LABORCOST IN11_LABORCOST IN11_LABORCOST IN11_LABORCOST IN11_LABORCOST 0 0 IN12_OTHERCOST IN12_OTHERCOST IN12_OTHERCOST IN12_OTHERCOST IN12_OTHERCOST 0 0 IN13_GTOTAL IN13_GTOTAL IN13_GTOTAL IN13_GTOTAL IN13_GTOTAL 0 0 IN14_QTYNUMBER IN14_QTYNUMBER IN14_QTYNUMBER IN14_QTYNUMBER IN14_QTYNUMBER 0 0 IN15_QTYKG IN15_QTYKG IN15_QTYKG IN15_QTYKG IN15_QTYKG 0 0 IN16_TOTAL IN16_TOTAL IN16_TOTAL IN16_TOTAL IN16_TOTAL 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training CODE CODE CODE CODE CODE 0 0 1 Rahu 2 Naini 3 Vakur 4 Common carp 5 Grass carp 6 Siver carve 7 Big head 8 Trout 97 Not aaplicable TYPE TYPE TYPE TYPE TYPE Types of Bhura 0 0 1 Hatchling 2 Fry 3 Fingerlings Sources of Bhura Sources of Bhura Sources of Bhura Sources of Bhura Sources of Bhura Sources of Bhura 0 0 1 District fisery office 2 private hacherry 3 own production 4 India 5 others No. of Times of Bhura No. of Times of Bhura No. of Times of Bhura No. of Times of Bhura No. of Times of Bhura Number of times of Bhura 0 0 UNIT UNIT UNIT UNIT UNIT Unit of Bhura 0 0 1 Liter 2 Number QTY QTY QTY QTY QTY Quantity of Bhura 0 0 UNITPRICE UNITPRICE UNITPRICE UNITPRICE UNITPRICE Perunit price of Bhura 0 0 TOTAL TOTAL TOTAL TOTAL TOTAL Total Price of Bhura 0 0 PACK_CHARGE PACK_CHARGE PACK_CHARGE PACK_CHARGE PACK_CHARGE Price of packing and transportation. 0 0 GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL Grand total expenditure. 0 0 GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL GRAND_TOTAL 0 0 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training CODENO CODENO CODENO CODENO CODENO 0 0 1 Pond Constration & Extension 2 Boundary 3 Bore Ring 4 Pumping set 5 Net 6 Balance & weight 7 Electric equipments USEDQTY USEDQTY USEDQTY USEDQTY USEDQTY Total number of Used 0 0 Total number of Used PRICE PRICE PRICE PRICE PRICE Total Price 0 0 Total Price 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training SN SN SN SN SN 0 0 1 Proprietor 2 Manager 3 Technical Worker 4 Production worker 9 Not applicable MALE MALE MALE MALE MALE Number of male emloyee 0 0 MSALARY MSALARY MSALARY MSALARY MSALARY Salary of male employee. 0 0 FEMALE FEMALE FEMALE FEMALE FEMALE Number of female Employee. 0 0 FSALARY FSALARY FSALARY FSALARY FSALARY Salary of female employee 0 0 0 0 Average salary of temporary male emplayee. 0 0 Average salary of temporary male emplayee. Average salary of temporary female emplayee. 0 0 Average salary of temporary female emplayee. Total salary of temporary emplayee. 0 0 Total salary of temporary emplayee. 0 0 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training 8.5S_NO 8.5S_NO 8.5S_NO 8.5S_NO 8.5S_NO Major three Problems faced by Fishery farmer. 0 0 Major three Problems faced by Fishery farmer. 1 Lack of capital 2 Lack of land 3 High interest rate 4 Lack improved species 5 Lack of market 6 High price of feeds 7 Lack of technical knowdge 8 No compensation on Electricity 9 Not applicable Rank Rank Rank Rank Rank 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training FP01_SNO FP01_SNO FP01_SNO FP01_SNO FP01_SNO 0 0 1 Rahu 2 Naini 3 Vakur 4 Common carp 5 Grass carp 6 Siver carp 7 Big head 8 Trout 9 Rahu Chhadi 10 Naini Chhadi 11 Others 97 not applicable FP03_NUMBER FP03_NUMBER FP03_NUMBER FP03_NUMBER FP03_NUMBER Total number of Bhura placed in Pond 0 0 FP04_MORTALITY FP04_MORTALITY FP04_MORTALITY FP04_MORTALITY FP04_MORTALITY Average death rate of Bhura. 0 0 Average death rate of Bhura. FP05_HARVTIMES FP05_HARVTIMES FP05_HARVTIMES FP05_HARVTIMES FP05_HARVTIMES times of fishing 0 0 FP06_HARVQTY FP06_HARVQTY FP06_HARVQTY FP06_HARVQTY FP06_HARVQTY Qantity of fishing 0 0 FP07_STDQTY FP07_STDQTY FP07_STDQTY FP07_STDQTY FP07_STDQTY Remaining qantity of fish in pond 0 0 FP08_TOTALQTY FP08_TOTALQTY FP08_TOTALQTY FP08_TOTALQTY FP08_TOTALQTY Total qantity of fish production. 0 0 FP09_AVGPRICE FP09_AVGPRICE FP09_AVGPRICE FP09_AVGPRICE FP09_AVGPRICE AVerage price of fish per k.g. 0 0 AVerage price of fish per k.g. FP10_TOTAL FP10_TOTAL FP10_TOTAL FP10_TOTAL FP10_TOTAL Total price of fish production. 0 0 Total price of fish production. 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training 2.1NO OF FISHING POND 2.1NO OF FISHING POND 2.1NO OF FISHING POND 2.1NO OF FISHING POND 2.1NO OF FISHING POND 0 0 Number of pond 2.2UTILITY OF POND 2.2UTILITY OF POND 2.2UTILITY OF POND 2.2UTILITY OF POND 2.2UTILITY OF POND 0 0 Use of pond 1 Fish production 2 Fingerlings Production 2.3SELLING PLACE 2.3SELLING PLACE 2.3SELLING PLACE 2.3SELLING PLACE 2.3SELLING PLACE 0 0 Where is the fish sold out? 1 Pond side 2 Market within district 3 Other district 4 Own use 2.4UNIT OF AREA 2.4UNIT OF AREA 2.4UNIT OF AREA 2.4UNIT OF AREA 2.4UNIT OF AREA 0 0 Unit of Area of pond used for fishery. 1 Bigha 2 Ropani Q25BIGHA Q25BIGHA Q25BIGHA Q25BIGHA Q25BIGHA 0 0 Q25KHATTA Q25KHATTA Q25KHATTA Q25KHATTA Q25KHATTA 0 0 Q25DHUR Q25DHUR Q25DHUR Q25DHUR Q25DHUR 0 0 Pond Ha. Pond Ha. Pond Ha. Pond Ha. Pond Ha. 0 0 Area of Pond Q26BIGHA Q26BIGHA Q26BIGHA Q26BIGHA Q26BIGHA 0 0 Q26KHATTA Q26KHATTA Q26KHATTA Q26KHATTA Q26KHATTA 0 0 Q26DHUR Q26DHUR Q26DHUR Q26DHUR Q26DHUR 0 0 Water Ha. Water Ha. Water Ha. Water Ha. Water Ha. 0 0 Area of water of pond Q27deepness Q27deepness Q27deepness Q27deepness Q27deepness 0 0 Dept of pond Q28ownership Q28ownership Q28ownership Q28ownership Q28ownership 0 0 Ownership of Pond 1 Own 2 Others 3 Government 4 Institutional Q29Rent year Q29Rent year Q29Rent year Q29Rent year Q29Rent year 0 0 Period of Rent Q2100rent amount Q2100rent amount Q2100rent amount Q2100rent amount Q2100rent amount 0 0 Rent amout Q211AGREEGATE FISHING Q211AGREEGATE FISHING Q211AGREEGATE FISHING Q211AGREEGATE FISHING Q211AGREEGATE FISHING 0 0 Has it been cultivated as a collective 1 Yes 2 No 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME District Name 0 0 DIST DIST DIST DIST DIST Code of district. 0 0 Code of district. 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training OPERATION DATE OPERATION DATE OPERATION DATE OPERATION DATE OPERATION DATE 0 0 NAME OF INSTITUTE NAME OF INSTITUTE NAME OF INSTITUTE NAME OF INSTITUTE NAME OF INSTITUTE Name of Intitute 0 0 Name of Intitute REGISTERED PLACE REGISTERED PLACE REGISTERED PLACE REGISTERED PLACE REGISTERED PLACE Place of Registration 0 0 Place of Registration DATE OF OPERATION DATE OF OPERATION DATE OF OPERATION DATE OF OPERATION DATE OF OPERATION Operation year 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training 8.1Loan 8.1Loan 8.1Loan 8.1Loan 8.1Loan Has <Name> taken load for fishery ? 0 0 1 Yes 2 No 8.2Name of loan provider 8.2Name of loan provider 8.2Name of loan provider 8.2Name of loan provider 8.2Name of loan provider Name of loan Provider 0 0 1 Cooperatives 2 Agricultural Development Bank 3 Commercial Bank 4 Other 8.3Interest Rate 8.3Interest Rate 8.3Interest Rate 8.3Interest Rate 8.3Interest Rate Interest rate 0 0 8.4Additional Loan 8.4Additional Loan 8.4Additional Loan 8.4Additional Loan 8.4Additional Loan Has <Name> needed additional loan for this fishery ? 0 0 1 Yes 2 No 8.5Purpose of loan 8.5Purpose of loan 8.5Purpose of loan 8.5Purpose of loan 8.5Purpose of loan Purpose of additional loan 0 0 1 Purchasing Bhura 2 Pond Constration 3 Equipments 4 Feeds 5 Others 8.6Insurence of fish 8.6Insurence of fish 8.6Insurence of fish 8.6Insurence of fish 8.6Insurence of fish Has <Name> did insurance of fish ? 0 0 Has <Name> did insurance of fish ? 1 Yes 2 No 8.7Insurance Amount 8.7Insurance Amount 8.7Insurance Amount 8.7Insurance Amount 8.7Insurance Amount Insurance amount 0 0 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training OI01_SNO OI01_SNO OI01_SNO OI01_SNO OI01_SNO 0 0 1 Water pump 2 Net 9 not app OI03_INCOME OI03_INCOME OI03_INCOME OI03_INCOME OI03_INCOME 0 0 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0 0 0 Form No. Form No. Form No. Form No. Form No. 0 0 DIST DIST DIST DIST DIST 0 0 1 Taplejung 2 Panchthar 3 Ilam 4 Jhapa 5 Morang 6 Sunsari 7 Dhankuta 8 Terhathum 9 Sankhuwasabha 10 Bhojpur 11 Solukhumbu 12 Okhaldhunga 13 Khotang 14 Udayapur 15 Saptari 16 Siraha 17 Dhanusa 18 Mahottari 19 Sarlahi 20 Sindhuli 21 Ramechhap 22 Dolakha 23 Sindhupalchok 24 Kavre 25 Lalitpur 26 Bhaktapur 27 Kathmandu 28 Nuwakot 29 Rasuwa 30 Dhading 31 Makwanpur 32 Rautahat 33 Bara 34 Parsa 35 Chitawan 36 Gorkha 37 Lamjung 38 Tanahu 39 Syangja 40 Kaski 41 Manang 42 Mustang 43 Myagdi 44 Parbat 45 Baglung 46 Gulmi 47 Palpa 48 Nawalparasi 49 Rupandehi 50 Kapilbastu 51 Arghakhanchi 52 Pyuthan 53 Rolpa 54 Rukum 55 Salyan 56 Dang 57 Banke 58 Bardiya 59 Surkhet 60 Dailekh 61 Jajarkot 62 Dolpa 63 Jumla 64 Kalikot 65 Mugu 66 Humla 67 Bajura 68 Bajhang 69 Achham 70 Doti 71 Kailali 72 Kanchanpur 73 Dadeldhura 74 Baitadi 75 Darchula DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME DISTRICT NAME 0 0 VDCMUN VDCMUN VDCMUN VDCMUN VDCMUN 0 0 WARD WARD WARD WARD WARD 0 0 PONDSNO PONDSNO PONDSNO PONDSNO PONDSNO 0 0 FHHSNO FHHSNO FHHSNO FHHSNO FHHSNO 0 0 FNAME FNAME FNAME FNAME FNAME 0 0 CASTE CODE CASTE CODE CASTE CODE CASTE CODE CASTE CODE 0 0 1 CHHETRI 2 BRAHMAN (HILL) 3 MAGAR 4 TAMANG 5 THARU 6 NEWAR 7 MUSLIM 8 KAMI 9 YADAV 10 RAI 11 GURUNG 12 DAMAIN/DHOLI 13 LIMBU 14 THAKURI 15 SARKI 16 TELI 17 CHAMAR/HARIJAN/RAM 18 KOIRI 19 KURMI 20 SANYASI 21 DHANUK 22 MUSAHAR 23 DUSADH/PASWAN/PASI 24 SHERPA 25 SONAR 26 KEWAT 27 BRAHMAN (TARAI) 28 BANIYA 29 GHARTI/BHUJEL 30 MALLAH 31 KALWAR 32 KUMAL 33 HAJAM/THAKUR 34 KANU 35 RAJBANSI 36 SUNUWAR 37 SUDHI 38 LOHAR 39 TATMA 40 KHATWE 41 DHOBI 42 MAJHI 43 NUNIYA 44 KUMHAR 45 DANUWAR 46 CHEPANG/PRAJA 47 HALUWAI 48 RAJPUT 49 KAYASTHA 50 BADHAE 51 MARWADI 52 SANTHAL/SATAR 53 DHAGAR/JHAGAR 54 BANTAR 55 BARAE 56 KAHAR 57 GANGAI 58 LODH 59 RAJBHAR 60 THAMI 61 DHIMAL 62 BHOTE 63 BING/BINDA 64 BHEDIYAR/GADERI 65 NURANG 66 YAKKHA 67 DARAI 68 TAJPURIYA 69 THAKALI 70 CHIDIMAR 71 PAHARI 72 MALI 73 BANGALI 74 CHHANTAL 75 DOM 76 KAMAR 77 BOTE 78 BRAHMU/BARAMU 79 GAINE 80 JIREL 81 ADIBASI/JANAJATI 82 CHURAUTE 83 BADI 84 MECHE 85 LEPCHA 86 HALKHOR 87 PUNJABI/SIKH 88 KISAN 89 RAJI 90 BYANGSI 91 HAYU 92 KOCHE 93 DHUNIA 94 WALUNG 95 JAIN 96 MUNDA 97 RAUTE 98 YEHLMO 99 PATHARKATA/KUSWADIYA 100 KUSUNDA 101 Bhumihar 102 Karmarong 103 Sakhariya CASTE CASTE CASTE CASTE CASTE 0 0 Sex Sex Sex Sex Sex 0 0 1 Male 2 Female AGE AGE AGE AGE AGE 0 0 OCCUPATION OCCUPATION OCCUPATION OCCUPATION OCCUPATION 0 0 1 Managers 2 Professionals 3 Technicians and associate professionals 4 Clerical support workers 5 Service and sales workers 6 Skilled agricultural, forestry and fishery workers 7 Craft and related trades workers 8 Plant and machine operators, and assemblers 9 Elementary worker 10 Household work 11 Student 12 Not working EDUCATION EDUCATION EDUCATION EDUCATION EDUCATION 0 0 1 Class 1 2 Class 2 3 Class 3 4 Class 4 5 Class 5 6 Class 6 7 Class 7 8 Class 8 9 Class 9 10 Class 10 11 SLC 12 Class 12/ Intermediate Level 13 Bachelors Level 14 Masters Level 15 Professional Degree 16 Literate (Non-Formal Education) 17 Illiterate TRANNING TRANNING TRANNING TRANNING TRANNING 0 0 1 Having traning 2 No Training SNO SNO SNO SNO SNO 0 0 97 not applicable COL03_UNIT COL03_UNIT COL03_UNIT COL03_UNIT COL03_UNIT 0 0 1 Quintal 2 kg 3 Liter 4 Mililiter USED_QTY USED_QTY USED_QTY USED_QTY USED_QTY Quantity of Used 0 0 UPRICE UPRICE UPRICE UPRICE UPRICE Per unit Price 0 0 COL06_TOTAL COL06_TOTAL COL06_TOTAL COL06_TOTAL COL06_TOTAL Total Price 0 0 TRANS_PRICE TRANS_PRICE TRANS_PRICE TRANS_PRICE TRANS_PRICE transportation Cost 0 0 GTOTAL GTOTAL GTOTAL GTOTAL GTOTAL Total other expenditure cost. 0 0 0 0 1 Census 2 Sample 3 Institutional 0 0