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