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Nepal Fishery Survey 2015

Nepal, 2015 - 2016
Agriculture, Forestry and Fisheries
Central Bureau of Statistics
Created on July 05, 2018 Last modified July 05, 2018 Page views 86242 Download 2582 Documentation in PDF Metadata DDI/XML JSON
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DIST (DIST)

Data file: AGGREGATED

Overview

Valid: 332
Invalid: 0
Minimum: 2
Maximum: 73
Type: Discrete
Decimal: 0
Width: 2
Range: 1 - 75
Format: Numeric

Questions and instructions

Categories
Value Category Cases
1 Taplejung 0
0%
2 Panchthar 5
1.5%
3 Ilam 3
0.9%
4 Jhapa 6
1.8%
5 Morang 8
2.4%
6 Sunsari 12
3.6%
7 Dhankuta 0
0%
8 Terhathum 1
0.3%
9 Sankhuwasabha 0
0%
10 Bhojpur 0
0%
11 Solukhumbu 0
0%
12 Okhaldhunga 0
0%
13 Khotang 6
1.8%
14 Udayapur 18
5.4%
15 Saptari 13
3.9%
16 Siraha 9
2.7%
17 Dhanusa 1
0.3%
18 Mahottari 0
0%
19 Sarlahi 0
0%
20 Sindhuli 2
0.6%
21 Ramechhap 4
1.2%
22 Dolakha 0
0%
23 Sindhupalchok 0
0%
24 Kavre 2
0.6%
25 Lalitpur 12
3.6%
26 Bhaktapur 1
0.3%
27 Kathmandu 3
0.9%
28 Nuwakot 4
1.2%
29 Rasuwa 0
0%
30 Dhading 7
2.1%
31 Makwanpur 8
2.4%
32 Rautahat 1
0.3%
33 Bara 9
2.7%
34 Parsa 7
2.1%
35 Chitawan 10
3%
36 Gorkha 14
4.2%
37 Lamjung 0
0%
38 Tanahu 11
3.3%
39 Syangja 10
3%
40 Kaski 13
3.9%
41 Manang 0
0%
42 Mustang 0
0%
43 Myagdi 3
0.9%
44 Parbat 7
2.1%
45 Baglung 14
4.2%
46 Gulmi 2
0.6%
47 Palpa 2
0.6%
48 Nawalparasi 14
4.2%
49 Rupandehi 23
6.9%
50 Kapilbastu 7
2.1%
51 Arghakhanchi 11
3.3%
52 Pyuthan 0
0%
53 Rolpa 0
0%
54 Rukum 6
1.8%
55 Salyan 3
0.9%
56 Dang 7
2.1%
57 Banke 9
2.7%
58 Bardiya 1
0.3%
59 Surkhet 7
2.1%
60 Dailekh 0
0%
61 Jajarkot 0
0%
62 Dolpa 0
0%
63 Jumla 0
0%
64 Kalikot 0
0%
65 Mugu 0
0%
66 Humla 0
0%
67 Bajura 0
0%
68 Bajhang 0
0%
69 Achham 1
0.3%
70 Doti 0
0%
71 Kailali 5
1.5%
72 Kanchanpur 9
2.7%
73 Dadeldhura 1
0.3%
74 Baitadi 0
0%
75 Darchula 0
0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.