Nepal Fishery Survey 2015

Nepal, 2015 - 2016
Agriculture, Forestry and Fisheries

Central Bureau of Statistics

CSV JSON

DIST (DIST)

Data file: OTHER_EXP

Overview

Valid: 12781

Invalid: 0

Minimum: 1

Maximum: 73

Type: Discrete

Decimal: 0

Width: 2

Range: 1 - 75

Format: Numeric

Questions and instructions

Categories

Value	Category	Cases
1	Taplejung	5	0%
2	Panchthar	15	0.1%
3	Ilam	33	0.3%
4	Jhapa	411	3.2%
5	Morang	708	5.5%
6	Sunsari	468	3.7%
7	Dhankuta	60	0.5%
8	Terhathum	39	0.3%
9	Sankhuwasabha	58	0.5%
10	Bhojpur	69	0.5%
11	Solukhumbu	3	0%
12	Okhaldhunga	9	0.1%
13	Khotang	65	0.5%
14	Udayapur	170	1.3%
15	Saptari	445	3.5%
16	Siraha	359	2.8%
17	Dhanusa	370	2.9%
18	Mahottari	269	2.1%
19	Sarlahi	340	2.7%
20	Sindhuli	48	0.4%
21	Ramechhap	75	0.6%
22	Dolakha	37	0.3%
23	Sindhupalchok	76	0.6%
24	Kavre	108	0.8%
25	Lalitpur	117	0.9%
26	Bhaktapur	65	0.5%
27	Kathmandu	97	0.8%
28	Nuwakot	207	1.6%
29	Rasuwa	49	0.4%
30	Dhading	210	1.6%
31	Makwanpur	255	2%
32	Rautahat	476	3.7%
33	Bara	670	5.2%
34	Parsa	463	3.6%
35	Chitawan	948	7.4%
36	Gorkha	170	1.3%
37	Lamjung	43	0.3%
38	Tanahu	151	1.2%
39	Syangja	174	1.4%
40	Kaski	250	2%
41	Manang	0	0%
42	Mustang	0	0%
43	Myagdi	87	0.7%
44	Parbat	81	0.6%
45	Baglung	107	0.8%
46	Gulmi	40	0.3%
47	Palpa	79	0.6%
48	Nawalparasi	672	5.3%
49	Rupandehi	743	5.8%
50	Kapilbastu	270	2.1%
51	Arghakhanchi	54	0.4%
52	Pyuthan	45	0.4%
53	Rolpa	26	0.2%
54	Rukum	48	0.4%
55	Salyan	62	0.5%
56	Dang	279	2.2%
57	Banke	269	2.1%
58	Bardiya	498	3.9%
59	Surkhet	83	0.6%
60	Dailekh	61	0.5%
61	Jajarkot	7	0.1%
62	Dolpa	0	0%
63	Jumla	6	0%
64	Kalikot	0	0%
65	Mugu	0	0%
66	Humla	0	0%
67	Bajura	8	0.1%
68	Bajhang	0	0%
69	Achham	11	0.1%
70	Doti	0	0%
71	Kailali	401	3.1%
72	Kanchanpur	247	1.9%
73	Dadeldhura	12	0.1%
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.