Nepal Fishery Survey 2015

Nepal, 2015 - 2016
Agriculture, Forestry and Fisheries

Central Bureau of Statistics

CSV JSON

DIST (DIST)

Data file: CAPITAL_EXP

Overview

Valid: 3168

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	3	0.1%
2	Panchthar	3	0.1%
3	Ilam	7	0.2%
4	Jhapa	59	1.9%
5	Morang	122	3.9%
6	Sunsari	182	5.7%
7	Dhankuta	5	0.2%
8	Terhathum	9	0.3%
9	Sankhuwasabha	16	0.5%
10	Bhojpur	17	0.5%
11	Solukhumbu	1	0%
12	Okhaldhunga	3	0.1%
13	Khotang	17	0.5%
14	Udayapur	21	0.7%
15	Saptari	121	3.8%
16	Siraha	166	5.2%
17	Dhanusa	33	1%
18	Mahottari	150	4.7%
19	Sarlahi	168	5.3%
20	Sindhuli	19	0.6%
21	Ramechhap	6	0.2%
22	Dolakha	9	0.3%
23	Sindhupalchok	38	1.2%
24	Kavre	44	1.4%
25	Lalitpur	8	0.3%
26	Bhaktapur	3	0.1%
27	Kathmandu	13	0.4%
28	Nuwakot	65	2.1%
29	Rasuwa	2	0.1%
30	Dhading	35	1.1%
31	Makwanpur	28	0.9%
32	Rautahat	140	4.4%
33	Bara	243	7.7%
34	Parsa	156	4.9%
35	Chitawan	104	3.3%
36	Gorkha	33	1%
37	Lamjung	15	0.5%
38	Tanahu	53	1.7%
39	Syangja	34	1.1%
40	Kaski	106	3.3%
41	Manang	0	0%
42	Mustang	0	0%
43	Myagdi	18	0.6%
44	Parbat	19	0.6%
45	Baglung	34	1.1%
46	Gulmi	8	0.3%
47	Palpa	21	0.7%
48	Nawalparasi	99	3.1%
49	Rupandehi	126	4%
50	Kapilbastu	65	2.1%
51	Arghakhanchi	17	0.5%
52	Pyuthan	11	0.3%
53	Rolpa	11	0.3%
54	Rukum	27	0.9%
55	Salyan	18	0.6%
56	Dang	60	1.9%
57	Banke	69	2.2%
58	Bardiya	145	4.6%
59	Surkhet	16	0.5%
60	Dailekh	21	0.7%
61	Jajarkot	2	0.1%
62	Dolpa	0	0%
63	Jumla	3	0.1%
64	Kalikot	0	0%
65	Mugu	0	0%
66	Humla	0	0%
67	Bajura	3	0.1%
68	Bajhang	0	0%
69	Achham	8	0.3%
70	Doti	0	0%
71	Kailali	51	1.6%
72	Kanchanpur	55	1.7%
73	Dadeldhura	4	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.