Overview

Dataset statistics

Number of variables10
Number of observations45
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory85.9 B

Variable types

Text3
Numeric2
Categorical5

Dataset

Description국립자연휴양림 홈페이지 정보를 제공하며 제공되는 항목은 휴양림명, 휴양림아이디, 관리부서명, 관리부서아이디, 휴양림이 위치한 지역, 홈페이지 주소를 확인할 수 있다.
URLhttps://www.data.go.kr/data/15088226/fileData.do

Alerts

그룹아이디 has constant value ""Constant
그룹명 has constant value ""Constant
관리부서명 is highly overall correlated with 정렬순서 and 2 other fieldsHigh correlation
관리부서아이디 is highly overall correlated with 정렬순서 and 2 other fieldsHigh correlation
정렬순서 is highly overall correlated with 관리부서아이디 and 2 other fieldsHigh correlation
지역 is highly overall correlated with 정렬순서 and 2 other fieldsHigh correlation
휴양림명 has unique valuesUnique
휴양림아이디 has unique valuesUnique
홈페이지주소 has unique valuesUnique
정렬순서 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:36:43.190919
Analysis finished2023-12-12 06:36:44.116500
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

휴양림명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T15:36:44.254763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.9111111
Min length8

Characters and Unicode

Total characters401
Distinct characters76
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row유명산 자연휴양림
2nd row산음 자연휴양림
3rd row중미산 자연휴양림
4th row운악산 자연휴양림
5th row속리산 자연휴양림
ValueCountFrequency (%)
자연휴양림 43
48.3%
화천숲속 1
 
1.1%
야영장 1
 
1.1%
대야산 1
 
1.1%
칠보산 1
 
1.1%
청옥산 1
 
1.1%
검마산 1
 
1.1%
통고산 1
 
1.1%
운문산 1
 
1.1%
신불산 1
 
1.1%
Other values (37) 37
41.6%
2023-12-12T15:36:44.588605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
11.0%
자 44
11.0%
연 44
11.0%
휴 44
11.0%
양 44
11.0%
림 44
11.0%
산 32
 
8.0%
용 4
 
1.0%
운 4
 
1.0%
리 4
 
1.0%
Other values (66) 93
23.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 357
89.0%
Space Separator 44
 
11.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 44
12.3%
연 44
12.3%
휴 44
12.3%
양 44
12.3%
림 44
12.3%
산 32
 
9.0%
용 4
 
1.1%
운 4
 
1.1%
리 4
 
1.1%
대 3
 
0.8%
Other values (65) 90
25.2%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 357
89.0%
Common 44
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 44
12.3%
연 44
12.3%
휴 44
12.3%
양 44
12.3%
림 44
12.3%
산 32
 
9.0%
용 4
 
1.1%
운 4
 
1.1%
리 4
 
1.1%
대 3
 
0.8%
Other values (65) 90
25.2%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 357
89.0%
ASCII 44
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
100.0%
Hangul
ValueCountFrequency (%)
자 44
12.3%
연 44
12.3%
휴 44
12.3%
양 44
12.3%
림 44
12.3%
산 32
 
9.0%
용 4
 
1.1%
운 4
 
1.1%
리 4
 
1.1%
대 3
 
0.8%
Other values (65) 90
25.2%

휴양림아이디
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean179.55556
Minimum101
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:36:44.759083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile103.2
Q1112
median189
Q3220
95-th percentile300.8
Maximum303
Range202
Interquartile range (IQR)108

Descriptive statistics

Standard deviation61.123777
Coefficient of variation (CV)0.34041708
Kurtosis-0.66264025
Mean179.55556
Median Absolute Deviation (MAD)53
Skewness0.32039627
Sum8080
Variance3736.1162
MonotonicityNot monotonic
2023-12-12T15:36:44.902706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
101 1
 
2.2%
181 1
 
2.2%
182 1
 
2.2%
183 1
 
2.2%
184 1
 
2.2%
193 1
 
2.2%
195 1
 
2.2%
105 1
 
2.2%
242 1
 
2.2%
202 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
101 1
2.2%
102 1
2.2%
103 1
2.2%
104 1
2.2%
105 1
2.2%
106 1
2.2%
107 1
2.2%
108 1
2.2%
109 1
2.2%
110 1
2.2%
ValueCountFrequency (%)
303 1
2.2%
302 1
2.2%
301 1
2.2%
300 1
2.2%
245 1
2.2%
244 1
2.2%
243 1
2.2%
242 1
2.2%
224 1
2.2%
223 1
2.2%

관리부서아이디
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
3000002
13 
3000001
11 
3000004
11 
3000003
10 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000001
2nd row3000001
3rd row3000001
4th row3000001
5th row3000001

Common Values

ValueCountFrequency (%)
3000002 13
28.9%
3000001 11
24.4%
3000004 11
24.4%
3000003 10
22.2%

Length

2023-12-12T15:36:45.077457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:45.243136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000002 13
28.9%
3000001 11
24.4%
3000004 11
24.4%
3000003 10
22.2%

관리부서명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
동부지역팀
13 
북부지역팀
11 
서부지역팀
11 
남부지역팀
10 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북부지역팀
2nd row북부지역팀
3rd row북부지역팀
4th row북부지역팀
5th row북부지역팀

Common Values

ValueCountFrequency (%)
동부지역팀 13
28.9%
북부지역팀 11
24.4%
서부지역팀 11
24.4%
남부지역팀 10
22.2%

Length

2023-12-12T15:36:45.391736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:45.522330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동부지역팀 13
28.9%
북부지역팀 11
24.4%
서부지역팀 11
24.4%
남부지역팀 10
22.2%

그룹아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
HYADM
45 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHYADM
2nd rowHYADM
3rd rowHYADM
4th rowHYADM
5th rowHYADM

Common Values

ValueCountFrequency (%)
HYADM 45
100.0%

Length

2023-12-12T15:36:45.635246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:45.733932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
hyadm 45
100.0%

그룹명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
국립자연휴양림
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국립자연휴양림
2nd row국립자연휴양림
3rd row국립자연휴양림
4th row국립자연휴양림
5th row국립자연휴양림

Common Values

ValueCountFrequency (%)
국립자연휴양림 45
100.0%

Length

2023-12-12T15:36:45.843743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:45.958339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국립자연휴양림 45
100.0%

지역
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
강원
13 
인천/경기
6 
대구/경북
6 
부산/경남
5 
전북
5 
Other values (3)
10 

Length

Max length5
Median length2
Mean length3.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천/경기
2nd row인천/경기
3rd row인천/경기
4th row인천/경기
5th row충북

Common Values

ValueCountFrequency (%)
강원 13
28.9%
인천/경기 6
13.3%
대구/경북 6
13.3%
부산/경남 5
 
11.1%
전북 5
 
11.1%
전남 4
 
8.9%
충북 3
 
6.7%
대전/충남 3
 
6.7%

Length

2023-12-12T15:36:46.133448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:46.247718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원 13
28.9%
인천/경기 6
13.3%
대구/경북 6
13.3%
부산/경남 5
 
11.1%
전북 5
 
11.1%
전남 4
 
8.9%
충북 3
 
6.7%
대전/충남 3
 
6.7%

상세지역
Text

Distinct43
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T15:36:46.463528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0666667
Min length2

Characters and Unicode

Total characters138
Distinct characters53
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)91.1%

Sample

1st row가평군
2nd row양평군
3rd row양평군
4th row포천시
5th row보은군
ValueCountFrequency (%)
양평군 2
 
4.3%
인제군 2
 
4.3%
진도군 1
 
2.2%
부안군 1
 
2.2%
영덕군 1
 
2.2%
봉화군 1
 
2.2%
영양군 1
 
2.2%
울진군 1
 
2.2%
청도군 1
 
2.2%
울주군 1
 
2.2%
Other values (34) 34
73.9%
2023-12-12T15:36:46.804160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 32
23.2%
시 13
 
9.4%
양 8
 
5.8%
천 6
 
4.3%
주 5
 
3.6%
평 4
 
2.9%
원 3
 
2.2%
청 3
 
2.2%
진 3
 
2.2%
장 3
 
2.2%
Other values (43) 58
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
99.3%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 32
23.4%
시 13
 
9.5%
양 8
 
5.8%
천 6
 
4.4%
주 5
 
3.6%
평 4
 
2.9%
원 3
 
2.2%
청 3
 
2.2%
진 3
 
2.2%
장 3
 
2.2%
Other values (42) 57
41.6%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 32
23.4%
시 13
 
9.5%
양 8
 
5.8%
천 6
 
4.4%
주 5
 
3.6%
평 4
 
2.9%
원 3
 
2.2%
청 3
 
2.2%
진 3
 
2.2%
장 3
 
2.2%
Other values (42) 57
41.6%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 32
23.4%
시 13
 
9.5%
양 8
 
5.8%
천 6
 
4.4%
주 5
 
3.6%
평 4
 
2.9%
원 3
 
2.2%
청 3
 
2.2%
진 3
 
2.2%
장 3
 
2.2%
Other values (42) 57
41.6%
ASCII
ValueCountFrequency (%)
1
100.0%

홈페이지주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T15:36:47.072171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters1440
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st rowhttp://www.foresttrip.go.kr/0101
2nd rowhttp://www.foresttrip.go.kr/0103
3rd rowhttp://www.foresttrip.go.kr/0108
4th rowhttp://www.foresttrip.go.kr/0224
5th rowhttp://www.foresttrip.go.kr/0115
ValueCountFrequency (%)
http://www.foresttrip.go.kr/0101 1
 
2.2%
http://www.foresttrip.go.kr/0116 1
 
2.2%
http://www.foresttrip.go.kr/0182 1
 
2.2%
http://www.foresttrip.go.kr/0183 1
 
2.2%
http://www.foresttrip.go.kr/0184 1
 
2.2%
http://www.foresttrip.go.kr/0193 1
 
2.2%
http://www.foresttrip.go.kr/0195 1
 
2.2%
http://www.foresttrip.go.kr/0105 1
 
2.2%
http://www.foresttrip.go.kr/0242 1
 
2.2%
http://www.foresttrip.go.kr/0202 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T15:36:47.502712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 180
12.5%
/ 135
 
9.4%
w 135
 
9.4%
. 135
 
9.4%
r 135
 
9.4%
p 90
 
6.2%
o 90
 
6.2%
0 66
 
4.6%
h 45
 
3.1%
k 45
 
3.1%
Other values (15) 384
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 945
65.6%
Other Punctuation 315
 
21.9%
Decimal Number 180
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 180
19.0%
w 135
14.3%
r 135
14.3%
p 90
9.5%
o 90
9.5%
h 45
 
4.8%
k 45
 
4.8%
g 45
 
4.8%
i 45
 
4.8%
s 45
 
4.8%
Other values (2) 90
9.5%
Decimal Number
ValueCountFrequency (%)
0 66
36.7%
1 43
23.9%
2 23
 
12.8%
3 11
 
6.1%
4 10
 
5.6%
8 9
 
5.0%
9 9
 
5.0%
5 4
 
2.2%
6 3
 
1.7%
7 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 135
42.9%
. 135
42.9%
: 45
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 945
65.6%
Common 495
34.4%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 135
27.3%
. 135
27.3%
0 66
13.3%
: 45
 
9.1%
1 43
 
8.7%
2 23
 
4.6%
3 11
 
2.2%
4 10
 
2.0%
8 9
 
1.8%
9 9
 
1.8%
Other values (3) 9
 
1.8%
Latin
ValueCountFrequency (%)
t 180
19.0%
w 135
14.3%
r 135
14.3%
p 90
9.5%
o 90
9.5%
h 45
 
4.8%
k 45
 
4.8%
g 45
 
4.8%
i 45
 
4.8%
s 45
 
4.8%
Other values (2) 90
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 180
12.5%
/ 135
 
9.4%
w 135
 
9.4%
. 135
 
9.4%
r 135
 
9.4%
p 90
 
6.2%
o 90
 
6.2%
0 66
 
4.6%
h 45
 
3.1%
k 45
 
3.1%
Other values (15) 384
26.7%

정렬순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T15:36:47.674131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2023-12-12T15:36:47.835552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

Interactions

2023-12-12T15:36:43.765531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:36:43.585984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:36:43.841619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:36:43.684499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:36:48.262057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴양림명휴양림아이디관리부서아이디관리부서명지역상세지역홈페이지주소정렬순서
휴양림명1.0001.0001.0001.0001.0001.0001.0001.000
휴양림아이디1.0001.0000.6940.6940.6781.0001.0000.493
관리부서아이디1.0000.6941.0001.0000.9971.0001.0000.940
관리부서명1.0000.6941.0001.0000.9971.0001.0000.940
지역1.0000.6780.9970.9971.0001.0001.0000.835
상세지역1.0001.0001.0001.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.000
정렬순서1.0000.4930.9400.9400.8351.0001.0001.000
2023-12-12T15:36:48.416113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역관리부서명관리부서아이디
지역1.0000.8800.880
관리부서명0.8801.0001.000
관리부서아이디0.8801.0001.000
2023-12-12T15:36:48.532002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴양림아이디정렬순서관리부서아이디관리부서명지역
휴양림아이디1.0000.3100.3470.3470.278
정렬순서0.3101.0000.8080.8080.599
관리부서아이디0.3470.8081.0001.0000.880
관리부서명0.3470.8081.0001.0000.880
지역0.2780.5990.8800.8801.000

Missing values

2023-12-12T15:36:43.931590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:36:44.060662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

휴양림명휴양림아이디관리부서아이디관리부서명그룹아이디그룹명지역상세지역홈페이지주소정렬순서
0유명산 자연휴양림1013000001북부지역팀HYADM국립자연휴양림인천/경기가평군http://www.foresttrip.go.kr/01011
1산음 자연휴양림1033000001북부지역팀HYADM국립자연휴양림인천/경기양평군http://www.foresttrip.go.kr/01032
2중미산 자연휴양림1083000001북부지역팀HYADM국립자연휴양림인천/경기양평군http://www.foresttrip.go.kr/01083
3운악산 자연휴양림2243000001북부지역팀HYADM국립자연휴양림인천/경기포천시http://www.foresttrip.go.kr/02244
4속리산 자연휴양림1153000001북부지역팀HYADM국립자연휴양림충북보은군http://www.foresttrip.go.kr/01155
5오서산 자연휴양림1913000001북부지역팀HYADM국립자연휴양림대전/충남보령시http://www.foresttrip.go.kr/01916
6희리산 자연휴양림1873000001북부지역팀HYADM국립자연휴양림대전/충남서천군http://www.foresttrip.go.kr/01877
7용현 자연휴양림2203000001북부지역팀HYADM국립자연휴양림대전/충남서산시http://www.foresttrip.go.kr/02208
8상당산성 자연휴양림3003000001북부지역팀HYADM국립자연휴양림충북청주시 청원구http://www.foresttrip.go.kr/03009
9아세안 자연휴양림1043000001북부지역팀HYADM국립자연휴양림인천/경기양주시http://www.foresttrip.go.kr/010410
휴양림명휴양림아이디관리부서아이디관리부서명그룹아이디그룹명지역상세지역홈페이지주소정렬순서
35덕유산 자연휴양림1413000004서부지역팀HYADM국립자연휴양림전북무주군http://www.foresttrip.go.kr/014136
36운장산 자연휴양림1943000004서부지역팀HYADM국립자연휴양림전북진안군http://www.foresttrip.go.kr/019437
37지리산 자연휴양림1903000004서부지역팀HYADM국립자연휴양림부산/경남함양군http://www.foresttrip.go.kr/019038
38남해편백 자연휴양림1923000004서부지역팀HYADM국립자연휴양림부산/경남남해군http://www.foresttrip.go.kr/019239
39회문산 자연휴양림1883000004서부지역팀HYADM국립자연휴양림전북순창군http://www.foresttrip.go.kr/018840
40천관산 자연휴양림1963000004서부지역팀HYADM국립자연휴양림전남장흥군http://www.foresttrip.go.kr/019641
41낙안민속 자연휴양림2003000004서부지역팀HYADM국립자연휴양림전남순천시http://www.foresttrip.go.kr/020042
42변산 자연휴양림1893000004서부지역팀HYADM국립자연휴양림전북부안군http://www.foresttrip.go.kr/018943
43진도 자연휴양림2013000004서부지역팀HYADM국립자연휴양림전남진도군http://www.foresttrip.go.kr/020144
44신시도자연휴양림3013000004서부지역팀HYADM국립자연휴양림전북군산시http://www.foresttrip.go.kr/030145