Overview

Dataset statistics

Number of variables6
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)38.7%
Total size in memory1.6 KiB
Average record size in memory54.3 B

Variable types

Text4
Numeric2

Dataset

Description충청북도 휴양림시설 현황에 대한 데이터로 휴양림의 명칭, 휴양림 주소, 위도, 경도, 휴양림 전화번호, 관할 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15099285/fileData.do

Alerts

Dataset has 12 (38.7%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 18:01:48.949264
Analysis finished2023-12-12 18:01:50.009864
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

휴양림_명칭
Text

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:01:50.171154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.1290323
Min length7

Characters and Unicode

Total characters252
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row계명산자연휴양림
2nd row문성자연휴양림
3rd row민주지산자연휴양림
4th row박달재자연휴양림
5th row백야자연휴양림
ValueCountFrequency (%)
계명산자연휴양림 2
 
6.5%
문성자연휴양림 2
 
6.5%
장령산자연휴양림 2
 
6.5%
옥화자연휴양림 2
 
6.5%
수레의산자연휴양림 2
 
6.5%
속리산숲체험휴양마을 2
 
6.5%
소선암자연휴양림 2
 
6.5%
소백산자연휴양림 2
 
6.5%
성불산자연휴양림 2
 
6.5%
생거진천자연휴양림 2
 
6.5%
Other values (7) 11
35.5%
2023-12-13T03:01:50.544487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
휴 31
12.3%
양 31
12.3%
자 29
11.5%
연 29
11.5%
림 29
11.5%
산 16
 
6.3%
소 4
 
1.6%
성 4
 
1.6%
백 4
 
1.6%
령 3
 
1.2%
Other values (40) 72
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
휴 31
12.3%
양 31
12.3%
자 29
11.5%
연 29
11.5%
림 29
11.5%
산 16
 
6.3%
소 4
 
1.6%
성 4
 
1.6%
백 4
 
1.6%
령 3
 
1.2%
Other values (40) 72
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
휴 31
12.3%
양 31
12.3%
자 29
11.5%
연 29
11.5%
림 29
11.5%
산 16
 
6.3%
소 4
 
1.6%
성 4
 
1.6%
백 4
 
1.6%
령 3
 
1.2%
Other values (40) 72
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
휴 31
12.3%
양 31
12.3%
자 29
11.5%
연 29
11.5%
림 29
11.5%
산 16
 
6.3%
소 4
 
1.6%
성 4
 
1.6%
백 4
 
1.6%
령 3
 
1.2%
Other values (40) 72
28.6%

휴양림_주소
Text

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:01:50.798445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length22.258065
Min length20

Characters and Unicode

Total characters690
Distinct characters93
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row충청북도 충주시 충주호수로 1170 (종민동)
2nd row충청북도 충주시 노은면 우성1길 191
3rd row충청북도 영동군 용화면 휴양림길 60
4th row충청북도 제천시 백운면 금봉로 228
5th row충청북도 음성군 금왕읍 백야로 461-97
ValueCountFrequency (%)
충청북도 31
 
19.7%
충주시 6
 
3.8%
음성군 4
 
2.5%
단양군 4
 
2.5%
괴산군 3
 
1.9%
보은군 3
 
1.9%
속리산로 3
 
1.9%
종민동 2
 
1.3%
78 2
 
1.3%
영춘면 2
 
1.3%
Other values (53) 97
61.8%
2023-12-13T03:01:51.230467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
18.3%
충 41
 
5.9%
청 33
 
4.8%
북 31
 
4.5%
도 31
 
4.5%
1 29
 
4.2%
면 24
 
3.5%
군 23
 
3.3%
길 17
 
2.5%
로 16
 
2.3%
Other values (83) 319
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
64.2%
Space Separator 126
 
18.3%
Decimal Number 111
 
16.1%
Dash Punctuation 6
 
0.9%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 41
 
9.3%
청 33
 
7.4%
북 31
 
7.0%
도 31
 
7.0%
면 24
 
5.4%
군 23
 
5.2%
길 17
 
3.8%
로 16
 
3.6%
산 13
 
2.9%
시 10
 
2.3%
Other values (69) 204
46.0%
Decimal Number
ValueCountFrequency (%)
1 29
26.1%
0 16
14.4%
5 13
11.7%
8 10
 
9.0%
9 9
 
8.1%
4 8
 
7.2%
7 8
 
7.2%
3 6
 
5.4%
2 6
 
5.4%
6 6
 
5.4%
Space Separator
ValueCountFrequency (%)
126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 443
64.2%
Common 247
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 41
 
9.3%
청 33
 
7.4%
북 31
 
7.0%
도 31
 
7.0%
면 24
 
5.4%
군 23
 
5.2%
길 17
 
3.8%
로 16
 
3.6%
산 13
 
2.9%
시 10
 
2.3%
Other values (69) 204
46.0%
Common
ValueCountFrequency (%)
126
51.0%
1 29
 
11.7%
0 16
 
6.5%
5 13
 
5.3%
8 10
 
4.0%
9 9
 
3.6%
4 8
 
3.2%
7 8
 
3.2%
3 6
 
2.4%
2 6
 
2.4%
Other values (4) 16
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 443
64.2%
ASCII 247
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
51.0%
1 29
 
11.7%
0 16
 
6.5%
5 13
 
5.3%
8 10
 
4.0%
9 9
 
3.6%
4 8
 
3.2%
7 8
 
3.2%
3 6
 
2.4%
2 6
 
2.4%
Other values (4) 16
 
6.5%
Hangul
ValueCountFrequency (%)
충 41
 
9.3%
청 33
 
7.4%
북 31
 
7.0%
도 31
 
7.0%
면 24
 
5.4%
군 23
 
5.2%
길 17
 
3.8%
로 16
 
3.6%
산 13
 
2.9%
시 10
 
2.3%
Other values (69) 204
46.0%

위도
Real number (ℝ)

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.83915
Minimum127.39023
Maximum128.46789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T03:01:51.392793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.39023
5-th percentile127.47161
Q1127.65138
median127.79247
Q3127.99509
95-th percentile128.3901
Maximum128.46789
Range1.0776607
Interquartile range (IQR)0.343703

Descriptive statistics

Standard deviation0.27435932
Coefficient of variation (CV)0.0021461292
Kurtosis0.44388042
Mean127.83915
Median Absolute Deviation (MAD)0.1413514
Skewness0.79975273
Sum3963.0135
Variance0.075273035
MonotonicityNot monotonic
2023-12-13T03:01:51.570302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
127.9950872 2
 
6.5%
128.4678947 2
 
6.5%
127.5529909 2
 
6.5%
127.6943726 2
 
6.5%
127.6513842 2
 
6.5%
127.792472 2
 
6.5%
127.7525206 2
 
6.5%
128.3123141 2
 
6.5%
127.8463 2
 
6.5%
127.390234 2
 
6.5%
Other values (7) 11
35.5%
ValueCountFrequency (%)
127.390234 2
6.5%
127.5529909 2
6.5%
127.6096488 2
6.5%
127.6511206 1
3.2%
127.6513842 2
6.5%
127.6943726 2
6.5%
127.7525206 2
6.5%
127.7858736 1
3.2%
127.792472 2
6.5%
127.8243884 2
6.5%
ValueCountFrequency (%)
128.4678947 2
6.5%
128.3123141 2
6.5%
128.0462421 1
3.2%
128.0457749 2
6.5%
127.9950872 2
6.5%
127.8463 2
6.5%
127.8297473 2
6.5%
127.8243884 2
6.5%
127.792472 2
6.5%
127.7858736 1
3.2%

경도
Real number (ℝ)

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.797109
Minimum36.053133
Maximum37.147064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-13T03:01:51.707289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.053133
5-th percentile36.149427
Q136.598949
median36.923998
Q337.033607
95-th percentile37.104164
Maximum37.147064
Range1.0939307
Interquartile range (IQR)0.43465821

Descriptive statistics

Standard deviation0.31414307
Coefficient of variation (CV)0.008537167
Kurtosis0.3808818
Mean36.797109
Median Absolute Deviation (MAD)0.13252321
Skewness-1.1545425
Sum1140.7104
Variance0.098685866
MonotonicityNot monotonic
2023-12-13T03:01:51.829331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
36.97931666 2
 
6.5%
37.06126424 2
 
6.5%
36.24572109 2
 
6.5%
36.59894867 2
 
6.5%
37.03888889 2
 
6.5%
36.49245442 2
 
6.5%
37.02832486 2
 
6.5%
36.91922041 2
 
6.5%
36.80794799 2
 
6.5%
36.92399781 2
 
6.5%
Other values (7) 11
35.5%
ValueCountFrequency (%)
36.05313318 2
6.5%
36.24572109 2
6.5%
36.49245442 2
6.5%
36.57319231 1
3.2%
36.59894867 2
6.5%
36.70556804 1
3.2%
36.80794799 2
6.5%
36.81234007 1
3.2%
36.91922041 2
6.5%
36.92399781 2
6.5%
ValueCountFrequency (%)
37.14706386 2
6.5%
37.06126424 2
6.5%
37.05652102 2
6.5%
37.03888889 2
6.5%
37.02832486 2
6.5%
36.97931666 2
6.5%
36.95683951 2
6.5%
36.92399781 2
6.5%
36.91922041 2
6.5%
36.81234007 1
3.2%

전화번호
Text

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:01:52.014718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row043-840-7930
2nd row043-870-7910
3rd row043-740-3438
4th row043-652-0910
5th row043-878-2556
ValueCountFrequency (%)
043-840-7930 2
 
6.5%
043-870-7910 2
 
6.5%
043-730-3491 2
 
6.5%
043-270-7381 2
 
6.5%
043-878-2013 2
 
6.5%
043-540-3220 2
 
6.5%
043-422-7839 2
 
6.5%
043-423-3117 2
 
6.5%
043-830-2679 2
 
6.5%
043-539-3552 2
 
6.5%
Other values (7) 11
35.5%
2023-12-13T03:01:52.282093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 63
16.9%
- 62
16.7%
0 61
16.4%
4 49
13.2%
7 30
8.1%
2 26
7.0%
8 24
 
6.5%
9 18
 
4.8%
5 18
 
4.8%
1 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 63
20.3%
0 61
19.7%
4 49
15.8%
7 30
9.7%
2 26
8.4%
8 24
 
7.7%
9 18
 
5.8%
5 18
 
5.8%
1 15
 
4.8%
6 6
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 63
16.9%
- 62
16.7%
0 61
16.4%
4 49
13.2%
7 30
8.1%
2 26
7.0%
8 24
 
6.5%
9 18
 
4.8%
5 18
 
4.8%
1 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 63
16.9%
- 62
16.7%
0 61
16.4%
4 49
13.2%
7 30
8.1%
2 26
7.0%
8 24
 
6.5%
9 18
 
4.8%
5 18
 
4.8%
1 15
 
4.0%

관할
Text

Distinct19
Distinct (%)61.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T03:01:52.458439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length16.064516
Min length12

Characters and Unicode

Total characters498
Distinct characters71
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

Unique7 ?
Unique (%)22.6%

Sample

1st row충청북도 충주시 종민동
2nd row충청북도 충주시 노은면 문성리
3rd row충청북도 영동군 융화면 조동리
4th row충청북도 제천시 백운면 평동리
5th row충청북도 음성군 금황읍 백야리
ValueCountFrequency (%)
충청북도 31
25.2%
충주시 6
 
4.9%
단양군 4
 
3.3%
음성군 3
 
2.4%
보은군 3
 
2.4%
괴산군 3
 
2.4%
미원면 2
 
1.6%
생극면 2
 
1.6%
차곡리 2
 
1.6%
청주시 2
 
1.6%
Other values (37) 65
52.8%
2023-12-13T03:01:52.758418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
19.5%
충 37
 
7.4%
청 33
 
6.6%
도 31
 
6.2%
리 31
 
6.2%
북 31
 
6.2%
면 24
 
4.8%
군 22
 
4.4%
시 10
 
2.0%
산 10
 
2.0%
Other values (61) 172
34.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 401
80.5%
Space Separator 97
 
19.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 37
 
9.2%
청 33
 
8.2%
도 31
 
7.7%
리 31
 
7.7%
북 31
 
7.7%
면 24
 
6.0%
군 22
 
5.5%
시 10
 
2.5%
산 10
 
2.5%
주 8
 
2.0%
Other values (60) 164
40.9%
Space Separator
ValueCountFrequency (%)
97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 401
80.5%
Common 97
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 37
 
9.2%
청 33
 
8.2%
도 31
 
7.7%
리 31
 
7.7%
북 31
 
7.7%
면 24
 
6.0%
군 22
 
5.5%
시 10
 
2.5%
산 10
 
2.5%
주 8
 
2.0%
Other values (60) 164
40.9%
Common
ValueCountFrequency (%)
97
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 401
80.5%
ASCII 97
 
19.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
100.0%
Hangul
ValueCountFrequency (%)
충 37
 
9.2%
청 33
 
8.2%
도 31
 
7.7%
리 31
 
7.7%
북 31
 
7.7%
면 24
 
6.0%
군 22
 
5.5%
시 10
 
2.5%
산 10
 
2.5%
주 8
 
2.0%
Other values (60) 164
40.9%

Interactions

2023-12-13T03:01:49.558380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:01:49.285206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:01:49.660549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:01:49.427971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:01:52.843190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴양림_명칭휴양림_주소위도경도전화번호관할
휴양림_명칭1.0001.0001.0001.0001.0001.000
휴양림_주소1.0001.0001.0001.0001.0001.000
위도1.0001.0001.0000.7991.0001.000
경도1.0001.0000.7991.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
관할1.0001.0001.0001.0001.0001.000
2023-12-13T03:01:52.955261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.345
경도0.3451.000

Missing values

2023-12-13T03:01:49.811130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:01:49.943355image/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

휴양림_명칭휴양림_주소위도경도전화번호관할
0계명산자연휴양림충청북도 충주시 충주호수로 1170 (종민동)127.99508736.979317043-840-7930충청북도 충주시 종민동
1문성자연휴양림충청북도 충주시 노은면 우성1길 191127.75252137.028325043-870-7910충청북도 충주시 노은면 문성리
2민주지산자연휴양림충청북도 영동군 용화면 휴양림길 60127.82438836.053133043-740-3438충청북도 영동군 융화면 조동리
3박달재자연휴양림충청북도 제천시 백운면 금봉로 228128.04577537.147064043-652-0910충청북도 제천시 백운면 평동리
4백야자연휴양림충청북도 음성군 금왕읍 백야로 461-97127.60964936.95684043-878-2556충청북도 음성군 금황읍 백야리
5봉황자연휴양림충청북도 충주시 중앙탑면 수룡봉황길 540127.82974737.056521043-870-7920충청북도 충주시 중앙탑면 봉황리
6생거진천자연휴양림충청북도 진천군 백곡면 명암길 435-135127.39023436.923998043-539-3552충청북도 진천군 백곡면 명암리
7성불산자연휴양림충청북도 괴산군 괴산읍 충민로기곡길 78127.846336.807948043-830-2679충청북도 괴산군 괴산읍 검승리
8소백산자연휴양림충청북도 단양군 영춘면 하리방터길 180128.46789537.061264043-423-3117충청북도 단양군 영춘면 하리
9소선암자연휴양림충청북도 단양군 단성면 대잠2길 15128.31231436.91922043-422-7839충청북도 단양군 단성면 대잠리
휴양림_명칭휴양림_주소위도경도전화번호관할
21성불산자연휴양림충청북도 괴산군 괴산읍 충민로기곡길 78127.846336.807948043-830-2679충청북도 괴산군 괴산읍 검승리
22소백산자연휴양림충청북도 단양군 영춘면 하리방터길 180128.46789537.061264043-423-3117충청북도 단양군 영춘면 하리
23소선암자연휴양림충청북도 단양군 단성면 대잠2길 15128.31231436.91922043-422-7839충청북도 단양군 단성면 대잠리
24속리산숲체험휴양마을충청북도 보은군 속리산면 속리산로 596127.79247236.492454043-540-3220충청북도 보은군 속리산면 갈목리
25수레의산자연휴양림충청북도 음성군 생극면 차생로 310-108127.65138437.038889043-878-2013충청북도 음성군 생극면 차곡리
26옥화자연휴양림충청북도 청주시 상당구 미원면 운암옥화길 140127.69437336.598949043-270-7381충청북도 청주시 상당구 미원면 운암리
27장령산자연휴양림충청북도 옥천군 군서면 장령산로 519127.55299136.245721043-730-3491충청북도 옥천군 군서면 금산리
28조령산자연휴양림충청북도 괴산군 연풍면 새재로 1795128.04624236.81234043-833-7994충청북도 괴산군 연풍면 원풍리
29좌구산자연휴양림충청북도 증평군 증평읍 솟점말길 107127.65112136.705568043-835-4552충청북도 증평군 증평읍 율리
30충북알프스자연휴양림충청북도 보은군 산외면 속리산로 1880127.78587436.573192043-543-1472충청북도 보은군 산외면 장갑리

Duplicate rows

Most frequently occurring

휴양림_명칭휴양림_주소위도경도전화번호관할# duplicates
0계명산자연휴양림충청북도 충주시 충주호수로 1170 (종민동)127.99508736.979317043-840-7930충청북도 충주시 종민동2
1문성자연휴양림충청북도 충주시 노은면 우성1길 191127.75252137.028325043-870-7910충청북도 충주시 노은면 문성리2
2민주지산자연휴양림충청북도 영동군 용화면 휴양림길 60127.82438836.053133043-740-3438충청북도 영동군 융화면 조동리2
3박달재자연휴양림충청북도 제천시 백운면 금봉로 228128.04577537.147064043-652-0910충청북도 제천시 백운면 평동리2
4봉황자연휴양림충청북도 충주시 중앙탑면 수룡봉황길 540127.82974737.056521043-870-7920충청북도 충주시 중앙탑면 봉황리2
5생거진천자연휴양림충청북도 진천군 백곡면 명암길 435-135127.39023436.923998043-539-3552충청북도 진천군 백곡면 명암리2
6성불산자연휴양림충청북도 괴산군 괴산읍 충민로기곡길 78127.846336.807948043-830-2679충청북도 괴산군 괴산읍 검승리2
7소백산자연휴양림충청북도 단양군 영춘면 하리방터길 180128.46789537.061264043-423-3117충청북도 단양군 영춘면 하리2
8소선암자연휴양림충청북도 단양군 단성면 대잠2길 15128.31231436.91922043-422-7839충청북도 단양군 단성면 대잠리2
9수레의산자연휴양림충청북도 음성군 생극면 차생로 310-108127.65138437.038889043-878-2013충청북도 음성군 생극면 차곡리2