Overview

Dataset statistics

Number of variables17
Number of observations2213
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory313.5 KiB
Average record size in memory145.1 B

Variable types

Numeric9
Categorical5
Text2
DateTime1

Dataset

Description사용자들이 숲나들e 사이트에서 관심상품으로 등록된 상품의 상품명, 상품분류, 최소인원, 최대인원, 상품적용시작일, 상품적용종료일, 면적, 단위, 가격정보를 제공합니다.
Author산림청 국립자연휴양림관리소
URLhttps://www.data.go.kr/data/15113703/fileData.do

Alerts

단위 has constant value ""Constant
상품분류 is highly overall correlated with 상위상품분류High correlation
상위상품분류 is highly overall correlated with 관심상품등록인원 and 6 other fieldsHigh correlation
기관아이디 is highly overall correlated with 기관명High correlation
관심상품등록인원 is highly overall correlated with 면적 and 5 other fieldsHigh correlation
최소인원수 is highly overall correlated with 최대인원수High correlation
최대인원수 is highly overall correlated with 최소인원수High correlation
면적 is highly overall correlated with 관심상품등록인원 and 4 other fieldsHigh correlation
비수기평일가격 is highly overall correlated with 관심상품등록인원 and 5 other fieldsHigh correlation
비수기주말가격 is highly overall correlated with 관심상품등록인원 and 5 other fieldsHigh correlation
성수기평일가격 is highly overall correlated with 관심상품등록인원 and 5 other fieldsHigh correlation
성수기주말가격 is highly overall correlated with 관심상품등록인원 and 5 other fieldsHigh correlation
기관명 is highly overall correlated with 기관아이디 and 1 other fieldsHigh correlation
상품적용종료일 is highly imbalanced (84.0%)Imbalance
상품아이디 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:22:18.164104
Analysis finished2023-12-12 04:22:29.731706
Duration11.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기관아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean166.37732
Minimum101
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:29.816336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile101
Q1109
median183
Q3195
95-th percentile300
Maximum303
Range202
Interquartile range (IQR)86

Descriptive statistics

Standard deviation57.383682
Coefficient of variation (CV)0.34490088
Kurtosis-0.54725229
Mean166.37732
Median Absolute Deviation (MAD)61
Skewness0.50929108
Sum368193
Variance3292.887
MonotonicityIncreasing
2023-12-12T13:22:30.018329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
101 153
 
6.9%
183 117
 
5.3%
112 103
 
4.7%
187 95
 
4.3%
103 90
 
4.1%
106 74
 
3.3%
195 69
 
3.1%
107 67
 
3.0%
111 67
 
3.0%
113 64
 
2.9%
Other values (35) 1314
59.4%
ValueCountFrequency (%)
101 153
6.9%
102 35
 
1.6%
103 90
4.1%
104 23
 
1.0%
105 58
 
2.6%
106 74
3.3%
107 67
3.0%
108 53
 
2.4%
109 29
 
1.3%
110 25
 
1.1%
ValueCountFrequency (%)
303 18
 
0.8%
302 16
 
0.7%
301 53
2.4%
300 34
1.5%
245 43
1.9%
244 38
1.7%
243 41
1.9%
242 36
1.6%
224 24
1.1%
223 20
 
0.9%

기관명
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
유명산 자연휴양림
 
153
청옥산 자연휴양림
 
117
미천골 자연휴양림
 
103
희리산 자연휴양림
 
95
산음 자연휴양림
 
90
Other values (40)
1655 

Length

Max length12
Median length9
Mean length8.9367375
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유명산 자연휴양림
2nd row유명산 자연휴양림
3rd row유명산 자연휴양림
4th row유명산 자연휴양림
5th row유명산 자연휴양림

Common Values

ValueCountFrequency (%)
유명산 자연휴양림 153
 
6.9%
청옥산 자연휴양림 117
 
5.3%
미천골 자연휴양림 103
 
4.7%
희리산 자연휴양림 95
 
4.3%
산음 자연휴양림 90
 
4.1%
청태산 자연휴양림 74
 
3.3%
운문산 자연휴양림 69
 
3.1%
삼봉 자연휴양림 67
 
3.0%
대관령 자연휴양림 67
 
3.0%
가리왕산 자연휴양림 64
 
2.9%
Other values (35) 1314
59.4%

Length

2023-12-12T13:22:30.227059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자연휴양림 2091
47.8%
유명산 153
 
3.5%
청옥산 117
 
2.7%
미천골 103
 
2.4%
희리산 95
 
2.2%
산음 90
 
2.1%
청태산 74
 
1.7%
운문산 69
 
1.6%
삼봉 67
 
1.5%
대관령 67
 
1.5%
Other values (38) 1447
33.1%

상품아이디
Text

UNIQUE 

Distinct2213
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
2023-12-12T13:22:30.498033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length18.521916
Min length15

Characters and Unicode

Total characters40989
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2213 ?
Unique (%)100.0%

Sample

1st rowG01010100100200259
2nd rowG01010100100200260
3rd rowG01010100100300053
4th rowG01010100100300054
5th rowG01010100100300061
ValueCountFrequency (%)
g01010100100200259 1
 
< 0.1%
g01920100100300113 1
 
< 0.1%
g01920100100300050 1
 
< 0.1%
g01920100101001003900143 1
 
< 0.1%
g01920100101001003900142 1
 
< 0.1%
g01920100100900118 1
 
< 0.1%
g01920100100300117 1
 
< 0.1%
g01920100100300114 1
 
< 0.1%
g01920100101001003900145 1
 
< 0.1%
g01920100101001003900144 1
 
< 0.1%
Other values (2203) 2203
99.5%
2023-12-12T13:22:30.959673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20936
51.1%
1 5725
 
14.0%
2 4336
 
10.6%
3 2233
 
5.4%
G 2213
 
5.4%
4 1221
 
3.0%
5 1023
 
2.5%
8 942
 
2.3%
9 863
 
2.1%
7 800
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38776
94.6%
Uppercase Letter 2213
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20936
54.0%
1 5725
 
14.8%
2 4336
 
11.2%
3 2233
 
5.8%
4 1221
 
3.1%
5 1023
 
2.6%
8 942
 
2.4%
9 863
 
2.2%
7 800
 
2.1%
6 697
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
G 2213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38776
94.6%
Latin 2213
 
5.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20936
54.0%
1 5725
 
14.8%
2 4336
 
11.2%
3 2233
 
5.8%
4 1221
 
3.1%
5 1023
 
2.6%
8 942
 
2.4%
9 863
 
2.2%
7 800
 
2.1%
6 697
 
1.8%
Latin
ValueCountFrequency (%)
G 2213
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40989
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20936
51.1%
1 5725
 
14.0%
2 4336
 
10.6%
3 2233
 
5.4%
G 2213
 
5.4%
4 1221
 
3.0%
5 1023
 
2.5%
8 942
 
2.3%
9 863
 
2.1%
7 800
 
2.0%

상품명
Text

Distinct1481
Distinct (%)66.9%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
2023-12-12T13:22:31.270978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length7.6927248
Min length2

Characters and Unicode

Total characters17024
Distinct characters425
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1283 ?
Unique (%)58.0%

Sample

1st row오두막A
2nd row오두막B
3rd row뻐꾸기
4th row산까치
5th row소쩍새
ValueCountFrequency (%)
오토캠프장 35
 
1.4%
1시간 26
 
1.0%
야영데크(106 23
 
0.9%
야영데크(104 23
 
0.9%
야영데크(102 23
 
0.9%
야영데크(103 23
 
0.9%
야영데크(101 23
 
0.9%
야영데크(105 21
 
0.8%
걸어가는)상단 21
 
0.8%
야영데크(107 20
 
0.8%
Other values (1442) 2330
90.7%
2023-12-12T13:22:31.733800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 1228
 
7.2%
( 1228
 
7.2%
1 1199
 
7.0%
2 834
 
4.9%
영 779
 
4.6%
야 771
 
4.5%
크 755
 
4.4%
0 753
 
4.4%
데 745
 
4.4%
3 395
 
2.3%
Other values (415) 8337
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9603
56.4%
Decimal Number 3977
23.4%
Close Punctuation 1379
 
8.1%
Open Punctuation 1379
 
8.1%
Space Separator 376
 
2.2%
Uppercase Letter 136
 
0.8%
Connector Punctuation 126
 
0.7%
Dash Punctuation 46
 
0.3%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 779
 
8.1%
야 771
 
8.0%
크 755
 
7.9%
데 745
 
7.8%
나 281
 
2.9%
무 266
 
2.8%
장 263
 
2.7%
호 253
 
2.6%
동 250
 
2.6%
캠 234
 
2.4%
Other values (390) 5006
52.1%
Decimal Number
ValueCountFrequency (%)
1 1199
30.1%
2 834
21.0%
0 753
18.9%
3 395
 
9.9%
4 187
 
4.7%
5 185
 
4.7%
6 135
 
3.4%
7 110
 
2.8%
8 95
 
2.4%
9 84
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 48
35.3%
B 38
27.9%
C 24
17.6%
D 15
 
11.0%
E 4
 
2.9%
F 4
 
2.9%
X 3
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 1228
89.1%
] 151
 
10.9%
Open Punctuation
ValueCountFrequency (%)
( 1228
89.1%
[ 151
 
10.9%
Space Separator
ValueCountFrequency (%)
376
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9603
56.4%
Common 7283
42.8%
Latin 138
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 779
 
8.1%
야 771
 
8.0%
크 755
 
7.9%
데 745
 
7.8%
나 281
 
2.9%
무 266
 
2.8%
장 263
 
2.7%
호 253
 
2.6%
동 250
 
2.6%
캠 234
 
2.4%
Other values (390) 5006
52.1%
Common
ValueCountFrequency (%)
) 1228
16.9%
( 1228
16.9%
1 1199
16.5%
2 834
11.5%
0 753
10.3%
3 395
 
5.4%
376
 
5.2%
4 187
 
2.6%
5 185
 
2.5%
[ 151
 
2.1%
Other values (7) 747
10.3%
Latin
ValueCountFrequency (%)
A 48
34.8%
B 38
27.5%
C 24
17.4%
D 15
 
10.9%
E 4
 
2.9%
F 4
 
2.9%
X 3
 
2.2%
x 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9603
56.4%
ASCII 7421
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 1228
16.5%
( 1228
16.5%
1 1199
16.2%
2 834
11.2%
0 753
10.1%
3 395
 
5.3%
376
 
5.1%
4 187
 
2.5%
5 185
 
2.5%
[ 151
 
2.0%
Other values (15) 885
11.9%
Hangul
ValueCountFrequency (%)
영 779
 
8.1%
야 771
 
8.0%
크 755
 
7.9%
데 745
 
7.8%
나 281
 
2.9%
무 266
 
2.8%
장 263
 
2.7%
호 253
 
2.6%
동 250
 
2.6%
캠 234
 
2.4%
Other values (390) 5006
52.1%

관심상품등록인원
Real number (ℝ)

HIGH CORRELATION 

Distinct147
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.999548
Minimum1
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:31.872818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q113
median32
Q355
95-th percentile95.4
Maximum303
Range302
Interquartile range (IQR)42

Descriptive statistics

Standard deviation31.796731
Coefficient of variation (CV)0.83676603
Kurtosis7.2499255
Mean37.999548
Median Absolute Deviation (MAD)20
Skewness1.8130382
Sum84093
Variance1011.0321
MonotonicityNot monotonic
2023-12-12T13:22:32.052368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 74
 
3.3%
9 68
 
3.1%
10 64
 
2.9%
13 61
 
2.8%
7 57
 
2.6%
12 57
 
2.6%
6 54
 
2.4%
11 52
 
2.3%
14 51
 
2.3%
15 45
 
2.0%
Other values (137) 1630
73.7%
ValueCountFrequency (%)
1 22
 
1.0%
2 10
 
0.5%
3 27
 
1.2%
4 24
 
1.1%
5 38
1.7%
6 54
2.4%
7 57
2.6%
8 74
3.3%
9 68
3.1%
10 64
2.9%
ValueCountFrequency (%)
303 1
< 0.1%
296 2
0.1%
203 1
< 0.1%
195 1
< 0.1%
178 1
< 0.1%
177 1
< 0.1%
171 1
< 0.1%
168 1
< 0.1%
165 1
< 0.1%
159 1
< 0.1%

상품분류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
야영데크
722 
휴양관
563 
숲속의집
350 
연립동
308 
오토캠핑장
193 
Other values (4)
77 

Length

Max length6
Median length5
Mean length3.7333936
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
야영데크 722
32.6%
휴양관 563
25.4%
숲속의집 350
15.8%
연립동 308
13.9%
오토캠핑장 193
 
8.7%
캠핑카야영장 41
 
1.9%
숲속수련장 20
 
0.9%
캐빈 10
 
0.5%
노지야영장 6
 
0.3%

Length

2023-12-12T13:22:32.182682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:22:32.302848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
야영데크 722
32.6%
휴양관 563
25.4%
숲속의집 350
15.8%
연립동 308
13.9%
오토캠핑장 193
 
8.7%
캠핑카야영장 41
 
1.9%
숲속수련장 20
 
0.9%
캐빈 10
 
0.5%
노지야영장 6
 
0.3%

상위상품분류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
숙소
1241 
야영장
972 

Length

Max length3
Median length2
Mean length2.4392228
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙소 1241
56.1%
야영장 972
43.9%

Length

2023-12-12T13:22:32.443800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:22:32.549541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙소 1241
56.1%
야영장 972
43.9%

최소인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4505197
Minimum3
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:32.688516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q14
median5
Q36
95-th percentile8
Maximum64
Range61
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.490473
Coefficient of variation (CV)0.45692395
Kurtosis290.68709
Mean5.4505197
Median Absolute Deviation (MAD)1
Skewness13.972688
Sum12062
Variance6.2024557
MonotonicityNot monotonic
2023-12-12T13:22:32.829743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
6 716
32.4%
5 627
28.3%
4 563
25.4%
8 114
 
5.2%
3 71
 
3.2%
7 58
 
2.6%
10 22
 
1.0%
9 16
 
0.7%
12 10
 
0.5%
11 7
 
0.3%
Other values (8) 9
 
0.4%
ValueCountFrequency (%)
3 71
 
3.2%
4 563
25.4%
5 627
28.3%
6 716
32.4%
7 58
 
2.6%
8 114
 
5.2%
9 16
 
0.7%
10 22
 
1.0%
11 7
 
0.3%
12 10
 
0.5%
ValueCountFrequency (%)
64 1
 
< 0.1%
60 1
 
< 0.1%
50 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
20 1
 
< 0.1%
16 1
 
< 0.1%
14 2
 
0.1%
12 10
0.5%
11 7
0.3%

최대인원수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4505197
Minimum3
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:32.951534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q14
median5
Q36
95-th percentile8
Maximum64
Range61
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.490473
Coefficient of variation (CV)0.45692395
Kurtosis290.68709
Mean5.4505197
Median Absolute Deviation (MAD)1
Skewness13.972688
Sum12062
Variance6.2024557
MonotonicityNot monotonic
2023-12-12T13:22:33.079504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
6 716
32.4%
5 627
28.3%
4 563
25.4%
8 114
 
5.2%
3 71
 
3.2%
7 58
 
2.6%
10 22
 
1.0%
9 16
 
0.7%
12 10
 
0.5%
11 7
 
0.3%
Other values (8) 9
 
0.4%
ValueCountFrequency (%)
3 71
 
3.2%
4 563
25.4%
5 627
28.3%
6 716
32.4%
7 58
 
2.6%
8 114
 
5.2%
9 16
 
0.7%
10 22
 
1.0%
11 7
 
0.3%
12 10
 
0.5%
ValueCountFrequency (%)
64 1
 
< 0.1%
60 1
 
< 0.1%
50 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
20 1
 
< 0.1%
16 1
 
< 0.1%
14 2
 
0.1%
12 10
0.5%
11 7
0.3%

상품적용시작일
Date

Distinct153
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
Minimum2006-01-01 00:00:00
Maximum2023-02-15 00:00:00
2023-12-12T13:22:33.205943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:33.376955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상품적용종료일
Categorical

IMBALANCE 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
2999-12-31
2020 
2099-12-31
 
108
2025-06-08
 
35
2020-04-21
 
21
2087-12-31
 
11
Other values (9)
 
18

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row2999-12-31
2nd row2999-12-31
3rd row2999-12-31
4th row2025-06-08
5th row2999-12-31

Common Values

ValueCountFrequency (%)
2999-12-31 2020
91.3%
2099-12-31 108
 
4.9%
2025-06-08 35
 
1.6%
2020-04-21 21
 
0.9%
2087-12-31 11
 
0.5%
2087-11-30 7
 
0.3%
2019-06-01 2
 
0.1%
2999-12-30 2
 
0.1%
2099-05-16 2
 
0.1%
2019-09-30 1
 
< 0.1%
Other values (4) 4
 
0.2%

Length

2023-12-12T13:22:33.882139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2999-12-31 2020
91.3%
2099-12-31 108
 
4.9%
2025-06-08 35
 
1.6%
2020-04-21 21
 
0.9%
2087-12-31 11
 
0.5%
2087-11-30 7
 
0.3%
2019-06-01 2
 
0.1%
2999-12-30 2
 
0.1%
2099-05-16 2
 
0.1%
2019-09-30 1
 
< 0.1%
Other values (4) 4
 
0.2%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.487122
Minimum4
Maximum899
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:34.025452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q113
median23
Q330
95-th percentile52
Maximum899
Range895
Interquartile range (IQR)17

Descriptive statistics

Standard deviation27.975406
Coefficient of variation (CV)1.0976291
Kurtosis515.09527
Mean25.487122
Median Absolute Deviation (MAD)10
Skewness18.688828
Sum56403
Variance782.62336
MonotonicityNot monotonic
2023-12-12T13:22:34.169540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 544
24.6%
23 142
 
6.4%
10 126
 
5.7%
29 115
 
5.2%
26 97
 
4.4%
30 86
 
3.9%
11 81
 
3.7%
33 63
 
2.8%
19 56
 
2.5%
31 56
 
2.5%
Other values (63) 847
38.3%
ValueCountFrequency (%)
4 24
 
1.1%
7 16
 
0.7%
10 126
 
5.7%
11 81
 
3.7%
12 54
 
2.4%
13 544
24.6%
14 26
 
1.2%
15 26
 
1.2%
16 22
 
1.0%
17 25
 
1.1%
ValueCountFrequency (%)
899 1
 
< 0.1%
591 1
 
< 0.1%
371 1
 
< 0.1%
146 1
 
< 0.1%
138 1
 
< 0.1%
126 1
 
< 0.1%
121 3
0.1%
111 1
 
< 0.1%
109 1
 
< 0.1%
100 3
0.1%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.4 KiB
㎡
2213 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row㎡
2nd row㎡
3rd row㎡
4th row㎡
5th row㎡

Common Values

ValueCountFrequency (%)
㎡ 2213
100.0%

Length

2023-12-12T13:22:34.310364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:22:34.409083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
㎡ 2213
100.0%

비수기평일가격
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41381.383
Minimum10000
Maximum402000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:34.516113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile14000
Q115000
median44000
Q356000
95-th percentile98000
Maximum402000
Range392000
Interquartile range (IQR)41000

Descriptive statistics

Standard deviation30817.509
Coefficient of variation (CV)0.74471917
Kurtosis18.453485
Mean41381.383
Median Absolute Deviation (MAD)29000
Skewness2.5277012
Sum91577000
Variance9.4971886 × 108
MonotonicityNot monotonic
2023-12-12T13:22:34.661346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
15000 493
22.3%
45000 248
11.2%
44000 241
10.9%
75000 203
9.2%
14000 200
9.0%
56000 168
 
7.6%
17000 139
 
6.3%
58000 120
 
5.4%
98000 87
 
3.9%
20000 43
 
1.9%
Other values (21) 271
12.2%
ValueCountFrequency (%)
10000 6
 
0.3%
12000 40
 
1.8%
14000 200
9.0%
15000 493
22.3%
17000 139
 
6.3%
20000 43
 
1.9%
22000 35
 
1.6%
23000 3
 
0.1%
27000 3
 
0.1%
32000 10
 
0.5%
ValueCountFrequency (%)
402000 2
 
0.1%
220000 1
 
< 0.1%
200000 3
 
0.1%
163000 11
 
0.5%
152000 2
 
0.1%
124000 25
 
1.1%
118000 4
 
0.2%
98000 87
3.9%
95000 38
1.7%
87000 2
 
0.1%

비수기주말가격
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68613.647
Minimum11000
Maximum550000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:34.843070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile15500
Q116500
median76000
Q3102000
95-th percentile173000
Maximum550000
Range539000
Interquartile range (IQR)85500

Descriptive statistics

Standard deviation54881.169
Coefficient of variation (CV)0.79985792
Kurtosis5.0246349
Mean68613.647
Median Absolute Deviation (MAD)58000
Skewness1.2908673
Sum1.51842 × 108
Variance3.0119427 × 109
MonotonicityNot monotonic
2023-12-12T13:22:34.985783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
16500 493
22.3%
82000 248
11.2%
76000 241
10.9%
134000 203
9.2%
15500 189
 
8.5%
102000 168
 
7.6%
20000 139
 
6.3%
106000 120
 
5.4%
173000 87
 
3.9%
25000 43
 
1.9%
Other values (23) 282
12.7%
ValueCountFrequency (%)
11000 6
 
0.3%
13000 40
 
1.8%
15000 11
 
0.5%
15500 189
 
8.5%
16500 493
22.3%
20000 139
 
6.3%
25000 43
 
1.9%
35000 35
 
1.6%
38000 3
 
0.1%
40000 10
 
0.5%
ValueCountFrequency (%)
550000 2
 
0.1%
320000 1
 
< 0.1%
260000 1
 
< 0.1%
250000 2
 
0.1%
240000 11
 
0.5%
236000 2
 
0.1%
208000 25
 
1.1%
197000 4
 
0.2%
173000 87
3.9%
162000 38
1.7%

성수기평일가격
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68613.647
Minimum11000
Maximum550000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:35.114916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile15500
Q116500
median76000
Q3102000
95-th percentile173000
Maximum550000
Range539000
Interquartile range (IQR)85500

Descriptive statistics

Standard deviation54881.169
Coefficient of variation (CV)0.79985792
Kurtosis5.0246349
Mean68613.647
Median Absolute Deviation (MAD)58000
Skewness1.2908673
Sum1.51842 × 108
Variance3.0119427 × 109
MonotonicityNot monotonic
2023-12-12T13:22:35.284780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
16500 493
22.3%
82000 248
11.2%
76000 241
10.9%
134000 203
9.2%
15500 189
 
8.5%
102000 168
 
7.6%
20000 139
 
6.3%
106000 120
 
5.4%
173000 87
 
3.9%
25000 43
 
1.9%
Other values (23) 282
12.7%
ValueCountFrequency (%)
11000 6
 
0.3%
13000 40
 
1.8%
15000 11
 
0.5%
15500 189
 
8.5%
16500 493
22.3%
20000 139
 
6.3%
25000 43
 
1.9%
35000 35
 
1.6%
38000 3
 
0.1%
40000 10
 
0.5%
ValueCountFrequency (%)
550000 2
 
0.1%
320000 1
 
< 0.1%
260000 1
 
< 0.1%
250000 2
 
0.1%
240000 11
 
0.5%
236000 2
 
0.1%
208000 25
 
1.1%
197000 4
 
0.2%
173000 87
3.9%
162000 38
1.7%

성수기주말가격
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68613.647
Minimum11000
Maximum550000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.6 KiB
2023-12-12T13:22:35.453521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile15500
Q116500
median76000
Q3102000
95-th percentile173000
Maximum550000
Range539000
Interquartile range (IQR)85500

Descriptive statistics

Standard deviation54881.169
Coefficient of variation (CV)0.79985792
Kurtosis5.0246349
Mean68613.647
Median Absolute Deviation (MAD)58000
Skewness1.2908673
Sum1.51842 × 108
Variance3.0119427 × 109
MonotonicityNot monotonic
2023-12-12T13:22:35.623560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
16500 493
22.3%
82000 248
11.2%
76000 241
10.9%
134000 203
9.2%
15500 189
 
8.5%
102000 168
 
7.6%
20000 139
 
6.3%
106000 120
 
5.4%
173000 87
 
3.9%
25000 43
 
1.9%
Other values (23) 282
12.7%
ValueCountFrequency (%)
11000 6
 
0.3%
13000 40
 
1.8%
15000 11
 
0.5%
15500 189
 
8.5%
16500 493
22.3%
20000 139
 
6.3%
25000 43
 
1.9%
35000 35
 
1.6%
38000 3
 
0.1%
40000 10
 
0.5%
ValueCountFrequency (%)
550000 2
 
0.1%
320000 1
 
< 0.1%
260000 1
 
< 0.1%
250000 2
 
0.1%
240000 11
 
0.5%
236000 2
 
0.1%
208000 25
 
1.1%
197000 4
 
0.2%
173000 87
3.9%
162000 38
1.7%

Interactions

2023-12-12T13:22:28.219031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.279946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.301237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.420821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.428628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.641172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.652856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.731090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.166841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.349757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.391951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.416220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.518493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.557314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.756016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.781331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.253289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.289605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.477257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.492520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.540301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.628462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.670761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.884109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.920733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.382918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.415407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.603816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.611378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.659048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.769660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.792109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.007167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.024343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.531540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.527857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.730611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.721147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.769247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.882640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.942358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.114047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.138817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.656753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.630524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.842171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.825973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.962184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.971103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.084100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.203776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.236585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.752048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.744985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.965997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:19.939863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.093410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.087919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.222972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.311773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.382963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.863151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.891739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:29.085356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.060570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.194088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.196520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.362127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.415619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.522497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:26.958903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.001741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:29.191054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:20.196815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:21.309455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:22.308207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:23.509082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:24.533382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:25.627137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:27.055706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:22:28.115173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:22:35.751524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관아이디기관명관심상품등록인원상품분류상위상품분류최소인원수최대인원수상품적용종료일면적비수기평일가격비수기주말가격성수기평일가격성수기주말가격
기관아이디1.0001.0000.2330.3950.3790.0390.0390.2210.0000.2170.3100.3100.310
기관명1.0001.0000.5660.8190.6170.1830.1830.6640.0680.4980.5750.5750.575
관심상품등록인원0.2330.5661.0000.5680.9450.1500.1500.0950.0000.3740.5370.5370.537
상품분류0.3950.8190.5681.0001.0000.4490.4490.3160.4100.5490.6740.6740.674
상위상품분류0.3790.6170.9451.0001.0000.1710.1710.3400.0000.5430.8980.8980.898
최소인원수0.0390.1830.1500.4490.1711.0001.0000.0000.8550.9060.8600.8600.860
최대인원수0.0390.1830.1500.4490.1711.0001.0000.0000.8550.9060.8600.8600.860
상품적용종료일0.2210.6640.0950.3160.3400.0000.0001.0000.0000.1240.2690.2690.269
면적0.0000.0680.0000.4100.0000.8550.8550.0001.0000.8490.8330.8330.833
비수기평일가격0.2170.4980.3740.5490.5430.9060.9060.1240.8491.0000.9900.9900.990
비수기주말가격0.3100.5750.5370.6740.8980.8600.8600.2690.8330.9901.0001.0001.000
성수기평일가격0.3100.5750.5370.6740.8980.8600.8600.2690.8330.9901.0001.0001.000
성수기주말가격0.3100.5750.5370.6740.8980.8600.8600.2690.8330.9901.0001.0001.000
2023-12-12T13:22:35.931517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관명상품분류상위상품분류상품적용종료일
기관명1.0000.4300.5160.254
상품분류0.4301.0000.9980.138
상위상품분류0.5160.9981.0000.265
상품적용종료일0.2540.1380.2651.000
2023-12-12T13:22:36.075045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기관아이디관심상품등록인원최소인원수최대인원수면적비수기평일가격비수기주말가격성수기평일가격성수기주말가격기관명상품분류상위상품분류상품적용종료일
기관아이디1.0000.062-0.029-0.0290.1720.2330.2330.2330.2330.9920.2060.2840.099
관심상품등록인원0.0621.000-0.131-0.1310.6530.7190.7200.7200.7200.2520.3220.7950.042
최소인원수-0.029-0.1311.0001.0000.2630.1410.1410.1410.1410.0780.2420.1230.000
최대인원수-0.029-0.1311.0001.0000.2630.1410.1410.1410.1410.0780.2420.1230.000
면적0.1720.6530.2630.2631.0000.9150.9140.9140.9140.0290.2510.0000.000
비수기평일가격0.2330.7190.1410.1410.9151.0001.0001.0001.0000.2250.3330.5830.046
비수기주말가격0.2330.7200.1410.1410.9141.0001.0001.0001.0000.2720.4440.9640.102
성수기평일가격0.2330.7200.1410.1410.9141.0001.0001.0001.0000.2720.4440.9640.102
성수기주말가격0.2330.7200.1410.1410.9141.0001.0001.0001.0000.2720.4440.9640.102
기관명0.9920.2520.0780.0780.0290.2250.2720.2720.2721.0000.4300.5160.254
상품분류0.2060.3220.2420.2420.2510.3330.4440.4440.4440.4301.0000.9980.138
상위상품분류0.2840.7950.1230.1230.0000.5830.9640.9640.9640.5160.9981.0000.265
상품적용종료일0.0990.0420.0000.0000.0000.0460.1020.1020.1020.2540.1380.2651.000

Missing values

2023-12-12T13:22:29.350474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:22:29.634445image/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

기관아이디기관명상품아이디상품명관심상품등록인원상품분류상위상품분류최소인원수최대인원수상품적용시작일상품적용종료일면적단위비수기평일가격비수기주말가격성수기평일가격성수기주말가격
0101유명산 자연휴양림G01010100100200259오두막A102숲속의집숙소332016-01-042999-12-3116㎡39000650006500065000
1101유명산 자연휴양림G01010100100200260오두막B74숲속의집숙소332016-01-042999-12-3116㎡39000650006500065000
2101유명산 자연휴양림G01010100100300053뻐꾸기105숲속의집숙소442006-01-012999-12-3123㎡45000820008200082000
3101유명산 자연휴양림G01010100100300054산까치65숲속의집숙소442006-01-012025-06-0826㎡45000820008200082000
4101유명산 자연휴양림G01010100100300061소쩍새56숲속의집숙소442012-03-012999-12-3126㎡45000820008200082000
5101유명산 자연휴양림G01010100100300248종달새61숲속의집숙소442006-01-012999-12-3123㎡45000820008200082000
6101유명산 자연휴양림G01010100100500039꾀꼬리77숲속의집숙소662006-01-012999-12-3139㎡75000134000134000134000
7101유명산 자연휴양림G01010100100500040너구리77숲속의집숙소662006-01-012999-12-3139㎡75000134000134000134000
8101유명산 자연휴양림G01010100100500051비둘기81숲속의집숙소662006-01-012999-12-3139㎡75000134000134000134000
9101유명산 자연휴양림G01010100100500058산토끼72숲속의집숙소662006-01-012999-12-3139㎡75000134000134000134000
기관아이디기관명상품아이디상품명관심상품등록인원상품분류상위상품분류최소인원수최대인원수상품적용시작일상품적용종료일면적단위비수기평일가격비수기주말가격성수기평일가격성수기주말가격
2203303무의도 자연휴양림G030301001000012선갑도3숲속의집숙소552022-05-232099-12-3131㎡58000106000106000106000
2204303무의도 자연휴양림G030301001000013대이작도10숲속의집숙소552022-05-232099-12-3129㎡58000106000106000106000
2205303무의도 자연휴양림G030301001000014소이작도16숲속의집숙소552022-05-232099-12-3129㎡58000106000106000106000
2206303무의도 자연휴양림G03030100301003001000015101호13연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2207303무의도 자연휴양림G03030100301003001000016102호9연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2208303무의도 자연휴양림G03030100301003001000017103호10연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2209303무의도 자연휴양림G03030100301003001000018105호7연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2210303무의도 자연휴양림G03030100301003001000019106호8연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2211303무의도 자연휴양림G03030100301003002000020107호11연립동숙소552022-05-232099-12-3129㎡58000106000106000106000
2212303무의도 자연휴양림G03030100301003002000021108호12연립동숙소552022-05-232099-12-3129㎡58000106000106000106000