Overview

Dataset statistics

Number of variables8
Number of observations7777
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows276
Duplicate rows (%)3.5%
Total size in memory493.8 KiB
Average record size in memory65.0 B

Variable types

Numeric1
Categorical2
Text4
DateTime1

Dataset

Description국립자연휴양림 객실과 야영에 대해 휴양림명, 판매제한구분, 판매제한명, 판매제한시작일, 판매제한종료일 데이터 정보 입니다.
Author산림청 국립자연휴양림관리소
URLhttps://www.data.go.kr/data/15113567/fileData.do

Alerts

Dataset has 276 (3.5%) duplicate rowsDuplicates
휴양림아이디 is highly overall correlated with 휴양림명High correlation
휴양림명 is highly overall correlated with 휴양림아이디High correlation

Reproduction

Analysis started2023-12-12 15:58:48.442012
Analysis finished2023-12-12 15:58:49.736096
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

휴양림아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169.56603
Minimum101
Maximum303
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size68.5 KiB
2023-12-13T00:58:50.140608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile102
Q1111
median183
Q3195
95-th percentile300
Maximum303
Range202
Interquartile range (IQR)84

Descriptive statistics

Standard deviation55.249768
Coefficient of variation (CV)0.32583041
Kurtosis-0.44826604
Mean169.56603
Median Absolute Deviation (MAD)42
Skewness0.41658869
Sum1318715
Variance3052.5368
MonotonicityNot monotonic
2023-12-13T00:58:50.320260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
183 685
 
8.8%
187 413
 
5.3%
107 387
 
5.0%
101 369
 
4.7%
111 310
 
4.0%
182 287
 
3.7%
184 283
 
3.6%
116 233
 
3.0%
195 231
 
3.0%
112 219
 
2.8%
Other values (35) 4360
56.1%
ValueCountFrequency (%)
101 369
4.7%
102 161
2.1%
103 210
2.7%
104 89
 
1.1%
105 202
2.6%
106 182
2.3%
107 387
5.0%
108 113
 
1.5%
109 47
 
0.6%
110 108
 
1.4%
ValueCountFrequency (%)
303 54
 
0.7%
302 55
 
0.7%
301 159
2.0%
300 136
1.7%
245 142
1.8%
244 178
2.3%
243 85
1.1%
242 123
1.6%
224 74
1.0%
223 69
 
0.9%

휴양림명
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
청옥산 자연휴양림
685 
희리산 자연휴양림
 
413
삼봉 자연휴양림
 
387
유명산 자연휴양림
 
369
대관령 자연휴양림
 
310
Other values (40)
5613 

Length

Max length12
Median length9
Mean length8.9033046
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 (%)
청옥산 자연휴양림 685
 
8.8%
희리산 자연휴양림 413
 
5.3%
삼봉 자연휴양림 387
 
5.0%
유명산 자연휴양림 369
 
4.7%
대관령 자연휴양림 310
 
4.0%
칠보산 자연휴양림 287
 
3.7%
검마산 자연휴양림 283
 
3.6%
화천숲속 야영장 233
 
3.0%
운문산 자연휴양림 231
 
3.0%
미천골 자연휴양림 219
 
2.8%
Other values (35) 4360
56.1%

Length

2023-12-13T00:58:50.507488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자연휴양림 7291
47.4%
청옥산 685
 
4.4%
희리산 413
 
2.7%
삼봉 387
 
2.5%
유명산 369
 
2.4%
대관령 310
 
2.0%
칠보산 287
 
1.9%
검마산 283
 
1.8%
화천숲속 233
 
1.5%
야영장 233
 
1.5%
Other values (38) 4904
31.9%

상품아이디
Text

Distinct2757
Distinct (%)35.5%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
2023-12-13T00:58:50.749108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length18.318246
Min length13

Characters and Unicode

Total characters142461
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

Unique547 ?
Unique (%)7.0%

Sample

1st rowG01010200200200187
2nd rowG01010200200200185
3rd rowG01010200200200177
4th rowG01010200200200177
5th rowG01010200200200179
ValueCountFrequency (%)
g01160200500300065 11
 
0.1%
g01160200500300063 11
 
0.1%
g01160200500300068 11
 
0.1%
g01160200500300062 11
 
0.1%
g01160200500300061 11
 
0.1%
g01160200500300067 11
 
0.1%
g01160200500300066 11
 
0.1%
g01160200500300064 11
 
0.1%
g01070100100300092 8
 
0.1%
g01070100100300040 8
 
0.1%
Other values (2747) 7673
98.7%
2023-12-13T00:58:51.133557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72668
51.0%
1 20317
 
14.3%
2 13559
 
9.5%
G 7777
 
5.5%
3 7341
 
5.2%
4 4641
 
3.3%
5 3887
 
2.7%
8 3820
 
2.7%
7 3038
 
2.1%
9 2841
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 134684
94.5%
Uppercase Letter 7777
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72668
54.0%
1 20317
 
15.1%
2 13559
 
10.1%
3 7341
 
5.5%
4 4641
 
3.4%
5 3887
 
2.9%
8 3820
 
2.8%
7 3038
 
2.3%
9 2841
 
2.1%
6 2572
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
G 7777
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 134684
94.5%
Latin 7777
 
5.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72668
54.0%
1 20317
 
15.1%
2 13559
 
10.1%
3 7341
 
5.5%
4 4641
 
3.4%
5 3887
 
2.9%
8 3820
 
2.8%
7 3038
 
2.3%
9 2841
 
2.1%
6 2572
 
1.9%
Latin
ValueCountFrequency (%)
G 7777
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 142461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72668
51.0%
1 20317
 
14.3%
2 13559
 
9.5%
G 7777
 
5.5%
3 7341
 
5.2%
4 4641
 
3.3%
5 3887
 
2.7%
8 3820
 
2.7%
7 3038
 
2.1%
9 2841
 
2.0%

상품명
Text

Distinct1732
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
2023-12-13T00:58:51.509909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length7.7277871
Min length2

Characters and Unicode

Total characters60099
Distinct characters431
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)0.6%

Sample

1st row야영데크(256)
2nd row야영데크(255)
3rd row야영데크(251)
4th row야영데크(251)
5th row야영데크(252)
ValueCountFrequency (%)
1시간 89
 
1.0%
걸어가는)상단 79
 
0.9%
하단 59
 
0.7%
야영데크(103 51
 
0.6%
소나무 51
 
0.6%
야영데크(104 50
 
0.6%
야영데크(101 49
 
0.6%
야영데크(102 49
 
0.6%
야영데크(106 48
 
0.5%
야영데크(105 46
 
0.5%
Other values (1680) 8320
93.6%
2023-12-13T00:58:51.984489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4318
 
7.2%
) 4318
 
7.2%
1 3577
 
6.0%
2 2878
 
4.8%
0 2410
 
4.0%
영 2076
 
3.5%
야 2045
 
3.4%
크 2015
 
3.4%
데 1975
 
3.3%
3 1285
 
2.1%
Other values (421) 33202
55.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34537
57.5%
Decimal Number 12927
 
21.5%
Open Punctuation 4933
 
8.2%
Close Punctuation 4933
 
8.2%
Space Separator 1187
 
2.0%
Connector Punctuation 654
 
1.1%
Uppercase Letter 632
 
1.1%
Dash Punctuation 193
 
0.3%
Lowercase Letter 103
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 2076
 
6.0%
야 2045
 
5.9%
크 2015
 
5.8%
데 1975
 
5.7%
장 1257
 
3.6%
나 1068
 
3.1%
캠 1043
 
3.0%
오 1032
 
3.0%
무 1009
 
2.9%
핑 1002
 
2.9%
Other values (396) 20015
58.0%
Decimal Number
ValueCountFrequency (%)
1 3577
27.7%
2 2878
22.3%
0 2410
18.6%
3 1285
 
9.9%
5 685
 
5.3%
4 663
 
5.1%
6 455
 
3.5%
7 394
 
3.0%
8 307
 
2.4%
9 273
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 179
28.3%
B 142
22.5%
X 116
18.4%
C 103
16.3%
D 68
 
10.8%
E 12
 
1.9%
F 12
 
1.9%
Open Punctuation
ValueCountFrequency (%)
( 4318
87.5%
[ 615
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 4318
87.5%
] 615
 
12.5%
Space Separator
ValueCountFrequency (%)
1187
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 654
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 193
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34537
57.5%
Common 24827
41.3%
Latin 735
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 2076
 
6.0%
야 2045
 
5.9%
크 2015
 
5.8%
데 1975
 
5.7%
장 1257
 
3.6%
나 1068
 
3.1%
캠 1043
 
3.0%
오 1032
 
3.0%
무 1009
 
2.9%
핑 1002
 
2.9%
Other values (396) 20015
58.0%
Common
ValueCountFrequency (%)
( 4318
17.4%
) 4318
17.4%
1 3577
14.4%
2 2878
11.6%
0 2410
9.7%
3 1285
 
5.2%
1187
 
4.8%
5 685
 
2.8%
4 663
 
2.7%
_ 654
 
2.6%
Other values (7) 2852
11.5%
Latin
ValueCountFrequency (%)
A 179
24.4%
B 142
19.3%
X 116
15.8%
C 103
14.0%
x 103
14.0%
D 68
 
9.3%
E 12
 
1.6%
F 12
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34531
57.5%
ASCII 25562
42.5%
Compat Jamo 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4318
16.9%
) 4318
16.9%
1 3577
14.0%
2 2878
11.3%
0 2410
9.4%
3 1285
 
5.0%
1187
 
4.6%
5 685
 
2.7%
4 663
 
2.6%
_ 654
 
2.6%
Other values (15) 3587
14.0%
Hangul
ValueCountFrequency (%)
영 2076
 
6.0%
야 2045
 
5.9%
크 2015
 
5.8%
데 1975
 
5.7%
장 1257
 
3.6%
나 1068
 
3.1%
캠 1043
 
3.0%
오 1032
 
3.0%
무 1009
 
2.9%
핑 1002
 
2.9%
Other values (395) 20009
57.9%
Compat Jamo
ValueCountFrequency (%)
ㅎ 6
100.0%

판매제한구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
천재지변
5165 
보수공사
1427 
동절기폐쇄
975 
기타
 
200
현장보존
 
10

Length

Max length5
Median length4
Mean length4.073936
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
천재지변 5165
66.4%
보수공사 1427
 
18.3%
동절기폐쇄 975
 
12.5%
기타 200
 
2.6%
현장보존 10
 
0.1%

Length

2023-12-13T00:58:52.162215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:58:52.288546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천재지변 5165
66.4%
보수공사 1427
 
18.3%
동절기폐쇄 975
 
12.5%
기타 200
 
2.6%
현장보존 10
 
0.1%

판매제한명
Text

Distinct65
Distinct (%)0.8%
Missing2
Missing (%)< 0.1%
Memory size60.9 KiB
2023-12-13T00:58:52.527895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length4.6810289
Min length2

Characters and Unicode

Total characters36395
Distinct characters155
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.2%

Sample

1st row수리중
2nd row수리중
3rd row수리중
4th row수리중
5th row수리중
ValueCountFrequency (%)
한파특보 1457
14.2%
한파 1308
12.7%
대설한파 1249
12.1%
폐쇄 1021
9.9%
동절기 858
 
8.3%
대설ㆍ한파 732
 
7.1%
수리중 531
 
5.2%
대설 448
 
4.4%
특보 338
 
3.3%
유지보수사업 160
 
1.6%
Other values (85) 2192
21.3%
2023-12-13T00:58:52.879846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 4938
13.6%
파 4892
13.4%
설 2610
 
7.2%
2519
 
6.9%
대 2474
 
6.8%
보 2112
 
5.8%
특 1795
 
4.9%
동 1068
 
2.9%
쇄 1065
 
2.9%
폐 1065
 
2.9%
Other values (145) 11857
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33850
93.0%
Space Separator 2519
 
6.9%
Open Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%
Math Symbol 6
 
< 0.1%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 4938
14.6%
파 4892
14.5%
설 2610
 
7.7%
대 2474
 
7.3%
보 2112
 
6.2%
특 1795
 
5.3%
동 1068
 
3.2%
쇄 1065
 
3.1%
폐 1065
 
3.1%
기 902
 
2.7%
Other values (140) 10929
32.3%
Space Separator
ValueCountFrequency (%)
2519
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%
Decimal Number
ValueCountFrequency (%)
7 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33850
93.0%
Common 2545
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 4938
14.6%
파 4892
14.5%
설 2610
 
7.7%
대 2474
 
7.3%
보 2112
 
6.2%
특 1795
 
5.3%
동 1068
 
3.2%
쇄 1065
 
3.1%
폐 1065
 
3.1%
기 902
 
2.7%
Other values (140) 10929
32.3%
Common
ValueCountFrequency (%)
2519
99.0%
( 7
 
0.3%
) 7
 
0.3%
~ 6
 
0.2%
7 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33118
91.0%
ASCII 2545
 
7.0%
Compat Jamo 732
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 4938
14.9%
파 4892
14.8%
설 2610
 
7.9%
대 2474
 
7.5%
보 2112
 
6.4%
특 1795
 
5.4%
동 1068
 
3.2%
쇄 1065
 
3.2%
폐 1065
 
3.2%
기 902
 
2.7%
Other values (139) 10197
30.8%
ASCII
ValueCountFrequency (%)
2519
99.0%
( 7
 
0.3%
) 7
 
0.3%
~ 6
 
0.2%
7 6
 
0.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 732
100.0%

판매제한시작일자
Date

Distinct109
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
Minimum2009-03-01 00:00:00
Maximum2023-09-23 00:00:00
2023-12-13T00:58:53.012195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:58:53.137680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

판매제한종료일자
Text

Distinct77
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size60.9 KiB
2023-12-13T00:58:53.343038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters77770
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

Unique9 ?
Unique (%)0.1%

Sample

1st row2999-12-31
2nd row2999-12-31
3rd row2999-12-31
4th row2999-12-31
5th row2999-12-31
ValueCountFrequency (%)
2023-01-24 1792
23.0%
2023-01-29 1729
22.2%
2023-01-15 1526
19.6%
2023-03-31 750
9.6%
2999-12-31 539
 
6.9%
2023-04-30 381
 
4.9%
2023-02-15 95
 
1.2%
2023-12-31 78
 
1.0%
2023-06-15 66
 
0.8%
2023-04-27 56
 
0.7%
Other values (67) 765
9.8%
2023-12-13T00:58:53.661485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19598
25.2%
- 15554
20.0%
0 15079
19.4%
3 9875
12.7%
1 9257
11.9%
9 3441
 
4.4%
4 2421
 
3.1%
5 1918
 
2.5%
6 402
 
0.5%
7 171
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62216
80.0%
Dash Punctuation 15554
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19598
31.5%
0 15079
24.2%
3 9875
15.9%
1 9257
14.9%
9 3441
 
5.5%
4 2421
 
3.9%
5 1918
 
3.1%
6 402
 
0.6%
7 171
 
0.3%
8 54
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 15554
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77770
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19598
25.2%
- 15554
20.0%
0 15079
19.4%
3 9875
12.7%
1 9257
11.9%
9 3441
 
4.4%
4 2421
 
3.1%
5 1918
 
2.5%
6 402
 
0.5%
7 171
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19598
25.2%
- 15554
20.0%
0 15079
19.4%
3 9875
12.7%
1 9257
11.9%
9 3441
 
4.4%
4 2421
 
3.1%
5 1918
 
2.5%
6 402
 
0.5%
7 171
 
0.2%

Interactions

2023-12-13T00:58:49.332917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:58:53.750997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴양림아이디휴양림명판매제한구분판매제한명판매제한종료일자
휴양림아이디1.0001.0000.2780.7370.709
휴양림명1.0001.0000.6400.9260.900
판매제한구분0.2780.6401.0000.9790.961
판매제한명0.7370.9260.9791.0000.996
판매제한종료일자0.7090.9000.9610.9961.000
2023-12-13T00:58:53.838488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매제한구분휴양림명
판매제한구분1.0000.335
휴양림명0.3351.000
2023-12-13T00:58:53.916178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴양림아이디휴양림명판매제한구분
휴양림아이디1.0000.9980.174
휴양림명0.9981.0000.335
판매제한구분0.1740.3351.000

Missing values

2023-12-13T00:58:49.515071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:58:49.673007image/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

휴양림아이디휴양림명상품아이디상품명판매제한구분판매제한명판매제한시작일자판매제한종료일자
0101유명산 자연휴양림G01010200200200187야영데크(256)보수공사수리중2011-08-012999-12-31
1101유명산 자연휴양림G01010200200200185야영데크(255)보수공사수리중2011-08-012999-12-31
2101유명산 자연휴양림G01010200200200177야영데크(251)보수공사수리중2011-08-012999-12-31
3101유명산 자연휴양림G01010200200200177야영데크(251)보수공사수리중2011-08-012999-12-31
4101유명산 자연휴양림G01010200200200179야영데크(252)보수공사수리중2011-08-012999-12-31
5101유명산 자연휴양림G01010200200200179야영데크(252)보수공사수리중2011-08-012999-12-31
6101유명산 자연휴양림G01010200200200185야영데크(255)보수공사수리중2011-08-012999-12-31
7101유명산 자연휴양림G01010200200200187야영데크(256)보수공사수리중2011-08-012999-12-31
8101유명산 자연휴양림G01010200200200184야영데크(254)보수공사수리중2011-08-012999-12-31
9101유명산 자연휴양림G01010200200200182야영데크(253)보수공사수리중2011-08-012999-12-31
휴양림아이디휴양림명상품아이디상품명판매제한구분판매제한명판매제한시작일자판매제한종료일자
7767301신시도자연휴양림G03010100101001002000026무녀도천재지변한파특보2023-01-252023-01-29
7768301신시도자연휴양림G03010100201002002000040상현달 202호천재지변한파특보2023-01-252023-01-29
7769301신시도자연휴양림G03010100101001002000025명도천재지변한파특보2023-01-252023-01-29
7770301신시도자연휴양림G03010100201002002000044상현달 303호천재지변한파특보2023-01-252023-01-29
7771301신시도자연휴양림G03010100101001002000021라온천재지변한파특보2023-01-252023-01-29
7772301신시도자연휴양림G03010100201002002000045상현달 304호천재지변한파특보2023-01-252023-01-29
7773301신시도자연휴양림G030101001000019누리천재지변한파특보2023-01-252023-01-29
7774301신시도자연휴양림G03010100201002002000051하현달 106호천재지변한파특보2023-01-252023-01-29
7775301신시도자연휴양림G030101001000018가온천재지변한파특보2023-01-252023-01-29
7776301신시도자연휴양림G03010100201002002000052하현달 201호천재지변한파특보2023-01-252023-01-29

Duplicate rows

Most frequently occurring

휴양림아이디휴양림명상품아이디상품명판매제한구분판매제한명판매제한시작일자판매제한종료일자# duplicates
0101유명산 자연휴양림G01010200200200177야영데크(251)보수공사수리중2011-08-012999-12-312
1101유명산 자연휴양림G01010200200200179야영데크(252)보수공사수리중2011-08-012999-12-312
2101유명산 자연휴양림G01010200200200182야영데크(253)보수공사수리중2011-08-012999-12-312
3101유명산 자연휴양림G01010200200200184야영데크(254)보수공사수리중2011-08-012999-12-312
4101유명산 자연휴양림G01010200200200185야영데크(255)보수공사수리중2011-08-012999-12-312
5101유명산 자연휴양림G01010200200200187야영데크(256)보수공사수리중2011-08-012999-12-312
6102용대 자연휴양림G01020100100200037폐쇄_고로쇠나무보수공사수리중2009-08-012999-12-312
7102용대 자연휴양림G01020100300200062폐쇄_박달나무보수공사수리중2009-06-012999-12-312
8102용대 자연휴양림G01020100300200153폐쇄_층층나무보수공사수리중2009-06-012999-12-312
9102용대 자연휴양림G01020200200200064야영데크(101)보수공사수리중2010-12-012999-12-312