Overview

Dataset statistics

Number of variables12
Number of observations57
Missing cells82
Missing cells (%)12.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory102.2 B

Variable types

Numeric3
DateTime2
Categorical6
Text1

Dataset

Description태안군에서 포획한 유해야생동물 중, 야생멧돼지의 포획일자, 포획방법과 위치 자료, 포획 개체 수, 포획한 지점의 지역유형에 대한 자료임
Author충청남도
URLhttps://www.data.go.kr/data/15109314/fileData.do

Alerts

보고일자 has constant value ""Constant
개체 종류 has constant value ""Constant
포획지시도 has constant value ""Constant
포획지시군 has constant value ""Constant
포획개체수 is highly overall correlated with 지역유형High correlation
포획유형 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
지역유형 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
연번 is highly overall correlated with 포획유형 and 1 other fieldsHigh correlation
포획지위도 is highly overall correlated with 지역유형High correlation
포획지경도 is highly overall correlated with 지역유형High correlation
포획개체수 is highly imbalanced (63.3%)Imbalance
보고일자 has 56 (98.2%) missing valuesMissing
포획지위도 has 13 (22.8%) missing valuesMissing
포획지경도 has 13 (22.8%) missing valuesMissing
연번 has unique valuesUnique
포획지상세주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 18:55:20.175103
Analysis finished2024-03-14 18:55:24.285821
Duration4.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4030.2456
Minimum40
Maximum6199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T03:55:24.438539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile275.2
Q11475
median4537
Q35468
95-th percentile6021.2
Maximum6199
Range6159
Interquartile range (IQR)3993

Descriptive statistics

Standard deviation2059.258
Coefficient of variation (CV)0.51095099
Kurtosis-0.71693374
Mean4030.2456
Median Absolute Deviation (MAD)994
Skewness-0.94548014
Sum229724
Variance4240543.5
MonotonicityStrictly increasing
2024-03-15T03:55:24.692906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 1
 
1.8%
5531 1
 
1.8%
4967 1
 
1.8%
4968 1
 
1.8%
5127 1
 
1.8%
5128 1
 
1.8%
5181 1
 
1.8%
5246 1
 
1.8%
5247 1
 
1.8%
5248 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
40 1
1.8%
133 1
1.8%
252 1
1.8%
281 1
1.8%
363 1
1.8%
377 1
1.8%
378 1
1.8%
463 1
1.8%
832 1
1.8%
912 1
1.8%
ValueCountFrequency (%)
6199 1
1.8%
6198 1
1.8%
6022 1
1.8%
6021 1
1.8%
5994 1
1.8%
5976 1
1.8%
5975 1
1.8%
5935 1
1.8%
5934 1
1.8%
5933 1
1.8%

보고일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing56
Missing (%)98.2%
Memory size584.0 B
Minimum2020-04-19 00:00:00
Maximum2020-04-19 00:00:00
2024-03-15T03:55:24.899019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:25.061539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

포획일자
Date

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
Minimum2020-04-19 00:00:00
Maximum2022-03-24 00:00:00
2024-03-15T03:55:25.372909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:25.784514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

개체 종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
멧돼지
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
멧돼지 57
100.0%

Length

2024-03-15T03:55:26.014939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:26.309847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
멧돼지 57
100.0%

포획유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
수렵
42 
총기포획
15 

Length

Max length4
Median length2
Mean length2.5263158
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수렵 42
73.7%
총기포획 15
 
26.3%

Length

2024-03-15T03:55:26.670662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:27.009541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수렵 42
73.7%
총기포획 15
 
26.3%

포획지시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
충청남도
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 57
100.0%

Length

2024-03-15T03:55:27.342905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:27.647042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 57
100.0%

포획지시군
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size584.0 B
태안군
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
태안군 57
100.0%

Length

2024-03-15T03:55:27.840891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:27.998862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태안군 57
100.0%

포획지상세주소
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
2024-03-15T03:55:28.923049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length12.964912
Min length11

Characters and Unicode

Total characters739
Distinct characters68
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row소원면 파도리 1395
2nd row원북면 대기리 산92
3rd row원북면 대기리 산75
4th row소원면 송현리 1174
5th row원북면 장대리산203
ValueCountFrequency (%)
소원면 25
 
14.4%
원북면 20
 
11.5%
태안읍 6
 
3.4%
소근리 6
 
3.4%
송현리 6
 
3.4%
신덕리 4
 
2.3%
반계리 4
 
2.3%
영전리 4
 
2.3%
산후리 3
 
1.7%
동해리 3
 
1.7%
Other values (87) 93
53.4%
2024-03-15T03:55:30.285043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
15.8%
1 56
 
7.6%
면 51
 
6.9%
리 49
 
6.6%
원 48
 
6.5%
- 33
 
4.5%
2 33
 
4.5%
소 32
 
4.3%
산 26
 
3.5%
3 25
 
3.4%
Other values (58) 269
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
49.8%
Decimal Number 220
29.8%
Space Separator 117
 
15.8%
Dash Punctuation 33
 
4.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 51
13.9%
리 49
13.3%
원 48
13.0%
소 32
 
8.7%
산 26
 
7.1%
북 20
 
5.4%
대 9
 
2.4%
안 8
 
2.2%
읍 8
 
2.2%
송 7
 
1.9%
Other values (45) 110
29.9%
Decimal Number
ValueCountFrequency (%)
1 56
25.5%
2 33
15.0%
3 25
11.4%
5 22
 
10.0%
6 21
 
9.5%
4 15
 
6.8%
8 13
 
5.9%
9 13
 
5.9%
0 12
 
5.5%
7 10
 
4.5%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 371
50.2%
Hangul 368
49.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 51
13.9%
리 49
13.3%
원 48
13.0%
소 32
 
8.7%
산 26
 
7.1%
북 20
 
5.4%
대 9
 
2.4%
안 8
 
2.2%
읍 8
 
2.2%
송 7
 
1.9%
Other values (45) 110
29.9%
Common
ValueCountFrequency (%)
117
31.5%
1 56
15.1%
- 33
 
8.9%
2 33
 
8.9%
3 25
 
6.7%
5 22
 
5.9%
6 21
 
5.7%
4 15
 
4.0%
8 13
 
3.5%
9 13
 
3.5%
Other values (3) 23
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 371
50.2%
Hangul 368
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
31.5%
1 56
15.1%
- 33
 
8.9%
2 33
 
8.9%
3 25
 
6.7%
5 22
 
5.9%
6 21
 
5.7%
4 15
 
4.0%
8 13
 
3.5%
9 13
 
3.5%
Other values (3) 23
 
6.2%
Hangul
ValueCountFrequency (%)
면 51
13.9%
리 49
13.3%
원 48
13.0%
소 32
 
8.7%
산 26
 
7.1%
북 20
 
5.4%
대 9
 
2.4%
안 8
 
2.2%
읍 8
 
2.2%
송 7
 
1.9%
Other values (45) 110
29.9%

포획지위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct43
Distinct (%)97.7%
Missing13
Missing (%)22.8%
Infinite0
Infinite (%)0.0%
Mean36.788727
Minimum36.484352
Maximum36.928766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T03:55:30.703420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.484352
5-th percentile36.697309
Q136.781629
median36.793781
Q336.814072
95-th percentile36.891539
Maximum36.928766
Range0.44441373
Interquartile range (IQR)0.032443262

Descriptive statistics

Standard deviation0.071816895
Coefficient of variation (CV)0.0019521441
Kurtosis8.7248247
Mean36.788727
Median Absolute Deviation (MAD)0.018116934
Skewness-2.2666974
Sum1618.704
Variance0.0051576664
MonotonicityNot monotonic
2024-03-15T03:55:31.121512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
36.8137603940733 2
 
3.5%
36.7983716130422 1
 
1.8%
36.768589206663606 1
 
1.8%
36.800034792411104 1
 
1.8%
36.789289078743295 1
 
1.8%
36.8457027124511 1
 
1.8%
36.8987955885208 1
 
1.8%
36.89720425787871 1
 
1.8%
36.7831294053041 1
 
1.8%
36.78415275878989 1
 
1.8%
Other values (33) 33
57.9%
(Missing) 13
 
22.8%
ValueCountFrequency (%)
36.4843524739985 1
1.8%
36.5659173513209 1
1.8%
36.6956157357112 1
1.8%
36.7069044197718 1
1.8%
36.7607852891456 1
1.8%
36.768589206663606 1
1.8%
36.768919843818 1
1.8%
36.7707510235025 1
1.8%
36.7750371929639 1
1.8%
36.77632275870421 1
1.8%
ValueCountFrequency (%)
36.92876620286479 1
1.8%
36.8987955885208 1
1.8%
36.89720425787871 1
1.8%
36.8594329383845 1
1.8%
36.8457027124511 1
1.8%
36.8292234325636 1
1.8%
36.825939123402 1
1.8%
36.8241886386216 1
1.8%
36.8231753370462 1
1.8%
36.820273405688894 1
1.8%

포획지경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct43
Distinct (%)97.7%
Missing13
Missing (%)22.8%
Infinite0
Infinite (%)0.0%
Mean126.23121
Minimum126.11552
Maximum126.36899
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size641.0 B
2024-03-15T03:55:31.520935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.11552
5-th percentile126.16428
Q1126.19426
median126.22318
Q3126.25602
95-th percentile126.33436
Maximum126.36899
Range0.253468
Interquartile range (IQR)0.061758816

Descriptive statistics

Standard deviation0.05577121
Coefficient of variation (CV)0.00044181792
Kurtosis0.10458334
Mean126.23121
Median Absolute Deviation (MAD)0.031354054
Skewness0.61349035
Sum5554.1732
Variance0.0031104278
MonotonicityNot monotonic
2024-03-15T03:55:31.938192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
126.227291118177 2
 
3.5%
126.236248467702 1
 
1.8%
126.194822176884 1
 
1.8%
126.319936541038 1
 
1.8%
126.351485371943 1
 
1.8%
126.210821887134 1
 
1.8%
126.20411250499 1
 
1.8%
126.278115305292 1
 
1.8%
126.314220647149 1
 
1.8%
126.314685849238 1
 
1.8%
Other values (33) 33
57.9%
(Missing) 13
 
22.8%
ValueCountFrequency (%)
126.115524127726 1
1.8%
126.163596083988 1
1.8%
126.164042750298 1
1.8%
126.165605957818 1
1.8%
126.167863033586 1
1.8%
126.169859878583 1
1.8%
126.170603232907 1
1.8%
126.173824329136 1
1.8%
126.186427851154 1
1.8%
126.18688231982 1
1.8%
ValueCountFrequency (%)
126.368992132357 1
1.8%
126.351485371943 1
1.8%
126.336906284117 1
1.8%
126.319936541038 1
1.8%
126.314685849238 1
1.8%
126.314220647149 1
1.8%
126.300820422005 1
1.8%
126.288396246683 1
1.8%
126.278115305292 1
1.8%
126.267922300141 1
1.8%

포획개체수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size584.0 B
1
49 
2
6 
3
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.5%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 49
86.0%
2 6
 
10.5%
3 1
 
1.8%
4 1
 
1.8%

Length

2024-03-15T03:55:32.340352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:32.636172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 49
86.0%
2 6
 
10.5%
3 1
 
1.8%
4 1
 
1.8%

지역유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size584.0 B
그외
41 
<NA>
16 

Length

Max length4
Median length2
Mean length2.5614035
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
그외 41
71.9%
<NA> 16
 
28.1%

Length

2024-03-15T03:55:33.026331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:55:33.283048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그외 41
71.9%
na 16
 
28.1%

Interactions

2024-03-15T03:55:22.108435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:20.629415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:21.384535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:22.359165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:20.894502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:21.631118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:22.595198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:21.137222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:55:21.872580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:55:33.471202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번포획일자포획유형포획지상세주소포획지위도포획지경도포획개체수
연번1.0001.0001.0001.0000.0000.0000.376
포획일자1.0001.0001.0001.0001.0001.0001.000
포획유형1.0001.0001.0001.0000.0000.1420.000
포획지상세주소1.0001.0001.0001.0001.0001.0001.000
포획지위도0.0001.0000.0001.0001.0000.7890.000
포획지경도0.0001.0000.1421.0000.7891.0000.000
포획개체수0.3761.0000.0001.0000.0000.0001.000
2024-03-15T03:55:33.828195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
포획개체수포획유형지역유형
포획개체수1.0000.0001.000
포획유형0.0001.0001.000
지역유형1.0001.0001.000
2024-03-15T03:55:34.086228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번포획지위도포획지경도포획유형포획개체수지역유형
연번1.0000.1140.0940.9630.2431.000
포획지위도0.1141.0000.0970.0000.0001.000
포획지경도0.0940.0971.0000.0690.0001.000
포획유형0.9630.0000.0691.0000.0001.000
포획개체수0.2430.0000.0000.0001.0001.000
지역유형1.0001.0001.0001.0001.0001.000

Missing values

2024-03-15T03:55:23.141667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:55:23.782896image/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.
2024-03-15T03:55:24.151365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번보고일자포획일자개체 종류포획유형포획지시도포획지시군포획지상세주소포획지위도포획지경도포획개체수지역유형
0402020-04-192020-04-19멧돼지총기포획충청남도태안군소원면 파도리 139536.706904126.1155241그외
1133<NA>2020-04-27멧돼지총기포획충청남도태안군원북면 대기리 산9236.798372126.2362481그외
2252<NA>2020-05-18멧돼지총기포획충청남도태안군원북면 대기리 산7536.79463126.2500971그외
3281<NA>2020-05-26멧돼지총기포획충청남도태안군소원면 송현리 117436.794991126.1640431그외
4363<NA>2020-06-16멧돼지총기포획충청남도태안군원북면 장대리산20336.783479126.2257852그외
5377<NA>2020-06-13멧돼지총기포획충청남도태안군소원면 신덕리 산16536.770751126.1925761그외
6378<NA>2020-06-18멧돼지총기포획충청남도태안군소원면 신덕리 123136.789767126.1864281그외
7463<NA>2020-07-03멧돼지총기포획충청남도태안군원북면 대동로 654-7 일원36.825939126.2196481그외
8832<NA>2020-07-28멧돼지총기포획충청남도태안군원북면 장대리 635-2<NA><NA>2그외
9912<NA>2020-07-29멧돼지총기포획충청남도태안군소원면 영전리 산11636.777127126.2205732그외
연번보고일자포획일자개체 종류포획유형포획지시도포획지시군포획지상세주소포획지위도포획지경도포획개체수지역유형
475933<NA>2022-02-11멧돼지수렵충청남도태안군원북면 신두리 산59-1<NA><NA>1그외
485934<NA>2022-02-13멧돼지수렵충청남도태안군소원면 소근리 31536.798456126.202991그외
495935<NA>2022-02-14멧돼지수렵충청남도태안군소원면 송현리 80-136.786475126.1635961그외
505975<NA>2022-02-19멧돼지수렵충청남도태안군소원면 영전리 산127-336.776323126.2272431그외
515976<NA>2022-02-21멧돼지수렵충청남도태안군원북면 장대리 588-636.78601126.2395691그외
525994<NA>2022-02-22멧돼지수렵충청남도태안군소원면 산가이길 149-23<NA><NA>1그외
536021<NA>2022-02-25멧돼지수렵충청남도태안군원북면 방갈리 515-21836.928766126.169861그외
546022<NA>2022-02-26멧돼지수렵충청남도태안군소원면 송현리 산118-136.786946126.1706031그외
556198<NA>2022-03-24멧돼지수렵충청남도태안군소원면 법산리 350-4<NA><NA>1그외
566199<NA>2022-03-24멧돼지수렵충청남도태안군소원면 서해로 862<NA><NA>1그외