Overview

Dataset statistics

Number of variables9
Number of observations1283
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory91.6 KiB
Average record size in memory73.1 B

Variable types

Categorical5
Text3
Numeric1

Dataset

Description2010년 전국 전통시장에 대한 데이터로 전통시장주소, 개설주기, 등록인정여부, 영업점포수, 공동화장실 보유여부, 주자창 보유여부를 제공합니다.
Author소상공인시장진흥공단
URLhttps://www.data.go.kr/data/15102810/fileData.do

Alerts

2010_영업점포 has 13 (1.0%) zerosZeros

Reproduction

Analysis started2023-12-13 00:58:31.361693
Analysis finished2023-12-13 00:58:32.185057
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct16
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
서울
169 
경북
147 
부산
146 
경남
141 
전남
107 
Other values (11)
573 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울 169
13.2%
경북 147
11.5%
부산 146
11.4%
경남 141
11.0%
전남 107
8.3%
경기 103
8.0%
대구 101
7.9%
전북 63
 
4.9%
충남 59
 
4.6%
강원 51
 
4.0%
Other values (6) 196
15.3%

Length

2023-12-13T09:58:32.236157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 169
13.2%
경북 147
11.5%
부산 146
11.4%
경남 141
11.0%
전남 107
8.3%
경기 103
8.0%
대구 101
7.9%
전북 63
 
4.9%
충남 59
 
4.6%
강원 51
 
4.0%
Other values (6) 196
15.3%

구시군
Text

Distinct201
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2023-12-13T09:58:32.492908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8947779
Min length2

Characters and Unicode

Total characters3714
Distinct characters126
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

Unique25 ?
Unique (%)1.9%

Sample

1st row종로구
2nd row종로구
3rd row금천구
4th row종로구
5th row종로구
ValueCountFrequency (%)
중구 67
 
5.2%
남구 45
 
3.5%
동구 45
 
3.5%
서구 34
 
2.7%
창원시 31
 
2.4%
부산진구 28
 
2.2%
포항시 28
 
2.2%
북구 28
 
2.2%
마산시 19
 
1.5%
부천시 19
 
1.5%
Other values (191) 939
73.2%
2023-12-13T09:58:32.872136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 550
 
14.8%
시 473
 
12.7%
군 302
 
8.1%
산 118
 
3.2%
주 116
 
3.1%
동 115
 
3.1%
천 103
 
2.8%
서 80
 
2.2%
남 79
 
2.1%
성 77
 
2.1%
Other values (116) 1701
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3714
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 550
 
14.8%
시 473
 
12.7%
군 302
 
8.1%
산 118
 
3.2%
주 116
 
3.1%
동 115
 
3.1%
천 103
 
2.8%
서 80
 
2.2%
남 79
 
2.1%
성 77
 
2.1%
Other values (116) 1701
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3714
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 550
 
14.8%
시 473
 
12.7%
군 302
 
8.1%
산 118
 
3.2%
주 116
 
3.1%
동 115
 
3.1%
천 103
 
2.8%
서 80
 
2.2%
남 79
 
2.1%
성 77
 
2.1%
Other values (116) 1701
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3714
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 550
 
14.8%
시 473
 
12.7%
군 302
 
8.1%
산 118
 
3.2%
주 116
 
3.1%
동 115
 
3.1%
천 103
 
2.8%
서 80
 
2.2%
남 79
 
2.1%
성 77
 
2.1%
Other values (116) 1701
45.8%

시장명
Text

Distinct1204
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2023-12-13T09:58:33.093745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length5.6250974
Min length3

Characters and Unicode

Total characters7217
Distinct characters341
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

Unique1167 ?
Unique (%)91.0%

Sample

1st row종로광장전통시장
2nd row동대문종합시장
3rd row대명합동시장(대명시장 및 주변상점가)
4th row동대문종합시장D동상가
5th row동문시장
ValueCountFrequency (%)
중앙시장 19
 
1.4%
동부시장 10
 
0.8%
서부시장 5
 
0.4%
역전시장 5
 
0.4%
제일시장 5
 
0.4%
시장 4
 
0.3%
서문시장 4
 
0.3%
골목시장 4
 
0.3%
남부시장 4
 
0.3%
신흥시장 4
 
0.3%
Other values (1214) 1261
95.2%
2023-12-13T09:58:33.422850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1258
 
17.4%
시 1241
 
17.2%
동 129
 
1.8%
산 127
 
1.8%
합 120
 
1.7%
종 117
 
1.6%
상 116
 
1.6%
가 103
 
1.4%
중 99
 
1.4%
일 92
 
1.3%
Other values (331) 3815
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6945
96.2%
Close Punctuation 78
 
1.1%
Open Punctuation 78
 
1.1%
Decimal Number 62
 
0.9%
Space Separator 44
 
0.6%
Other Symbol 4
 
0.1%
Other Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1258
 
18.1%
시 1241
 
17.9%
동 129
 
1.9%
산 127
 
1.8%
합 120
 
1.7%
종 117
 
1.7%
상 116
 
1.7%
가 103
 
1.5%
중 99
 
1.4%
일 92
 
1.3%
Other values (318) 3543
51.0%
Decimal Number
ValueCountFrequency (%)
5 44
71.0%
1 8
 
12.9%
2 5
 
8.1%
3 3
 
4.8%
4 2
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
· 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 78
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6949
96.3%
Common 267
 
3.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1258
 
18.1%
시 1241
 
17.9%
동 129
 
1.9%
산 127
 
1.8%
합 120
 
1.7%
종 117
 
1.7%
상 116
 
1.7%
가 103
 
1.5%
중 99
 
1.4%
일 92
 
1.3%
Other values (319) 3547
51.0%
Common
ValueCountFrequency (%)
) 78
29.2%
( 78
29.2%
5 44
16.5%
44
16.5%
1 8
 
3.0%
2 5
 
1.9%
3 3
 
1.1%
+ 2
 
0.7%
. 2
 
0.7%
4 2
 
0.7%
Latin
ValueCountFrequency (%)
D 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6945
96.2%
ASCII 267
 
3.7%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1258
 
18.1%
시 1241
 
17.9%
동 129
 
1.9%
산 127
 
1.8%
합 120
 
1.7%
종 117
 
1.7%
상 116
 
1.7%
가 103
 
1.5%
중 99
 
1.4%
일 92
 
1.3%
Other values (318) 3543
51.0%
ASCII
ValueCountFrequency (%)
) 78
29.2%
( 78
29.2%
5 44
16.5%
44
16.5%
1 8
 
3.0%
2 5
 
1.9%
3 3
 
1.1%
+ 2
 
0.7%
. 2
 
0.7%
4 2
 
0.7%
None
ValueCountFrequency (%)
㈜ 4
80.0%
· 1
 
20.0%

시장주소
Text

Distinct1279
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2023-12-13T09:58:33.723861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length17.782541
Min length8

Characters and Unicode

Total characters22815
Distinct characters282
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1276 ?
Unique (%)99.5%

Sample

1st row서울 종로구 예지동 6-1
2nd row서울 종로구 종로6가 289-42
3rd row서울 금천구 시흥본동 885-4
4th row서울 종로구 종로6가 270-3
5th row서울 종로구 창신동 437
ValueCountFrequency (%)
서울 169
 
3.0%
경북 147
 
2.6%
부산 146
 
2.6%
경남 141
 
2.5%
전남 107
 
1.9%
대구 100
 
1.8%
경기 89
 
1.6%
중구 68
 
1.2%
전북 63
 
1.1%
충남 59
 
1.0%
Other values (2720) 4610
80.9%
2023-12-13T09:58:34.125039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4466
 
19.6%
1 1182
 
5.2%
동 1038
 
4.5%
- 927
 
4.1%
구 795
 
3.5%
2 741
 
3.2%
3 584
 
2.6%
4 504
 
2.2%
남 484
 
2.1%
시 482
 
2.1%
Other values (272) 11612
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12073
52.9%
Decimal Number 5305
23.3%
Space Separator 4466
 
19.6%
Dash Punctuation 927
 
4.1%
Other Punctuation 39
 
0.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1038
 
8.6%
구 795
 
6.6%
남 484
 
4.0%
시 482
 
4.0%
산 420
 
3.5%
경 420
 
3.5%
리 401
 
3.3%
북 345
 
2.9%
군 310
 
2.6%
서 291
 
2.4%
Other values (254) 7087
58.7%
Decimal Number
ValueCountFrequency (%)
1 1182
22.3%
2 741
14.0%
3 584
11.0%
4 504
9.5%
5 467
 
8.8%
6 415
 
7.8%
7 376
 
7.1%
8 355
 
6.7%
0 343
 
6.5%
9 338
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 19
48.7%
/ 14
35.9%
. 6
 
15.4%
Space Separator
ValueCountFrequency (%)
4466
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 927
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12073
52.9%
Common 10742
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1038
 
8.6%
구 795
 
6.6%
남 484
 
4.0%
시 482
 
4.0%
산 420
 
3.5%
경 420
 
3.5%
리 401
 
3.3%
북 345
 
2.9%
군 310
 
2.6%
서 291
 
2.4%
Other values (254) 7087
58.7%
Common
ValueCountFrequency (%)
4466
41.6%
1 1182
 
11.0%
- 927
 
8.6%
2 741
 
6.9%
3 584
 
5.4%
4 504
 
4.7%
5 467
 
4.3%
6 415
 
3.9%
7 376
 
3.5%
8 355
 
3.3%
Other values (8) 725
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12073
52.9%
ASCII 10742
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4466
41.6%
1 1182
 
11.0%
- 927
 
8.6%
2 741
 
6.9%
3 584
 
5.4%
4 504
 
4.7%
5 467
 
4.3%
6 415
 
3.9%
7 376
 
3.5%
8 355
 
3.3%
Other values (8) 725
 
6.7%
Hangul
ValueCountFrequency (%)
동 1038
 
8.6%
구 795
 
6.6%
남 484
 
4.0%
시 482
 
4.0%
산 420
 
3.5%
경 420
 
3.5%
리 401
 
3.3%
북 345
 
2.9%
군 310
 
2.6%
서 291
 
2.4%
Other values (254) 7087
58.7%

2010_개설주기
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
상설
904 
정기
242 
상설+정기
137 

Length

Max length5
Median length2
Mean length2.3203429
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상설 904
70.5%
정기 242
 
18.9%
상설+정기 137
 
10.7%

Length

2023-12-13T09:58:34.450208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:58:34.525929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상설 904
70.5%
정기 242
 
18.9%
상설+정기 137
 
10.7%

2010_등록_인정 여부
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
등록
816 
인정
467 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
등록 816
63.6%
인정 467
36.4%

Length

2023-12-13T09:58:34.604320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:58:34.673385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록 816
63.6%
인정 467
36.4%

2010_영업점포
Real number (ℝ)

ZEROS 

Distinct323
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.01637
Minimum0
Maximum5200
Zeros13
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-12-13T09:58:34.764430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11
Q131
median65
Q3124
95-th percentile399.6
Maximum5200
Range5200
Interquartile range (IQR)93

Descriptive statistics

Standard deviation259.33892
Coefficient of variation (CV)2.0579781
Kurtosis160.14665
Mean126.01637
Median Absolute Deviation (MAD)40
Skewness10.23986
Sum161679
Variance67256.676
MonotonicityNot monotonic
2023-12-13T09:58:34.871985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60 24
 
1.9%
15 21
 
1.6%
25 20
 
1.6%
12 19
 
1.5%
30 18
 
1.4%
10 17
 
1.3%
40 17
 
1.3%
20 17
 
1.3%
18 16
 
1.2%
56 15
 
1.2%
Other values (313) 1099
85.7%
ValueCountFrequency (%)
0 13
1.0%
2 3
 
0.2%
3 4
 
0.3%
4 3
 
0.2%
5 4
 
0.3%
6 2
 
0.2%
7 3
 
0.2%
8 9
0.7%
9 2
 
0.2%
10 17
1.3%
ValueCountFrequency (%)
5200 1
0.1%
4009 1
0.1%
2025 1
0.1%
1900 1
0.1%
1779 1
0.1%
1479 1
0.1%
1364 1
0.1%
1300 1
0.1%
1204 1
0.1%
1145 1
0.1%

2010_공동화장실 보유여부
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
보유
1102 
미보유
181 

Length

Max length3
Median length2
Mean length2.1410756
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보유 1102
85.9%
미보유 181
 
14.1%

Length

2023-12-13T09:58:34.970783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:58:35.045006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보유 1102
85.9%
미보유 181
 
14.1%

2010_고객 주차장 보유여부
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
보유
649 
미보유
634 

Length

Max length3
Median length2
Mean length2.4941543
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미보유
2nd row보유
3rd row미보유
4th row미보유
5th row미보유

Common Values

ValueCountFrequency (%)
보유 649
50.6%
미보유 634
49.4%

Length

2023-12-13T09:58:35.120668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:58:35.193416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보유 649
50.6%
미보유 634
49.4%

Interactions

2023-12-13T09:58:31.948035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:58:35.240551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도2010_개설주기2010_등록_인정 여부2010_영업점포2010_공동화장실 보유여부2010_고객 주차장 보유여부
시도1.0000.6570.5290.0000.3030.354
2010_개설주기0.6571.0000.1310.0000.0700.094
2010_등록_인정 여부0.5290.1311.0000.0000.5850.176
2010_영업점포0.0000.0000.0001.0000.0000.063
2010_공동화장실 보유여부0.3030.0700.5850.0001.0000.389
2010_고객 주차장 보유여부0.3540.0940.1760.0630.3891.000
2023-12-13T09:58:35.324577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2010_고객 주차장 보유여부2010_등록_인정 여부시도2010_개설주기2010_공동화장실 보유여부
2010_고객 주차장 보유여부1.0000.1120.2770.1550.254
2010_등록_인정 여부0.1121.0000.4160.2170.398
시도0.2770.4161.0000.4610.237
2010_개설주기0.1550.2170.4611.0000.115
2010_공동화장실 보유여부0.2540.3980.2370.1151.000
2023-12-13T09:58:35.404603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2010_영업점포시도2010_개설주기2010_등록_인정 여부2010_공동화장실 보유여부2010_고객 주차장 보유여부
2010_영업점포1.0000.0000.0000.0000.0000.046
시도0.0001.0000.4610.4160.2370.277
2010_개설주기0.0000.4611.0000.2170.1150.155
2010_등록_인정 여부0.0000.4160.2171.0000.3980.112
2010_공동화장실 보유여부0.0000.2370.1150.3981.0000.254
2010_고객 주차장 보유여부0.0460.2770.1550.1120.2541.000

Missing values

2023-12-13T09:58:32.038940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:58:32.142155image/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

시도구시군시장명시장주소2010_개설주기2010_등록_인정 여부2010_영업점포2010_공동화장실 보유여부2010_고객 주차장 보유여부
0서울종로구종로광장전통시장서울 종로구 예지동 6-1상설등록1204보유미보유
1서울종로구동대문종합시장서울 종로구 종로6가 289-42상설등록4009보유보유
2서울금천구대명합동시장(대명시장 및 주변상점가)서울 금천구 시흥본동 885-4상설등록120보유미보유
3서울종로구동대문종합시장D동상가서울 종로구 종로6가 270-3상설등록1145보유미보유
4서울종로구동문시장서울 종로구 창신동 437상설등록300보유미보유
5서울종로구신설종합시장서울 종로구 숭인동 206-9상설등록145보유미보유
6서울종로구종로신진시장서울 종로구 종로5가 225-21상설인정56보유미보유
7서울종로구통인시장서울 종로구 통인동 44상설인정76보유미보유
8서울종로구한일상가서울 종로구 종로5가 314-7상설인정230보유보유
9서울중구신중부시장서울 중구 오장동 44-12상설인정256미보유미보유
시도구시군시장명시장주소2010_개설주기2010_등록_인정 여부2010_영업점포2010_공동화장실 보유여부2010_고객 주차장 보유여부
1273서울관악구봉일시장서울 관악구 은천동 951-25상설등록30보유보유
1274서울서초구남부종합시장서울 서초구 방배동 767-1상설등록83보유보유
1275서울서초구양재종합시장서울 서초구 양재동 1-7,8상설등록16보유미보유
1276서울강남구논현종합시장서울 강남구 논현동 227-4상설등록50보유보유
1277서울강동구동서울종합시장서울 강동구 길동 339-1상설등록25보유보유
1278서울강동구양지종합시장서울 강동구 암사동 451-16상설등록43미보유미보유
1279서울영등포구영등포유통상가서울 영등포구 당산동2가 30-2상설등록850보유보유
1280전남장흥군관산시장전남 장흥군 관산읍 옥당리 494-10상설+정기등록44보유보유
1281충남부여군부여5일시장충남 부여군 부여읍 구아리 420정기인정83보유미보유
1282부산사상구르네시떼부산 사상구 괘법동 529-1상설등록1779보유보유