Overview

Dataset statistics

Number of variables22
Number of observations1462
Missing cells7250
Missing cells (%)22.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory267.1 KiB
Average record size in memory187.1 B

Variable types

Numeric7
Text5
Categorical5
Unsupported4
Boolean1

Dataset

Description파일 다운로드
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15046/S/1/datasetView.do

Alerts

영업상태명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
위생업종명 has constant value ""Constant
위생업태명 has constant value ""Constant
상세영업상태명 has constant value ""Constant
건물소유구분명 is highly imbalanced (51.8%)Imbalance
도로명전체주소 has 60 (4.1%) missing valuesMissing
폐업일자 has 1462 (100.0%) missing valuesMissing
휴업시작일자 has 1462 (100.0%) missing valuesMissing
휴업종료일자 has 1462 (100.0%) missing valuesMissing
재개업일자 has 1462 (100.0%) missing valuesMissing
소재지면적 has 144 (9.8%) missing valuesMissing
소재지우편번호 has 37 (2.5%) missing valuesMissing
전화번호 has 1100 (75.2%) missing valuesMissing
위치정보(X) has 30 (2.1%) missing valuesMissing
위치정보(Y) has 30 (2.1%) missing valuesMissing
소재지면적 is highly skewed (γ1 = 25.83973187)Skewed
번호 has unique valuesUnique
인허가번호 has unique valuesUnique
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 169 (11.6%) zerosZeros

Reproduction

Analysis started2023-12-11 05:49:41.592445
Analysis finished2023-12-11 05:49:42.482628
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1462
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean731.5
Minimum1
Maximum1462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:42.566690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile74.05
Q1366.25
median731.5
Q31096.75
95-th percentile1388.95
Maximum1462
Range1461
Interquartile range (IQR)730.5

Descriptive statistics

Standard deviation422.18736
Coefficient of variation (CV)0.57715292
Kurtosis-1.2
Mean731.5
Median Absolute Deviation (MAD)365.5
Skewness0
Sum1069453
Variance178242.17
MonotonicityStrictly increasing
2023-12-11T14:49:42.772522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
984 1
 
0.1%
982 1
 
0.1%
981 1
 
0.1%
980 1
 
0.1%
979 1
 
0.1%
978 1
 
0.1%
977 1
 
0.1%
976 1
 
0.1%
975 1
 
0.1%
Other values (1452) 1452
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1462 1
0.1%
1461 1
0.1%
1460 1
0.1%
1459 1
0.1%
1458 1
0.1%
1457 1
0.1%
1456 1
0.1%
1455 1
0.1%
1454 1
0.1%
1453 1
0.1%
Distinct1363
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-11T14:49:43.141344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length6.6709986
Min length1

Characters and Unicode

Total characters9753
Distinct characters517
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

Unique1320 ?
Unique (%)90.3%

Sample

1st row영축실업
2nd row개풍빌딩
3rd row서울특별시시설관리공단
4th row한서빌딩
5th row(주)삼일공사
ValueCountFrequency (%)
0 35
 
2.0%
빌딩 33
 
1.9%
업무시설 17
 
1.0%
오피스텔 16
 
0.9%
외1 15
 
0.9%
문래동 12
 
0.7%
11
 
0.6%
주식회사 9
 
0.5%
양평동 9
 
0.5%
외2 8
 
0.5%
Other values (1469) 1593
90.6%
2023-12-11T14:49:43.669323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
403
 
4.1%
371
 
3.8%
300
 
3.1%
231
 
2.4%
204
 
2.1%
192
 
2.0%
180
 
1.8%
) 176
 
1.8%
( 176
 
1.8%
151
 
1.5%
Other values (507) 7369
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8470
86.8%
Decimal Number 319
 
3.3%
Space Separator 300
 
3.1%
Uppercase Letter 229
 
2.3%
Close Punctuation 178
 
1.8%
Open Punctuation 178
 
1.8%
Lowercase Letter 40
 
0.4%
Other Punctuation 26
 
0.3%
Dash Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
403
 
4.8%
371
 
4.4%
231
 
2.7%
204
 
2.4%
192
 
2.3%
180
 
2.1%
151
 
1.8%
147
 
1.7%
146
 
1.7%
122
 
1.4%
Other values (444) 6323
74.7%
Uppercase Letter
ValueCountFrequency (%)
S 26
11.4%
K 25
10.9%
C 24
 
10.5%
T 22
 
9.6%
E 14
 
6.1%
A 12
 
5.2%
B 12
 
5.2%
L 12
 
5.2%
O 10
 
4.4%
G 10
 
4.4%
Other values (15) 62
27.1%
Lowercase Letter
ValueCountFrequency (%)
e 8
20.0%
l 4
10.0%
c 4
10.0%
w 3
 
7.5%
o 3
 
7.5%
a 3
 
7.5%
i 2
 
5.0%
r 2
 
5.0%
s 2
 
5.0%
d 2
 
5.0%
Other values (6) 7
17.5%
Decimal Number
ValueCountFrequency (%)
1 112
35.1%
0 78
24.5%
2 58
18.2%
3 34
 
10.7%
4 13
 
4.1%
5 9
 
2.8%
6 5
 
1.6%
7 4
 
1.3%
9 4
 
1.3%
8 2
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 12
46.2%
/ 5
19.2%
& 4
 
15.4%
. 3
 
11.5%
: 1
 
3.8%
1
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 176
98.9%
] 2
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 176
98.9%
[ 2
 
1.1%
Space Separator
ValueCountFrequency (%)
300
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8470
86.8%
Common 1014
 
10.4%
Latin 269
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
403
 
4.8%
371
 
4.4%
231
 
2.7%
204
 
2.4%
192
 
2.3%
180
 
2.1%
151
 
1.8%
147
 
1.7%
146
 
1.7%
122
 
1.4%
Other values (444) 6323
74.7%
Latin
ValueCountFrequency (%)
S 26
 
9.7%
K 25
 
9.3%
C 24
 
8.9%
T 22
 
8.2%
E 14
 
5.2%
A 12
 
4.5%
B 12
 
4.5%
L 12
 
4.5%
O 10
 
3.7%
G 10
 
3.7%
Other values (31) 102
37.9%
Common
ValueCountFrequency (%)
300
29.6%
) 176
17.4%
( 176
17.4%
1 112
 
11.0%
0 78
 
7.7%
2 58
 
5.7%
3 34
 
3.4%
- 13
 
1.3%
4 13
 
1.3%
, 12
 
1.2%
Other values (12) 42
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8470
86.8%
ASCII 1282
 
13.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
403
 
4.8%
371
 
4.4%
231
 
2.7%
204
 
2.4%
192
 
2.3%
180
 
2.1%
151
 
1.8%
147
 
1.7%
146
 
1.7%
122
 
1.4%
Other values (444) 6323
74.7%
ASCII
ValueCountFrequency (%)
300
23.4%
) 176
13.7%
( 176
13.7%
1 112
 
8.7%
0 78
 
6.1%
2 58
 
4.5%
3 34
 
2.7%
S 26
 
2.0%
K 25
 
2.0%
C 24
 
1.9%
Other values (52) 273
21.3%
None
ValueCountFrequency (%)
1
100.0%
Distinct1400
Distinct (%)95.8%
Missing1
Missing (%)0.1%
Memory size11.6 KiB
2023-12-11T14:49:44.013816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length38
Mean length22.848734
Min length18

Characters and Unicode

Total characters33382
Distinct characters263
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1352 ?
Unique (%)92.5%

Sample

1st row서울특별시 성동구 용답동 235-8번지
2nd row서울특별시 성동구 성수동1가 656-766번지
3rd row서울특별시 성동구 마장동 527-6번지
4th row서울특별시 성동구 성수동2가 315-58번지
5th row서울특별시 성동구 성수동1가 656-282번지
ValueCountFrequency (%)
서울특별시 1461
24.2%
강남구 237
 
3.9%
중구 131
 
2.2%
영등포구 123
 
2.0%
마포구 117
 
1.9%
서초구 113
 
1.9%
역삼동 76
 
1.3%
서초동 76
 
1.3%
종로구 75
 
1.2%
관악구 70
 
1.2%
Other values (1754) 3565
59.0%
2023-12-11T14:49:44.470237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6044
18.1%
1779
 
5.3%
1583
 
4.7%
1580
 
4.7%
1503
 
4.5%
1473
 
4.4%
1470
 
4.4%
1462
 
4.4%
1462
 
4.4%
1461
 
4.4%
Other values (253) 13565
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19856
59.5%
Decimal Number 6105
 
18.3%
Space Separator 6044
 
18.1%
Dash Punctuation 1247
 
3.7%
Close Punctuation 47
 
0.1%
Open Punctuation 47
 
0.1%
Uppercase Letter 30
 
0.1%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1779
 
9.0%
1583
 
8.0%
1580
 
8.0%
1503
 
7.6%
1473
 
7.4%
1470
 
7.4%
1462
 
7.4%
1462
 
7.4%
1461
 
7.4%
341
 
1.7%
Other values (226) 5742
28.9%
Uppercase Letter
ValueCountFrequency (%)
C 8
26.7%
K 5
16.7%
M 3
 
10.0%
E 3
 
10.0%
S 3
 
10.0%
D 2
 
6.7%
B 2
 
6.7%
T 1
 
3.3%
I 1
 
3.3%
P 1
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 1288
21.1%
2 786
12.9%
3 625
10.2%
5 556
9.1%
4 543
8.9%
6 526
8.6%
7 512
 
8.4%
8 429
 
7.0%
0 428
 
7.0%
9 412
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Space Separator
ValueCountFrequency (%)
6044
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1247
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19856
59.5%
Common 13496
40.4%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1779
 
9.0%
1583
 
8.0%
1580
 
8.0%
1503
 
7.6%
1473
 
7.4%
1470
 
7.4%
1462
 
7.4%
1462
 
7.4%
1461
 
7.4%
341
 
1.7%
Other values (226) 5742
28.9%
Common
ValueCountFrequency (%)
6044
44.8%
1 1288
 
9.5%
- 1247
 
9.2%
2 786
 
5.8%
3 625
 
4.6%
5 556
 
4.1%
4 543
 
4.0%
6 526
 
3.9%
7 512
 
3.8%
8 429
 
3.2%
Other values (6) 940
 
7.0%
Latin
ValueCountFrequency (%)
C 8
26.7%
K 5
16.7%
M 3
 
10.0%
E 3
 
10.0%
S 3
 
10.0%
D 2
 
6.7%
B 2
 
6.7%
T 1
 
3.3%
I 1
 
3.3%
P 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19856
59.5%
ASCII 13526
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6044
44.7%
1 1288
 
9.5%
- 1247
 
9.2%
2 786
 
5.8%
3 625
 
4.6%
5 556
 
4.1%
4 543
 
4.0%
6 526
 
3.9%
7 512
 
3.8%
8 429
 
3.2%
Other values (17) 970
 
7.2%
Hangul
ValueCountFrequency (%)
1779
 
9.0%
1583
 
8.0%
1580
 
8.0%
1503
 
7.6%
1473
 
7.4%
1470
 
7.4%
1462
 
7.4%
1462
 
7.4%
1461
 
7.4%
341
 
1.7%
Other values (226) 5742
28.9%

도로명전체주소
Text

MISSING 

Distinct1354
Distinct (%)96.6%
Missing60
Missing (%)4.1%
Memory size11.6 KiB
2023-12-11T14:49:44.780138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length40
Mean length25.07632
Min length20

Characters and Unicode

Total characters35157
Distinct characters329
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1315 ?
Unique (%)93.8%

Sample

1st row서울특별시 성동구 자동차시장1길 85 (용답동)
2nd row서울특별시 성동구 아차산로 38 (성수동1가)
3rd row서울특별시 성동구 청계천로 540 (마장동)
4th row서울특별시 성동구 연무장7길 16 (성수동2가)
5th row서울특별시 성동구 아차산로 33 (성수동1가)
ValueCountFrequency (%)
서울특별시 1402
 
19.8%
강남구 237
 
3.3%
중구 118
 
1.7%
서초구 111
 
1.6%
마포구 110
 
1.6%
영등포구 104
 
1.5%
역삼동 76
 
1.1%
종로구 75
 
1.1%
서초동 74
 
1.0%
관악구 66
 
0.9%
Other values (1521) 4716
66.5%
2023-12-11T14:49:45.211891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5687
 
16.2%
1810
 
5.1%
1658
 
4.7%
1637
 
4.7%
1536
 
4.4%
) 1450
 
4.1%
( 1450
 
4.1%
1438
 
4.1%
1405
 
4.0%
1403
 
4.0%
Other values (319) 15683
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21731
61.8%
Space Separator 5687
 
16.2%
Decimal Number 4619
 
13.1%
Close Punctuation 1450
 
4.1%
Open Punctuation 1450
 
4.1%
Other Punctuation 138
 
0.4%
Dash Punctuation 62
 
0.2%
Uppercase Letter 20
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1810
 
8.3%
1658
 
7.6%
1637
 
7.5%
1536
 
7.1%
1438
 
6.6%
1405
 
6.5%
1403
 
6.5%
1402
 
6.5%
439
 
2.0%
413
 
1.9%
Other values (294) 8590
39.5%
Decimal Number
ValueCountFrequency (%)
1 927
20.1%
2 636
13.8%
3 539
11.7%
4 470
10.2%
5 448
9.7%
6 395
8.6%
7 333
 
7.2%
8 308
 
6.7%
0 305
 
6.6%
9 258
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 6
30.0%
K 5
25.0%
S 3
15.0%
M 1
 
5.0%
I 1
 
5.0%
P 1
 
5.0%
T 1
 
5.0%
E 1
 
5.0%
J 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 137
99.3%
. 1
 
0.7%
Space Separator
ValueCountFrequency (%)
5687
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21731
61.8%
Common 13406
38.1%
Latin 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1810
 
8.3%
1658
 
7.6%
1637
 
7.5%
1536
 
7.1%
1438
 
6.6%
1405
 
6.5%
1403
 
6.5%
1402
 
6.5%
439
 
2.0%
413
 
1.9%
Other values (294) 8590
39.5%
Common
ValueCountFrequency (%)
5687
42.4%
) 1450
 
10.8%
( 1450
 
10.8%
1 927
 
6.9%
2 636
 
4.7%
3 539
 
4.0%
4 470
 
3.5%
5 448
 
3.3%
6 395
 
2.9%
7 333
 
2.5%
Other values (6) 1071
 
8.0%
Latin
ValueCountFrequency (%)
C 6
30.0%
K 5
25.0%
S 3
15.0%
M 1
 
5.0%
I 1
 
5.0%
P 1
 
5.0%
T 1
 
5.0%
E 1
 
5.0%
J 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21731
61.8%
ASCII 13426
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5687
42.4%
) 1450
 
10.8%
( 1450
 
10.8%
1 927
 
6.9%
2 636
 
4.7%
3 539
 
4.0%
4 470
 
3.5%
5 448
 
3.3%
6 395
 
2.9%
7 333
 
2.5%
Other values (15) 1091
 
8.1%
Hangul
ValueCountFrequency (%)
1810
 
8.3%
1658
 
7.6%
1637
 
7.5%
1536
 
7.1%
1438
 
6.6%
1405
 
6.5%
1403
 
6.5%
1402
 
6.5%
439
 
2.0%
413
 
1.9%
Other values (294) 8590
39.5%

인허가일자
Real number (ℝ)

Distinct332
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20065845
Minimum19691226
Maximum20160817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:45.339898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19691226
5-th percentile19950516
Q120070228
median20070604
Q320090210
95-th percentile20140109
Maximum20160817
Range469591
Interquartile range (IQR)19982

Descriptive statistics

Standard deviation57223.186
Coefficient of variation (CV)0.0028517705
Kurtosis8.635558
Mean20065845
Median Absolute Deviation (MAD)9498
Skewness-2.4458209
Sum2.9336266 × 1010
Variance3.274493 × 109
MonotonicityNot monotonic
2023-12-11T14:49:45.471504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070604 128
 
8.8%
20070331 127
 
8.7%
20070417 89
 
6.1%
20090210 87
 
6.0%
20080102 74
 
5.1%
20070102 74
 
5.1%
20070928 60
 
4.1%
20070718 35
 
2.4%
20100401 34
 
2.3%
20070419 30
 
2.1%
Other values (322) 724
49.5%
ValueCountFrequency (%)
19691226 1
0.1%
19730528 1
0.1%
19740302 1
0.1%
19740802 1
0.1%
19760724 1
0.1%
19760817 1
0.1%
19761126 1
0.1%
19770105 1
0.1%
19791220 1
0.1%
19810710 1
0.1%
ValueCountFrequency (%)
20160817 6
0.4%
20160323 1
 
0.1%
20151211 1
 
0.1%
20151120 2
 
0.1%
20150828 1
 
0.1%
20150821 1
 
0.1%
20150729 1
 
0.1%
20150622 1
 
0.1%
20150602 2
 
0.1%
20150508 2
 
0.1%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
운영중
1462 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 1462
100.0%

Length

2023-12-11T14:49:45.587550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:49:45.668988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 1462
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1462
Missing (%)100.0%
Memory size13.0 KiB

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1462
Missing (%)100.0%
Memory size13.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1462
Missing (%)100.0%
Memory size13.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1462
Missing (%)100.0%
Memory size13.0 KiB

소재지면적
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1137
Distinct (%)86.3%
Missing144
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean17658.923
Minimum0
Maximum3793621
Zeros169
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:45.765288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13305.37
median5448.365
Q312765.365
95-th percentile45064.404
Maximum3793621
Range3793621
Interquartile range (IQR)9459.995

Descriptive statistics

Standard deviation120768.91
Coefficient of variation (CV)6.8389734
Kurtosis757.31962
Mean17658.923
Median Absolute Deviation (MAD)3372.35
Skewness25.839732
Sum23274461
Variance1.4585128 × 1010
MonotonicityNot monotonic
2023-12-11T14:49:45.890791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 169
 
11.6%
3246.63 3
 
0.2%
16323.95 2
 
0.1%
12324.0 2
 
0.1%
40480.06 2
 
0.1%
5940.0 2
 
0.1%
4797.0 2
 
0.1%
35136.18 2
 
0.1%
4022.99 2
 
0.1%
46103.44 2
 
0.1%
Other values (1127) 1130
77.3%
(Missing) 144
 
9.8%
ValueCountFrequency (%)
0.0 169
11.6%
324.52 1
 
0.1%
334.53 1
 
0.1%
453.36 1
 
0.1%
900.0 1
 
0.1%
1297.07 1
 
0.1%
1734.24 1
 
0.1%
2007.82 1
 
0.1%
2014.99 1
 
0.1%
2015.89 1
 
0.1%
ValueCountFrequency (%)
3793621.0 1
0.1%
1660439.0 1
0.1%
1073868.0 1
0.1%
672042.0 1
0.1%
471154.0 1
0.1%
186022.95 1
0.1%
184421.71 1
0.1%
181014.93 1
0.1%
168050.01 1
0.1%
166429.08 1
0.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct715
Distinct (%)50.2%
Missing37
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean134675.7
Minimum100011
Maximum158887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:46.024803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100011
5-th percentile100400
Q1122809
median135910
Q3150105
95-th percentile157837.6
Maximum158887
Range58876
Interquartile range (IQR)27296

Descriptive statistics

Standard deviation16330.316
Coefficient of variation (CV)0.12125659
Kurtosis-0.32297645
Mean134675.7
Median Absolute Deviation (MAD)14056
Skewness-0.61163538
Sum1.9191288 × 108
Variance2.6667922 × 108
MonotonicityNot monotonic
2023-12-11T14:49:46.147756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
157805 13
 
0.9%
150096 11
 
0.8%
157930 11
 
0.8%
135882 10
 
0.7%
150833 10
 
0.7%
121807 9
 
0.6%
152842 9
 
0.6%
137872 9
 
0.6%
158050 9
 
0.6%
135845 8
 
0.5%
Other values (705) 1326
90.7%
(Missing) 37
 
2.5%
ValueCountFrequency (%)
100011 2
0.1%
100013 2
0.1%
100015 1
 
0.1%
100021 4
0.3%
100031 1
 
0.1%
100032 3
0.2%
100043 1
 
0.1%
100052 1
 
0.1%
100053 1
 
0.1%
100070 3
0.2%
ValueCountFrequency (%)
158887 1
 
0.1%
158885 8
0.5%
158884 3
 
0.2%
158879 1
 
0.1%
158878 1
 
0.1%
158877 2
 
0.1%
158876 1
 
0.1%
158872 1
 
0.1%
158865 1
 
0.1%
158860 2
 
0.1%

건물소유구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
<NA>
1170 
자가
282 
임대
 
10

Length

Max length4
Median length4
Mean length3.6005472
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1170
80.0%
자가 282
 
19.3%
임대 10
 
0.7%

Length

2023-12-11T14:49:46.282573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:49:46.385437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1170
80.0%
자가 282
 
19.3%
임대 10
 
0.7%

년도
Real number (ℝ)

Distinct40
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.6443
Minimum1969
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:46.482039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1969
5-th percentile1995
Q12007
median2007
Q32009
95-th percentile2014
Maximum2016
Range47
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.6670722
Coefficient of variation (CV)0.0028241538
Kurtosis9.9892914
Mean2006.6443
Median Absolute Deviation (MAD)1
Skewness-2.6223575
Sum2933714
Variance32.115707
MonotonicityNot monotonic
2023-12-11T14:49:46.597407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2007 688
47.1%
2009 114
 
7.8%
2008 112
 
7.7%
2010 94
 
6.4%
2011 87
 
6.0%
2015 55
 
3.8%
2004 38
 
2.6%
2001 35
 
2.4%
2014 28
 
1.9%
2013 20
 
1.4%
Other values (30) 191
 
13.1%
ValueCountFrequency (%)
1969 1
 
0.1%
1973 1
 
0.1%
1974 4
0.3%
1976 3
0.2%
1981 1
 
0.1%
1982 3
0.2%
1983 2
 
0.1%
1984 7
0.5%
1985 5
0.3%
1986 3
0.2%
ValueCountFrequency (%)
2016 7
 
0.5%
2015 55
 
3.8%
2014 28
 
1.9%
2013 20
 
1.4%
2012 12
 
0.8%
2011 87
 
6.0%
2010 94
 
6.4%
2009 114
 
7.8%
2008 112
 
7.7%
2007 688
47.1%

다중이용업소여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
False
1462 
ValueCountFrequency (%)
False 1462
100.0%
2023-12-11T14:49:46.808247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위생업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
공중이용시설
1462 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공중이용시설 1462
100.0%

Length

2023-12-11T14:49:46.985638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:49:47.123794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공중이용시설 1462
100.0%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
업무시설
1462 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
업무시설 1462
100.0%

Length

2023-12-11T14:49:47.226153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:49:47.325726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업무시설 1462
100.0%

전화번호
Text

MISSING 

Distinct356
Distinct (%)98.3%
Missing1100
Missing (%)75.2%
Memory size11.6 KiB
2023-12-11T14:49:47.597092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.696133
Min length7

Characters and Unicode

Total characters3872
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

Unique350 ?
Unique (%)96.7%

Sample

1st row0222132321
2nd row02 4992275
3rd row0222906185
4th row02 4625151
5th row02 4611911
ValueCountFrequency (%)
02 225
32.6%
776 4
 
0.6%
732 4
 
0.6%
733 3
 
0.4%
708 3
 
0.4%
7266343 2
 
0.3%
725 2
 
0.3%
763 2
 
0.3%
730 2
 
0.3%
450 2
 
0.3%
Other values (426) 441
63.9%
2023-12-11T14:49:48.031358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 737
19.0%
0 655
16.9%
491
12.7%
3 331
8.5%
1 322
8.3%
7 261
 
6.7%
6 234
 
6.0%
4 229
 
5.9%
5 207
 
5.3%
8 205
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3381
87.3%
Space Separator 491
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 737
21.8%
0 655
19.4%
3 331
9.8%
1 322
9.5%
7 261
 
7.7%
6 234
 
6.9%
4 229
 
6.8%
5 207
 
6.1%
8 205
 
6.1%
9 200
 
5.9%
Space Separator
ValueCountFrequency (%)
491
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3872
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 737
19.0%
0 655
16.9%
491
12.7%
3 331
8.5%
1 322
8.3%
7 261
 
6.7%
6 234
 
6.0%
4 229
 
5.9%
5 207
 
5.3%
8 205
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 737
19.0%
0 655
16.9%
491
12.7%
3 331
8.5%
1 322
8.3%
7 261
 
6.7%
6 234
 
6.0%
4 229
 
5.9%
5 207
 
5.3%
8 205
 
5.3%

위치정보(X)
Real number (ℝ)

MISSING 

Distinct1363
Distinct (%)95.2%
Missing30
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean198743.91
Minimum182835.61
Maximum215493.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:48.198302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182835.61
5-th percentile188007.45
Q1193411.57
median199053.53
Q3203875.01
95-th percentile207328.16
Maximum215493.08
Range32657.477
Interquartile range (IQR)10463.443

Descriptive statistics

Standard deviation6331.1873
Coefficient of variation (CV)0.031856006
Kurtosis-0.79657795
Mean198743.91
Median Absolute Deviation (MAD)5198.98
Skewness-0.21922458
Sum2.8460128 × 108
Variance40083932
MonotonicityNot monotonic
2023-12-11T14:49:48.708307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190591.096947 5
 
0.3%
190689.184769 4
 
0.3%
190246.459845 4
 
0.3%
190155.934915 4
 
0.3%
190176.974214 4
 
0.3%
197047.479192 3
 
0.2%
197672.213474 3
 
0.2%
190980.751902 3
 
0.2%
211169.456172 2
 
0.1%
191082.007569 2
 
0.1%
Other values (1353) 1398
95.6%
(Missing) 30
 
2.1%
ValueCountFrequency (%)
182835.607635 1
0.1%
183007.782214 1
0.1%
183048.977863 1
0.1%
183111.063873 1
0.1%
183352.836788 1
0.1%
183410.44583 1
0.1%
183440.48499 1
0.1%
184906.025453 1
0.1%
185042.586039 1
0.1%
185679.0 1
0.1%
ValueCountFrequency (%)
215493.084318 1
0.1%
215356.306654 1
0.1%
212795.20742 1
0.1%
212719.182336 1
0.1%
212673.839004 1
0.1%
212480.049998 1
0.1%
212439.756611 1
0.1%
212292.034565 1
0.1%
212167.637923 1
0.1%
212051.812883 1
0.1%

위치정보(Y)
Real number (ℝ)

MISSING 

Distinct1363
Distinct (%)95.2%
Missing30
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean448903.66
Minimum438480.3
Maximum464517.67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.0 KiB
2023-12-11T14:49:48.841393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438480.3
5-th percentile442272.32
Q1444826.85
median448502.8
Q3451653.18
95-th percentile460605.21
Maximum464517.67
Range26037.363
Interquartile range (IQR)6826.3282

Descriptive statistics

Standard deviation5130.3502
Coefficient of variation (CV)0.011428622
Kurtosis0.37498996
Mean448903.66
Median Absolute Deviation (MAD)3327.1389
Skewness0.78979993
Sum6.4283004 × 108
Variance26320493
MonotonicityNot monotonic
2023-12-11T14:49:48.977193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445250.903907 5
 
0.3%
448914.532275 4
 
0.3%
447524.6848 4
 
0.3%
446511.559361 4
 
0.3%
446620.479275 4
 
0.3%
450629.318487 3
 
0.2%
451336.718396 3
 
0.2%
446555.908192 3
 
0.2%
447690.068998 2
 
0.1%
442929.676337 2
 
0.1%
Other values (1353) 1398
95.6%
(Missing) 30
 
2.1%
ValueCountFrequency (%)
438480.304856 1
0.1%
438616.739663 1
0.1%
438744.21858 1
0.1%
438847.401864 1
0.1%
438889.795679 1
0.1%
439400.366475 1
0.1%
439516.337797 1
0.1%
439717.621202 1
0.1%
439814.465835 1
0.1%
440024.356719 1
0.1%
ValueCountFrequency (%)
464517.668032 1
0.1%
464504.48986 1
0.1%
464385.978294 1
0.1%
464269.521956 1
0.1%
464194.123664 1
0.1%
464077.693186 1
0.1%
463891.35961 1
0.1%
463337.202863 1
0.1%
463272.572489 1
0.1%
463230.733127 1
0.1%

인허가번호
Text

UNIQUE 

Distinct1462
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
2023-12-11T14:49:49.162282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters32164
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

Unique1462 ?
Unique (%)100.0%

Sample

1st row3030000-210-2001-00070
2nd row3030000-210-2001-00073
3rd row3030000-210-2001-00075
4th row3030000-210-2001-00077
5th row3030000-210-2001-00079
ValueCountFrequency (%)
3030000-210-2001-00070 1
 
0.1%
3180000-210-2007-00526 1
 
0.1%
3180000-210-2007-00523 1
 
0.1%
3180000-210-2007-00522 1
 
0.1%
3180000-210-2007-00521 1
 
0.1%
3180000-210-2007-00520 1
 
0.1%
3180000-210-2007-00519 1
 
0.1%
3180000-210-2007-00518 1
 
0.1%
3180000-210-2007-00517 1
 
0.1%
3180000-210-2007-00516 1
 
0.1%
Other values (1452) 1452
99.3%
2023-12-11T14:49:49.515493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14858
46.2%
- 4386
 
13.6%
2 3977
 
12.4%
1 3480
 
10.8%
3 2036
 
6.3%
7 994
 
3.1%
9 613
 
1.9%
5 517
 
1.6%
8 492
 
1.5%
4 435
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27778
86.4%
Dash Punctuation 4386
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14858
53.5%
2 3977
 
14.3%
1 3480
 
12.5%
3 2036
 
7.3%
7 994
 
3.6%
9 613
 
2.2%
5 517
 
1.9%
8 492
 
1.8%
4 435
 
1.6%
6 376
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 4386
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32164
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14858
46.2%
- 4386
 
13.6%
2 3977
 
12.4%
1 3480
 
10.8%
3 2036
 
6.3%
7 994
 
3.1%
9 613
 
1.9%
5 517
 
1.6%
8 492
 
1.5%
4 435
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14858
46.2%
- 4386
 
13.6%
2 3977
 
12.4%
1 3480
 
10.8%
3 2036
 
6.3%
7 994
 
3.1%
9 613
 
1.9%
5 517
 
1.6%
8 492
 
1.5%
4 435
 
1.4%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.6 KiB
영업
1462 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 1462
100.0%

Length

2023-12-11T14:49:49.650782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T14:49:49.755011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 1462
100.0%

Sample

번호사업장명소재지전체주소도로명전체주소인허가일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적소재지우편번호건물소유구분명년도다중이용업소여부위생업종명위생업태명전화번호위치정보(X)위치정보(Y)인허가번호상세영업상태명
01영축실업서울특별시 성동구 용답동 235-8번지서울특별시 성동구 자동차시장1길 85 (용답동)20010101운영중<NA><NA><NA><NA>0.0133850<NA>2001N공중이용시설업무시설0222132321205932.871684451225.1708743030000-210-2001-00070영업
12개풍빌딩서울특별시 성동구 성수동1가 656-766번지서울특별시 성동구 아차산로 38 (성수동1가)20010101운영중<NA><NA><NA><NA>0.0133843<NA>2001N공중이용시설업무시설02 4992275204286.02391449675.4497853030000-210-2001-00073영업
23서울특별시시설관리공단서울특별시 성동구 마장동 527-6번지서울특별시 성동구 청계천로 540 (마장동)20010101운영중<NA><NA><NA><NA>0.0133814<NA>2001N공중이용시설업무시설0222906185203184.532428452452.856173030000-210-2001-00075영업
34한서빌딩서울특별시 성동구 성수동2가 315-58번지서울특별시 성동구 연무장7길 16 (성수동2가)20010101운영중<NA><NA><NA><NA>0.0133835<NA>2001N공중이용시설업무시설02 4625151204869.293313449383.2756983030000-210-2001-00077영업
45(주)삼일공사서울특별시 성동구 성수동1가 656-282번지서울특별시 성동구 아차산로 33 (성수동1가)20010101운영중<NA><NA><NA><NA>0.0133823<NA>2001N공중이용시설업무시설02 4611911204273.528434449745.2449423030000-210-2001-00079영업
56성동경찰서서울특별시 성동구 행당동 192-8번지서울특별시 성동구 왕십리광장로 9 (행당동)20010101운영중<NA><NA><NA><NA>0.0133866<NA>2001N공중이용시설업무시설0222920882203244.613558451387.5977633030000-210-2001-00083영업
67삼호오피스텔서울특별시 성동구 용답동 236-10번지서울특별시 성동구 자동차시장1길 103 (용답동)20010101운영중<NA><NA><NA><NA>0.0133851<NA>2001N공중이용시설업무시설0222425808206110.996784451189.5088563030000-210-2001-00086영업
78동방빌딩서울특별시 성동구 마장동 517번지서울특별시 성동구 고산자로 300 (마장동)20010101운영중<NA><NA><NA><NA>0.0133814<NA>2001N공중이용시설업무시설0222943511203271.37585451862.4774713030000-210-2001-00010영업
89한국전력-성동지점서울특별시 성동구 마장동 765-1번지서울특별시 성동구 마장로39길 7 (마장동)20010101운영중<NA><NA><NA><NA>0.0133815<NA>2001N공중이용시설업무시설0222905211203559.993631451658.888393030000-210-2001-00011영업
910에스콰이아서울특별시 성동구 성수동2가 656-75번지<NA>20010101운영중<NA><NA><NA><NA>0.0133830<NA>2001N공중이용시설업무시설02 4699292<NA><NA>3030000-210-2001-00027영업
번호사업장명소재지전체주소도로명전체주소인허가일자영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지면적소재지우편번호건물소유구분명년도다중이용업소여부위생업종명위생업태명전화번호위치정보(X)위치정보(Y)인허가번호상세영업상태명
14521453동신빌딩서울특별시 동대문구 장안동 370-4번지서울특별시 동대문구 답십리로 272-6 (장안동)20150417운영중<NA><NA><NA><NA><NA>130842<NA>2015N공중이용시설업무시설02 60126912206221.645024452487.5932583050000-210-2015-00006영업
14531454백경서울특별시 동대문구 신설동 97-9번지<NA>20150417운영중<NA><NA><NA><NA><NA>130811<NA>2015N공중이용시설업무시설02 922 7381<NA><NA>3050000-210-2015-00008영업
14541455연천장학관서울특별시 동대문구 신설동 103-21번지서울특별시 동대문구 난계로30길 27 (신설동)20150420운영중<NA><NA><NA><NA><NA>130812<NA>2015N공중이용시설업무시설031 839 4672202208.135498452742.755773050000-210-2015-00010영업
14551456신설프라자서울특별시 동대문구 신설동 117-4번지서울특별시 동대문구 난계로 254 (신설동)20150420운영중<NA><NA><NA><NA><NA>130814<NA>2015N공중이용시설업무시설02 62333600202095.066187452754.1685193050000-210-2015-00011영업
14561457삼성전자서비스신설동점서울특별시 동대문구 신설동 92-27번지<NA>20150421운영중<NA><NA><NA><NA><NA>130811<NA>2015N공중이용시설업무시설02 927 0004<NA><NA>3050000-210-2015-00015영업
14571458엔코어호텔서울특별시 동대문구 신설동 98-24번지서울특별시 동대문구 왕산로 22 (신설동)20150421운영중<NA><NA><NA><NA><NA>130811<NA>2015N공중이용시설업무시설02 21166030202302.698178452959.7619943050000-210-2015-00016영업
14581459BYC청량리오피스텔서울특별시 동대문구 용두동 10-3번지<NA>20150422운영중<NA><NA><NA><NA><NA>130817<NA>2015N공중이용시설업무시설02 33954910<NA><NA>3050000-210-2015-00026영업
14591460용담빌딩서울특별시 동대문구 답십리동 498-4번지서울특별시 동대문구 고미술로 14 (답십리동)20150423운영중<NA><NA><NA><NA><NA>130805<NA>2015N공중이용시설업무시설02 22174971204435.908708452236.8787773050000-210-2015-00027영업
14601461국제호텔직업전문학교서울특별시 동대문구 신설동 98-30번지서울특별시 동대문구 왕산로 14 (신설동)20150421운영중<NA><NA><NA><NA><NA>130811<NA>2015N공중이용시설업무시설02 9948814202235.169195452933.559693050000-210-2015-00028영업
14611462삼희상가(아파트) 1동서울특별시 동대문구 답십리동 530-5번지서울특별시 동대문구 고미술로 11 (답십리동)20150423운영중<NA><NA><NA><NA><NA>130805<NA>2015N공중이용시설업무시설<NA>204454.780819452280.4288523050000-210-2015-00029영업