Overview

Dataset statistics

Number of variables44
Number of observations8713
Missing cells100349
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 MiB
Average record size in memory375.0 B

Variable types

Categorical18
Text8
DateTime4
Unsupported7
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18700/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
전통업소지정번호 has constant value ""Constant
영업장주변구분명 is highly imbalanced (59.2%)Imbalance
등급구분명 is highly imbalanced (53.7%)Imbalance
급수시설구분명 is highly imbalanced (53.0%)Imbalance
총인원 is highly imbalanced (74.9%)Imbalance
본사종업원수 is highly imbalanced (74.6%)Imbalance
공장사무직종업원수 is highly imbalanced (74.6%)Imbalance
공장판매직종업원수 is highly imbalanced (74.6%)Imbalance
공장생산직종업원수 is highly imbalanced (74.6%)Imbalance
보증액 is highly imbalanced (74.6%)Imbalance
월세액 is highly imbalanced (74.6%)Imbalance
다중이용업소여부 is highly imbalanced (95.0%)Imbalance
인허가취소일자 has 8713 (100.0%) missing valuesMissing
폐업일자 has 2578 (29.6%) missing valuesMissing
휴업시작일자 has 8713 (100.0%) missing valuesMissing
휴업종료일자 has 8713 (100.0%) missing valuesMissing
재개업일자 has 8713 (100.0%) missing valuesMissing
전화번호 has 5097 (58.5%) missing valuesMissing
소재지면적 has 205 (2.4%) missing valuesMissing
도로명주소 has 2882 (33.1%) missing valuesMissing
도로명우편번호 has 2927 (33.6%) missing valuesMissing
좌표정보(X) has 432 (5.0%) missing valuesMissing
좌표정보(Y) has 432 (5.0%) missing valuesMissing
남성종사자수 has 6084 (69.8%) missing valuesMissing
여성종사자수 has 6067 (69.6%) missing valuesMissing
건물소유구분명 has 8713 (100.0%) missing valuesMissing
다중이용업소여부 has 1969 (22.6%) missing valuesMissing
시설총규모 has 1969 (22.6%) missing valuesMissing
전통업소지정번호 has 8712 (> 99.9%) missing valuesMissing
전통업소주된음식 has 8713 (100.0%) missing valuesMissing
홈페이지 has 8713 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 2147 (24.6%) zerosZeros
여성종사자수 has 1675 (19.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:40:06.219325
Analysis finished2024-05-11 05:40:10.132883
Duration3.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
3230000
8713 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 8713
100.0%

Length

2024-05-11T14:40:10.252951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:10.427786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 8713
100.0%

관리번호
Text

UNIQUE 

Distinct8713
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
2024-05-11T14:40:10.708320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters191686
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

Unique8713 ?
Unique (%)100.0%

Sample

1st row3230000-104-1904-01121
2nd row3230000-104-1948-01733
3rd row3230000-104-1975-01833
4th row3230000-104-1976-01917
5th row3230000-104-1976-01976
ValueCountFrequency (%)
3230000-104-1904-01121 1
 
< 0.1%
3230000-104-2017-00431 1
 
< 0.1%
3230000-104-2017-00437 1
 
< 0.1%
3230000-104-2017-00436 1
 
< 0.1%
3230000-104-2017-00435 1
 
< 0.1%
3230000-104-2017-00434 1
 
< 0.1%
3230000-104-2017-00433 1
 
< 0.1%
3230000-104-2017-00432 1
 
< 0.1%
3230000-104-2018-00091 1
 
< 0.1%
3230000-104-2018-00090 1
 
< 0.1%
Other values (8703) 8703
99.9%
2024-05-11T14:40:11.188648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72075
37.6%
- 26139
 
13.6%
2 22347
 
11.7%
3 21467
 
11.2%
1 20218
 
10.5%
4 11998
 
6.3%
9 5983
 
3.1%
8 3119
 
1.6%
7 2910
 
1.5%
6 2717
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 165547
86.4%
Dash Punctuation 26139
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72075
43.5%
2 22347
 
13.5%
3 21467
 
13.0%
1 20218
 
12.2%
4 11998
 
7.2%
9 5983
 
3.6%
8 3119
 
1.9%
7 2910
 
1.8%
6 2717
 
1.6%
5 2713
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 26139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 191686
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72075
37.6%
- 26139
 
13.6%
2 22347
 
11.7%
3 21467
 
11.2%
1 20218
 
10.5%
4 11998
 
6.3%
9 5983
 
3.1%
8 3119
 
1.6%
7 2910
 
1.5%
6 2717
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 191686
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72075
37.6%
- 26139
 
13.6%
2 22347
 
11.7%
3 21467
 
11.2%
1 20218
 
10.5%
4 11998
 
6.3%
9 5983
 
3.1%
8 3119
 
1.6%
7 2910
 
1.5%
6 2717
 
1.4%
Distinct4945
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
Minimum1904-08-08 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:40:11.417265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:11.652483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
3
6135 
1
2578 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 6135
70.4%
1 2578
29.6%

Length

2024-05-11T14:40:11.877921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:12.053806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6135
70.4%
1 2578
29.6%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
폐업
6135 
영업/정상
2578 

Length

Max length5
Median length2
Mean length2.8876392
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6135
70.4%
영업/정상 2578
29.6%

Length

2024-05-11T14:40:12.367305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:12.587104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6135
70.4%
영업/정상 2578
29.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
2
6135 
1
2578 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 6135
70.4%
1 2578
29.6%

Length

2024-05-11T14:40:12.765553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:12.972538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6135
70.4%
1 2578
29.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
폐업
6135 
영업
2578 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6135
70.4%
영업 2578
29.6%

Length

2024-05-11T14:40:13.167366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:13.315234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6135
70.4%
영업 2578
29.6%

폐업일자
Date

MISSING 

Distinct3829
Distinct (%)62.4%
Missing2578
Missing (%)29.6%
Memory size68.2 KiB
Minimum1989-03-17 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:40:13.530196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:13.777557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

전화번호
Text

MISSING 

Distinct3118
Distinct (%)86.2%
Missing5097
Missing (%)58.5%
Memory size68.2 KiB
2024-05-11T14:40:14.161925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.614768
Min length2

Characters and Unicode

Total characters38383
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2942 ?
Unique (%)81.4%

Sample

1st row0204693489
2nd row0204778561
3rd row0204132108
4th row02 4224110
5th row02 4130880
ValueCountFrequency (%)
02 3030
40.2%
070 95
 
1.3%
00000 59
 
0.8%
031 46
 
0.6%
4112000 45
 
0.6%
0200000000 40
 
0.5%
400 33
 
0.4%
422 32
 
0.4%
412 32
 
0.4%
411 30
 
0.4%
Other values (3248) 4097
54.3%
2024-05-11T14:40:14.792600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7647
19.9%
2 6485
16.9%
5274
13.7%
4 4558
11.9%
1 3189
8.3%
3 2342
 
6.1%
8 1948
 
5.1%
7 1948
 
5.1%
5 1803
 
4.7%
6 1628
 
4.2%
Other values (2) 1561
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33103
86.2%
Space Separator 5274
 
13.7%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7647
23.1%
2 6485
19.6%
4 4558
13.8%
1 3189
9.6%
3 2342
 
7.1%
8 1948
 
5.9%
7 1948
 
5.9%
5 1803
 
5.4%
6 1628
 
4.9%
9 1555
 
4.7%
Space Separator
ValueCountFrequency (%)
5274
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38383
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7647
19.9%
2 6485
16.9%
5274
13.7%
4 4558
11.9%
1 3189
8.3%
3 2342
 
6.1%
8 1948
 
5.1%
7 1948
 
5.1%
5 1803
 
4.7%
6 1628
 
4.2%
Other values (2) 1561
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7647
19.9%
2 6485
16.9%
5274
13.7%
4 4558
11.9%
1 3189
8.3%
3 2342
 
6.1%
8 1948
 
5.1%
7 1948
 
5.1%
5 1803
 
4.7%
6 1628
 
4.2%
Other values (2) 1561
 
4.1%

소재지면적
Text

MISSING 

Distinct3313
Distinct (%)38.9%
Missing205
Missing (%)2.4%
Memory size68.2 KiB
2024-05-11T14:40:15.417834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.9077339
Min length3

Characters and Unicode

Total characters41755
Distinct characters12
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

Unique2331 ?
Unique (%)27.4%

Sample

1st row6.10
2nd row47.86
3rd row69.90
4th row77.39
5th row105.00
ValueCountFrequency (%)
3.30 481
 
5.7%
6.60 277
 
3.3%
33.00 178
 
2.1%
26.40 127
 
1.5%
30.00 116
 
1.4%
10.00 108
 
1.3%
9.90 92
 
1.1%
20.00 89
 
1.0%
16.50 89
 
1.0%
29.70 72
 
0.8%
Other values (3303) 6879
80.9%
2024-05-11T14:40:16.240356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8703
20.8%
. 8508
20.4%
3 3891
9.3%
2 3701
8.9%
1 3346
 
8.0%
6 2953
 
7.1%
5 2432
 
5.8%
4 2400
 
5.7%
9 2116
 
5.1%
8 2023
 
4.8%
Other values (2) 1682
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33245
79.6%
Other Punctuation 8510
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8703
26.2%
3 3891
11.7%
2 3701
11.1%
1 3346
 
10.1%
6 2953
 
8.9%
5 2432
 
7.3%
4 2400
 
7.2%
9 2116
 
6.4%
8 2023
 
6.1%
7 1680
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 8508
> 99.9%
, 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 41755
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8703
20.8%
. 8508
20.4%
3 3891
9.3%
2 3701
8.9%
1 3346
 
8.0%
6 2953
 
7.1%
5 2432
 
5.8%
4 2400
 
5.7%
9 2116
 
5.1%
8 2023
 
4.8%
Other values (2) 1682
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41755
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8703
20.8%
. 8508
20.4%
3 3891
9.3%
2 3701
8.9%
1 3346
 
8.0%
6 2953
 
7.1%
5 2432
 
5.8%
4 2400
 
5.7%
9 2116
 
5.1%
8 2023
 
4.8%
Other values (2) 1682
 
4.0%
Distinct252
Distinct (%)2.9%
Missing2
Missing (%)< 0.1%
Memory size68.2 KiB
2024-05-11T14:40:16.813863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1595684
Min length6

Characters and Unicode

Total characters53656
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

Unique34 ?
Unique (%)0.4%

Sample

1st row138863
2nd row138879
3rd row138819
4th row138861
5th row138861
ValueCountFrequency (%)
138915 540
 
6.2%
138888 417
 
4.8%
138934 403
 
4.6%
138721 246
 
2.8%
138861 196
 
2.3%
138200 178
 
2.0%
138854 172
 
2.0%
138829 169
 
1.9%
138889 154
 
1.8%
138885 138
 
1.6%
Other values (242) 6098
70.0%
2024-05-11T14:40:17.605783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 16767
31.2%
1 11297
21.1%
3 10467
19.5%
9 2415
 
4.5%
2 2147
 
4.0%
0 2136
 
4.0%
4 2117
 
3.9%
5 1990
 
3.7%
6 1525
 
2.8%
7 1405
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52266
97.4%
Dash Punctuation 1390
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 16767
32.1%
1 11297
21.6%
3 10467
20.0%
9 2415
 
4.6%
2 2147
 
4.1%
0 2136
 
4.1%
4 2117
 
4.1%
5 1990
 
3.8%
6 1525
 
2.9%
7 1405
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 1390
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53656
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 16767
31.2%
1 11297
21.1%
3 10467
19.5%
9 2415
 
4.5%
2 2147
 
4.0%
0 2136
 
4.0%
4 2117
 
3.9%
5 1990
 
3.7%
6 1525
 
2.8%
7 1405
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53656
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 16767
31.2%
1 11297
21.1%
3 10467
19.5%
9 2415
 
4.5%
2 2147
 
4.0%
0 2136
 
4.0%
4 2117
 
3.9%
5 1990
 
3.7%
6 1525
 
2.8%
7 1405
 
2.6%
Distinct6058
Distinct (%)69.5%
Missing2
Missing (%)< 0.1%
Memory size68.2 KiB
2024-05-11T14:40:18.043356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length46
Mean length25.426128
Min length14

Characters and Unicode

Total characters221487
Distinct characters482
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5128 ?
Unique (%)58.9%

Sample

1st row서울특별시 송파구 잠실동 228-9번지
2nd row서울특별시 송파구 풍납동 410-1번지
3rd row서울특별시 송파구 마천동 190-42번지
4th row서울특별시 송파구 잠실동 184-11번지
5th row서울특별시 송파구 잠실동 184-5번지
ValueCountFrequency (%)
서울특별시 8711
20.5%
송파구 8711
20.5%
잠실동 2028
 
4.8%
문정동 1214
 
2.9%
가락동 905
 
2.1%
방이동 855
 
2.0%
지상1층 754
 
1.8%
송파동 655
 
1.5%
신천동 626
 
1.5%
40-1번지 615
 
1.4%
Other values (5503) 17351
40.9%
2024-05-11T14:40:18.740525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40128
18.1%
1 10254
 
4.6%
10194
 
4.6%
9559
 
4.3%
9144
 
4.1%
8901
 
4.0%
8823
 
4.0%
8819
 
4.0%
8780
 
4.0%
8712
 
3.9%
Other values (472) 98173
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136684
61.7%
Space Separator 40128
 
18.1%
Decimal Number 36154
 
16.3%
Dash Punctuation 6921
 
3.1%
Uppercase Letter 745
 
0.3%
Close Punctuation 295
 
0.1%
Open Punctuation 293
 
0.1%
Other Punctuation 229
 
0.1%
Lowercase Letter 22
 
< 0.1%
Math Symbol 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10194
 
7.5%
9559
 
7.0%
9144
 
6.7%
8901
 
6.5%
8823
 
6.5%
8819
 
6.5%
8780
 
6.4%
8712
 
6.4%
8711
 
6.4%
7871
 
5.8%
Other values (414) 47170
34.5%
Uppercase Letter
ValueCountFrequency (%)
B 176
23.6%
A 130
17.4%
S 60
 
8.1%
F 42
 
5.6%
T 42
 
5.6%
G 38
 
5.1%
C 32
 
4.3%
I 27
 
3.6%
Y 26
 
3.5%
K 23
 
3.1%
Other values (14) 149
20.0%
Decimal Number
ValueCountFrequency (%)
1 10254
28.4%
2 4748
13.1%
0 3761
 
10.4%
4 3572
 
9.9%
3 2538
 
7.0%
8 2365
 
6.5%
9 2364
 
6.5%
6 2318
 
6.4%
5 2235
 
6.2%
7 1999
 
5.5%
Lowercase Letter
ValueCountFrequency (%)
e 6
27.3%
a 3
13.6%
s 3
13.6%
y 2
 
9.1%
c 2
 
9.1%
t 2
 
9.1%
o 1
 
4.5%
x 1
 
4.5%
b 1
 
4.5%
m 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
, 191
83.4%
. 18
 
7.9%
/ 11
 
4.8%
? 4
 
1.7%
& 4
 
1.7%
@ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Space Separator
ValueCountFrequency (%)
40128
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6921
100.0%
Close Punctuation
ValueCountFrequency (%)
) 295
100.0%
Open Punctuation
ValueCountFrequency (%)
( 293
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136680
61.7%
Common 84032
37.9%
Latin 771
 
0.3%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10194
 
7.5%
9559
 
7.0%
9144
 
6.7%
8901
 
6.5%
8823
 
6.5%
8819
 
6.5%
8780
 
6.4%
8712
 
6.4%
8711
 
6.4%
7871
 
5.8%
Other values (412) 47166
34.5%
Latin
ValueCountFrequency (%)
B 176
22.8%
A 130
16.9%
S 60
 
7.8%
F 42
 
5.4%
T 42
 
5.4%
G 38
 
4.9%
C 32
 
4.2%
I 27
 
3.5%
Y 26
 
3.4%
K 23
 
3.0%
Other values (27) 175
22.7%
Common
ValueCountFrequency (%)
40128
47.8%
1 10254
 
12.2%
- 6921
 
8.2%
2 4748
 
5.7%
0 3761
 
4.5%
4 3572
 
4.3%
3 2538
 
3.0%
8 2365
 
2.8%
9 2364
 
2.8%
6 2318
 
2.8%
Other values (11) 5063
 
6.0%
Han
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136680
61.7%
ASCII 84799
38.3%
CJK 4
 
< 0.1%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40128
47.3%
1 10254
 
12.1%
- 6921
 
8.2%
2 4748
 
5.6%
0 3761
 
4.4%
4 3572
 
4.2%
3 2538
 
3.0%
8 2365
 
2.8%
9 2364
 
2.8%
6 2318
 
2.7%
Other values (45) 5830
 
6.9%
Hangul
ValueCountFrequency (%)
10194
 
7.5%
9559
 
7.0%
9144
 
6.7%
8901
 
6.5%
8823
 
6.5%
8819
 
6.5%
8780
 
6.4%
8712
 
6.4%
8711
 
6.4%
7871
 
5.8%
Other values (412) 47166
34.5%
CJK
ValueCountFrequency (%)
2
50.0%
2
50.0%
Number Forms
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

도로명주소
Text

MISSING 

Distinct5092
Distinct (%)87.3%
Missing2882
Missing (%)33.1%
Memory size68.2 KiB
2024-05-11T14:40:19.171743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length57
Mean length37.287944
Min length21

Characters and Unicode

Total characters217426
Distinct characters502
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4724 ?
Unique (%)81.0%

Sample

1st row서울특별시 송파구 가락로 51 (석촌동)
2nd row서울특별시 송파구 백제고분로 262 (삼전동)
3rd row서울특별시 송파구 송파대로 365 (석촌동)
4th row서울특별시 송파구 올림픽로 240, 호 (잠실동,(쇼핑몰1층))
5th row서울특별시 송파구 올림픽로 240, 지하1층 (잠실동, 롯데백화점)
ValueCountFrequency (%)
서울특별시 5830
 
13.9%
송파구 5830
 
13.9%
1층 2017
 
4.8%
올림픽로 1278
 
3.1%
잠실동 1209
 
2.9%
지하1층 1005
 
2.4%
문정동 949
 
2.3%
지상1층 667
 
1.6%
240 560
 
1.3%
가락동 516
 
1.2%
Other values (3712) 21999
52.6%
2024-05-11T14:40:19.946442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36085
 
16.6%
1 11380
 
5.2%
7633
 
3.5%
, 7607
 
3.5%
7130
 
3.3%
6897
 
3.2%
6119
 
2.8%
) 5949
 
2.7%
( 5949
 
2.7%
5947
 
2.7%
Other values (492) 116730
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 126641
58.2%
Space Separator 36085
 
16.6%
Decimal Number 32871
 
15.1%
Other Punctuation 7633
 
3.5%
Close Punctuation 5950
 
2.7%
Open Punctuation 5950
 
2.7%
Uppercase Letter 1297
 
0.6%
Dash Punctuation 846
 
0.4%
Lowercase Letter 120
 
0.1%
Math Symbol 28
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7633
 
6.0%
7130
 
5.6%
6897
 
5.4%
6119
 
4.8%
5947
 
4.7%
5945
 
4.7%
5941
 
4.7%
5882
 
4.6%
5832
 
4.6%
5831
 
4.6%
Other values (425) 63484
50.1%
Uppercase Letter
ValueCountFrequency (%)
B 391
30.1%
A 316
24.4%
C 100
 
7.7%
G 70
 
5.4%
E 53
 
4.1%
S 51
 
3.9%
H 51
 
3.9%
F 48
 
3.7%
Y 39
 
3.0%
T 36
 
2.8%
Other values (14) 142
 
10.9%
Lowercase Letter
ValueCountFrequency (%)
b 25
20.8%
a 17
14.2%
r 16
13.3%
t 16
13.3%
m 15
12.5%
e 9
 
7.5%
c 4
 
3.3%
o 4
 
3.3%
s 4
 
3.3%
y 3
 
2.5%
Other values (5) 7
 
5.8%
Decimal Number
ValueCountFrequency (%)
1 11380
34.6%
2 4743
14.4%
0 3935
 
12.0%
3 2931
 
8.9%
4 2823
 
8.6%
5 1882
 
5.7%
6 1740
 
5.3%
8 1330
 
4.0%
7 1068
 
3.2%
9 1039
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 7607
99.7%
. 8
 
0.1%
/ 7
 
0.1%
& 5
 
0.1%
? 3
 
< 0.1%
* 1
 
< 0.1%
! 1
 
< 0.1%
@ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5949
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5949
> 99.9%
[ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
36085
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 846
100.0%
Math Symbol
ValueCountFrequency (%)
~ 28
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126637
58.2%
Common 89365
41.1%
Latin 1420
 
0.7%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7633
 
6.0%
7130
 
5.6%
6897
 
5.4%
6119
 
4.8%
5947
 
4.7%
5945
 
4.7%
5941
 
4.7%
5882
 
4.6%
5832
 
4.6%
5831
 
4.6%
Other values (423) 63480
50.1%
Latin
ValueCountFrequency (%)
B 391
27.5%
A 316
22.3%
C 100
 
7.0%
G 70
 
4.9%
E 53
 
3.7%
S 51
 
3.6%
H 51
 
3.6%
F 48
 
3.4%
Y 39
 
2.7%
T 36
 
2.5%
Other values (31) 265
18.7%
Common
ValueCountFrequency (%)
36085
40.4%
1 11380
 
12.7%
, 7607
 
8.5%
) 5949
 
6.7%
( 5949
 
6.7%
2 4743
 
5.3%
0 3935
 
4.4%
3 2931
 
3.3%
4 2823
 
3.2%
5 1882
 
2.1%
Other values (16) 6081
 
6.8%
Han
ValueCountFrequency (%)
2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 126637
58.2%
ASCII 90782
41.8%
CJK 4
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36085
39.7%
1 11380
 
12.5%
, 7607
 
8.4%
) 5949
 
6.6%
( 5949
 
6.6%
2 4743
 
5.2%
0 3935
 
4.3%
3 2931
 
3.2%
4 2823
 
3.1%
5 1882
 
2.1%
Other values (55) 7498
 
8.3%
Hangul
ValueCountFrequency (%)
7633
 
6.0%
7130
 
5.6%
6897
 
5.4%
6119
 
4.8%
5947
 
4.7%
5945
 
4.7%
5941
 
4.7%
5882
 
4.6%
5832
 
4.6%
5831
 
4.6%
Other values (423) 63480
50.1%
CJK
ValueCountFrequency (%)
2
50.0%
2
50.0%
Number Forms
ValueCountFrequency (%)
2
66.7%
1
33.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct335
Distinct (%)5.8%
Missing2927
Missing (%)33.6%
Infinite0
Infinite (%)0.0%
Mean5659.6896
Minimum5500
Maximum5857
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:20.243324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5500
5-th percentile5504
Q15554
median5639
Q35769
95-th percentile5852
Maximum5857
Range357
Interquartile range (IQR)215

Descriptive statistics

Standard deviation118.50847
Coefficient of variation (CV)0.02093904
Kurtosis-1.3119904
Mean5659.6896
Median Absolute Deviation (MAD)88
Skewness0.33105139
Sum32746964
Variance14044.257
MonotonicityNot monotonic
2024-05-11T14:40:20.496792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5554 559
 
6.4%
5838 209
 
2.4%
5551 192
 
2.2%
5510 179
 
2.1%
5500 129
 
1.5%
5854 119
 
1.4%
5855 116
 
1.3%
5836 105
 
1.2%
5852 88
 
1.0%
5502 84
 
1.0%
Other values (325) 4006
46.0%
(Missing) 2927
33.6%
ValueCountFrequency (%)
5500 129
1.5%
5501 56
0.6%
5502 84
1.0%
5503 16
 
0.2%
5504 49
 
0.6%
5505 64
0.7%
5506 1
 
< 0.1%
5507 50
 
0.6%
5508 3
 
< 0.1%
5509 1
 
< 0.1%
ValueCountFrequency (%)
5857 2
 
< 0.1%
5856 1
 
< 0.1%
5855 116
1.3%
5854 119
1.4%
5853 3
 
< 0.1%
5852 88
1.0%
5850 3
 
< 0.1%
5849 47
 
0.5%
5848 6
 
0.1%
5847 5
 
0.1%
Distinct7893
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
2024-05-11T14:40:20.985171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length7.9015265
Min length1

Characters and Unicode

Total characters68846
Distinct characters1020
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7346 ?
Unique (%)84.3%

Sample

1st row코리아세븐
2nd row볼라커피숍
3rd row초원다방
4th row국제다방
5th row약속
ValueCountFrequency (%)
카페 193
 
1.5%
세븐일레븐 187
 
1.4%
gs25 149
 
1.1%
잠실점 113
 
0.9%
씨유 110
 
0.8%
커피 84
 
0.6%
cafe 81
 
0.6%
송파점 66
 
0.5%
coffee 58
 
0.4%
이마트24 50
 
0.4%
Other values (8382) 12189
91.8%
2024-05-11T14:40:21.778749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4578
 
6.6%
2770
 
4.0%
1920
 
2.8%
1667
 
2.4%
) 1225
 
1.8%
1223
 
1.8%
( 1221
 
1.8%
1159
 
1.7%
982
 
1.4%
808
 
1.2%
Other values (1010) 51293
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53211
77.3%
Space Separator 4578
 
6.6%
Lowercase Letter 3489
 
5.1%
Uppercase Letter 3453
 
5.0%
Decimal Number 1374
 
2.0%
Close Punctuation 1225
 
1.8%
Open Punctuation 1221
 
1.8%
Other Punctuation 242
 
0.4%
Dash Punctuation 40
 
0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2770
 
5.2%
1920
 
3.6%
1667
 
3.1%
1223
 
2.3%
1159
 
2.2%
982
 
1.8%
808
 
1.5%
672
 
1.3%
659
 
1.2%
655
 
1.2%
Other values (925) 40696
76.5%
Uppercase Letter
ValueCountFrequency (%)
C 425
12.3%
S 383
 
11.1%
G 285
 
8.3%
E 269
 
7.8%
A 216
 
6.3%
O 213
 
6.2%
P 181
 
5.2%
F 176
 
5.1%
B 142
 
4.1%
T 142
 
4.1%
Other values (17) 1021
29.6%
Lowercase Letter
ValueCountFrequency (%)
e 590
16.9%
o 352
10.1%
a 336
 
9.6%
f 261
 
7.5%
n 199
 
5.7%
c 194
 
5.6%
i 190
 
5.4%
r 179
 
5.1%
s 176
 
5.0%
t 133
 
3.8%
Other values (16) 879
25.2%
Other Punctuation
ValueCountFrequency (%)
. 61
25.2%
& 44
18.2%
' 43
17.8%
, 34
14.0%
/ 20
 
8.3%
? 13
 
5.4%
! 10
 
4.1%
# 9
 
3.7%
: 5
 
2.1%
% 2
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 484
35.2%
5 341
24.8%
1 143
 
10.4%
3 101
 
7.4%
4 95
 
6.9%
9 54
 
3.9%
0 50
 
3.6%
8 41
 
3.0%
6 33
 
2.4%
7 32
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 4
66.7%
> 1
 
16.7%
< 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
° 1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4578
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1225
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53196
77.3%
Common 8693
 
12.6%
Latin 6941
 
10.1%
Han 15
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2770
 
5.2%
1920
 
3.6%
1667
 
3.1%
1223
 
2.3%
1159
 
2.2%
982
 
1.8%
808
 
1.5%
672
 
1.3%
659
 
1.2%
655
 
1.2%
Other values (910) 40681
76.5%
Latin
ValueCountFrequency (%)
e 590
 
8.5%
C 425
 
6.1%
S 383
 
5.5%
o 352
 
5.1%
a 336
 
4.8%
G 285
 
4.1%
E 269
 
3.9%
f 261
 
3.8%
A 216
 
3.1%
O 213
 
3.1%
Other values (42) 3611
52.0%
Common
ValueCountFrequency (%)
4578
52.7%
) 1225
 
14.1%
( 1221
 
14.0%
2 484
 
5.6%
5 341
 
3.9%
1 143
 
1.6%
3 101
 
1.2%
4 95
 
1.1%
. 61
 
0.7%
9 54
 
0.6%
Other values (22) 390
 
4.5%
Han
ValueCountFrequency (%)
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (5) 5
33.3%
Greek
ValueCountFrequency (%)
Χ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53189
77.3%
ASCII 15631
 
22.7%
CJK 14
 
< 0.1%
Compat Jamo 7
 
< 0.1%
None 3
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4578
29.3%
) 1225
 
7.8%
( 1221
 
7.8%
e 590
 
3.8%
2 484
 
3.1%
C 425
 
2.7%
S 383
 
2.5%
o 352
 
2.3%
5 341
 
2.2%
a 336
 
2.1%
Other values (71) 5696
36.4%
Hangul
ValueCountFrequency (%)
2770
 
5.2%
1920
 
3.6%
1667
 
3.1%
1223
 
2.3%
1159
 
2.2%
982
 
1.8%
808
 
1.5%
672
 
1.3%
659
 
1.2%
655
 
1.2%
Other values (903) 40674
76.5%
CJK
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4) 4
28.6%
None
ValueCountFrequency (%)
° 1
33.3%
Χ 1
33.3%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct6850
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
Minimum1999-02-02 00:00:00
Maximum2024-05-09 15:16:13
2024-05-11T14:40:22.389572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:22.701776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
I
5664 
U
3049 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 5664
65.0%
U 3049
35.0%

Length

2024-05-11T14:40:22.936023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:23.157064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5664
65.0%
u 3049
35.0%
Distinct1558
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:40:23.366973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:40:23.595157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
기타 휴게음식점
2991 
커피숍
1706 
일반조리판매
1425 
다방
678 
과자점
651 
Other values (13)
1262 

Length

Max length8
Median length6
Mean length5.2570871
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row패스트푸드
2nd row다방
3rd row과자점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
기타 휴게음식점 2991
34.3%
커피숍 1706
19.6%
일반조리판매 1425
16.4%
다방 678
 
7.8%
과자점 651
 
7.5%
편의점 493
 
5.7%
패스트푸드 466
 
5.3%
백화점 149
 
1.7%
아이스크림 46
 
0.5%
푸드트럭 45
 
0.5%
Other values (8) 63
 
0.7%

Length

2024-05-11T14:40:23.815906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 2991
25.6%
휴게음식점 2991
25.6%
커피숍 1706
14.6%
일반조리판매 1425
12.2%
다방 678
 
5.8%
과자점 651
 
5.6%
편의점 493
 
4.2%
패스트푸드 466
 
4.0%
백화점 149
 
1.3%
아이스크림 46
 
0.4%
Other values (9) 108
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2976
Distinct (%)35.9%
Missing432
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean209804.63
Minimum206168.6
Maximum213999.96
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:24.045259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206168.6
5-th percentile207222.41
Q1208589.36
median209790.96
Q3210960.33
95-th percentile212692.98
Maximum213999.96
Range7831.3524
Interquartile range (IQR)2370.9672

Descriptive statistics

Standard deviation1635.0444
Coefficient of variation (CV)0.007793176
Kurtosis-0.4976748
Mean209804.63
Median Absolute Deviation (MAD)1201.5966
Skewness0.13395409
Sum1.7373922 × 109
Variance2673370.3
MonotonicityNot monotonic
2024-05-11T14:40:24.337263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208589.363343145 861
 
9.9%
209074.900840074 204
 
2.3%
210986.460698452 161
 
1.8%
206383.829438022 126
 
1.4%
210343.699256005 88
 
1.0%
208707.089897534 73
 
0.8%
209607.590372037 71
 
0.8%
207624.424720682 69
 
0.8%
207373.50021477 69
 
0.8%
211619.368009793 67
 
0.8%
Other values (2966) 6492
74.5%
(Missing) 432
 
5.0%
ValueCountFrequency (%)
206168.604353473 2
 
< 0.1%
206383.829438022 126
1.4%
206397.34797252 12
 
0.1%
206425.501600423 17
 
0.2%
206487.800145227 1
 
< 0.1%
206498.438841963 5
 
0.1%
206531.147433206 8
 
0.1%
206597.102072932 4
 
< 0.1%
206684.903140953 1
 
< 0.1%
206686.271395553 3
 
< 0.1%
ValueCountFrequency (%)
213999.956783491 1
< 0.1%
213977.355937651 1
< 0.1%
213886.824622785 1
< 0.1%
213885.153488894 1
< 0.1%
213859.070843691 2
< 0.1%
213851.828839367 1
< 0.1%
213843.762365507 1
< 0.1%
213831.277063773 1
< 0.1%
213812.280315584 1
< 0.1%
213795.835875629 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2975
Distinct (%)35.9%
Missing432
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean444705.95
Minimum440878.06
Maximum448805.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:24.594388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440878.06
5-th percentile442053.23
Q1443891.39
median444932.83
Q3445455.9
95-th percentile446539.28
Maximum448805.06
Range7927.0046
Interquartile range (IQR)1564.5158

Descriptive statistics

Standard deviation1338.7571
Coefficient of variation (CV)0.0030104322
Kurtosis0.28894115
Mean444705.95
Median Absolute Deviation (MAD)724.97578
Skewness-0.22166047
Sum3.68261 × 109
Variance1792270.6
MonotonicityNot monotonic
2024-05-11T14:40:24.877339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
445455.90405262 861
 
9.9%
445657.80932984 204
 
2.3%
441725.293491662 161
 
1.8%
446030.128073052 126
 
1.4%
443288.284974717 88
 
1.0%
446299.352775446 73
 
0.8%
447120.577229325 71
 
0.8%
445533.439634339 69
 
0.8%
445545.656024061 69
 
0.8%
445963.384875409 67
 
0.8%
Other values (2965) 6492
74.5%
(Missing) 432
 
5.0%
ValueCountFrequency (%)
440878.058652314 1
 
< 0.1%
440949.654290777 2
 
< 0.1%
441406.981434166 3
 
< 0.1%
441411.906445707 4
 
< 0.1%
441412.0 9
0.1%
441426.0 10
0.1%
441446.0 4
 
< 0.1%
441478.403213437 1
 
< 0.1%
441548.0 1
 
< 0.1%
441586.029967716 7
0.1%
ValueCountFrequency (%)
448805.063230447 1
 
< 0.1%
448601.324644324 1
 
< 0.1%
448593.535808124 3
< 0.1%
448553.63680263 2
< 0.1%
448533.079525241 1
 
< 0.1%
448499.494831757 1
 
< 0.1%
448472.581253344 1
 
< 0.1%
448461.082353287 1
 
< 0.1%
448453.051938704 2
< 0.1%
448437.083161462 1
 
< 0.1%

위생업태명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
기타 휴게음식점
2244 
<NA>
1969 
일반조리판매
1282 
커피숍
968 
다방
675 
Other values (14)
1575 

Length

Max length8
Median length5
Mean length4.9815219
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row패스트푸드
2nd row다방
3rd row과자점
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
기타 휴게음식점 2244
25.8%
<NA> 1969
22.6%
일반조리판매 1282
14.7%
커피숍 968
11.1%
다방 675
 
7.7%
과자점 649
 
7.4%
패스트푸드 408
 
4.7%
편의점 304
 
3.5%
백화점 130
 
1.5%
푸드트럭 30
 
0.3%
Other values (9) 54
 
0.6%

Length

2024-05-11T14:40:25.116691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 2244
20.5%
휴게음식점 2244
20.5%
na 1969
18.0%
일반조리판매 1282
11.7%
커피숍 968
8.8%
다방 675
 
6.2%
과자점 649
 
5.9%
패스트푸드 408
 
3.7%
편의점 304
 
2.8%
백화점 130
 
1.2%
Other values (10) 84
 
0.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing6084
Missing (%)69.8%
Infinite0
Infinite (%)0.0%
Mean0.21947509
Minimum0
Maximum8
Zeros2147
Zeros (%)24.6%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:25.295306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.53930831
Coefficient of variation (CV)2.4572644
Kurtosis31.881569
Mean0.21947509
Median Absolute Deviation (MAD)0
Skewness4.1317652
Sum577
Variance0.29085345
MonotonicityNot monotonic
2024-05-11T14:40:25.504489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 2147
 
24.6%
1 419
 
4.8%
2 45
 
0.5%
3 13
 
0.1%
5 3
 
< 0.1%
8 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 6084
69.8%
ValueCountFrequency (%)
0 2147
24.6%
1 419
 
4.8%
2 45
 
0.5%
3 13
 
0.1%
5 3
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 1
 
< 0.1%
5 3
 
< 0.1%
3 13
 
0.1%
2 45
 
0.5%
1 419
 
4.8%
0 2147
24.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.3%
Missing6067
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean0.59486017
Minimum0
Maximum9
Zeros1675
Zeros (%)19.2%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:25.672886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9230692
Coefficient of variation (CV)1.5517415
Kurtosis3.7665306
Mean0.59486017
Median Absolute Deviation (MAD)0
Skewness1.6948421
Sum1574
Variance0.85205675
MonotonicityNot monotonic
2024-05-11T14:40:25.825310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 1675
 
19.2%
1 534
 
6.1%
2 294
 
3.4%
3 126
 
1.4%
4 15
 
0.2%
5 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 6067
69.6%
ValueCountFrequency (%)
0 1675
19.2%
1 534
 
6.1%
2 294
 
3.4%
3 126
 
1.4%
4 15
 
0.2%
5 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
5 1
 
< 0.1%
4 15
 
0.2%
3 126
 
1.4%
2 294
 
3.4%
1 534
 
6.1%
0 1675
19.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
6653 
주택가주변
1152 
기타
 
661
아파트지역
 
172
유흥업소밀집지역
 
60
Other values (2)
 
15

Length

Max length8
Median length4
Mean length4.0346609
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row학교정화(상대)
2nd row주택가주변
3rd row주택가주변
4th row주택가주변
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 6653
76.4%
주택가주변 1152
 
13.2%
기타 661
 
7.6%
아파트지역 172
 
2.0%
유흥업소밀집지역 60
 
0.7%
학교정화(상대) 9
 
0.1%
학교정화(절대) 6
 
0.1%

Length

2024-05-11T14:40:26.047712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:26.252681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6653
76.4%
주택가주변 1152
 
13.2%
기타 661
 
7.6%
아파트지역 172
 
2.0%
유흥업소밀집지역 60
 
0.7%
학교정화(상대 9
 
0.1%
학교정화(절대 6
 
0.1%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
6659 
기타
916 
 
351
지도
 
305
우수
 
281
Other values (2)
 
201

Length

Max length4
Median length4
Mean length3.4806611
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지도
2nd row기타
3rd row지도
4th row지도
5th row지도

Common Values

ValueCountFrequency (%)
<NA> 6659
76.4%
기타 916
 
10.5%
351
 
4.0%
지도 305
 
3.5%
우수 281
 
3.2%
자율 135
 
1.5%
66
 
0.8%

Length

2024-05-11T14:40:26.545069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:26.770009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6659
76.4%
기타 916
 
10.5%
351
 
4.0%
지도 305
 
3.5%
우수 281
 
3.2%
자율 135
 
1.5%
66
 
0.8%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
6881 
상수도전용
1829 
상수도(음용)지하수(주방용)겸용
 
3

Length

Max length17
Median length4
Mean length4.2143923
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6881
79.0%
상수도전용 1829
 
21.0%
상수도(음용)지하수(주방용)겸용 3
 
< 0.1%

Length

2024-05-11T14:40:27.016234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:27.189265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6881
79.0%
상수도전용 1829
 
21.0%
상수도(음용)지하수(주방용)겸용 3
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8347 
0
 
366

Length

Max length4
Median length4
Mean length3.8739814
Min length1

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> 8347
95.8%
0 366
 
4.2%

Length

2024-05-11T14:40:27.380992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:27.550664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8347
95.8%
0 366
 
4.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:27.732645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:27.900123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:28.054041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:28.216115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:28.385249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:28.568275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:28.759667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:28.937135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:29.106605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:29.293788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size68.2 KiB
<NA>
8342 
0
 
371

Length

Max length4
Median length4
Mean length3.8722598
Min length1

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> 8342
95.7%
0 371
 
4.3%

Length

2024-05-11T14:40:29.465964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:40:29.594823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8342
95.7%
0 371
 
4.3%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1969
Missing (%)22.6%
Memory size17.1 KiB
False
6706 
True
 
38
(Missing)
1969 
ValueCountFrequency (%)
False 6706
77.0%
True 38
 
0.4%
(Missing) 1969
 
22.6%
2024-05-11T14:40:29.717745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct2809
Distinct (%)41.7%
Missing1969
Missing (%)22.6%
Infinite0
Infinite (%)0.0%
Mean43.381395
Minimum0
Maximum1069.97
Zeros74
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size76.7 KiB
2024-05-11T14:40:29.907067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q114.9075
median28
Q352.455
95-th percentile132.7265
Maximum1069.97
Range1069.97
Interquartile range (IQR)37.5475

Descriptive statistics

Standard deviation53.882958
Coefficient of variation (CV)1.2420753
Kurtosis64.120565
Mean43.381395
Median Absolute Deviation (MAD)16.66
Skewness5.4895129
Sum292564.13
Variance2903.3732
MonotonicityNot monotonic
2024-05-11T14:40:30.107051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 321
 
3.7%
6.6 219
 
2.5%
33.0 137
 
1.6%
26.4 121
 
1.4%
30.0 90
 
1.0%
10.0 84
 
1.0%
0.0 74
 
0.8%
16.5 74
 
0.8%
9.9 73
 
0.8%
20.0 67
 
0.8%
Other values (2799) 5484
62.9%
(Missing) 1969
 
22.6%
ValueCountFrequency (%)
0.0 74
0.8%
1.0 2
 
< 0.1%
1.1 2
 
< 0.1%
1.33 1
 
< 0.1%
1.5 1
 
< 0.1%
1.56 1
 
< 0.1%
1.6 1
 
< 0.1%
1.61 1
 
< 0.1%
1.69 1
 
< 0.1%
1.8 1
 
< 0.1%
ValueCountFrequency (%)
1069.97 1
< 0.1%
1044.0 1
< 0.1%
964.14 1
< 0.1%
703.92 1
< 0.1%
538.37 1
< 0.1%
532.56 1
< 0.1%
528.0 1
< 0.1%
498.3 1
< 0.1%
488.0 1
< 0.1%
465.82 1
< 0.1%

전통업소지정번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing8712
Missing (%)> 99.9%
Memory size68.2 KiB
2024-05-11T14:40:30.215759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
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

Unique1 ?
Unique (%)100.0%

Sample

1st row]
ValueCountFrequency (%)
1
100.0%
2024-05-11T14:40:30.473424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
] 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Close Punctuation 1
100.0%

Most frequent character per category

Close Punctuation
ValueCountFrequency (%)
] 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
] 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
] 1
100.0%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing8713
Missing (%)100.0%
Memory size76.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032300003230000-104-1904-0112119040808<NA>3폐업2폐업19931231<NA><NA><NA>02046934896.10138863서울특별시 송파구 잠실동 228-9번지<NA><NA>코리아세븐2003-02-25 00:00:00I2018-08-31 23:59:59.0패스트푸드207129.464565444919.982461패스트푸드11학교정화(상대)지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N6.1<NA><NA><NA>
132300003230000-104-1948-0173319480115<NA>3폐업2폐업19950126<NA><NA><NA>020477856147.86138879서울특별시 송파구 풍납동 410-1번지<NA><NA>볼라커피숍2003-05-26 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N47.86<NA><NA><NA>
232300003230000-104-1975-0183319751231<NA>3폐업2폐업19960613<NA><NA><NA>020413210869.90138819서울특별시 송파구 마천동 190-42번지<NA><NA>초원다방2003-05-21 00:00:00I2018-08-31 23:59:59.0과자점213516.620377443907.67229과자점03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N69.9<NA><NA><NA>
332300003230000-104-1976-0191719761012<NA>3폐업2폐업20010305<NA><NA><NA>02 422411077.39138861서울특별시 송파구 잠실동 184-11번지<NA><NA>국제다방2003-05-21 00:00:00I2018-08-31 23:59:59.0다방207486.840733445411.639115다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N77.39<NA><NA><NA>
432300003230000-104-1976-0197619761103<NA>3폐업2폐업19951116<NA><NA><NA>02 4130880105.00138861서울특별시 송파구 잠실동 184-5번지<NA><NA>약속2003-05-20 00:00:00I2018-08-31 23:59:59.0다방207386.680174445464.294872다방02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N105.0<NA><NA><NA>
532300003230000-104-1976-0224819760922<NA>3폐업2폐업19980909<NA><NA><NA>02 4220120159.36138861서울특별시 송파구 잠실동 184-7번지<NA><NA>은성2003-02-25 00:00:00I2018-08-31 23:59:59.0다방207438.254279445455.610915다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N159.36<NA><NA><NA>
632300003230000-104-1977-0193219770915<NA>3폐업2폐업19971122<NA><NA><NA>02 400770589.25138821서울특별시 송파구 마천동 308-31번지<NA><NA>태양다방2003-05-21 00:00:00I2018-08-31 23:59:59.0다방213468.096259443412.865756다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N89.25<NA><NA><NA>
732300003230000-104-1977-0202719770524<NA>3폐업2폐업19951214<NA><NA><NA>02 4220073120.85138861서울특별시 송파구 잠실동 175-7번지<NA><NA>재동2003-05-20 00:00:00I2018-08-31 23:59:59.0과자점206944.17767445484.879944과자점13주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N120.85<NA><NA><NA>
832300003230000-104-1978-0178719780425<NA>3폐업2폐업19960701<NA><NA><NA>02 4000288109.94138819서울특별시 송파구 마천동 127-9번지<NA><NA>삼보2003-05-23 00:00:00I2018-08-31 23:59:59.0과자점213020.821868443891.388218과자점03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N109.94<NA><NA><NA>
932300003230000-104-1978-0192619780209<NA>3폐업2폐업19990112<NA><NA><NA>02 403102371.66138050서울특별시 송파구 방이동 17-1번지<NA><NA>왕천2003-05-21 00:00:00I2018-08-31 23:59:59.0다방210351.496696445172.631396다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N71.66<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
870332300003230000-104-2024-001422024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-881서울특별시 송파구 가락동 600 가락동 농수산물도매시장서울특별시 송파구 양재대로 932, 가락시장 가락몰 (가락동)5699카페비포유2024-05-03 14:24:49I2023-12-05 00:05:00.0기타 휴게음식점209790.959909443481.212174<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870432300003230000-104-2024-001432024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>5.60138-853서울특별시 송파구 송파동 167-1 한영해시안 아파트서울특별시 송파구 오금로32길 35, 상가1층 105호 (송파동, 한영해시안 아파트)5673지에스(GS)25송파해시안점2024-05-07 13:35:51I2023-12-05 00:09:00.0편의점210454.620819444560.998707<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870532300003230000-104-2024-001442024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.84138-934서울특별시 송파구 신천동 29 롯데월드타워앤드롯데월드몰서울특별시 송파구 올림픽로 300, 롯데월드몰 지하1층 (신천동)5551주다호두 롯데월드몰점2024-05-07 13:43:32I2023-12-05 00:09:00.0기타 휴게음식점209074.90084445657.80933<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870632300003230000-104-2024-001452024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.84138-888서울특별시 송파구 문정동 652-5 문정 아이파크서울특별시 송파구 법원로4길 6, 문정 아이파크 1동 1층 122호 (문정동)5855밀탑 문정점2024-05-07 13:59:45I2023-12-05 00:09:00.0커피숍<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870732300003230000-104-2024-001462024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-881서울특별시 송파구 가락동 600 가락동 농수산물도매시장서울특별시 송파구 양재대로 932, 가락동 농수산물도매시장 3층 (가락동)5699(주)빌리엔젤 강남2024-05-07 17:15:00I2023-12-05 00:09:00.0기타 휴게음식점209790.959909443481.212174<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870832300003230000-104-2024-001472024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-736서울특별시 송파구 풍납동 388-1 서울아산병원서울특별시 송파구 올림픽로43길 88, 서울아산병원(동관 Hmart) 지하1층 (풍납동)5505팥붕슈붕2024-05-08 14:19:12I2023-12-04 23:00:00.0기타 휴게음식점209607.590372447120.577229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
870932300003230000-104-2024-001482024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-934서울특별시 송파구 신천동 29 롯데월드타워앤드롯데월드몰서울특별시 송파구 올림픽로 300, 롯데월드타워앤드롯데월드몰 5층 (신천동)5551청232024-05-09 09:09:37I2023-12-04 23:01:00.0기타 휴게음식점209074.90084445657.80933<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
871032300003230000-104-2024-001492024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.88138-854서울특별시 송파구 송파동 194서울특별시 송파구 송파대로38길 6, 1층 102호 (송파동)5676경성찹쌀꽈배기 송파일신여상점2024-05-09 09:56:54I2023-12-04 23:01:00.0일반조리판매209867.274217444283.915571<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
871132300003230000-104-2024-001502024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>138-721서울특별시 송파구 잠실동 40-1 롯데월드서울특별시 송파구 올림픽로 240, 롯데월드 롯데마트 제타플렉스 지하1층 (잠실동)5554담소2024-05-09 13:38:14I2023-12-04 23:01:00.0기타 휴게음식점208589.363343445455.904053<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
871232300003230000-104-2024-001512024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30138-829서울특별시 송파구 방이동 89 올림픽선수기자촌아파트서울특별시 송파구 양재대로 1218, 상가 101, 102호 (방이동, 올림픽선수기자촌아파트)5649지에스(GS)25 송파오륜점2024-05-09 15:16:13I2023-12-04 23:01:00.0편의점211986.297246446156.529775<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>