Overview

Dataset statistics

Number of variables44
Number of observations7896
Missing cells88855
Missing cells (%)25.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory376.0 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
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
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18678/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (58.2%)Imbalance
급수시설구분명 is highly imbalanced (50.3%)Imbalance
총인원 is highly imbalanced (80.6%)Imbalance
본사종업원수 is highly imbalanced (80.0%)Imbalance
공장사무직종업원수 is highly imbalanced (80.0%)Imbalance
공장판매직종업원수 is highly imbalanced (80.0%)Imbalance
공장생산직종업원수 is highly imbalanced (80.0%)Imbalance
보증액 is highly imbalanced (80.0%)Imbalance
월세액 is highly imbalanced (80.0%)Imbalance
다중이용업소여부 is highly imbalanced (90.4%)Imbalance
인허가취소일자 has 7896 (100.0%) missing valuesMissing
폐업일자 has 2213 (28.0%) missing valuesMissing
휴업시작일자 has 7896 (100.0%) missing valuesMissing
휴업종료일자 has 7896 (100.0%) missing valuesMissing
재개업일자 has 7896 (100.0%) missing valuesMissing
전화번호 has 3477 (44.0%) missing valuesMissing
소재지면적 has 110 (1.4%) missing valuesMissing
도로명주소 has 2986 (37.8%) missing valuesMissing
도로명우편번호 has 3040 (38.5%) missing valuesMissing
좌표정보(X) has 641 (8.1%) missing valuesMissing
좌표정보(Y) has 641 (8.1%) missing valuesMissing
남성종사자수 has 4750 (60.2%) missing valuesMissing
여성종사자수 has 4735 (60.0%) missing valuesMissing
건물소유구분명 has 7896 (100.0%) missing valuesMissing
다중이용업소여부 has 1537 (19.5%) missing valuesMissing
시설총규모 has 1537 (19.5%) missing valuesMissing
전통업소지정번호 has 7896 (100.0%) missing valuesMissing
전통업소주된음식 has 7896 (100.0%) missing valuesMissing
홈페이지 has 7896 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 43.69948619)Skewed
시설총규모 is highly skewed (γ1 = 72.75347432)Skewed
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
전통업소지정번호 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 2571 (32.6%) zerosZeros
여성종사자수 has 1813 (23.0%) zerosZeros
시설총규모 has 151 (1.9%) zerosZeros

Reproduction

Analysis started2024-05-11 05:53:01.155308
Analysis finished2024-05-11 05:53:04.276045
Duration3.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
3010000
7896 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3010000
2nd row3010000
3rd row3010000
4th row3010000
5th row3010000

Common Values

ValueCountFrequency (%)
3010000 7896
100.0%

Length

2024-05-11T14:53:04.377206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:04.584306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 7896
100.0%

관리번호
Text

UNIQUE 

Distinct7896
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
2024-05-11T14:53:04.816704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters173712
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

Unique7896 ?
Unique (%)100.0%

Sample

1st row3010000-104-1936-01068
2nd row3010000-104-1965-00200
3rd row3010000-104-1966-00905
4th row3010000-104-1966-00970
5th row3010000-104-1966-00995
ValueCountFrequency (%)
3010000-104-1936-01068 1
 
< 0.1%
3010000-104-2016-00122 1
 
< 0.1%
3010000-104-2016-00120 1
 
< 0.1%
3010000-104-2016-00119 1
 
< 0.1%
3010000-104-2016-00118 1
 
< 0.1%
3010000-104-2016-00117 1
 
< 0.1%
3010000-104-2016-00116 1
 
< 0.1%
3010000-104-2016-00115 1
 
< 0.1%
3010000-104-2016-00114 1
 
< 0.1%
3010000-104-2016-00113 1
 
< 0.1%
Other values (7886) 7886
99.9%
2024-05-11T14:53:05.294755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 73758
42.5%
1 26845
 
15.5%
- 23688
 
13.6%
3 11119
 
6.4%
2 10892
 
6.3%
4 10609
 
6.1%
9 5658
 
3.3%
8 3093
 
1.8%
6 2784
 
1.6%
7 2762
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150024
86.4%
Dash Punctuation 23688
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 73758
49.2%
1 26845
 
17.9%
3 11119
 
7.4%
2 10892
 
7.3%
4 10609
 
7.1%
9 5658
 
3.8%
8 3093
 
2.1%
6 2784
 
1.9%
7 2762
 
1.8%
5 2504
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 23688
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 173712
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 73758
42.5%
1 26845
 
15.5%
- 23688
 
13.6%
3 11119
 
6.4%
2 10892
 
6.3%
4 10609
 
6.1%
9 5658
 
3.3%
8 3093
 
1.8%
6 2784
 
1.6%
7 2762
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173712
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 73758
42.5%
1 26845
 
15.5%
- 23688
 
13.6%
3 11119
 
6.4%
2 10892
 
6.3%
4 10609
 
6.1%
9 5658
 
3.3%
8 3093
 
1.8%
6 2784
 
1.6%
7 2762
 
1.6%
Distinct4986
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
Minimum1936-10-23 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:53:05.484393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:53:05.679868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
3
5683 
1
2213 

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 5683
72.0%
1 2213
 
28.0%

Length

2024-05-11T14:53:05.906827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:06.069399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 5683
72.0%
1 2213
 
28.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
폐업
5683 
영업/정상
2213 

Length

Max length5
Median length2
Mean length2.8408055
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 5683
72.0%
영업/정상 2213
 
28.0%

Length

2024-05-11T14:53:06.241288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:06.422002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5683
72.0%
영업/정상 2213
 
28.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
2
5683 
1
2213 

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 5683
72.0%
1 2213
 
28.0%

Length

2024-05-11T14:53:06.629041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:06.786133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5683
72.0%
1 2213
 
28.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
폐업
5683 
영업
2213 

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 5683
72.0%
영업 2213
 
28.0%

Length

2024-05-11T14:53:06.948961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:07.104463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 5683
72.0%
영업 2213
 
28.0%

폐업일자
Date

MISSING 

Distinct3592
Distinct (%)63.2%
Missing2213
Missing (%)28.0%
Memory size61.8 KiB
Minimum1980-07-06 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T14:53:07.291667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:53:07.491856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

전화번호
Text

MISSING 

Distinct3619
Distinct (%)81.9%
Missing3477
Missing (%)44.0%
Memory size61.8 KiB
2024-05-11T14:53:07.973960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.8167006
Min length1

Characters and Unicode

Total characters43380
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

Unique3418 ?
Unique (%)77.3%

Sample

1st row0207766023
2nd row02 2520892
3rd row0202650534
4th row02 00000
5th row0222675839
ValueCountFrequency (%)
02 2030
30.3%
0200000000 138
 
2.1%
3127776 125
 
1.9%
0 74
 
1.1%
070 45
 
0.7%
031 40
 
0.6%
00000 34
 
0.5%
318 15
 
0.2%
0222901234 11
 
0.2%
032 10
 
0.1%
Other values (3754) 4177
62.4%
2024-05-11T14:53:08.744027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9045
20.9%
2 8800
20.3%
7 4745
10.9%
3 3352
 
7.7%
2990
 
6.9%
5 2873
 
6.6%
6 2708
 
6.2%
1 2677
 
6.2%
8 2309
 
5.3%
4 2035
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40390
93.1%
Space Separator 2990
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9045
22.4%
2 8800
21.8%
7 4745
11.7%
3 3352
 
8.3%
5 2873
 
7.1%
6 2708
 
6.7%
1 2677
 
6.6%
8 2309
 
5.7%
4 2035
 
5.0%
9 1846
 
4.6%
Space Separator
ValueCountFrequency (%)
2990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9045
20.9%
2 8800
20.3%
7 4745
10.9%
3 3352
 
7.7%
2990
 
6.9%
5 2873
 
6.6%
6 2708
 
6.2%
1 2677
 
6.2%
8 2309
 
5.3%
4 2035
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9045
20.9%
2 8800
20.3%
7 4745
10.9%
3 3352
 
7.7%
2990
 
6.9%
5 2873
 
6.6%
6 2708
 
6.2%
1 2677
 
6.2%
8 2309
 
5.3%
4 2035
 
4.7%

소재지면적
Text

MISSING 

Distinct3589
Distinct (%)46.1%
Missing110
Missing (%)1.4%
Memory size61.8 KiB
2024-05-11T14:53:09.327521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8886463
Min length3

Characters and Unicode

Total characters38063
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

Unique2685 ?
Unique (%)34.5%

Sample

1st row111.60
2nd row24.70
3rd row101.14
4th row63.68
5th row141.33
ValueCountFrequency (%)
3.30 389
 
5.0%
6.60 229
 
2.9%
10.00 184
 
2.4%
26.00 152
 
2.0%
9.90 119
 
1.5%
16.50 86
 
1.1%
6.00 82
 
1.1%
33.00 79
 
1.0%
9.00 78
 
1.0%
00 74
 
1.0%
Other values (3579) 6314
81.1%
2024-05-11T14:53:10.096256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7786
20.5%
0 7221
19.0%
1 3696
9.7%
3 3136
8.2%
6 3055
 
8.0%
2 2831
 
7.4%
5 2437
 
6.4%
9 2209
 
5.8%
4 2124
 
5.6%
8 1874
 
4.9%
Other values (2) 1694
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30276
79.5%
Other Punctuation 7787
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7221
23.9%
1 3696
12.2%
3 3136
10.4%
6 3055
10.1%
2 2831
 
9.4%
5 2437
 
8.0%
9 2209
 
7.3%
4 2124
 
7.0%
8 1874
 
6.2%
7 1693
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 7786
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 38063
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7786
20.5%
0 7221
19.0%
1 3696
9.7%
3 3136
8.2%
6 3055
 
8.0%
2 2831
 
7.4%
5 2437
 
6.4%
9 2209
 
5.8%
4 2124
 
5.6%
8 1874
 
4.9%
Other values (2) 1694
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7786
20.5%
0 7221
19.0%
1 3696
9.7%
3 3136
8.2%
6 3055
 
8.0%
2 2831
 
7.4%
5 2437
 
6.4%
9 2209
 
5.8%
4 2124
 
5.6%
8 1874
 
4.9%
Other values (2) 1694
 
4.5%
Distinct350
Distinct (%)4.4%
Missing10
Missing (%)0.1%
Memory size61.8 KiB
2024-05-11T14:53:10.664683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1464621
Min length6

Characters and Unicode

Total characters48471
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

Unique49 ?
Unique (%)0.6%

Sample

1st row100844
2nd row100841
3rd row100142
4th row100814
5th row100195
ValueCountFrequency (%)
100070 684
 
8.7%
100011 662
 
8.4%
100162 235
 
3.0%
100810 215
 
2.7%
100851 207
 
2.6%
100861 154
 
2.0%
100850 132
 
1.7%
100197 110
 
1.4%
100845 106
 
1.3%
100-747 103
 
1.3%
Other values (340) 5278
66.9%
2024-05-11T14:53:11.477233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21095
43.5%
1 12394
25.6%
8 3862
 
8.0%
7 2068
 
4.3%
2 1739
 
3.6%
4 1584
 
3.3%
3 1247
 
2.6%
5 1237
 
2.6%
- 1155
 
2.4%
6 1100
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47316
97.6%
Dash Punctuation 1155
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21095
44.6%
1 12394
26.2%
8 3862
 
8.2%
7 2068
 
4.4%
2 1739
 
3.7%
4 1584
 
3.3%
3 1247
 
2.6%
5 1237
 
2.6%
6 1100
 
2.3%
9 990
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 1155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 48471
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21095
43.5%
1 12394
25.6%
8 3862
 
8.0%
7 2068
 
4.3%
2 1739
 
3.6%
4 1584
 
3.3%
3 1247
 
2.6%
5 1237
 
2.6%
- 1155
 
2.4%
6 1100
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48471
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21095
43.5%
1 12394
25.6%
8 3862
 
8.0%
7 2068
 
4.3%
2 1739
 
3.6%
4 1584
 
3.3%
3 1247
 
2.6%
5 1237
 
2.6%
- 1155
 
2.4%
6 1100
 
2.3%
Distinct5397
Distinct (%)68.4%
Missing10
Missing (%)0.1%
Memory size61.8 KiB
2024-05-11T14:53:11.808478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length54
Mean length25.975907
Min length13

Characters and Unicode

Total characters204846
Distinct characters442
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4798 ?
Unique (%)60.8%

Sample

1st row서울특별시 중구 을지로2가 18-3번지
2nd row서울특별시 중구 신당동 369-0번지
3rd row서울특별시 중구 의주로2가 92-1번지
4th row서울특별시 중구 서소문동 84-1번지
5th row서울특별시 중구 을지로5가 273-4번지
ValueCountFrequency (%)
서울특별시 7886
20.1%
중구 7886
20.1%
1층 1006
 
2.6%
지하1층 950
 
2.4%
충무로1가 929
 
2.4%
신당동 783
 
2.0%
소공동 779
 
2.0%
1번지 461
 
1.2%
을지로6가 448
 
1.1%
롯데백화점 413
 
1.1%
Other values (4616) 17776
45.2%
2024-05-11T14:53:12.398544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37765
18.4%
1 11553
 
5.6%
9187
 
4.5%
8299
 
4.1%
8179
 
4.0%
8077
 
3.9%
8059
 
3.9%
8058
 
3.9%
7893
 
3.9%
7888
 
3.9%
Other values (432) 89888
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120573
58.9%
Space Separator 37765
 
18.4%
Decimal Number 36934
 
18.0%
Dash Punctuation 6017
 
2.9%
Open Punctuation 1186
 
0.6%
Close Punctuation 1185
 
0.6%
Uppercase Letter 637
 
0.3%
Other Punctuation 338
 
0.2%
Lowercase Letter 139
 
0.1%
Math Symbol 68
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9187
 
7.6%
8299
 
6.9%
8179
 
6.8%
8077
 
6.7%
8059
 
6.7%
8058
 
6.7%
7893
 
6.5%
7888
 
6.5%
5647
 
4.7%
5117
 
4.2%
Other values (371) 44169
36.6%
Uppercase Letter
ValueCountFrequency (%)
D 128
20.1%
B 94
14.8%
P 69
10.8%
A 49
 
7.7%
C 33
 
5.2%
T 29
 
4.6%
E 27
 
4.2%
G 25
 
3.9%
S 24
 
3.8%
R 18
 
2.8%
Other values (13) 141
22.1%
Lowercase Letter
ValueCountFrequency (%)
n 24
17.3%
e 22
15.8%
i 20
14.4%
a 18
12.9%
r 9
 
6.5%
t 7
 
5.0%
s 7
 
5.0%
o 6
 
4.3%
l 5
 
3.6%
c 5
 
3.6%
Other values (6) 16
11.5%
Decimal Number
ValueCountFrequency (%)
1 11553
31.3%
2 7003
19.0%
5 3952
 
10.7%
3 2911
 
7.9%
0 2527
 
6.8%
4 2183
 
5.9%
6 2069
 
5.6%
7 1825
 
4.9%
8 1535
 
4.2%
9 1376
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 298
88.2%
. 31
 
9.2%
? 4
 
1.2%
/ 3
 
0.9%
# 1
 
0.3%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
37765
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6017
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1185
100.0%
Math Symbol
ValueCountFrequency (%)
~ 68
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120572
58.9%
Common 83497
40.8%
Latin 776
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9187
 
7.6%
8299
 
6.9%
8179
 
6.8%
8077
 
6.7%
8059
 
6.7%
8058
 
6.7%
7893
 
6.5%
7888
 
6.5%
5647
 
4.7%
5117
 
4.2%
Other values (370) 44168
36.6%
Latin
ValueCountFrequency (%)
D 128
16.5%
B 94
 
12.1%
P 69
 
8.9%
A 49
 
6.3%
C 33
 
4.3%
T 29
 
3.7%
E 27
 
3.5%
G 25
 
3.2%
S 24
 
3.1%
n 24
 
3.1%
Other values (29) 274
35.3%
Common
ValueCountFrequency (%)
37765
45.2%
1 11553
 
13.8%
2 7003
 
8.4%
- 6017
 
7.2%
5 3952
 
4.7%
3 2911
 
3.5%
0 2527
 
3.0%
4 2183
 
2.6%
6 2069
 
2.5%
7 1825
 
2.2%
Other values (12) 5692
 
6.8%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120571
58.9%
ASCII 84269
41.1%
CJK Compat 4
 
< 0.1%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37765
44.8%
1 11553
 
13.7%
2 7003
 
8.3%
- 6017
 
7.1%
5 3952
 
4.7%
3 2911
 
3.5%
0 2527
 
3.0%
4 2183
 
2.6%
6 2069
 
2.5%
7 1825
 
2.2%
Other values (50) 6464
 
7.7%
Hangul
ValueCountFrequency (%)
9187
 
7.6%
8299
 
6.9%
8179
 
6.8%
8077
 
6.7%
8059
 
6.7%
8058
 
6.7%
7893
 
6.5%
7888
 
6.5%
5647
 
4.7%
5117
 
4.2%
Other values (369) 44167
36.6%
CJK Compat
ValueCountFrequency (%)
4
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct3350
Distinct (%)68.2%
Missing2986
Missing (%)37.8%
Memory size61.8 KiB
2024-05-11T14:53:12.819372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length58
Mean length33.121181
Min length20

Characters and Unicode

Total characters162625
Distinct characters422
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3069 ?
Unique (%)62.5%

Sample

1st row서울특별시 중구 을지로35길 35 (주교동)
2nd row서울특별시 중구 장충단로13길 7 (을지로6가)
3rd row서울특별시 중구 세종대로 13 (남대문로5가)
4th row서울특별시 중구 수표로 30 (저동2가)
5th row서울특별시 중구 을지로 170 (을지로4가)
ValueCountFrequency (%)
서울특별시 4910
 
15.3%
중구 4910
 
15.3%
1층 1424
 
4.4%
지하1층 1174
 
3.7%
충무로1가 591
 
1.8%
소공로 584
 
1.8%
63 546
 
1.7%
남대문로 541
 
1.7%
소공동 483
 
1.5%
81 458
 
1.4%
Other values (2690) 16407
51.2%
2024-05-11T14:53:13.513710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27162
 
16.7%
1 8510
 
5.2%
6560
 
4.0%
5421
 
3.3%
( 5400
 
3.3%
) 5399
 
3.3%
, 5266
 
3.2%
5213
 
3.2%
5140
 
3.2%
5122
 
3.1%
Other values (412) 83432
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93573
57.5%
Space Separator 27162
 
16.7%
Decimal Number 24298
 
14.9%
Open Punctuation 5400
 
3.3%
Close Punctuation 5399
 
3.3%
Other Punctuation 5296
 
3.3%
Uppercase Letter 756
 
0.5%
Dash Punctuation 536
 
0.3%
Lowercase Letter 141
 
0.1%
Math Symbol 64
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6560
 
7.0%
5421
 
5.8%
5213
 
5.6%
5140
 
5.5%
5122
 
5.5%
5021
 
5.4%
4919
 
5.3%
4918
 
5.3%
4210
 
4.5%
3723
 
4.0%
Other values (353) 43326
46.3%
Uppercase Letter
ValueCountFrequency (%)
D 181
23.9%
B 129
17.1%
P 95
12.6%
A 59
 
7.8%
C 30
 
4.0%
T 30
 
4.0%
E 27
 
3.6%
S 25
 
3.3%
G 21
 
2.8%
F 18
 
2.4%
Other values (13) 141
18.7%
Lowercase Letter
ValueCountFrequency (%)
n 24
17.0%
e 22
15.6%
i 20
14.2%
a 18
12.8%
r 9
 
6.4%
s 7
 
5.0%
t 7
 
5.0%
o 6
 
4.3%
c 6
 
4.3%
l 5
 
3.5%
Other values (6) 17
12.1%
Decimal Number
ValueCountFrequency (%)
1 8510
35.0%
2 3882
16.0%
3 2439
 
10.0%
6 1884
 
7.8%
0 1598
 
6.6%
4 1587
 
6.5%
8 1441
 
5.9%
5 1167
 
4.8%
7 1151
 
4.7%
9 639
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 5266
99.4%
. 21
 
0.4%
? 5
 
0.1%
/ 2
 
< 0.1%
# 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
27162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5400
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 536
100.0%
Math Symbol
ValueCountFrequency (%)
~ 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93573
57.5%
Common 68155
41.9%
Latin 897
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6560
 
7.0%
5421
 
5.8%
5213
 
5.6%
5140
 
5.5%
5122
 
5.5%
5021
 
5.4%
4919
 
5.3%
4918
 
5.3%
4210
 
4.5%
3723
 
4.0%
Other values (353) 43326
46.3%
Latin
ValueCountFrequency (%)
D 181
20.2%
B 129
14.4%
P 95
 
10.6%
A 59
 
6.6%
C 30
 
3.3%
T 30
 
3.3%
E 27
 
3.0%
S 25
 
2.8%
n 24
 
2.7%
e 22
 
2.5%
Other values (29) 275
30.7%
Common
ValueCountFrequency (%)
27162
39.9%
1 8510
 
12.5%
( 5400
 
7.9%
) 5399
 
7.9%
, 5266
 
7.7%
2 3882
 
5.7%
3 2439
 
3.6%
6 1884
 
2.8%
0 1598
 
2.3%
4 1587
 
2.3%
Other values (10) 5028
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93573
57.5%
ASCII 69052
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
27162
39.3%
1 8510
 
12.3%
( 5400
 
7.8%
) 5399
 
7.8%
, 5266
 
7.6%
2 3882
 
5.6%
3 2439
 
3.5%
6 1884
 
2.7%
0 1598
 
2.3%
4 1587
 
2.3%
Other values (49) 5925
 
8.6%
Hangul
ValueCountFrequency (%)
6560
 
7.0%
5421
 
5.8%
5213
 
5.6%
5140
 
5.5%
5122
 
5.5%
5021
 
5.4%
4919
 
5.3%
4918
 
5.3%
4210
 
4.5%
3723
 
4.0%
Other values (353) 43326
46.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)2.8%
Missing3040
Missing (%)38.5%
Infinite0
Infinite (%)0.0%
Mean4551.591
Minimum4500
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:13.734603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4500
5-th percentile4509
Q14530
median4536
Q34566
95-th percentile4627
Maximum4637
Range137
Interquartile range (IQR)36

Descriptive statistics

Standard deviation34.178612
Coefficient of variation (CV)0.007509157
Kurtosis0.082895678
Mean4551.591
Median Absolute Deviation (MAD)19
Skewness0.98250358
Sum22102526
Variance1168.1775
MonotonicityNot monotonic
2024-05-11T14:53:14.177002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4530 610
 
7.7%
4533 498
 
6.3%
4509 211
 
2.7%
4563 206
 
2.6%
4566 186
 
2.4%
4536 164
 
2.1%
4534 83
 
1.1%
4564 77
 
1.0%
4637 70
 
0.9%
4537 68
 
0.9%
Other values (124) 2683
34.0%
(Missing) 3040
38.5%
ValueCountFrequency (%)
4500 11
 
0.1%
4501 11
 
0.1%
4502 12
 
0.2%
4503 5
 
0.1%
4504 4
 
0.1%
4505 24
 
0.3%
4506 7
 
0.1%
4507 6
 
0.1%
4508 9
 
0.1%
4509 211
2.7%
ValueCountFrequency (%)
4637 70
0.9%
4635 11
 
0.1%
4634 17
 
0.2%
4633 9
 
0.1%
4632 18
 
0.2%
4631 63
0.8%
4630 17
 
0.2%
4629 25
 
0.3%
4628 6
 
0.1%
4627 20
 
0.3%
Distinct6688
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
2024-05-11T14:53:14.551013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length6.9435157
Min length1

Characters and Unicode

Total characters54826
Distinct characters1007
Distinct categories14 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6024 ?
Unique (%)76.3%

Sample

1st row정동
2nd row장군
3rd row은호
4th row수련
5th row수도
ValueCountFrequency (%)
카페 106
 
1.0%
세븐일레븐 100
 
0.9%
gs25 82
 
0.8%
씨유 67
 
0.6%
스타벅스 67
 
0.6%
명동점 65
 
0.6%
주식회사 63
 
0.6%
커피 44
 
0.4%
본점 44
 
0.4%
리은푸드 39
 
0.4%
Other values (7076) 10155
93.8%
2024-05-11T14:53:15.093742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2947
 
5.4%
1817
 
3.3%
1798
 
3.3%
) 1191
 
2.2%
( 1186
 
2.2%
1136
 
2.1%
1034
 
1.9%
825
 
1.5%
725
 
1.3%
723
 
1.3%
Other values (997) 41444
75.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 43559
79.4%
Space Separator 2947
 
5.4%
Uppercase Letter 2172
 
4.0%
Lowercase Letter 2115
 
3.9%
Decimal Number 1443
 
2.6%
Close Punctuation 1192
 
2.2%
Open Punctuation 1187
 
2.2%
Other Punctuation 159
 
0.3%
Dash Punctuation 29
 
0.1%
Connector Punctuation 12
 
< 0.1%
Other values (4) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1817
 
4.2%
1798
 
4.1%
1136
 
2.6%
1034
 
2.4%
825
 
1.9%
725
 
1.7%
723
 
1.7%
722
 
1.7%
663
 
1.5%
639
 
1.5%
Other values (912) 33477
76.9%
Uppercase Letter
ValueCountFrequency (%)
S 230
 
10.6%
C 197
 
9.1%
G 186
 
8.6%
E 167
 
7.7%
A 149
 
6.9%
O 118
 
5.4%
B 113
 
5.2%
T 96
 
4.4%
P 93
 
4.3%
F 91
 
4.2%
Other values (16) 732
33.7%
Lowercase Letter
ValueCountFrequency (%)
e 366
17.3%
a 230
10.9%
o 187
 
8.8%
f 180
 
8.5%
r 116
 
5.5%
n 115
 
5.4%
i 114
 
5.4%
c 114
 
5.4%
s 103
 
4.9%
t 92
 
4.3%
Other values (15) 498
23.5%
Decimal Number
ValueCountFrequency (%)
2 416
28.8%
1 230
15.9%
5 218
15.1%
9 175
12.1%
0 92
 
6.4%
3 89
 
6.2%
4 79
 
5.5%
7 56
 
3.9%
8 52
 
3.6%
6 36
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 49
30.8%
& 44
27.7%
' 29
18.2%
? 16
 
10.1%
, 8
 
5.0%
# 6
 
3.8%
/ 2
 
1.3%
! 2
 
1.3%
2
 
1.3%
: 1
 
0.6%
Math Symbol
ValueCountFrequency (%)
+ 3
50.0%
| 1
 
16.7%
< 1
 
16.7%
> 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 1191
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1186
99.9%
[ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2947
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 12
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 2
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 43548
79.4%
Common 6979
 
12.7%
Latin 4288
 
7.8%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1817
 
4.2%
1798
 
4.1%
1136
 
2.6%
1034
 
2.4%
825
 
1.9%
725
 
1.7%
723
 
1.7%
722
 
1.7%
663
 
1.5%
639
 
1.5%
Other values (901) 33466
76.8%
Latin
ValueCountFrequency (%)
e 366
 
8.5%
a 230
 
5.4%
S 230
 
5.4%
C 197
 
4.6%
o 187
 
4.4%
G 186
 
4.3%
f 180
 
4.2%
E 167
 
3.9%
A 149
 
3.5%
O 118
 
2.8%
Other values (42) 2278
53.1%
Common
ValueCountFrequency (%)
2947
42.2%
) 1191
17.1%
( 1186
17.0%
2 416
 
6.0%
1 230
 
3.3%
5 218
 
3.1%
9 175
 
2.5%
0 92
 
1.3%
3 89
 
1.3%
4 79
 
1.1%
Other values (23) 356
 
5.1%
Han
ValueCountFrequency (%)
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 43544
79.4%
ASCII 11262
 
20.5%
CJK 10
 
< 0.1%
Compat Jamo 4
 
< 0.1%
None 4
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2947
26.2%
) 1191
 
10.6%
( 1186
 
10.5%
2 416
 
3.7%
e 366
 
3.2%
a 230
 
2.0%
1 230
 
2.0%
S 230
 
2.0%
5 218
 
1.9%
C 197
 
1.7%
Other values (72) 4051
36.0%
Hangul
ValueCountFrequency (%)
1817
 
4.2%
1798
 
4.1%
1136
 
2.6%
1034
 
2.4%
825
 
1.9%
725
 
1.7%
723
 
1.7%
722
 
1.7%
663
 
1.5%
639
 
1.5%
Other values (899) 33462
76.8%
Compat Jamo
ValueCountFrequency (%)
2
50.0%
2
50.0%
None
ValueCountFrequency (%)
² 2
50.0%
2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Distinct5766
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
Minimum1999-01-27 00:00:00
Maximum2024-05-09 17:06:19
2024-05-11T14:53:15.276489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:53:15.529559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
I
5555 
U
2341 

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 5555
70.4%
U 2341
29.6%

Length

2024-05-11T14:53:15.805586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:15.970685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 5555
70.4%
u 2341
29.6%
Distinct1247
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:53:16.131478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:53:16.350931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
커피숍
1978 
다방
1600 
일반조리판매
1197 
기타 휴게음식점
1063 
편의점
441 
Other values (11)
1617 

Length

Max length8
Median length6
Mean length4.0881459
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row다방
2nd row일반조리판매
3rd row다방
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
커피숍 1978
25.1%
다방 1600
20.3%
일반조리판매 1197
15.2%
기타 휴게음식점 1063
13.5%
편의점 441
 
5.6%
백화점 425
 
5.4%
과자점 415
 
5.3%
패스트푸드 325
 
4.1%
푸드트럭 168
 
2.1%
철도역구내 149
 
1.9%
Other values (6) 135
 
1.7%

Length

2024-05-11T14:53:16.571634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1978
22.1%
다방 1600
17.9%
일반조리판매 1197
13.4%
기타 1063
11.9%
휴게음식점 1063
11.9%
편의점 441
 
4.9%
백화점 425
 
4.7%
과자점 415
 
4.6%
패스트푸드 325
 
3.6%
푸드트럭 168
 
1.9%
Other values (7) 284
 
3.2%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2466
Distinct (%)34.0%
Missing641
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean199037.53
Minimum196606.64
Maximum202207.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:16.773469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196606.64
5-th percentile197243.22
Q1198259.65
median198521.02
Q3200131.47
95-th percentile201421.46
Maximum202207.97
Range5601.3304
Interquartile range (IQR)1871.8177

Descriptive statistics

Standard deviation1294.2761
Coefficient of variation (CV)0.0065026738
Kurtosis-0.77086966
Mean199037.53
Median Absolute Deviation (MAD)693.80875
Skewness0.60840608
Sum1.4440173 × 109
Variance1675150.7
MonotonicityNot monotonic
2024-05-11T14:53:16.961376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198259.65357739 722
 
9.1%
198263.90839194 639
 
8.1%
197243.215346366 170
 
2.2%
200613.510297669 144
 
1.8%
198253.896034899 99
 
1.3%
201010.262527 89
 
1.1%
198418.741655644 83
 
1.1%
200703.625559248 77
 
1.0%
197230.206089772 62
 
0.8%
201823.908977364 56
 
0.7%
Other values (2456) 5114
64.8%
(Missing) 641
 
8.1%
ValueCountFrequency (%)
196606.636582259 1
 
< 0.1%
196619.953130724 1
 
< 0.1%
196632.663625144 1
 
< 0.1%
196652.500708538 1
 
< 0.1%
196655.581895878 3
< 0.1%
196662.44522421 1
 
< 0.1%
196691.269917831 1
 
< 0.1%
196697.116895888 4
0.1%
196700.055871163 3
< 0.1%
196709.823390756 1
 
< 0.1%
ValueCountFrequency (%)
202207.966958973 1
< 0.1%
202173.151048935 1
< 0.1%
202131.747052459 1
< 0.1%
202128.136971071 2
< 0.1%
202081.929309726 1
< 0.1%
202069.003734613 1
< 0.1%
202067.813447095 1
< 0.1%
202052.773390411 1
< 0.1%
202013.322106429 1
< 0.1%
201993.235429752 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2467
Distinct (%)34.0%
Missing641
Missing (%)8.1%
Infinite0
Infinite (%)0.0%
Mean451195.66
Minimum449562.22
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:17.172051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449562.22
5-th percentile450426.62
Q1450960.76
median451237.17
Q3451494.7
95-th percentile451836.46
Maximum452076.82
Range2514.5998
Interquartile range (IQR)533.93474

Descriptive statistics

Standard deviation435.75511
Coefficient of variation (CV)0.00096577858
Kurtosis0.49307452
Mean451195.66
Median Absolute Deviation (MAD)276.40563
Skewness-0.55597247
Sum3.2734245 × 109
Variance189882.51
MonotonicityNot monotonic
2024-05-11T14:53:17.416044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451392.198218657 722
 
9.1%
450960.762964932 639
 
8.1%
450655.104239931 170
 
2.2%
451817.515366883 144
 
1.8%
450905.28446798 99
 
1.3%
451995.163058 89
 
1.1%
451237.168596152 83
 
1.1%
451836.458256618 77
 
1.0%
450446.684395506 62
 
0.8%
451624.092552007 56
 
0.7%
Other values (2457) 5114
64.8%
(Missing) 641
 
8.1%
ValueCountFrequency (%)
449562.218888591 4
 
0.1%
449582.535532427 1
 
< 0.1%
449611.221496994 1
 
< 0.1%
449636.902522046 1
 
< 0.1%
449638.824308081 22
0.3%
449646.639622415 1
 
< 0.1%
449668.334731592 1
 
< 0.1%
449670.613249189 2
 
< 0.1%
449687.143213423 5
 
0.1%
449701.767704298 1
 
< 0.1%
ValueCountFrequency (%)
452076.818664092 56
0.7%
452026.206096556 1
 
< 0.1%
452010.293409273 1
 
< 0.1%
452008.928365747 1
 
< 0.1%
452008.363110583 1
 
< 0.1%
452004.220606602 1
 
< 0.1%
452001.282161008 1
 
< 0.1%
452000.627548961 1
 
< 0.1%
451995.163058 89
1.1%
451979.752939172 2
 
< 0.1%

위생업태명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
다방
1581 
<NA>
1537 
커피숍
1339 
일반조리판매
1062 
기타 휴게음식점
725 
Other values (12)
1652 

Length

Max length8
Median length6
Mean length3.9946809
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row다방
2nd row일반조리판매
3rd row다방
4th row다방
5th row다방

Common Values

ValueCountFrequency (%)
다방 1581
20.0%
<NA> 1537
19.5%
커피숍 1339
17.0%
일반조리판매 1062
13.4%
기타 휴게음식점 725
9.2%
과자점 408
 
5.2%
백화점 322
 
4.1%
편의점 296
 
3.7%
패스트푸드 283
 
3.6%
철도역구내 148
 
1.9%
Other values (7) 195
 
2.5%

Length

2024-05-11T14:53:17.626524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다방 1581
18.3%
na 1537
17.8%
커피숍 1339
15.5%
일반조리판매 1062
12.3%
기타 725
8.4%
휴게음식점 725
8.4%
과자점 408
 
4.7%
백화점 322
 
3.7%
편의점 296
 
3.4%
패스트푸드 283
 
3.3%
Other values (8) 343
 
4.0%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.3%
Missing4750
Missing (%)60.2%
Infinite0
Infinite (%)0.0%
Mean0.2927527
Minimum0
Maximum93
Zeros2571
Zeros (%)32.6%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:17.806473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.802081
Coefficient of variation (CV)6.1556426
Kurtosis2230.2415
Mean0.2927527
Median Absolute Deviation (MAD)0
Skewness43.699486
Sum921
Variance3.2474959
MonotonicityNot monotonic
2024-05-11T14:53:17.980795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 2571
32.6%
1 410
 
5.2%
2 120
 
1.5%
3 27
 
0.3%
4 9
 
0.1%
5 5
 
0.1%
12 3
 
< 0.1%
93 1
 
< 0.1%
(Missing) 4750
60.2%
ValueCountFrequency (%)
0 2571
32.6%
1 410
 
5.2%
2 120
 
1.5%
3 27
 
0.3%
4 9
 
0.1%
5 5
 
0.1%
12 3
 
< 0.1%
93 1
 
< 0.1%
ValueCountFrequency (%)
93 1
 
< 0.1%
12 3
 
< 0.1%
5 5
 
0.1%
4 9
 
0.1%
3 27
 
0.3%
2 120
 
1.5%
1 410
 
5.2%
0 2571
32.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)0.3%
Missing4735
Missing (%)60.0%
Infinite0
Infinite (%)0.0%
Mean1.1192661
Minimum0
Maximum12
Zeros1813
Zeros (%)23.0%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:18.173294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum12
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4866534
Coefficient of variation (CV)1.3282395
Kurtosis2.4750648
Mean1.1192661
Median Absolute Deviation (MAD)0
Skewness1.2608345
Sum3538
Variance2.2101382
MonotonicityNot monotonic
2024-05-11T14:53:18.362324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 1813
 
23.0%
3 605
 
7.7%
2 391
 
5.0%
1 187
 
2.4%
4 121
 
1.5%
5 26
 
0.3%
7 6
 
0.1%
6 6
 
0.1%
10 3
 
< 0.1%
12 2
 
< 0.1%
(Missing) 4735
60.0%
ValueCountFrequency (%)
0 1813
23.0%
1 187
 
2.4%
2 391
 
5.0%
3 605
 
7.7%
4 121
 
1.5%
5 26
 
0.3%
6 6
 
0.1%
7 6
 
0.1%
8 1
 
< 0.1%
10 3
 
< 0.1%
ValueCountFrequency (%)
12 2
 
< 0.1%
10 3
 
< 0.1%
8 1
 
< 0.1%
7 6
 
0.1%
6 6
 
0.1%
5 26
 
0.3%
4 121
 
1.5%
3 605
7.7%
2 391
5.0%
1 187
 
2.4%

영업장주변구분명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
5353 
기타
1998 
유흥업소밀집지역
 
339
아파트지역
 
113
주택가주변
 
66
Other values (3)
 
27

Length

Max length8
Median length4
Mean length3.7009878
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5353
67.8%
기타 1998
 
25.3%
유흥업소밀집지역 339
 
4.3%
아파트지역 113
 
1.4%
주택가주변 66
 
0.8%
학교정화(상대) 13
 
0.2%
결혼예식장주변 8
 
0.1%
학교정화(절대) 6
 
0.1%

Length

2024-05-11T14:53:18.572313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:18.768335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5353
67.8%
기타 1998
 
25.3%
유흥업소밀집지역 339
 
4.3%
아파트지역 113
 
1.4%
주택가주변 66
 
0.8%
학교정화(상대 13
 
0.2%
결혼예식장주변 8
 
0.1%
학교정화(절대 6
 
0.1%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
5462 
기타
895 
지도
735 
 
265
우수
 
196
Other values (3)
 
343

Length

Max length4
Median length4
Mean length3.3304205
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5462
69.2%
기타 895
 
11.3%
지도 735
 
9.3%
265
 
3.4%
우수 196
 
2.5%
자율 187
 
2.4%
154
 
2.0%
관리 2
 
< 0.1%

Length

2024-05-11T14:53:18.981353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:19.177200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5462
69.2%
기타 895
 
11.3%
지도 735
 
9.3%
265
 
3.4%
우수 196
 
2.5%
자율 187
 
2.4%
154
 
2.0%
관리 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
4499 
상수도전용
3392 
상수도(음용)지하수(주방용)겸용
 
4
간이상수도
 
1

Length

Max length17
Median length4
Mean length4.4362969
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4499
57.0%
상수도전용 3392
43.0%
상수도(음용)지하수(주방용)겸용 4
 
0.1%
간이상수도 1
 
< 0.1%

Length

2024-05-11T14:53:19.408591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:19.607531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4499
57.0%
상수도전용 3392
43.0%
상수도(음용)지하수(주방용)겸용 4
 
0.1%
간이상수도 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7660 
0
 
236

Length

Max length4
Median length4
Mean length3.9103343
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> 7660
97.0%
0 236
 
3.0%

Length

2024-05-11T14:53:19.818951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:19.979052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7660
97.0%
0 236
 
3.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:20.153100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:20.351921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:20.522624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:20.685740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:20.842423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:21.000624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:21.163442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:21.307172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:21.475631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:21.625830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size61.8 KiB
<NA>
7650 
0
 
246

Length

Max length4
Median length4
Mean length3.906535
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> 7650
96.9%
0 246
 
3.1%

Length

2024-05-11T14:53:21.768820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:53:21.946644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 7650
96.9%
0 246
 
3.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1537
Missing (%)19.5%
Memory size15.6 KiB
False
6280 
True
 
79
(Missing)
1537 
ValueCountFrequency (%)
False 6280
79.5%
True 79
 
1.0%
(Missing) 1537
 
19.5%
2024-05-11T14:53:22.073449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct3186
Distinct (%)50.1%
Missing1537
Missing (%)19.5%
Infinite0
Infinite (%)0.0%
Mean54.331999
Minimum0
Maximum20012.82
Zeros151
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size69.5 KiB
2024-05-11T14:53:22.235366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q110.56
median29.58
Q369.42
95-th percentile166.081
Maximum20012.82
Range20012.82
Interquartile range (IQR)58.86

Descriptive statistics

Standard deviation258.15367
Coefficient of variation (CV)4.7514113
Kurtosis5621.621
Mean54.331999
Median Absolute Deviation (MAD)22.88
Skewness72.753474
Sum345497.18
Variance66643.317
MonotonicityNot monotonic
2024-05-11T14:53:22.462430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 227
 
2.9%
6.6 154
 
2.0%
0.0 151
 
1.9%
26.0 149
 
1.9%
10.0 131
 
1.7%
9.9 83
 
1.1%
16.5 72
 
0.9%
33.0 55
 
0.7%
13.2 52
 
0.7%
5.0 52
 
0.7%
Other values (3176) 5233
66.3%
(Missing) 1537
 
19.5%
ValueCountFrequency (%)
0.0 151
1.9%
0.92 1
 
< 0.1%
0.99 2
 
< 0.1%
1.0 4
 
0.1%
1.35 1
 
< 0.1%
1.5 2
 
< 0.1%
1.65 4
 
0.1%
1.69 1
 
< 0.1%
1.8 1
 
< 0.1%
1.86 1
 
< 0.1%
ValueCountFrequency (%)
20012.82 1
< 0.1%
901.89 1
< 0.1%
900.0 1
< 0.1%
600.66 1
< 0.1%
582.84 1
< 0.1%
569.32 1
< 0.1%
567.04 1
< 0.1%
565.41 1
< 0.1%
559.4 1
< 0.1%
551.0 1
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7896
Missing (%)100.0%
Memory size69.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-104-1936-0106819361023<NA>3폐업2폐업19960620<NA><NA><NA>0207766023111.60100844서울특별시 중구 을지로2가 18-3번지<NA><NA>정동2001-10-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방02기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N111.6<NA><NA><NA>
130100003010000-104-1965-0020019650724<NA>3폐업2폐업19960112<NA><NA><NA>02 252089224.70100841서울특별시 중구 신당동 369-0번지<NA><NA>장군2001-10-08 00:00:00I2018-08-31 23:59:59.0일반조리판매<NA><NA>일반조리판매00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N24.7<NA><NA><NA>
230100003010000-104-1966-0090519660720<NA>3폐업2폐업19900706<NA><NA><NA>0202650534101.14100142서울특별시 중구 의주로2가 92-1번지<NA><NA>은호2001-10-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N101.14<NA><NA><NA>
330100003010000-104-1966-0097019660912<NA>3폐업2폐업19961010<NA><NA><NA>02 0000063.68100814서울특별시 중구 서소문동 84-1번지<NA><NA>수련2001-10-08 00:00:00I2018-08-31 23:59:59.0다방197747.653908451221.062411다방00기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.68<NA><NA><NA>
430100003010000-104-1966-0099519660630<NA>3폐업2폐업20031010<NA><NA><NA>0222675839141.33100195서울특별시 중구 을지로5가 273-4번지<NA><NA>수도2003-03-10 00:00:00I2018-08-31 23:59:59.0다방200096.930688451569.929638다방03결혼예식장주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N141.33<NA><NA><NA>
530100003010000-104-1966-0103719660921<NA>3폐업2폐업20031017<NA><NA><NA>020778564871.08100093서울특별시 중구 남대문로3가 30-7번지<NA><NA>은자다방2002-07-29 00:00:00I2018-08-31 23:59:59.0다방197977.904481450946.759938다방03기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N71.08<NA><NA><NA>
630100003010000-104-1966-0103819660620<NA>3폐업2폐업20071120<NA><NA><NA>020753472478.49100093서울특별시 중구 남대문로3가 92-2번지<NA><NA>푸른들2001-10-08 00:00:00I2018-08-31 23:59:59.0다방198011.936183451004.121399다방03기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N78.49<NA><NA><NA>
730100003010000-104-1966-0111619661201<NA>3폐업2폐업19890719<NA><NA><NA>0200000000105.00100200서울특별시 중구 삼각동 113-0번지<NA><NA>로방2001-10-08 00:00:00I2018-08-31 23:59:59.0다방198446.349545451684.80853다방02아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N105.0<NA><NA><NA>
830100003010000-104-1966-0114019661220<NA>3폐업2폐업19951101<NA><NA><NA>02 235567479.50100420서울특별시 중구 무학동 50-2번지<NA><NA>오두막2001-10-08 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방12기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N79.5<NA><NA><NA>
930100003010000-104-1966-0124319660725<NA>3폐업2폐업20030402<NA><NA><NA>02 393405265.28100858서울특별시 중구 중림동 67-0번지 68<NA><NA>남지다방2000-06-23 00:00:00I2018-08-31 23:59:59.0다방197185.178806450729.302107다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.28<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
788630100003010000-104-2024-001292024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530리은푸드2024-04-30 10:08:38I2023-12-05 00:02:00.0백화점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
788730100003010000-104-2024-001302024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530감동푸드2024-04-30 15:17:07I2023-12-05 00:02:00.0백화점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
788830100003010000-104-2024-001312024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530엘리스파이2024-05-02 13:16:45I2023-12-05 00:04:00.0기타 휴게음식점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
788930100003010000-104-2024-001322024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.20100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지1층 (소공동)4533삼진식품(주)2024-05-02 16:22:17I2023-12-05 00:04:00.0일반조리판매198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789030100003010000-104-2024-001332024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.00100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530미당2024-05-03 09:21:28I2023-12-05 00:05:00.0기타 휴게음식점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789130100003010000-104-2024-001342024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.90100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지1층 (충무로1가)4530주식회사 지오에프앤씨2024-05-07 14:58:07I2023-12-05 00:09:00.0기타 휴게음식점198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789230100003010000-104-2024-001352024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.00100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지1층 (소공동)4533유키모찌 롯데백화점 본점2024-05-08 13:22:25I2023-12-04 23:00:00.0기타 휴게음식점198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789330100003010000-104-2024-001362024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.48100-281서울특별시 중구 인현동1가 158 남산센트럴뷰 스위트서울특별시 중구 충무로 24, 남산센트럴뷰 스위트 1층 103호 (인현동1가)4556카페요아정 을지로점2024-05-08 13:36:00I2023-12-04 23:00:00.0아이스크림199345.466097451233.369781<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789430100003010000-104-2024-001372024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>12.00100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지하1층 (소공동)4533레자미오네뜨2024-05-09 10:54:59I2023-12-04 23:01:00.0백화점198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
789530100003010000-104-2024-001382024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.00100-890서울특별시 중구 신당동 304-482서울특별시 중구 다산로31길 26, 1층 (신당동)4610퀸즈베리도넛하우스 작업실2024-05-09 13:27:24I2023-12-04 23:01:00.0커피숍201091.0812451087.465263<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>