Overview

Dataset statistics

Number of variables44
Number of observations4830
Missing cells50576
Missing cells (%)23.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory376.0 B

Variable types

Categorical19
Text7
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18701/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업장주변구분명 is highly imbalanced (62.6%)Imbalance
등급구분명 is highly imbalanced (59.4%)Imbalance
급수시설구분명 is highly imbalanced (60.6%)Imbalance
총인원 is highly imbalanced (71.1%)Imbalance
본사종업원수 is highly imbalanced (70.8%)Imbalance
공장사무직종업원수 is highly imbalanced (70.8%)Imbalance
공장판매직종업원수 is highly imbalanced (70.8%)Imbalance
공장생산직종업원수 is highly imbalanced (70.8%)Imbalance
보증액 is highly imbalanced (70.8%)Imbalance
월세액 is highly imbalanced (70.8%)Imbalance
다중이용업소여부 is highly imbalanced (91.5%)Imbalance
전통업소지정번호 is highly imbalanced (99.7%)Imbalance
인허가취소일자 has 4830 (100.0%) missing valuesMissing
폐업일자 has 1329 (27.5%) missing valuesMissing
휴업시작일자 has 4830 (100.0%) missing valuesMissing
휴업종료일자 has 4830 (100.0%) missing valuesMissing
재개업일자 has 4830 (100.0%) missing valuesMissing
전화번호 has 2702 (55.9%) missing valuesMissing
소재지면적 has 176 (3.6%) missing valuesMissing
도로명주소 has 1528 (31.6%) missing valuesMissing
도로명우편번호 has 1546 (32.0%) missing valuesMissing
좌표정보(X) has 115 (2.4%) missing valuesMissing
좌표정보(Y) has 115 (2.4%) missing valuesMissing
남성종사자수 has 3376 (69.9%) missing valuesMissing
여성종사자수 has 3369 (69.8%) missing valuesMissing
건물소유구분명 has 4830 (100.0%) missing valuesMissing
다중이용업소여부 has 1254 (26.0%) missing valuesMissing
시설총규모 has 1254 (26.0%) missing valuesMissing
전통업소주된음식 has 4830 (100.0%) missing valuesMissing
홈페이지 has 4830 (100.0%) missing valuesMissing
남성종사자수 is highly skewed (γ1 = 35.32217176)Skewed
시설총규모 is highly skewed (γ1 = 57.63759196)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
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 1383 (28.6%) zerosZeros
여성종사자수 has 996 (20.6%) zerosZeros
시설총규모 has 66 (1.4%) zerosZeros

Reproduction

Analysis started2024-05-11 06:22:58.806412
Analysis finished2024-05-11 06:23:01.756361
Duration2.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
3240000
4830 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 4830
100.0%

Length

2024-05-11T15:23:01.875290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:02.034131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 4830
100.0%

관리번호
Text

UNIQUE 

Distinct4830
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T15:23:02.427975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters106260
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

Unique4830 ?
Unique (%)100.0%

Sample

1st row3240000-104-1970-04572
2nd row3240000-104-1971-04366
3rd row3240000-104-1971-04606
4th row3240000-104-1975-04603
5th row3240000-104-1976-04147
ValueCountFrequency (%)
3240000-104-1970-04572 1
 
< 0.1%
3240000-104-2018-00085 1
 
< 0.1%
3240000-104-2018-00083 1
 
< 0.1%
3240000-104-2018-00082 1
 
< 0.1%
3240000-104-2018-00081 1
 
< 0.1%
3240000-104-2018-00080 1
 
< 0.1%
3240000-104-2018-00079 1
 
< 0.1%
3240000-104-2018-00078 1
 
< 0.1%
3240000-104-2018-00077 1
 
< 0.1%
3240000-104-2018-00076 1
 
< 0.1%
Other values (4820) 4820
99.8%
2024-05-11T15:23:03.002089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41040
38.6%
- 14490
 
13.6%
2 12180
 
11.5%
4 11786
 
11.1%
1 11059
 
10.4%
3 6895
 
6.5%
9 2851
 
2.7%
8 1736
 
1.6%
5 1447
 
1.4%
6 1398
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91770
86.4%
Dash Punctuation 14490
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41040
44.7%
2 12180
 
13.3%
4 11786
 
12.8%
1 11059
 
12.1%
3 6895
 
7.5%
9 2851
 
3.1%
8 1736
 
1.9%
5 1447
 
1.6%
6 1398
 
1.5%
7 1378
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 14490
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 106260
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41040
38.6%
- 14490
 
13.6%
2 12180
 
11.5%
4 11786
 
11.1%
1 11059
 
10.4%
3 6895
 
6.5%
9 2851
 
2.7%
8 1736
 
1.6%
5 1447
 
1.4%
6 1398
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106260
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41040
38.6%
- 14490
 
13.6%
2 12180
 
11.5%
4 11786
 
11.1%
1 11059
 
10.4%
3 6895
 
6.5%
9 2851
 
2.7%
8 1736
 
1.6%
5 1447
 
1.4%
6 1398
 
1.3%
Distinct3328
Distinct (%)68.9%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
Minimum1970-03-06 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:23:03.316611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:03.618498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
3
3501 
1
1329 

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 3501
72.5%
1 1329
 
27.5%

Length

2024-05-11T15:23:03.936535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:04.130683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3501
72.5%
1 1329
 
27.5%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
폐업
3501 
영업/정상
1329 

Length

Max length5
Median length2
Mean length2.8254658
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3501
72.5%
영업/정상 1329
 
27.5%

Length

2024-05-11T15:23:04.386863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:04.604106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3501
72.5%
영업/정상 1329
 
27.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2
3501 
1
1329 

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 3501
72.5%
1 1329
 
27.5%

Length

2024-05-11T15:23:04.815114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:05.110650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3501
72.5%
1 1329
 
27.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
폐업
3501 
영업
1329 

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 3501
72.5%
영업 1329
 
27.5%

Length

2024-05-11T15:23:05.442949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:05.645858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3501
72.5%
영업 1329
 
27.5%

폐업일자
Date

MISSING 

Distinct2461
Distinct (%)70.3%
Missing1329
Missing (%)27.5%
Memory size37.9 KiB
Minimum1990-02-05 00:00:00
Maximum2024-05-09 00:00:00
2024-05-11T15:23:05.895360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:06.690221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

전화번호
Text

MISSING 

Distinct1772
Distinct (%)83.3%
Missing2702
Missing (%)55.9%
Memory size37.9 KiB
2024-05-11T15:23:07.219767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.054981
Min length2

Characters and Unicode

Total characters21397
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

Unique1688 ?
Unique (%)79.3%

Sample

1st row0204833118
2nd row0204781196
3rd row0204781196
4th row0204781481
5th row02 4422188
ValueCountFrequency (%)
02 1559
37.9%
070 58
 
1.4%
426 39
 
0.9%
0200000000 36
 
0.9%
470 34
 
0.8%
00000 33
 
0.8%
427 28
 
0.7%
475 24
 
0.6%
0 23
 
0.6%
477 20
 
0.5%
Other values (1842) 2263
55.0%
2024-05-11T15:23:08.032238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4133
19.3%
2 3663
17.1%
2728
12.7%
4 2503
11.7%
7 1833
8.6%
8 1609
 
7.5%
1 1064
 
5.0%
5 1034
 
4.8%
6 1031
 
4.8%
3 1018
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18669
87.3%
Space Separator 2728
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4133
22.1%
2 3663
19.6%
4 2503
13.4%
7 1833
9.8%
8 1609
 
8.6%
1 1064
 
5.7%
5 1034
 
5.5%
6 1031
 
5.5%
3 1018
 
5.5%
9 781
 
4.2%
Space Separator
ValueCountFrequency (%)
2728
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21397
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4133
19.3%
2 3663
17.1%
2728
12.7%
4 2503
11.7%
7 1833
8.6%
8 1609
 
7.5%
1 1064
 
5.0%
5 1034
 
4.8%
6 1031
 
4.8%
3 1018
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21397
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4133
19.3%
2 3663
17.1%
2728
12.7%
4 2503
11.7%
7 1833
8.6%
8 1609
 
7.5%
1 1064
 
5.0%
5 1034
 
4.8%
6 1031
 
4.8%
3 1018
 
4.8%

소재지면적
Text

MISSING 

Distinct2025
Distinct (%)43.5%
Missing176
Missing (%)3.6%
Memory size37.9 KiB
2024-05-11T15:23:08.849629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.8856897
Min length3

Characters and Unicode

Total characters22738
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

Unique1547 ?
Unique (%)33.2%

Sample

1st row97.72
2nd row63.45
3rd row63.45
4th row65.04
5th row99.92
ValueCountFrequency (%)
3.30 467
 
10.0%
6.60 167
 
3.6%
33.00 95
 
2.0%
26.40 84
 
1.8%
9.90 79
 
1.7%
30.00 74
 
1.6%
10.00 55
 
1.2%
20.00 50
 
1.1%
16.50 47
 
1.0%
23.10 44
 
0.9%
Other values (2015) 3492
75.0%
2024-05-11T15:23:09.842674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4654
20.5%
0 4644
20.4%
3 2459
10.8%
2 1855
 
8.2%
1 1852
 
8.1%
6 1631
 
7.2%
4 1354
 
6.0%
5 1230
 
5.4%
9 1166
 
5.1%
8 1032
 
4.5%
Other values (2) 861
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18083
79.5%
Other Punctuation 4655
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4644
25.7%
3 2459
13.6%
2 1855
 
10.3%
1 1852
 
10.2%
6 1631
 
9.0%
4 1354
 
7.5%
5 1230
 
6.8%
9 1166
 
6.4%
8 1032
 
5.7%
7 860
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 4654
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 22738
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4654
20.5%
0 4644
20.4%
3 2459
10.8%
2 1855
 
8.2%
1 1852
 
8.1%
6 1631
 
7.2%
4 1354
 
6.0%
5 1230
 
5.4%
9 1166
 
5.1%
8 1032
 
4.5%
Other values (2) 861
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4654
20.5%
0 4644
20.4%
3 2459
10.8%
2 1855
 
8.2%
1 1852
 
8.1%
6 1631
 
7.2%
4 1354
 
6.0%
5 1230
 
5.4%
9 1166
 
5.1%
8 1032
 
4.5%
Other values (2) 861
 
3.8%
Distinct186
Distinct (%)3.9%
Missing1
Missing (%)< 0.1%
Memory size37.9 KiB
2024-05-11T15:23:10.434960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1756057
Min length6

Characters and Unicode

Total characters29822
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

Unique21 ?
Unique (%)0.4%

Sample

1st row134871
2nd row134870
3rd row134870
4th row134866
5th row134854
ValueCountFrequency (%)
134874 286
 
5.9%
134779 230
 
4.8%
134830 218
 
4.5%
134825 168
 
3.5%
134864 151
 
3.1%
134861 131
 
2.7%
134-779 120
 
2.5%
134840 119
 
2.5%
134822 106
 
2.2%
134859 105
 
2.2%
Other values (176) 3195
66.2%
2024-05-11T15:23:11.166324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 6186
20.7%
1 5846
19.6%
3 5547
18.6%
8 4733
15.9%
7 1903
 
6.4%
0 1494
 
5.0%
6 897
 
3.0%
5 860
 
2.9%
- 848
 
2.8%
9 765
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28974
97.2%
Dash Punctuation 848
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 6186
21.4%
1 5846
20.2%
3 5547
19.1%
8 4733
16.3%
7 1903
 
6.6%
0 1494
 
5.2%
6 897
 
3.1%
5 860
 
3.0%
9 765
 
2.6%
2 743
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 848
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 29822
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 6186
20.7%
1 5846
19.6%
3 5547
18.6%
8 4733
15.9%
7 1903
 
6.4%
0 1494
 
5.0%
6 897
 
3.0%
5 860
 
2.9%
- 848
 
2.8%
9 765
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29822
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 6186
20.7%
1 5846
19.6%
3 5547
18.6%
8 4733
15.9%
7 1903
 
6.4%
0 1494
 
5.0%
6 897
 
3.0%
5 860
 
2.9%
- 848
 
2.8%
9 765
 
2.6%
Distinct3505
Distinct (%)72.6%
Missing1
Missing (%)< 0.1%
Memory size37.9 KiB
2024-05-11T15:23:11.550643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length23.939325
Min length13

Characters and Unicode

Total characters115603
Distinct characters399
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2887 ?
Unique (%)59.8%

Sample

1st row서울특별시 강동구 천호동 397-330번지
2nd row서울특별시 강동구 천호동 403-17번지
3rd row서울특별시 강동구 천호동 403-17번지
4th row서울특별시 강동구 천호동 237-34번지
5th row서울특별시 강동구 암사동 421-6번지
ValueCountFrequency (%)
서울특별시 4829
21.9%
강동구 4829
21.9%
천호동 1570
 
7.1%
성내동 949
 
4.3%
명일동 565
 
2.6%
길동 523
 
2.4%
암사동 454
 
2.1%
현대백화점 323
 
1.5%
둔촌동 252
 
1.1%
1층 246
 
1.1%
Other values (3551) 7516
34.1%
2024-05-11T15:23:12.209825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20684
17.9%
9933
 
8.6%
5084
 
4.4%
4893
 
4.2%
4855
 
4.2%
4853
 
4.2%
4840
 
4.2%
4833
 
4.2%
4829
 
4.2%
- 3851
 
3.3%
Other values (389) 46948
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68848
59.6%
Decimal Number 21410
 
18.5%
Space Separator 20684
 
17.9%
Dash Punctuation 3851
 
3.3%
Open Punctuation 258
 
0.2%
Close Punctuation 258
 
0.2%
Uppercase Letter 155
 
0.1%
Other Punctuation 95
 
0.1%
Lowercase Letter 36
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9933
14.4%
5084
 
7.4%
4893
 
7.1%
4855
 
7.1%
4853
 
7.0%
4840
 
7.0%
4833
 
7.0%
4829
 
7.0%
3277
 
4.8%
2931
 
4.3%
Other values (328) 18520
26.9%
Uppercase Letter
ValueCountFrequency (%)
A 17
 
11.0%
S 16
 
10.3%
B 15
 
9.7%
K 14
 
9.0%
U 12
 
7.7%
E 9
 
5.8%
P 8
 
5.2%
G 7
 
4.5%
R 6
 
3.9%
T 6
 
3.9%
Other values (14) 45
29.0%
Lowercase Letter
ValueCountFrequency (%)
e 5
13.9%
t 5
13.9%
n 4
11.1%
i 4
11.1%
l 3
8.3%
s 3
8.3%
o 2
 
5.6%
a 2
 
5.6%
r 2
 
5.6%
y 1
 
2.8%
Other values (5) 5
13.9%
Decimal Number
ValueCountFrequency (%)
1 3715
17.4%
4 3452
16.1%
5 2705
12.6%
2 2690
12.6%
3 2407
11.2%
0 1515
7.1%
7 1394
 
6.5%
8 1267
 
5.9%
6 1143
 
5.3%
9 1122
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 87
91.6%
. 5
 
5.3%
? 2
 
2.1%
& 1
 
1.1%
Math Symbol
ValueCountFrequency (%)
< 3
42.9%
> 3
42.9%
~ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
20684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3851
100.0%
Open Punctuation
ValueCountFrequency (%)
( 258
100.0%
Close Punctuation
ValueCountFrequency (%)
) 258
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68848
59.6%
Common 46563
40.3%
Latin 192
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9933
14.4%
5084
 
7.4%
4893
 
7.1%
4855
 
7.1%
4853
 
7.0%
4840
 
7.0%
4833
 
7.0%
4829
 
7.0%
3277
 
4.8%
2931
 
4.3%
Other values (328) 18520
26.9%
Latin
ValueCountFrequency (%)
A 17
 
8.9%
S 16
 
8.3%
B 15
 
7.8%
K 14
 
7.3%
U 12
 
6.2%
E 9
 
4.7%
P 8
 
4.2%
G 7
 
3.6%
R 6
 
3.1%
T 6
 
3.1%
Other values (30) 82
42.7%
Common
ValueCountFrequency (%)
20684
44.4%
- 3851
 
8.3%
1 3715
 
8.0%
4 3452
 
7.4%
5 2705
 
5.8%
2 2690
 
5.8%
3 2407
 
5.2%
0 1515
 
3.3%
7 1394
 
3.0%
8 1267
 
2.7%
Other values (11) 2883
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68848
59.6%
ASCII 46754
40.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20684
44.2%
- 3851
 
8.2%
1 3715
 
7.9%
4 3452
 
7.4%
5 2705
 
5.8%
2 2690
 
5.8%
3 2407
 
5.1%
0 1515
 
3.2%
7 1394
 
3.0%
8 1267
 
2.7%
Other values (50) 3074
 
6.6%
Hangul
ValueCountFrequency (%)
9933
14.4%
5084
 
7.4%
4893
 
7.1%
4855
 
7.1%
4853
 
7.0%
4840
 
7.0%
4833
 
7.0%
4829
 
7.0%
3277
 
4.8%
2931
 
4.3%
Other values (328) 18520
26.9%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct2707
Distinct (%)82.0%
Missing1528
Missing (%)31.6%
Memory size37.9 KiB
2024-05-11T15:23:12.612457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length57
Mean length33.57874
Min length21

Characters and Unicode

Total characters110877
Distinct characters393
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2485 ?
Unique (%)75.3%

Sample

1st row서울특별시 강동구 천호옛길 55 (성내동)
2nd row서울특별시 강동구 풍성로52길 1 (성내동)
3rd row서울특별시 강동구 진황도로 190 (둔촌동)
4th row서울특별시 강동구 진황도로49길 46 (길동)
5th row서울특별시 강동구 고덕로 390 (상일동, 주공3 다상가 205호)
ValueCountFrequency (%)
서울특별시 3302
 
15.2%
강동구 3302
 
15.2%
1층 1474
 
6.8%
천호동 962
 
4.4%
성내동 617
 
2.8%
천호대로 593
 
2.7%
1005 404
 
1.9%
현대백화점 320
 
1.5%
길동 307
 
1.4%
명일동 306
 
1.4%
Other values (2059) 10088
46.5%
2024-05-11T15:23:13.235894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18384
 
16.6%
7195
 
6.5%
1 6192
 
5.6%
3607
 
3.3%
3584
 
3.2%
, 3452
 
3.1%
) 3450
 
3.1%
( 3450
 
3.1%
3375
 
3.0%
3323
 
3.0%
Other values (383) 54865
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62923
56.8%
Decimal Number 18704
 
16.9%
Space Separator 18384
 
16.6%
Other Punctuation 3457
 
3.1%
Close Punctuation 3450
 
3.1%
Open Punctuation 3450
 
3.1%
Dash Punctuation 248
 
0.2%
Uppercase Letter 210
 
0.2%
Lowercase Letter 31
 
< 0.1%
Math Symbol 19
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7195
 
11.4%
3607
 
5.7%
3584
 
5.7%
3375
 
5.4%
3323
 
5.3%
3319
 
5.3%
3305
 
5.3%
3302
 
5.2%
3265
 
5.2%
3193
 
5.1%
Other values (326) 25455
40.5%
Uppercase Letter
ValueCountFrequency (%)
B 54
25.7%
A 30
14.3%
S 17
 
8.1%
K 12
 
5.7%
U 12
 
5.7%
E 10
 
4.8%
G 8
 
3.8%
C 7
 
3.3%
P 7
 
3.3%
I 6
 
2.9%
Other values (12) 47
22.4%
Lowercase Letter
ValueCountFrequency (%)
t 4
12.9%
n 4
12.9%
e 4
12.9%
i 3
9.7%
o 2
6.5%
a 2
6.5%
b 2
6.5%
r 2
6.5%
l 2
6.5%
s 2
6.5%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
1 6192
33.1%
0 2647
14.2%
2 2130
 
11.4%
5 1552
 
8.3%
3 1502
 
8.0%
4 1039
 
5.6%
7 1015
 
5.4%
6 931
 
5.0%
9 899
 
4.8%
8 797
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 3452
99.9%
. 2
 
0.1%
& 1
 
< 0.1%
/ 1
 
< 0.1%
? 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
18384
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3450
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3450
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 248
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62923
56.8%
Common 47712
43.0%
Latin 242
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7195
 
11.4%
3607
 
5.7%
3584
 
5.7%
3375
 
5.4%
3323
 
5.3%
3319
 
5.3%
3305
 
5.3%
3302
 
5.2%
3265
 
5.2%
3193
 
5.1%
Other values (326) 25455
40.5%
Latin
ValueCountFrequency (%)
B 54
22.3%
A 30
 
12.4%
S 17
 
7.0%
K 12
 
5.0%
U 12
 
5.0%
E 10
 
4.1%
G 8
 
3.3%
C 7
 
2.9%
P 7
 
2.9%
I 6
 
2.5%
Other values (27) 79
32.6%
Common
ValueCountFrequency (%)
18384
38.5%
1 6192
 
13.0%
, 3452
 
7.2%
) 3450
 
7.2%
( 3450
 
7.2%
0 2647
 
5.5%
2 2130
 
4.5%
5 1552
 
3.3%
3 1502
 
3.1%
4 1039
 
2.2%
Other values (10) 3914
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62923
56.8%
ASCII 47953
43.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18384
38.3%
1 6192
 
12.9%
, 3452
 
7.2%
) 3450
 
7.2%
( 3450
 
7.2%
0 2647
 
5.5%
2 2130
 
4.4%
5 1552
 
3.2%
3 1502
 
3.1%
4 1039
 
2.2%
Other values (46) 4155
 
8.7%
Hangul
ValueCountFrequency (%)
7195
 
11.4%
3607
 
5.7%
3584
 
5.7%
3375
 
5.4%
3323
 
5.3%
3319
 
5.3%
3305
 
5.3%
3302
 
5.2%
3265
 
5.2%
3193
 
5.1%
Other values (326) 25455
40.5%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct198
Distinct (%)6.0%
Missing1546
Missing (%)32.0%
Infinite0
Infinite (%)0.0%
Mean5318.5773
Minimum5201
Maximum5416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:13.535062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5201
5-th percentile5225
Q15269
median5328
Q35360.25
95-th percentile5404
Maximum5416
Range215
Interquartile range (IQR)91.25

Descriptive statistics

Standard deviation54.730729
Coefficient of variation (CV)0.010290483
Kurtosis-0.92877836
Mean5318.5773
Median Absolute Deviation (MAD)45
Skewness-0.15614138
Sum17466208
Variance2995.4527
MonotonicityNot monotonic
2024-05-11T15:23:13.812757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5328 458
 
9.5%
5269 114
 
2.4%
5292 50
 
1.0%
5351 50
 
1.0%
5404 47
 
1.0%
5399 45
 
0.9%
5248 43
 
0.9%
5339 40
 
0.8%
5283 38
 
0.8%
5222 38
 
0.8%
Other values (188) 2361
48.9%
(Missing) 1546
32.0%
ValueCountFrequency (%)
5201 3
 
0.1%
5203 16
0.3%
5206 1
 
< 0.1%
5208 3
 
0.1%
5209 3
 
0.1%
5210 4
 
0.1%
5211 37
0.8%
5212 1
 
< 0.1%
5213 1
 
< 0.1%
5214 3
 
0.1%
ValueCountFrequency (%)
5416 2
 
< 0.1%
5415 8
 
0.2%
5414 1
 
< 0.1%
5412 5
 
0.1%
5411 5
 
0.1%
5409 2
 
< 0.1%
5408 37
0.8%
5407 13
 
0.3%
5406 18
0.4%
5405 37
0.8%
Distinct4338
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
2024-05-11T15:23:14.331770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length25
Mean length7.5182195
Min length1

Characters and Unicode

Total characters36313
Distinct characters896
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4018 ?
Unique (%)83.2%

Sample

1st row장미
2nd row양지
3rd row양지
4th row
5th row칸느
ValueCountFrequency (%)
한시적영업 164
 
2.4%
세븐일레븐 110
 
1.6%
천호점 78
 
1.2%
gs25 68
 
1.0%
씨유 65
 
1.0%
지에스25 43
 
0.6%
카페 41
 
0.6%
coffee 34
 
0.5%
강동점 31
 
0.5%
명일점 30
 
0.4%
Other values (4506) 6104
90.2%
2024-05-11T15:23:15.117865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1944
 
5.4%
1489
 
4.1%
986
 
2.7%
716
 
2.0%
709
 
2.0%
) 610
 
1.7%
( 605
 
1.7%
593
 
1.6%
581
 
1.6%
512
 
1.4%
Other values (886) 27568
75.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28953
79.7%
Space Separator 1944
 
5.4%
Lowercase Letter 1722
 
4.7%
Uppercase Letter 1584
 
4.4%
Decimal Number 787
 
2.2%
Close Punctuation 610
 
1.7%
Open Punctuation 605
 
1.7%
Other Punctuation 84
 
0.2%
Dash Punctuation 17
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1489
 
5.1%
986
 
3.4%
716
 
2.5%
709
 
2.4%
593
 
2.0%
581
 
2.0%
512
 
1.8%
496
 
1.7%
428
 
1.5%
412
 
1.4%
Other values (804) 22031
76.1%
Lowercase Letter
ValueCountFrequency (%)
e 310
18.0%
a 172
10.0%
o 166
9.6%
f 156
9.1%
c 110
 
6.4%
i 102
 
5.9%
s 91
 
5.3%
n 85
 
4.9%
r 80
 
4.6%
t 72
 
4.2%
Other values (16) 378
22.0%
Uppercase Letter
ValueCountFrequency (%)
C 248
15.7%
S 221
14.0%
G 196
12.4%
P 122
 
7.7%
E 91
 
5.7%
U 85
 
5.4%
A 77
 
4.9%
O 76
 
4.8%
F 56
 
3.5%
T 48
 
3.0%
Other values (16) 364
23.0%
Decimal Number
ValueCountFrequency (%)
2 284
36.1%
5 244
31.0%
1 58
 
7.4%
4 46
 
5.8%
0 39
 
5.0%
3 39
 
5.0%
9 28
 
3.6%
6 19
 
2.4%
8 19
 
2.4%
7 11
 
1.4%
Other Punctuation
ValueCountFrequency (%)
& 27
32.1%
' 19
22.6%
. 16
19.0%
, 8
 
9.5%
# 4
 
4.8%
! 3
 
3.6%
? 3
 
3.6%
/ 2
 
2.4%
: 1
 
1.2%
1
 
1.2%
Math Symbol
ValueCountFrequency (%)
< 1
33.3%
> 1
33.3%
~ 1
33.3%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
1944
100.0%
Close Punctuation
ValueCountFrequency (%)
) 610
100.0%
Open Punctuation
ValueCountFrequency (%)
( 605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28946
79.7%
Common 4052
 
11.2%
Latin 3308
 
9.1%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1489
 
5.1%
986
 
3.4%
716
 
2.5%
709
 
2.4%
593
 
2.0%
581
 
2.0%
512
 
1.8%
496
 
1.7%
428
 
1.5%
412
 
1.4%
Other values (797) 22024
76.1%
Latin
ValueCountFrequency (%)
e 310
 
9.4%
C 248
 
7.5%
S 221
 
6.7%
G 196
 
5.9%
a 172
 
5.2%
o 166
 
5.0%
f 156
 
4.7%
P 122
 
3.7%
c 110
 
3.3%
i 102
 
3.1%
Other values (44) 1505
45.5%
Common
ValueCountFrequency (%)
1944
48.0%
) 610
 
15.1%
( 605
 
14.9%
2 284
 
7.0%
5 244
 
6.0%
1 58
 
1.4%
4 46
 
1.1%
0 39
 
1.0%
3 39
 
1.0%
9 28
 
0.7%
Other values (18) 155
 
3.8%
Han
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28945
79.7%
ASCII 7355
 
20.3%
CJK 7
 
< 0.1%
Letterlike Symbols 2
 
< 0.1%
Number Forms 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1944
26.4%
) 610
 
8.3%
( 605
 
8.2%
e 310
 
4.2%
2 284
 
3.9%
C 248
 
3.4%
5 244
 
3.3%
S 221
 
3.0%
G 196
 
2.7%
a 172
 
2.3%
Other values (68) 2521
34.3%
Hangul
ValueCountFrequency (%)
1489
 
5.1%
986
 
3.4%
716
 
2.5%
709
 
2.4%
593
 
2.0%
581
 
2.0%
512
 
1.8%
496
 
1.7%
428
 
1.5%
412
 
1.4%
Other values (796) 22023
76.1%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct4056
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
Minimum1999-02-06 00:00:00
Maximum2024-05-09 16:37:38
2024-05-11T15:23:15.408452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:15.763892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
I
3072 
U
1758 

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 3072
63.6%
U 1758
36.4%

Length

2024-05-11T15:23:16.062874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:16.252086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3072
63.6%
u 1758
36.4%
Distinct1136
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:23:16.485738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:23:16.754418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct14
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
커피숍
1388 
일반조리판매
834 
다방
683 
편의점
608 
패스트푸드
497 
Other values (9)
820 

Length

Max length8
Median length6
Mean length4.0519669
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
커피숍 1388
28.7%
일반조리판매 834
17.3%
다방 683
14.1%
편의점 608
12.6%
패스트푸드 497
 
10.3%
기타 휴게음식점 443
 
9.2%
백화점 285
 
5.9%
과자점 29
 
0.6%
떡카페 17
 
0.4%
키즈카페 11
 
0.2%
Other values (4) 35
 
0.7%

Length

2024-05-11T15:23:17.060198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
커피숍 1388
26.3%
일반조리판매 834
15.8%
다방 683
13.0%
편의점 608
11.5%
패스트푸드 497
 
9.4%
기타 443
 
8.4%
휴게음식점 443
 
8.4%
백화점 285
 
5.4%
과자점 29
 
0.5%
떡카페 17
 
0.3%
Other values (5) 46
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2097
Distinct (%)44.5%
Missing115
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean212092.21
Minimum209888.92
Maximum216076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:17.317232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum209888.92
5-th percentile210858.05
Q1211122.42
median211820.88
Q3212651.76
95-th percentile214973.46
Maximum216076.82
Range6187.907
Interquartile range (IQR)1529.3488

Descriptive statistics

Standard deviation1185.1125
Coefficient of variation (CV)0.005587723
Kurtosis0.74356339
Mean212092.21
Median Absolute Deviation (MAD)767.25345
Skewness1.1344889
Sum1.0000148 × 109
Variance1404491.6
MonotonicityNot monotonic
2024-05-11T15:23:17.597873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210929.919693661 257
 
5.3%
210931.643485 236
 
4.9%
212501.369116329 46
 
1.0%
211025.924972294 40
 
0.8%
213700.877714971 39
 
0.8%
213493.90717524 26
 
0.5%
212334.9584644 26
 
0.5%
213839.356195548 24
 
0.5%
213048.692179757 22
 
0.5%
212334.69890736 20
 
0.4%
Other values (2087) 3979
82.4%
(Missing) 115
 
2.4%
ValueCountFrequency (%)
209888.915845495 1
 
< 0.1%
210185.825916808 1
 
< 0.1%
210268.695726798 1
 
< 0.1%
210480.767564873 4
0.1%
210521.84184835 1
 
< 0.1%
210539.388167582 1
 
< 0.1%
210566.875626134 7
0.1%
210607.529826692 1
 
< 0.1%
210622.73929089 1
 
< 0.1%
210630.209443525 4
0.1%
ValueCountFrequency (%)
216076.822850039 1
 
< 0.1%
215927.688523964 2
< 0.1%
215898.113091143 1
 
< 0.1%
215888.898816 3
0.1%
215875.024969 3
0.1%
215784.2264 3
0.1%
215728.497758 1
 
< 0.1%
215672.146934322 1
 
< 0.1%
215661.222623 1
 
< 0.1%
215659.154061 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2097
Distinct (%)44.5%
Missing115
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean448875.14
Minimum446408.47
Maximum452309.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:17.879988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446408.47
5-th percentile447242.11
Q1448212.93
median448613.01
Q3449707.57
95-th percentile450637.02
Maximum452309.71
Range5901.2408
Interquartile range (IQR)1494.6377

Descriptive statistics

Standard deviation1052.353
Coefficient of variation (CV)0.0023444225
Kurtosis-0.3005301
Mean448875.14
Median Absolute Deviation (MAD)809.79263
Skewness0.28270242
Sum2.1164463 × 109
Variance1107446.8
MonotonicityNot monotonic
2024-05-11T15:23:18.222998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448537.406728283 257
 
5.3%
448522.079827 236
 
4.9%
449282.31038379 46
 
1.0%
448495.189151526 40
 
0.8%
450278.100930843 39
 
0.8%
450038.847319845 26
 
0.5%
450346.790651613 26
 
0.5%
450118.261707983 24
 
0.5%
450124.105734971 22
 
0.5%
447728.865137096 20
 
0.4%
Other values (2087) 3979
82.4%
(Missing) 115
 
2.4%
ValueCountFrequency (%)
446408.470922092 1
 
< 0.1%
446449.267425948 1
 
< 0.1%
446598.591776331 3
0.1%
446680.303498539 1
 
< 0.1%
446699.196101461 4
0.1%
446732.640167362 2
 
< 0.1%
446745.460398406 4
0.1%
446748.493341691 5
0.1%
446753.841167447 2
 
< 0.1%
446761.604007505 1
 
< 0.1%
ValueCountFrequency (%)
452309.711718 1
 
< 0.1%
452305.723682264 1
 
< 0.1%
452269.014454429 1
 
< 0.1%
452250.027592269 1
 
< 0.1%
452213.416817557 1
 
< 0.1%
452195.587817951 1
 
< 0.1%
452189.755118282 4
0.1%
452130.329696 3
0.1%
452107.257532 1
 
< 0.1%
452076.939632 1
 
< 0.1%

위생업태명
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
1254 
커피숍
852 
일반조리판매
696 
다방
682 
패스트푸드
430 
Other values (10)
916 

Length

Max length8
Median length6
Mean length4.0751553
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1254
26.0%
커피숍 852
17.6%
일반조리판매 696
14.4%
다방 682
14.1%
패스트푸드 430
 
8.9%
편의점 376
 
7.8%
기타 휴게음식점 327
 
6.8%
백화점 144
 
3.0%
과자점 29
 
0.6%
푸드트럭 9
 
0.2%
Other values (5) 31
 
0.6%

Length

2024-05-11T15:23:18.513834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1254
24.3%
커피숍 852
16.5%
일반조리판매 696
13.5%
다방 682
13.2%
패스트푸드 430
 
8.3%
편의점 376
 
7.3%
기타 327
 
6.3%
휴게음식점 327
 
6.3%
백화점 144
 
2.8%
과자점 29
 
0.6%
Other values (6) 40
 
0.8%

남성종사자수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct6
Distinct (%)0.4%
Missing3376
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean0.13342503
Minimum0
Maximum92
Zeros1383
Zeros (%)28.6%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:18.808473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum92
Range92
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4816069
Coefficient of variation (CV)18.59926
Kurtosis1297.6908
Mean0.13342503
Median Absolute Deviation (MAD)0
Skewness35.322172
Sum194
Variance6.1583727
MonotonicityNot monotonic
2024-05-11T15:23:19.011439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1383
28.6%
1 57
 
1.2%
2 11
 
0.2%
20 1
 
< 0.1%
92 1
 
< 0.1%
3 1
 
< 0.1%
(Missing) 3376
69.9%
ValueCountFrequency (%)
0 1383
28.6%
1 57
 
1.2%
2 11
 
0.2%
3 1
 
< 0.1%
20 1
 
< 0.1%
92 1
 
< 0.1%
ValueCountFrequency (%)
92 1
 
< 0.1%
20 1
 
< 0.1%
3 1
 
< 0.1%
2 11
 
0.2%
1 57
 
1.2%
0 1383
28.6%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)0.5%
Missing3369
Missing (%)69.8%
Infinite0
Infinite (%)0.0%
Mean0.68240931
Minimum0
Maximum30
Zeros996
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:19.184430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum30
Range30
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3118631
Coefficient of variation (CV)1.9223992
Kurtosis170.46543
Mean0.68240931
Median Absolute Deviation (MAD)0
Skewness8.3782133
Sum997
Variance1.7209849
MonotonicityNot monotonic
2024-05-11T15:23:19.382818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 996
 
20.6%
2 254
 
5.3%
3 103
 
2.1%
1 94
 
1.9%
4 12
 
0.2%
30 1
 
< 0.1%
8 1
 
< 0.1%
(Missing) 3369
69.8%
ValueCountFrequency (%)
0 996
20.6%
1 94
 
1.9%
2 254
 
5.3%
3 103
 
2.1%
4 12
 
0.2%
8 1
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
8 1
 
< 0.1%
4 12
 
0.2%
3 103
 
2.1%
2 254
 
5.3%
1 94
 
1.9%
0 996
20.6%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
3838 
주택가주변
610 
기타
 
174
유흥업소밀집지역
 
156
아파트지역
 
46
Other values (2)
 
6

Length

Max length8
Median length4
Mean length4.1968944
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3838
79.5%
주택가주변 610
 
12.6%
기타 174
 
3.6%
유흥업소밀집지역 156
 
3.2%
아파트지역 46
 
1.0%
결혼예식장주변 5
 
0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-05-11T15:23:19.613431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:19.812713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3838
79.5%
주택가주변 610
 
12.6%
기타 174
 
3.6%
유흥업소밀집지역 156
 
3.2%
아파트지역 46
 
1.0%
결혼예식장주변 5
 
0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
3843 
자율
 
334
기타
 
300
 
259
지도
 
46
Other values (2)
 
48

Length

Max length4
Median length4
Mean length3.5291925
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3843
79.6%
자율 334
 
6.9%
기타 300
 
6.2%
259
 
5.4%
지도 46
 
1.0%
41
 
0.8%
우수 7
 
0.1%

Length

2024-05-11T15:23:20.076058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:20.319915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3843
79.6%
자율 334
 
6.9%
기타 300
 
6.2%
259
 
5.4%
지도 46
 
1.0%
41
 
0.8%
우수 7
 
0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
3722 
상수도전용
1103 
상수도(음용)지하수(주방용)겸용
 
3
지하수전용
 
2

Length

Max length17
Median length4
Mean length4.236853
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3722
77.1%
상수도전용 1103
 
22.8%
상수도(음용)지하수(주방용)겸용 3
 
0.1%
지하수전용 2
 
< 0.1%

Length

2024-05-11T15:23:20.562466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:20.742495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3722
77.1%
상수도전용 1103
 
22.8%
상수도(음용)지하수(주방용)겸용 3
 
0.1%
지하수전용 2
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4585 
0
 
245

Length

Max length4
Median length4
Mean length3.8478261
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> 4585
94.9%
0 245
 
5.1%

Length

2024-05-11T15:23:20.981360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:21.199517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4585
94.9%
0 245
 
5.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:21.380117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:21.552809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:21.749127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:21.935145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:22.138434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:22.316128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:22.523073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:22.736646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:22.931472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:23.586197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4582 
0
 
248

Length

Max length4
Median length4
Mean length3.8459627
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> 4582
94.9%
0 248
 
5.1%

Length

2024-05-11T15:23:23.764901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:23.956044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4582
94.9%
0 248
 
5.1%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing1254
Missing (%)26.0%
Memory size9.6 KiB
False
3538 
True
 
38
(Missing)
1254 
ValueCountFrequency (%)
False 3538
73.3%
True 38
 
0.8%
(Missing) 1254
 
26.0%
2024-05-11T15:23:24.124936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct1693
Distinct (%)47.3%
Missing1254
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean51.819871
Minimum0
Maximum20000
Zeros66
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size42.6 KiB
2024-05-11T15:23:24.394592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q112.18
median29
Q365.0175
95-th percentile134.0175
Maximum20000
Range20000
Interquartile range (IQR)52.8375

Descriptive statistics

Standard deviation337.81808
Coefficient of variation (CV)6.5190838
Kurtosis3403.7114
Mean51.819871
Median Absolute Deviation (MAD)20.5
Skewness57.637592
Sum185307.86
Variance114121.06
MonotonicityNot monotonic
2024-05-11T15:23:24.681075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 282
 
5.8%
6.6 121
 
2.5%
33.0 81
 
1.7%
26.4 75
 
1.6%
0.0 66
 
1.4%
9.9 63
 
1.3%
30.0 46
 
1.0%
10.0 44
 
0.9%
23.1 40
 
0.8%
16.5 37
 
0.8%
Other values (1683) 2721
56.3%
(Missing) 1254
26.0%
ValueCountFrequency (%)
0.0 66
1.4%
0.5 1
 
< 0.1%
0.96 1
 
< 0.1%
1.0 1
 
< 0.1%
1.26 1
 
< 0.1%
1.5 1
 
< 0.1%
1.6 1
 
< 0.1%
1.62 2
 
< 0.1%
1.65 5
 
0.1%
2.0 4
 
0.1%
ValueCountFrequency (%)
20000.0 1
< 0.1%
541.61 1
< 0.1%
539.6 1
< 0.1%
463.92 1
< 0.1%
458.9 1
< 0.1%
446.4 1
< 0.1%
439.68 1
< 0.1%
422.3 1
< 0.1%
410.0 1
< 0.1%
390.54 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size37.9 KiB
<NA>
4829 
84
 
1

Length

Max length4
Median length4
Mean length3.9995859
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4829
> 99.9%
84 1
 
< 0.1%

Length

2024-05-11T15:23:24.975049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:23:25.164551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4829
> 99.9%
84 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4830
Missing (%)100.0%
Memory size42.6 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-104-1970-0457219700306<NA>3폐업2폐업20080102<NA><NA><NA>020483311897.72134871서울특별시 강동구 천호동 397-330번지<NA><NA>장미2008-02-12 16:14:11I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.72<NA><NA><NA>
132400003240000-104-1971-0436619710318<NA>3폐업2폐업20120906<NA><NA><NA>020478119663.45134870서울특별시 강동구 천호동 403-17번지<NA><NA>양지2002-06-05 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.45<NA><NA><NA>
232400003240000-104-1971-0460619710318<NA>3폐업2폐업19900205<NA><NA><NA>020478119663.45134870서울특별시 강동구 천호동 403-17번지<NA><NA>양지2002-08-26 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N63.45<NA><NA><NA>
332400003240000-104-1975-0460319750906<NA>3폐업2폐업19930809<NA><NA><NA>020478148165.04134866서울특별시 강동구 천호동 237-34번지<NA><NA>2002-06-05 00:00:00I2018-08-31 23:59:59.0다방211778.410243449314.94535다방03주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N65.04<NA><NA><NA>
432400003240000-104-1976-0414719761021<NA>3폐업2폐업20080731<NA><NA><NA>02 442218899.92134854서울특별시 강동구 암사동 421-6번지<NA><NA>칸느2006-11-24 00:00:00I2018-08-31 23:59:59.0다방212277.968752449839.218954다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N99.92<NA><NA><NA>
532400003240000-104-1976-0417719761223<NA>3폐업2폐업19991222<NA><NA><NA>0267.08134859서울특별시 강동구 암사동 496-18번지<NA><NA>2002-06-05 00:00:00I2018-08-31 23:59:59.0다방211312.527191449728.213491다방02주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N67.08<NA><NA><NA>
632400003240000-104-1976-0430019760528<NA>3폐업2폐업20050310<NA><NA><NA>02 478342997.06134873서울특별시 강동구 천호동 421-9번지<NA><NA>청원다방2002-06-05 00:00:00I2018-08-31 23:59:59.0다방211225.962728448721.094751다방03유흥업소밀집지역상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N97.06<NA><NA><NA>
732400003240000-104-1976-0453919761029<NA>3폐업2폐업19911213<NA><NA><NA>020472007553.81134859서울특별시 강동구 암사동 496-15번지<NA><NA>다향2002-06-05 00:00:00I2018-08-31 23:59:59.0다방211321.02474449774.71317다방01주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.81<NA><NA><NA>
832400003240000-104-1977-0410919770801<NA>3폐업2폐업20030516<NA><NA><NA>020478344571.83134874서울특별시 강동구 천호동 461-18번지<NA><NA>성혼다방2002-06-05 00:00:00I2018-08-31 23:59:59.0다방210766.924777448833.004036다방03주택가주변상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N71.83<NA><NA><NA>
932400003240000-104-1977-0434319770409<NA>3폐업2폐업20040924<NA><NA><NA>02 4751955126.07134870서울특별시 강동구 천호동 403-2번지 .3.5<NA><NA>돌다방2000-06-28 00:00:00I2018-08-31 23:59:59.0다방<NA><NA>다방00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N126.07<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
482032400003240000-104-2024-000822024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.00134-841서울특별시 강동구 성내동 118-16서울특별시 강동구 천호옛길 47, 1층 102호 (성내동)5385아미띠에2024-04-25 17:03:39I2023-12-03 22:07:00.0커피숍210814.16645447933.506573<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482132400003240000-104-2024-000832024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>62.20134-870서울특별시 강동구 천호동 362-37서울특별시 강동구 올림픽로80길 45, 1층 (천호동)5324카페아이엔지 천호공원점2024-04-26 14:23:59I2023-12-03 22:08:00.0커피숍211221.975219448980.785231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482232400003240000-104-2024-000842024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30134-822서울특별시 강동구 둔촌동 490-12서울특별시 강동구 풍성로63길 47, 1층 (둔촌동)5372세븐일레븐 강동둔촌점2024-04-26 17:27:14I2023-12-03 22:08:00.0편의점212246.369633447581.449698<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482332400003240000-104-2024-000852024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.15134-805서울특별시 강동구 고덕동 499 고덕아이파크서울특별시 강동구 동남로79길 26, 상가동 1층 102호 (고덕동, 고덕아이파크)5232달더라 과일가게2024-04-29 10:36:46I2023-12-05 00:01:00.0일반조리판매213646.900696450750.547533<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482432400003240000-104-2024-000862024-04-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>134-779서울특별시 강동구 천호동 572 현대백화점서울특별시 강동구 천호대로 1005, 현대백화점 지2층 (천호동)5328온누리농특산 한시적영업2024-04-29 14:48:28I2023-12-05 00:01:00.0백화점210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
482532400003240000-104-2024-000872024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>60.00134-857서울특별시 강동구 암사동 463서울특별시 강동구 올림픽로 816, 103호 (암사동)5251메가엠지씨커피 선사사거리점2024-05-02 11:24:49I2023-12-05 00:04:00.0커피숍211338.526335450163.935831<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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482832400003240000-104-2024-000902024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>134-779서울특별시 강동구 천호동 572 현대백화점서울특별시 강동구 천호대로 1005, 현대백화점 지2층 (천호동)5328주바른 한시적영업2024-05-08 09:25:13I2023-12-04 23:00:00.0백화점210929.919694448537.406728<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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