Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells98327
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory384.0 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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18657/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
급수시설구분명 is highly imbalanced (51.2%)Imbalance
총인원 is highly imbalanced (85.1%)Imbalance
본사종업원수 is highly imbalanced (84.6%)Imbalance
공장사무직종업원수 is highly imbalanced (84.6%)Imbalance
공장판매직종업원수 is highly imbalanced (84.6%)Imbalance
공장생산직종업원수 is highly imbalanced (84.6%)Imbalance
보증액 is highly imbalanced (84.6%)Imbalance
월세액 is highly imbalanced (84.6%)Imbalance
다중이용업소여부 is highly imbalanced (89.1%)Imbalance
전통업소지정번호 is highly imbalanced (99.9%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 1999 (20.0%) missing valuesMissing
휴업시작일자 has 10000 (100.0%) missing valuesMissing
휴업종료일자 has 10000 (100.0%) missing valuesMissing
재개업일자 has 10000 (100.0%) missing valuesMissing
전화번호 has 2928 (29.3%) missing valuesMissing
도로명주소 has 5809 (58.1%) missing valuesMissing
도로명우편번호 has 5902 (59.0%) missing valuesMissing
좌표정보(X) has 722 (7.2%) missing valuesMissing
좌표정보(Y) has 722 (7.2%) missing valuesMissing
남성종사자수 has 3802 (38.0%) missing valuesMissing
여성종사자수 has 3797 (38.0%) missing valuesMissing
건물소유구분명 has 10000 (100.0%) missing valuesMissing
다중이용업소여부 has 1315 (13.2%) missing valuesMissing
시설총규모 has 1315 (13.2%) missing valuesMissing
전통업소주된음식 has 10000 (100.0%) missing valuesMissing
홈페이지 has 10000 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 5141 (51.4%) zerosZeros
여성종사자수 has 4461 (44.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:27:17.518754
Analysis finished2024-05-11 06:27:21.429796
Duration3.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3050000
10000 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 10000
100.0%

Length

2024-05-11T15:27:21.539497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:21.681664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 10000
100.0%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:27:21.981115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters220000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row3050000-101-2000-12234
2nd row3050000-101-2015-00338
3rd row3050000-101-1999-11233
4th row3050000-101-1995-10396
5th row3050000-101-2001-13245
ValueCountFrequency (%)
3050000-101-2000-12234 1
 
< 0.1%
3050000-101-2006-00167 1
 
< 0.1%
3050000-101-1988-04322 1
 
< 0.1%
3050000-101-2001-12578 1
 
< 0.1%
3050000-101-2013-00103 1
 
< 0.1%
3050000-101-1998-03541 1
 
< 0.1%
3050000-101-2001-12697 1
 
< 0.1%
3050000-101-2001-13124 1
 
< 0.1%
3050000-101-2001-12753 1
 
< 0.1%
3050000-101-2013-00085 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T15:27:22.587626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 86840
39.5%
1 33501
 
15.2%
- 30000
 
13.6%
3 15318
 
7.0%
5 14085
 
6.4%
2 11729
 
5.3%
9 11555
 
5.3%
8 4679
 
2.1%
4 4435
 
2.0%
6 3947
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190000
86.4%
Dash Punctuation 30000
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 86840
45.7%
1 33501
 
17.6%
3 15318
 
8.1%
5 14085
 
7.4%
2 11729
 
6.2%
9 11555
 
6.1%
8 4679
 
2.5%
4 4435
 
2.3%
6 3947
 
2.1%
7 3911
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 86840
39.5%
1 33501
 
15.2%
- 30000
 
13.6%
3 15318
 
7.0%
5 14085
 
6.4%
2 11729
 
5.3%
9 11555
 
5.3%
8 4679
 
2.1%
4 4435
 
2.0%
6 3947
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 86840
39.5%
1 33501
 
15.2%
- 30000
 
13.6%
3 15318
 
7.0%
5 14085
 
6.4%
2 11729
 
5.3%
9 11555
 
5.3%
8 4679
 
2.1%
4 4435
 
2.0%
6 3947
 
1.8%
Distinct6241
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1967-01-01 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T15:27:22.810062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:27:23.045836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
8001 
1
1999 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 8001
80.0%
1 1999
 
20.0%

Length

2024-05-11T15:27:23.278453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:23.491429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 8001
80.0%
1 1999
 
20.0%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8001 
영업/정상
1999 

Length

Max length5
Median length2
Mean length2.5997
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 8001
80.0%
영업/정상 1999
 
20.0%

Length

2024-05-11T15:27:23.708326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:23.881125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8001
80.0%
영업/정상 1999
 
20.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8001 
1
1999 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 8001
80.0%
1 1999
 
20.0%

Length

2024-05-11T15:27:24.046978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:24.547181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8001
80.0%
1 1999
 
20.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
8001 
영업
1999 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 8001
80.0%
영업 1999
 
20.0%

Length

2024-05-11T15:27:24.728901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:24.884002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 8001
80.0%
영업 1999
 
20.0%

폐업일자
Date

MISSING 

Distinct4554
Distinct (%)56.9%
Missing1999
Missing (%)20.0%
Memory size156.2 KiB
Minimum1989-06-28 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T15:27:25.045916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:27:25.272615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

전화번호
Text

MISSING 

Distinct6340
Distinct (%)89.6%
Missing2928
Missing (%)29.3%
Memory size156.2 KiB
2024-05-11T15:27:25.728455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.9116233
Min length2

Characters and Unicode

Total characters70095
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

Unique6120 ?
Unique (%)86.5%

Sample

1st row0222480203
2nd row02 9573300
3rd row02 9571175
4th row0209261277
5th row0202148209
ValueCountFrequency (%)
02 3469
32.3%
0200000000 178
 
1.7%
0 125
 
1.2%
0201768800 85
 
0.8%
00000 47
 
0.4%
1768800 18
 
0.2%
966 15
 
0.1%
957 14
 
0.1%
960 13
 
0.1%
963 13
 
0.1%
Other values (6401) 6762
63.0%
2024-05-11T15:27:26.466879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15966
22.8%
0 13587
19.4%
9 6504
9.3%
6 5482
 
7.8%
4 5169
 
7.4%
4332
 
6.2%
1 4094
 
5.8%
5 4022
 
5.7%
3 3826
 
5.5%
7 3643
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65763
93.8%
Space Separator 4332
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15966
24.3%
0 13587
20.7%
9 6504
9.9%
6 5482
 
8.3%
4 5169
 
7.9%
1 4094
 
6.2%
5 4022
 
6.1%
3 3826
 
5.8%
7 3643
 
5.5%
8 3470
 
5.3%
Space Separator
ValueCountFrequency (%)
4332
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70095
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15966
22.8%
0 13587
19.4%
9 6504
9.3%
6 5482
 
7.8%
4 5169
 
7.4%
4332
 
6.2%
1 4094
 
5.8%
5 4022
 
5.7%
3 3826
 
5.5%
7 3643
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15966
22.8%
0 13587
19.4%
9 6504
9.3%
6 5482
 
7.8%
4 5169
 
7.4%
4332
 
6.2%
1 4094
 
5.8%
5 4022
 
5.7%
3 3826
 
5.5%
7 3643
 
5.2%
Distinct4516
Distinct (%)45.2%
Missing12
Missing (%)0.1%
Memory size156.2 KiB
2024-05-11T15:27:27.049029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.1013216
Min length3

Characters and Unicode

Total characters50952
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

Unique2967 ?
Unique (%)29.7%

Sample

1st row27.20
2nd row59.80
3rd row9.00
4th row6.21
5th row10.00
ValueCountFrequency (%)
33.00 124
 
1.2%
26.40 119
 
1.2%
30.00 117
 
1.2%
20.00 98
 
1.0%
23.10 94
 
0.9%
19.80 83
 
0.8%
25.00 70
 
0.7%
66.00 70
 
0.7%
28.00 57
 
0.6%
29.70 57
 
0.6%
Other values (4506) 9099
91.1%
2024-05-11T15:27:27.866230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9988
19.6%
0 8401
16.5%
2 5406
10.6%
1 4662
9.1%
3 3816
 
7.5%
4 3577
 
7.0%
5 3528
 
6.9%
6 3280
 
6.4%
8 3174
 
6.2%
9 2648
 
5.2%
Other values (2) 2472
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40957
80.4%
Other Punctuation 9995
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8401
20.5%
2 5406
13.2%
1 4662
11.4%
3 3816
9.3%
4 3577
8.7%
5 3528
8.6%
6 3280
 
8.0%
8 3174
 
7.7%
9 2648
 
6.5%
7 2465
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 9988
99.9%
, 7
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50952
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9988
19.6%
0 8401
16.5%
2 5406
10.6%
1 4662
9.1%
3 3816
 
7.5%
4 3577
 
7.0%
5 3528
 
6.9%
6 3280
 
6.4%
8 3174
 
6.2%
9 2648
 
5.2%
Other values (2) 2472
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9988
19.6%
0 8401
16.5%
2 5406
10.6%
1 4662
9.1%
3 3816
 
7.5%
4 3577
 
7.0%
5 3528
 
6.9%
6 3280
 
6.4%
8 3174
 
6.2%
9 2648
 
5.2%
Other values (2) 2472
 
4.9%
Distinct181
Distinct (%)1.8%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:27:28.404396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0885177
Min length6

Characters and Unicode

Total characters60873
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

Unique19 ?
Unique (%)0.2%

Sample

1st row130848
2nd row130851
3rd row130869
4th row130860
5th row130827
ValueCountFrequency (%)
130872 629
 
6.3%
130840 424
 
4.2%
130842 323
 
3.2%
130851 319
 
3.2%
130817 291
 
2.9%
130862 278
 
2.8%
130805 272
 
2.7%
130831 235
 
2.4%
130860 228
 
2.3%
130802 225
 
2.3%
Other values (171) 6774
67.8%
2024-05-11T15:27:29.091880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13148
21.6%
3 11983
19.7%
1 11950
19.6%
8 10388
17.1%
2 2768
 
4.5%
7 2486
 
4.1%
4 2385
 
3.9%
6 2177
 
3.6%
5 1949
 
3.2%
- 885
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59988
98.5%
Dash Punctuation 885
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13148
21.9%
3 11983
20.0%
1 11950
19.9%
8 10388
17.3%
2 2768
 
4.6%
7 2486
 
4.1%
4 2385
 
4.0%
6 2177
 
3.6%
5 1949
 
3.2%
9 754
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 885
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60873
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13148
21.6%
3 11983
19.7%
1 11950
19.6%
8 10388
17.1%
2 2768
 
4.5%
7 2486
 
4.1%
4 2385
 
3.9%
6 2177
 
3.6%
5 1949
 
3.2%
- 885
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60873
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13148
21.6%
3 11983
19.7%
1 11950
19.6%
8 10388
17.1%
2 2768
 
4.5%
7 2486
 
4.1%
4 2385
 
3.9%
6 2177
 
3.6%
5 1949
 
3.2%
- 885
 
1.5%
Distinct7444
Distinct (%)74.5%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-11T15:27:29.534170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length56
Mean length25.616923
Min length15

Characters and Unicode

Total characters256118
Distinct characters355
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

Unique5968 ?
Unique (%)59.7%

Sample

1st row서울특별시 동대문구 전농동 20-425번지
2nd row서울특별시 동대문구 전농동 597-41
3rd row서울특별시 동대문구 청량리동 656-0번지 (홍릉길 39-14)
4th row서울특별시 동대문구 제기동 135-27번지 (제기로 25)
5th row서울특별시 동대문구 이문동 251-5번지
ValueCountFrequency (%)
서울특별시 9998
22.3%
동대문구 9997
22.3%
장안동 2457
 
5.5%
답십리동 1209
 
2.7%
전농동 1153
 
2.6%
제기동 1001
 
2.2%
이문동 921
 
2.1%
용두동 842
 
1.9%
회기동 802
 
1.8%
1층 684
 
1.5%
Other values (7068) 15738
35.1%
2024-05-11T15:27:30.196503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43403
 
16.9%
20278
 
7.9%
11012
 
4.3%
10177
 
4.0%
10170
 
4.0%
10087
 
3.9%
10033
 
3.9%
10012
 
3.9%
10011
 
3.9%
9998
 
3.9%
Other values (345) 110937
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 149761
58.5%
Decimal Number 49602
 
19.4%
Space Separator 43403
 
16.9%
Dash Punctuation 9543
 
3.7%
Open Punctuation 1750
 
0.7%
Close Punctuation 1750
 
0.7%
Other Punctuation 147
 
0.1%
Uppercase Letter 112
 
< 0.1%
Lowercase Letter 35
 
< 0.1%
Math Symbol 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
20278
13.5%
11012
 
7.4%
10177
 
6.8%
10170
 
6.8%
10087
 
6.7%
10033
 
6.7%
10012
 
6.7%
10011
 
6.7%
9998
 
6.7%
8620
 
5.8%
Other values (293) 39363
26.3%
Uppercase Letter
ValueCountFrequency (%)
S 15
13.4%
K 15
13.4%
B 14
12.5%
A 14
12.5%
F 7
 
6.2%
T 6
 
5.4%
J 6
 
5.4%
Y 5
 
4.5%
E 4
 
3.6%
W 4
 
3.6%
Other values (11) 22
19.6%
Decimal Number
ValueCountFrequency (%)
1 9517
19.2%
2 6696
13.5%
3 6599
13.3%
4 5157
10.4%
5 4153
8.4%
6 4134
8.3%
0 3689
 
7.4%
7 3286
 
6.6%
9 3282
 
6.6%
8 3089
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 7
20.0%
s 6
17.1%
x 6
17.1%
t 4
11.4%
l 4
11.4%
w 2
 
5.7%
a 2
 
5.7%
k 2
 
5.7%
f 1
 
2.9%
b 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 133
90.5%
. 9
 
6.1%
@ 3
 
2.0%
: 2
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 1749
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1749
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
43403
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9543
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149761
58.5%
Common 106210
41.5%
Latin 147
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
20278
13.5%
11012
 
7.4%
10177
 
6.8%
10170
 
6.8%
10087
 
6.7%
10033
 
6.7%
10012
 
6.7%
10011
 
6.7%
9998
 
6.7%
8620
 
5.8%
Other values (293) 39363
26.3%
Latin
ValueCountFrequency (%)
S 15
 
10.2%
K 15
 
10.2%
B 14
 
9.5%
A 14
 
9.5%
e 7
 
4.8%
F 7
 
4.8%
s 6
 
4.1%
x 6
 
4.1%
T 6
 
4.1%
J 6
 
4.1%
Other values (21) 51
34.7%
Common
ValueCountFrequency (%)
43403
40.9%
- 9543
 
9.0%
1 9517
 
9.0%
2 6696
 
6.3%
3 6599
 
6.2%
4 5157
 
4.9%
5 4153
 
3.9%
6 4134
 
3.9%
0 3689
 
3.5%
7 3286
 
3.1%
Other values (11) 10033
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149761
58.5%
ASCII 106357
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43403
40.8%
- 9543
 
9.0%
1 9517
 
8.9%
2 6696
 
6.3%
3 6599
 
6.2%
4 5157
 
4.8%
5 4153
 
3.9%
6 4134
 
3.9%
0 3689
 
3.5%
7 3286
 
3.1%
Other values (42) 10180
 
9.6%
Hangul
ValueCountFrequency (%)
20278
13.5%
11012
 
7.4%
10177
 
6.8%
10170
 
6.8%
10087
 
6.7%
10033
 
6.7%
10012
 
6.7%
10011
 
6.7%
9998
 
6.7%
8620
 
5.8%
Other values (293) 39363
26.3%

도로명주소
Text

MISSING 

Distinct3635
Distinct (%)86.7%
Missing5809
Missing (%)58.1%
Memory size156.2 KiB
2024-05-11T15:27:30.620168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length59
Mean length32.244572
Min length22

Characters and Unicode

Total characters135137
Distinct characters346
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

Unique3201 ?
Unique (%)76.4%

Sample

1st row서울특별시 동대문구 왕산로 226, 지하1층 (전농동, 호텔 더 디자이너스)
2nd row서울특별시 동대문구 홍릉로 39-6 (청량리동,(홍릉길 39-14))
3rd row서울특별시 동대문구 사가정로 229, 5층 (장안동)
4th row서울특별시 동대문구 한천로24길 74-8, 103호 (장안동)
5th row서울특별시 동대문구 한천로14길 45, 1층 (장안동)
ValueCountFrequency (%)
서울특별시 4191
 
16.3%
동대문구 4190
 
16.3%
1층 2170
 
8.5%
장안동 826
 
3.2%
제기동 393
 
1.5%
전농동 369
 
1.4%
이문동 350
 
1.4%
회기동 331
 
1.3%
답십리동 323
 
1.3%
용두동 261
 
1.0%
Other values (2280) 12242
47.7%
2024-05-11T15:27:31.282053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21455
 
15.9%
8767
 
6.5%
1 6954
 
5.1%
4901
 
3.6%
4897
 
3.6%
) 4883
 
3.6%
( 4883
 
3.6%
4530
 
3.4%
4377
 
3.2%
4348
 
3.2%
Other values (336) 65142
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78228
57.9%
Space Separator 21455
 
15.9%
Decimal Number 20483
 
15.2%
Close Punctuation 4884
 
3.6%
Open Punctuation 4884
 
3.6%
Other Punctuation 4223
 
3.1%
Dash Punctuation 803
 
0.6%
Uppercase Letter 114
 
0.1%
Math Symbol 38
 
< 0.1%
Lowercase Letter 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
8767
 
11.2%
4901
 
6.3%
4897
 
6.3%
4530
 
5.8%
4377
 
5.6%
4348
 
5.6%
4303
 
5.5%
4196
 
5.4%
4195
 
5.4%
4191
 
5.4%
Other values (287) 29523
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 23
20.2%
A 13
11.4%
S 11
9.6%
K 9
 
7.9%
F 8
 
7.0%
Y 6
 
5.3%
T 5
 
4.4%
J 5
 
4.4%
C 5
 
4.4%
W 4
 
3.5%
Other values (10) 25
21.9%
Decimal Number
ValueCountFrequency (%)
1 6954
34.0%
2 2940
14.4%
3 1987
 
9.7%
4 1597
 
7.8%
0 1429
 
7.0%
6 1325
 
6.5%
5 1269
 
6.2%
7 1154
 
5.6%
8 1048
 
5.1%
9 780
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
e 7
28.0%
t 4
16.0%
s 4
16.0%
l 4
16.0%
a 2
 
8.0%
w 2
 
8.0%
x 1
 
4.0%
b 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 4212
99.7%
. 9
 
0.2%
: 1
 
< 0.1%
/ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 4883
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 4883
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
21455
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 803
100.0%
Math Symbol
ValueCountFrequency (%)
~ 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78228
57.9%
Common 56770
42.0%
Latin 139
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
8767
 
11.2%
4901
 
6.3%
4897
 
6.3%
4530
 
5.8%
4377
 
5.6%
4348
 
5.6%
4303
 
5.5%
4196
 
5.4%
4195
 
5.4%
4191
 
5.4%
Other values (287) 29523
37.7%
Latin
ValueCountFrequency (%)
B 23
16.5%
A 13
 
9.4%
S 11
 
7.9%
K 9
 
6.5%
F 8
 
5.8%
e 7
 
5.0%
Y 6
 
4.3%
T 5
 
3.6%
J 5
 
3.6%
C 5
 
3.6%
Other values (18) 47
33.8%
Common
ValueCountFrequency (%)
21455
37.8%
1 6954
 
12.2%
) 4883
 
8.6%
( 4883
 
8.6%
, 4212
 
7.4%
2 2940
 
5.2%
3 1987
 
3.5%
4 1597
 
2.8%
0 1429
 
2.5%
6 1325
 
2.3%
Other values (11) 5105
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78228
57.9%
ASCII 56909
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21455
37.7%
1 6954
 
12.2%
) 4883
 
8.6%
( 4883
 
8.6%
, 4212
 
7.4%
2 2940
 
5.2%
3 1987
 
3.5%
4 1597
 
2.8%
0 1429
 
2.5%
6 1325
 
2.3%
Other values (39) 5244
 
9.2%
Hangul
ValueCountFrequency (%)
8767
 
11.2%
4901
 
6.3%
4897
 
6.3%
4530
 
5.8%
4377
 
5.6%
4348
 
5.6%
4303
 
5.5%
4196
 
5.4%
4195
 
5.4%
4191
 
5.4%
Other values (287) 29523
37.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct228
Distinct (%)5.6%
Missing5902
Missing (%)59.0%
Infinite0
Infinite (%)0.0%
Mean2537.6672
Minimum2400
Maximum2860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:31.563781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2400
5-th percentile2424
Q12473
median2547
Q32594
95-th percentile2639
Maximum2860
Range460
Interquartile range (IQR)121

Descriptive statistics

Standard deviation70.287103
Coefficient of variation (CV)0.027697526
Kurtosis-1.1193704
Mean2537.6672
Median Absolute Deviation (MAD)60
Skewness-0.14550196
Sum10399360
Variance4940.2768
MonotonicityNot monotonic
2024-05-11T15:27:31.813020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2454 160
 
1.6%
2573 126
 
1.3%
2453 102
 
1.0%
2637 83
 
0.8%
2639 78
 
0.8%
2624 77
 
0.8%
2473 72
 
0.7%
2572 70
 
0.7%
2644 66
 
0.7%
2440 60
 
0.6%
Other values (218) 3204
32.0%
(Missing) 5902
59.0%
ValueCountFrequency (%)
2400 22
0.2%
2401 5
 
0.1%
2402 8
 
0.1%
2403 9
0.1%
2404 5
 
0.1%
2405 11
0.1%
2406 14
0.1%
2407 1
 
< 0.1%
2409 13
0.1%
2410 6
 
0.1%
ValueCountFrequency (%)
2860 1
 
< 0.1%
2646 7
 
0.1%
2645 13
 
0.1%
2644 66
0.7%
2643 35
0.4%
2642 3
 
< 0.1%
2641 3
 
< 0.1%
2640 22
 
0.2%
2639 78
0.8%
2638 5
 
0.1%
Distinct8339
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T15:27:32.291132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length5.0599
Min length1

Characters and Unicode

Total characters50599
Distinct characters1078
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7416 ?
Unique (%)74.2%

Sample

1st row소마
2nd row엠키친 앤 카페
3rd row은지
4th row엄마손칼국수
5th row예인
ValueCountFrequency (%)
전주식당 39
 
0.4%
장안점 38
 
0.3%
실내포장마차 33
 
0.3%
경희대점 31
 
0.3%
청량리점 26
 
0.2%
김밥천국 23
 
0.2%
회기점 19
 
0.2%
답십리점 18
 
0.2%
진미식당 17
 
0.2%
장안식당 16
 
0.1%
Other values (8735) 10728
97.6%
2024-05-11T15:27:33.009269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1503
 
3.0%
1169
 
2.3%
1020
 
2.0%
989
 
2.0%
847
 
1.7%
780
 
1.5%
690
 
1.4%
665
 
1.3%
652
 
1.3%
617
 
1.2%
Other values (1068) 41667
82.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46549
92.0%
Space Separator 989
 
2.0%
Lowercase Letter 935
 
1.8%
Uppercase Letter 719
 
1.4%
Decimal Number 460
 
0.9%
Close Punctuation 398
 
0.8%
Open Punctuation 397
 
0.8%
Other Punctuation 133
 
0.3%
Dash Punctuation 12
 
< 0.1%
Math Symbol 3
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1503
 
3.2%
1169
 
2.5%
1020
 
2.2%
847
 
1.8%
780
 
1.7%
690
 
1.5%
665
 
1.4%
652
 
1.4%
617
 
1.3%
575
 
1.2%
Other values (986) 38031
81.7%
Lowercase Letter
ValueCountFrequency (%)
e 118
12.6%
o 105
 
11.2%
a 93
 
9.9%
n 63
 
6.7%
i 48
 
5.1%
c 47
 
5.0%
r 46
 
4.9%
s 46
 
4.9%
l 43
 
4.6%
t 43
 
4.6%
Other values (16) 283
30.3%
Uppercase Letter
ValueCountFrequency (%)
B 64
 
8.9%
A 59
 
8.2%
O 56
 
7.8%
C 54
 
7.5%
E 41
 
5.7%
S 39
 
5.4%
I 35
 
4.9%
T 34
 
4.7%
N 32
 
4.5%
M 32
 
4.5%
Other values (16) 273
38.0%
Other Punctuation
ValueCountFrequency (%)
. 44
33.1%
& 43
32.3%
' 15
 
11.3%
? 11
 
8.3%
, 10
 
7.5%
! 2
 
1.5%
: 2
 
1.5%
# 2
 
1.5%
/ 2
 
1.5%
1
 
0.8%
Decimal Number
ValueCountFrequency (%)
2 83
18.0%
0 83
18.0%
1 79
17.2%
9 42
9.1%
5 35
7.6%
4 35
7.6%
8 30
 
6.5%
7 29
 
6.3%
3 29
 
6.3%
6 15
 
3.3%
Math Symbol
ValueCountFrequency (%)
+ 2
66.7%
1
33.3%
Space Separator
ValueCountFrequency (%)
989
100.0%
Close Punctuation
ValueCountFrequency (%)
) 398
100.0%
Open Punctuation
ValueCountFrequency (%)
( 397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Letter Number
ValueCountFrequency (%)
2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46526
92.0%
Common 2394
 
4.7%
Latin 1656
 
3.3%
Han 23
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1503
 
3.2%
1169
 
2.5%
1020
 
2.2%
847
 
1.8%
780
 
1.7%
690
 
1.5%
665
 
1.4%
652
 
1.4%
617
 
1.3%
575
 
1.2%
Other values (966) 38008
81.7%
Latin
ValueCountFrequency (%)
e 118
 
7.1%
o 105
 
6.3%
a 93
 
5.6%
B 64
 
3.9%
n 63
 
3.8%
A 59
 
3.6%
O 56
 
3.4%
C 54
 
3.3%
i 48
 
2.9%
c 47
 
2.8%
Other values (43) 949
57.3%
Common
ValueCountFrequency (%)
989
41.3%
) 398
16.6%
( 397
16.6%
2 83
 
3.5%
0 83
 
3.5%
1 79
 
3.3%
. 44
 
1.8%
& 43
 
1.8%
9 42
 
1.8%
5 35
 
1.5%
Other values (19) 201
 
8.4%
Han
ValueCountFrequency (%)
3
 
13.0%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (10) 10
43.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46526
92.0%
ASCII 4044
 
8.0%
CJK 23
 
< 0.1%
Number Forms 2
 
< 0.1%
Punctuation 2
 
< 0.1%
None 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1503
 
3.2%
1169
 
2.5%
1020
 
2.2%
847
 
1.8%
780
 
1.7%
690
 
1.5%
665
 
1.4%
652
 
1.4%
617
 
1.3%
575
 
1.2%
Other values (966) 38008
81.7%
ASCII
ValueCountFrequency (%)
989
24.5%
) 398
 
9.8%
( 397
 
9.8%
e 118
 
2.9%
o 105
 
2.6%
a 93
 
2.3%
2 83
 
2.1%
0 83
 
2.1%
1 79
 
2.0%
B 64
 
1.6%
Other values (67) 1635
40.4%
CJK
ValueCountFrequency (%)
3
 
13.0%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
Other values (10) 10
43.5%
Number Forms
ValueCountFrequency (%)
2
100.0%
None
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
50.0%
1
50.0%
Math Operators
ValueCountFrequency (%)
1
100.0%
Distinct6553
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1998-12-31 00:00:00
Maximum2024-05-08 17:31:59
2024-05-11T15:27:33.263227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:27:33.530199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7873 
U
2127 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7873
78.7%
U 2127
 
21.3%

Length

2024-05-11T15:27:33.837575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:34.088383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7873
78.7%
u 2127
 
21.3%
Distinct1197
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T15:27:34.336386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:27:34.618212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4595 
분식
1839 
호프/통닭
920 
경양식
716 
기타
668 
Other values (22)
1262 

Length

Max length15
Median length2
Mean length2.6724
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row경양식
3rd row호프/통닭
4th row분식
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 4595
46.0%
분식 1839
18.4%
호프/통닭 920
 
9.2%
경양식 716
 
7.2%
기타 668
 
6.7%
중국식 311
 
3.1%
일식 286
 
2.9%
정종/대포집/소주방 188
 
1.9%
통닭(치킨) 152
 
1.5%
패스트푸드 74
 
0.7%
Other values (17) 251
 
2.5%

Length

2024-05-11T15:27:34.939298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4595
46.0%
분식 1839
18.4%
호프/통닭 920
 
9.2%
경양식 716
 
7.2%
기타 668
 
6.7%
중국식 311
 
3.1%
일식 286
 
2.9%
정종/대포집/소주방 188
 
1.9%
통닭(치킨 152
 
1.5%
패스트푸드 74
 
0.7%
Other values (17) 251
 
2.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4188
Distinct (%)45.1%
Missing722
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean204717.53
Minimum200665.24
Maximum206630.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:35.190040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200665.24
5-th percentile202536.15
Q1203815.14
median204886.67
Q3205725.45
95-th percentile206292.86
Maximum206630.9
Range5965.6575
Interquartile range (IQR)1910.3144

Descriptive statistics

Standard deviation1161.0071
Coefficient of variation (CV)0.0056712635
Kurtosis-0.68708371
Mean204717.53
Median Absolute Deviation (MAD)898.86469
Skewness-0.47559442
Sum1.8993693 × 109
Variance1347937.4
MonotonicityNot monotonic
2024-05-11T15:27:35.455869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
204081.282117393 36
 
0.4%
202186.468072494 35
 
0.4%
203793.67250079 34
 
0.3%
203996.013917877 33
 
0.3%
205980.772169045 31
 
0.3%
204082.111844228 28
 
0.3%
204089.817117361 27
 
0.3%
206325.349431713 27
 
0.3%
203075.098504907 26
 
0.3%
204884.451934202 22
 
0.2%
Other values (4178) 8979
89.8%
(Missing) 722
 
7.2%
ValueCountFrequency (%)
200665.244120436 1
 
< 0.1%
201995.643218229 1
 
< 0.1%
201998.969766069 1
 
< 0.1%
202000.516482784 2
 
< 0.1%
202013.401502902 3
< 0.1%
202014.988956307 3
< 0.1%
202015.296604 1
 
< 0.1%
202023.921749857 5
0.1%
202024.479054844 1
 
< 0.1%
202028.666639027 1
 
< 0.1%
ValueCountFrequency (%)
206630.901669352 1
 
< 0.1%
206607.014952243 5
0.1%
206603.429234746 1
 
< 0.1%
206603.229942876 2
 
< 0.1%
206592.423303981 2
 
< 0.1%
206590.046202018 4
< 0.1%
206586.572428103 2
 
< 0.1%
206582.46704114 1
 
< 0.1%
206574.561496753 3
< 0.1%
206573.59398246 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4188
Distinct (%)45.1%
Missing722
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean453043.74
Minimum450994.91
Maximum455917.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:35.737878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450994.91
5-th percentile451397.86
Q1452185.82
median452876.35
Q3453895.61
95-th percentile454895.85
Maximum455917.55
Range4922.6388
Interquartile range (IQR)1709.7818

Descriptive statistics

Standard deviation1111.1364
Coefficient of variation (CV)0.0024526029
Kurtosis-0.70378977
Mean453043.74
Median Absolute Deviation (MAD)803.75161
Skewness0.34947092
Sum4.2033398 × 109
Variance1234624
MonotonicityNot monotonic
2024-05-11T15:27:36.010335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453187.395154017 36
 
0.4%
452282.607415166 35
 
0.4%
453201.200861783 34
 
0.3%
453058.665828669 33
 
0.3%
455275.835949587 31
 
0.3%
452472.990548179 28
 
0.3%
453314.135663101 27
 
0.3%
452184.2101607 27
 
0.3%
452918.836458244 26
 
0.3%
451529.148204191 22
 
0.2%
Other values (4178) 8979
89.8%
(Missing) 722
 
7.2%
ValueCountFrequency (%)
450994.913744005 1
 
< 0.1%
451017.179310496 2
 
< 0.1%
451017.540622804 1
 
< 0.1%
451019.703974623 2
 
< 0.1%
451022.143962631 2
 
< 0.1%
451031.533506626 1
 
< 0.1%
451031.569748553 5
0.1%
451042.369315593 1
 
< 0.1%
451045.898346812 1
 
< 0.1%
451049.960154453 1
 
< 0.1%
ValueCountFrequency (%)
455917.552544887 2
 
< 0.1%
455899.982370316 1
 
< 0.1%
455846.122930171 1
 
< 0.1%
455833.63750058 1
 
< 0.1%
455813.713540339 9
0.1%
455803.028832488 5
0.1%
455797.417581881 9
0.1%
455790.631069022 2
 
< 0.1%
455774.398634748 2
 
< 0.1%
455771.62005247 5
0.1%

위생업태명
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한식
4072 
분식
1771 
<NA>
1316 
호프/통닭
805 
경양식
669 
Other values (21)
1367 

Length

Max length15
Median length2
Mean length2.8623
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row분식
2nd row경양식
3rd row호프/통닭
4th row분식
5th row호프/통닭

Common Values

ValueCountFrequency (%)
한식 4072
40.7%
분식 1771
17.7%
<NA> 1316
 
13.2%
호프/통닭 805
 
8.1%
경양식 669
 
6.7%
기타 269
 
2.7%
중국식 259
 
2.6%
일식 242
 
2.4%
정종/대포집/소주방 177
 
1.8%
통닭(치킨) 144
 
1.4%
Other values (16) 276
 
2.8%

Length

2024-05-11T15:27:36.306904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 4072
40.7%
분식 1771
17.7%
na 1316
 
13.2%
호프/통닭 805
 
8.1%
경양식 669
 
6.7%
기타 269
 
2.7%
중국식 259
 
2.6%
일식 242
 
2.4%
정종/대포집/소주방 177
 
1.8%
통닭(치킨 144
 
1.4%
Other values (16) 276
 
2.8%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)0.2%
Missing3802
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean0.25653437
Minimum0
Maximum18
Zeros5141
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:36.532988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.72196797
Coefficient of variation (CV)2.8143129
Kurtosis84.024006
Mean0.25653437
Median Absolute Deviation (MAD)0
Skewness6.1568908
Sum1590
Variance0.52123775
MonotonicityNot monotonic
2024-05-11T15:27:36.781011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 5141
51.4%
1 727
 
7.3%
2 218
 
2.2%
3 73
 
0.7%
4 24
 
0.2%
5 6
 
0.1%
9 2
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 3802
38.0%
ValueCountFrequency (%)
0 5141
51.4%
1 727
 
7.3%
2 218
 
2.2%
3 73
 
0.7%
4 24
 
0.2%
5 6
 
0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
18 1
 
< 0.1%
10 1
 
< 0.1%
9 2
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
5 6
 
0.1%
4 24
 
0.2%
3 73
 
0.7%
2 218
2.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)0.2%
Missing3797
Missing (%)38.0%
Infinite0
Infinite (%)0.0%
Mean0.41979687
Minimum0
Maximum15
Zeros4461
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:37.024946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum15
Range15
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.83872426
Coefficient of variation (CV)1.9979288
Kurtosis44.04248
Mean0.41979687
Median Absolute Deviation (MAD)0
Skewness4.3330678
Sum2604
Variance0.70345839
MonotonicityNot monotonic
2024-05-11T15:27:37.248042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 4461
44.6%
1 1096
 
11.0%
2 522
 
5.2%
3 96
 
1.0%
4 13
 
0.1%
5 6
 
0.1%
12 4
 
< 0.1%
15 1
 
< 0.1%
6 1
 
< 0.1%
8 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
(Missing) 3797
38.0%
ValueCountFrequency (%)
0 4461
44.6%
1 1096
 
11.0%
2 522
 
5.2%
3 96
 
1.0%
4 13
 
0.1%
5 6
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
12 4
 
< 0.1%
10 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 6
 
0.1%
4 13
 
0.1%
3 96
 
1.0%
2 522
5.2%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4588 
주택가주변
2506 
기타
2223 
유흥업소밀집지역
 
323
학교정화(상대)
 
175
Other values (3)
 
185

Length

Max length8
Median length7
Mean length4.0452
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4588
45.9%
주택가주변 2506
25.1%
기타 2223
22.2%
유흥업소밀집지역 323
 
3.2%
학교정화(상대) 175
 
1.8%
아파트지역 98
 
1.0%
결혼예식장주변 46
 
0.5%
학교정화(절대) 41
 
0.4%

Length

2024-05-11T15:27:37.919157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:38.150047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4588
45.9%
주택가주변 2506
25.1%
기타 2223
22.2%
유흥업소밀집지역 323
 
3.2%
학교정화(상대 175
 
1.8%
아파트지역 98
 
1.0%
결혼예식장주변 46
 
0.5%
학교정화(절대 41
 
0.4%

등급구분명
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
4771 
기타
3545 
지도
1136 
자율
 
350
 
119
Other values (3)
 
79

Length

Max length4
Median length2
Mean length2.9353
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4771
47.7%
기타 3545
35.4%
지도 1136
 
11.4%
자율 350
 
3.5%
119
 
1.2%
70
 
0.7%
우수 7
 
0.1%
관리 2
 
< 0.1%

Length

2024-05-11T15:27:38.415571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:38.651189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4771
47.7%
기타 3545
35.4%
지도 1136
 
11.4%
자율 350
 
3.5%
119
 
1.2%
70
 
0.7%
우수 7
 
0.1%
관리 2
 
< 0.1%

급수시설구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상수도전용
6142 
<NA>
3845 
상수도(음용)지하수(주방용)겸용
 
12
지하수전용
 
1

Length

Max length17
Median length5
Mean length4.6299
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 6142
61.4%
<NA> 3845
38.5%
상수도(음용)지하수(주방용)겸용 12
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-05-11T15:27:38.866483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:39.039929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 6142
61.4%
na 3845
38.5%
상수도(음용)지하수(주방용)겸용 12
 
0.1%
지하수전용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9787 
0
 
213

Length

Max length4
Median length4
Mean length3.9361
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> 9787
97.9%
0 213
 
2.1%

Length

2024-05-11T15:27:39.266845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:39.444321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9787
97.9%
0 213
 
2.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:39.703659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:39.916167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:40.109178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:40.272867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:40.431860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:40.623557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:40.822139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:41.023680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:41.221218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:41.400939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9778 
0
 
222

Length

Max length4
Median length4
Mean length3.9334
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> 9778
97.8%
0 222
 
2.2%

Length

2024-05-11T15:27:41.594782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:41.785139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9778
97.8%
0 222
 
2.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing1315
Missing (%)13.2%
Memory size97.7 KiB
False
8559 
True
 
126
(Missing)
1315 
ValueCountFrequency (%)
False 8559
85.6%
True 126
 
1.3%
(Missing) 1315
 
13.2%
2024-05-11T15:27:41.942546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING 

Distinct4167
Distinct (%)48.0%
Missing1315
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean55.617675
Minimum0
Maximum3072.18
Zeros13
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T15:27:42.212641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.15
Q122.68
median33
Q364.8
95-th percentile149.156
Maximum3072.18
Range3072.18
Interquartile range (IQR)42.12

Descriptive statistics

Standard deviation83.04661
Coefficient of variation (CV)1.4931694
Kurtosis346.42928
Mean55.617675
Median Absolute Deviation (MAD)14.78
Skewness13.718635
Sum483039.51
Variance6896.7395
MonotonicityNot monotonic
2024-05-11T15:27:42.609188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.4 106
 
1.1%
30.0 87
 
0.9%
33.0 85
 
0.9%
23.1 77
 
0.8%
19.8 76
 
0.8%
20.0 68
 
0.7%
66.0 58
 
0.6%
25.0 56
 
0.6%
29.7 53
 
0.5%
28.0 52
 
0.5%
Other values (4157) 7967
79.7%
(Missing) 1315
 
13.2%
ValueCountFrequency (%)
0.0 13
0.1%
0.7 1
 
< 0.1%
3.3 1
 
< 0.1%
3.5 1
 
< 0.1%
3.62 1
 
< 0.1%
4.25 1
 
< 0.1%
4.5 1
 
< 0.1%
4.8 1
 
< 0.1%
4.84 1
 
< 0.1%
4.95 1
 
< 0.1%
ValueCountFrequency (%)
3072.18 1
< 0.1%
2358.25 1
< 0.1%
1679.3 1
< 0.1%
1667.06 1
< 0.1%
1647.45 1
< 0.1%
1562.0 1
< 0.1%
1065.5 1
< 0.1%
988.75 1
< 0.1%
984.5 1
< 0.1%
976.8 1
< 0.1%

전통업소지정번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9999 
1
 
1

Length

Max length4
Median length4
Mean length3.9997
Min length1

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> 9999
> 99.9%
1 1
 
< 0.1%

Length

2024-05-11T15:27:42.859260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:27:43.050243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9999
> 99.9%
1 1
 
< 0.1%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1036430500003050000-101-2000-1223420001030<NA>3폐업2폐업20010824<NA><NA><NA>022248020327.20130848서울특별시 동대문구 전농동 20-425번지<NA><NA>소마2001-08-27 00:00:00I2018-08-31 23:59:59.0분식205532.672505452858.811221분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.2<NA><NA><NA>
1747130500003050000-101-2015-0033820151119<NA>1영업/정상1영업<NA><NA><NA><NA>02 957330059.80130851서울특별시 동대문구 전농동 597-41서울특별시 동대문구 왕산로 226, 지하1층 (전농동, 호텔 더 디자이너스)2554엠키친 앤 카페2021-11-05 13:29:39U2021-11-07 02:40:00.0경양식204138.950469453269.018798경양식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N59.8<NA><NA><NA>
947130500003050000-101-1999-1123319991006<NA>3폐업2폐업20200601<NA><NA><NA>02 95711759.00130869서울특별시 동대문구 청량리동 656-0번지 (홍릉길 39-14)서울특별시 동대문구 홍릉로 39-6 (청량리동,(홍릉길 39-14))2483은지2020-06-01 11:50:04U2020-06-04 02:40:00.0호프/통닭203788.502726453506.545828호프/통닭00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N9.0<NA><NA><NA>
643030500003050000-101-1995-1039619950317<NA>3폐업2폐업20111108<NA><NA><NA>02092612776.21130860서울특별시 동대문구 제기동 135-27번지 (제기로 25)<NA><NA>엄마손칼국수2008-07-17 13:39:09I2018-08-31 23:59:59.0분식203086.222958453820.357534분식00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N6.21<NA><NA><NA>
1128530500003050000-101-2001-1324520011213<NA>3폐업2폐업20020703<NA><NA><NA><NA>10.00130827서울특별시 동대문구 이문동 251-5번지<NA><NA>예인2001-12-13 00:00:00I2018-08-31 23:59:59.0호프/통닭205385.112959455813.71354호프/통닭00<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.0<NA><NA><NA>
312630500003050000-101-1991-0214919910920<NA>3폐업2폐업19921012<NA><NA><NA>020214820939.45130800서울특별시 동대문구 답십리동 19번지<NA><NA>한나훼밀리2002-01-28 00:00:00I2018-08-31 23:59:59.0한식205064.070668451723.771469한식02기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N39.45<NA><NA><NA>
1807730500003050000-101-2017-0020820170721<NA>3폐업2폐업20210406<NA><NA><NA><NA>133.98130838서울특별시 동대문구 장안동 285-1서울특별시 동대문구 사가정로 229, 5층 (장안동)2515쏠레2021-04-06 12:02:51U2021-04-08 02:40:00.0기타206152.840847452968.451677기타<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>Y133.98<NA><NA><NA>
1615430500003050000-101-2012-0008820120426<NA>3폐업2폐업20131018<NA><NA><NA>02 33946689144.75130842서울특별시 동대문구 장안동 381-3번지서울특별시 동대문구 한천로24길 74-8, 103호 (장안동)2625복분자숙성 간장게장 무한리필2013-09-12 14:44:24I2018-08-31 23:59:59.0한식205952.506671451814.91562한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N144.75<NA><NA><NA>
2012430500003050000-101-2022-002652022-08-29<NA>3폐업2폐업2023-12-11<NA><NA><NA><NA>24.50130-842서울특별시 동대문구 장안동 398-11서울특별시 동대문구 한천로14길 45, 1층 (장안동)2628써니호프2023-12-11 10:23:58U2022-11-01 23:03:00.0호프/통닭205698.284371451636.641316<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2078830500003050000-101-2024-000182024-01-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>133.18130-805서울특별시 동대문구 답십리동 530-16서울특별시 동대문구 고미술로 81, 1층 (답십리동)2622(주)메밀애찬2024-01-17 11:23:51I2023-11-30 23:09:00.0한식204855.976027451481.169445<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
1336330500003050000-101-2005-0019020050524<NA>3폐업2폐업20130213<NA><NA><NA>02 9644065331.00130817서울특별시 동대문구 용두동 29-4번지 (해성빌딩 2층) (고산자로 162)<NA><NA>품향촌2008-10-06 08:48:08I2018-08-31 23:59:59.0중국식203340.686375452607.843299중국식00<NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N331.0<NA><NA><NA>
994830500003050000-101-2000-1176820000508<NA>3폐업2폐업20141121<NA><NA><NA>022217680351.50130805서울특별시 동대문구 답십리동 497-12번지 (원동길 4-2)서울특별시 동대문구 천호대로 251-3 (답십리동,(원동길 4-2))<NA>맛깊은집2011-03-25 09:27:01I2018-08-31 23:59:59.0한식204368.872337451879.36394한식00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.5<NA><NA><NA>
451130500003050000-101-1993-0522119931027<NA>3폐업2폐업19981027<NA><NA><NA>0209590730101.45130874서울특별시 동대문구 휘경동 42-66번지<NA><NA>돈보2003-08-13 00:00:00I2018-08-31 23:59:59.0일식<NA><NA>일식01주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N101.45<NA><NA><NA>
1931530500003050000-101-2020-0028820200914<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.83130870서울특별시 동대문구 청량리동 773서울특별시 동대문구 홍릉로1길 17, 1층 (청량리동)2573성남순대2020-09-14 10:32:18I2020-09-16 00:23:12.0한식203785.187629453142.707683한식<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N19.83<NA><NA><NA>
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