Overview

Dataset statistics

Number of variables44
Number of observations2077
Missing cells31374
Missing cells (%)34.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory766.8 KiB
Average record size in memory378.1 B

Variable types

Categorical15
Text7
DateTime4
Unsupported10
Numeric7
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18077/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
남성종사자수 is highly imbalanced (57.0%)Imbalance
여성종사자수 is highly imbalanced (57.0%)Imbalance
급수시설구분명 is highly imbalanced (93.5%)Imbalance
총인원 is highly imbalanced (57.0%)Imbalance
본사종업원수 is highly imbalanced (74.9%)Imbalance
공장사무직종업원수 is highly imbalanced (74.0%)Imbalance
다중이용업소여부 is highly imbalanced (97.9%)Imbalance
인허가취소일자 has 2077 (100.0%) missing valuesMissing
폐업일자 has 766 (36.9%) missing valuesMissing
휴업시작일자 has 2077 (100.0%) missing valuesMissing
휴업종료일자 has 2077 (100.0%) missing valuesMissing
재개업일자 has 2077 (100.0%) missing valuesMissing
전화번호 has 942 (45.4%) missing valuesMissing
소재지면적 has 1262 (60.8%) missing valuesMissing
소재지우편번호 has 35 (1.7%) missing valuesMissing
지번주소 has 35 (1.7%) missing valuesMissing
도로명주소 has 407 (19.6%) missing valuesMissing
도로명우편번호 has 418 (20.1%) missing valuesMissing
업태구분명 has 2077 (100.0%) missing valuesMissing
좌표정보(X) has 35 (1.7%) missing valuesMissing
좌표정보(Y) has 35 (1.7%) missing valuesMissing
영업장주변구분명 has 2077 (100.0%) missing valuesMissing
등급구분명 has 2077 (100.0%) missing valuesMissing
공장판매직종업원수 has 1806 (87.0%) missing valuesMissing
보증액 has 1870 (90.0%) missing valuesMissing
월세액 has 1871 (90.1%) missing valuesMissing
다중이용업소여부 has 561 (27.0%) missing valuesMissing
시설총규모 has 561 (27.0%) missing valuesMissing
전통업소지정번호 has 2077 (100.0%) missing valuesMissing
전통업소주된음식 has 2077 (100.0%) missing valuesMissing
홈페이지 has 2077 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 31.26804417)Skewed
시설총규모 is highly skewed (γ1 = 34.06285469)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
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공장판매직종업원수 has 259 (12.5%) zerosZeros
보증액 has 197 (9.5%) zerosZeros
월세액 has 197 (9.5%) zerosZeros
시설총규모 has 1507 (72.6%) zerosZeros

Reproduction

Analysis started2024-04-29 19:35:31.252358
Analysis finished2024-04-29 19:35:32.588161
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
3000000
2077 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 2077
100.0%

Length

2024-04-30T04:35:32.654350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:32.742177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 2077
100.0%

관리번호
Text

UNIQUE 

Distinct2077
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
2024-04-30T04:35:32.885227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters45694
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

Unique2077 ?
Unique (%)100.0%

Sample

1st row3000000-134-2004-00001
2nd row3000000-134-2004-00002
3rd row3000000-134-2004-00003
4th row3000000-134-2004-00004
5th row3000000-134-2004-00005
ValueCountFrequency (%)
3000000-134-2004-00001 1
 
< 0.1%
3000000-134-2019-00046 1
 
< 0.1%
3000000-134-2019-00011 1
 
< 0.1%
3000000-134-2019-00010 1
 
< 0.1%
3000000-134-2019-00009 1
 
< 0.1%
3000000-134-2019-00008 1
 
< 0.1%
3000000-134-2019-00007 1
 
< 0.1%
3000000-134-2019-00006 1
 
< 0.1%
3000000-134-2019-00005 1
 
< 0.1%
3000000-134-2019-00004 1
 
< 0.1%
Other values (2067) 2067
99.5%
2024-04-30T04:35:33.149756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21772
47.6%
- 6231
 
13.6%
3 4815
 
10.5%
1 3957
 
8.7%
2 3402
 
7.4%
4 2855
 
6.2%
5 594
 
1.3%
6 550
 
1.2%
7 522
 
1.1%
9 509
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39463
86.4%
Dash Punctuation 6231
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21772
55.2%
3 4815
 
12.2%
1 3957
 
10.0%
2 3402
 
8.6%
4 2855
 
7.2%
5 594
 
1.5%
6 550
 
1.4%
7 522
 
1.3%
9 509
 
1.3%
8 487
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 6231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45694
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21772
47.6%
- 6231
 
13.6%
3 4815
 
10.5%
1 3957
 
8.7%
2 3402
 
7.4%
4 2855
 
6.2%
5 594
 
1.3%
6 550
 
1.2%
7 522
 
1.1%
9 509
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21772
47.6%
- 6231
 
13.6%
3 4815
 
10.5%
1 3957
 
8.7%
2 3402
 
7.4%
4 2855
 
6.2%
5 594
 
1.3%
6 550
 
1.2%
7 522
 
1.1%
9 509
 
1.1%
Distinct1504
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
Minimum2004-02-26 00:00:00
Maximum2024-04-22 00:00:00
2024-04-30T04:35:33.264514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:33.388736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
3
1311 
1
766 

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 1311
63.1%
1 766
36.9%

Length

2024-04-30T04:35:33.498850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:33.580496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1311
63.1%
1 766
36.9%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
폐업
1311 
영업/정상
766 

Length

Max length5
Median length2
Mean length3.1064035
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1311
63.1%
영업/정상 766
36.9%

Length

2024-04-30T04:35:33.667947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:33.754063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1311
63.1%
영업/정상 766
36.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
2
1311 
1
766 

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 1311
63.1%
1 766
36.9%

Length

2024-04-30T04:35:33.839448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:33.915654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1311
63.1%
1 766
36.9%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
폐업
1311 
영업
766 

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 1311
63.1%
영업 766
36.9%

Length

2024-04-30T04:35:34.002396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:34.082083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1311
63.1%
영업 766
36.9%

폐업일자
Date

MISSING 

Distinct992
Distinct (%)75.7%
Missing766
Missing (%)36.9%
Memory size16.4 KiB
Minimum2004-06-30 00:00:00
Maximum2024-04-24 00:00:00
2024-04-30T04:35:34.167574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:34.277614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

전화번호
Text

MISSING 

Distinct1094
Distinct (%)96.4%
Missing942
Missing (%)45.4%
Memory size16.4 KiB
2024-04-30T04:35:34.560916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.081938
Min length7

Characters and Unicode

Total characters12578
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

Unique1061 ?
Unique (%)93.5%

Sample

1st row02 7350153
2nd row02 3956823
3rd row02 7363551
4th row0222661087
5th row02 7386355
ValueCountFrequency (%)
02 870
35.4%
070 56
 
2.3%
741 22
 
0.9%
722 18
 
0.7%
720 17
 
0.7%
733 15
 
0.6%
725 13
 
0.5%
765 12
 
0.5%
766 12
 
0.5%
745 12
 
0.5%
Other values (1180) 1414
57.5%
2024-04-30T04:35:34.956463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2208
17.6%
0 1972
15.7%
1874
14.9%
7 1380
11.0%
3 1012
8.0%
5 793
 
6.3%
6 789
 
6.3%
4 731
 
5.8%
1 675
 
5.4%
8 586
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10704
85.1%
Space Separator 1874
 
14.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2208
20.6%
0 1972
18.4%
7 1380
12.9%
3 1012
9.5%
5 793
 
7.4%
6 789
 
7.4%
4 731
 
6.8%
1 675
 
6.3%
8 586
 
5.5%
9 558
 
5.2%
Space Separator
ValueCountFrequency (%)
1874
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12578
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2208
17.6%
0 1972
15.7%
1874
14.9%
7 1380
11.0%
3 1012
8.0%
5 793
 
6.3%
6 789
 
6.3%
4 731
 
5.8%
1 675
 
5.4%
8 586
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12578
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2208
17.6%
0 1972
15.7%
1874
14.9%
7 1380
11.0%
3 1012
8.0%
5 793
 
6.3%
6 789
 
6.3%
4 731
 
5.8%
1 675
 
5.4%
8 586
 
4.7%

소재지면적
Text

MISSING 

Distinct229
Distinct (%)28.1%
Missing1262
Missing (%)60.8%
Memory size16.4 KiB
2024-04-30T04:35:35.272296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.2503067
Min length3

Characters and Unicode

Total characters3464
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

Unique183 ?
Unique (%)22.5%

Sample

1st row46.00
2nd row10.00
3rd row82.31
4th row30.00
5th row0.00
ValueCountFrequency (%)
00 196
24.0%
3.30 122
15.0%
0.00 117
14.4%
10.00 25
 
3.1%
3.00 19
 
2.3%
30.00 18
 
2.2%
15.00 12
 
1.5%
9.90 7
 
0.9%
5.00 7
 
0.9%
20.00 7
 
0.9%
Other values (219) 285
35.0%
2024-04-30T04:35:35.694332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1433
41.4%
. 815
23.5%
3 389
 
11.2%
1 149
 
4.3%
2 130
 
3.8%
6 114
 
3.3%
5 112
 
3.2%
9 98
 
2.8%
4 94
 
2.7%
7 69
 
2.0%
Other values (2) 61
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2646
76.4%
Other Punctuation 818
 
23.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1433
54.2%
3 389
 
14.7%
1 149
 
5.6%
2 130
 
4.9%
6 114
 
4.3%
5 112
 
4.2%
9 98
 
3.7%
4 94
 
3.6%
7 69
 
2.6%
8 58
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 815
99.6%
, 3
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 3464
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1433
41.4%
. 815
23.5%
3 389
 
11.2%
1 149
 
4.3%
2 130
 
3.8%
6 114
 
3.3%
5 112
 
3.2%
9 98
 
2.8%
4 94
 
2.7%
7 69
 
2.0%
Other values (2) 61
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1433
41.4%
. 815
23.5%
3 389
 
11.2%
1 149
 
4.3%
2 130
 
3.8%
6 114
 
3.3%
5 112
 
3.2%
9 98
 
2.8%
4 94
 
2.7%
7 69
 
2.0%
Other values (2) 61
 
1.8%

소재지우편번호
Text

MISSING 

Distinct302
Distinct (%)14.8%
Missing35
Missing (%)1.7%
Memory size16.4 KiB
2024-04-30T04:35:35.982053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1650343
Min length6

Characters and Unicode

Total characters12589
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

Unique78 ?
Unique (%)3.8%

Sample

1st row110140
2nd row110803
3rd row110756
4th row110853
5th row110045
ValueCountFrequency (%)
110826 43
 
2.1%
110111 34
 
1.7%
110841 34
 
1.7%
110847 32
 
1.6%
110837 31
 
1.5%
110836 31
 
1.5%
110522 31
 
1.5%
110827 31
 
1.5%
110122 31
 
1.5%
110809 30
 
1.5%
Other values (292) 1714
83.9%
2024-04-30T04:35:36.365317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4853
38.5%
0 3199
25.4%
8 990
 
7.9%
2 726
 
5.8%
4 589
 
4.7%
3 530
 
4.2%
5 447
 
3.6%
7 401
 
3.2%
- 337
 
2.7%
6 328
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12252
97.3%
Dash Punctuation 337
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4853
39.6%
0 3199
26.1%
8 990
 
8.1%
2 726
 
5.9%
4 589
 
4.8%
3 530
 
4.3%
5 447
 
3.6%
7 401
 
3.3%
6 328
 
2.7%
9 189
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12589
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4853
38.5%
0 3199
25.4%
8 990
 
7.9%
2 726
 
5.8%
4 589
 
4.7%
3 530
 
4.2%
5 447
 
3.6%
7 401
 
3.2%
- 337
 
2.7%
6 328
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12589
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4853
38.5%
0 3199
25.4%
8 990
 
7.9%
2 726
 
5.8%
4 589
 
4.7%
3 530
 
4.2%
5 447
 
3.6%
7 401
 
3.2%
- 337
 
2.7%
6 328
 
2.6%

지번주소
Text

MISSING 

Distinct1522
Distinct (%)74.5%
Missing35
Missing (%)1.7%
Memory size16.4 KiB
2024-04-30T04:35:36.623258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length49
Mean length26.177277
Min length15

Characters and Unicode

Total characters53454
Distinct characters408
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

Unique1254 ?
Unique (%)61.4%

Sample

1st row서울특별시 종로구 수송동 **-*번지 석탄회관*층
2nd row서울특별시 종로구 구기동 ***-*번지 요진빌딩***호
3rd row서울특별시 종로구 적선동 **번지 적선현대빌딩***호
4th row서울특별시 종로구 종로*가 ***-*번지 외*필지(**번지)
5th row서울특별시 종로구 체부동 *-*번지 *층
ValueCountFrequency (%)
서울특별시 2041
19.5%
종로구 2037
19.4%
번지 1146
10.9%
874
 
8.3%
458
 
4.4%
410
 
3.9%
종로*가 233
 
2.2%
숭인동 215
 
2.0%
창신동 182
 
1.7%
명륜*가 101
 
1.0%
Other values (859) 2791
26.6%
2024-04-30T04:35:37.030191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 9797
18.3%
9718
18.2%
2426
 
4.5%
2360
 
4.4%
2103
 
3.9%
2101
 
3.9%
2089
 
3.9%
2058
 
3.9%
2045
 
3.8%
2041
 
3.8%
Other values (398) 16716
31.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31965
59.8%
Other Punctuation 9882
 
18.5%
Space Separator 9718
 
18.2%
Dash Punctuation 1272
 
2.4%
Lowercase Letter 211
 
0.4%
Uppercase Letter 159
 
0.3%
Decimal Number 140
 
0.3%
Close Punctuation 52
 
0.1%
Open Punctuation 52
 
0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2426
 
7.6%
2360
 
7.4%
2103
 
6.6%
2101
 
6.6%
2089
 
6.5%
2058
 
6.4%
2045
 
6.4%
2041
 
6.4%
1832
 
5.7%
1378
 
4.3%
Other values (332) 11532
36.1%
Lowercase Letter
ValueCountFrequency (%)
o 27
12.8%
w 26
12.3%
c 21
10.0%
i 15
 
7.1%
a 14
 
6.6%
r 14
 
6.6%
n 12
 
5.7%
m 11
 
5.2%
l 10
 
4.7%
k 9
 
4.3%
Other values (12) 52
24.6%
Uppercase Letter
ValueCountFrequency (%)
B 38
23.9%
S 19
11.9%
A 16
10.1%
K 13
 
8.2%
D 12
 
7.5%
L 9
 
5.7%
M 8
 
5.0%
G 6
 
3.8%
Y 6
 
3.8%
U 6
 
3.8%
Other values (11) 26
16.4%
Decimal Number
ValueCountFrequency (%)
1 39
27.9%
2 19
13.6%
4 14
 
10.0%
0 14
 
10.0%
5 13
 
9.3%
8 11
 
7.9%
7 10
 
7.1%
3 10
 
7.1%
6 7
 
5.0%
9 3
 
2.1%
Other Punctuation
ValueCountFrequency (%)
* 9797
99.1%
, 46
 
0.5%
. 29
 
0.3%
@ 6
 
0.1%
/ 3
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
9718
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1272
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31965
59.8%
Common 21117
39.5%
Latin 372
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2426
 
7.6%
2360
 
7.4%
2103
 
6.6%
2101
 
6.6%
2089
 
6.5%
2058
 
6.4%
2045
 
6.4%
2041
 
6.4%
1832
 
5.7%
1378
 
4.3%
Other values (332) 11532
36.1%
Latin
ValueCountFrequency (%)
B 38
 
10.2%
o 27
 
7.3%
w 26
 
7.0%
c 21
 
5.6%
S 19
 
5.1%
A 16
 
4.3%
i 15
 
4.0%
a 14
 
3.8%
r 14
 
3.8%
K 13
 
3.5%
Other values (35) 169
45.4%
Common
ValueCountFrequency (%)
* 9797
46.4%
9718
46.0%
- 1272
 
6.0%
) 52
 
0.2%
( 52
 
0.2%
, 46
 
0.2%
1 39
 
0.2%
. 29
 
0.1%
2 19
 
0.1%
4 14
 
0.1%
Other values (11) 79
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31965
59.8%
ASCII 21487
40.2%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 9797
45.6%
9718
45.2%
- 1272
 
5.9%
) 52
 
0.2%
( 52
 
0.2%
, 46
 
0.2%
1 39
 
0.2%
B 38
 
0.2%
. 29
 
0.1%
o 27
 
0.1%
Other values (54) 417
 
1.9%
Hangul
ValueCountFrequency (%)
2426
 
7.6%
2360
 
7.4%
2103
 
6.6%
2101
 
6.6%
2089
 
6.5%
2058
 
6.4%
2045
 
6.4%
2041
 
6.4%
1832
 
5.7%
1378
 
4.3%
Other values (332) 11532
36.1%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명주소
Text

MISSING 

Distinct1392
Distinct (%)83.4%
Missing407
Missing (%)19.6%
Memory size16.4 KiB
2024-04-30T04:35:37.245753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length48
Mean length34.020359
Min length21

Characters and Unicode

Total characters56814
Distinct characters401
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

Unique1210 ?
Unique (%)72.5%

Sample

1st row서울특별시 종로구 종로 *** (종로*가,외*필지(**번지))
2nd row서울특별시 종로구 자하문로*길 ** (체부동,*층)
3rd row서울특별시 종로구 청계천로 ** (관철동,지하*층)
4th row서울특별시 종로구 북촌로 **-* (재동)
5th row서울특별시 종로구 청계천로 **, **층 (서린동)
ValueCountFrequency (%)
서울특별시 1669
14.9%
종로구 1666
14.9%
1664
14.8%
745
 
6.6%
731
 
6.5%
종로 238
 
2.1%
종로*가 153
 
1.4%
창신동 146
 
1.3%
숭인동 143
 
1.3%
종로**길 93
 
0.8%
Other values (999) 3966
35.4%
2024-04-30T04:35:37.577201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9549
16.8%
* 9187
16.2%
3388
 
6.0%
2337
 
4.1%
, 1963
 
3.5%
1734
 
3.1%
1724
 
3.0%
1714
 
3.0%
1694
 
3.0%
( 1693
 
3.0%
Other values (391) 21831
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31852
56.1%
Other Punctuation 11160
 
19.6%
Space Separator 9549
 
16.8%
Open Punctuation 1693
 
3.0%
Close Punctuation 1693
 
3.0%
Dash Punctuation 342
 
0.6%
Uppercase Letter 212
 
0.4%
Decimal Number 206
 
0.4%
Lowercase Letter 95
 
0.2%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3388
 
10.6%
2337
 
7.3%
1734
 
5.4%
1724
 
5.4%
1714
 
5.4%
1694
 
5.3%
1684
 
5.3%
1673
 
5.3%
1669
 
5.2%
939
 
2.9%
Other values (329) 13296
41.7%
Uppercase Letter
ValueCountFrequency (%)
B 65
30.7%
A 28
13.2%
S 19
 
9.0%
D 15
 
7.1%
K 12
 
5.7%
C 10
 
4.7%
L 7
 
3.3%
U 6
 
2.8%
M 6
 
2.8%
Y 6
 
2.8%
Other values (12) 38
17.9%
Lowercase Letter
ValueCountFrequency (%)
c 14
14.7%
o 12
12.6%
a 9
9.5%
w 9
9.5%
i 8
8.4%
n 8
8.4%
r 6
 
6.3%
m 5
 
5.3%
d 5
 
5.3%
l 4
 
4.2%
Other values (8) 15
15.8%
Decimal Number
ValueCountFrequency (%)
1 48
23.3%
2 34
16.5%
0 27
13.1%
3 27
13.1%
4 18
 
8.7%
5 14
 
6.8%
8 13
 
6.3%
7 11
 
5.3%
9 7
 
3.4%
6 7
 
3.4%
Other Punctuation
ValueCountFrequency (%)
* 9187
82.3%
, 1963
 
17.6%
. 8
 
0.1%
/ 1
 
< 0.1%
& 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
9549
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1693
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1693
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31852
56.1%
Common 24653
43.4%
Latin 309
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3388
 
10.6%
2337
 
7.3%
1734
 
5.4%
1724
 
5.4%
1714
 
5.4%
1694
 
5.3%
1684
 
5.3%
1673
 
5.3%
1669
 
5.2%
939
 
2.9%
Other values (329) 13296
41.7%
Latin
ValueCountFrequency (%)
B 65
21.0%
A 28
 
9.1%
S 19
 
6.1%
D 15
 
4.9%
c 14
 
4.5%
o 12
 
3.9%
K 12
 
3.9%
C 10
 
3.2%
a 9
 
2.9%
w 9
 
2.9%
Other values (32) 116
37.5%
Common
ValueCountFrequency (%)
9549
38.7%
* 9187
37.3%
, 1963
 
8.0%
( 1693
 
6.9%
) 1693
 
6.9%
- 342
 
1.4%
1 48
 
0.2%
2 34
 
0.1%
0 27
 
0.1%
3 27
 
0.1%
Other values (10) 90
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31852
56.1%
ASCII 24960
43.9%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9549
38.3%
* 9187
36.8%
, 1963
 
7.9%
( 1693
 
6.8%
) 1693
 
6.8%
- 342
 
1.4%
B 65
 
0.3%
1 48
 
0.2%
2 34
 
0.1%
A 28
 
0.1%
Other values (50) 358
 
1.4%
Hangul
ValueCountFrequency (%)
3388
 
10.6%
2337
 
7.3%
1734
 
5.4%
1724
 
5.4%
1714
 
5.4%
1694
 
5.3%
1684
 
5.3%
1673
 
5.3%
1669
 
5.2%
939
 
2.9%
Other values (329) 13296
41.7%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct185
Distinct (%)11.2%
Missing418
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3130.994
Minimum3001
Maximum16425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:37.712594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3001
5-th percentile3015
Q13079
median3121
Q33163.5
95-th percentile3192
Maximum16425
Range13424
Interquartile range (IQR)84.5

Descriptive statistics

Standard deviation364.02288
Coefficient of variation (CV)0.11626432
Kurtosis1094.4139
Mean3130.994
Median Absolute Deviation (MAD)42
Skewness31.268044
Sum5194319
Variance132512.66
MonotonicityNot monotonic
2024-04-30T04:35:37.838551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3150 34
 
1.6%
3115 33
 
1.6%
3173 33
 
1.6%
3130 32
 
1.5%
3195 30
 
1.4%
3121 30
 
1.4%
3192 28
 
1.3%
3157 28
 
1.3%
3126 28
 
1.3%
3129 27
 
1.3%
Other values (175) 1356
65.3%
(Missing) 418
 
20.1%
ValueCountFrequency (%)
3001 2
 
0.1%
3002 1
 
< 0.1%
3003 5
0.2%
3004 6
0.3%
3005 5
0.2%
3006 3
 
0.1%
3007 7
0.3%
3008 9
0.4%
3009 8
0.4%
3010 3
 
0.1%
ValueCountFrequency (%)
16425 1
 
< 0.1%
7282 1
 
< 0.1%
7265 1
 
< 0.1%
4990 1
 
< 0.1%
3198 7
 
0.3%
3197 14
0.7%
3196 5
 
0.2%
3195 30
1.4%
3194 10
 
0.5%
3193 12
 
0.6%
Distinct2002
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
2024-04-30T04:35:38.263327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length27
Mean length7.6408281
Min length2

Characters and Unicode

Total characters15870
Distinct characters695
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1942 ?
Unique (%)93.5%

Sample

1st row서광인터내셔널
2nd row씨네인터내셔널
3rd row만다발효(주)만다코리아지점
4th row종로4가건강원
5th row미건의료기효자지점
ValueCountFrequency (%)
주식회사 116
 
4.3%
지에스25 35
 
1.3%
세븐일레븐 21
 
0.8%
아리따움 12
 
0.4%
애터미 12
 
0.4%
인셀덤 9
 
0.3%
광화문점 9
 
0.3%
정관장 8
 
0.3%
종로 7
 
0.3%
아모레 7
 
0.3%
Other values (2197) 2472
91.3%
2024-04-30T04:35:38.663333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
632
 
4.0%
499
 
3.1%
496
 
3.1%
) 489
 
3.1%
( 488
 
3.1%
455
 
2.9%
365
 
2.3%
304
 
1.9%
270
 
1.7%
264
 
1.7%
Other values (685) 11608
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13212
83.3%
Space Separator 632
 
4.0%
Close Punctuation 489
 
3.1%
Open Punctuation 488
 
3.1%
Uppercase Letter 449
 
2.8%
Lowercase Letter 309
 
1.9%
Decimal Number 237
 
1.5%
Other Punctuation 39
 
0.2%
Dash Punctuation 13
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
499
 
3.8%
496
 
3.8%
455
 
3.4%
365
 
2.8%
304
 
2.3%
270
 
2.0%
264
 
2.0%
211
 
1.6%
201
 
1.5%
184
 
1.4%
Other values (614) 9963
75.4%
Uppercase Letter
ValueCountFrequency (%)
S 47
 
10.5%
G 31
 
6.9%
T 29
 
6.5%
O 27
 
6.0%
C 27
 
6.0%
A 26
 
5.8%
N 24
 
5.3%
H 23
 
5.1%
L 23
 
5.1%
E 23
 
5.1%
Other values (15) 169
37.6%
Lowercase Letter
ValueCountFrequency (%)
e 42
13.6%
a 31
 
10.0%
i 28
 
9.1%
o 24
 
7.8%
n 24
 
7.8%
r 20
 
6.5%
l 20
 
6.5%
s 17
 
5.5%
c 12
 
3.9%
t 12
 
3.9%
Other values (14) 79
25.6%
Decimal Number
ValueCountFrequency (%)
2 76
32.1%
5 68
28.7%
1 25
 
10.5%
4 20
 
8.4%
3 17
 
7.2%
0 13
 
5.5%
6 7
 
3.0%
7 5
 
2.1%
8 4
 
1.7%
9 2
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 15
38.5%
& 9
23.1%
, 6
 
15.4%
? 5
 
12.8%
3
 
7.7%
# 1
 
2.6%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
632
100.0%
Close Punctuation
ValueCountFrequency (%)
) 489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 488
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13211
83.2%
Common 1900
 
12.0%
Latin 758
 
4.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
499
 
3.8%
496
 
3.8%
455
 
3.4%
365
 
2.8%
304
 
2.3%
270
 
2.0%
264
 
2.0%
211
 
1.6%
201
 
1.5%
184
 
1.4%
Other values (613) 9962
75.4%
Latin
ValueCountFrequency (%)
S 47
 
6.2%
e 42
 
5.5%
a 31
 
4.1%
G 31
 
4.1%
T 29
 
3.8%
i 28
 
3.7%
O 27
 
3.6%
C 27
 
3.6%
A 26
 
3.4%
o 24
 
3.2%
Other values (39) 446
58.8%
Common
ValueCountFrequency (%)
632
33.3%
) 489
25.7%
( 488
25.7%
2 76
 
4.0%
5 68
 
3.6%
1 25
 
1.3%
4 20
 
1.1%
3 17
 
0.9%
. 15
 
0.8%
0 13
 
0.7%
Other values (12) 57
 
3.0%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13211
83.2%
ASCII 2655
 
16.7%
None 3
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
632
23.8%
) 489
18.4%
( 488
18.4%
2 76
 
2.9%
5 68
 
2.6%
S 47
 
1.8%
e 42
 
1.6%
a 31
 
1.2%
G 31
 
1.2%
T 29
 
1.1%
Other values (60) 722
27.2%
Hangul
ValueCountFrequency (%)
499
 
3.8%
496
 
3.8%
455
 
3.4%
365
 
2.8%
304
 
2.3%
270
 
2.0%
264
 
2.0%
211
 
1.6%
201
 
1.5%
184
 
1.4%
Other values (613) 9962
75.4%
None
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1985
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
Minimum2004-03-29 00:00:00
Maximum2024-04-24 17:12:30
2024-04-30T04:35:38.799178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:38.929273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
I
1345 
U
731 
D
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
I 1345
64.8%
U 731
35.2%
D 1
 
< 0.1%

Length

2024-04-30T04:35:39.049968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:39.164385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1345
64.8%
u 731
35.2%
d 1
 
< 0.1%
Distinct721
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T04:35:39.269913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:35:39.392641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1180
Distinct (%)57.8%
Missing35
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean199069.31
Minimum189784.91
Maximum206813.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:39.516554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189784.91
5-th percentile196555.03
Q1197607.4
median198992.79
Q3200284.08
95-th percentile201744.68
Maximum206813.62
Range17028.708
Interquartile range (IQR)2676.6814

Descriptive statistics

Standard deviation1660.0667
Coefficient of variation (CV)0.0083391391
Kurtosis-0.24114707
Mean199069.31
Median Absolute Deviation (MAD)1360.8553
Skewness-0.043439854
Sum4.0649953 × 108
Variance2755821.3
MonotonicityNot monotonic
2024-04-30T04:35:39.632189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198324.653631679 31
 
1.5%
198150.300374121 25
 
1.2%
199045.043602772 23
 
1.1%
201273.887781838 23
 
1.1%
197607.398336321 16
 
0.8%
199812.609633255 15
 
0.7%
197181.393301659 14
 
0.7%
201258.062657124 13
 
0.6%
201850.462764525 13
 
0.6%
198658.943470079 13
 
0.6%
Other values (1170) 1856
89.4%
(Missing) 35
 
1.7%
ValueCountFrequency (%)
189784.908763399 1
 
< 0.1%
190934.205820178 1
 
< 0.1%
196010.602015955 1
 
< 0.1%
196047.812876606 1
 
< 0.1%
196051.036130261 1
 
< 0.1%
196059.394152414 1
 
< 0.1%
196068.538240402 2
 
0.1%
196079.849668445 2
 
0.1%
196092.743907822 7
0.3%
196112.95679095 3
0.1%
ValueCountFrequency (%)
206813.616512143 1
 
< 0.1%
201966.262330671 1
 
< 0.1%
201962.62904341 2
 
0.1%
201961.92701636 1
 
< 0.1%
201960.951300031 5
0.2%
201959.37639057 1
 
< 0.1%
201958.489788275 2
 
0.1%
201949.65163583 1
 
< 0.1%
201946.86632604 8
0.4%
201937.460305076 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1180
Distinct (%)57.8%
Missing35
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean452715.12
Minimum420426.91
Maximum457030.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:39.758866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum420426.91
5-th percentile451896.03
Q1452119.72
median452382.35
Q3452900.78
95-th percentile455616.98
Maximum457030.13
Range36603.222
Interquartile range (IQR)781.05379

Descriptive statistics

Standard deviation1275.1859
Coefficient of variation (CV)0.0028167513
Kurtosis202.845
Mean452715.12
Median Absolute Deviation (MAD)325.21921
Skewness-6.8709829
Sum9.2444428 × 108
Variance1626099.1
MonotonicityNot monotonic
2024-04-30T04:35:39.898445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452252.812389497 31
 
1.5%
452019.212642931 25
 
1.2%
451939.677286976 23
 
1.1%
452163.292543039 23
 
1.1%
452120.026024435 16
 
0.8%
452132.648343993 15
 
0.7%
452458.826651573 14
 
0.7%
452787.132831042 13
 
0.6%
452407.508781009 13
 
0.6%
452604.254902527 13
 
0.6%
Other values (1170) 1856
89.4%
(Missing) 35
 
1.7%
ValueCountFrequency (%)
420426.906405359 1
 
< 0.1%
446328.212964956 1
 
< 0.1%
446806.690149729 1
 
< 0.1%
450161.864274532 1
 
< 0.1%
451543.629004831 1
 
< 0.1%
451580.195594285 1
 
< 0.1%
451658.76871749 3
0.1%
451678.787536538 2
0.1%
451682.368379486 1
 
< 0.1%
451683.728773742 2
0.1%
ValueCountFrequency (%)
457030.128121556 1
< 0.1%
456953.830967924 1
< 0.1%
456938.881785189 1
< 0.1%
456868.007813687 1
< 0.1%
456820.854229395 1
< 0.1%
456770.721646662 1
< 0.1%
456750.289960344 1
< 0.1%
456741.351523696 1
< 0.1%
456736.653120123 1
< 0.1%
456713.766839892 1
< 0.1%

위생업태명
Categorical

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
영업장판매
741 
<NA>
561 
전자상거래(통신판매업)
403 
통신판매
122 
방문판매
116 
Other values (6)
134 

Length

Max length14
Median length12
Mean length6.05922
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업장판매 741
35.7%
<NA> 561
27.0%
전자상거래(통신판매업) 403
19.4%
통신판매 122
 
5.9%
방문판매 116
 
5.6%
다단계판매 69
 
3.3%
전화권유판매 26
 
1.3%
기타(복합 등) 18
 
0.9%
도매업(유통) 12
 
0.6%
기타 건강기능식품일반판매업 8
 
0.4%

Length

2024-04-30T04:35:40.029503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
영업장판매 741
35.2%
na 561
26.7%
전자상거래(통신판매업 403
19.2%
통신판매 122
 
5.8%
방문판매 116
 
5.5%
다단계판매 69
 
3.3%
전화권유판매 26
 
1.2%
기타(복합 18
 
0.9%
18
 
0.9%
도매업(유통 12
 
0.6%
Other values (3) 17
 
0.8%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1894 
0
 
183

Length

Max length4
Median length4
Mean length3.7356765
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> 1894
91.2%
0 183
 
8.8%

Length

2024-04-30T04:35:40.131461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:40.234084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1894
91.2%
0 183
 
8.8%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1894 
0
 
183

Length

Max length4
Median length4
Mean length3.7356765
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> 1894
91.2%
0 183
 
8.8%

Length

2024-04-30T04:35:40.345450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:40.438606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1894
91.2%
0 183
 
8.8%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
2061 
상수도전용
 
16

Length

Max length5
Median length4
Mean length4.0077034
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2061
99.2%
상수도전용 16
 
0.8%

Length

2024-04-30T04:35:40.527066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:40.626487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2061
99.2%
상수도전용 16
 
0.8%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1894 
0
 
183

Length

Max length4
Median length4
Mean length3.7356765
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> 1894
91.2%
0 183
 
8.8%

Length

2024-04-30T04:35:40.727111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:40.820219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1894
91.2%
0 183
 
8.8%

본사종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1806 
0
265 
1
 
4
7
 
1
2
 
1

Length

Max length4
Median length4
Mean length3.6085701
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1806
87.0%
0 265
 
12.8%
1 4
 
0.2%
7 1
 
< 0.1%
2 1
 
< 0.1%

Length

2024-04-30T04:35:40.922588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:41.015801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1806
87.0%
0 265
 
12.8%
1 4
 
0.2%
7 1
 
< 0.1%
2 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1807 
0
254 
1
 
14
2
 
1
4
 
1

Length

Max length4
Median length4
Mean length3.6100144
Min length1

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 1807
87.0%
0 254
 
12.2%
1 14
 
0.7%
2 1
 
< 0.1%
4 1
 
< 0.1%

Length

2024-04-30T04:35:41.120907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:41.223952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1807
87.0%
0 254
 
12.2%
1 14
 
0.7%
2 1
 
< 0.1%
4 1
 
< 0.1%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)2.6%
Missing1806
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean0.59778598
Minimum0
Maximum70
Zeros259
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:41.303457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum70
Range70
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8667799
Coefficient of variation (CV)9.8141812
Kurtosis129.64054
Mean0.59778598
Median Absolute Deviation (MAD)0
Skewness11.361246
Sum162
Variance34.419106
MonotonicityNot monotonic
2024-04-30T04:35:41.391556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 259
 
12.5%
1 4
 
0.2%
2 3
 
0.1%
3 2
 
0.1%
10 1
 
< 0.1%
66 1
 
< 0.1%
70 1
 
< 0.1%
(Missing) 1806
87.0%
ValueCountFrequency (%)
0 259
12.5%
1 4
 
0.2%
2 3
 
0.1%
3 2
 
0.1%
10 1
 
< 0.1%
66 1
 
< 0.1%
70 1
 
< 0.1%
ValueCountFrequency (%)
70 1
 
< 0.1%
66 1
 
< 0.1%
10 1
 
< 0.1%
3 2
 
0.1%
2 3
 
0.1%
1 4
 
0.2%
0 259
12.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1810 
0
267 

Length

Max length4
Median length4
Mean length3.6143476
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 1810
87.1%
0 267
 
12.9%

Length

2024-04-30T04:35:41.492847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:41.586715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1810
87.1%
0 267
 
12.9%
Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size16.4 KiB
<NA>
1199 
자가
522 
임대
356 

Length

Max length4
Median length4
Mean length3.1545498
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1199
57.7%
자가 522
25.1%
임대 356
 
17.1%

Length

2024-04-30T04:35:41.689616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:35:41.786353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1199
57.7%
자가 522
25.1%
임대 356
 
17.1%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)4.3%
Missing1870
Missing (%)90.0%
Infinite0
Infinite (%)0.0%
Mean3775362.3
Minimum0
Maximum5.7 × 108
Zeros197
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:41.857550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5.7 × 108
Range5.7 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation40166631
Coefficient of variation (CV)10.639146
Kurtosis194.39804
Mean3775362.3
Median Absolute Deviation (MAD)0
Skewness13.773307
Sum7.815 × 108
Variance1.6133583 × 1015
MonotonicityNot monotonic
2024-04-30T04:35:41.937964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 197
 
9.5%
15000000 2
 
0.1%
5000000 2
 
0.1%
570000000 1
 
< 0.1%
80000000 1
 
< 0.1%
30000000 1
 
< 0.1%
1500000 1
 
< 0.1%
50000000 1
 
< 0.1%
10000000 1
 
< 0.1%
(Missing) 1870
90.0%
ValueCountFrequency (%)
0 197
9.5%
1500000 1
 
< 0.1%
5000000 2
 
0.1%
10000000 1
 
< 0.1%
15000000 2
 
0.1%
30000000 1
 
< 0.1%
50000000 1
 
< 0.1%
80000000 1
 
< 0.1%
570000000 1
 
< 0.1%
ValueCountFrequency (%)
570000000 1
 
< 0.1%
80000000 1
 
< 0.1%
50000000 1
 
< 0.1%
30000000 1
 
< 0.1%
15000000 2
 
0.1%
10000000 1
 
< 0.1%
5000000 2
 
0.1%
1500000 1
 
< 0.1%
0 197
9.5%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)4.9%
Missing1871
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean80097.087
Minimum0
Maximum7200000
Zeros197
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:42.020358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7200000
Range7200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation594582.85
Coefficient of variation (CV)7.4232769
Kurtosis107.51531
Mean80097.087
Median Absolute Deviation (MAD)0
Skewness9.8504128
Sum16500000
Variance3.5352877 × 1011
MonotonicityNot monotonic
2024-04-30T04:35:42.117670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 197
 
9.5%
1000000 1
 
< 0.1%
300000 1
 
< 0.1%
7200000 1
 
< 0.1%
3000000 1
 
< 0.1%
150000 1
 
< 0.1%
250000 1
 
< 0.1%
3300000 1
 
< 0.1%
500000 1
 
< 0.1%
800000 1
 
< 0.1%
(Missing) 1871
90.1%
ValueCountFrequency (%)
0 197
9.5%
150000 1
 
< 0.1%
250000 1
 
< 0.1%
300000 1
 
< 0.1%
500000 1
 
< 0.1%
800000 1
 
< 0.1%
1000000 1
 
< 0.1%
3000000 1
 
< 0.1%
3300000 1
 
< 0.1%
7200000 1
 
< 0.1%
ValueCountFrequency (%)
7200000 1
 
< 0.1%
3300000 1
 
< 0.1%
3000000 1
 
< 0.1%
1000000 1
 
< 0.1%
800000 1
 
< 0.1%
500000 1
 
< 0.1%
300000 1
 
< 0.1%
250000 1
 
< 0.1%
150000 1
 
< 0.1%
0 197
9.5%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.1%
Missing561
Missing (%)27.0%
Memory size4.2 KiB
False
1513 
True
 
3
(Missing)
561 
ValueCountFrequency (%)
False 1513
72.8%
True 3
 
0.1%
(Missing) 561
 
27.0%
2024-04-30T04:35:42.204638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct10
Distinct (%)0.7%
Missing561
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean0.29216359
Minimum0
Maximum255
Zeros1507
Zeros (%)72.6%
Negative0
Negative (%)0.0%
Memory size18.4 KiB
2024-04-30T04:35:42.276056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum255
Range255
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.8856162
Coefficient of variation (CV)23.567674
Kurtosis1242.0225
Mean0.29216359
Median Absolute Deviation (MAD)0
Skewness34.062855
Sum442.92
Variance47.41171
MonotonicityNot monotonic
2024-04-30T04:35:42.384080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.0 1507
72.6%
255.0 1
 
< 0.1%
12.22 1
 
< 0.1%
46.34 1
 
< 0.1%
54.6 1
 
< 0.1%
30.0 1
 
< 0.1%
23.46 1
 
< 0.1%
3.3 1
 
< 0.1%
13.0 1
 
< 0.1%
5.0 1
 
< 0.1%
(Missing) 561
 
27.0%
ValueCountFrequency (%)
0.0 1507
72.6%
3.3 1
 
< 0.1%
5.0 1
 
< 0.1%
12.22 1
 
< 0.1%
13.0 1
 
< 0.1%
23.46 1
 
< 0.1%
30.0 1
 
< 0.1%
46.34 1
 
< 0.1%
54.6 1
 
< 0.1%
255.0 1
 
< 0.1%
ValueCountFrequency (%)
255.0 1
 
< 0.1%
54.6 1
 
< 0.1%
46.34 1
 
< 0.1%
30.0 1
 
< 0.1%
23.46 1
 
< 0.1%
13.0 1
 
< 0.1%
12.22 1
 
< 0.1%
5.0 1
 
< 0.1%
3.3 1
 
< 0.1%
0.0 1507
72.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2077
Missing (%)100.0%
Memory size18.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030000003000000-134-2004-0000120040226<NA>3폐업2폐업20050127<NA><NA><NA>02 7350153<NA>110140서울특별시 종로구 수송동 **-*번지 석탄회관*층<NA><NA>서광인터내셔널2004-05-27 00:00:00I2018-08-31 23:59:59.0<NA>198204.837323452293.432531영업장판매<NA><NA><NA><NA><NA><NA>0000임대<NA><NA>N0.0<NA><NA><NA>
130000003000000-134-2004-0000220040227<NA>3폐업2폐업20040827<NA><NA><NA>02 3956823<NA>110803서울특별시 종로구 구기동 ***-*번지 요진빌딩***호<NA><NA>씨네인터내셔널2004-03-29 00:00:00I2018-08-31 23:59:59.0<NA>196092.743908456198.595932영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230000003000000-134-2004-0000320040304<NA>3폐업2폐업20070312<NA><NA><NA>02 7363551<NA>110756서울특별시 종로구 적선동 **번지 적선현대빌딩***호<NA><NA>만다발효(주)만다코리아지점2004-06-16 00:00:00I2018-08-31 23:59:59.0<NA>197567.849954452567.159554영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330000003000000-134-2004-0000420040313<NA>3폐업2폐업20171222<NA><NA><NA>0222661087<NA>110853서울특별시 종로구 종로*가 ***-*번지 외*필지(**번지)서울특별시 종로구 종로 *** (종로*가,외*필지(**번지))3194종로4가건강원2017-12-22 13:44:05I2018-08-31 23:59:59.0<NA>199672.728576452018.394947영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430000003000000-134-2004-0000520040326<NA>3폐업2폐업20171222<NA><NA><NA>02 7386355<NA>110045서울특별시 종로구 체부동 *-*번지 *층서울특별시 종로구 자하문로*길 ** (체부동,*층)3040미건의료기효자지점2017-12-22 14:06:51I2018-08-31 23:59:59.0<NA>197306.7724452970.369825영업장판매<NA><NA><NA><NA>상수도전용<NA>1110임대<NA><NA>N0.0<NA><NA><NA>
530000003000000-134-2004-0000620040329<NA>3폐업2폐업20101101<NA><NA><NA>0222531051<NA>110825서울특별시 종로구 숭인동 ***-**번지 삼일빌딩***호<NA><NA>고보상사2004-05-27 00:00:00I2018-08-31 23:59:59.0<NA>201853.26838452392.927257영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630000003000000-134-2004-0000720040331<NA>3폐업2폐업20220714<NA><NA><NA>02 7335150<NA>110111서울특별시 종로구 관철동 *** 지하*층서울특별시 종로구 청계천로 ** (관철동,지하*층)3189송도삼업2022-07-14 16:46:36U2021-12-06 23:06:00.0<NA>198484.065112451860.352943<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
730000003000000-134-2004-0000820040409<NA>3폐업2폐업20221017<NA><NA><NA>02 7662890<NA>110250서울특별시 종로구 재동 **-**서울특별시 종로구 북촌로 **-* (재동)3059홍원재동점2022-10-17 15:15:51U2021-10-30 23:09:00.0<NA>198668.519161452866.61234<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
830000003000000-134-2004-0000920040421<NA>3폐업2폐업20060113<NA><NA><NA>02 7393781<NA>110759서울특별시 종로구 당주동 ***-**번지 동원빌딩***호<NA><NA>주식회사오티시2004-04-21 00:00:00I2018-08-31 23:59:59.0<NA>197484.983911452162.304535영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930000003000000-134-2004-0001020040421<NA>3폐업2폐업20051107<NA><NA><NA>02 7305768<NA>110044서울특별시 종로구 필운동 **번지 외**필지배화여대창업보육센터****호<NA><NA>(주)다존이십일2004-07-14 00:00:00I2018-08-31 23:59:59.0<NA>197002.668256452893.430637영업장판매<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
206730000003000000-134-2024-000182024-03-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-849서울특별시 종로구 평창동 ***-**서울특별시 종로구 평창**길 **, *층 (평창동)3005레안보우애플스토2024-03-19 10:01:07I2023-12-02 22:01:00.0<NA>197066.351155456741.351524<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
206830000003000000-134-2024-000192024-03-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-850서울특별시 종로구 효제동 ***서울특별시 종로구 종로**길 **, 대화빌딩 ***호 (효제동)3126SMAD(스메드)텍스2024-03-25 16:02:23U2023-12-02 22:07:00.0<NA>200278.353783452242.710933<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
206930000003000000-134-2024-000202024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA>02 263283350.00110-809서울특별시 종로구 동숭동 *-** 계우빌딩서울특별시 종로구 대학로**길 **, 계우빌딩 *층 ***호 (동숭동)3086씨케이쇼핑2024-03-27 15:38:17I2023-12-02 22:09:00.0<NA>200284.07971453238.540021<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207030000003000000-134-2024-000212024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA>070 828723250.00110-410서울특별시 종로구 인의동 ***-* 세운스퀘어서울특별시 종로구 창경궁로 ***, 세운스퀘어 별관동 ***호 (인의동)3137에스케이컴퍼니2024-03-27 17:48:55I2023-12-02 22:09:00.0<NA>199670.979885452221.775006<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207130000003000000-134-2024-000222024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-837서울특별시 종로구 창신동 ***-***서울특별시 종로구 창신길 ***-*, *층 (창신동)3089위더스2024-04-01 11:20:29I2023-12-04 00:03:00.0<NA>200751.028899452999.931916<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207230000003000000-134-2024-000232024-04-05<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-844서울특별시 종로구 충신동 ** 힐스테이트 창경궁서울특별시 종로구 율곡로 ***, ***동 ****호 (충신동, 힐스테이트 창경궁)3123유라나2024-04-05 15:39:51I2023-12-04 00:07:00.0<NA>200342.282273452556.296391<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207330000003000000-134-2024-000242024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-841서울특별시 종로구 창신동 ***-** 시즌서울특별시 종로구 지봉로 **, 시즌 *층 D**호 (창신동)3121에스 엔2024-04-08 17:39:03I2023-12-03 23:00:00.0<NA>201273.887782452163.292543<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207430000003000000-134-2024-000252024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-809서울특별시 종로구 동숭동 *-** 계우빌딩서울특별시 종로구 대학로**길 **, 계우빌딩 *층 ***호 (동숭동)3086셀다 코리아2024-04-09 17:15:01I2023-12-03 23:01:00.0<NA>200284.07971453238.540021<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207530000003000000-134-2024-000262024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-825서울특별시 종로구 숭인동 ***-**서울특별시 종로구 난계로**길 **-*, *층 (숭인동)3115시화당스토어2024-04-12 11:48:38I2023-12-03 23:04:00.0<NA>201799.694508452323.456559<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
207630000003000000-134-2024-000272024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00110-833서울특별시 종로구 예지동 ***-** 평화직물서울특별시 종로구 청계천로 ***, 평화직물 ***호 (예지동)3195수정모피2024-04-22 11:02:01I2023-12-03 22:04:00.0<NA>199972.227303451932.287241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>