Overview

Dataset statistics

Number of variables44
Number of observations596
Missing cells6858
Missing cells (%)26.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory219.0 KiB
Average record size in memory376.2 B

Variable types

Categorical18
Text7
DateTime4
Unsupported8
Numeric6
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-18403/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (76.2%)Imbalance
등급구분명 is highly imbalanced (79.2%)Imbalance
급수시설구분명 is highly imbalanced (50.0%)Imbalance
총인원 is highly imbalanced (60.8%)Imbalance
본사종업원수 is highly imbalanced (60.2%)Imbalance
공장사무직종업원수 is highly imbalanced (60.2%)Imbalance
공장판매직종업원수 is highly imbalanced (60.2%)Imbalance
공장생산직종업원수 is highly imbalanced (60.2%)Imbalance
보증액 is highly imbalanced (60.2%)Imbalance
월세액 is highly imbalanced (60.2%)Imbalance
다중이용업소여부 is highly imbalanced (85.7%)Imbalance
인허가취소일자 has 596 (100.0%) missing valuesMissing
폐업일자 has 154 (25.8%) missing valuesMissing
휴업시작일자 has 596 (100.0%) missing valuesMissing
휴업종료일자 has 596 (100.0%) missing valuesMissing
재개업일자 has 596 (100.0%) missing valuesMissing
전화번호 has 363 (60.9%) missing valuesMissing
소재지면적 has 43 (7.2%) missing valuesMissing
도로명주소 has 92 (15.4%) missing valuesMissing
도로명우편번호 has 96 (16.1%) missing valuesMissing
좌표정보(X) has 21 (3.5%) missing valuesMissing
좌표정보(Y) has 21 (3.5%) missing valuesMissing
남성종사자수 has 446 (74.8%) missing valuesMissing
여성종사자수 has 446 (74.8%) missing valuesMissing
건물소유구분명 has 596 (100.0%) missing valuesMissing
다중이용업소여부 has 202 (33.9%) missing valuesMissing
시설총규모 has 202 (33.9%) missing valuesMissing
전통업소지정번호 has 596 (100.0%) missing valuesMissing
전통업소주된음식 has 596 (100.0%) missing valuesMissing
홈페이지 has 596 (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
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
남성종사자수 has 127 (21.3%) zerosZeros
여성종사자수 has 125 (21.0%) zerosZeros
시설총규모 has 38 (6.4%) zerosZeros

Reproduction

Analysis started2024-04-29 19:42:02.816249
Analysis finished2024-04-29 19:42:03.884890
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
3010000
596 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3010000 596
100.0%

Length

2024-04-30T04:42:03.948844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:04.026192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3010000 596
100.0%

관리번호
Text

UNIQUE 

Distinct596
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-04-30T04:42:04.167830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13112
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

Unique596 ?
Unique (%)100.0%

Sample

1st row3010000-121-1970-00001
2nd row3010000-121-1977-00001
3rd row3010000-121-1977-00002
4th row3010000-121-1978-01894
5th row3010000-121-1979-01809
ValueCountFrequency (%)
3010000-121-1970-00001 1
 
0.2%
3010000-121-2020-00008 1
 
0.2%
3010000-121-2020-00017 1
 
0.2%
3010000-121-2020-00011 1
 
0.2%
3010000-121-2020-00012 1
 
0.2%
3010000-121-2020-00013 1
 
0.2%
3010000-121-2020-00014 1
 
0.2%
3010000-121-2020-00015 1
 
0.2%
3010000-121-2020-00016 1
 
0.2%
3010000-121-2020-00018 1
 
0.2%
Other values (586) 586
98.3%
2024-04-30T04:42:04.462548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5583
42.6%
1 2461
18.8%
- 1788
 
13.6%
2 1620
 
12.4%
3 806
 
6.1%
9 179
 
1.4%
4 147
 
1.1%
5 144
 
1.1%
7 133
 
1.0%
8 129
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11324
86.4%
Dash Punctuation 1788
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5583
49.3%
1 2461
21.7%
2 1620
 
14.3%
3 806
 
7.1%
9 179
 
1.6%
4 147
 
1.3%
5 144
 
1.3%
7 133
 
1.2%
8 129
 
1.1%
6 122
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1788
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13112
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5583
42.6%
1 2461
18.8%
- 1788
 
13.6%
2 1620
 
12.4%
3 806
 
6.1%
9 179
 
1.4%
4 147
 
1.1%
5 144
 
1.1%
7 133
 
1.0%
8 129
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5583
42.6%
1 2461
18.8%
- 1788
 
13.6%
2 1620
 
12.4%
3 806
 
6.1%
9 179
 
1.4%
4 147
 
1.1%
5 144
 
1.1%
7 133
 
1.0%
8 129
 
1.0%
Distinct533
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
Minimum1970-03-10 00:00:00
Maximum2024-04-25 00:00:00
2024-04-30T04:42:04.582111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:42:04.693433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
3
442 
1
154 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 442
74.2%
1 154
 
25.8%

Length

2024-04-30T04:42:04.809449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:04.899096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 442
74.2%
1 154
 
25.8%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
폐업
442 
영업/정상
154 

Length

Max length5
Median length2
Mean length2.7751678
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 442
74.2%
영업/정상 154
 
25.8%

Length

2024-04-30T04:42:04.998653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:05.087150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 442
74.2%
영업/정상 154
 
25.8%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2
442 
1
154 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 442
74.2%
1 154
 
25.8%

Length

2024-04-30T04:42:05.174104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:05.254432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 442
74.2%
1 154
 
25.8%
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
폐업
442 
영업
154 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 442
74.2%
영업 154
 
25.8%

Length

2024-04-30T04:42:05.337302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:05.410992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 442
74.2%
영업 154
 
25.8%

폐업일자
Date

MISSING 

Distinct366
Distinct (%)82.8%
Missing154
Missing (%)25.8%
Memory size4.8 KiB
Minimum2005-12-08 00:00:00
Maximum2024-04-18 00:00:00
2024-04-30T04:42:05.504936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:42:05.621525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

전화번호
Text

MISSING 

Distinct219
Distinct (%)94.0%
Missing363
Missing (%)60.9%
Memory size4.8 KiB
2024-04-30T04:42:05.833477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.343348
Min length2

Characters and Unicode

Total characters2410
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

Unique207 ?
Unique (%)88.8%

Sample

1st row02 7710500
2nd row02 3107100
3rd row0202753044
4th row02
5th row02 3924931
ValueCountFrequency (%)
02 110
28.1%
031 5
 
1.3%
051 4
 
1.0%
0220485230 4
 
1.0%
310 3
 
0.8%
5870955 2
 
0.5%
5679108 2
 
0.5%
032 2
 
0.5%
771 2
 
0.5%
070 2
 
0.5%
Other values (244) 256
65.3%
2024-04-30T04:42:06.174331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 461
19.1%
0 427
17.7%
3 230
9.5%
7 213
8.8%
207
8.6%
5 198
8.2%
1 186
7.7%
8 148
 
6.1%
4 131
 
5.4%
6 113
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2203
91.4%
Space Separator 207
 
8.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 461
20.9%
0 427
19.4%
3 230
10.4%
7 213
9.7%
5 198
9.0%
1 186
8.4%
8 148
 
6.7%
4 131
 
5.9%
6 113
 
5.1%
9 96
 
4.4%
Space Separator
ValueCountFrequency (%)
207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2410
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 461
19.1%
0 427
17.7%
3 230
9.5%
7 213
8.8%
207
8.6%
5 198
8.2%
1 186
7.7%
8 148
 
6.1%
4 131
 
5.4%
6 113
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2410
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 461
19.1%
0 427
17.7%
3 230
9.5%
7 213
8.8%
207
8.6%
5 198
8.2%
1 186
7.7%
8 148
 
6.1%
4 131
 
5.4%
6 113
 
4.7%

소재지면적
Text

MISSING 

Distinct348
Distinct (%)62.9%
Missing43
Missing (%)7.2%
Memory size4.8 KiB
2024-04-30T04:42:06.459089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length4.8173599
Min length3

Characters and Unicode

Total characters2664
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

Unique286 ?
Unique (%)51.7%

Sample

1st row134.89
2nd row229.00
3rd row56.13
4th row58.90
5th row61.85
ValueCountFrequency (%)
3.30 27
 
4.9%
9.90 21
 
3.8%
6.00 17
 
3.1%
00 16
 
2.9%
6.60 12
 
2.2%
9.00 10
 
1.8%
16.50 10
 
1.8%
9.91 7
 
1.3%
1.10 7
 
1.3%
8.26 6
 
1.1%
Other values (338) 420
75.9%
2024-04-30T04:42:06.818596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 569
21.4%
. 553
20.8%
1 265
9.9%
3 211
 
7.9%
6 211
 
7.9%
9 185
 
6.9%
2 178
 
6.7%
5 159
 
6.0%
4 131
 
4.9%
8 113
 
4.2%
Other values (2) 89
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2110
79.2%
Other Punctuation 554
 
20.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 569
27.0%
1 265
12.6%
3 211
 
10.0%
6 211
 
10.0%
9 185
 
8.8%
2 178
 
8.4%
5 159
 
7.5%
4 131
 
6.2%
8 113
 
5.4%
7 88
 
4.2%
Other Punctuation
ValueCountFrequency (%)
. 553
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2664
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 569
21.4%
. 553
20.8%
1 265
9.9%
3 211
 
7.9%
6 211
 
7.9%
9 185
 
6.9%
2 178
 
6.7%
5 159
 
6.0%
4 131
 
4.9%
8 113
 
4.2%
Other values (2) 89
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 569
21.4%
. 553
20.8%
1 265
9.9%
3 211
 
7.9%
6 211
 
7.9%
9 185
 
6.9%
2 178
 
6.7%
5 159
 
6.0%
4 131
 
4.9%
8 113
 
4.2%
Other values (2) 89
 
3.3%
Distinct146
Distinct (%)24.6%
Missing2
Missing (%)0.3%
Memory size4.8 KiB
2024-04-30T04:42:07.080508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2188552
Min length6

Characters and Unicode

Total characters3694
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

Unique65 ?
Unique (%)10.9%

Sample

1st row100070
2nd row100864
3rd row100032
4th row100013
5th row100859
ValueCountFrequency (%)
100011 128
21.5%
100070 72
 
12.1%
100-011 30
 
5.1%
100-070 23
 
3.9%
100-747 14
 
2.4%
100747 14
 
2.4%
100850 11
 
1.9%
100859 10
 
1.7%
100162 9
 
1.5%
100845 9
 
1.5%
Other values (136) 274
46.1%
2024-04-30T04:42:07.465982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1684
45.6%
1 1055
28.6%
8 194
 
5.3%
7 186
 
5.0%
- 130
 
3.5%
4 122
 
3.3%
5 80
 
2.2%
2 72
 
1.9%
3 59
 
1.6%
9 56
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3564
96.5%
Dash Punctuation 130
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1684
47.3%
1 1055
29.6%
8 194
 
5.4%
7 186
 
5.2%
4 122
 
3.4%
5 80
 
2.2%
2 72
 
2.0%
3 59
 
1.7%
9 56
 
1.6%
6 56
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3694
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1684
45.6%
1 1055
28.6%
8 194
 
5.3%
7 186
 
5.0%
- 130
 
3.5%
4 122
 
3.3%
5 80
 
2.2%
2 72
 
1.9%
3 59
 
1.6%
9 56
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3694
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1684
45.6%
1 1055
28.6%
8 194
 
5.3%
7 186
 
5.0%
- 130
 
3.5%
4 122
 
3.3%
5 80
 
2.2%
2 72
 
1.9%
3 59
 
1.6%
9 56
 
1.5%
Distinct371
Distinct (%)62.5%
Missing2
Missing (%)0.3%
Memory size4.8 KiB
2024-04-30T04:42:07.719620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length25.858586
Min length14

Characters and Unicode

Total characters15360
Distinct characters220
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique332 ?
Unique (%)55.9%

Sample

1st row서울특별시 중구 소공동 87-1번지
2nd row서울특별시 중구 태평로2가 23번지 (지하1층)
3rd row서울특별시 중구 저동2가 75번지 (지상1층)
4th row서울특별시 중구 충무로3가 60-1번지
5th row서울특별시 중구 중림동 398-6번지
ValueCountFrequency (%)
서울특별시 594
19.7%
중구 593
19.7%
충무로1가 186
 
6.2%
지하1층 116
 
3.8%
소공동 96
 
3.2%
52-5 93
 
3.1%
1층 65
 
2.2%
신당동 64
 
2.1%
1 50
 
1.7%
롯데백화점 48
 
1.6%
Other values (537) 1111
36.8%
2024-04-30T04:42:08.210348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2814
18.3%
1 920
 
6.0%
614
 
4.0%
608
 
4.0%
605
 
3.9%
604
 
3.9%
599
 
3.9%
595
 
3.9%
594
 
3.9%
589
 
3.8%
Other values (210) 6818
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9179
59.8%
Space Separator 2814
 
18.3%
Decimal Number 2702
 
17.6%
Dash Punctuation 397
 
2.6%
Open Punctuation 107
 
0.7%
Close Punctuation 107
 
0.7%
Uppercase Letter 27
 
0.2%
Other Punctuation 24
 
0.2%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
614
 
6.7%
608
 
6.6%
605
 
6.6%
604
 
6.6%
599
 
6.5%
595
 
6.5%
594
 
6.5%
589
 
6.4%
375
 
4.1%
327
 
3.6%
Other values (181) 3669
40.0%
Uppercase Letter
ValueCountFrequency (%)
B 7
25.9%
C 4
14.8%
J 3
11.1%
D 3
11.1%
P 2
 
7.4%
G 2
 
7.4%
W 1
 
3.7%
I 1
 
3.7%
L 1
 
3.7%
O 1
 
3.7%
Other values (2) 2
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 920
34.0%
2 491
18.2%
5 453
16.8%
4 168
 
6.2%
3 166
 
6.1%
0 148
 
5.5%
6 111
 
4.1%
7 90
 
3.3%
8 80
 
3.0%
9 75
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 17
70.8%
. 7
29.2%
Space Separator
ValueCountFrequency (%)
2814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 397
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9179
59.8%
Common 6154
40.1%
Latin 27
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
614
 
6.7%
608
 
6.6%
605
 
6.6%
604
 
6.6%
599
 
6.5%
595
 
6.5%
594
 
6.5%
589
 
6.4%
375
 
4.1%
327
 
3.6%
Other values (181) 3669
40.0%
Common
ValueCountFrequency (%)
2814
45.7%
1 920
 
14.9%
2 491
 
8.0%
5 453
 
7.4%
- 397
 
6.5%
4 168
 
2.7%
3 166
 
2.7%
0 148
 
2.4%
6 111
 
1.8%
( 107
 
1.7%
Other values (7) 379
 
6.2%
Latin
ValueCountFrequency (%)
B 7
25.9%
C 4
14.8%
J 3
11.1%
D 3
11.1%
P 2
 
7.4%
G 2
 
7.4%
W 1
 
3.7%
I 1
 
3.7%
L 1
 
3.7%
O 1
 
3.7%
Other values (2) 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9179
59.8%
ASCII 6181
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2814
45.5%
1 920
 
14.9%
2 491
 
7.9%
5 453
 
7.3%
- 397
 
6.4%
4 168
 
2.7%
3 166
 
2.7%
0 148
 
2.4%
6 111
 
1.8%
( 107
 
1.7%
Other values (19) 406
 
6.6%
Hangul
ValueCountFrequency (%)
614
 
6.7%
608
 
6.6%
605
 
6.6%
604
 
6.6%
599
 
6.5%
595
 
6.5%
594
 
6.5%
589
 
6.4%
375
 
4.1%
327
 
3.6%
Other values (181) 3669
40.0%

도로명주소
Text

MISSING 

Distinct312
Distinct (%)61.9%
Missing92
Missing (%)15.4%
Memory size4.8 KiB
2024-04-30T04:42:08.482885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length32.952381
Min length21

Characters and Unicode

Total characters16608
Distinct characters232
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

Unique285 ?
Unique (%)56.5%

Sample

1st row서울특별시 중구 소공로 119 (태평로2가,(지하1층))
2nd row서울특별시 중구 마른내로 17-1 (저동2가,(지상1층))
3rd row서울특별시 중구 퇴계로 173 (충무로3가)
4th row서울특별시 중구 명동길 61 (명동1가)
5th row서울특별시 중구 퇴계로 210 (필동2가)
ValueCountFrequency (%)
서울특별시 504
 
15.3%
중구 503
 
15.3%
지하1층 223
 
6.8%
충무로1가 151
 
4.6%
소공로 128
 
3.9%
63 122
 
3.7%
1층 89
 
2.7%
남대문로 82
 
2.5%
소공동 80
 
2.4%
81 74
 
2.3%
Other values (532) 1330
40.5%
2024-04-30T04:42:08.934778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2786
 
16.8%
1 957
 
5.8%
736
 
4.4%
) 550
 
3.3%
( 550
 
3.3%
, 537
 
3.2%
531
 
3.2%
519
 
3.1%
519
 
3.1%
518
 
3.1%
Other values (222) 8405
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9680
58.3%
Space Separator 2786
 
16.8%
Decimal Number 2395
 
14.4%
Close Punctuation 550
 
3.3%
Open Punctuation 550
 
3.3%
Other Punctuation 544
 
3.3%
Uppercase Letter 54
 
0.3%
Dash Punctuation 46
 
0.3%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
736
 
7.6%
531
 
5.5%
519
 
5.4%
519
 
5.4%
518
 
5.4%
514
 
5.3%
507
 
5.2%
504
 
5.2%
460
 
4.8%
417
 
4.3%
Other values (189) 4455
46.0%
Uppercase Letter
ValueCountFrequency (%)
B 25
46.3%
C 5
 
9.3%
D 5
 
9.3%
P 3
 
5.6%
J 3
 
5.6%
A 2
 
3.7%
M 2
 
3.7%
G 2
 
3.7%
W 1
 
1.9%
Y 1
 
1.9%
Other values (5) 5
 
9.3%
Decimal Number
ValueCountFrequency (%)
1 957
40.0%
2 271
 
11.3%
3 260
 
10.9%
6 216
 
9.0%
0 180
 
7.5%
8 134
 
5.6%
7 125
 
5.2%
4 116
 
4.8%
5 91
 
3.8%
9 45
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 537
98.7%
. 7
 
1.3%
Space Separator
ValueCountFrequency (%)
2786
100.0%
Close Punctuation
ValueCountFrequency (%)
) 550
100.0%
Open Punctuation
ValueCountFrequency (%)
( 550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9680
58.3%
Common 6873
41.4%
Latin 55
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
736
 
7.6%
531
 
5.5%
519
 
5.4%
519
 
5.4%
518
 
5.4%
514
 
5.3%
507
 
5.2%
504
 
5.2%
460
 
4.8%
417
 
4.3%
Other values (189) 4455
46.0%
Common
ValueCountFrequency (%)
2786
40.5%
1 957
 
13.9%
) 550
 
8.0%
( 550
 
8.0%
, 537
 
7.8%
2 271
 
3.9%
3 260
 
3.8%
6 216
 
3.1%
0 180
 
2.6%
8 134
 
1.9%
Other values (7) 432
 
6.3%
Latin
ValueCountFrequency (%)
B 25
45.5%
C 5
 
9.1%
D 5
 
9.1%
P 3
 
5.5%
J 3
 
5.5%
A 2
 
3.6%
M 2
 
3.6%
G 2
 
3.6%
W 1
 
1.8%
Y 1
 
1.8%
Other values (6) 6
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9680
58.3%
ASCII 6928
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2786
40.2%
1 957
 
13.8%
) 550
 
7.9%
( 550
 
7.9%
, 537
 
7.8%
2 271
 
3.9%
3 260
 
3.8%
6 216
 
3.1%
0 180
 
2.6%
8 134
 
1.9%
Other values (23) 487
 
7.0%
Hangul
ValueCountFrequency (%)
736
 
7.6%
531
 
5.5%
519
 
5.4%
519
 
5.4%
518
 
5.4%
514
 
5.3%
507
 
5.2%
504
 
5.2%
460
 
4.8%
417
 
4.3%
Other values (189) 4455
46.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct95
Distinct (%)19.0%
Missing96
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean4546.55
Minimum4320
Maximum4637
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:09.065277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4320
5-th percentile4511.95
Q14530
median4533
Q34563
95-th percentile4618.05
Maximum4637
Range317
Interquartile range (IQR)33

Descriptive statistics

Standard deviation33.552153
Coefficient of variation (CV)0.0073796952
Kurtosis4.4003099
Mean4546.55
Median Absolute Deviation (MAD)3
Skewness0.57257135
Sum2273275
Variance1125.747
MonotonicityNot monotonic
2024-04-30T04:42:09.206189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4530 157
26.3%
4533 80
13.4%
4563 12
 
2.0%
4509 12
 
2.0%
4534 8
 
1.3%
4561 7
 
1.2%
4515 7
 
1.2%
4637 7
 
1.2%
4572 6
 
1.0%
4526 6
 
1.0%
Other values (85) 198
33.2%
(Missing) 96
16.1%
ValueCountFrequency (%)
4320 1
 
0.2%
4500 1
 
0.2%
4501 1
 
0.2%
4502 2
 
0.3%
4504 1
 
0.2%
4505 1
 
0.2%
4507 1
 
0.2%
4508 2
 
0.3%
4509 12
2.0%
4510 2
 
0.3%
ValueCountFrequency (%)
4637 7
1.2%
4635 1
 
0.2%
4634 1
 
0.2%
4633 1
 
0.2%
4632 1
 
0.2%
4631 5
0.8%
4627 2
 
0.3%
4626 2
 
0.3%
4625 2
 
0.3%
4623 1
 
0.2%
Distinct488
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
2024-04-30T04:42:09.498931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length26
Mean length8.0587248
Min length2

Characters and Unicode

Total characters4803
Distinct characters443
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique442 ?
Unique (%)74.2%

Sample

1st row(주)신세계조선호텔 베끼아에누보델리
2nd row에릭케제르(EK)
3rd row파리바게뜨
4th row뚜레쥬르충무로극동점
5th row케익나라몽블랑
ValueCountFrequency (%)
연희양과점 26
 
3.0%
파리바게뜨 22
 
2.5%
달콤한위로 20
 
2.3%
본점 13
 
1.5%
던킨도너츠 10
 
1.1%
뚜레쥬르 9
 
1.0%
리암스 8
 
0.9%
명동점 8
 
0.9%
베이커리 6
 
0.7%
디피오리 6
 
0.7%
Other values (591) 743
85.3%
2024-04-30T04:42:10.128229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
275
 
5.7%
203
 
4.2%
172
 
3.6%
114
 
2.4%
101
 
2.1%
( 92
 
1.9%
) 92
 
1.9%
72
 
1.5%
58
 
1.2%
58
 
1.2%
Other values (433) 3566
74.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3903
81.3%
Space Separator 275
 
5.7%
Lowercase Letter 257
 
5.4%
Uppercase Letter 132
 
2.7%
Open Punctuation 92
 
1.9%
Close Punctuation 92
 
1.9%
Decimal Number 41
 
0.9%
Other Punctuation 10
 
0.2%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
203
 
5.2%
172
 
4.4%
114
 
2.9%
101
 
2.6%
72
 
1.8%
58
 
1.5%
58
 
1.5%
53
 
1.4%
53
 
1.4%
52
 
1.3%
Other values (371) 2967
76.0%
Uppercase Letter
ValueCountFrequency (%)
D 13
 
9.8%
L 11
 
8.3%
B 11
 
8.3%
E 10
 
7.6%
A 10
 
7.6%
T 9
 
6.8%
K 7
 
5.3%
N 7
 
5.3%
S 6
 
4.5%
G 6
 
4.5%
Other values (14) 42
31.8%
Lowercase Letter
ValueCountFrequency (%)
e 34
13.2%
i 25
9.7%
a 23
 
8.9%
o 21
 
8.2%
r 19
 
7.4%
n 18
 
7.0%
l 17
 
6.6%
t 15
 
5.8%
u 14
 
5.4%
s 13
 
5.1%
Other values (12) 58
22.6%
Decimal Number
ValueCountFrequency (%)
1 9
22.0%
2 8
19.5%
3 8
19.5%
5 5
12.2%
9 4
9.8%
4 3
 
7.3%
6 2
 
4.9%
0 2
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
' 2
 
20.0%
& 2
 
20.0%
, 1
 
10.0%
Space Separator
ValueCountFrequency (%)
275
100.0%
Open Punctuation
ValueCountFrequency (%)
( 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3903
81.3%
Common 511
 
10.6%
Latin 389
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
203
 
5.2%
172
 
4.4%
114
 
2.9%
101
 
2.6%
72
 
1.8%
58
 
1.5%
58
 
1.5%
53
 
1.4%
53
 
1.4%
52
 
1.3%
Other values (371) 2967
76.0%
Latin
ValueCountFrequency (%)
e 34
 
8.7%
i 25
 
6.4%
a 23
 
5.9%
o 21
 
5.4%
r 19
 
4.9%
n 18
 
4.6%
l 17
 
4.4%
t 15
 
3.9%
u 14
 
3.6%
D 13
 
3.3%
Other values (36) 190
48.8%
Common
ValueCountFrequency (%)
275
53.8%
( 92
 
18.0%
) 92
 
18.0%
1 9
 
1.8%
2 8
 
1.6%
3 8
 
1.6%
5 5
 
1.0%
. 5
 
1.0%
9 4
 
0.8%
4 3
 
0.6%
Other values (6) 10
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3902
81.2%
ASCII 900
 
18.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
275
30.6%
( 92
 
10.2%
) 92
 
10.2%
e 34
 
3.8%
i 25
 
2.8%
a 23
 
2.6%
o 21
 
2.3%
r 19
 
2.1%
n 18
 
2.0%
l 17
 
1.9%
Other values (52) 284
31.6%
Hangul
ValueCountFrequency (%)
203
 
5.2%
172
 
4.4%
114
 
2.9%
101
 
2.6%
72
 
1.8%
58
 
1.5%
58
 
1.5%
53
 
1.4%
53
 
1.4%
52
 
1.3%
Other values (370) 2966
76.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Distinct543
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
Minimum2000-04-07 00:00:00
Maximum2024-04-25 15:23:51
2024-04-30T04:42:10.250353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:42:10.369808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
U
299 
I
297 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 299
50.2%
I 297
49.8%

Length

2024-04-30T04:42:10.489801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:10.563119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 299
50.2%
i 297
49.8%
Distinct259
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:03:00
2024-04-30T04:42:10.655670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:42:10.818760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
제과점영업
596 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 596
100.0%

Length

2024-04-30T04:42:11.026271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:11.182621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 596
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct239
Distinct (%)41.6%
Missing21
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean198832.57
Minimum196655.58
Maximum201958.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:11.362256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196655.58
5-th percentile197230.21
Q1198253.9
median198263.91
Q3199375.19
95-th percentile201444.03
Maximum201958.2
Range5302.6228
Interquartile range (IQR)1121.2983

Descriptive statistics

Standard deviation1260.3105
Coefficient of variation (CV)0.0063385518
Kurtosis-0.099876022
Mean198832.57
Median Absolute Deviation (MAD)168.1132
Skewness1.0168584
Sum1.1432873 × 108
Variance1588382.7
MonotonicityNot monotonic
2024-04-30T04:42:11.695544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198263.90839194 125
21.0%
198259.65357739 90
 
15.1%
198253.896034899 46
 
7.7%
200613.510297669 11
 
1.8%
197230.206089772 8
 
1.3%
201823.908977364 7
 
1.2%
197612.995083649 5
 
0.8%
197620.676444642 5
 
0.8%
200219.373968049 4
 
0.7%
198921.241301241 3
 
0.5%
Other values (229) 271
45.5%
(Missing) 21
 
3.5%
ValueCountFrequency (%)
196655.581895878 1
 
0.2%
196691.269917831 1
 
0.2%
196728.729522546 1
 
0.2%
196746.506418769 1
 
0.2%
196864.942838297 3
0.5%
196873.878042516 1
 
0.2%
196948.933328771 1
 
0.2%
197036.394106154 1
 
0.2%
197047.239390501 1
 
0.2%
197063.020822371 2
0.3%
ValueCountFrequency (%)
201958.204672457 1
 
0.2%
201866.039519433 2
 
0.3%
201859.57751126 1
 
0.2%
201823.908977364 7
1.2%
201792.385974356 1
 
0.2%
201697.627637864 1
 
0.2%
201693.294849784 1
 
0.2%
201686.07376784 1
 
0.2%
201678.367260135 1
 
0.2%
201676.280853428 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct239
Distinct (%)41.6%
Missing21
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean451096.31
Minimum449638.82
Maximum452076.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:11.911315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum449638.82
5-th percentile450339.4
Q1450905.28
median450960.76
Q3451392.2
95-th percentile451791.52
Maximum452076.82
Range2437.9944
Interquartile range (IQR)486.91375

Descriptive statistics

Standard deviation428.21373
Coefficient of variation (CV)0.0009492734
Kurtosis0.90786699
Mean451096.31
Median Absolute Deviation (MAD)325.2506
Skewness-0.50726034
Sum2.5938038 × 108
Variance183367
MonotonicityNot monotonic
2024-04-30T04:42:12.081593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450960.762964932 125
21.0%
451392.198218657 90
 
15.1%
450905.28446798 46
 
7.7%
451817.515366883 11
 
1.8%
450446.684395506 8
 
1.3%
452076.818664092 7
 
1.2%
450539.857693464 5
 
0.8%
450361.506112161 5
 
0.8%
451288.387900531 4
 
0.7%
451495.985361171 3
 
0.5%
Other values (229) 271
45.5%
(Missing) 21
 
3.5%
ValueCountFrequency (%)
449638.824308081 3
0.5%
449670.613249189 1
 
0.2%
449687.143213423 2
0.3%
449777.515840267 1
 
0.2%
449991.726117085 3
0.5%
450010.190882608 1
 
0.2%
450014.537949042 1
 
0.2%
450049.376670602 2
0.3%
450093.361161044 1
 
0.2%
450126.414301168 1
 
0.2%
ValueCountFrequency (%)
452076.818664092 7
1.2%
452009.399759421 1
 
0.2%
451995.163058 3
 
0.5%
451862.189542378 1
 
0.2%
451847.338754039 1
 
0.2%
451837.481623546 1
 
0.2%
451836.458256618 1
 
0.2%
451817.515366883 11
1.8%
451808.098341971 1
 
0.2%
451793.816975812 2
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
제과점영업
394 
<NA>
202 

Length

Max length5
Median length5
Mean length4.6610738
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 394
66.1%
<NA> 202
33.9%

Length

2024-04-30T04:42:12.221234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:12.359204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 394
66.1%
na 202
33.9%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)4.0%
Missing446
Missing (%)74.8%
Infinite0
Infinite (%)0.0%
Mean0.26
Minimum0
Maximum5
Zeros127
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:12.466552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.73667127
Coefficient of variation (CV)2.833351
Kurtosis16.522593
Mean0.26
Median Absolute Deviation (MAD)0
Skewness3.7311821
Sum39
Variance0.54268456
MonotonicityNot monotonic
2024-04-30T04:42:12.570417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 127
 
21.3%
1 13
 
2.2%
2 7
 
1.2%
4 1
 
0.2%
3 1
 
0.2%
5 1
 
0.2%
(Missing) 446
74.8%
ValueCountFrequency (%)
0 127
21.3%
1 13
 
2.2%
2 7
 
1.2%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 1
 
0.2%
3 1
 
0.2%
2 7
 
1.2%
1 13
 
2.2%
0 127
21.3%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)4.7%
Missing446
Missing (%)74.8%
Infinite0
Infinite (%)0.0%
Mean0.46
Minimum0
Maximum10
Zeros125
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:12.676934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2618831
Coefficient of variation (CV)2.7432242
Kurtosis23.81291
Mean0.46
Median Absolute Deviation (MAD)0
Skewness4.1739016
Sum69
Variance1.592349
MonotonicityNot monotonic
2024-04-30T04:42:12.768948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 125
 
21.0%
2 13
 
2.2%
3 7
 
1.2%
1 2
 
0.3%
4 1
 
0.2%
10 1
 
0.2%
6 1
 
0.2%
(Missing) 446
74.8%
ValueCountFrequency (%)
0 125
21.0%
1 2
 
0.3%
2 13
 
2.2%
3 7
 
1.2%
4 1
 
0.2%
6 1
 
0.2%
10 1
 
0.2%
ValueCountFrequency (%)
10 1
 
0.2%
6 1
 
0.2%
4 1
 
0.2%
3 7
 
1.2%
2 13
 
2.2%
1 2
 
0.3%
0 125
21.0%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
531 
기타
 
51
주택가주변
 
7
유흥업소밀집지역
 
5
아파트지역
 
1

Length

Max length8
Median length4
Mean length3.8825503
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 531
89.1%
기타 51
 
8.6%
주택가주변 7
 
1.2%
유흥업소밀집지역 5
 
0.8%
아파트지역 1
 
0.2%
학교정화(상대) 1
 
0.2%

Length

2024-04-30T04:42:12.866357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:12.961024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 531
89.1%
기타 51
 
8.6%
주택가주변 7
 
1.2%
유흥업소밀집지역 5
 
0.8%
아파트지역 1
 
0.2%
학교정화(상대 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
544 
기타
 
29
우수
 
12
지도
 
6
 
2
Other values (2)
 
3

Length

Max length4
Median length4
Mean length3.8187919
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 544
91.3%
기타 29
 
4.9%
우수 12
 
2.0%
지도 6
 
1.0%
2
 
0.3%
2
 
0.3%
자율 1
 
0.2%

Length

2024-04-30T04:42:13.071054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:13.165265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 544
91.3%
기타 29
 
4.9%
우수 12
 
2.0%
지도 6
 
1.0%
2
 
0.3%
2
 
0.3%
자율 1
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
459 
상수도전용
136 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.25
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 459
77.0%
상수도전용 136
 
22.8%
상수도(음용)지하수(주방용)겸용 1
 
0.2%

Length

2024-04-30T04:42:13.269834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:13.353460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 459
77.0%
상수도전용 136
 
22.8%
상수도(음용)지하수(주방용)겸용 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
550 
0
 
46

Length

Max length4
Median length4
Mean length3.7684564
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> 550
92.3%
0 46
 
7.7%

Length

2024-04-30T04:42:13.457865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:13.543098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 550
92.3%
0 46
 
7.7%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:13.634091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:13.714703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:13.798359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:13.882438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:13.987713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:14.089015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:14.189903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:14.272709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:14.371311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:14.450863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.8 KiB
<NA>
549 
0
 
47

Length

Max length4
Median length4
Mean length3.7634228
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> 549
92.1%
0 47
 
7.9%

Length

2024-04-30T04:42:14.546366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:42:14.640698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 549
92.1%
0 47
 
7.9%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.5%
Missing202
Missing (%)33.9%
Memory size1.3 KiB
False
386 
True
 
8
(Missing)
202 
ValueCountFrequency (%)
False 386
64.8%
True 8
 
1.3%
(Missing) 202
33.9%
2024-04-30T04:42:14.712590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct258
Distinct (%)65.5%
Missing202
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean51.134975
Minimum0
Maximum789.63
Zeros38
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size5.4 KiB
2024-04-30T04:42:14.817760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19.9
median29.12
Q361.7025
95-th percentile178.966
Maximum789.63
Range789.63
Interquartile range (IQR)51.8025

Descriptive statistics

Standard deviation75.695236
Coefficient of variation (CV)1.4803026
Kurtosis33.316589
Mean51.134975
Median Absolute Deviation (MAD)21.155
Skewness4.6410764
Sum20147.18
Variance5729.7688
MonotonicityNot monotonic
2024-04-30T04:42:14.969572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 38
 
6.4%
9.9 16
 
2.7%
16.5 8
 
1.3%
6.6 7
 
1.2%
9.91 6
 
1.0%
9.0 6
 
1.0%
3.3 6
 
1.0%
8.26 6
 
1.0%
33.0 4
 
0.7%
6.61 4
 
0.7%
Other values (248) 293
49.2%
(Missing) 202
33.9%
ValueCountFrequency (%)
0.0 38
6.4%
3.0 2
 
0.3%
3.3 6
 
1.0%
3.91 1
 
0.2%
4.5 1
 
0.2%
4.95 1
 
0.2%
5.3 1
 
0.2%
5.4 1
 
0.2%
5.8 1
 
0.2%
6.0 4
 
0.7%
ValueCountFrequency (%)
789.63 1
0.2%
617.77 1
0.2%
452.6 1
0.2%
417.02 1
0.2%
288.87 1
0.2%
264.0 1
0.2%
241.91 1
0.2%
229.0 2
0.3%
224.63 1
0.2%
222.26 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing596
Missing (%)100.0%
Memory size5.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030100003010000-121-1970-0000119700310<NA>3폐업2폐업20131223<NA><NA><NA>02 7710500134.89100070서울특별시 중구 소공동 87-1번지<NA><NA>(주)신세계조선호텔 베끼아에누보델리2013-04-08 11:15:08I2018-08-31 23:59:59.0제과점영업198172.151119451350.969223제과점영업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N134.89<NA><NA><NA>
130100003010000-121-1977-0000119770331<NA>3폐업2폐업20191028<NA><NA><NA>02 3107100229.00100864서울특별시 중구 태평로2가 23번지 (지하1층)서울특별시 중구 소공로 119 (태평로2가,(지하1층))4525에릭케제르(EK)2019-10-28 16:23:00U2019-10-30 02:40:00.0제과점영업197979.02123451376.783372제과점영업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N229.0<NA><NA><NA>
230100003010000-121-1977-0000219770810<NA>1영업/정상1영업<NA><NA><NA><NA>020275304456.13100032서울특별시 중구 저동2가 75번지 (지상1층)서울특별시 중구 마른내로 17-1 (저동2가,(지상1층))4551파리바게뜨2015-08-12 13:03:45I2018-08-31 23:59:59.0제과점영업199028.604946451410.68942제과점영업12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.13<NA><NA><NA>
330100003010000-121-1978-0189419780805<NA>3폐업2폐업20180703<NA><NA><NA>0258.90100013서울특별시 중구 충무로3가 60-1번지서울특별시 중구 퇴계로 173 (충무로3가)4554뚜레쥬르충무로극동점2018-07-03 11:25:21I2018-08-31 23:59:59.0제과점영업199145.324201451040.432662제과점영업23기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N58.9<NA><NA><NA>
430100003010000-121-1979-0180919790507<NA>3폐업2폐업20060615<NA><NA><NA>02 392493161.85100859서울특별시 중구 중림동 398-6번지<NA><NA>케익나라몽블랑2001-10-08 00:00:00I2018-08-31 23:59:59.0제과점영업196691.269918450743.675359제과점영업12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N61.85<NA><NA><NA>
530100003010000-121-1980-0000119801223<NA>1영업/정상1영업<NA><NA><NA><NA>020776567141.23100810서울특별시 중구 명동2가 105-0번지<NA><NA>도향촌2008-06-20 10:31:58I2018-08-31 23:59:59.0제과점영업198380.641346451105.033104제과점영업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N41.23<NA><NA><NA>
630100003010000-121-1983-0182719830906<NA>3폐업2폐업20060714<NA><NA><NA>020234303050.60100836서울특별시 중구 신당동 471-0번지<NA><NA>앙트르메2001-10-29 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업12기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N50.6<NA><NA><NA>
730100003010000-121-1983-0197319830729<NA>1영업/정상1영업<NA><NA><NA><NA>020756111220.83100021서울특별시 중구 명동1가 6-3번지서울특별시 중구 명동길 61 (명동1가)4538파티스리 에또끌레(Patisserie Etocle)2016-03-17 15:53:57I2018-08-31 23:59:59.0제과점영업198662.073221451337.206273제과점영업13기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N20.83<NA><NA><NA>
830100003010000-121-1984-0000119840824<NA>3폐업2폐업20150123<NA><NA><NA>020267756194.48100272서울특별시 중구 필동2가 15-2번지서울특별시 중구 퇴계로 210 (필동2가)4625비알코리아(주)던킨도너츠충무로역점2009-08-18 16:55:28I2018-08-31 23:59:59.0제과점영업199562.772927451300.183411제과점영업00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N94.48<NA><NA><NA>
930100003010000-121-1986-019081986-07-05<NA>1영업/정상1영업<NA><NA><NA><NA>022234045261.75100-450서울특별시 중구 신당동 368-104 , 105 (2층)서울특별시 중구 다산로 103 (신당동,, 105 (2층))4598화수분 베이커리2023-12-06 11:03:27U2022-11-02 00:08:00.0제과점영업200771.361127450126.414301<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
58630100003010000-121-2024-000072024-03-06<NA>3폐업2폐업2024-03-14<NA><NA><NA><NA>9.90100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지1층 (소공동)4533데포르메2024-03-15 04:15:09U2023-12-02 23:07:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58730100003010000-121-2024-000082024-03-07<NA>3폐업2폐업2024-03-14<NA><NA><NA><NA>0.90100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지하1층 (소공동)4533마들젠2024-03-15 04:15:09U2023-12-02 23:07:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58830100003010000-121-2024-000092024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.30100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지하1층 (소공동)4533콘디토리오븐2024-03-21 16:56:16I2023-12-02 22:03:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58930100003010000-121-2024-000102024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.49100-053서울특별시 중구 회현동3가 1-11 서울N스퀘어서울특별시 중구 퇴계로 110, 서울N스퀘어 1층 103호 (회현동3가)4631서울페이스트리 명동점2024-03-22 15:15:17I2023-12-02 22:04:00.0제과점영업198531.297995450909.106572<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59030100003010000-121-2024-000112024-03-28<NA>1영업/정상1영업<NA><NA><NA><NA>02 378957065.90100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지하1층 (충무로1가)4530오뗄두스2024-03-28 17:36:48I2023-12-02 21:00:00.0제과점영업198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59130100003010000-121-2024-000122024-03-29<NA>3폐업2폐업2024-04-18<NA><NA><NA><NA>10.00100-747서울특별시 중구 충무로1가 52-5 신세계백화점건물서울특별시 중구 소공로 63, 신세계백화점건물 지하1층 (충무로1가)4530리암스2024-04-19 04:15:08U2023-12-03 22:01:00.0제과점영업198263.908392450960.762965<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59230100003010000-121-2024-000132024-04-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.89100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지1층 (소공동)4533마망갸또 신사점2024-04-22 16:04:40I2023-12-03 22:04:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59330100003010000-121-2024-000142024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>71.20100-864서울특별시 중구 태평로2가 69-1서울특별시 중구 세종대로14길 6-2, 1층 (태평로2가)4526푸르파파2024-04-23 13:18:50I2023-12-03 22:05:00.0제과점영업197904.611069451181.559973<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59430100003010000-121-2024-000152024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA>02 790 10137.65100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지하1층 (소공동)4533팥알로2024-04-25 11:43:07I2023-12-03 22:07:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59530100003010000-121-2024-000162024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30100-070서울특별시 중구 소공동 1 롯데백화점 본점서울특별시 중구 남대문로 81, 롯데백화점 본점 지하1층 (소공동)4533만나당2024-04-25 15:23:51I2023-12-03 22:07:00.0제과점영업198259.653577451392.198219<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>