Overview

Dataset statistics

Number of variables44
Number of observations1026
Missing cells10339
Missing cells (%)22.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory377.9 KiB
Average record size in memory377.1 B

Variable types

Categorical20
Text6
DateTime4
Unsupported8
Numeric5
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
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-18423/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 is highly imbalanced (98.9%)Imbalance
남성종사자수 is highly imbalanced (58.7%)Imbalance
여성종사자수 is highly imbalanced (57.7%)Imbalance
영업장주변구분명 is highly imbalanced (73.0%)Imbalance
등급구분명 is highly imbalanced (75.8%)Imbalance
급수시설구분명 is highly imbalanced (51.3%)Imbalance
총인원 is highly imbalanced (66.3%)Imbalance
본사종업원수 is highly imbalanced (66.3%)Imbalance
공장사무직종업원수 is highly imbalanced (66.3%)Imbalance
공장판매직종업원수 is highly imbalanced (66.3%)Imbalance
공장생산직종업원수 is highly imbalanced (66.3%)Imbalance
보증액 is highly imbalanced (66.3%)Imbalance
월세액 is highly imbalanced (66.3%)Imbalance
다중이용업소여부 is highly imbalanced (70.1%)Imbalance
인허가취소일자 has 1026 (100.0%) missing valuesMissing
폐업일자 has 259 (25.2%) missing valuesMissing
휴업시작일자 has 1026 (100.0%) missing valuesMissing
휴업종료일자 has 1026 (100.0%) missing valuesMissing
재개업일자 has 1026 (100.0%) missing valuesMissing
전화번호 has 656 (63.9%) missing valuesMissing
소재지면적 has 64 (6.2%) missing valuesMissing
도로명주소 has 223 (21.7%) missing valuesMissing
도로명우편번호 has 231 (22.5%) missing valuesMissing
좌표정보(X) has 20 (1.9%) missing valuesMissing
좌표정보(Y) has 20 (1.9%) missing valuesMissing
건물소유구분명 has 1026 (100.0%) missing valuesMissing
다중이용업소여부 has 329 (32.1%) missing valuesMissing
시설총규모 has 329 (32.1%) missing valuesMissing
전통업소지정번호 has 1026 (100.0%) missing valuesMissing
전통업소주된음식 has 1026 (100.0%) missing valuesMissing
홈페이지 has 1026 (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
소재지면적 has 58 (5.7%) zerosZeros
시설총규모 has 18 (1.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:29:04.203075
Analysis finished2024-05-11 05:29:05.918403
Duration1.72 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
3210000
1026 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3210000
2nd row3210000
3rd row3210000
4th row3210000
5th row3210000

Common Values

ValueCountFrequency (%)
3210000 1026
100.0%

Length

2024-05-11T14:29:06.005263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:06.139400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3210000 1026
100.0%

관리번호
Text

UNIQUE 

Distinct1026
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T14:29:06.425180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters22572
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

Unique1026 ?
Unique (%)100.0%

Sample

1st row3210000-121-1974-01915
2nd row3210000-121-1977-01983
3rd row3210000-121-1979-01899
4th row3210000-121-1980-01965
5th row3210000-121-1981-01839
ValueCountFrequency (%)
3210000-121-1974-01915 1
 
0.1%
3210000-121-2021-00015 1
 
0.1%
3210000-121-2019-00031 1
 
0.1%
3210000-121-2019-00015 1
 
0.1%
3210000-121-2019-00002 1
 
0.1%
3210000-121-2019-00003 1
 
0.1%
3210000-121-2019-00004 1
 
0.1%
3210000-121-2019-00005 1
 
0.1%
3210000-121-2019-00006 1
 
0.1%
3210000-121-2019-00007 1
 
0.1%
Other values (1016) 1016
99.0%
2024-05-11T14:29:06.899557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8466
37.5%
1 4110
18.2%
2 3752
16.6%
- 3078
 
13.6%
3 1460
 
6.5%
9 406
 
1.8%
4 317
 
1.4%
5 258
 
1.1%
8 246
 
1.1%
7 241
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19494
86.4%
Dash Punctuation 3078
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8466
43.4%
1 4110
21.1%
2 3752
19.2%
3 1460
 
7.5%
9 406
 
2.1%
4 317
 
1.6%
5 258
 
1.3%
8 246
 
1.3%
7 241
 
1.2%
6 238
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3078
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22572
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8466
37.5%
1 4110
18.2%
2 3752
16.6%
- 3078
 
13.6%
3 1460
 
6.5%
9 406
 
1.8%
4 317
 
1.4%
5 258
 
1.1%
8 246
 
1.1%
7 241
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22572
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8466
37.5%
1 4110
18.2%
2 3752
16.6%
- 3078
 
13.6%
3 1460
 
6.5%
9 406
 
1.8%
4 317
 
1.4%
5 258
 
1.1%
8 246
 
1.1%
7 241
 
1.1%

인허가일자
Date

Distinct914
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1974-09-07 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T14:29:07.142676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:29:07.368202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
3
767 
1
259 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 767
74.8%
1 259
 
25.2%

Length

2024-05-11T14:29:07.577141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:07.727190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 767
74.8%
1 259
 
25.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
767 
영업/정상
259 

Length

Max length5
Median length2
Mean length2.7573099
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 767
74.8%
영업/정상 259
 
25.2%

Length

2024-05-11T14:29:07.907000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:08.080354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 767
74.8%
영업/정상 259
 
25.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2
767 
1
259 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 767
74.8%
1 259
 
25.2%

Length

2024-05-11T14:29:08.274444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:08.429345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 767
74.8%
1 259
 
25.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
폐업
767 
영업
259 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 767
74.8%
영업 259
 
25.2%

Length

2024-05-11T14:29:08.594188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:08.764986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 767
74.8%
영업 259
 
25.2%

폐업일자
Date

MISSING 

Distinct611
Distinct (%)79.7%
Missing259
Missing (%)25.2%
Memory size8.1 KiB
Minimum2005-10-04 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T14:29:08.924261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:29:09.146974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

전화번호
Text

MISSING 

Distinct358
Distinct (%)96.8%
Missing656
Missing (%)63.9%
Memory size8.1 KiB
2024-05-11T14:29:09.623082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.559459
Min length2

Characters and Unicode

Total characters3907
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

Unique346 ?
Unique (%)93.5%

Sample

1st row0205993647
2nd row02 5911118
3rd row02 5831184
4th row0231410215
5th row0205911802
ValueCountFrequency (%)
02 226
32.2%
070 12
 
1.7%
031 11
 
1.6%
525 6
 
0.9%
523 5
 
0.7%
532 5
 
0.7%
533 4
 
0.6%
535 3
 
0.4%
594 3
 
0.4%
598 3
 
0.4%
Other values (402) 423
60.3%
2024-05-11T14:29:10.256604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 669
17.1%
2 620
15.9%
448
11.5%
5 434
11.1%
3 345
8.8%
4 259
 
6.6%
1 255
 
6.5%
7 250
 
6.4%
8 234
 
6.0%
9 208
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3459
88.5%
Space Separator 448
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 669
19.3%
2 620
17.9%
5 434
12.5%
3 345
10.0%
4 259
 
7.5%
1 255
 
7.4%
7 250
 
7.2%
8 234
 
6.8%
9 208
 
6.0%
6 185
 
5.3%
Space Separator
ValueCountFrequency (%)
448
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3907
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 669
17.1%
2 620
15.9%
448
11.5%
5 434
11.1%
3 345
8.8%
4 259
 
6.6%
1 255
 
6.5%
7 250
 
6.4%
8 234
 
6.0%
9 208
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3907
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 669
17.1%
2 620
15.9%
448
11.5%
5 434
11.1%
3 345
8.8%
4 259
 
6.6%
1 255
 
6.5%
7 250
 
6.4%
8 234
 
6.0%
9 208
 
5.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct588
Distinct (%)61.1%
Missing64
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean52.270821
Minimum0
Maximum771.56
Zeros58
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T14:29:10.487895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110.585
median31.555
Q364.375
95-th percentile167.9765
Maximum771.56
Range771.56
Interquartile range (IQR)53.79

Descriptive statistics

Standard deviation68.193972
Coefficient of variation (CV)1.3046279
Kurtosis20.98519
Mean52.270821
Median Absolute Deviation (MAD)23.33
Skewness3.5672602
Sum50284.53
Variance4650.4178
MonotonicityNot monotonic
2024-05-11T14:29:11.064296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 58
 
5.7%
6.6 31
 
3.0%
3.3 23
 
2.2%
9.9 15
 
1.5%
16.5 13
 
1.3%
6.0 12
 
1.2%
13.2 11
 
1.1%
33.0 10
 
1.0%
6.61 10
 
1.0%
10.0 10
 
1.0%
Other values (578) 769
75.0%
(Missing) 64
 
6.2%
ValueCountFrequency (%)
0.0 58
5.7%
1.0 1
 
0.1%
1.4 1
 
0.1%
1.98 1
 
0.1%
2.0 2
 
0.2%
2.7 1
 
0.1%
2.9 2
 
0.2%
3.0 4
 
0.4%
3.3 23
 
2.2%
3.33 1
 
0.1%
ValueCountFrequency (%)
771.56 1
0.1%
555.64 1
0.1%
436.18 1
0.1%
426.22 1
0.1%
395.0 1
0.1%
363.0 1
0.1%
361.2 1
0.1%
355.0 1
0.1%
350.41 1
0.1%
343.55 1
0.1%

소재지우편번호
Text

Distinct181
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T14:29:11.498397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.214425
Min length6

Characters and Unicode

Total characters6376
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

Unique57 ?
Unique (%)5.6%

Sample

1st row137040
2nd row137800
3rd row137845
4th row137837
5th row137-907
ValueCountFrequency (%)
137713 229
22.3%
137-713 60
 
5.8%
137-960 43
 
4.2%
137040 41
 
4.0%
137908 24
 
2.3%
137893 18
 
1.8%
137856 15
 
1.5%
137882 14
 
1.4%
137806 14
 
1.4%
137960 13
 
1.3%
Other values (171) 555
54.1%
2024-05-11T14:29:12.078959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 1476
23.1%
1 1427
22.4%
3 1424
22.3%
8 646
10.1%
0 392
 
6.1%
9 270
 
4.2%
- 220
 
3.5%
6 179
 
2.8%
4 130
 
2.0%
5 128
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6156
96.5%
Dash Punctuation 220
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 1476
24.0%
1 1427
23.2%
3 1424
23.1%
8 646
10.5%
0 392
 
6.4%
9 270
 
4.4%
6 179
 
2.9%
4 130
 
2.1%
5 128
 
2.1%
2 84
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 1476
23.1%
1 1427
22.4%
3 1424
22.3%
8 646
10.1%
0 392
 
6.1%
9 270
 
4.2%
- 220
 
3.5%
6 179
 
2.8%
4 130
 
2.0%
5 128
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 1476
23.1%
1 1427
22.4%
3 1424
22.3%
8 646
10.1%
0 392
 
6.1%
9 270
 
4.2%
- 220
 
3.5%
6 179
 
2.8%
4 130
 
2.0%
5 128
 
2.0%

지번주소
Text

Distinct783
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T14:29:12.445376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length50
Mean length30.495127
Min length18

Characters and Unicode

Total characters31288
Distinct characters319
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

Unique729 ?
Unique (%)71.1%

Sample

1st row서울특별시 서초구 반포동 885번지 (1층)
2nd row서울특별시 서초구 반포동 2-8번지
3rd row서울특별시 서초구 방배동 951-31번지 (1층)
4th row서울특별시 서초구 방배동 852-16번지
5th row서울특별시 서초구 잠원동 57 (116호)
ValueCountFrequency (%)
서울특별시 1026
17.1%
서초구 1026
17.1%
반포동 459
 
7.6%
1층 270
 
4.5%
지하1층 262
 
4.4%
서초동 235
 
3.9%
19-3 196
 
3.3%
신세계백화점 186
 
3.1%
방배동 152
 
2.5%
19-3번지 133
 
2.2%
Other values (1130) 2057
34.3%
2024-05-11T14:29:13.032879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5612
17.9%
서 2335
 
7.5%
1 2090
 
6.7%
초 1293
 
4.1%
시 1117
 
3.6%
동 1076
 
3.4%
울 1043
 
3.3%
구 1032
 
3.3%
별 1027
 
3.3%
특 1027
 
3.3%
Other values (309) 13636
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18526
59.2%
Decimal Number 5800
 
18.5%
Space Separator 5612
 
17.9%
Dash Punctuation 964
 
3.1%
Uppercase Letter 148
 
0.5%
Other Punctuation 94
 
0.3%
Close Punctuation 61
 
0.2%
Open Punctuation 61
 
0.2%
Lowercase Letter 14
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 2335
 
12.6%
초 1293
 
7.0%
시 1117
 
6.0%
동 1076
 
5.8%
울 1043
 
5.6%
구 1032
 
5.6%
별 1027
 
5.5%
특 1027
 
5.5%
지 926
 
5.0%
층 669
 
3.6%
Other values (264) 6981
37.7%
Uppercase Letter
ValueCountFrequency (%)
B 41
27.7%
A 19
12.8%
T 15
 
10.1%
C 10
 
6.8%
L 7
 
4.7%
P 6
 
4.1%
J 6
 
4.1%
E 6
 
4.1%
F 5
 
3.4%
G 5
 
3.4%
Other values (10) 28
18.9%
Decimal Number
ValueCountFrequency (%)
1 2090
36.0%
3 773
 
13.3%
9 538
 
9.3%
2 519
 
8.9%
0 517
 
8.9%
5 307
 
5.3%
4 302
 
5.2%
7 271
 
4.7%
6 261
 
4.5%
8 222
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
f 4
28.6%
i 3
21.4%
e 3
21.4%
v 3
21.4%
p 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 92
97.9%
: 1
 
1.1%
. 1
 
1.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
5612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 964
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18526
59.2%
Common 12596
40.3%
Latin 166
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 2335
 
12.6%
초 1293
 
7.0%
시 1117
 
6.0%
동 1076
 
5.8%
울 1043
 
5.6%
구 1032
 
5.6%
별 1027
 
5.5%
특 1027
 
5.5%
지 926
 
5.0%
층 669
 
3.6%
Other values (264) 6981
37.7%
Latin
ValueCountFrequency (%)
B 41
24.7%
A 19
11.4%
T 15
 
9.0%
C 10
 
6.0%
L 7
 
4.2%
P 6
 
3.6%
J 6
 
3.6%
E 6
 
3.6%
F 5
 
3.0%
G 5
 
3.0%
Other values (17) 46
27.7%
Common
ValueCountFrequency (%)
5612
44.6%
1 2090
 
16.6%
- 964
 
7.7%
3 773
 
6.1%
9 538
 
4.3%
2 519
 
4.1%
0 517
 
4.1%
5 307
 
2.4%
4 302
 
2.4%
7 271
 
2.2%
Other values (8) 703
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18526
59.2%
ASCII 12758
40.8%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5612
44.0%
1 2090
 
16.4%
- 964
 
7.6%
3 773
 
6.1%
9 538
 
4.2%
2 519
 
4.1%
0 517
 
4.1%
5 307
 
2.4%
4 302
 
2.4%
7 271
 
2.1%
Other values (33) 865
 
6.8%
Hangul
ValueCountFrequency (%)
서 2335
 
12.6%
초 1293
 
7.0%
시 1117
 
6.0%
동 1076
 
5.8%
울 1043
 
5.6%
구 1032
 
5.6%
별 1027
 
5.5%
특 1027
 
5.5%
지 926
 
5.0%
층 669
 
3.6%
Other values (264) 6981
37.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅰ 1
 
25.0%

도로명주소
Text

MISSING 

Distinct582
Distinct (%)72.5%
Missing223
Missing (%)21.7%
Memory size8.1 KiB
2024-05-11T14:29:13.571908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length53
Mean length37.145704
Min length21

Characters and Unicode

Total characters29828
Distinct characters313
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

Unique539 ?
Unique (%)67.1%

Sample

1st row서울특별시 서초구 신반포로 27-6 (반포동)
2nd row서울특별시 서초구 잠원로8길 25 (잠원동)
3rd row서울특별시 서초구 신반포로15길 29, 상가동 158호 (반포동,반포종합)
4th row서울특별시 서초구 신반포로 194 (반포동)
5th row서울특별시 서초구 효령로 15, 1층 (방배동, 지상)
ValueCountFrequency (%)
서울특별시 803
 
13.9%
서초구 803
 
13.9%
반포동 344
 
5.9%
신반포로 316
 
5.5%
176 285
 
4.9%
지하1층 284
 
4.9%
1층 265
 
4.6%
신세계백화점 199
 
3.4%
서초동 165
 
2.9%
강남점 156
 
2.7%
Other values (858) 2168
37.5%
2024-05-11T14:29:14.209282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4991
 
16.7%
서 1941
 
6.5%
1 1571
 
5.3%
초 1107
 
3.7%
, 1053
 
3.5%
동 865
 
2.9%
시 841
 
2.8%
) 820
 
2.7%
( 820
 
2.7%
울 815
 
2.7%
Other values (303) 15004
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17758
59.5%
Space Separator 4991
 
16.7%
Decimal Number 4150
 
13.9%
Other Punctuation 1054
 
3.5%
Close Punctuation 820
 
2.7%
Open Punctuation 820
 
2.7%
Uppercase Letter 128
 
0.4%
Dash Punctuation 85
 
0.3%
Lowercase Letter 16
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1941
 
10.9%
초 1107
 
6.2%
동 865
 
4.9%
시 841
 
4.7%
울 815
 
4.6%
로 811
 
4.6%
구 810
 
4.6%
특 803
 
4.5%
별 803
 
4.5%
포 734
 
4.1%
Other values (259) 8228
46.3%
Uppercase Letter
ValueCountFrequency (%)
B 42
32.8%
A 18
14.1%
T 11
 
8.6%
P 8
 
6.2%
C 6
 
4.7%
F 5
 
3.9%
G 5
 
3.9%
L 5
 
3.9%
S 4
 
3.1%
R 4
 
3.1%
Other values (10) 20
15.6%
Decimal Number
ValueCountFrequency (%)
1 1571
37.9%
2 471
 
11.3%
6 426
 
10.3%
7 424
 
10.2%
0 329
 
7.9%
3 272
 
6.6%
4 197
 
4.7%
5 184
 
4.4%
8 142
 
3.4%
9 134
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
f 5
31.2%
e 3
18.8%
v 3
18.8%
i 3
18.8%
p 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 1053
99.9%
. 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%
Space Separator
ValueCountFrequency (%)
4991
100.0%
Close Punctuation
ValueCountFrequency (%)
) 820
100.0%
Open Punctuation
ValueCountFrequency (%)
( 820
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17758
59.5%
Common 11924
40.0%
Latin 146
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1941
 
10.9%
초 1107
 
6.2%
동 865
 
4.9%
시 841
 
4.7%
울 815
 
4.6%
로 811
 
4.6%
구 810
 
4.6%
특 803
 
4.5%
별 803
 
4.5%
포 734
 
4.1%
Other values (259) 8228
46.3%
Latin
ValueCountFrequency (%)
B 42
28.8%
A 18
12.3%
T 11
 
7.5%
P 8
 
5.5%
C 6
 
4.1%
F 5
 
3.4%
G 5
 
3.4%
L 5
 
3.4%
f 5
 
3.4%
S 4
 
2.7%
Other values (17) 37
25.3%
Common
ValueCountFrequency (%)
4991
41.9%
1 1571
 
13.2%
, 1053
 
8.8%
) 820
 
6.9%
( 820
 
6.9%
2 471
 
4.0%
6 426
 
3.6%
7 424
 
3.6%
0 329
 
2.8%
3 272
 
2.3%
Other values (7) 747
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17758
59.5%
ASCII 12068
40.5%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4991
41.4%
1 1571
 
13.0%
, 1053
 
8.7%
) 820
 
6.8%
( 820
 
6.8%
2 471
 
3.9%
6 426
 
3.5%
7 424
 
3.5%
0 329
 
2.7%
3 272
 
2.3%
Other values (32) 891
 
7.4%
Hangul
ValueCountFrequency (%)
서 1941
 
10.9%
초 1107
 
6.2%
동 865
 
4.9%
시 841
 
4.7%
울 815
 
4.6%
로 811
 
4.6%
구 810
 
4.6%
특 803
 
4.5%
별 803
 
4.5%
포 734
 
4.1%
Other values (259) 8228
46.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
50.0%
Ⅰ 1
50.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct199
Distinct (%)25.0%
Missing231
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean6607.9711
Minimum6500
Maximum6802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T14:29:14.385593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6500
5-th percentile6525.7
Q16546
median6564
Q36664
95-th percentile6781
Maximum6802
Range302
Interquartile range (IQR)118

Descriptive statistics

Standard deviation83.497073
Coefficient of variation (CV)0.012635811
Kurtosis-0.42685397
Mean6607.9711
Median Absolute Deviation (MAD)25
Skewness0.94756557
Sum5253337
Variance6971.7611
MonotonicityNot monotonic
2024-05-11T14:29:14.567478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6546 284
27.7%
6545 21
 
2.0%
6797 13
 
1.3%
6511 12
 
1.2%
6634 10
 
1.0%
6576 9
 
0.9%
6611 8
 
0.8%
6577 7
 
0.7%
6735 7
 
0.7%
6586 7
 
0.7%
Other values (189) 417
40.6%
(Missing) 231
22.5%
ValueCountFrequency (%)
6500 1
 
0.1%
6501 1
 
0.1%
6502 3
 
0.3%
6503 2
 
0.2%
6506 2
 
0.2%
6509 1
 
0.1%
6510 3
 
0.3%
6511 12
1.2%
6512 2
 
0.2%
6515 3
 
0.3%
ValueCountFrequency (%)
6802 2
 
0.2%
6800 6
0.6%
6797 13
1.3%
6795 1
 
0.1%
6793 1
 
0.1%
6788 1
 
0.1%
6787 4
 
0.4%
6786 2
 
0.2%
6785 3
 
0.3%
6783 1
 
0.1%

사업장명
Text

Distinct859
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-05-11T14:29:14.934015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length8.3528265
Min length1

Characters and Unicode

Total characters8570
Distinct characters555
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique780 ?
Unique (%)76.0%

Sample

1st row독일제과
2nd row아미드팡과자점
3rd row쁘띠뺑
4th row던킨도넛츠
5th row브레댄코(bread&co. DAILY-NEW)
ValueCountFrequency (%)
파리바게뜨 37
 
2.3%
강남점 26
 
1.6%
던킨도너츠 22
 
1.4%
강남 21
 
1.3%
뚜레쥬르 20
 
1.2%
베이커리 20
 
1.2%
파리바게트 15
 
0.9%
서초점 15
 
0.9%
신세계백화점 15
 
0.9%
노티드 14
 
0.9%
Other values (1035) 1413
87.3%
2024-05-11T14:29:15.544771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
593
 
6.9%
점 315
 
3.7%
리 291
 
3.4%
이 237
 
2.8%
스 185
 
2.2%
( 175
 
2.0%
) 175
 
2.0%
레 137
 
1.6%
파 115
 
1.3%
베 114
 
1.3%
Other values (545) 6233
72.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6620
77.2%
Space Separator 593
 
6.9%
Lowercase Letter 593
 
6.9%
Uppercase Letter 337
 
3.9%
Open Punctuation 175
 
2.0%
Close Punctuation 175
 
2.0%
Other Punctuation 42
 
0.5%
Decimal Number 31
 
0.4%
Dash Punctuation 2
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 315
 
4.8%
리 291
 
4.4%
이 237
 
3.6%
스 185
 
2.8%
레 137
 
2.1%
파 115
 
1.7%
베 114
 
1.7%
남 104
 
1.6%
강 100
 
1.5%
드 95
 
1.4%
Other values (474) 4927
74.4%
Lowercase Letter
ValueCountFrequency (%)
e 84
14.2%
a 63
10.6%
o 56
 
9.4%
r 46
 
7.8%
t 37
 
6.2%
n 37
 
6.2%
i 37
 
6.2%
s 36
 
6.1%
l 31
 
5.2%
m 26
 
4.4%
Other values (15) 140
23.6%
Uppercase Letter
ValueCountFrequency (%)
E 33
 
9.8%
B 29
 
8.6%
S 25
 
7.4%
A 24
 
7.1%
O 22
 
6.5%
R 19
 
5.6%
C 18
 
5.3%
T 18
 
5.3%
M 17
 
5.0%
P 16
 
4.7%
Other values (14) 116
34.4%
Decimal Number
ValueCountFrequency (%)
2 17
54.8%
1 5
 
16.1%
0 2
 
6.5%
9 2
 
6.5%
5 1
 
3.2%
4 1
 
3.2%
3 1
 
3.2%
6 1
 
3.2%
7 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
. 11
26.2%
& 10
23.8%
' 8
19.0%
? 7
16.7%
, 4
 
9.5%
! 1
 
2.4%
/ 1
 
2.4%
Space Separator
ValueCountFrequency (%)
593
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6620
77.2%
Common 1020
 
11.9%
Latin 930
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 315
 
4.8%
리 291
 
4.4%
이 237
 
3.6%
스 185
 
2.8%
레 137
 
2.1%
파 115
 
1.7%
베 114
 
1.7%
남 104
 
1.6%
강 100
 
1.5%
드 95
 
1.4%
Other values (474) 4927
74.4%
Latin
ValueCountFrequency (%)
e 84
 
9.0%
a 63
 
6.8%
o 56
 
6.0%
r 46
 
4.9%
t 37
 
4.0%
n 37
 
4.0%
i 37
 
4.0%
s 36
 
3.9%
E 33
 
3.5%
l 31
 
3.3%
Other values (39) 470
50.5%
Common
ValueCountFrequency (%)
593
58.1%
( 175
 
17.2%
) 175
 
17.2%
2 17
 
1.7%
. 11
 
1.1%
& 10
 
1.0%
' 8
 
0.8%
? 7
 
0.7%
1 5
 
0.5%
, 4
 
0.4%
Other values (12) 15
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6620
77.2%
ASCII 1950
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
593
30.4%
( 175
 
9.0%
) 175
 
9.0%
e 84
 
4.3%
a 63
 
3.2%
o 56
 
2.9%
r 46
 
2.4%
t 37
 
1.9%
n 37
 
1.9%
i 37
 
1.9%
Other values (61) 647
33.2%
Hangul
ValueCountFrequency (%)
점 315
 
4.8%
리 291
 
4.4%
이 237
 
3.6%
스 185
 
2.8%
레 137
 
2.1%
파 115
 
1.7%
베 114
 
1.7%
남 104
 
1.6%
강 100
 
1.5%
드 95
 
1.4%
Other values (474) 4927
74.4%

최종수정일자
Date

Distinct950
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum1999-04-03 00:00:00
Maximum2024-05-07 17:18:19
2024-05-11T14:29:15.738487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:29:15.924614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
I
549 
U
476 
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 rowU

Common Values

ValueCountFrequency (%)
I 549
53.5%
U 476
46.4%
D 1
 
0.1%

Length

2024-05-11T14:29:16.159050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:16.332331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 549
53.5%
u 476
46.4%
d 1
 
0.1%

데이터갱신일자
Date

Distinct386
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:29:16.457432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:29:16.608038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
제과점영업
1025 
푸드트럭
 
1

Length

Max length5
Median length5
Mean length4.9990253
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 1025
99.9%
푸드트럭 1
 
0.1%

Length

2024-05-11T14:29:16.761395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:16.888705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 1025
99.9%
푸드트럭 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct468
Distinct (%)46.5%
Missing20
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean200800.5
Minimum198341.21
Maximum207505.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T14:29:17.014951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum198341.21
5-th percentile198703.58
Q1200250.45
median200250.45
Q3201507.9
95-th percentile203665.44
Maximum207505.87
Range9164.6571
Interquartile range (IQR)1257.452

Descriptive statistics

Standard deviation1378.8465
Coefficient of variation (CV)0.0068667482
Kurtosis0.82762234
Mean200800.5
Median Absolute Deviation (MAD)703.25321
Skewness0.83219554
Sum2.020053 × 108
Variance1901217.6
MonotonicityNot monotonic
2024-05-11T14:29:17.165876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200250.447804795 328
32.0%
200576.608647619 20
 
1.9%
203811.366422118 16
 
1.6%
200554.74395758 12
 
1.2%
201386.338220173 9
 
0.9%
200514.002958761 6
 
0.6%
203392.793460583 6
 
0.6%
201310.167766645 6
 
0.6%
202882.878990174 5
 
0.5%
201071.474356912 5
 
0.5%
Other values (458) 593
57.8%
(Missing) 20
 
1.9%
ValueCountFrequency (%)
198341.208478761 1
0.1%
198341.255698142 1
0.1%
198345.279900118 1
0.1%
198359.032400861 2
0.2%
198367.956597525 1
0.1%
198392.031081002 1
0.1%
198394.433265008 2
0.2%
198397.235721331 1
0.1%
198405.322905974 2
0.2%
198413.327404748 1
0.1%
ValueCountFrequency (%)
207505.865571 1
 
0.1%
205525.422778498 3
0.3%
205235.018649725 1
 
0.1%
205221.03374911 1
 
0.1%
205203.899329664 1
 
0.1%
204783.612470826 1
 
0.1%
204418.836684211 1
 
0.1%
204157.558320607 1
 
0.1%
204057.795297117 2
0.2%
204052.450645256 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct468
Distinct (%)46.5%
Missing20
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean443663.41
Minimum438520.18
Maximum446331.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T14:29:17.298676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438520.18
5-th percentile440676.38
Q1442735.71
median444279.1
Q3444683.22
95-th percentile445241.9
Maximum446331.38
Range7811.198
Interquartile range (IQR)1947.5092

Descriptive statistics

Standard deviation1420.7192
Coefficient of variation (CV)0.0032022456
Kurtosis0.41400546
Mean443663.41
Median Absolute Deviation (MAD)621.08471
Skewness-1.0040075
Sum4.4632539 × 108
Variance2018443
MonotonicityNot monotonic
2024-05-11T14:29:17.442543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
444683.220506107 328
32.0%
445241.8984183 20
 
1.9%
440070.727589935 16
 
1.6%
444811.364826199 12
 
1.2%
443689.075119969 9
 
0.9%
444644.771176041 6
 
0.6%
440676.379919661 6
 
0.6%
442438.500304691 6
 
0.6%
442509.972957846 5
 
0.5%
444356.613248306 5
 
0.5%
Other values (458) 593
57.8%
(Missing) 20
 
1.9%
ValueCountFrequency (%)
438520.182013694 1
 
0.1%
439029.959102177 1
 
0.1%
439208.962102822 3
0.3%
439363.863225029 1
 
0.1%
439390.862880938 1
 
0.1%
439407.27399616 1
 
0.1%
439730.929547293 1
 
0.1%
439958.443578701 1
 
0.1%
439984.847528537 2
0.2%
440039.132834615 2
0.2%
ValueCountFrequency (%)
446331.380046658 1
 
0.1%
446268.294338007 1
 
0.1%
446247.719636035 1
 
0.1%
446179.309516814 3
0.3%
445992.459343379 2
0.2%
445948.552865248 1
 
0.1%
445946.899831444 1
 
0.1%
445925.192925207 1
 
0.1%
445892.414984064 1
 
0.1%
445858.186112938 1
 
0.1%

위생업태명
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
제과점영업
697 
<NA>
329 

Length

Max length5
Median length5
Mean length4.6793372
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 697
67.9%
<NA> 329
32.1%

Length

2024-05-11T14:29:17.615677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:17.766213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 697
67.9%
na 329
32.1%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
730 
0
262 
1
 
15
2
 
14
3
 
3

Length

Max length4
Median length4
Mean length3.1345029
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row4
3rd row1
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 730
71.2%
0 262
 
25.5%
1 15
 
1.5%
2 14
 
1.4%
3 3
 
0.3%
4 2
 
0.2%

Length

2024-05-11T14:29:17.922393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:18.072983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 730
71.2%
0 262
 
25.5%
1 15
 
1.5%
2 14
 
1.4%
3 3
 
0.3%
4 2
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
730 
0
255 
2
 
23
1
 
13
3
 
4

Length

Max length4
Median length4
Mean length3.1345029
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row2
2nd row0
3rd row2
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 730
71.2%
0 255
 
24.9%
2 23
 
2.2%
1 13
 
1.3%
3 4
 
0.4%
4 1
 
0.1%

Length

2024-05-11T14:29:18.231951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:18.381858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 730
71.2%
0 255
 
24.9%
2 23
 
2.2%
1 13
 
1.3%
3 4
 
0.4%
4 1
 
0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
924 
기타
 
55
아파트지역
 
24
주택가주변
 
19
유흥업소밀집지역
 
4

Length

Max length8
Median length4
Mean length3.9502924
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 924
90.1%
기타 55
 
5.4%
아파트지역 24
 
2.3%
주택가주변 19
 
1.9%
유흥업소밀집지역 4
 
0.4%

Length

2024-05-11T14:29:18.563192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:18.694451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 924
90.1%
기타 55
 
5.4%
아파트지역 24
 
2.3%
주택가주변 19
 
1.9%
유흥업소밀집지역 4
 
0.4%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
924 
기타
 
60
지도
 
22
자율
 
15
갑
 
3

Length

Max length4
Median length4
Mean length3.7962963
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 924
90.1%
기타 60
 
5.8%
지도 22
 
2.1%
자율 15
 
1.5%
갑 3
 
0.3%
을 2
 
0.2%

Length

2024-05-11T14:29:18.862704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:18.980998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 924
90.1%
기타 60
 
5.8%
지도 22
 
2.1%
자율 15
 
1.5%
갑 3
 
0.3%
을 2
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
799 
상수도전용
226 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.2329435
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 799
77.9%
상수도전용 226
 
22.0%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

Length

2024-05-11T14:29:19.119033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:19.232019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 799
77.9%
상수도전용 226
 
22.0%
상수도(음용)지하수(주방용)겸용 1
 
0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:19.359042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:19.471027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:19.583512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:19.691053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:19.832376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:19.996238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:20.138081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:20.269359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:20.414631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:20.537723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:20.667623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:21.158731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
<NA>
962 
0
 
64

Length

Max length4
Median length4
Mean length3.8128655
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> 962
93.8%
0 64
 
6.2%

Length

2024-05-11T14:29:21.366365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:29:21.524658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 962
93.8%
0 64
 
6.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.3%
Missing329
Missing (%)32.1%
Memory size2.1 KiB
False
660 
True
 
37
(Missing)
329 
ValueCountFrequency (%)
False 660
64.3%
True 37
 
3.6%
(Missing) 329
32.1%
2024-05-11T14:29:21.624807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct459
Distinct (%)65.9%
Missing329
Missing (%)32.1%
Infinite0
Infinite (%)0.0%
Mean52.014419
Minimum0
Maximum771.56
Zeros18
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-05-11T14:29:21.770078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q112
median32.5
Q360
95-th percentile162.812
Maximum771.56
Range771.56
Interquartile range (IQR)48

Descriptive statistics

Standard deviation68.470785
Coefficient of variation (CV)1.3163809
Kurtosis26.03637
Mean52.014419
Median Absolute Deviation (MAD)22.6
Skewness4.0000838
Sum36254.05
Variance4688.2485
MonotonicityNot monotonic
2024-05-11T14:29:21.951498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.6 26
 
2.5%
3.3 18
 
1.8%
0.0 18
 
1.8%
9.9 12
 
1.2%
6.0 11
 
1.1%
6.61 10
 
1.0%
13.2 10
 
1.0%
16.5 10
 
1.0%
33.0 8
 
0.8%
26.4 7
 
0.7%
Other values (449) 567
55.3%
(Missing) 329
32.1%
ValueCountFrequency (%)
0.0 18
1.8%
1.4 1
 
0.1%
1.98 1
 
0.1%
2.0 2
 
0.2%
2.7 1
 
0.1%
2.9 2
 
0.2%
3.0 4
 
0.4%
3.3 18
1.8%
3.33 1
 
0.1%
3.5 1
 
0.1%
ValueCountFrequency (%)
771.56 1
0.1%
555.64 1
0.1%
426.22 1
0.1%
395.0 1
0.1%
363.0 1
0.1%
355.0 1
0.1%
350.41 1
0.1%
341.66 1
0.1%
330.0 1
0.1%
321.08 1
0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1026
Missing (%)100.0%
Memory size9.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032100003210000-121-1974-0191519740907<NA>1영업/정상1영업<NA><NA><NA><NA>020599364738.11137040서울특별시 서초구 반포동 885번지 (1층)서울특별시 서초구 신반포로 27-6 (반포동)6502독일제과2016-05-18 16:30:36I2018-08-31 23:59:59.0제과점영업198845.040146444439.89559제과점영업22아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N38.11<NA><NA><NA>
132100003210000-121-1977-0198319770813<NA>3폐업2폐업20130124<NA><NA><NA>02 591111853.63137800서울특별시 서초구 반포동 2-8번지<NA><NA>아미드팡과자점2012-01-19 11:52:05I2018-08-31 23:59:59.0제과점영업199448.513022444800.550773제과점영업40아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.63<NA><NA><NA>
232100003210000-121-1979-0189919790920<NA>3폐업2폐업20060905<NA><NA><NA>02 583118451.69137845서울특별시 서초구 방배동 951-31번지 (1층)<NA><NA>쁘띠뺑2004-06-10 00:00:00I2018-08-31 23:59:59.0제과점영업198679.695934442520.445712제과점영업12주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N51.69<NA><NA><NA>
332100003210000-121-1980-0196519800719<NA>3폐업2폐업20091009<NA><NA><NA>023141021543.0137837서울특별시 서초구 방배동 852-16번지<NA><NA>던킨도넛츠2004-02-11 00:00:00I2018-08-31 23:59:59.0제과점영업199268.84242442961.791793제과점영업22주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.0<NA><NA><NA>
432100003210000-121-1981-018391981-12-12<NA>3폐업2폐업2022-12-12<NA><NA><NA>020591180223.8137-907서울특별시 서초구 잠원동 57 (116호)서울특별시 서초구 잠원로8길 25 (잠원동)6518브레댄코(bread&co. DAILY-NEW)2022-12-12 12:12:19U2022-12-04 22:06:00.0제과점영업200958.810529445792.191399<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
532100003210000-121-1981-0184219811212<NA>3폐업2폐업20130117<NA><NA><NA>02 532142527.6137906서울특별시 서초구 잠원동 50-2번지 설악복지 센타동 107호<NA><NA>좋은빵만들기2001-09-29 00:00:00I2018-08-31 23:59:59.0제과점영업201293.260056446179.309517제과점영업22아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N27.6<NA><NA><NA>
632100003210000-121-1981-0187719811203<NA>3폐업2폐업20110614<NA><NA><NA>02 535202842.44137713서울특별시 서초구 반포동 19-4번지 지상1층<NA><NA>쉘브르 베이커리2007-10-30 15:17:19I2018-08-31 23:59:59.0제과점영업200554.743958444811.364826제과점영업13기타지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.44<NA><NA><NA>
732100003210000-121-1981-0199819810731<NA>3폐업2폐업20211201<NA><NA><NA>02 590446837.96137800서울특별시 서초구 반포동 2-8 반포종합 상가동 158호서울특별시 서초구 신반포로15길 29, 상가동 158호 (반포동,반포종합)6503씨엘드프랑스과자점2021-12-06 14:16:47U2021-12-08 02:40:00.0제과점영업199448.513022444800.550773제과점영업22아파트지역지도상수도전용00000<NA>00N37.96<NA><NA><NA>
832100003210000-121-1981-0212219811118<NA>3폐업2폐업20071002<NA><NA><NA>02 533888471.82137040서울특별시 서초구 반포동 444-1번지<NA><NA>파리바게트(반포가든점)2002-06-27 00:00:00I2018-08-31 23:59:59.0제과점영업<NA><NA>제과점영업12아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N71.82<NA><NA><NA>
932100003210000-121-1982-0188219821117<NA>3폐업2폐업20061218<NA><NA><NA>023482557426.99137776서울특별시 서초구 서초동 1315-0번지 진흥아파트상가 105호<NA><NA>뺑아미과자점2004-03-18 00:00:00I2018-08-31 23:59:59.0제과점영업201930.014908443904.461724제과점영업22아파트지역지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.99<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
101632100003210000-121-2024-000402024-04-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>100.39137-840서울특별시 서초구 방배동 877-35 101호서울특별시 서초구 방배로26길 32, 101호 (방배동)6588보나블랑제리2024-04-08 17:37:00I2023-12-03 23:00:00.0제과점영업199455.898766443034.152203<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101732100003210000-121-2024-000412024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 594 3686148.8137-855서울특별시 서초구 서초동 1303-6 102,103호서울특별시 서초구 사평대로58길 6, 102,103호 (서초동)6611쿄 베이커리와 더 인피닛 카페2024-04-09 15:10:05I2023-12-03 23:01:00.0제과점영업202012.421909444597.759429<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101832100003210000-121-2024-000422024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA>10.0137-713서울특별시 서초구 반포동 19-3 신세계백화점 강남점 지하1층 식품관서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 식품관 (반포동)6546리암스2024-04-17 17:32:45I2023-12-03 23:09:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
101932100003210000-121-2024-000432024-04-22<NA>3폐업2폐업2024-04-30<NA><NA><NA><NA><NA>137-960서울특별시 서초구 반포동 19-3 센트럴시티서울특별시 서초구 신반포로 176, 신세계백화점 지하1층 (반포동)6546플디 도산점2024-05-01 04:15:09U2023-12-05 00:03:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102032100003210000-121-2024-000442024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA>31.7137-960서울특별시 서초구 반포동 19-3 센트럴시티서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하 1층 스위트파크 (반포동)6546슬라이폭스2024-04-25 15:38:31I2023-12-03 22:07:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102132100003210000-121-2024-000452024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-713서울특별시 서초구 반포동 19-3 신세계백화점 강남점 지하1층서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 (반포동)6546농업회사법인 흥만소 주식회사2024-05-01 14:52:46I2023-12-05 00:03:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102232100003210000-121-2024-000462024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>67.68137-809서울특별시 서초구 반포동 725-15 1층서울특별시 서초구 사평대로55길 75-1, 1층 (반포동)6540크림브리즈모먼트(Cream Breeze Moment)2024-05-02 15:26:14I2023-12-05 00:04:00.0제과점영업201814.670274444995.876714<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102332100003210000-121-2024-000472024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>9.9137-713서울특별시 서초구 반포동 19-3 지하1층서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 (반포동)6546빵어니스타2024-05-02 16:08:20I2023-12-05 00:04:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102432100003210000-121-2024-000482024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>137-713서울특별시 서초구 반포동 19-3 신세계백화점 강남점 지하1층 스위트파크서울특별시 서초구 신반포로 176, 신세계백화점 강남점 지하1층 스위트파크 (반포동)6546퍼프베이커리2024-05-07 09:26:29I2023-12-05 00:09:00.0제과점영업200250.447805444683.220506<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
102532100003210000-121-2024-000492024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>19.97137-893서울특별시 서초구 양재동 230 하나로마트 양재점 2층서울특별시 서초구 청계산로 10, 하나로마트 양재점 2층 2층 (양재동)6797카페 베즐리(CAFE VEZZLY)2024-05-07 10:03:56I2023-12-05 00:09:00.0제과점영업203811.145834440070.874223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>