Overview

Dataset statistics

Number of variables44
Number of observations660
Missing cells7313
Missing cells (%)25.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory243.1 KiB
Average record size in memory377.2 B

Variable types

Categorical18
Text6
DateTime4
Unsupported8
Numeric7
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18417/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
영업장주변구분명 is highly imbalanced (60.6%)Imbalance
등급구분명 is highly imbalanced (57.3%)Imbalance
총인원 is highly imbalanced (67.0%)Imbalance
본사종업원수 is highly imbalanced (66.4%)Imbalance
공장사무직종업원수 is highly imbalanced (66.4%)Imbalance
공장판매직종업원수 is highly imbalanced (66.4%)Imbalance
공장생산직종업원수 is highly imbalanced (66.4%)Imbalance
보증액 is highly imbalanced (66.4%)Imbalance
월세액 is highly imbalanced (66.4%)Imbalance
다중이용업소여부 is highly imbalanced (93.5%)Imbalance
인허가취소일자 has 660 (100.0%) missing valuesMissing
폐업일자 has 200 (30.3%) missing valuesMissing
휴업시작일자 has 660 (100.0%) missing valuesMissing
휴업종료일자 has 660 (100.0%) missing valuesMissing
재개업일자 has 660 (100.0%) missing valuesMissing
전화번호 has 232 (35.2%) missing valuesMissing
소재지면적 has 20 (3.0%) missing valuesMissing
도로명주소 has 162 (24.5%) missing valuesMissing
도로명우편번호 has 167 (25.3%) missing valuesMissing
좌표정보(X) has 29 (4.4%) missing valuesMissing
좌표정보(Y) has 29 (4.4%) missing valuesMissing
남성종사자수 has 457 (69.2%) missing valuesMissing
여성종사자수 has 453 (68.6%) missing valuesMissing
건물소유구분명 has 660 (100.0%) missing valuesMissing
다중이용업소여부 has 142 (21.5%) missing valuesMissing
시설총규모 has 142 (21.5%) missing valuesMissing
전통업소지정번호 has 660 (100.0%) missing valuesMissing
전통업소주된음식 has 660 (100.0%) missing valuesMissing
홈페이지 has 660 (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 100 (15.2%) zerosZeros
여성종사자수 has 91 (13.8%) zerosZeros
시설총규모 has 17 (2.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:58:42.329164
Analysis finished2024-05-11 06:58:43.342518
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3150000
660 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 660
100.0%

Length

2024-05-11T15:58:43.406679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:43.499178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 660
100.0%

관리번호
Text

UNIQUE 

Distinct660
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:58:43.686002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters14520
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

Unique660 ?
Unique (%)100.0%

Sample

1st row3150000-121-1977-00001
2nd row3150000-121-1979-00001
3rd row3150000-121-1980-00001
4th row3150000-121-1980-00002
5th row3150000-121-1980-00003
ValueCountFrequency (%)
3150000-121-1977-00001 1
 
0.2%
3150000-121-2015-00031 1
 
0.2%
3150000-121-2016-00008 1
 
0.2%
3150000-121-2016-00001 1
 
0.2%
3150000-121-2016-00002 1
 
0.2%
3150000-121-2016-00003 1
 
0.2%
3150000-121-2016-00004 1
 
0.2%
3150000-121-2016-00005 1
 
0.2%
3150000-121-2016-00006 1
 
0.2%
3150000-121-2016-00007 1
 
0.2%
Other values (650) 650
98.5%
2024-05-11T15:58:44.111840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5783
39.8%
1 2757
19.0%
- 1980
 
13.6%
2 1567
 
10.8%
3 827
 
5.7%
5 793
 
5.5%
9 313
 
2.2%
8 153
 
1.1%
4 126
 
0.9%
7 115
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12540
86.4%
Dash Punctuation 1980
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5783
46.1%
1 2757
22.0%
2 1567
 
12.5%
3 827
 
6.6%
5 793
 
6.3%
9 313
 
2.5%
8 153
 
1.2%
4 126
 
1.0%
7 115
 
0.9%
6 106
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1980
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5783
39.8%
1 2757
19.0%
- 1980
 
13.6%
2 1567
 
10.8%
3 827
 
5.7%
5 793
 
5.5%
9 313
 
2.2%
8 153
 
1.1%
4 126
 
0.9%
7 115
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5783
39.8%
1 2757
19.0%
- 1980
 
13.6%
2 1567
 
10.8%
3 827
 
5.7%
5 793
 
5.5%
9 313
 
2.2%
8 153
 
1.1%
4 126
 
0.9%
7 115
 
0.8%

인허가일자
Date

Distinct618
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum1977-07-06 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T15:58:44.305558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:44.472988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
3
460 
1
200 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 460
69.7%
1 200
30.3%

Length

2024-05-11T15:58:44.621181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:44.729104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 460
69.7%
1 200
30.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
460 
영업/정상
200 

Length

Max length5
Median length2
Mean length2.9090909
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 460
69.7%
영업/정상 200
30.3%

Length

2024-05-11T15:58:44.868367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:45.066753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 460
69.7%
영업/정상 200
30.3%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2
460 
1
200 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 460
69.7%
1 200
30.3%

Length

2024-05-11T15:58:45.189535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:45.296771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 460
69.7%
1 200
30.3%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
폐업
460 
영업
200 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 460
69.7%
영업 200
30.3%

Length

2024-05-11T15:58:45.419801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:45.533797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 460
69.7%
영업 200
30.3%

폐업일자
Date

MISSING 

Distinct387
Distinct (%)84.1%
Missing200
Missing (%)30.3%
Memory size5.3 KiB
Minimum1984-12-07 00:00:00
Maximum2024-04-16 00:00:00
2024-05-11T15:58:45.678332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:45.874804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

전화번호
Text

MISSING 

Distinct395
Distinct (%)92.3%
Missing232
Missing (%)35.2%
Memory size5.3 KiB
2024-05-11T15:58:46.125682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.004673
Min length2

Characters and Unicode

Total characters4282
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

Unique372 ?
Unique (%)86.9%

Sample

1st row02 6947293
2nd row0226058468
3rd row0236649965
4th row0226044189
5th row0206528669
ValueCountFrequency (%)
02 89
 
17.4%
07071237606 4
 
0.8%
0236634445 3
 
0.6%
0236621500 3
 
0.6%
0226626055 2
 
0.4%
0226679854 2
 
0.4%
0 2
 
0.4%
0236640804 2
 
0.4%
0226669092 2
 
0.4%
0226645259 2
 
0.4%
Other values (388) 401
78.3%
2024-05-11T15:58:46.557108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 861
20.1%
0 845
19.7%
6 721
16.8%
3 290
 
6.8%
5 269
 
6.3%
9 258
 
6.0%
4 249
 
5.8%
8 242
 
5.7%
7 229
 
5.3%
1 209
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4173
97.5%
Space Separator 109
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 861
20.6%
0 845
20.2%
6 721
17.3%
3 290
 
6.9%
5 269
 
6.4%
9 258
 
6.2%
4 249
 
6.0%
8 242
 
5.8%
7 229
 
5.5%
1 209
 
5.0%
Space Separator
ValueCountFrequency (%)
109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4282
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 861
20.1%
0 845
19.7%
6 721
16.8%
3 290
 
6.8%
5 269
 
6.3%
9 258
 
6.0%
4 249
 
5.8%
8 242
 
5.7%
7 229
 
5.3%
1 209
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 861
20.1%
0 845
19.7%
6 721
16.8%
3 290
 
6.8%
5 269
 
6.3%
9 258
 
6.0%
4 249
 
5.8%
8 242
 
5.7%
7 229
 
5.3%
1 209
 
4.9%

소재지면적
Real number (ℝ)

MISSING 

Distinct477
Distinct (%)74.5%
Missing20
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean45.375672
Minimum0
Maximum337.05
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:46.756612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.995
Q125.175
median35.8
Q353.37
95-th percentile109.149
Maximum337.05
Range337.05
Interquartile range (IQR)28.195

Descriptive statistics

Standard deviation36.555992
Coefficient of variation (CV)0.80562978
Kurtosis16.037828
Mean45.375672
Median Absolute Deviation (MAD)12.695
Skewness3.1441738
Sum29040.43
Variance1336.3406
MonotonicityNot monotonic
2024-05-11T15:58:46.950894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 21
 
3.2%
20.0 8
 
1.2%
19.8 7
 
1.1%
66.0 6
 
0.9%
3.3 6
 
0.9%
6.6 6
 
0.9%
25.0 5
 
0.8%
40.0 5
 
0.8%
24.0 5
 
0.8%
25.92 4
 
0.6%
Other values (467) 567
85.9%
(Missing) 20
 
3.0%
ValueCountFrequency (%)
0.0 1
 
0.2%
1.86 1
 
0.2%
1.96 1
 
0.2%
2.0 1
 
0.2%
3.0 1
 
0.2%
3.3 6
0.9%
4.0 1
 
0.2%
4.95 1
 
0.2%
5.0 3
0.5%
6.0 3
0.5%
ValueCountFrequency (%)
337.05 1
0.2%
309.47 1
0.2%
295.93 1
0.2%
235.2 1
0.2%
215.1 1
0.2%
202.66 1
0.2%
174.32 1
0.2%
173.3 1
0.2%
165.68 1
0.2%
159.5 1
0.2%

소재지우편번호
Text

Distinct145
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:58:47.394321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1242424
Min length6

Characters and Unicode

Total characters4042
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

Unique54 ?
Unique (%)8.2%

Sample

1st row157879
2nd row157915
3rd row157862
4th row157873
5th row157837
ValueCountFrequency (%)
157210 59
 
8.9%
157930 41
 
6.2%
157220 19
 
2.9%
157-210 19
 
2.9%
157846 18
 
2.7%
157840 18
 
2.7%
157280 17
 
2.6%
157835 15
 
2.3%
157847 14
 
2.1%
157836 13
 
2.0%
Other values (135) 427
64.7%
2024-05-11T15:58:48.029172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 854
21.1%
5 752
18.6%
7 752
18.6%
8 459
11.4%
0 337
 
8.3%
2 246
 
6.1%
9 207
 
5.1%
3 143
 
3.5%
4 113
 
2.8%
6 97
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3960
98.0%
Dash Punctuation 82
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 854
21.6%
5 752
19.0%
7 752
19.0%
8 459
11.6%
0 337
 
8.5%
2 246
 
6.2%
9 207
 
5.2%
3 143
 
3.6%
4 113
 
2.9%
6 97
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4042
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 854
21.1%
5 752
18.6%
7 752
18.6%
8 459
11.4%
0 337
 
8.3%
2 246
 
6.1%
9 207
 
5.1%
3 143
 
3.5%
4 113
 
2.8%
6 97
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4042
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 854
21.1%
5 752
18.6%
7 752
18.6%
8 459
11.4%
0 337
 
8.3%
2 246
 
6.1%
9 207
 
5.1%
3 143
 
3.5%
4 113
 
2.8%
6 97
 
2.4%

지번주소
Text

Distinct637
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:58:48.384394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length49
Mean length31.869697
Min length18

Characters and Unicode

Total characters21034
Distinct characters268
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique616 ?
Unique (%)93.3%

Sample

1st row서울특별시 강서구 화곡동 340-47번지
2nd row서울특별시 강서구 화곡동 976-1 (지상 1층)
3rd row서울특별시 강서구 염창동 264-10번지
4th row서울특별시 강서구 화곡동 1059-50번지
5th row서울특별시 강서구 등촌동 567-17번지
ValueCountFrequency (%)
서울특별시 660
16.5%
강서구 660
16.5%
1층 317
 
7.9%
지상 238
 
5.9%
화곡동 197
 
4.9%
방화동 111
 
2.8%
등촌동 103
 
2.6%
마곡동 78
 
1.9%
내발산동 61
 
1.5%
가양동 39
 
1.0%
Other values (903) 1536
38.4%
2024-05-11T15:58:48.964671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3749
 
17.8%
서 1343
 
6.4%
1 1247
 
5.9%
지 810
 
3.9%
동 742
 
3.5%
강 685
 
3.3%
시 680
 
3.2%
구 666
 
3.2%
울 666
 
3.2%
특 660
 
3.1%
Other values (258) 9786
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11584
55.1%
Decimal Number 4269
 
20.3%
Space Separator 3749
 
17.8%
Dash Punctuation 627
 
3.0%
Open Punctuation 335
 
1.6%
Close Punctuation 334
 
1.6%
Uppercase Letter 67
 
0.3%
Other Punctuation 44
 
0.2%
Math Symbol 19
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1343
 
11.6%
지 810
 
7.0%
동 742
 
6.4%
강 685
 
5.9%
시 680
 
5.9%
구 666
 
5.7%
울 666
 
5.7%
특 660
 
5.7%
별 660
 
5.7%
층 436
 
3.8%
Other values (221) 4236
36.6%
Uppercase Letter
ValueCountFrequency (%)
A 10
14.9%
I 8
11.9%
B 7
10.4%
C 6
9.0%
N 6
9.0%
W 6
9.0%
T 5
7.5%
M 3
 
4.5%
O 3
 
4.5%
G 2
 
3.0%
Other values (8) 11
16.4%
Decimal Number
ValueCountFrequency (%)
1 1247
29.2%
0 501
11.7%
2 421
 
9.9%
6 344
 
8.1%
7 331
 
7.8%
4 330
 
7.7%
3 293
 
6.9%
8 278
 
6.5%
9 268
 
6.3%
5 256
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 42
95.5%
. 2
 
4.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅰ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3749
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 627
100.0%
Open Punctuation
ValueCountFrequency (%)
( 335
100.0%
Close Punctuation
ValueCountFrequency (%)
) 334
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11584
55.1%
Common 9377
44.6%
Latin 73
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1343
 
11.6%
지 810
 
7.0%
동 742
 
6.4%
강 685
 
5.9%
시 680
 
5.9%
구 666
 
5.7%
울 666
 
5.7%
특 660
 
5.7%
별 660
 
5.7%
층 436
 
3.8%
Other values (221) 4236
36.6%
Latin
ValueCountFrequency (%)
A 10
13.7%
I 8
11.0%
B 7
9.6%
C 6
8.2%
N 6
8.2%
W 6
8.2%
Ⅱ 5
 
6.8%
T 5
 
6.8%
M 3
 
4.1%
O 3
 
4.1%
Other values (10) 14
19.2%
Common
ValueCountFrequency (%)
3749
40.0%
1 1247
 
13.3%
- 627
 
6.7%
0 501
 
5.3%
2 421
 
4.5%
6 344
 
3.7%
( 335
 
3.6%
) 334
 
3.6%
7 331
 
3.5%
4 330
 
3.5%
Other values (7) 1158
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11584
55.1%
ASCII 9444
44.9%
Number Forms 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3749
39.7%
1 1247
 
13.2%
- 627
 
6.6%
0 501
 
5.3%
2 421
 
4.5%
6 344
 
3.6%
( 335
 
3.5%
) 334
 
3.5%
7 331
 
3.5%
4 330
 
3.5%
Other values (25) 1225
 
13.0%
Hangul
ValueCountFrequency (%)
서 1343
 
11.6%
지 810
 
7.0%
동 742
 
6.4%
강 685
 
5.9%
시 680
 
5.9%
구 666
 
5.7%
울 666
 
5.7%
특 660
 
5.7%
별 660
 
5.7%
층 436
 
3.8%
Other values (221) 4236
36.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅰ 1
 
16.7%

도로명주소
Text

MISSING 

Distinct478
Distinct (%)96.0%
Missing162
Missing (%)24.5%
Memory size5.3 KiB
2024-05-11T15:58:49.349765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length49
Mean length37.827309
Min length22

Characters and Unicode

Total characters18838
Distinct characters281
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique460 ?
Unique (%)92.4%

Sample

1st row서울특별시 강서구 강서로 64 (화곡동)
2nd row서울특별시 강서구 까치산로 119, 1층 (화곡동, 6동)
3rd row서울특별시 강서구 화곡로43가길 29 (화곡동)
4th row서울특별시 강서구 공항대로 24, 1층 (공항동)
5th row서울특별시 강서구 등촌로39길 6, 1층 (등촌동, 2동)
ValueCountFrequency (%)
서울특별시 498
 
13.3%
강서구 498
 
13.3%
1층 345
 
9.2%
화곡동 126
 
3.4%
마곡동 78
 
2.1%
등촌동 74
 
2.0%
방화동 64
 
1.7%
1동 58
 
1.6%
내발산동 43
 
1.2%
공항대로 42
 
1.1%
Other values (754) 1910
51.1%
2024-05-11T15:58:50.007614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3240
 
17.2%
서 1120
 
5.9%
1 1119
 
5.9%
동 768
 
4.1%
, 754
 
4.0%
강 617
 
3.3%
) 536
 
2.8%
( 536
 
2.8%
시 517
 
2.7%
울 504
 
2.7%
Other values (271) 9127
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10496
55.7%
Space Separator 3240
 
17.2%
Decimal Number 3111
 
16.5%
Other Punctuation 755
 
4.0%
Close Punctuation 536
 
2.8%
Open Punctuation 536
 
2.8%
Uppercase Letter 74
 
0.4%
Dash Punctuation 63
 
0.3%
Math Symbol 21
 
0.1%
Letter Number 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1120
 
10.7%
동 768
 
7.3%
강 617
 
5.9%
시 517
 
4.9%
울 504
 
4.8%
구 503
 
4.8%
별 498
 
4.7%
특 498
 
4.7%
로 477
 
4.5%
층 444
 
4.2%
Other values (234) 4550
43.3%
Uppercase Letter
ValueCountFrequency (%)
A 10
13.5%
I 8
10.8%
B 8
10.8%
N 7
9.5%
C 7
9.5%
W 6
8.1%
M 4
 
5.4%
G 4
 
5.4%
F 4
 
5.4%
T 3
 
4.1%
Other values (8) 13
17.6%
Decimal Number
ValueCountFrequency (%)
1 1119
36.0%
2 390
 
12.5%
3 290
 
9.3%
0 270
 
8.7%
5 227
 
7.3%
4 215
 
6.9%
6 197
 
6.3%
8 143
 
4.6%
7 140
 
4.5%
9 120
 
3.9%
Other Punctuation
ValueCountFrequency (%)
, 754
99.9%
. 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅰ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3240
100.0%
Close Punctuation
ValueCountFrequency (%)
) 536
100.0%
Open Punctuation
ValueCountFrequency (%)
( 536
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10496
55.7%
Common 8262
43.9%
Latin 80
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1120
 
10.7%
동 768
 
7.3%
강 617
 
5.9%
시 517
 
4.9%
울 504
 
4.8%
구 503
 
4.8%
별 498
 
4.7%
특 498
 
4.7%
로 477
 
4.5%
층 444
 
4.2%
Other values (234) 4550
43.3%
Latin
ValueCountFrequency (%)
A 10
12.5%
I 8
10.0%
B 8
10.0%
N 7
8.8%
C 7
8.8%
W 6
 
7.5%
Ⅱ 5
 
6.2%
M 4
 
5.0%
G 4
 
5.0%
F 4
 
5.0%
Other values (10) 17
21.2%
Common
ValueCountFrequency (%)
3240
39.2%
1 1119
 
13.5%
, 754
 
9.1%
) 536
 
6.5%
( 536
 
6.5%
2 390
 
4.7%
3 290
 
3.5%
0 270
 
3.3%
5 227
 
2.7%
4 215
 
2.6%
Other values (7) 685
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10496
55.7%
ASCII 8336
44.3%
Number Forms 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3240
38.9%
1 1119
 
13.4%
, 754
 
9.0%
) 536
 
6.4%
( 536
 
6.4%
2 390
 
4.7%
3 290
 
3.5%
0 270
 
3.2%
5 227
 
2.7%
4 215
 
2.6%
Other values (25) 759
 
9.1%
Hangul
ValueCountFrequency (%)
서 1120
 
10.7%
동 768
 
7.3%
강 617
 
5.9%
시 517
 
4.9%
울 504
 
4.8%
구 503
 
4.8%
별 498
 
4.7%
특 498
 
4.7%
로 477
 
4.5%
층 444
 
4.2%
Other values (234) 4550
43.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 5
83.3%
Ⅰ 1
 
16.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct169
Distinct (%)34.3%
Missing167
Missing (%)25.3%
Infinite0
Infinite (%)0.0%
Mean7649.7404
Minimum7505
Maximum7809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:50.190792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7505
5-th percentile7505
Q17574
median7637
Q37738
95-th percentile7803
Maximum7809
Range304
Interquartile range (IQR)164

Descriptive statistics

Standard deviation95.048177
Coefficient of variation (CV)0.01242502
Kurtosis-1.21142
Mean7649.7404
Median Absolute Deviation (MAD)78
Skewness0.16678621
Sum3771322
Variance9034.156
MonotonicityNot monotonic
2024-05-11T15:58:50.375739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7505 28
 
4.2%
7803 16
 
2.4%
7639 15
 
2.3%
7738 12
 
1.8%
7806 11
 
1.7%
7567 11
 
1.7%
7631 10
 
1.5%
7584 10
 
1.5%
7604 10
 
1.5%
7741 10
 
1.5%
Other values (159) 360
54.5%
(Missing) 167
25.3%
ValueCountFrequency (%)
7505 28
4.2%
7506 2
 
0.3%
7509 1
 
0.2%
7510 6
 
0.9%
7511 5
 
0.8%
7516 3
 
0.5%
7517 2
 
0.3%
7523 2
 
0.3%
7524 4
 
0.6%
7525 1
 
0.2%
ValueCountFrequency (%)
7809 1
 
0.2%
7808 2
 
0.3%
7807 2
 
0.3%
7806 11
1.7%
7804 1
 
0.2%
7803 16
2.4%
7802 6
 
0.9%
7801 3
 
0.5%
7798 2
 
0.3%
7792 1
 
0.2%

사업장명
Text

Distinct603
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
2024-05-11T15:58:50.734716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length7.6121212
Min length1

Characters and Unicode

Total characters5024
Distinct characters469
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique569 ?
Unique (%)86.2%

Sample

1st row빵굽는마을
2nd row빵집이야기
3rd row아비앙또
4th row김정식베이커리
5th row행복한 빵 세상
ValueCountFrequency (%)
파리바게뜨 27
 
3.0%
뚜레쥬르 23
 
2.6%
베이커리 19
 
2.1%
던킨도너츠 10
 
1.1%
김포공항점 8
 
0.9%
몽블랑제 8
 
0.9%
크라운베이커리 7
 
0.8%
강서점 7
 
0.8%
가양점 6
 
0.7%
데이앤데이 6
 
0.7%
Other values (674) 770
86.4%
2024-05-11T15:58:51.403954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
 
4.6%
점 202
 
4.0%
리 200
 
4.0%
이 192
 
3.8%
베 114
 
2.3%
커 97
 
1.9%
스 96
 
1.9%
레 95
 
1.9%
빵 91
 
1.8%
) 84
 
1.7%
Other values (459) 3621
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4266
84.9%
Space Separator 232
 
4.6%
Lowercase Letter 165
 
3.3%
Uppercase Letter 110
 
2.2%
Close Punctuation 85
 
1.7%
Open Punctuation 85
 
1.7%
Decimal Number 72
 
1.4%
Other Punctuation 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 202
 
4.7%
리 200
 
4.7%
이 192
 
4.5%
베 114
 
2.7%
커 97
 
2.3%
스 96
 
2.3%
레 95
 
2.2%
빵 91
 
2.1%
바 66
 
1.5%
파 61
 
1.4%
Other values (396) 3052
71.5%
Lowercase Letter
ValueCountFrequency (%)
e 22
13.3%
a 21
12.7%
r 13
 
7.9%
o 12
 
7.3%
n 11
 
6.7%
i 10
 
6.1%
t 7
 
4.2%
s 7
 
4.2%
d 6
 
3.6%
p 6
 
3.6%
Other values (12) 50
30.3%
Uppercase Letter
ValueCountFrequency (%)
E 11
 
10.0%
S 10
 
9.1%
C 9
 
8.2%
B 9
 
8.2%
N 8
 
7.3%
A 8
 
7.3%
O 7
 
6.4%
G 7
 
6.4%
H 6
 
5.5%
T 6
 
5.5%
Other values (11) 29
26.4%
Decimal Number
ValueCountFrequency (%)
2 19
26.4%
1 16
22.2%
5 10
13.9%
0 7
 
9.7%
9 6
 
8.3%
4 5
 
6.9%
3 4
 
5.6%
6 2
 
2.8%
8 2
 
2.8%
7 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
? 3
33.3%
& 3
33.3%
: 1
 
11.1%
, 1
 
11.1%
! 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 84
98.8%
] 1
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 84
98.8%
[ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4262
84.8%
Common 483
 
9.6%
Latin 275
 
5.5%
Han 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 202
 
4.7%
리 200
 
4.7%
이 192
 
4.5%
베 114
 
2.7%
커 97
 
2.3%
스 96
 
2.3%
레 95
 
2.2%
빵 91
 
2.1%
바 66
 
1.5%
파 61
 
1.4%
Other values (392) 3048
71.5%
Latin
ValueCountFrequency (%)
e 22
 
8.0%
a 21
 
7.6%
r 13
 
4.7%
o 12
 
4.4%
E 11
 
4.0%
n 11
 
4.0%
i 10
 
3.6%
S 10
 
3.6%
C 9
 
3.3%
B 9
 
3.3%
Other values (33) 147
53.5%
Common
ValueCountFrequency (%)
232
48.0%
) 84
 
17.4%
( 84
 
17.4%
2 19
 
3.9%
1 16
 
3.3%
5 10
 
2.1%
0 7
 
1.4%
9 6
 
1.2%
4 5
 
1.0%
3 4
 
0.8%
Other values (10) 16
 
3.3%
Han
ValueCountFrequency (%)
味 1
25.0%
美 1
25.0%
安 1
25.0%
寧 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4262
84.8%
ASCII 758
 
15.1%
CJK 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
30.6%
) 84
 
11.1%
( 84
 
11.1%
e 22
 
2.9%
a 21
 
2.8%
2 19
 
2.5%
1 16
 
2.1%
r 13
 
1.7%
o 12
 
1.6%
E 11
 
1.5%
Other values (53) 244
32.2%
Hangul
ValueCountFrequency (%)
점 202
 
4.7%
리 200
 
4.7%
이 192
 
4.5%
베 114
 
2.7%
커 97
 
2.3%
스 96
 
2.3%
레 95
 
2.2%
빵 91
 
2.1%
바 66
 
1.5%
파 61
 
1.4%
Other values (392) 3048
71.5%
CJK
ValueCountFrequency (%)
味 1
25.0%
美 1
25.0%
安 1
25.0%
寧 1
25.0%

최종수정일자
Date

Distinct637
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2000-05-30 00:00:00
Maximum2024-05-03 10:31:52
2024-05-11T15:58:51.596492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:52.118821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
I
396 
U
264 

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 (%)
I 396
60.0%
U 264
40.0%

Length

2024-05-11T15:58:52.279517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:52.414521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 396
60.0%
u 264
40.0%

데이터갱신일자
Date

Distinct232
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T15:58:52.560907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:52.775154image/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 size5.3 KiB
제과점영업
660 

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 660
100.0%

Length

2024-05-11T15:58:52.979500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:53.112259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 660
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct449
Distinct (%)71.2%
Missing29
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean185662.39
Minimum182141.21
Maximum189098.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:53.269747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile182951.03
Q1184567.93
median185813.15
Q3186739.56
95-th percentile188186.79
Maximum189098.81
Range6957.6013
Interquartile range (IQR)2171.6307

Descriptive statistics

Standard deviation1655.5768
Coefficient of variation (CV)0.0089171363
Kurtosis-0.74349152
Mean185662.39
Median Absolute Deviation (MAD)1083.984
Skewness-0.20688526
Sum1.1715297 × 108
Variance2740934.7
MonotonicityNot monotonic
2024-05-11T15:58:53.457698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182524.823835629 21
 
3.2%
187119.948165892 12
 
1.8%
185824.428508883 9
 
1.4%
186687.131804431 9
 
1.4%
187464.403178638 7
 
1.1%
183366.101249557 6
 
0.9%
187761.194273879 6
 
0.9%
183410.412077203 5
 
0.8%
182974.850127567 5
 
0.8%
183402.594183427 4
 
0.6%
Other values (439) 547
82.9%
(Missing) 29
 
4.4%
ValueCountFrequency (%)
182141.205465089 3
 
0.5%
182524.823835629 21
3.2%
182846.62641593 1
 
0.2%
182876.367858149 2
 
0.3%
182908.975451896 1
 
0.2%
182914.770762913 1
 
0.2%
182944.731406147 3
 
0.5%
182957.325956453 1
 
0.2%
182974.850127567 5
 
0.8%
182984.891498757 1
 
0.2%
ValueCountFrequency (%)
189098.806779959 3
0.5%
189003.872396936 1
 
0.2%
188917.095297226 1
 
0.2%
188891.283361072 1
 
0.2%
188883.085593065 1
 
0.2%
188872.058097899 1
 
0.2%
188844.263978802 1
 
0.2%
188818.542553678 1
 
0.2%
188816.672230969 1
 
0.2%
188745.853508441 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct449
Distinct (%)71.2%
Missing29
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean450204.6
Minimum447326.55
Maximum453178.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:53.626899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447326.55
5-th percentile447776.25
Q1449244.81
median450427.7
Q3451268.39
95-th percentile452292.35
Maximum453178.31
Range5851.7571
Interquartile range (IQR)2023.5811

Descriptive statistics

Standard deviation1429.1788
Coefficient of variation (CV)0.0031745096
Kurtosis-0.82090356
Mean450204.6
Median Absolute Deviation (MAD)946.44242
Skewness-0.28282898
Sum2.840791 × 108
Variance2042552.1
MonotonicityNot monotonic
2024-05-11T15:58:53.811047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
451438.25089679 21
 
3.2%
450691.593173724 12
 
1.8%
450866.252126246 9
 
1.4%
451342.773451086 9
 
1.4%
447877.710664426 7
 
1.1%
452817.469477897 6
 
0.9%
450640.214509068 6
 
0.9%
452801.707821111 5
 
0.8%
450419.684560487 5
 
0.8%
452008.728839666 4
 
0.6%
Other values (439) 547
82.9%
(Missing) 29
 
4.4%
ValueCountFrequency (%)
447326.548615694 1
0.2%
447412.204356767 1
0.2%
447458.207510979 1
0.2%
447490.504198119 1
0.2%
447529.951936004 1
0.2%
447570.2391768 1
0.2%
447571.649333861 1
0.2%
447576.805180714 1
0.2%
447592.317631258 1
0.2%
447615.55541547 1
0.2%
ValueCountFrequency (%)
453178.305694113 1
 
0.2%
453050.733807442 2
 
0.3%
452817.469477897 6
0.9%
452801.707821111 5
0.8%
452783.158197133 2
 
0.3%
452726.015586166 1
 
0.2%
452545.112117132 1
 
0.2%
452514.491608298 1
 
0.2%
452449.274183571 1
 
0.2%
452426.754650691 1
 
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
제과점영업
518 
<NA>
142 

Length

Max length5
Median length5
Mean length4.7848485
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 518
78.5%
<NA> 142
 
21.5%

Length

2024-05-11T15:58:53.976267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:54.126212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 518
78.5%
na 142
 
21.5%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)3.0%
Missing457
Missing (%)69.2%
Infinite0
Infinite (%)0.0%
Mean0.8817734
Minimum0
Maximum5
Zeros100
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:54.325774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1326884
Coefficient of variation (CV)1.2845572
Kurtosis1.6091326
Mean0.8817734
Median Absolute Deviation (MAD)1
Skewness1.411469
Sum179
Variance1.282983
MonotonicityNot monotonic
2024-05-11T15:58:54.540389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 100
 
15.2%
1 58
 
8.8%
2 24
 
3.6%
3 13
 
2.0%
4 6
 
0.9%
5 2
 
0.3%
(Missing) 457
69.2%
ValueCountFrequency (%)
0 100
15.2%
1 58
8.8%
2 24
 
3.6%
3 13
 
2.0%
4 6
 
0.9%
5 2
 
0.3%
ValueCountFrequency (%)
5 2
 
0.3%
4 6
 
0.9%
3 13
 
2.0%
2 24
 
3.6%
1 58
8.8%
0 100
15.2%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)3.9%
Missing453
Missing (%)68.6%
Infinite0
Infinite (%)0.0%
Mean0.96135266
Minimum0
Maximum8
Zeros91
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:54.726234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2181691
Coefficient of variation (CV)1.2671408
Kurtosis7.8159414
Mean0.96135266
Median Absolute Deviation (MAD)1
Skewness2.2057673
Sum199
Variance1.483936
MonotonicityNot monotonic
2024-05-11T15:58:54.936381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 91
 
13.8%
1 65
 
9.8%
2 36
 
5.5%
4 6
 
0.9%
3 6
 
0.9%
8 1
 
0.2%
5 1
 
0.2%
7 1
 
0.2%
(Missing) 453
68.6%
ValueCountFrequency (%)
0 91
13.8%
1 65
9.8%
2 36
 
5.5%
3 6
 
0.9%
4 6
 
0.9%
5 1
 
0.2%
7 1
 
0.2%
8 1
 
0.2%
ValueCountFrequency (%)
8 1
 
0.2%
7 1
 
0.2%
5 1
 
0.2%
4 6
 
0.9%
3 6
 
0.9%
2 36
 
5.5%
1 65
9.8%
0 91
13.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
523 
주택가주변
65 
기타
 
37
아파트지역
 
27
유흥업소밀집지역
 
6
Other values (2)
 
2

Length

Max length8
Median length4
Mean length4.0742424
Min length2

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 523
79.2%
주택가주변 65
 
9.8%
기타 37
 
5.6%
아파트지역 27
 
4.1%
유흥업소밀집지역 6
 
0.9%
결혼예식장주변 1
 
0.2%
학교정화(상대) 1
 
0.2%

Length

2024-05-11T15:58:55.155488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:55.375042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 523
79.2%
주택가주변 65
 
9.8%
기타 37
 
5.6%
아파트지역 27
 
4.1%
유흥업소밀집지역 6
 
0.9%
결혼예식장주변 1
 
0.2%
학교정화(상대 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
521 
기타
65 
자율
 
37
갑
 
32
지도
 
3

Length

Max length4
Median length4
Mean length3.5272727
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 521
78.9%
기타 65
 
9.8%
자율 37
 
5.6%
갑 32
 
4.8%
지도 3
 
0.5%
을 2
 
0.3%

Length

2024-05-11T15:58:55.562579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:55.724318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 521
78.9%
기타 65
 
9.8%
자율 37
 
5.6%
갑 32
 
4.8%
지도 3
 
0.5%
을 2
 
0.3%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
상수도전용
394 
<NA>
262 
지하수전용
 
4

Length

Max length5
Median length5
Mean length4.6030303
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 394
59.7%
<NA> 262
39.7%
지하수전용 4
 
0.6%

Length

2024-05-11T15:58:55.889185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:56.040439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 394
59.7%
na 262
39.7%
지하수전용 4
 
0.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
620 
0
 
40

Length

Max length4
Median length4
Mean length3.8181818
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> 620
93.9%
0 40
 
6.1%

Length

2024-05-11T15:58:56.231486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:56.409932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 620
93.9%
0 40
 
6.1%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:56.608227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:56.807418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:56.981555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:57.200865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:57.378048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:57.538059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:57.691942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:57.839369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:58.017447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:58.183913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.3 KiB
<NA>
619 
0
 
41

Length

Max length4
Median length4
Mean length3.8136364
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> 619
93.8%
0 41
 
6.2%

Length

2024-05-11T15:58:58.372094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:58.547144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 619
93.8%
0 41
 
6.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing142
Missing (%)21.5%
Memory size1.4 KiB
False
514 
True
 
4
(Missing)
142 
ValueCountFrequency (%)
False 514
77.9%
True 4
 
0.6%
(Missing) 142
 
21.5%
2024-05-11T15:58:58.681662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct396
Distinct (%)76.4%
Missing142
Missing (%)21.5%
Infinite0
Infinite (%)0.0%
Mean41.974073
Minimum0
Maximum309.47
Zeros17
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size5.9 KiB
2024-05-11T15:58:58.889784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.8075
Q124.6775
median34.39
Q349.85
95-th percentile97.1315
Maximum309.47
Range309.47
Interquartile range (IQR)25.1725

Descriptive statistics

Standard deviation32.733776
Coefficient of variation (CV)0.77985702
Kurtosis14.010565
Mean41.974073
Median Absolute Deviation (MAD)11.625
Skewness2.8278975
Sum21742.57
Variance1071.5001
MonotonicityNot monotonic
2024-05-11T15:58:59.147463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 18
 
2.7%
0.0 17
 
2.6%
19.8 7
 
1.1%
66.0 6
 
0.9%
40.0 4
 
0.6%
3.3 4
 
0.6%
25.0 4
 
0.6%
6.6 4
 
0.6%
26.4 4
 
0.6%
36.3 4
 
0.6%
Other values (386) 446
67.6%
(Missing) 142
 
21.5%
ValueCountFrequency (%)
0.0 17
2.6%
1.86 1
 
0.2%
1.96 1
 
0.2%
2.0 1
 
0.2%
3.0 1
 
0.2%
3.3 4
 
0.6%
4.0 1
 
0.2%
4.95 1
 
0.2%
5.0 1
 
0.2%
6.0 2
 
0.3%
ValueCountFrequency (%)
309.47 1
0.2%
235.2 1
0.2%
215.1 1
0.2%
202.66 1
0.2%
174.32 1
0.2%
173.3 1
0.2%
159.5 1
0.2%
156.75 1
0.2%
150.15 1
0.2%
144.29 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing660
Missing (%)100.0%
Memory size5.9 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031500003150000-121-1977-0000119770706<NA>3폐업2폐업20140530<NA><NA><NA>02 694729349.94157879서울특별시 강서구 화곡동 340-47번지서울특별시 강서구 강서로 64 (화곡동)7756빵굽는마을2009-12-04 10:22:12I2018-08-31 23:59:59.0제과점영업186325.541633447926.397003제과점영업22주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N49.94<NA><NA><NA>
131500003150000-121-1979-0000119790315<NA>3폐업2폐업20230104<NA><NA><NA>022605846863.06157915서울특별시 강서구 화곡동 976-1 (지상 1층)서울특별시 강서구 까치산로 119, 1층 (화곡동, 6동)7663빵집이야기2023-01-04 13:55:48U2022-12-01 00:06:00.0제과점영업186676.378727449604.879383<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231500003150000-121-1980-0000119800109<NA>3폐업2폐업20060928<NA><NA><NA>023664996525.79157862서울특별시 강서구 염창동 264-10번지<NA><NA>아비앙또2002-08-21 00:00:00I2018-08-31 23:59:59.0제과점영업188715.065865449755.844937제과점영업00주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N25.79<NA><NA><NA>
331500003150000-121-1980-0000219800318<NA>3폐업2폐업20070122<NA><NA><NA>022604418943.76157873서울특별시 강서구 화곡동 1059-50번지<NA><NA>김정식베이커리2000-06-13 00:00:00I2018-08-31 23:59:59.0제과점영업186060.144036449071.06399제과점영업21아파트지역갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.76<NA><NA><NA>
431500003150000-121-1980-0000319800913<NA>3폐업2폐업20080620<NA><NA><NA>020652866916.43157837서울특별시 강서구 등촌동 567-17번지<NA><NA>행복한 빵 세상2006-06-26 00:00:00I2018-08-31 23:59:59.0제과점영업187786.278647448166.132917제과점영업10주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N16.43<NA><NA><NA>
531500003150000-121-1981-0000119811001<NA>3폐업2폐업20090417<NA><NA><NA>0292.7157863서울특별시 강서구 염창동 275-3번지<NA><NA>컴온샌드위치2006-07-20 00:00:00I2018-08-31 23:59:59.0제과점영업188232.288045449739.920657제과점영업00주택가주변기타지하수전용<NA><NA><NA><NA><NA><NA><NA><NA>N92.7<NA><NA><NA>
631500003150000-121-1981-0000219811106<NA>3폐업2폐업20091123<NA><NA><NA>02 603218440.43157030서울특별시 강서구 등촌동 655-38번지 , 39호 (지상 1층)<NA><NA>파리바게뜨강서하이웨이점2009-11-19 10:39:22I2018-08-31 23:59:59.0제과점영업187076.509393450365.543295제과점영업31주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N40.43<NA><NA><NA>
731500003150000-121-1982-0000119820701<NA>3폐업2폐업20140211<NA><NA><NA>0253.46157869서울특별시 강서구 화곡동 80-27번지서울특별시 강서구 화곡로43가길 29 (화곡동)7690케익하우스퀸2014-02-11 09:35:12I2018-08-31 23:59:59.0제과점영업186157.462433449528.458295제과점영업21아파트지역을상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N53.46<NA><NA><NA>
831500003150000-121-1982-0000219821126<NA>3폐업2폐업20100405<NA><NA><NA>02 662441934.85157846서울특별시 강서구 방화동 249-254번지 (지상 1층)<NA><NA>빵사랑6512010-04-05 14:54:20I2018-08-31 23:59:59.0제과점영업183418.792478451956.800731제과점영업11주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.85<NA><NA><NA>
931500003150000-121-1982-0000319820712<NA>1영업/정상1영업<NA><NA><NA><NA>0226614030105.0157812서울특별시 강서구 공항동 53-1번지 (지상 1층)서울특별시 강서구 공항대로 24, 1층 (공항동)7623파리바게뜨(송정역점)2019-01-15 17:26:53U2019-01-17 02:40:00.0제과점영업183138.805912451002.52504제과점영업44주택가주변갑상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N105.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
65031500003150000-121-2023-000142023-11-14<NA>1영업/정상1영업<NA><NA><NA><NA>026228008559.28157-210서울특별시 강서구 마곡동 797 에이스타워 마곡서울특별시 강서구 공항대로 237, 에이스타워 마곡 2층 216호 (마곡동)7803(주)라크루뜨2023-12-04 16:51:48U2022-11-02 00:06:00.0제과점영업185253.478151450811.037606<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65131500003150000-121-2023-000152023-11-14<NA>1영업/정상1영업<NA><NA><NA><NA>0262280085111.84157-210서울특별시 강서구 마곡동 797 에이스타워 마곡서울특별시 강서구 공항대로 237, 에이스타워 마곡 1층 111,112호 (마곡동)7803(주)라크루뜨2023-12-04 16:51:58U2022-11-02 00:06:00.0제과점영업185253.478151450811.037606<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65231500003150000-121-2023-000162023-11-16<NA>3폐업2폐업2024-01-04<NA><NA><NA>0261165715151.23157-220서울특별시 강서구 방화동 886 김포공항, 롯데몰, 스카이시티 지하2층서울특별시 강서구 하늘길 38, 김포공항, 롯데몰, 스카이시티 지하2층 (방화동)7505엔제리너스커피 롯데몰 김포공항점2024-01-04 14:53:19U2023-12-01 00:06:00.0제과점영업182524.823836451438.250897<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65331500003150000-121-2023-000172023-11-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>50.52157-030서울특별시 강서구 등촌동 63-12 어위쉬예다인서울특별시 강서구 양천로 452, 어위쉬예다인 1층 109호 (등촌동)7574타르데마1942(등촌점)2023-12-21 10:23:20U2022-11-01 22:03:00.0제과점영업186763.420086451176.923654<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65431500003150000-121-2023-000182023-12-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA>36.86157-220서울특별시 강서구 방화동 904 신마곡벽산블루밍 판매시설1동 104동 112호서울특별시 강서구 양천로10길 38, 판매시설1동 104동 112호 (방화동, 신마곡벽산블루밍)7602뉴욕베이글2023-12-14 10:35:13I2022-11-01 23:06:00.0제과점영업182984.891499452116.873946<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65531500003150000-121-2024-000012024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.0157-898서울특별시 강서구 화곡동 799-10서울특별시 강서구 곰달래로 245, 1-5호 (화곡동)7741뚜레쥬르 목동사거리점2024-01-19 15:35:43I2023-11-30 22:01:00.0제과점영업187579.647224447775.786484<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65631500003150000-121-2024-000022024-01-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.0157-930서울특별시 강서구 등촌동 663-7 재경빌딩서울특별시 강서구 화곡로63길 125, 재경빌딩 1층 101호 (등촌동)7590오트스퀘어2024-01-19 17:23:40I2023-11-30 22:01:00.0제과점영업186336.124848450732.03485<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65731500003150000-121-2024-000032024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>47.98157-870서울특별시 강서구 화곡동 88-2서울특별시 강서구 우현로 9, 1층 좌측호 (화곡동)7695초코폰2024-03-21 15:02:42I2023-12-02 22:03:00.0제과점영업186166.477854449407.647562<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65831500003150000-121-2024-000042024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>99.0157-924서울특별시 강서구 화곡동 1066-1 전원빌딩서울특별시 강서구 화곡로 137, 전원빌딩 1층 대로변 우측호 (화곡동)7714찰찰보리식빵2024-04-15 12:10:02I2023-12-03 23:07:00.0제과점영업185525.03734448760.644761<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
65931500003150000-121-2024-000052024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>32.56157-210서울특별시 강서구 마곡동 799-11 파인스퀘어서울특별시 강서구 마곡중앙4로 22, 파인스퀘어 A동 2층 215호 (마곡동)7631요빵조빵2024-04-30 09:25:56I2023-12-05 00:02:00.0제과점영업184844.841587450680.365609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>