Overview

Dataset statistics

Number of variables44
Number of observations614
Missing cells6141
Missing cells (%)22.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory226.2 KiB
Average record size in memory377.2 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
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18416/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
남성종사자수 is highly imbalanced (51.3%)Imbalance
영업장주변구분명 is highly imbalanced (67.3%)Imbalance
등급구분명 is highly imbalanced (75.0%)Imbalance
급수시설구분명 is highly imbalanced (55.0%)Imbalance
총인원 is highly imbalanced (71.2%)Imbalance
본사종업원수 is highly imbalanced (70.5%)Imbalance
공장사무직종업원수 is highly imbalanced (70.5%)Imbalance
공장판매직종업원수 is highly imbalanced (70.5%)Imbalance
공장생산직종업원수 is highly imbalanced (70.5%)Imbalance
보증액 is highly imbalanced (70.5%)Imbalance
월세액 is highly imbalanced (70.5%)Imbalance
다중이용업소여부 is highly imbalanced (96.0%)Imbalance
인허가취소일자 has 614 (100.0%) missing valuesMissing
폐업일자 has 144 (23.5%) missing valuesMissing
휴업시작일자 has 614 (100.0%) missing valuesMissing
휴업종료일자 has 614 (100.0%) missing valuesMissing
재개업일자 has 614 (100.0%) missing valuesMissing
전화번호 has 348 (56.7%) missing valuesMissing
소재지면적 has 56 (9.1%) missing valuesMissing
도로명주소 has 189 (30.8%) missing valuesMissing
도로명우편번호 has 192 (31.3%) missing valuesMissing
건물소유구분명 has 614 (100.0%) missing valuesMissing
다중이용업소여부 has 144 (23.5%) missing valuesMissing
시설총규모 has 144 (23.5%) missing valuesMissing
전통업소지정번호 has 614 (100.0%) missing valuesMissing
전통업소주된음식 has 614 (100.0%) missing valuesMissing
홈페이지 has 614 (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
시설총규모 has 25 (4.1%) zerosZeros

Reproduction

Analysis started2024-05-11 03:44:36.184734
Analysis finished2024-05-11 03:44:38.046249
Duration1.86 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3140000
614 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 614
100.0%

Length

2024-05-11T03:44:38.238791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:38.578845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 614
100.0%

관리번호
Text

UNIQUE 

Distinct614
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T03:44:38.960928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13508
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

Unique614 ?
Unique (%)100.0%

Sample

1st row3140000-121-1978-06035
2nd row3140000-121-1979-06021
3rd row3140000-121-1979-06062
4th row3140000-121-1980-06033
5th row3140000-121-1981-05914
ValueCountFrequency (%)
3140000-121-1978-06035 1
 
0.2%
3140000-121-2015-00022 1
 
0.2%
3140000-121-2015-00016 1
 
0.2%
3140000-121-2015-00032 1
 
0.2%
3140000-121-2015-00017 1
 
0.2%
3140000-121-2015-00018 1
 
0.2%
3140000-121-2015-00019 1
 
0.2%
3140000-121-2015-00020 1
 
0.2%
3140000-121-2015-00021 1
 
0.2%
3140000-121-2015-00023 1
 
0.2%
Other values (604) 604
98.4%
2024-05-11T03:44:39.798679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5209
38.6%
1 2483
18.4%
- 1842
 
13.6%
2 1558
 
11.5%
3 801
 
5.9%
4 751
 
5.6%
9 245
 
1.8%
6 177
 
1.3%
8 159
 
1.2%
5 151
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11666
86.4%
Dash Punctuation 1842
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5209
44.7%
1 2483
21.3%
2 1558
 
13.4%
3 801
 
6.9%
4 751
 
6.4%
9 245
 
2.1%
6 177
 
1.5%
8 159
 
1.4%
5 151
 
1.3%
7 132
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1842
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13508
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5209
38.6%
1 2483
18.4%
- 1842
 
13.6%
2 1558
 
11.5%
3 801
 
5.9%
4 751
 
5.6%
9 245
 
1.8%
6 177
 
1.3%
8 159
 
1.2%
5 151
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13508
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5209
38.6%
1 2483
18.4%
- 1842
 
13.6%
2 1558
 
11.5%
3 801
 
5.9%
4 751
 
5.6%
9 245
 
1.8%
6 177
 
1.3%
8 159
 
1.2%
5 151
 
1.1%

인허가일자
Date

Distinct554
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1978-12-01 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T03:44:40.192301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:40.753050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
470 
1
144 

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 (%)
3 470
76.5%
1 144
 
23.5%

Length

2024-05-11T03:44:41.213522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:41.550768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 470
76.5%
1 144
 
23.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
470 
영업/정상
144 

Length

Max length5
Median length2
Mean length2.7035831
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 470
76.5%
영업/정상 144
 
23.5%

Length

2024-05-11T03:44:41.950614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:42.408410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 470
76.5%
영업/정상 144
 
23.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2
470 
1
144 

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 (%)
2 470
76.5%
1 144
 
23.5%

Length

2024-05-11T03:44:42.795432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:43.121162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 470
76.5%
1 144
 
23.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
470 
영업
144 

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 470
76.5%
영업 144
 
23.5%

Length

2024-05-11T03:44:43.433556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:43.728325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 470
76.5%
영업 144
 
23.5%

폐업일자
Date

MISSING 

Distinct410
Distinct (%)87.2%
Missing144
Missing (%)23.5%
Memory size4.9 KiB
Minimum2005-10-04 00:00:00
Maximum2024-05-02 00:00:00
2024-05-11T03:44:44.074194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:44.493008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

전화번호
Text

MISSING 

Distinct259
Distinct (%)97.4%
Missing348
Missing (%)56.7%
Memory size4.9 KiB
2024-05-11T03:44:44.981375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.172932
Min length6

Characters and Unicode

Total characters2706
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

Unique252 ?
Unique (%)94.7%

Sample

1st row0226038208
2nd row0226933941
3rd row0226040794
4th row0226941741
5th row02 26051621
ValueCountFrequency (%)
02 68
 
19.4%
031 3
 
0.9%
041 2
 
0.6%
0220613871 2
 
0.6%
5433909 2
 
0.6%
0260845705 2
 
0.6%
032 2
 
0.6%
0200000000 2
 
0.6%
0226468284 2
 
0.6%
0221632233 2
 
0.6%
Other values (263) 264
75.2%
2024-05-11T03:44:45.708690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 588
21.7%
0 520
19.2%
6 343
12.7%
4 212
 
7.8%
5 184
 
6.8%
3 161
 
5.9%
8 156
 
5.8%
1 154
 
5.7%
9 135
 
5.0%
7 132
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2585
95.5%
Space Separator 121
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 588
22.7%
0 520
20.1%
6 343
13.3%
4 212
 
8.2%
5 184
 
7.1%
3 161
 
6.2%
8 156
 
6.0%
1 154
 
6.0%
9 135
 
5.2%
7 132
 
5.1%
Space Separator
ValueCountFrequency (%)
121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2706
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 588
21.7%
0 520
19.2%
6 343
12.7%
4 212
 
7.8%
5 184
 
6.8%
3 161
 
5.9%
8 156
 
5.8%
1 154
 
5.7%
9 135
 
5.0%
7 132
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2706
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 588
21.7%
0 520
19.2%
6 343
12.7%
4 212
 
7.8%
5 184
 
6.8%
3 161
 
5.9%
8 156
 
5.8%
1 154
 
5.7%
9 135
 
5.0%
7 132
 
4.9%

소재지면적
Real number (ℝ)

MISSING 

Distinct345
Distinct (%)61.8%
Missing56
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean39.87353
Minimum0
Maximum411.65
Zeros4
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T03:44:46.083106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.3
Q117
median29.85
Q350.37
95-th percentile105.1795
Maximum411.65
Range411.65
Interquartile range (IQR)33.37

Descriptive statistics

Standard deviation38.936049
Coefficient of variation (CV)0.97648863
Kurtosis24.177177
Mean39.87353
Median Absolute Deviation (MAD)16.35
Skewness3.7022682
Sum22249.43
Variance1516.0159
MonotonicityNot monotonic
2024-05-11T03:44:46.393446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 18
 
2.9%
10.0 15
 
2.4%
30.0 13
 
2.1%
6.6 10
 
1.6%
6.0 10
 
1.6%
33.0 9
 
1.5%
9.9 9
 
1.5%
28.0 9
 
1.5%
66.0 8
 
1.3%
26.4 6
 
1.0%
Other values (335) 451
73.5%
(Missing) 56
 
9.1%
ValueCountFrequency (%)
0.0 4
 
0.7%
1.0 2
 
0.3%
2.0 3
 
0.5%
2.5 1
 
0.2%
3.2 1
 
0.2%
3.24 1
 
0.2%
3.3 18
2.9%
3.6 1
 
0.2%
4.0 1
 
0.2%
4.4 1
 
0.2%
ValueCountFrequency (%)
411.65 1
0.2%
318.68 1
0.2%
311.96 1
0.2%
199.97 1
0.2%
191.82 1
0.2%
179.54 1
0.2%
178.0 1
0.2%
165.29 1
0.2%
162.36 1
0.2%
155.44 1
0.2%

소재지우편번호
Text

Distinct101
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T03:44:46.866134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1188925
Min length6

Characters and Unicode

Total characters3757
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

Unique30 ?
Unique (%)4.9%

Sample

1st row158831
2nd row158829
3rd row158090
4th row158813
5th row158864
ValueCountFrequency (%)
158050 112
 
18.2%
158724 41
 
6.7%
158070 38
 
6.2%
158-724 22
 
3.6%
158806 22
 
3.6%
158860 22
 
3.6%
158849 17
 
2.8%
158811 15
 
2.4%
158861 13
 
2.1%
158877 12
 
2.0%
Other values (91) 300
48.9%
2024-05-11T03:44:47.554754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1047
27.9%
5 801
21.3%
1 738
19.6%
0 412
 
11.0%
7 210
 
5.6%
4 147
 
3.9%
2 140
 
3.7%
6 104
 
2.8%
- 73
 
1.9%
9 53
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3684
98.1%
Dash Punctuation 73
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1047
28.4%
5 801
21.7%
1 738
20.0%
0 412
 
11.2%
7 210
 
5.7%
4 147
 
4.0%
2 140
 
3.8%
6 104
 
2.8%
9 53
 
1.4%
3 32
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3757
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1047
27.9%
5 801
21.3%
1 738
19.6%
0 412
 
11.0%
7 210
 
5.6%
4 147
 
3.9%
2 140
 
3.7%
6 104
 
2.8%
- 73
 
1.9%
9 53
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3757
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1047
27.9%
5 801
21.3%
1 738
19.6%
0 412
 
11.0%
7 210
 
5.6%
4 147
 
3.9%
2 140
 
3.7%
6 104
 
2.8%
- 73
 
1.9%
9 53
 
1.4%

지번주소
Text

Distinct500
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T03:44:48.007939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length29.123779
Min length18

Characters and Unicode

Total characters17882
Distinct characters223
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

Unique473 ?
Unique (%)77.0%

Sample

1st row서울특별시 양천구 신월동 228-1 1층
2nd row서울특별시 양천구 신월동 147-4번지
3rd row서울특별시 양천구 신월동 23-14번지 ,15
4th row서울특별시 양천구 목동 721-5번지
5th row서울특별시 양천구 신정동 1190-6번지
ValueCountFrequency (%)
양천구 615
18.2%
서울특별시 614
18.2%
목동 353
 
10.5%
신정동 184
 
5.5%
1층 119
 
3.5%
신월동 85
 
2.5%
지하2층 72
 
2.1%
916번지 66
 
2.0%
916 65
 
1.9%
현대하이페리온 60
 
1.8%
Other values (700) 1140
33.8%
2024-05-11T03:44:48.994837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3180
 
17.8%
1 1020
 
5.7%
동 748
 
4.2%
지 641
 
3.6%
시 629
 
3.5%
양 627
 
3.5%
천 623
 
3.5%
구 619
 
3.5%
서 615
 
3.4%
특 615
 
3.4%
Other values (213) 8565
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10602
59.3%
Decimal Number 3472
 
19.4%
Space Separator 3180
 
17.8%
Dash Punctuation 417
 
2.3%
Open Punctuation 57
 
0.3%
Close Punctuation 57
 
0.3%
Uppercase Letter 53
 
0.3%
Other Punctuation 37
 
0.2%
Math Symbol 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 748
 
7.1%
지 641
 
6.0%
시 629
 
5.9%
양 627
 
5.9%
천 623
 
5.9%
구 619
 
5.8%
서 615
 
5.8%
특 615
 
5.8%
별 614
 
5.8%
울 614
 
5.8%
Other values (184) 4257
40.2%
Decimal Number
ValueCountFrequency (%)
1 1020
29.4%
2 461
13.3%
9 398
 
11.5%
0 375
 
10.8%
6 316
 
9.1%
3 250
 
7.2%
7 198
 
5.7%
4 167
 
4.8%
5 147
 
4.2%
8 140
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 16
30.2%
B 12
22.6%
S 11
20.8%
G 10
18.9%
C 2
 
3.8%
P 1
 
1.9%
T 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 32
86.5%
. 2
 
5.4%
@ 2
 
5.4%
? 1
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
g 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
3180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 417
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10602
59.3%
Common 7224
40.4%
Latin 56
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 748
 
7.1%
지 641
 
6.0%
시 629
 
5.9%
양 627
 
5.9%
천 623
 
5.9%
구 619
 
5.8%
서 615
 
5.8%
특 615
 
5.8%
별 614
 
5.8%
울 614
 
5.8%
Other values (184) 4257
40.2%
Common
ValueCountFrequency (%)
3180
44.0%
1 1020
 
14.1%
2 461
 
6.4%
- 417
 
5.8%
9 398
 
5.5%
0 375
 
5.2%
6 316
 
4.4%
3 250
 
3.5%
7 198
 
2.7%
4 167
 
2.3%
Other values (9) 442
 
6.1%
Latin
ValueCountFrequency (%)
A 16
28.6%
B 12
21.4%
S 11
19.6%
G 10
17.9%
C 2
 
3.6%
Ⅰ 1
 
1.8%
P 1
 
1.8%
T 1
 
1.8%
g 1
 
1.8%
s 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10602
59.3%
ASCII 7279
40.7%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3180
43.7%
1 1020
 
14.0%
2 461
 
6.3%
- 417
 
5.7%
9 398
 
5.5%
0 375
 
5.2%
6 316
 
4.3%
3 250
 
3.4%
7 198
 
2.7%
4 167
 
2.3%
Other values (18) 497
 
6.8%
Hangul
ValueCountFrequency (%)
동 748
 
7.1%
지 641
 
6.0%
시 629
 
5.9%
양 627
 
5.9%
천 623
 
5.9%
구 619
 
5.8%
서 615
 
5.8%
특 615
 
5.8%
별 614
 
5.8%
울 614
 
5.8%
Other values (184) 4257
40.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct335
Distinct (%)78.8%
Missing189
Missing (%)30.8%
Memory size4.9 KiB
2024-05-11T03:44:49.567775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length54
Mean length36.357647
Min length22

Characters and Unicode

Total characters15452
Distinct characters219
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

Unique320 ?
Unique (%)75.3%

Sample

1st row서울특별시 양천구 곰달래로 48, 1층 (신월동)
2nd row서울특별시 양천구 오목로 75, 1층 (신월동)
3rd row서울특별시 양천구 오목로 149 (신정동)
4th row서울특별시 양천구 목동중앙본로 123, 지상1층 (목동)
5th row서울특별시 양천구 신월로10길 17 (신월동)
ValueCountFrequency (%)
양천구 426
 
14.5%
서울특별시 425
 
14.4%
목동 222
 
7.5%
목동동로 144
 
4.9%
1층 127
 
4.3%
신정동 117
 
4.0%
257 109
 
3.7%
지하2층 104
 
3.5%
현대하이페리온 63
 
2.1%
목동서로 47
 
1.6%
Other values (507) 1158
39.4%
2024-05-11T03:44:50.604470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2517
 
16.3%
동 971
 
6.3%
목 654
 
4.2%
, 618
 
4.0%
1 603
 
3.9%
서 479
 
3.1%
양 444
 
2.9%
( 443
 
2.9%
) 443
 
2.9%
시 440
 
2.8%
Other values (209) 7840
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9125
59.1%
Space Separator 2517
 
16.3%
Decimal Number 2225
 
14.4%
Other Punctuation 620
 
4.0%
Open Punctuation 443
 
2.9%
Close Punctuation 443
 
2.9%
Uppercase Letter 39
 
0.3%
Dash Punctuation 32
 
0.2%
Math Symbol 5
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 971
 
10.6%
목 654
 
7.2%
서 479
 
5.2%
양 444
 
4.9%
시 440
 
4.8%
천 434
 
4.8%
구 430
 
4.7%
로 430
 
4.7%
별 425
 
4.7%
특 425
 
4.7%
Other values (181) 3993
43.8%
Decimal Number
ValueCountFrequency (%)
1 603
27.1%
2 431
19.4%
0 254
11.4%
5 226
 
10.2%
7 211
 
9.5%
3 177
 
8.0%
4 120
 
5.4%
9 73
 
3.3%
8 65
 
2.9%
6 65
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
A 11
28.2%
S 9
23.1%
G 9
23.1%
B 7
17.9%
C 1
 
2.6%
T 1
 
2.6%
P 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 618
99.7%
? 1
 
0.2%
@ 1
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
g 1
50.0%
Space Separator
ValueCountFrequency (%)
2517
100.0%
Open Punctuation
ValueCountFrequency (%)
( 443
100.0%
Close Punctuation
ValueCountFrequency (%)
) 443
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9125
59.1%
Common 6285
40.7%
Latin 42
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 971
 
10.6%
목 654
 
7.2%
서 479
 
5.2%
양 444
 
4.9%
시 440
 
4.8%
천 434
 
4.8%
구 430
 
4.7%
로 430
 
4.7%
별 425
 
4.7%
특 425
 
4.7%
Other values (181) 3993
43.8%
Common
ValueCountFrequency (%)
2517
40.0%
, 618
 
9.8%
1 603
 
9.6%
( 443
 
7.0%
) 443
 
7.0%
2 431
 
6.9%
0 254
 
4.0%
5 226
 
3.6%
7 211
 
3.4%
3 177
 
2.8%
Other values (8) 362
 
5.8%
Latin
ValueCountFrequency (%)
A 11
26.2%
S 9
21.4%
G 9
21.4%
B 7
16.7%
s 1
 
2.4%
C 1
 
2.4%
Ⅰ 1
 
2.4%
T 1
 
2.4%
P 1
 
2.4%
g 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9125
59.1%
ASCII 6326
40.9%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2517
39.8%
, 618
 
9.8%
1 603
 
9.5%
( 443
 
7.0%
) 443
 
7.0%
2 431
 
6.8%
0 254
 
4.0%
5 226
 
3.6%
7 211
 
3.3%
3 177
 
2.8%
Other values (17) 403
 
6.4%
Hangul
ValueCountFrequency (%)
동 971
 
10.6%
목 654
 
7.2%
서 479
 
5.2%
양 444
 
4.9%
시 440
 
4.8%
천 434
 
4.8%
구 430
 
4.7%
로 430
 
4.7%
별 425
 
4.7%
특 425
 
4.7%
Other values (181) 3993
43.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)27.7%
Missing192
Missing (%)31.3%
Infinite0
Infinite (%)0.0%
Mean8004.2014
Minimum7902
Maximum8106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T03:44:50.966594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7902
5-th percentile7930
Q17983
median7998
Q38020.25
95-th percentile8093
Maximum8106
Range204
Interquartile range (IQR)37.25

Descriptive statistics

Standard deviation45.765847
Coefficient of variation (CV)0.0057177281
Kurtosis0.052648176
Mean8004.2014
Median Absolute Deviation (MAD)17
Skewness0.34117651
Sum3377773
Variance2094.5128
MonotonicityNot monotonic
2024-05-11T03:44:51.291973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7998 109
17.8%
7993 11
 
1.8%
8014 10
 
1.6%
7997 10
 
1.6%
8093 9
 
1.5%
8082 8
 
1.3%
8011 7
 
1.1%
7983 7
 
1.1%
7984 7
 
1.1%
7946 6
 
1.0%
Other values (107) 238
38.8%
(Missing) 192
31.3%
ValueCountFrequency (%)
7902 2
0.3%
7903 3
0.5%
7904 1
 
0.2%
7906 1
 
0.2%
7910 2
0.3%
7911 1
 
0.2%
7912 2
0.3%
7915 1
 
0.2%
7918 2
0.3%
7919 1
 
0.2%
ValueCountFrequency (%)
8106 1
 
0.2%
8105 1
 
0.2%
8104 1
 
0.2%
8101 2
 
0.3%
8100 3
 
0.5%
8097 2
 
0.3%
8096 3
 
0.5%
8095 5
0.8%
8093 9
1.5%
8092 4
0.7%

사업장명
Text

Distinct513
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T03:44:51.744896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length7.4234528
Min length2

Characters and Unicode

Total characters4558
Distinct characters453
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique462 ?
Unique (%)75.2%

Sample

1st row파리바게뜨
2nd row베르떼과자점
3rd row크라운베이커리
4th row케익하우스몽마
5th row크라운베이커리
ValueCountFrequency (%)
목동점 24
 
3.1%
파리바게뜨 21
 
2.7%
뚜레쥬르 15
 
1.9%
베즐리 11
 
1.4%
베이커리 11
 
1.4%
파리바게트 8
 
1.0%
크라운베이커리 7
 
0.9%
아띠베이커리 6
 
0.8%
이지바이 6
 
0.8%
월드하우스 6
 
0.8%
Other values (554) 665
85.3%
2024-05-11T03:44:52.699170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 220
 
4.8%
점 199
 
4.4%
이 187
 
4.1%
166
 
3.6%
베 126
 
2.8%
스 107
 
2.3%
목 106
 
2.3%
동 98
 
2.2%
커 97
 
2.1%
레 78
 
1.7%
Other values (443) 3174
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3935
86.3%
Space Separator 166
 
3.6%
Uppercase Letter 121
 
2.7%
Lowercase Letter 120
 
2.6%
Close Punctuation 77
 
1.7%
Open Punctuation 76
 
1.7%
Decimal Number 44
 
1.0%
Other Punctuation 14
 
0.3%
Dash Punctuation 3
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 220
 
5.6%
점 199
 
5.1%
이 187
 
4.8%
베 126
 
3.2%
스 107
 
2.7%
목 106
 
2.7%
동 98
 
2.5%
커 97
 
2.5%
레 78
 
2.0%
드 74
 
1.9%
Other values (382) 2643
67.2%
Uppercase Letter
ValueCountFrequency (%)
B 20
16.5%
E 14
11.6%
A 11
9.1%
R 9
 
7.4%
K 8
 
6.6%
T 8
 
6.6%
G 8
 
6.6%
Y 7
 
5.8%
C 6
 
5.0%
S 5
 
4.1%
Other values (12) 25
20.7%
Lowercase Letter
ValueCountFrequency (%)
e 21
17.5%
a 12
10.0%
r 11
9.2%
s 9
 
7.5%
d 9
 
7.5%
i 8
 
6.7%
o 8
 
6.7%
n 7
 
5.8%
y 4
 
3.3%
u 4
 
3.3%
Other values (11) 27
22.5%
Decimal Number
ValueCountFrequency (%)
2 14
31.8%
1 9
20.5%
4 8
18.2%
7 5
 
11.4%
3 5
 
11.4%
5 2
 
4.5%
9 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
? 5
35.7%
. 4
28.6%
& 3
21.4%
' 1
 
7.1%
! 1
 
7.1%
Space Separator
ValueCountFrequency (%)
166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3934
86.3%
Common 382
 
8.4%
Latin 241
 
5.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 220
 
5.6%
점 199
 
5.1%
이 187
 
4.8%
베 126
 
3.2%
스 107
 
2.7%
목 106
 
2.7%
동 98
 
2.5%
커 97
 
2.5%
레 78
 
2.0%
드 74
 
1.9%
Other values (381) 2642
67.2%
Latin
ValueCountFrequency (%)
e 21
 
8.7%
B 20
 
8.3%
E 14
 
5.8%
a 12
 
5.0%
r 11
 
4.6%
A 11
 
4.6%
s 9
 
3.7%
R 9
 
3.7%
d 9
 
3.7%
i 8
 
3.3%
Other values (33) 117
48.5%
Common
ValueCountFrequency (%)
166
43.5%
) 77
20.2%
( 76
19.9%
2 14
 
3.7%
1 9
 
2.4%
4 8
 
2.1%
7 5
 
1.3%
? 5
 
1.3%
3 5
 
1.3%
. 4
 
1.0%
Other values (8) 13
 
3.4%
Han
ValueCountFrequency (%)
米 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3934
86.3%
ASCII 623
 
13.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 220
 
5.6%
점 199
 
5.1%
이 187
 
4.8%
베 126
 
3.2%
스 107
 
2.7%
목 106
 
2.7%
동 98
 
2.5%
커 97
 
2.5%
레 78
 
2.0%
드 74
 
1.9%
Other values (381) 2642
67.2%
ASCII
ValueCountFrequency (%)
166
26.6%
) 77
 
12.4%
( 76
 
12.2%
e 21
 
3.4%
B 20
 
3.2%
E 14
 
2.2%
2 14
 
2.2%
a 12
 
1.9%
r 11
 
1.8%
A 11
 
1.8%
Other values (51) 201
32.3%
CJK
ValueCountFrequency (%)
米 1
100.0%

최종수정일자
Date

Distinct582
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1999-11-08 00:00:00
Maximum2024-05-08 17:03:46
2024-05-11T03:44:53.099267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:53.550391image/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 size4.9 KiB
I
395 
U
219 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 395
64.3%
U 219
35.7%

Length

2024-05-11T03:44:53.914968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:54.106843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 395
64.3%
u 219
35.7%

데이터갱신일자
Date

Distinct204
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T03:44:54.314979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:44:54.602231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
제과점영업
614 

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 614
100.0%

Length

2024-05-11T03:44:54.859137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:55.171329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 614
100.0%

좌표정보(X)
Real number (ℝ)

Distinct322
Distinct (%)53.0%
Missing6
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean187956.79
Minimum184571.8
Maximum189755.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T03:44:55.536018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184571.8
5-th percentile185183.98
Q1187600.07
median188385.25
Q3188884.08
95-th percentile189084.3
Maximum189755.54
Range5183.741
Interquartile range (IQR)1284.0018

Descriptive statistics

Standard deviation1224.003
Coefficient of variation (CV)0.0065121512
Kurtosis0.54321586
Mean187956.79
Median Absolute Deviation (MAD)498.82083
Skewness-1.2389574
Sum1.1427773 × 108
Variance1498183.4
MonotonicityNot monotonic
2024-05-11T03:44:56.021694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188884.075622342 130
 
21.2%
188729.190478822 11
 
1.8%
188977.171050288 10
 
1.6%
188039.543424546 8
 
1.3%
188248.45432693 7
 
1.1%
187734.983111761 6
 
1.0%
189473.530827695 5
 
0.8%
188700.851169641 5
 
0.8%
188793.15163303 5
 
0.8%
188431.286329151 4
 
0.7%
Other values (312) 417
67.9%
(Missing) 6
 
1.0%
ValueCountFrequency (%)
184571.800289929 1
0.2%
184633.623963945 1
0.2%
184644.415616888 1
0.2%
184649.657252374 1
0.2%
184655.396681504 1
0.2%
184678.753937033 1
0.2%
184694.128184681 1
0.2%
184712.279100404 1
0.2%
184758.160681476 2
0.3%
184773.372180974 1
0.2%
ValueCountFrequency (%)
189755.541308355 1
 
0.2%
189749.776358917 1
 
0.2%
189709.803505321 1
 
0.2%
189676.766585898 1
 
0.2%
189508.199599752 1
 
0.2%
189473.530827695 5
0.8%
189471.306217651 4
0.7%
189423.528553032 2
 
0.3%
189371.998478153 1
 
0.2%
189348.372526225 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct322
Distinct (%)53.0%
Missing6
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean447240.37
Minimum444913.02
Maximum449656.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T03:44:56.291378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444913.02
5-th percentile445879.05
Q1446605.3
median447186.89
Q3447777.84
95-th percentile449332.85
Maximum449656.73
Range4743.714
Interquartile range (IQR)1172.54

Descriptive statistics

Standard deviation976.73557
Coefficient of variation (CV)0.0021839164
Kurtosis0.065222142
Mean447240.37
Median Absolute Deviation (MAD)587.68083
Skewness0.54572499
Sum2.7192214 × 108
Variance954012.37
MonotonicityNot monotonic
2024-05-11T03:44:56.603198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447186.888604306 130
 
21.2%
447572.610039376 11
 
1.8%
447466.355031447 10
 
1.6%
446149.197185122 8
 
1.3%
447406.301288366 7
 
1.1%
446030.714521005 6
 
1.0%
448365.502006523 5
 
0.8%
448020.090999138 5
 
0.8%
446945.537493279 5
 
0.8%
446909.365903882 4
 
0.7%
Other values (312) 417
67.9%
(Missing) 6
 
1.0%
ValueCountFrequency (%)
444913.015801315 1
0.2%
445006.611450798 1
0.2%
445124.131588947 1
0.2%
445180.40867328 2
0.3%
445191.39723995 1
0.2%
445297.986765501 1
0.2%
445428.447103333 2
0.3%
445546.556343923 1
0.2%
445562.576452316 2
0.3%
445601.70796781 1
0.2%
ValueCountFrequency (%)
449656.729753851 3
0.5%
449654.079008626 1
 
0.2%
449649.016215774 4
0.7%
449626.380102558 3
0.5%
449596.304559134 2
0.3%
449596.162199226 1
 
0.2%
449578.286440857 1
 
0.2%
449567.1501626 1
 
0.2%
449565.722768071 1
 
0.2%
449554.911976327 1
 
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
제과점영업
470 
<NA>
144 

Length

Max length5
Median length5
Mean length4.7654723
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 470
76.5%
<NA> 144
 
23.5%

Length

2024-05-11T03:44:56.855255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:57.160523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 470
76.5%
na 144
 
23.5%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
426 
0
137 
1
 
34
2
 
10
3
 
5

Length

Max length4
Median length4
Mean length3.0814332
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 426
69.4%
0 137
 
22.3%
1 34
 
5.5%
2 10
 
1.6%
3 5
 
0.8%
4 2
 
0.3%

Length

2024-05-11T03:44:57.519364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:57.876848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 426
69.4%
0 137
 
22.3%
1 34
 
5.5%
2 10
 
1.6%
3 5
 
0.8%
4 2
 
0.3%

여성종사자수
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
427 
0
134 
1
44 
2
 
9

Length

Max length4
Median length4
Mean length3.0863192
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 427
69.5%
0 134
 
21.8%
1 44
 
7.2%
2 9
 
1.5%

Length

2024-05-11T03:44:58.270128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:58.606147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 427
69.5%
0 134
 
21.8%
1 44
 
7.2%
2 9
 
1.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
546 
주택가주변
 
34
아파트지역
 
27
기타
 
7

Length

Max length5
Median length4
Mean length4.0765472
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 546
88.9%
주택가주변 34
 
5.5%
아파트지역 27
 
4.4%
기타 7
 
1.1%

Length

2024-05-11T03:44:59.007904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:44:59.367725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 546
88.9%
주택가주변 34
 
5.5%
아파트지역 27
 
4.4%
기타 7
 
1.1%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
553 
기타
 
42
지도
 
16
자율
 
2
우수
 
1

Length

Max length4
Median length4
Mean length3.8013029
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 553
90.1%
기타 42
 
6.8%
지도 16
 
2.6%
자율 2
 
0.3%
우수 1
 
0.2%

Length

2024-05-11T03:44:59.843841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:00.236716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 553
90.1%
기타 42
 
6.8%
지도 16
 
2.6%
자율 2
 
0.3%
우수 1
 
0.2%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
498 
상수도전용
115 
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.2084691
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 498
81.1%
상수도전용 115
 
18.7%
상수도(음용)지하수(주방용)겸용 1
 
0.2%

Length

2024-05-11T03:45:00.644803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:00.992020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 498
81.1%
상수도전용 115
 
18.7%
상수도(음용)지하수(주방용)겸용 1
 
0.2%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
583 
0
 
31

Length

Max length4
Median length4
Mean length3.8485342
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> 583
95.0%
0 31
 
5.0%

Length

2024-05-11T03:45:01.404678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:01.751807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 583
95.0%
0 31
 
5.0%

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:02.118999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:02.468034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:02.959654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:03.266064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:03.642298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:03.983882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:04.277257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:04.471901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:04.688464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:04.971163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
582 
0
 
32

Length

Max length4
Median length4
Mean length3.8436482
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> 582
94.8%
0 32
 
5.2%

Length

2024-05-11T03:45:05.385088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:45:05.581121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 582
94.8%
0 32
 
5.2%

다중이용업소여부
Boolean

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing144
Missing (%)23.5%
Memory size1.3 KiB
False
468 
True
 
2
(Missing)
144 
ValueCountFrequency (%)
False 468
76.2%
True 2
 
0.3%
(Missing) 144
 
23.5%
2024-05-11T03:45:05.728995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct287
Distinct (%)61.1%
Missing144
Missing (%)23.5%
Infinite0
Infinite (%)0.0%
Mean36.86617
Minimum0
Maximum411.65
Zeros25
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T03:45:06.062943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115.2
median28.75
Q346.9025
95-th percentile100.781
Maximum411.65
Range411.65
Interquartile range (IQR)31.7025

Descriptive statistics

Standard deviation36.9824
Coefficient of variation (CV)1.0031527
Kurtosis29.42155
Mean36.86617
Median Absolute Deviation (MAD)16.75
Skewness3.9527196
Sum17327.1
Variance1367.6979
MonotonicityNot monotonic
2024-05-11T03:45:06.499881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 25
 
4.1%
3.3 15
 
2.4%
10.0 12
 
2.0%
30.0 11
 
1.8%
6.6 10
 
1.6%
6.0 10
 
1.6%
28.0 8
 
1.3%
33.0 8
 
1.3%
9.9 7
 
1.1%
24.0 6
 
1.0%
Other values (277) 358
58.3%
(Missing) 144
23.5%
ValueCountFrequency (%)
0.0 25
4.1%
2.0 3
 
0.5%
2.5 1
 
0.2%
3.24 1
 
0.2%
3.3 15
2.4%
3.6 1
 
0.2%
4.0 1
 
0.2%
4.4 1
 
0.2%
4.65 1
 
0.2%
4.95 1
 
0.2%
ValueCountFrequency (%)
411.65 1
0.2%
311.96 1
0.2%
199.97 1
0.2%
178.0 1
0.2%
162.36 1
0.2%
155.44 1
0.2%
145.76 1
0.2%
132.0 1
0.2%
123.54 1
0.2%
122.4 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing614
Missing (%)100.0%
Memory size5.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-121-1978-0603519781201<NA>1영업/정상1영업<NA><NA><NA><NA>022603820866.0158831서울특별시 양천구 신월동 228-1 1층서울특별시 양천구 곰달래로 48, 1층 (신월동)7925파리바게뜨2022-12-30 14:13:32U2022-12-01 00:01:00.0제과점영업185618.848964447519.079979<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131400003140000-121-1979-0602119790927<NA>3폐업2폐업20080418<NA><NA><NA>022693394137.76158829서울특별시 양천구 신월동 147-4번지<NA><NA>베르떼과자점2003-06-03 00:00:00I2018-08-31 23:59:59.0제과점영업184758.160681448125.6934제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N37.76<NA><NA><NA>
231400003140000-121-1979-0606219790730<NA>3폐업2폐업20120307<NA><NA><NA>022604079456.8158090서울특별시 양천구 신월동 23-14번지 ,15<NA><NA>크라운베이커리2007-10-10 16:43:54I2018-08-31 23:59:59.0제과점영업185219.063118448660.569381제과점영업02주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N56.8<NA><NA><NA>
331400003140000-121-1980-0603319801004<NA>3폐업2폐업20071001<NA><NA><NA>022694174128.6158813서울특별시 양천구 목동 721-5번지<NA><NA>케익하우스몽마2001-09-28 00:00:00I2018-08-31 23:59:59.0제과점영업187911.742213448585.991544제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N28.6<NA><NA><NA>
431400003140000-121-1981-0591419810529<NA>3폐업2폐업20100811<NA><NA><NA>02 2605162134.22158864서울특별시 양천구 신정동 1190-6번지<NA><NA>크라운베이커리2008-05-27 16:57:03I2018-08-31 23:59:59.0제과점영업186887.779002446481.970676제과점영업12주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N34.22<NA><NA><NA>
531400003140000-121-1982-0593319820210<NA>3폐업2폐업20060807<NA><NA><NA>020698040426.0158857서울특별시 양천구 신정동 903-28번지<NA><NA>빵굽는나라2001-09-28 00:00:00I2018-08-31 23:59:59.0제과점영업187581.377183447068.526916제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N26.0<NA><NA><NA>
631400003140000-121-1982-0600319820907<NA>1영업/정상1영업<NA><NA><NA><NA>022604775662.4158838서울특별시 양천구 신월동 492-16 1층서울특별시 양천구 오목로 75, 1층 (신월동)7935로띠르베이커리2022-12-30 14:48:51U2022-12-01 00:01:00.0제과점영업186302.868074446772.054243<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
731400003140000-121-1983-0602819830618<NA>3폐업2폐업20120912<NA><NA><NA>020694354439.9158828서울특별시 양천구 신월동 131-20번지<NA><NA>월드하우스2001-09-28 00:00:00I2018-08-31 23:59:59.0제과점영업185057.599002447754.80543제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N39.9<NA><NA><NA>
831400003140000-121-1983-0609519830706<NA>1영업/정상1영업<NA><NA><NA><NA>0226996994122.4158858서울특별시 양천구 신정동 922-3서울특별시 양천구 오목로 149 (신정동)7943파리바게뜨(신정역점)2021-02-23 16:14:35U2021-02-25 02:40:00.0제과점영업187017.21531446972.628283제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N122.4<NA><NA><NA>
931400003140000-121-1984-0604819840330<NA>3폐업2폐업20191122<NA><NA><NA>022643227670.0158807서울특별시 양천구 목동 506-1번지 지상1층서울특별시 양천구 목동중앙본로 123, 지상1층 (목동)7948뚜레쥬르2019-11-22 14:54:40U2019-11-24 02:40:00.0제과점영업188571.326971449374.388365제과점영업11주택가주변지도상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N70.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
60431400003140000-121-2023-000232023-11-23<NA>3폐업2폐업2023-11-30<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998꿀넹쿠키 연남점2023-12-01 04:15:08U2022-11-02 00:03:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60531400003140000-121-2023-000242023-12-19<NA>3폐업2폐업2023-12-31<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998(주)현대그린푸드 베즐리 베이커리2024-01-01 04:15:09U2023-12-01 00:03:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60631400003140000-121-2023-000252023-12-20<NA>3폐업2폐업2023-12-25<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998해피베어데이2023-12-26 04:15:09U2022-11-01 22:08:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60731400003140000-121-2024-000012024-01-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.8158-806서울특별시 양천구 목동 406-30 오목교역서울특별시 양천구 오목로 지하 342, 오목교역 지하2층 204호 (목동)8006BGT호두단팥빵 오목교점2024-01-03 10:16:04I2023-12-01 00:05:00.0제과점영업188793.151633446945.537493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60831400003140000-121-2024-000022024-01-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.4158-827서울특별시 양천구 신월동 104-12서울특별시 양천구 곰달래로13길 58, 1층 1호 (신월동)7918아르테2024-01-10 14:58:01I2023-11-30 23:03:00.0제과점영업185328.724762448077.22778<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60931400003140000-121-2024-000032024-02-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.0158-806서울특별시 양천구 목동 406-30 오목교역 110호서울특별시 양천구 오목로 지하 342, 오목교역 지하1층 110호 (목동)8006맛빵시대2024-02-22 10:52:01I2023-12-01 22:04:00.0제과점영업188793.151633446945.537493<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61031400003140000-121-2024-000042024-02-29<NA>3폐업2폐업2024-03-07<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998농업회사법인 흥만소 주식회사2024-03-08 04:15:09U2023-12-02 23:00:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61131400003140000-121-2024-000052024-03-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>57.42158-806서울특별시 양천구 목동 406-28 목동 슬로우스퀘어 107호서울특별시 양천구 오목로 345, 목동 슬로우스퀘어 107호 (목동)7999루브레드 오목교역점2024-03-22 10:16:45I2023-12-02 22:04:00.0제과점영업188951.756198446969.38865<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61231400003140000-121-2024-000062024-04-18<NA>3폐업2폐업2024-05-02<NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998쓰임(see-im)2024-05-03 04:15:09U2023-12-05 00:05:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61331400003140000-121-2024-000072024-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 916 현대하이페리온서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)7998당고집2024-05-08 13:13:05I2023-12-04 23:00:00.0제과점영업188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>