Overview

Dataset statistics

Number of variables44
Number of observations4141
Missing cells57780
Missing cells (%)31.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory379.0 B

Variable types

Categorical16
Text6
DateTime4
Unsupported10
Numeric7
Boolean1

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),위생업태명,남성종사자수,여성종사자수,영업장주변구분명,등급구분명,급수시설구분명,총인원,본사종업원수,공장사무직종업원수,공장판매직종업원수,공장생산직종업원수,건물소유구분명,보증액,월세액,다중이용업소여부,시설총규모,전통업소지정번호,전통업소주된음식,홈페이지
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18091/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (69.5%)Imbalance
여성종사자수 is highly imbalanced (69.5%)Imbalance
급수시설구분명 is highly imbalanced (88.9%)Imbalance
총인원 is highly imbalanced (69.9%)Imbalance
공장판매직종업원수 is highly imbalanced (56.7%)Imbalance
인허가취소일자 has 4141 (100.0%) missing valuesMissing
폐업일자 has 985 (23.8%) missing valuesMissing
휴업시작일자 has 4141 (100.0%) missing valuesMissing
휴업종료일자 has 4141 (100.0%) missing valuesMissing
재개업일자 has 4141 (100.0%) missing valuesMissing
전화번호 has 2297 (55.5%) missing valuesMissing
소재지면적 has 1640 (39.6%) missing valuesMissing
도로명주소 has 1002 (24.2%) missing valuesMissing
도로명우편번호 has 1036 (25.0%) missing valuesMissing
업태구분명 has 4141 (100.0%) missing valuesMissing
좌표정보(X) has 46 (1.1%) missing valuesMissing
좌표정보(Y) has 46 (1.1%) missing valuesMissing
영업장주변구분명 has 4141 (100.0%) missing valuesMissing
등급구분명 has 4141 (100.0%) missing valuesMissing
보증액 has 3569 (86.2%) missing valuesMissing
월세액 has 3569 (86.2%) missing valuesMissing
다중이용업소여부 has 1089 (26.3%) missing valuesMissing
시설총규모 has 1089 (26.3%) missing valuesMissing
전통업소지정번호 has 4141 (100.0%) missing valuesMissing
전통업소주된음식 has 4141 (100.0%) missing valuesMissing
홈페이지 has 4141 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 51.68184869)Skewed
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
영업장주변구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
등급구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 845 (20.4%) zerosZeros
보증액 has 522 (12.6%) zerosZeros
월세액 has 523 (12.6%) zerosZeros
시설총규모 has 2718 (65.6%) zerosZeros

Reproduction

Analysis started2024-05-11 04:42:15.716183
Analysis finished2024-05-11 04:42:19.710032
Duration3.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
3140000
4141 

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 4141
100.0%

Length

2024-05-11T04:42:19.868050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:20.142290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 4141
100.0%

관리번호
Text

UNIQUE 

Distinct4141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
2024-05-11T04:42:20.623883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters91102
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

Unique4141 ?
Unique (%)100.0%

Sample

1st row3140000-134-2004-00001
2nd row3140000-134-2004-00002
3rd row3140000-134-2004-00003
4th row3140000-134-2004-00004
5th row3140000-134-2004-00005
ValueCountFrequency (%)
3140000-134-2004-00001 1
 
< 0.1%
3140000-134-2018-00096 1
 
< 0.1%
3140000-134-2018-00066 1
 
< 0.1%
3140000-134-2018-00080 1
 
< 0.1%
3140000-134-2018-00067 1
 
< 0.1%
3140000-134-2018-00068 1
 
< 0.1%
3140000-134-2018-00069 1
 
< 0.1%
3140000-134-2018-00070 1
 
< 0.1%
3140000-134-2018-00071 1
 
< 0.1%
3140000-134-2018-00072 1
 
< 0.1%
Other values (4131) 4131
99.8%
2024-05-11T04:42:21.632034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33650
36.9%
1 12830
 
14.1%
- 12423
 
13.6%
4 9831
 
10.8%
3 9815
 
10.8%
2 7213
 
7.9%
9 1148
 
1.3%
5 1116
 
1.2%
6 1066
 
1.2%
8 1033
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78679
86.4%
Dash Punctuation 12423
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33650
42.8%
1 12830
 
16.3%
4 9831
 
12.5%
3 9815
 
12.5%
2 7213
 
9.2%
9 1148
 
1.5%
5 1116
 
1.4%
6 1066
 
1.4%
8 1033
 
1.3%
7 977
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 12423
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 91102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33650
36.9%
1 12830
 
14.1%
- 12423
 
13.6%
4 9831
 
10.8%
3 9815
 
10.8%
2 7213
 
7.9%
9 1148
 
1.3%
5 1116
 
1.2%
6 1066
 
1.2%
8 1033
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 91102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33650
36.9%
1 12830
 
14.1%
- 12423
 
13.6%
4 9831
 
10.8%
3 9815
 
10.8%
2 7213
 
7.9%
9 1148
 
1.3%
5 1116
 
1.2%
6 1066
 
1.2%
8 1033
 
1.1%

인허가일자
Date

Distinct2505
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
Minimum2004-03-05 00:00:00
Maximum2024-05-07 00:00:00
2024-05-11T04:42:22.109089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:42:22.637233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
3
3156 
1
985 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 3156
76.2%
1 985
 
23.8%

Length

2024-05-11T04:42:23.156066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:23.543638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3156
76.2%
1 985
 
23.8%

영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
폐업
3156 
영업/정상
985 

Length

Max length5
Median length2
Mean length2.7135957
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3156
76.2%
영업/정상 985
 
23.8%

Length

2024-05-11T04:42:23.955452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:24.348961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3156
76.2%
영업/정상 985
 
23.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
2
3156 
1
985 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 3156
76.2%
1 985
 
23.8%

Length

2024-05-11T04:42:24.958788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:25.284701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 3156
76.2%
1 985
 
23.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
폐업
3156 
영업
985 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 3156
76.2%
영업 985
 
23.8%

Length

2024-05-11T04:42:25.718667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:26.241745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 3156
76.2%
영업 985
 
23.8%

폐업일자
Date

MISSING 

Distinct1910
Distinct (%)60.5%
Missing985
Missing (%)23.8%
Memory size32.5 KiB
Minimum2004-05-28 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T04:42:26.715165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:42:27.171533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

전화번호
Text

MISSING 

Distinct1745
Distinct (%)94.6%
Missing2297
Missing (%)55.5%
Memory size32.5 KiB
2024-05-11T04:42:27.794105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.231562
Min length2

Characters and Unicode

Total characters18867
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

Unique1681 ?
Unique (%)91.2%

Sample

1st row0226442387
2nd row0221685252
3rd row0226965876
4th row02 67161234
5th row0226998174
ValueCountFrequency (%)
02 433
 
17.9%
070 49
 
2.0%
0226916566 16
 
0.7%
031 12
 
0.5%
26916566 12
 
0.5%
26985410 9
 
0.4%
032 6
 
0.2%
0226518216 3
 
0.1%
20621053 3
 
0.1%
0232848112 3
 
0.1%
Other values (1790) 1867
77.4%
2024-05-11T04:42:29.046526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3855
20.4%
0 3187
16.9%
6 2464
13.1%
5 1397
 
7.4%
4 1363
 
7.2%
1 1184
 
6.3%
3 1147
 
6.1%
7 1137
 
6.0%
8 1099
 
5.8%
9 1071
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17904
94.9%
Space Separator 963
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3855
21.5%
0 3187
17.8%
6 2464
13.8%
5 1397
 
7.8%
4 1363
 
7.6%
1 1184
 
6.6%
3 1147
 
6.4%
7 1137
 
6.4%
8 1099
 
6.1%
9 1071
 
6.0%
Space Separator
ValueCountFrequency (%)
963
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18867
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3855
20.4%
0 3187
16.9%
6 2464
13.1%
5 1397
 
7.4%
4 1363
 
7.2%
1 1184
 
6.3%
3 1147
 
6.1%
7 1137
 
6.0%
8 1099
 
5.8%
9 1071
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3855
20.4%
0 3187
16.9%
6 2464
13.1%
5 1397
 
7.4%
4 1363
 
7.2%
1 1184
 
6.3%
3 1147
 
6.1%
7 1137
 
6.0%
8 1099
 
5.8%
9 1071
 
5.7%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct592
Distinct (%)23.7%
Missing1640
Missing (%)39.6%
Infinite0
Infinite (%)0.0%
Mean33.559324
Minimum0
Maximum892
Zeros845
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:29.620445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q333
95-th percentile150
Maximum892
Range892
Interquartile range (IQR)33

Descriptive statistics

Standard deviation69.251785
Coefficient of variation (CV)2.0635632
Kurtosis37.758967
Mean33.559324
Median Absolute Deviation (MAD)6
Skewness4.9196616
Sum83931.87
Variance4795.8097
MonotonicityNot monotonic
2024-05-11T04:42:30.137232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 845
20.4%
3.3 312
 
7.5%
33.0 68
 
1.6%
6.6 64
 
1.5%
3.0 42
 
1.0%
30.0 28
 
0.7%
10.0 25
 
0.6%
16.5 20
 
0.5%
26.4 19
 
0.5%
9.9 19
 
0.5%
Other values (582) 1059
25.6%
(Missing) 1640
39.6%
ValueCountFrequency (%)
0.0 845
20.4%
1.0 9
 
0.2%
1.05 1
 
< 0.1%
1.1 1
 
< 0.1%
1.5 1
 
< 0.1%
1.65 1
 
< 0.1%
1.75 1
 
< 0.1%
1.8 1
 
< 0.1%
2.0 6
 
0.1%
3.0 42
 
1.0%
ValueCountFrequency (%)
892.0 1
< 0.1%
836.0 1
< 0.1%
825.0 1
< 0.1%
748.34 1
< 0.1%
594.0 1
< 0.1%
522.68 1
< 0.1%
495.0 2
< 0.1%
492.1 2
< 0.1%
490.0 1
< 0.1%
458.0 1
< 0.1%

소재지우편번호
Text

Distinct245
Distinct (%)5.9%
Missing1
Missing (%)< 0.1%
Memory size32.5 KiB
2024-05-11T04:42:31.069988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1678744
Min length6

Characters and Unicode

Total characters25535
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

Unique35 ?
Unique (%)0.8%

Sample

1st row158814
2nd row158719
3rd row158859
4th row158-822
5th row158859
ValueCountFrequency (%)
158050 312
 
7.5%
158070 209
 
5.0%
158857 176
 
4.3%
158860 147
 
3.6%
158811 115
 
2.8%
158806 100
 
2.4%
158859 81
 
2.0%
158849 74
 
1.8%
158877 71
 
1.7%
158827 68
 
1.6%
Other values (235) 2787
67.3%
2024-05-11T04:42:32.699154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 7759
30.4%
5 5313
20.8%
1 5057
19.8%
0 2128
 
8.3%
7 1371
 
5.4%
6 817
 
3.2%
- 695
 
2.7%
2 673
 
2.6%
4 654
 
2.6%
9 572
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24840
97.3%
Dash Punctuation 695
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 7759
31.2%
5 5313
21.4%
1 5057
20.4%
0 2128
 
8.6%
7 1371
 
5.5%
6 817
 
3.3%
2 673
 
2.7%
4 654
 
2.6%
9 572
 
2.3%
3 496
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 695
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25535
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 7759
30.4%
5 5313
20.8%
1 5057
19.8%
0 2128
 
8.3%
7 1371
 
5.4%
6 817
 
3.2%
- 695
 
2.7%
2 673
 
2.6%
4 654
 
2.6%
9 572
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25535
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 7759
30.4%
5 5313
20.8%
1 5057
19.8%
0 2128
 
8.3%
7 1371
 
5.4%
6 817
 
3.2%
- 695
 
2.7%
2 673
 
2.6%
4 654
 
2.6%
9 572
 
2.2%

지번주소
Text

Distinct2218
Distinct (%)53.6%
Missing1
Missing (%)< 0.1%
Memory size32.5 KiB
2024-05-11T04:42:33.632646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length44
Mean length28.87657
Min length16

Characters and Unicode

Total characters119549
Distinct characters437
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1824 ?
Unique (%)44.1%

Sample

1st row서울특별시 양천구 목동 ***-*번지 (지상*층)
2nd row서울특별시 양천구 목동 ***-**번지 서울이동통신빌딩(**층)
3rd row서울특별시 양천구 신정동 ***-**번지 (*층)
4th row서울특별시 양천구 신월동 **
5th row서울특별시 양천구 신정동 ***-*번지 클레버타워 ***호
ValueCountFrequency (%)
서울특별시 4139
18.3%
양천구 4139
18.3%
번지 2569
11.4%
목동 1691
7.5%
1549
 
6.9%
신정동 1529
 
6.8%
호 1318
 
5.8%
신월동 973
 
4.3%
층 887
 
3.9%
동 332
 
1.5%
Other values (1438) 3459
15.3%
2024-05-11T04:42:35.516639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 25525
21.4%
20738
17.3%
동 5370
 
4.5%
시 4383
 
3.7%
양 4213
 
3.5%
천 4187
 
3.5%
서 4174
 
3.5%
구 4167
 
3.5%
울 4149
 
3.5%
별 4139
 
3.5%
Other values (427) 38504
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68457
57.3%
Other Punctuation 25607
 
21.4%
Space Separator 20738
 
17.3%
Dash Punctuation 3248
 
2.7%
Decimal Number 581
 
0.5%
Open Punctuation 300
 
0.3%
Close Punctuation 299
 
0.3%
Uppercase Letter 291
 
0.2%
Lowercase Letter 18
 
< 0.1%
Math Symbol 7
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5370
 
7.8%
시 4383
 
6.4%
양 4213
 
6.2%
천 4187
 
6.1%
서 4174
 
6.1%
구 4167
 
6.1%
울 4149
 
6.1%
별 4139
 
6.0%
특 4139
 
6.0%
지 3474
 
5.1%
Other values (372) 26062
38.1%
Uppercase Letter
ValueCountFrequency (%)
B 111
38.1%
A 55
18.9%
S 25
 
8.6%
C 22
 
7.6%
D 11
 
3.8%
M 9
 
3.1%
O 8
 
2.7%
K 8
 
2.7%
L 6
 
2.1%
E 5
 
1.7%
Other values (13) 31
 
10.7%
Decimal Number
ValueCountFrequency (%)
1 141
24.3%
2 72
12.4%
3 66
11.4%
0 61
10.5%
9 49
 
8.4%
6 45
 
7.7%
7 43
 
7.4%
4 43
 
7.4%
5 39
 
6.7%
8 22
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
l 4
22.2%
e 3
16.7%
a 3
16.7%
c 3
16.7%
s 1
 
5.6%
r 1
 
5.6%
d 1
 
5.6%
h 1
 
5.6%
b 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
* 25525
99.7%
, 57
 
0.2%
@ 12
 
< 0.1%
/ 7
 
< 0.1%
. 4
 
< 0.1%
& 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
20738
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3248
100.0%
Open Punctuation
ValueCountFrequency (%)
( 300
100.0%
Close Punctuation
ValueCountFrequency (%)
) 299
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 68457
57.3%
Common 50781
42.5%
Latin 311
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5370
 
7.8%
시 4383
 
6.4%
양 4213
 
6.2%
천 4187
 
6.1%
서 4174
 
6.1%
구 4167
 
6.1%
울 4149
 
6.1%
별 4139
 
6.0%
특 4139
 
6.0%
지 3474
 
5.1%
Other values (372) 26062
38.1%
Latin
ValueCountFrequency (%)
B 111
35.7%
A 55
17.7%
S 25
 
8.0%
C 22
 
7.1%
D 11
 
3.5%
M 9
 
2.9%
O 8
 
2.6%
K 8
 
2.6%
L 6
 
1.9%
E 5
 
1.6%
Other values (23) 51
16.4%
Common
ValueCountFrequency (%)
* 25525
50.3%
20738
40.8%
- 3248
 
6.4%
( 300
 
0.6%
) 299
 
0.6%
1 141
 
0.3%
2 72
 
0.1%
3 66
 
0.1%
0 61
 
0.1%
, 57
 
0.1%
Other values (12) 274
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68457
57.3%
ASCII 51090
42.7%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 25525
50.0%
20738
40.6%
- 3248
 
6.4%
( 300
 
0.6%
) 299
 
0.6%
1 141
 
0.3%
B 111
 
0.2%
2 72
 
0.1%
3 66
 
0.1%
0 61
 
0.1%
Other values (44) 529
 
1.0%
Hangul
ValueCountFrequency (%)
동 5370
 
7.8%
시 4383
 
6.4%
양 4213
 
6.2%
천 4187
 
6.1%
서 4174
 
6.1%
구 4167
 
6.1%
울 4149
 
6.1%
별 4139
 
6.0%
특 4139
 
6.0%
지 3474
 
5.1%
Other values (372) 26062
38.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명주소
Text

MISSING 

Distinct2204
Distinct (%)70.2%
Missing1002
Missing (%)24.2%
Memory size32.5 KiB
2024-05-11T04:42:36.198476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51
Mean length36.552405
Min length20

Characters and Unicode

Total characters114738
Distinct characters419
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

Unique1803 ?
Unique (%)57.4%

Sample

1st row서울특별시 양천구 중앙로 ***-* (신정동,(*층))
2nd row서울특별시 양천구 화곡로 ** (신월동)
3rd row서울특별시 양천구 등촌로 * (목동)
4th row서울특별시 양천구 신월로 ** (신월동,시영상가지하)
5th row서울특별시 양천구 목동동로 ***, 현대**타워 ****호 (목동)
ValueCountFrequency (%)
서울특별시 3138
14.6%
양천구 3138
14.6%
3119
14.5%
호 1672
 
7.8%
목동 1103
 
5.1%
신정동 1008
 
4.7%
층 925
 
4.3%
신월동 690
 
3.2%
동 558
 
2.6%
목동동로 334
 
1.5%
Other values (1451) 5873
27.2%
2024-05-11T04:42:37.356590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 19198
16.7%
18426
 
16.1%
동 6296
 
5.5%
, 4285
 
3.7%
목 3590
 
3.1%
서 3494
 
3.0%
시 3354
 
2.9%
양 3290
 
2.9%
( 3246
 
2.8%
) 3245
 
2.8%
Other values (409) 46314
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64711
56.4%
Other Punctuation 23492
 
20.5%
Space Separator 18426
 
16.1%
Open Punctuation 3246
 
2.8%
Close Punctuation 3245
 
2.8%
Decimal Number 780
 
0.7%
Dash Punctuation 547
 
0.5%
Uppercase Letter 268
 
0.2%
Lowercase Letter 17
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6296
 
9.7%
목 3590
 
5.5%
서 3494
 
5.4%
시 3354
 
5.2%
양 3290
 
5.1%
로 3213
 
5.0%
천 3191
 
4.9%
구 3161
 
4.9%
울 3143
 
4.9%
별 3139
 
4.9%
Other values (355) 28840
44.6%
Uppercase Letter
ValueCountFrequency (%)
B 111
41.4%
A 39
 
14.6%
S 26
 
9.7%
C 20
 
7.5%
M 9
 
3.4%
O 8
 
3.0%
K 8
 
3.0%
L 6
 
2.2%
T 5
 
1.9%
I 5
 
1.9%
Other values (13) 31
 
11.6%
Decimal Number
ValueCountFrequency (%)
1 204
26.2%
0 142
18.2%
2 116
14.9%
3 72
 
9.2%
6 58
 
7.4%
4 56
 
7.2%
5 45
 
5.8%
7 43
 
5.5%
9 25
 
3.2%
8 19
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
l 4
23.5%
a 3
17.6%
b 3
17.6%
e 2
11.8%
s 1
 
5.9%
r 1
 
5.9%
d 1
 
5.9%
h 1
 
5.9%
c 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
* 19198
81.7%
, 4285
 
18.2%
@ 3
 
< 0.1%
. 3
 
< 0.1%
& 2
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
18426
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3246
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 547
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64711
56.4%
Common 49740
43.4%
Latin 287
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6296
 
9.7%
목 3590
 
5.5%
서 3494
 
5.4%
시 3354
 
5.2%
양 3290
 
5.1%
로 3213
 
5.0%
천 3191
 
4.9%
구 3161
 
4.9%
울 3143
 
4.9%
별 3139
 
4.9%
Other values (355) 28840
44.6%
Latin
ValueCountFrequency (%)
B 111
38.7%
A 39
 
13.6%
S 26
 
9.1%
C 20
 
7.0%
M 9
 
3.1%
O 8
 
2.8%
K 8
 
2.8%
L 6
 
2.1%
T 5
 
1.7%
I 5
 
1.7%
Other values (23) 50
17.4%
Common
ValueCountFrequency (%)
* 19198
38.6%
18426
37.0%
, 4285
 
8.6%
( 3246
 
6.5%
) 3245
 
6.5%
- 547
 
1.1%
1 204
 
0.4%
0 142
 
0.3%
2 116
 
0.2%
3 72
 
0.1%
Other values (11) 259
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64711
56.4%
ASCII 50025
43.6%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 19198
38.4%
18426
36.8%
, 4285
 
8.6%
( 3246
 
6.5%
) 3245
 
6.5%
- 547
 
1.1%
1 204
 
0.4%
0 142
 
0.3%
2 116
 
0.2%
B 111
 
0.2%
Other values (43) 505
 
1.0%
Hangul
ValueCountFrequency (%)
동 6296
 
9.7%
목 3590
 
5.5%
서 3494
 
5.4%
시 3354
 
5.2%
양 3290
 
5.1%
로 3213
 
5.0%
천 3191
 
4.9%
구 3161
 
4.9%
울 3143
 
4.9%
별 3139
 
4.9%
Other values (355) 28840
44.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct202
Distinct (%)6.5%
Missing1036
Missing (%)25.0%
Infinite0
Infinite (%)0.0%
Mean7998.5253
Minimum7900
Maximum21344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:38.047173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7900
5-th percentile7912
Q17948
median7993
Q38028
95-th percentile8096
Maximum21344
Range13444
Interquartile range (IQR)80

Descriptive statistics

Standard deviation245.66522
Coefficient of variation (CV)0.030713814
Kurtosis2808.1212
Mean7998.5253
Median Absolute Deviation (MAD)41
Skewness51.681849
Sum24835421
Variance60351.398
MonotonicityNot monotonic
2024-05-11T04:42:38.559996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7945 98
 
2.4%
7997 91
 
2.2%
7946 65
 
1.6%
7998 61
 
1.5%
7983 60
 
1.4%
7938 56
 
1.4%
7960 44
 
1.1%
8022 42
 
1.0%
8023 40
 
1.0%
8007 36
 
0.9%
Other values (192) 2512
60.7%
(Missing) 1036
25.0%
ValueCountFrequency (%)
7900 12
0.3%
7901 2
 
< 0.1%
7902 18
0.4%
7903 22
0.5%
7904 20
0.5%
7905 15
0.4%
7906 11
0.3%
7907 6
 
0.1%
7908 3
 
0.1%
7909 23
0.6%
ValueCountFrequency (%)
21344 1
 
< 0.1%
8111 2
 
< 0.1%
8110 1
 
< 0.1%
8109 7
 
0.2%
8108 6
 
0.1%
8107 13
0.3%
8106 17
0.4%
8105 5
 
0.1%
8104 28
0.7%
8102 2
 
< 0.1%

사업장명
Text

Distinct3734
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
2024-05-11T04:42:39.371835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length6.8903646
Min length1

Characters and Unicode

Total characters28533
Distinct characters801
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

Unique3557 ?
Unique (%)85.9%

Sample

1st row(주)비바스포츠
2nd row(주)우리홈쇼핑
3rd row남양알로에
4th row(주)이마트 신월점
5th row서부에너지
ValueCountFrequency (%)
주식회사 73
 
1.5%
허브다이어트 50
 
1.0%
목동점 49
 
1.0%
아모레카운셀러 41
 
0.8%
인셀덤 29
 
0.6%
하이리빙 27
 
0.5%
세븐일레븐 24
 
0.5%
한국암웨이 20
 
0.4%
메디팜생활건강 19
 
0.4%
다이어트 18
 
0.4%
Other values (4000) 4593
92.9%
2024-05-11T04:42:40.868117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1226
 
4.3%
803
 
2.8%
스 778
 
2.7%
) 613
 
2.1%
( 610
 
2.1%
리 580
 
2.0%
점 554
 
1.9%
주 529
 
1.9%
트 483
 
1.7%
아 426
 
1.5%
Other values (791) 21931
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24534
86.0%
Uppercase Letter 850
 
3.0%
Space Separator 803
 
2.8%
Lowercase Letter 673
 
2.4%
Close Punctuation 613
 
2.1%
Open Punctuation 610
 
2.1%
Decimal Number 358
 
1.3%
Other Punctuation 64
 
0.2%
Dash Punctuation 21
 
0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1226
 
5.0%
스 778
 
3.2%
리 580
 
2.4%
점 554
 
2.3%
주 529
 
2.2%
트 483
 
2.0%
아 426
 
1.7%
브 402
 
1.6%
어 395
 
1.6%
동 387
 
1.6%
Other values (714) 18774
76.5%
Uppercase Letter
ValueCountFrequency (%)
S 130
15.3%
G 93
 
10.9%
C 50
 
5.9%
A 46
 
5.4%
E 41
 
4.8%
I 41
 
4.8%
O 39
 
4.6%
N 37
 
4.4%
B 37
 
4.4%
T 36
 
4.2%
Other values (16) 300
35.3%
Lowercase Letter
ValueCountFrequency (%)
e 86
12.8%
o 61
 
9.1%
a 56
 
8.3%
i 54
 
8.0%
l 54
 
8.0%
n 42
 
6.2%
r 40
 
5.9%
t 37
 
5.5%
d 25
 
3.7%
u 25
 
3.7%
Other values (14) 193
28.7%
Decimal Number
ValueCountFrequency (%)
2 114
31.8%
5 87
24.3%
4 39
 
10.9%
1 38
 
10.6%
3 29
 
8.1%
6 18
 
5.0%
0 17
 
4.7%
9 7
 
2.0%
7 6
 
1.7%
8 3
 
0.8%
Other Punctuation
ValueCountFrequency (%)
& 29
45.3%
. 25
39.1%
' 3
 
4.7%
/ 2
 
3.1%
? 2
 
3.1%
, 1
 
1.6%
# 1
 
1.6%
! 1
 
1.6%
Math Symbol
ValueCountFrequency (%)
+ 2
33.3%
= 2
33.3%
< 1
16.7%
> 1
16.7%
Space Separator
ValueCountFrequency (%)
803
100.0%
Close Punctuation
ValueCountFrequency (%)
) 613
100.0%
Open Punctuation
ValueCountFrequency (%)
( 610
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24531
86.0%
Common 2476
 
8.7%
Latin 1523
 
5.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1226
 
5.0%
스 778
 
3.2%
리 580
 
2.4%
점 554
 
2.3%
주 529
 
2.2%
트 483
 
2.0%
아 426
 
1.7%
브 402
 
1.6%
어 395
 
1.6%
동 387
 
1.6%
Other values (712) 18771
76.5%
Latin
ValueCountFrequency (%)
S 130
 
8.5%
G 93
 
6.1%
e 86
 
5.6%
o 61
 
4.0%
a 56
 
3.7%
i 54
 
3.5%
l 54
 
3.5%
C 50
 
3.3%
A 46
 
3.0%
n 42
 
2.8%
Other values (40) 851
55.9%
Common
ValueCountFrequency (%)
803
32.4%
) 613
24.8%
( 610
24.6%
2 114
 
4.6%
5 87
 
3.5%
4 39
 
1.6%
1 38
 
1.5%
& 29
 
1.2%
3 29
 
1.2%
. 25
 
1.0%
Other values (17) 89
 
3.6%
Han
ValueCountFrequency (%)
美 2
66.7%
眞 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24531
86.0%
ASCII 3999
 
14.0%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1226
 
5.0%
스 778
 
3.2%
리 580
 
2.4%
점 554
 
2.3%
주 529
 
2.2%
트 483
 
2.0%
아 426
 
1.7%
브 402
 
1.6%
어 395
 
1.6%
동 387
 
1.6%
Other values (712) 18771
76.5%
ASCII
ValueCountFrequency (%)
803
20.1%
) 613
15.3%
( 610
15.3%
S 130
 
3.3%
2 114
 
2.9%
G 93
 
2.3%
5 87
 
2.2%
e 86
 
2.2%
o 61
 
1.5%
a 56
 
1.4%
Other values (67) 1346
33.7%
CJK
ValueCountFrequency (%)
美 2
66.7%
眞 1
33.3%

최종수정일자
Date

Distinct3878
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
Minimum2004-04-29 00:00:00
Maximum2024-05-09 17:05:18
2024-05-11T04:42:41.380434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:42:41.852441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
I
2859 
U
1282 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2859
69.0%
U 1282
31.0%

Length

2024-05-11T04:42:42.344460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:42.813594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2859
69.0%
u 1282
31.0%

데이터갱신일자
Date

Distinct948
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T04:42:43.178161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T04:42:43.648610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1935
Distinct (%)47.3%
Missing46
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean187475.81
Minimum176534.72
Maximum189878.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:44.209132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176534.72
5-th percentile184971.29
Q1186370.87
median187889.32
Q3188581.96
95-th percentile189151.21
Maximum189878.41
Range13343.687
Interquartile range (IQR)2211.0942

Descriptive statistics

Standard deviation1372.6314
Coefficient of variation (CV)0.0073216456
Kurtosis0.13658003
Mean187475.81
Median Absolute Deviation (MAD)870.28638
Skewness-0.72201608
Sum7.6771342 × 108
Variance1884117
MonotonicityNot monotonic
2024-05-11T04:42:45.125533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188953.066831076 75
 
1.8%
188884.075622342 73
 
1.8%
187734.804380866 65
 
1.6%
189151.208015925 44
 
1.1%
188584.345447275 39
 
0.9%
188467.215363052 32
 
0.8%
185263.865468449 30
 
0.7%
187995.261631804 29
 
0.7%
188965.738829492 28
 
0.7%
188977.171050288 27
 
0.7%
Other values (1925) 3653
88.2%
(Missing) 46
 
1.1%
ValueCountFrequency (%)
176534.72 1
 
< 0.1%
184242.730019702 4
0.1%
184320.196338406 1
 
< 0.1%
184330.402293717 1
 
< 0.1%
184359.248011837 1
 
< 0.1%
184372.497302648 1
 
< 0.1%
184373.07604881 3
0.1%
184383.170672011 1
 
< 0.1%
184388.747620342 1
 
< 0.1%
184404.050073915 1
 
< 0.1%
ValueCountFrequency (%)
189878.40729119 9
0.2%
189755.541308355 2
 
< 0.1%
189749.776358917 17
0.4%
189743.464254868 1
 
< 0.1%
189676.766585898 2
 
< 0.1%
189645.577035228 4
 
0.1%
189643.735000001 1
 
< 0.1%
189519.862506193 3
 
0.1%
189512.045139098 2
 
< 0.1%
189508.199599752 13
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1935
Distinct (%)47.3%
Missing46
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean447300.94
Minimum444831.85
Maximum449843.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:45.731388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444831.85
5-th percentile445602
Q1446540.72
median447125.5
Q3448196.04
95-th percentile449366.53
Maximum449843.2
Range5011.3552
Interquartile range (IQR)1655.3143

Descriptive statistics

Standard deviation1117.6783
Coefficient of variation (CV)0.0024987166
Kurtosis-0.62939384
Mean447300.94
Median Absolute Deviation (MAD)798.40987
Skewness0.32839074
Sum1.8316974 × 109
Variance1249204.8
MonotonicityNot monotonic
2024-05-11T04:42:46.391265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447333.569187997 75
 
1.8%
447186.888604306 73
 
1.8%
447125.503353306 65
 
1.6%
448200.067716589 44
 
1.1%
447255.070457495 39
 
0.9%
446003.941216623 32
 
0.8%
446199.492398091 30
 
0.7%
445782.650926649 29
 
0.7%
448365.713974147 28
 
0.7%
447466.355031447 27
 
0.7%
Other values (1925) 3653
88.2%
(Missing) 46
 
1.1%
ValueCountFrequency (%)
444831.84775875 1
 
< 0.1%
444834.394155811 1
 
< 0.1%
444854.165988454 2
 
< 0.1%
444911.609710795 7
0.2%
444982.894549103 1
 
< 0.1%
445001.620672229 5
0.1%
445006.611450798 1
 
< 0.1%
445039.928375227 1
 
< 0.1%
445071.1 1
 
< 0.1%
445072.698531887 1
 
< 0.1%
ValueCountFrequency (%)
449843.203005652 1
 
< 0.1%
449833.140237863 2
< 0.1%
449821.719712552 1
 
< 0.1%
449791.902771997 1
 
< 0.1%
449789.613381329 4
0.1%
449783.944486969 1
 
< 0.1%
449783.451870726 2
< 0.1%
449774.340142666 3
0.1%
449768.831273316 1
 
< 0.1%
449767.441786782 4
0.1%

위생업태명
Categorical

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
영업장판매
1489 
<NA>
1089 
전자상거래(통신판매업)
585 
통신판매
409 
방문판매
364 
Other values (5)
205 

Length

Max length14
Median length12
Mean length5.5525235
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row영업장판매
2nd row통신판매
3rd row방문판매
4th row<NA>
5th row방문판매

Common Values

ValueCountFrequency (%)
영업장판매 1489
36.0%
<NA> 1089
26.3%
전자상거래(통신판매업) 585
 
14.1%
통신판매 409
 
9.9%
방문판매 364
 
8.8%
다단계판매 185
 
4.5%
도매업(유통) 9
 
0.2%
전화권유판매 7
 
0.2%
기타 건강기능식품일반판매업 3
 
0.1%
기타(복합 등) 1
 
< 0.1%

Length

2024-05-11T04:42:47.046295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:47.600121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업장판매 1489
35.9%
na 1089
26.3%
전자상거래(통신판매업 585
 
14.1%
통신판매 409
 
9.9%
방문판매 364
 
8.8%
다단계판매 185
 
4.5%
도매업(유통 9
 
0.2%
전화권유판매 7
 
0.2%
기타 3
 
0.1%
건강기능식품일반판매업 3
 
0.1%
Other values (2) 2
 
< 0.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
3916 
0
 
225

Length

Max length4
Median length4
Mean length3.8369959
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> 3916
94.6%
0 225
 
5.4%

Length

2024-05-11T04:42:48.270225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:48.733585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3916
94.6%
0 225
 
5.4%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
3916 
0
 
225

Length

Max length4
Median length4
Mean length3.8369959
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> 3916
94.6%
0 225
 
5.4%

Length

2024-05-11T04:42:49.164286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:49.524988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3916
94.6%
0 225
 
5.4%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
4080 
상수도전용
 
61

Length

Max length5
Median length4
Mean length4.0147307
Min length4

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> 4080
98.5%
상수도전용 61
 
1.5%

Length

2024-05-11T04:42:49.957311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:50.321840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4080
98.5%
상수도전용 61
 
1.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
3920 
0
 
221

Length

Max length4
Median length4
Mean length3.8398937
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> 3920
94.7%
0 221
 
5.3%

Length

2024-05-11T04:42:50.821447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:51.298667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3920
94.7%
0 221
 
5.3%

본사종업원수
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
2980 
0
1160 
2
 
1

Length

Max length4
Median length4
Mean length3.1588988
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2980
72.0%
0 1160
 
28.0%
2 1
 
< 0.1%

Length

2024-05-11T04:42:51.780200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:52.152123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2980
72.0%
0 1160
 
28.0%
2 1
 
< 0.1%

공장사무직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
2980 
0
1161 

Length

Max length4
Median length4
Mean length3.1588988
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2980
72.0%
0 1161
 
28.0%

Length

2024-05-11T04:42:52.696393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:53.129136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2980
72.0%
0 1161
 
28.0%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
2979 
0
1158 
1
 
2
2
 
2

Length

Max length4
Median length4
Mean length3.1581744
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2979
71.9%
0 1158
 
28.0%
1 2
 
< 0.1%
2 2
 
< 0.1%

Length

2024-05-11T04:42:53.614614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:54.084864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2979
71.9%
0 1158
 
28.0%
1 2
 
< 0.1%
2 2
 
< 0.1%

공장생산직종업원수
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
2980 
0
1161 

Length

Max length4
Median length4
Mean length3.1588988
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2980
72.0%
0 1161
 
28.0%

Length

2024-05-11T04:42:54.665249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:55.123993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2980
72.0%
0 1161
 
28.0%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.5 KiB
<NA>
2402 
임대
891 
자가
848 

Length

Max length4
Median length4
Mean length3.1601063
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2402
58.0%
임대 891
 
21.5%
자가 848
 
20.5%

Length

2024-05-11T04:42:55.607546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T04:42:56.015966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2402
58.0%
임대 891
 
21.5%
자가 848
 
20.5%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)3.0%
Missing3569
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean1611419.6
Minimum0
Maximum1 × 108
Zeros522
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:56.804446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10000000
Maximum1 × 108
Range1 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8933613.1
Coefficient of variation (CV)5.5439398
Kurtosis76.997954
Mean1611419.6
Median Absolute Deviation (MAD)0
Skewness8.3415009
Sum9.21732 × 108
Variance7.9809444 × 1013
MonotonicityNot monotonic
2024-05-11T04:42:57.220303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 522
 
12.6%
10000000 14
 
0.3%
5000000 10
 
0.2%
20000000 7
 
0.2%
100000000 2
 
< 0.1%
50000000 2
 
< 0.1%
1000000 2
 
< 0.1%
15000000 2
 
< 0.1%
4000000 2
 
< 0.1%
3000000 2
 
< 0.1%
Other values (7) 7
 
0.2%
(Missing) 3569
86.2%
ValueCountFrequency (%)
0 522
12.6%
700000 1
 
< 0.1%
1000000 2
 
< 0.1%
1400000 1
 
< 0.1%
3000000 2
 
< 0.1%
4000000 2
 
< 0.1%
5000000 10
 
0.2%
8000000 1
 
< 0.1%
10000000 14
 
0.3%
10632000 1
 
< 0.1%
ValueCountFrequency (%)
100000000 2
 
< 0.1%
80000000 1
 
< 0.1%
75000000 1
 
< 0.1%
70000000 1
 
< 0.1%
50000000 2
 
< 0.1%
20000000 7
0.2%
15000000 2
 
< 0.1%
10632000 1
 
< 0.1%
10000000 14
0.3%
8000000 1
 
< 0.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)4.4%
Missing3569
Missing (%)86.2%
Infinite0
Infinite (%)0.0%
Mean77386.958
Minimum0
Maximum4840000
Zeros523
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:57.665051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile500000
Maximum4840000
Range4840000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation384648.7
Coefficient of variation (CV)4.970459
Kurtosis88.405251
Mean77386.958
Median Absolute Deviation (MAD)0
Skewness8.5475554
Sum44265340
Variance1.4795462 × 1011
MonotonicityNot monotonic
2024-05-11T04:42:58.340794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 523
 
12.6%
300000 5
 
0.1%
1000000 5
 
0.1%
500000 4
 
0.1%
400000 3
 
0.1%
450000 3
 
0.1%
750000 3
 
0.1%
1500000 3
 
0.1%
800000 3
 
0.1%
550000 2
 
< 0.1%
Other values (15) 18
 
0.4%
(Missing) 3569
86.2%
ValueCountFrequency (%)
0 523
12.6%
300 1
 
< 0.1%
200000 2
 
< 0.1%
250000 1
 
< 0.1%
300000 5
 
0.1%
305040 1
 
< 0.1%
400000 3
 
0.1%
440000 1
 
< 0.1%
450000 3
 
0.1%
480000 1
 
< 0.1%
ValueCountFrequency (%)
4840000 1
 
< 0.1%
4500000 1
 
< 0.1%
3700000 1
 
< 0.1%
2600000 1
 
< 0.1%
1500000 3
0.1%
1300000 1
 
< 0.1%
1000000 5
0.1%
900000 1
 
< 0.1%
800000 3
0.1%
750000 3
0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1089
Missing (%)26.3%
Memory size8.2 KiB
False
3052 
(Missing)
1089 
ValueCountFrequency (%)
False 3052
73.7%
(Missing) 1089
 
26.3%
2024-05-11T04:42:58.820708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct170
Distinct (%)5.6%
Missing1089
Missing (%)26.3%
Infinite0
Infinite (%)0.0%
Mean5.5540662
Minimum0
Maximum495
Zeros2718
Zeros (%)65.6%
Negative0
Negative (%)0.0%
Memory size36.5 KiB
2024-05-11T04:42:59.378484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile29.7
Maximum495
Range495
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27.553847
Coefficient of variation (CV)4.9610224
Kurtosis106.16502
Mean5.5540662
Median Absolute Deviation (MAD)0
Skewness8.7370674
Sum16951.01
Variance759.21448
MonotonicityNot monotonic
2024-05-11T04:43:00.148011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2718
65.6%
3.3 67
 
1.6%
6.6 11
 
0.3%
33.0 10
 
0.2%
30.0 8
 
0.2%
13.2 7
 
0.2%
3.0 7
 
0.2%
19.8 5
 
0.1%
25.0 5
 
0.1%
12.0 4
 
0.1%
Other values (160) 210
 
5.1%
(Missing) 1089
26.3%
ValueCountFrequency (%)
0.0 2718
65.6%
3.0 7
 
0.2%
3.3 67
 
1.6%
5.0 1
 
< 0.1%
6.6 11
 
0.3%
9.28 1
 
< 0.1%
9.9 1
 
< 0.1%
10.0 1
 
< 0.1%
10.56 1
 
< 0.1%
11.59 1
 
< 0.1%
ValueCountFrequency (%)
495.0 1
 
< 0.1%
490.0 1
 
< 0.1%
420.0 1
 
< 0.1%
330.0 1
 
< 0.1%
250.0 3
0.1%
228.0 1
 
< 0.1%
225.0 2
< 0.1%
215.74 1
 
< 0.1%
196.54 1
 
< 0.1%
196.0 1
 
< 0.1%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4141
Missing (%)100.0%
Memory size36.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-134-2004-0000120040331<NA>3폐업2폐업20080118<NA><NA><NA>0226442387<NA>158814서울특별시 양천구 목동 ***-*번지 (지상*층)<NA><NA>(주)비바스포츠2004-12-13 00:00:00I2018-08-31 23:59:59.0<NA>187907.52712448520.18473영업장판매<NA><NA><NA><NA><NA><NA>0000자가<NA><NA>N0.0<NA><NA><NA>
131400003140000-134-2004-0000220040331<NA>3폐업2폐업20100319<NA><NA><NA>0221685252<NA>158719서울특별시 양천구 목동 ***-**번지 서울이동통신빌딩(**층)<NA><NA>(주)우리홈쇼핑2008-04-03 15:49:40I2018-08-31 23:59:59.0<NA>188572.016057447304.797407통신판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
231400003140000-134-2004-0000320040407<NA>3폐업2폐업20140320<NA><NA><NA>0226965876<NA>158859서울특별시 양천구 신정동 ***-**번지 (*층)서울특별시 양천구 중앙로 ***-* (신정동,(*층))8019남양알로에2004-05-24 00:00:00I2018-08-31 23:59:59.0<NA>186805.701099446834.194942방문판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
331400003140000-134-2004-000042004-04-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 67161234<NA>158-822서울특별시 양천구 신월동 **서울특별시 양천구 화곡로 ** (신월동)7902(주)이마트 신월점2024-04-19 10:08:13U2023-12-03 22:01:00.0<NA>184796.999053448625.389555<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431400003140000-134-2004-0000520040414<NA>3폐업2폐업20090120<NA><NA><NA>0226998174<NA>158859서울특별시 양천구 신정동 ***-*번지 클레버타워 ***호<NA><NA>서부에너지2005-10-06 00:00:00I2018-08-31 23:59:59.0<NA>186861.841551446885.258092방문판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
531400003140000-134-2004-0000620040414<NA>3폐업2폐업20170925<NA><NA><NA>0226435316<NA>158070서울특별시 양천구 신정동 ***-***번지 *층<NA><NA>해외개발(주)2017-09-25 14:58:50I2018-08-31 23:59:59.0<NA><NA><NA>영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631400003140000-134-2004-0000720040414<NA>3폐업2폐업20120807<NA><NA><NA>0226552303<NA>158819서울특별시 양천구 목동 ***-*번지서울특별시 양천구 등촌로 * (목동)7966정관장목동본점2012-03-14 11:24:07I2018-08-31 23:59:59.0<NA>187932.321835447589.327702영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731400003140000-134-2004-0000820040416<NA>3폐업2폐업20071231<NA><NA><NA>0226434764<NA>158070서울특별시 양천구 신정동 ***번지 *단지 비상가***<NA><NA>풀무원내츄럴하우스2004-07-14 00:00:00I2018-08-31 23:59:59.0<NA>187766.276178446265.890841영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
831400003140000-134-2004-0000920040416<NA>3폐업2폐업20150708<NA><NA><NA>0226982313<NA>158847서울특별시 양천구 신월동 ***-*번지 시영상가지하서울특별시 양천구 신월로 ** (신월동,시영상가지하)8042지리산도원양봉원2004-05-24 00:00:00I2018-08-31 23:59:59.0<NA>185263.865468446199.492398통신판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931400003140000-134-2004-0001020040420<NA>3폐업2폐업20050309<NA><NA><NA>0221662239<NA>158050서울특별시 양천구 목동 ***-**번지 현대드림타워****<NA><NA>(주)세원에프앤비2004-08-16 00:00:00I2018-08-31 23:59:59.0<NA>188584.345447447255.070457영업장판매<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
413131400003140000-134-2024-000522024-04-12<NA>3폐업2폐업2024-04-18<NA><NA><NA>02 336 92468.3158-724서울특별시 양천구 목동 *** 현대하이페리온서울특별시 양천구 목동동로 ***, 지하*층 (목동, 현대하이페리온)7998주식회사 슬로우켓2024-04-19 04:15:09U2023-12-03 22:01:00.0<NA>188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413231400003140000-134-2024-000532024-04-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-724서울특별시 양천구 목동 *** 현대하이페리온서울특별시 양천구 목동동로 ***, 지하*층 (목동, 현대하이페리온)7998호랑이 건강원2024-04-15 10:34:38I2023-12-03 23:07:00.0<NA>188884.075622447186.888604<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413331400003140000-134-2024-000542024-04-17<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-857서울특별시 양천구 신정동 ***-**서울특별시 양천구 오목로 ***, *층 (신정동)7945다비치안경(목동역점)2024-05-08 09:26:00U2023-12-04 23:01:00.0<NA>187796.641104447102.058469<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413431400003140000-134-2024-000552024-04-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-811서울특별시 양천구 목동 ***-**서울특별시 양천구 등촌로 ***, *층 (목동)7946다비치안경 등촌역점2024-04-24 16:45:12U2023-12-03 22:07:00.0<NA>187945.843697449821.719713<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413531400003140000-134-2024-000562024-04-19<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-856서울특별시 양천구 신정동 ***-*서울특별시 양천구 신정중앙로 **, *층 **호 (신정동)7938블립2024-04-19 09:59:36I2023-12-03 22:01:00.0<NA>187587.553793447206.02622<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413631400003140000-134-2024-000572024-04-25<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-860서울특별시 양천구 신정동 ***-**서울특별시 양천구 신월로 ***, *층 (신정동)8027양천에이스 내과의원2024-04-25 17:10:18I2023-12-03 22:07:00.0<NA>187327.221318446637.940797<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413731400003140000-134-2024-000582024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>158-832서울특별시 양천구 신월동 ***-**서울특별시 양천구 남부순환로**길 **, *층 ***호 (신월동)7928365당뇨&혈관건강센터2024-04-30 13:12:37I2023-12-05 00:02:00.0<NA>185642.073225446805.710967<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413831400003140000-134-2024-000592024-05-03<NA>1영업/정상1영업<NA><NA><NA><NA>02265835180.0158-811서울특별시 양천구 목동 ***-*서울특별시 양천구 공항대로 ***, *층 *호 (목동)7947가람약국2024-05-03 11:49:39I2023-12-05 00:05:00.0<NA>188253.377395449654.079009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
413931400003140000-134-2024-000602024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0158-880서울특별시 양천구 목동 *** 목동신시가지아파트*단지서울특별시 양천구 목동동로 ***, ***동 ***호 (목동, 목동신시가지아파트*단지)7987빅트리즈 스퀘어2024-05-07 11:20:44I2023-12-05 00:09:00.0<NA>189508.1996447992.012379<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
414031400003140000-134-2024-000612024-05-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0158-864서울특별시 양천구 신정동 ****-* 파크그린빌라서울특별시 양천구 중앙로**길 **, *층 ***호 (신정동, 파크그린빌라)8060더블에이치2024-05-07 11:51:38I2023-12-05 00:09:00.0<NA>186583.2364446613.138977<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>