Overview

Dataset statistics

Number of variables44
Number of observations347
Missing cells3588
Missing cells (%)23.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory127.5 KiB
Average record size in memory376.4 B

Variable types

Categorical19
Text6
DateTime4
Unsupported7
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-18391/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (75.3%)Imbalance
여성종사자수 is highly imbalanced (71.1%)Imbalance
영업장주변구분명 is highly imbalanced (76.7%)Imbalance
등급구분명 is highly imbalanced (61.6%)Imbalance
총인원 is highly imbalanced (74.3%)Imbalance
공장사무직종업원수 is highly imbalanced (50.4%)Imbalance
공장생산직종업원수 is highly imbalanced (50.4%)Imbalance
인허가취소일자 has 347 (100.0%) missing valuesMissing
폐업일자 has 102 (29.4%) missing valuesMissing
휴업시작일자 has 347 (100.0%) missing valuesMissing
휴업종료일자 has 347 (100.0%) missing valuesMissing
재개업일자 has 347 (100.0%) missing valuesMissing
전화번호 has 121 (34.9%) missing valuesMissing
소재지면적 has 34 (9.8%) missing valuesMissing
도로명주소 has 93 (26.8%) missing valuesMissing
도로명우편번호 has 96 (27.7%) missing valuesMissing
보증액 has 273 (78.7%) missing valuesMissing
월세액 has 274 (79.0%) missing valuesMissing
다중이용업소여부 has 82 (23.6%) missing valuesMissing
시설총규모 has 82 (23.6%) missing valuesMissing
전통업소지정번호 has 347 (100.0%) missing valuesMissing
전통업소주된음식 has 347 (100.0%) missing valuesMissing
홈페이지 has 347 (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
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 18 (5.2%) zerosZeros
보증액 has 60 (17.3%) zerosZeros
월세액 has 60 (17.3%) zerosZeros
시설총규모 has 235 (67.7%) zerosZeros

Reproduction

Analysis started2024-05-17 23:20:25.372726
Analysis finished2024-05-17 23:20:27.749174
Duration2.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3140000
347 

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 347
100.0%

Length

2024-05-18T08:20:28.018828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:28.684851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 347
100.0%

관리번호
Text

UNIQUE 

Distinct347
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T08:20:29.145508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7634
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

Unique347 ?
Unique (%)100.0%

Sample

1st row3140000-113-1994-00001
2nd row3140000-113-1995-00352
3rd row3140000-113-1996-00353
4th row3140000-113-1996-00354
5th row3140000-113-1996-00355
ValueCountFrequency (%)
3140000-113-1994-00001 1
 
0.3%
3140000-113-2018-00001 1
 
0.3%
3140000-113-2018-00009 1
 
0.3%
3140000-113-2018-00008 1
 
0.3%
3140000-113-2018-00007 1
 
0.3%
3140000-113-2018-00006 1
 
0.3%
3140000-113-2018-00005 1
 
0.3%
3140000-113-2018-00004 1
 
0.3%
3140000-113-2018-00003 1
 
0.3%
3140000-113-2018-00015 1
 
0.3%
Other values (337) 337
97.1%
2024-05-18T08:20:30.297574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3120
40.9%
1 1356
17.8%
- 1041
 
13.6%
3 787
 
10.3%
2 531
 
7.0%
4 435
 
5.7%
9 85
 
1.1%
6 81
 
1.1%
5 75
 
1.0%
8 62
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6593
86.4%
Dash Punctuation 1041
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3120
47.3%
1 1356
20.6%
3 787
 
11.9%
2 531
 
8.1%
4 435
 
6.6%
9 85
 
1.3%
6 81
 
1.2%
5 75
 
1.1%
8 62
 
0.9%
7 61
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1041
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7634
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3120
40.9%
1 1356
17.8%
- 1041
 
13.6%
3 787
 
10.3%
2 531
 
7.0%
4 435
 
5.7%
9 85
 
1.1%
6 81
 
1.1%
5 75
 
1.0%
8 62
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7634
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3120
40.9%
1 1356
17.8%
- 1041
 
13.6%
3 787
 
10.3%
2 531
 
7.0%
4 435
 
5.7%
9 85
 
1.1%
6 81
 
1.1%
5 75
 
1.0%
8 62
 
0.8%

인허가일자
Date

Distinct331
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1994-12-05 00:00:00
Maximum2024-05-16 00:00:00
2024-05-18T08:20:30.867286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:31.391642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
3
245 
1
102 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 245
70.6%
1 102
29.4%

Length

2024-05-18T08:20:31.790796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:32.189511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 245
70.6%
1 102
29.4%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
245 
영업/정상
102 

Length

Max length5
Median length2
Mean length2.8818444
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 245
70.6%
영업/정상 102
29.4%

Length

2024-05-18T08:20:32.647605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:33.070598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 245
70.6%
영업/정상 102
29.4%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2
245 
1
102 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
2 245
70.6%
1 102
29.4%

Length

2024-05-18T08:20:33.525864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:33.976035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 245
70.6%
1 102
29.4%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
폐업
245 
영업
102 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 245
70.6%
영업 102
29.4%

Length

2024-05-18T08:20:34.428781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:34.872893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 245
70.6%
영업 102
29.4%

폐업일자
Date

MISSING 

Distinct187
Distinct (%)76.3%
Missing102
Missing (%)29.4%
Memory size2.8 KiB
Minimum1996-09-04 00:00:00
Maximum2024-04-08 00:00:00
2024-05-18T08:20:35.386047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:35.969634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

전화번호
Text

MISSING 

Distinct215
Distinct (%)95.1%
Missing121
Missing (%)34.9%
Memory size2.8 KiB
2024-05-18T08:20:36.532928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.960177
Min length2

Characters and Unicode

Total characters2251
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

Unique206 ?
Unique (%)91.2%

Sample

1st row0226540708
2nd row02 6917630
3rd row02
4th row0226084611
5th row02 6524296
ValueCountFrequency (%)
02 38
 
13.9%
070 6
 
2.2%
0226991164 3
 
1.1%
0220650340 2
 
0.7%
0226435316 2
 
0.7%
0226970529 2
 
0.7%
0226550303 2
 
0.7%
26950260 2
 
0.7%
0226981140 2
 
0.7%
16617189 2
 
0.7%
Other values (213) 213
77.7%
2024-05-18T08:20:37.492686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 452
20.1%
0 412
18.3%
6 275
12.2%
4 166
 
7.4%
8 162
 
7.2%
1 156
 
6.9%
5 152
 
6.8%
9 149
 
6.6%
7 133
 
5.9%
3 130
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2187
97.2%
Space Separator 64
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 452
20.7%
0 412
18.8%
6 275
12.6%
4 166
 
7.6%
8 162
 
7.4%
1 156
 
7.1%
5 152
 
7.0%
9 149
 
6.8%
7 133
 
6.1%
3 130
 
5.9%
Space Separator
ValueCountFrequency (%)
64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2251
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 452
20.1%
0 412
18.3%
6 275
12.2%
4 166
 
7.4%
8 162
 
7.2%
1 156
 
6.9%
5 152
 
6.8%
9 149
 
6.6%
7 133
 
5.9%
3 130
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2251
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 452
20.1%
0 412
18.3%
6 275
12.2%
4 166
 
7.4%
8 162
 
7.2%
1 156
 
6.9%
5 152
 
6.8%
9 149
 
6.6%
7 133
 
5.9%
3 130
 
5.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct200
Distinct (%)63.9%
Missing34
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean64.918275
Minimum0
Maximum507.73
Zeros18
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:20:37.941480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.83
median40.3
Q382.5
95-th percentile206.296
Maximum507.73
Range507.73
Interquartile range (IQR)62.67

Descriptive statistics

Standard deviation72.943863
Coefficient of variation (CV)1.123626
Kurtosis9.9236021
Mean64.918275
Median Absolute Deviation (MAD)27.3
Skewness2.6658921
Sum20319.42
Variance5320.8072
MonotonicityNot monotonic
2024-05-18T08:20:38.581020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 18
 
5.2%
33.0 14
 
4.0%
10.0 7
 
2.0%
15.0 7
 
2.0%
30.0 7
 
2.0%
49.5 5
 
1.4%
82.5 5
 
1.4%
6.6 5
 
1.4%
44.1 4
 
1.2%
39.6 4
 
1.2%
Other values (190) 237
68.3%
(Missing) 34
 
9.8%
ValueCountFrequency (%)
0.0 18
5.2%
3.3 2
 
0.6%
3.5 1
 
0.3%
3.6 1
 
0.3%
4.0 1
 
0.3%
4.1 1
 
0.3%
5.0 1
 
0.3%
6.0 2
 
0.6%
6.6 5
 
1.4%
7.0 3
 
0.9%
ValueCountFrequency (%)
507.73 1
0.3%
488.56 1
0.3%
409.9 1
0.3%
330.0 1
0.3%
325.3 1
0.3%
313.5 1
0.3%
264.0 1
0.3%
260.0 2
0.6%
249.6 1
0.3%
244.33 1
0.3%

소재지우편번호
Text

Distinct92
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T08:20:39.159010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1642651
Min length6

Characters and Unicode

Total characters2139
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

Unique36 ?
Unique (%)10.4%

Sample

1st row158852
2nd row158860
3rd row158845
4th row158848
5th row158814
ValueCountFrequency (%)
158050 46
 
13.3%
158857 21
 
6.1%
158859 19
 
5.5%
158860 16
 
4.6%
158070 14
 
4.0%
158856 12
 
3.5%
158806 12
 
3.5%
158835 7
 
2.0%
158877 7
 
2.0%
158823 7
 
2.0%
Other values (82) 186
53.6%
2024-05-18T08:20:40.288904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 640
29.9%
5 489
22.9%
1 407
19.0%
0 200
 
9.4%
7 89
 
4.2%
6 74
 
3.5%
- 57
 
2.7%
2 53
 
2.5%
9 46
 
2.2%
3 44
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2082
97.3%
Dash Punctuation 57
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 640
30.7%
5 489
23.5%
1 407
19.5%
0 200
 
9.6%
7 89
 
4.3%
6 74
 
3.6%
2 53
 
2.5%
9 46
 
2.2%
3 44
 
2.1%
4 40
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 640
29.9%
5 489
22.9%
1 407
19.0%
0 200
 
9.4%
7 89
 
4.2%
6 74
 
3.5%
- 57
 
2.7%
2 53
 
2.5%
9 46
 
2.2%
3 44
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 640
29.9%
5 489
22.9%
1 407
19.0%
0 200
 
9.4%
7 89
 
4.2%
6 74
 
3.5%
- 57
 
2.7%
2 53
 
2.5%
9 46
 
2.2%
3 44
 
2.1%

지번주소
Text

Distinct337
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T08:20:41.011766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length26.596542
Min length18

Characters and Unicode

Total characters9229
Distinct characters185
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)94.5%

Sample

1st row서울특별시 양천구 신정동 296-168
2nd row서울특별시 양천구 신정동 1000-1
3rd row서울특별시 양천구 신월동 953-5
4th row서울특별시 양천구 신월동 1003-1
5th row서울특별시 양천구 목동 729-8
ValueCountFrequency (%)
서울특별시 347
19.0%
양천구 347
19.0%
신정동 142
 
7.8%
목동 133
 
7.3%
신월동 74
 
4.1%
917-9 26
 
1.4%
현대41타워 24
 
1.3%
2층 22
 
1.2%
1층 21
 
1.2%
지하1층 16
 
0.9%
Other values (471) 672
36.8%
2024-05-18T08:20:42.225540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1705
18.5%
1 472
 
5.1%
동 384
 
4.2%
양 355
 
3.8%
시 353
 
3.8%
서 350
 
3.8%
천 350
 
3.8%
특 348
 
3.8%
별 348
 
3.8%
구 348
 
3.8%
Other values (175) 4216
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4942
53.5%
Decimal Number 2170
23.5%
Space Separator 1705
 
18.5%
Dash Punctuation 328
 
3.6%
Open Punctuation 27
 
0.3%
Close Punctuation 27
 
0.3%
Uppercase Letter 18
 
0.2%
Other Punctuation 9
 
0.1%
Lowercase Letter 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 384
 
7.8%
양 355
 
7.2%
시 353
 
7.1%
서 350
 
7.1%
천 350
 
7.1%
특 348
 
7.0%
별 348
 
7.0%
구 348
 
7.0%
울 348
 
7.0%
신 232
 
4.7%
Other values (150) 1526
30.9%
Decimal Number
ValueCountFrequency (%)
1 472
21.8%
2 286
13.2%
9 262
12.1%
0 222
10.2%
4 181
 
8.3%
3 175
 
8.1%
5 167
 
7.7%
7 155
 
7.1%
6 127
 
5.9%
8 123
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
44.4%
A 3
 
16.7%
C 2
 
11.1%
S 2
 
11.1%
D 1
 
5.6%
M 1
 
5.6%
J 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 8
88.9%
/ 1
 
11.1%
Space Separator
ValueCountFrequency (%)
1705
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4942
53.5%
Common 4267
46.2%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 384
 
7.8%
양 355
 
7.2%
시 353
 
7.1%
서 350
 
7.1%
천 350
 
7.1%
특 348
 
7.0%
별 348
 
7.0%
구 348
 
7.0%
울 348
 
7.0%
신 232
 
4.7%
Other values (150) 1526
30.9%
Common
ValueCountFrequency (%)
1705
40.0%
1 472
 
11.1%
- 328
 
7.7%
2 286
 
6.7%
9 262
 
6.1%
0 222
 
5.2%
4 181
 
4.2%
3 175
 
4.1%
5 167
 
3.9%
7 155
 
3.6%
Other values (7) 314
 
7.4%
Latin
ValueCountFrequency (%)
B 8
40.0%
A 3
 
15.0%
l 2
 
10.0%
C 2
 
10.0%
S 2
 
10.0%
D 1
 
5.0%
M 1
 
5.0%
J 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4942
53.5%
ASCII 4287
46.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1705
39.8%
1 472
 
11.0%
- 328
 
7.7%
2 286
 
6.7%
9 262
 
6.1%
0 222
 
5.2%
4 181
 
4.2%
3 175
 
4.1%
5 167
 
3.9%
7 155
 
3.6%
Other values (15) 334
 
7.8%
Hangul
ValueCountFrequency (%)
동 384
 
7.8%
양 355
 
7.2%
시 353
 
7.1%
서 350
 
7.1%
천 350
 
7.1%
특 348
 
7.0%
별 348
 
7.0%
구 348
 
7.0%
울 348
 
7.0%
신 232
 
4.7%
Other values (150) 1526
30.9%

도로명주소
Text

MISSING 

Distinct249
Distinct (%)98.0%
Missing93
Missing (%)26.8%
Memory size2.8 KiB
2024-05-18T08:20:42.876365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length45
Mean length34.484252
Min length23

Characters and Unicode

Total characters8759
Distinct characters188
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)96.9%

Sample

1st row서울특별시 양천구 신월로 110 (신월동)
2nd row서울특별시 양천구 신목로14길 26 (신정동,복지B/D 2층)
3rd row서울특별시 양천구 국회대로 20 (신월동,2층)
4th row서울특별시 양천구 목동중앙북로8길 80-1 (목동)
5th row서울특별시 양천구 목동동로 258 (목동,가람빌딩4층)
ValueCountFrequency (%)
서울특별시 254
 
15.0%
양천구 254
 
15.0%
신정동 87
 
5.1%
목동 78
 
4.6%
신월동 47
 
2.8%
목동동로 31
 
1.8%
2층 26
 
1.5%
목동서로 25
 
1.5%
1층 23
 
1.4%
오목로 21
 
1.2%
Other values (466) 844
49.9%
2024-05-18T08:20:44.281006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1437
 
16.4%
동 430
 
4.9%
1 337
 
3.8%
, 297
 
3.4%
서 287
 
3.3%
) 268
 
3.1%
( 268
 
3.1%
양 268
 
3.1%
로 262
 
3.0%
시 261
 
3.0%
Other values (178) 4644
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4936
56.4%
Decimal Number 1488
 
17.0%
Space Separator 1437
 
16.4%
Other Punctuation 298
 
3.4%
Close Punctuation 268
 
3.1%
Open Punctuation 268
 
3.1%
Dash Punctuation 43
 
0.5%
Uppercase Letter 16
 
0.2%
Lowercase Letter 3
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 430
 
8.7%
서 287
 
5.8%
양 268
 
5.4%
로 262
 
5.3%
시 261
 
5.3%
천 257
 
5.2%
울 255
 
5.2%
구 255
 
5.2%
특 255
 
5.2%
별 255
 
5.2%
Other values (154) 2151
43.6%
Decimal Number
ValueCountFrequency (%)
1 337
22.6%
2 258
17.3%
3 201
13.5%
0 169
11.4%
4 115
 
7.7%
5 103
 
6.9%
9 88
 
5.9%
7 82
 
5.5%
6 77
 
5.2%
8 58
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
B 9
56.2%
A 4
25.0%
D 1
 
6.2%
M 1
 
6.2%
J 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 297
99.7%
/ 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
l 2
66.7%
c 1
33.3%
Space Separator
ValueCountFrequency (%)
1437
100.0%
Close Punctuation
ValueCountFrequency (%)
) 268
100.0%
Open Punctuation
ValueCountFrequency (%)
( 268
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4936
56.4%
Common 3804
43.4%
Latin 19
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 430
 
8.7%
서 287
 
5.8%
양 268
 
5.4%
로 262
 
5.3%
시 261
 
5.3%
천 257
 
5.2%
울 255
 
5.2%
구 255
 
5.2%
특 255
 
5.2%
별 255
 
5.2%
Other values (154) 2151
43.6%
Common
ValueCountFrequency (%)
1437
37.8%
1 337
 
8.9%
, 297
 
7.8%
) 268
 
7.0%
( 268
 
7.0%
2 258
 
6.8%
3 201
 
5.3%
0 169
 
4.4%
4 115
 
3.0%
5 103
 
2.7%
Other values (7) 351
 
9.2%
Latin
ValueCountFrequency (%)
B 9
47.4%
A 4
21.1%
l 2
 
10.5%
c 1
 
5.3%
D 1
 
5.3%
M 1
 
5.3%
J 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4936
56.4%
ASCII 3823
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1437
37.6%
1 337
 
8.8%
, 297
 
7.8%
) 268
 
7.0%
( 268
 
7.0%
2 258
 
6.7%
3 201
 
5.3%
0 169
 
4.4%
4 115
 
3.0%
5 103
 
2.7%
Other values (14) 370
 
9.7%
Hangul
ValueCountFrequency (%)
동 430
 
8.7%
서 287
 
5.8%
양 268
 
5.4%
로 262
 
5.3%
시 261
 
5.3%
천 257
 
5.2%
울 255
 
5.2%
구 255
 
5.2%
특 255
 
5.2%
별 255
 
5.2%
Other values (154) 2151
43.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct93
Distinct (%)37.1%
Missing96
Missing (%)27.7%
Infinite0
Infinite (%)0.0%
Mean7989.5299
Minimum7902
Maximum8104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:20:44.824887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7902
5-th percentile7917
Q17944
median7995
Q38022
95-th percentile8087
Maximum8104
Range202
Interquartile range (IQR)78

Descriptive statistics

Standard deviation50.383272
Coefficient of variation (CV)0.0063061623
Kurtosis-0.62459576
Mean7989.5299
Median Absolute Deviation (MAD)37
Skewness0.32175265
Sum2005372
Variance2538.4741
MonotonicityNot monotonic
2024-05-18T08:20:45.395107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7997 23
 
6.6%
7995 11
 
3.2%
7938 10
 
2.9%
8023 9
 
2.6%
7968 7
 
2.0%
7937 7
 
2.0%
7945 7
 
2.0%
8020 6
 
1.7%
8019 6
 
1.7%
8022 6
 
1.7%
Other values (83) 159
45.8%
(Missing) 96
27.7%
ValueCountFrequency (%)
7902 1
 
0.3%
7903 2
 
0.6%
7906 1
 
0.3%
7909 5
1.4%
7910 1
 
0.3%
7915 2
 
0.6%
7917 3
0.9%
7921 1
 
0.3%
7922 1
 
0.3%
7923 1
 
0.3%
ValueCountFrequency (%)
8104 2
 
0.6%
8097 1
 
0.3%
8094 1
 
0.3%
8093 6
1.7%
8089 2
 
0.6%
8087 2
 
0.6%
8086 2
 
0.6%
8082 2
 
0.6%
8079 3
0.9%
8078 1
 
0.3%

사업장명
Text

Distinct338
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-05-18T08:20:46.241668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length7.1095101
Min length1

Characters and Unicode

Total characters2467
Distinct characters391
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique330 ?
Unique (%)95.1%

Sample

1st row서벽물산
2nd row연자방
3rd row한비식품
4th row속초식품
5th row고려제과
ValueCountFrequency (%)
주식회사 35
 
8.5%
주)정은자의자연기행 3
 
0.7%
바이오 2
 
0.5%
다올 2
 
0.5%
주)예바른푸드 2
 
0.5%
가포생활건강 2
 
0.5%
코리아 2
 
0.5%
더포이아시아퍼시픽(주 2
 
0.5%
브루스리테일 2
 
0.5%
주)강화홍삼공사 2
 
0.5%
Other values (355) 356
86.8%
2024-05-18T08:20:47.394579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 167
 
6.8%
( 134
 
5.4%
) 134
 
5.4%
이 94
 
3.8%
63
 
2.6%
사 61
 
2.5%
식 58
 
2.4%
스 56
 
2.3%
에 46
 
1.9%
회 41
 
1.7%
Other values (381) 1613
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2025
82.1%
Open Punctuation 134
 
5.4%
Close Punctuation 134
 
5.4%
Uppercase Letter 72
 
2.9%
Space Separator 63
 
2.6%
Lowercase Letter 20
 
0.8%
Decimal Number 10
 
0.4%
Other Punctuation 8
 
0.3%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 167
 
8.2%
이 94
 
4.6%
사 61
 
3.0%
식 58
 
2.9%
스 56
 
2.8%
에 46
 
2.3%
회 41
 
2.0%
앤 34
 
1.7%
드 30
 
1.5%
리 30
 
1.5%
Other values (335) 1408
69.5%
Uppercase Letter
ValueCountFrequency (%)
S 8
 
11.1%
I 7
 
9.7%
G 6
 
8.3%
A 5
 
6.9%
M 5
 
6.9%
O 4
 
5.6%
H 4
 
5.6%
L 4
 
5.6%
B 3
 
4.2%
N 3
 
4.2%
Other values (12) 23
31.9%
Lowercase Letter
ValueCountFrequency (%)
n 3
15.0%
i 3
15.0%
f 2
10.0%
d 2
10.0%
o 2
10.0%
r 2
10.0%
a 1
 
5.0%
y 1
 
5.0%
e 1
 
5.0%
k 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
0 4
40.0%
9 2
20.0%
2 2
20.0%
5 1
 
10.0%
4 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
& 5
62.5%
. 2
 
25.0%
? 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2025
82.1%
Common 350
 
14.2%
Latin 92
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 167
 
8.2%
이 94
 
4.6%
사 61
 
3.0%
식 58
 
2.9%
스 56
 
2.8%
에 46
 
2.3%
회 41
 
2.0%
앤 34
 
1.7%
드 30
 
1.5%
리 30
 
1.5%
Other values (335) 1408
69.5%
Latin
ValueCountFrequency (%)
S 8
 
8.7%
I 7
 
7.6%
G 6
 
6.5%
A 5
 
5.4%
M 5
 
5.4%
O 4
 
4.3%
H 4
 
4.3%
L 4
 
4.3%
n 3
 
3.3%
i 3
 
3.3%
Other values (24) 43
46.7%
Common
ValueCountFrequency (%)
( 134
38.3%
) 134
38.3%
63
18.0%
& 5
 
1.4%
0 4
 
1.1%
. 2
 
0.6%
9 2
 
0.6%
2 2
 
0.6%
5 1
 
0.3%
4 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2025
82.1%
ASCII 442
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 167
 
8.2%
이 94
 
4.6%
사 61
 
3.0%
식 58
 
2.9%
스 56
 
2.8%
에 46
 
2.3%
회 41
 
2.0%
앤 34
 
1.7%
드 30
 
1.5%
리 30
 
1.5%
Other values (335) 1408
69.5%
ASCII
ValueCountFrequency (%)
( 134
30.3%
) 134
30.3%
63
14.3%
S 8
 
1.8%
I 7
 
1.6%
G 6
 
1.4%
& 5
 
1.1%
A 5
 
1.1%
M 5
 
1.1%
O 4
 
0.9%
Other values (36) 71
16.1%

최종수정일자
Date

Distinct332
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1999-02-12 00:00:00
Maximum2024-05-16 16:59:30
2024-05-18T08:20:47.922619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:48.574841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
I
257 
U
90 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 257
74.1%
U 90
 
25.9%

Length

2024-05-18T08:20:49.372740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:49.843736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 257
74.1%
u 90
 
25.9%

데이터갱신일자
Date

Distinct129
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-18T08:20:50.263960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T08:20:50.734448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
유통전문판매업
347 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 347
100.0%

Length

2024-05-18T08:20:51.240805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:51.913619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 347
100.0%

좌표정보(X)
Real number (ℝ)

Distinct232
Distinct (%)67.1%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean187544.59
Minimum184242.73
Maximum189743.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:20:52.280745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184242.73
5-th percentile185035.11
Q1186795.84
median187823.5
Q3188622.51
95-th percentile189042.5
Maximum189743.46
Range5500.7342
Interquartile range (IQR)1826.6744

Descriptive statistics

Standard deviation1305.5885
Coefficient of variation (CV)0.0069614832
Kurtosis-0.4303698
Mean187544.59
Median Absolute Deviation (MAD)894.67885
Skewness-0.7228032
Sum64890427
Variance1704561.3
MonotonicityNot monotonic
2024-05-18T08:20:52.735742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188953.066831076 26
 
7.5%
187324.561350406 11
 
3.2%
188584.345447275 10
 
2.9%
187823.500716444 7
 
2.0%
188871.512837973 6
 
1.7%
189151.208015925 6
 
1.7%
186583.853430927 6
 
1.7%
187925.667553697 5
 
1.4%
187734.983111761 5
 
1.4%
188493.762740612 4
 
1.2%
Other values (222) 260
74.9%
ValueCountFrequency (%)
184242.730019702 1
 
0.3%
184325.616204517 1
 
0.3%
184399.574301212 1
 
0.3%
184534.619036954 3
0.9%
184625.70334445 1
 
0.3%
184651.515751007 1
 
0.3%
184672.622849866 1
 
0.3%
184698.083646784 1
 
0.3%
184817.116668717 1
 
0.3%
184848.217797927 1
 
0.3%
ValueCountFrequency (%)
189743.464254868 2
 
0.6%
189473.530827695 1
 
0.3%
189471.306217651 1
 
0.3%
189460.484490723 1
 
0.3%
189415.269803933 1
 
0.3%
189332.773428473 1
 
0.3%
189311.02246611 1
 
0.3%
189274.417717013 1
 
0.3%
189151.208015925 6
1.7%
189128.248867296 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

Distinct232
Distinct (%)67.1%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean447258.57
Minimum444842.87
Maximum449814.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:20:53.155512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum444842.87
5-th percentile445941.75
Q1446739.8
median447197.8
Q3447511.5
95-th percentile449204.59
Maximum449814.22
Range4971.3455
Interquartile range (IQR)771.69851

Descriptive statistics

Standard deviation932.20585
Coefficient of variation (CV)0.0020842661
Kurtosis0.53942462
Mean447258.57
Median Absolute Deviation (MAD)457.99987
Skewness0.46343313
Sum1.5475146 × 108
Variance869007.75
MonotonicityNot monotonic
2024-05-18T08:20:53.598087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447333.569187997 26
 
7.5%
446982.136451416 11
 
3.2%
447255.070457495 10
 
2.9%
447457.457884414 7
 
2.0%
447348.13213342 6
 
1.7%
448200.067716589 6
 
1.7%
447197.797629393 6
 
1.7%
446739.797762899 5
 
1.4%
446030.714521005 5
 
1.4%
447213.539278579 4
 
1.2%
Other values (222) 260
74.9%
ValueCountFrequency (%)
444842.873729184 2
0.6%
445081.396522145 1
 
0.3%
445091.494659491 1
 
0.3%
445094.16222004 1
 
0.3%
445124.131588947 1
 
0.3%
445205.65952284 2
0.6%
445532.444934761 1
 
0.3%
445569.639465968 3
0.9%
445601.995865959 1
 
0.3%
445655.04439912 1
 
0.3%
ValueCountFrequency (%)
449814.219229842 1
0.3%
449741.843967266 1
0.3%
449649.016215774 1
0.3%
449602.163833876 1
0.3%
449583.899391857 1
0.3%
449560.639015671 1
0.3%
449396.806374349 1
0.3%
449394.675249633 1
0.3%
449390.943275 2
0.6%
449390.11431197 1
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
유통전문판매업
265 
<NA>
82 

Length

Max length7
Median length7
Mean length6.2910663
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 265
76.4%
<NA> 82
 
23.6%

Length

2024-05-18T08:20:54.047561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:54.379008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 265
76.4%
na 82
 
23.6%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
311 
0
 
23
2
 
7
1
 
4
4
 
1

Length

Max length4
Median length4
Mean length3.6916427
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row<NA>
2nd row1
3rd row0
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 311
89.6%
0 23
 
6.6%
2 7
 
2.0%
1 4
 
1.2%
4 1
 
0.3%
18 1
 
0.3%

Length

2024-05-18T08:20:54.855033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:55.402976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 311
89.6%
0 23
 
6.6%
2 7
 
2.0%
1 4
 
1.2%
4 1
 
0.3%
18 1
 
0.3%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
311 
0
 
27
1
 
8
2
 
1

Length

Max length4
Median length4
Mean length3.6887608
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 311
89.6%
0 27
 
7.8%
1 8
 
2.3%
2 1
 
0.3%

Length

2024-05-18T08:20:55.836215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:56.311248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 311
89.6%
0 27
 
7.8%
1 8
 
2.3%
2 1
 
0.3%

영업장주변구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
321 
주택가주변
 
17
기타
 
8
아파트지역
 
1

Length

Max length5
Median length4
Mean length4.0057637
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 321
92.5%
주택가주변 17
 
4.9%
기타 8
 
2.3%
아파트지역 1
 
0.3%

Length

2024-05-18T08:20:56.721231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:57.055827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
92.5%
주택가주변 17
 
4.9%
기타 8
 
2.3%
아파트지역 1
 
0.3%

등급구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
321 
기타
 
26

Length

Max length4
Median length4
Mean length3.8501441
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 321
92.5%
기타 26
 
7.5%

Length

2024-05-18T08:20:57.617759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:58.034878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 321
92.5%
기타 26
 
7.5%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
300 
상수도전용
47 

Length

Max length5
Median length4
Mean length4.1354467
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 300
86.5%
상수도전용 47
 
13.5%

Length

2024-05-18T08:20:58.376995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:58.871350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 300
86.5%
상수도전용 47
 
13.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
332 
0
 
15

Length

Max length4
Median length4
Mean length3.870317
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> 332
95.7%
0 15
 
4.3%

Length

2024-05-18T08:20:59.327552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:20:59.725711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 332
95.7%
0 15
 
4.3%

본사종업원수
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
222 
0
125 

Length

Max length4
Median length4
Mean length2.9193084
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 222
64.0%
0 125
36.0%

Length

2024-05-18T08:21:00.103266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:21:00.411457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
64.0%
0 125
36.0%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
222 
0
123 
1
 
1
2
 
1

Length

Max length4
Median length4
Mean length2.9193084
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 222
64.0%
0 123
35.4%
1 1
 
0.3%
2 1
 
0.3%

Length

2024-05-18T08:21:00.896426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:21:01.486369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
64.0%
0 123
35.4%
1 1
 
0.3%
2 1
 
0.3%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
222 
0
122 
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length2.9193084
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 222
64.0%
0 122
35.2%
1 2
 
0.6%
3 1
 
0.3%

Length

2024-05-18T08:21:02.273738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:21:02.664283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
64.0%
0 122
35.2%
1 2
 
0.6%
3 1
 
0.3%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
222 
0
123 
1
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.9193084
Min length1

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 222
64.0%
0 123
35.4%
1 1
 
0.3%
3 1
 
0.3%

Length

2024-05-18T08:21:02.999791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:21:03.302212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 222
64.0%
0 123
35.4%
1 1
 
0.3%
3 1
 
0.3%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
<NA>
146 
임대
124 
자가
77 

Length

Max length4
Median length2
Mean length2.8414986
Min length2

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> 146
42.1%
임대 124
35.7%
자가 77
22.2%

Length

2024-05-18T08:21:03.781823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T08:21:04.146623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 146
42.1%
임대 124
35.7%
자가 77
22.2%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)10.8%
Missing273
Missing (%)78.7%
Infinite0
Infinite (%)0.0%
Mean2797297.3
Minimum0
Maximum40000000
Zeros60
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:21:04.486801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20000000
Maximum40000000
Range40000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7309179.3
Coefficient of variation (CV)2.6129433
Kurtosis11.281731
Mean2797297.3
Median Absolute Deviation (MAD)0
Skewness3.2192155
Sum2.07 × 108
Variance5.3424102 × 1013
MonotonicityNot monotonic
2024-05-18T08:21:04.946668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 60
 
17.3%
10000000 5
 
1.4%
20000000 3
 
0.9%
5000000 2
 
0.6%
40000000 1
 
0.3%
30000000 1
 
0.3%
15000000 1
 
0.3%
2000000 1
 
0.3%
(Missing) 273
78.7%
ValueCountFrequency (%)
0 60
17.3%
2000000 1
 
0.3%
5000000 2
 
0.6%
10000000 5
 
1.4%
15000000 1
 
0.3%
20000000 3
 
0.9%
30000000 1
 
0.3%
40000000 1
 
0.3%
ValueCountFrequency (%)
40000000 1
 
0.3%
30000000 1
 
0.3%
20000000 3
 
0.9%
15000000 1
 
0.3%
10000000 5
 
1.4%
5000000 2
 
0.6%
2000000 1
 
0.3%
0 60
17.3%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct14
Distinct (%)19.2%
Missing274
Missing (%)79.0%
Infinite0
Infinite (%)0.0%
Mean179566.21
Minimum0
Maximum3000000
Zeros60
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:21:05.421780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1080000
Maximum3000000
Range3000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation495868.42
Coefficient of variation (CV)2.7614797
Kurtosis15.708727
Mean179566.21
Median Absolute Deviation (MAD)0
Skewness3.6633809
Sum13108333
Variance2.4588549 × 1011
MonotonicityNot monotonic
2024-05-18T08:21:05.951684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 60
 
17.3%
1200000 1
 
0.3%
1000000 1
 
0.3%
1800000 1
 
0.3%
458333 1
 
0.3%
850000 1
 
0.3%
600000 1
 
0.3%
700000 1
 
0.3%
900000 1
 
0.3%
650000 1
 
0.3%
Other values (4) 4
 
1.2%
(Missing) 274
79.0%
ValueCountFrequency (%)
0 60
17.3%
150000 1
 
0.3%
300000 1
 
0.3%
458333 1
 
0.3%
600000 1
 
0.3%
650000 1
 
0.3%
700000 1
 
0.3%
850000 1
 
0.3%
900000 1
 
0.3%
1000000 1
 
0.3%
ValueCountFrequency (%)
3000000 1
0.3%
1800000 1
0.3%
1500000 1
0.3%
1200000 1
0.3%
1000000 1
0.3%
900000 1
0.3%
850000 1
0.3%
700000 1
0.3%
650000 1
0.3%
600000 1
0.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing82
Missing (%)23.6%
Memory size826.0 B
False
265 
(Missing)
82 
ValueCountFrequency (%)
False 265
76.4%
(Missing) 82
 
23.6%
2024-05-18T08:21:06.341642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)10.6%
Missing82
Missing (%)23.6%
Infinite0
Infinite (%)0.0%
Mean8.0716604
Minimum0
Maximum215.74
Zeros235
Zeros (%)67.7%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-05-18T08:21:06.953159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile61.192
Maximum215.74
Range215.74
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28.620729
Coefficient of variation (CV)3.5458292
Kurtosis20.795101
Mean8.0716604
Median Absolute Deviation (MAD)0
Skewness4.3643113
Sum2138.99
Variance819.14614
MonotonicityNot monotonic
2024-05-18T08:21:07.361070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 235
67.7%
33.0 3
 
0.9%
82.5 2
 
0.6%
70.0 1
 
0.3%
44.1 1
 
0.3%
128.34 1
 
0.3%
172.11 1
 
0.3%
215.74 1
 
0.3%
9.9 1
 
0.3%
6.6 1
 
0.3%
Other values (18) 18
 
5.2%
(Missing) 82
 
23.6%
ValueCountFrequency (%)
0.0 235
67.7%
6.6 1
 
0.3%
7.0 1
 
0.3%
9.9 1
 
0.3%
21.0 1
 
0.3%
26.04 1
 
0.3%
26.4 1
 
0.3%
31.5 1
 
0.3%
33.0 3
 
0.9%
42.0 1
 
0.3%
ValueCountFrequency (%)
215.74 1
0.3%
172.11 1
0.3%
141.06 1
0.3%
137.94 1
0.3%
132.0 1
0.3%
128.34 1
0.3%
124.08 1
0.3%
123.06 1
0.3%
82.5 2
0.6%
80.0 1
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing347
Missing (%)100.0%
Memory size3.2 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031400003140000-113-1994-0000119941205<NA>3폐업2폐업20131018<NA><NA><NA>0226540708<NA>158852서울특별시 양천구 신정동 296-168<NA><NA>서벽물산2007-12-04 09:57:00I2018-08-31 23:59:59.0유통전문판매업188718.865813446423.688766유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131400003140000-113-1995-0035219951004<NA>3폐업2폐업19960904<NA><NA><NA>02 69176300.0158860서울특별시 양천구 신정동 1000-1<NA><NA>연자방2001-09-28 00:00:00I2018-08-31 23:59:59.0유통전문판매업187600.567169446935.532838유통전문판매업10주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
231400003140000-113-1996-0035319960509<NA>3폐업2폐업19990412<NA><NA><NA>020.0158845서울특별시 양천구 신월동 953-5<NA><NA>한비식품1999-04-12 00:00:00I2018-08-31 23:59:59.0유통전문판매업185260.652301446562.393749유통전문판매업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331400003140000-113-1996-0035419960708<NA>3폐업2폐업20140514<NA><NA><NA>02260846110.0158848서울특별시 양천구 신월동 1003-1서울특별시 양천구 신월로 110 (신월동)8047속초식품2014-10-08 10:19:42I2018-08-31 23:59:59.0유통전문판매업185459.334501445976.534537유통전문판매업2<NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431400003140000-113-1996-0035519960715<NA>3폐업2폐업19970425<NA><NA><NA>02 65242960.0158814서울특별시 양천구 목동 729-8<NA><NA>고려제과2001-09-28 00:00:00I2018-08-31 23:59:59.0유통전문판매업188029.553509448385.512676유통전문판매업<NA>1주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
531400003140000-113-1997-0035619970604<NA>3폐업2폐업20131220<NA><NA><NA>022643846040.3158849서울특별시 양천구 신정동 127-2 복지B/D 2층서울특별시 양천구 신목로14길 26 (신정동,복지B/D 2층)8009동승인터내셔날2013-12-20 13:57:19I2018-08-31 23:59:59.0유통전문판매업188990.004976446463.739777유통전문판매업11주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
631400003140000-113-1997-0035719970609<NA>3폐업2폐업19980724<NA><NA><NA>02 60733810.0158841서울특별시 양천구 신월동 549-1<NA><NA>서울리아(주)2001-09-28 00:00:00I2018-08-31 23:59:59.0유통전문판매업185830.02138446106.372543유통전문판매업21주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
731400003140000-113-1997-0035819970802<NA>3폐업2폐업19990202<NA><NA><NA>02 69367890.0158838서울특별시 양천구 신월동 509-1 3층<NA><NA>(주)양천물산1999-02-12 00:00:00I2018-08-31 23:59:59.0유통전문판매업186202.649871446699.633449유통전문판매업21주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
831400003140000-113-1998-0035919980916<NA>3폐업2폐업20131220<NA><NA><NA>02260690650.0158832서울특별시 양천구 신월동 410-1 2층서울특별시 양천구 국회대로 20 (신월동,2층)7928선우물산2013-12-20 11:57:56I2018-08-31 23:59:59.0유통전문판매업185536.771641447051.369004유통전문판매업21주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
931400003140000-113-1998-0036019980919<NA>3폐업2폐업20131220<NA><NA><NA>02265445110.0158812서울특별시 양천구 목동 640-1서울특별시 양천구 목동중앙북로8길 80-1 (목동)7952마시나라2013-12-20 11:58:25I2018-08-31 23:59:59.0유통전문판매업188012.154198449194.407443유통전문판매업21주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
33731400003140000-113-2023-000152023-11-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA>84.0158-777서울특별시 양천구 목동 928 건영아파트서울특별시 양천구 목동중앙본로22길 63, 102동 1002호 (목동, 건영아파트)7974새미집2023-11-07 10:52:46I2022-11-01 00:09:00.0유통전문판매업188686.846664448854.579418<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33831400003140000-113-2023-000162023-12-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA>17.57158-859서울특별시 양천구 신정동 972-6 퀸즈 포디엄서울특별시 양천구 신월로 289, 퀸즈 포디엄 1408호 (신정동)8026원바이오사이언스2023-12-22 15:35:38I2022-11-01 22:04:00.0유통전문판매업186928.826903446591.038133<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
33931400003140000-113-2024-000012024-01-05<NA>1영업/정상1영업<NA><NA><NA><NA>070 7624768933.0158-847서울특별시 양천구 신월동 988-3서울특별시 양천구 지양로5길 5, 3층 (신월동)8038오늘담2024-01-05 14:16:24I2023-12-01 00:07:00.0유통전문판매업185246.464487446499.196966<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34031400003140000-113-2024-000022024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA>90.0158-788서울특별시 양천구 신월동 591-1 신안약수아파트서울특별시 양천구 중앙로29길 55, 102동 307호 (신월동, 신안약수아파트)8070여행자의 식탁2024-01-12 14:22:11I2023-11-30 23:04:00.0유통전문판매업186443.256012446043.758277<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34131400003140000-113-2024-000032024-01-26<NA>1영업/정상1영업<NA><NA><NA><NA>02264545270.0158-806서울특별시 양천구 목동 405 목동대림아파트서울특별시 양천구 목동동로12길 23, 상가동 202호 (목동, 목동대림아파트)8006영파워 코리아2024-01-26 09:53:03I2023-11-30 22:08:00.0유통전문판매업188815.060184446814.889014<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34231400003140000-113-2024-000042024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>21.5158-871서울특별시 양천구 신정동 939-1서울특별시 양천구 중앙로 340, 1층 103호 (신정동)7942케이디푸드2024-03-27 13:56:15I2023-12-02 22:09:00.0유통전문판매업186679.515116447124.449385<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34331400003140000-113-2024-000052024-04-23<NA>1영업/정상1영업<NA><NA><NA><NA><NA>61.96158-859서울특별시 양천구 신정동 945-2 신정스포렉스서울특별시 양천구 오목로 138, 신정스포렉스 1층 101호,102호 (신정동)8019(주)포트코퍼레이션2024-04-23 10:01:01I2023-12-03 22:05:00.0유통전문판매업186908.412208446899.767783<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34431400003140000-113-2024-000062024-04-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA>15.0158-861서울특별시 양천구 신정동 1016-7 남부빌딩서울특별시 양천구 은행정로6길 22, 남부빌딩 4층 401-3호 (신정동)8087주식회사 스테디스트2024-04-26 17:09:33I2023-12-03 22:08:00.0유통전문판매업187728.969922446595.053009<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34531400003140000-113-2024-000072024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.0158-804서울특별시 양천구 목동 318-68서울특별시 양천구 목동중앙본로7가길 73-16, 2층 202호 (목동)7955이너피스코리아2024-05-02 10:49:47I2023-12-05 00:04:00.0유통전문판매업188052.537607448906.794813<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34631400003140000-113-2024-000082024-05-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>25.0158-859서울특별시 양천구 신정동 963-31서울특별시 양천구 오목로38길 22, 2층 일부호 (신정동)8025이지앤웰스2024-05-16 16:59:30I2023-12-04 23:08:00.0유통전문판매업187229.430967446770.309074<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>