Overview

Dataset statistics

Number of variables44
Number of observations357
Missing cells5285
Missing cells (%)33.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.6 KiB
Average record size in memory377.4 B

Variable types

Categorical15
Text7
DateTime4
Unsupported9
Numeric8
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
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-18065/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (67.7%)Imbalance
여성종사자수 is highly imbalanced (67.7%)Imbalance
급수시설구분명 is highly imbalanced (78.8%)Imbalance
총인원 is highly imbalanced (68.9%)Imbalance
공장생산직종업원수 is highly imbalanced (63.7%)Imbalance
시설총규모 is highly imbalanced (56.9%)Imbalance
인허가취소일자 has 357 (100.0%) missing valuesMissing
폐업일자 has 140 (39.2%) missing valuesMissing
휴업시작일자 has 357 (100.0%) missing valuesMissing
휴업종료일자 has 357 (100.0%) missing valuesMissing
재개업일자 has 357 (100.0%) missing valuesMissing
전화번호 has 117 (32.8%) missing valuesMissing
소재지면적 has 177 (49.6%) missing valuesMissing
소재지우편번호 has 5 (1.4%) missing valuesMissing
지번주소 has 5 (1.4%) missing valuesMissing
도로명주소 has 63 (17.6%) missing valuesMissing
도로명우편번호 has 64 (17.9%) missing valuesMissing
좌표정보(X) has 8 (2.2%) missing valuesMissing
좌표정보(Y) has 8 (2.2%) missing valuesMissing
영업장주변구분명 has 357 (100.0%) missing valuesMissing
등급구분명 has 357 (100.0%) missing valuesMissing
본사종업원수 has 267 (74.8%) missing valuesMissing
공장사무직종업원수 has 265 (74.2%) missing valuesMissing
공장판매직종업원수 has 268 (75.1%) missing valuesMissing
보증액 has 271 (75.9%) missing valuesMissing
월세액 has 271 (75.9%) missing valuesMissing
다중이용업소여부 has 143 (40.1%) missing valuesMissing
전통업소지정번호 has 357 (100.0%) missing valuesMissing
전통업소주된음식 has 357 (100.0%) missing valuesMissing
홈페이지 has 357 (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
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
본사종업원수 has 73 (20.4%) zerosZeros
공장사무직종업원수 has 54 (15.1%) zerosZeros
공장판매직종업원수 has 62 (17.4%) zerosZeros
보증액 has 34 (9.5%) zerosZeros
월세액 has 35 (9.8%) zerosZeros

Reproduction

Analysis started2024-05-11 05:30:43.285446
Analysis finished2024-05-11 05:30:45.715844
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
3130000
357 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 357
100.0%

Length

2024-05-11T05:30:46.106523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:46.521589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 357
100.0%

관리번호
Text

UNIQUE 

Distinct357
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-11T05:30:47.014536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7854
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

Unique357 ?
Unique (%)100.0%

Sample

1st row3130000-135-2004-00001
2nd row3130000-135-2004-00002
3rd row3130000-135-2004-00003
4th row3130000-135-2004-00004
5th row3130000-135-2004-00005
ValueCountFrequency (%)
3130000-135-2004-00001 1
 
0.3%
3130000-135-2017-00012 1
 
0.3%
3130000-135-2020-00015 1
 
0.3%
3130000-135-2020-00014 1
 
0.3%
3130000-135-2020-00013 1
 
0.3%
3130000-135-2020-00012 1
 
0.3%
3130000-135-2020-00011 1
 
0.3%
3130000-135-2020-00010 1
 
0.3%
3130000-135-2020-00009 1
 
0.3%
3130000-135-2020-00008 1
 
0.3%
Other values (347) 347
97.2%
2024-05-11T05:30:48.647293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3166
40.3%
3 1165
 
14.8%
- 1071
 
13.6%
1 1066
 
13.6%
2 622
 
7.9%
5 437
 
5.6%
4 87
 
1.1%
6 63
 
0.8%
8 62
 
0.8%
9 60
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6783
86.4%
Dash Punctuation 1071
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3166
46.7%
3 1165
 
17.2%
1 1066
 
15.7%
2 622
 
9.2%
5 437
 
6.4%
4 87
 
1.3%
6 63
 
0.9%
8 62
 
0.9%
9 60
 
0.9%
7 55
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 1071
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7854
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3166
40.3%
3 1165
 
14.8%
- 1071
 
13.6%
1 1066
 
13.6%
2 622
 
7.9%
5 437
 
5.6%
4 87
 
1.1%
6 63
 
0.8%
8 62
 
0.8%
9 60
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3166
40.3%
3 1165
 
14.8%
- 1071
 
13.6%
1 1066
 
13.6%
2 622
 
7.9%
5 437
 
5.6%
4 87
 
1.1%
6 63
 
0.8%
8 62
 
0.8%
9 60
 
0.8%
Distinct326
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2004-03-23 00:00:00
Maximum2024-04-01 00:00:00
2024-05-11T05:30:49.107249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:49.562876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
3
217 
1
140 

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 (%)
3 217
60.8%
1 140
39.2%

Length

2024-05-11T05:30:50.314146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:51.153936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 217
60.8%
1 140
39.2%

영업상태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
폐업
217 
영업/정상
140 

Length

Max length5
Median length2
Mean length3.1764706
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 217
60.8%
영업/정상 140
39.2%

Length

2024-05-11T05:30:51.605392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:51.972383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 217
60.8%
영업/정상 140
39.2%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2
217 
1
140 

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 (%)
2 217
60.8%
1 140
39.2%

Length

2024-05-11T05:30:52.535435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:53.131429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 217
60.8%
1 140
39.2%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
폐업
217 
영업
140 

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 217
60.8%
영업 140
39.2%

Length

2024-05-11T05:30:53.711447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:30:54.283717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 217
60.8%
영업 140
39.2%

폐업일자
Date

MISSING 

Distinct193
Distinct (%)88.9%
Missing140
Missing (%)39.2%
Memory size2.9 KiB
Minimum2004-11-22 00:00:00
Maximum2024-04-11 00:00:00
2024-05-11T05:30:54.862171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:30:55.677111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

전화번호
Text

MISSING 

Distinct229
Distinct (%)95.4%
Missing117
Missing (%)32.8%
Memory size2.9 KiB
2024-05-11T05:30:56.681964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.666667
Min length7

Characters and Unicode

Total characters2560
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

Unique218 ?
Unique (%)90.8%

Sample

1st row02 3382904
2nd row02 3225989
3rd row02 3623271
4th row02 3228631
5th row02 3346033
ValueCountFrequency (%)
02 128
29.3%
070 16
 
3.7%
323 5
 
1.1%
715 3
 
0.7%
322 3
 
0.7%
336 3
 
0.7%
0909 2
 
0.5%
3035004 2
 
0.5%
332 2
 
0.5%
701 2
 
0.5%
Other values (257) 271
62.0%
2024-05-11T05:30:58.088519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 463
18.1%
2 374
14.6%
3 288
11.2%
269
10.5%
7 219
8.6%
8 175
 
6.8%
4 175
 
6.8%
6 170
 
6.6%
1 168
 
6.6%
5 146
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2291
89.5%
Space Separator 269
 
10.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 463
20.2%
2 374
16.3%
3 288
12.6%
7 219
9.6%
8 175
 
7.6%
4 175
 
7.6%
6 170
 
7.4%
1 168
 
7.3%
5 146
 
6.4%
9 113
 
4.9%
Space Separator
ValueCountFrequency (%)
269
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2560
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 463
18.1%
2 374
14.6%
3 288
11.2%
269
10.5%
7 219
8.6%
8 175
 
6.8%
4 175
 
6.8%
6 170
 
6.6%
1 168
 
6.6%
5 146
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 463
18.1%
2 374
14.6%
3 288
11.2%
269
10.5%
7 219
8.6%
8 175
 
6.8%
4 175
 
6.8%
6 170
 
6.6%
1 168
 
6.6%
5 146
 
5.7%

소재지면적
Text

MISSING 

Distinct136
Distinct (%)75.6%
Missing177
Missing (%)49.6%
Memory size2.9 KiB
2024-05-11T05:30:59.202923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.0111111
Min length3

Characters and Unicode

Total characters902
Distinct characters12
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

Unique121 ?
Unique (%)67.2%

Sample

1st row17.35
2nd row85.00
3rd row92.60
4th row198.00
5th row92.60
ValueCountFrequency (%)
00 15
 
8.3%
0.00 7
 
3.9%
10.00 5
 
2.8%
100.00 5
 
2.8%
3.30 4
 
2.2%
92.60 3
 
1.7%
20.00 3
 
1.7%
3.00 3
 
1.7%
12.00 2
 
1.1%
75.90 2
 
1.1%
Other values (126) 131
72.8%
2024-05-11T05:31:00.828606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 251
27.8%
. 180
20.0%
1 76
 
8.4%
2 73
 
8.1%
5 63
 
7.0%
3 54
 
6.0%
6 48
 
5.3%
4 43
 
4.8%
7 40
 
4.4%
8 37
 
4.1%
Other values (2) 37
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
79.9%
Other Punctuation 181
 
20.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 251
34.8%
1 76
 
10.5%
2 73
 
10.1%
5 63
 
8.7%
3 54
 
7.5%
6 48
 
6.7%
4 43
 
6.0%
7 40
 
5.5%
8 37
 
5.1%
9 36
 
5.0%
Other Punctuation
ValueCountFrequency (%)
. 180
99.4%
, 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 902
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 251
27.8%
. 180
20.0%
1 76
 
8.4%
2 73
 
8.1%
5 63
 
7.0%
3 54
 
6.0%
6 48
 
5.3%
4 43
 
4.8%
7 40
 
4.4%
8 37
 
4.1%
Other values (2) 37
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 251
27.8%
. 180
20.0%
1 76
 
8.4%
2 73
 
8.1%
5 63
 
7.0%
3 54
 
6.0%
6 48
 
5.3%
4 43
 
4.8%
7 40
 
4.4%
8 37
 
4.1%
Other values (2) 37
 
4.1%

소재지우편번호
Text

MISSING 

Distinct140
Distinct (%)39.8%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2024-05-11T05:31:01.917222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2784091
Min length6

Characters and Unicode

Total characters2210
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

Unique63 ?
Unique (%)17.9%

Sample

1st row121816
2nd row121050
3rd row121817
4th row121896
5th row121817
ValueCountFrequency (%)
121893 11
 
3.1%
121846 10
 
2.8%
121812 9
 
2.6%
121869 9
 
2.6%
121842 9
 
2.6%
121904 9
 
2.6%
121816 9
 
2.6%
121815 7
 
2.0%
121805 7
 
2.0%
121897 6
 
1.7%
Other values (130) 266
75.6%
2024-05-11T05:31:03.938532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 789
35.7%
2 403
18.2%
8 331
15.0%
9 106
 
4.8%
- 98
 
4.4%
4 97
 
4.4%
0 93
 
4.2%
7 81
 
3.7%
6 73
 
3.3%
5 72
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2112
95.6%
Dash Punctuation 98
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 789
37.4%
2 403
19.1%
8 331
15.7%
9 106
 
5.0%
4 97
 
4.6%
0 93
 
4.4%
7 81
 
3.8%
6 73
 
3.5%
5 72
 
3.4%
3 67
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 789
35.7%
2 403
18.2%
8 331
15.0%
9 106
 
4.8%
- 98
 
4.4%
4 97
 
4.4%
0 93
 
4.2%
7 81
 
3.7%
6 73
 
3.3%
5 72
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 789
35.7%
2 403
18.2%
8 331
15.0%
9 106
 
4.8%
- 98
 
4.4%
4 97
 
4.4%
0 93
 
4.2%
7 81
 
3.7%
6 73
 
3.3%
5 72
 
3.3%

지번주소
Text

MISSING 

Distinct292
Distinct (%)83.0%
Missing5
Missing (%)1.4%
Memory size2.9 KiB
2024-05-11T05:31:05.104177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length35.5
Mean length27.198864
Min length17

Characters and Unicode

Total characters9574
Distinct characters263
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)73.3%

Sample

1st row서울특별시 마포구 동교동 ***-*번지 마젤란** ***호
2nd row서울특별시 마포구 마포동 ***-*번지 강변한신코아 ****호
3rd row서울특별시 마포구 동교동 ***-*번지 엘지팰리스빌딩 ****호
4th row서울특별시 마포구 서교동 ***-**번지 (*층)
5th row서울특별시 마포구 동교동 ***-*번지 엘지팰리스 ****호
ValueCountFrequency (%)
서울특별시 352
19.1%
마포구 352
19.1%
181
 
9.8%
번지 161
 
8.7%
91
 
4.9%
서교동 74
 
4.0%
64
 
3.5%
도화동 42
 
2.3%
동교동 35
 
1.9%
합정동 33
 
1.8%
Other values (221) 458
24.9%
2024-05-11T05:31:06.924306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1847
19.3%
1673
17.5%
447
 
4.7%
413
 
4.3%
374
 
3.9%
369
 
3.9%
361
 
3.8%
354
 
3.7%
354
 
3.7%
354
 
3.7%
Other values (253) 3028
31.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5627
58.8%
Other Punctuation 1863
 
19.5%
Space Separator 1673
 
17.5%
Dash Punctuation 284
 
3.0%
Decimal Number 54
 
0.6%
Uppercase Letter 45
 
0.5%
Lowercase Letter 11
 
0.1%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
447
 
7.9%
413
 
7.3%
374
 
6.6%
369
 
6.6%
361
 
6.4%
354
 
6.3%
354
 
6.3%
354
 
6.3%
352
 
6.3%
191
 
3.4%
Other values (208) 2058
36.6%
Uppercase Letter
ValueCountFrequency (%)
B 5
11.1%
L 5
11.1%
O 4
 
8.9%
P 4
 
8.9%
A 3
 
6.7%
T 3
 
6.7%
C 3
 
6.7%
S 3
 
6.7%
E 2
 
4.4%
H 2
 
4.4%
Other values (8) 11
24.4%
Lowercase Letter
ValueCountFrequency (%)
s 2
18.2%
p 1
9.1%
n 1
9.1%
i 1
9.1%
r 1
9.1%
e 1
9.1%
u 1
9.1%
g 1
9.1%
o 1
9.1%
h 1
9.1%
Decimal Number
ValueCountFrequency (%)
1 16
29.6%
2 9
16.7%
5 6
 
11.1%
3 6
 
11.1%
7 5
 
9.3%
4 4
 
7.4%
6 3
 
5.6%
0 3
 
5.6%
8 2
 
3.7%
Other Punctuation
ValueCountFrequency (%)
* 1847
99.1%
, 15
 
0.8%
@ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1673
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 284
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5627
58.8%
Common 3890
40.6%
Latin 57
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
447
 
7.9%
413
 
7.3%
374
 
6.6%
369
 
6.6%
361
 
6.4%
354
 
6.3%
354
 
6.3%
354
 
6.3%
352
 
6.3%
191
 
3.4%
Other values (208) 2058
36.6%
Latin
ValueCountFrequency (%)
B 5
 
8.8%
L 5
 
8.8%
O 4
 
7.0%
P 4
 
7.0%
A 3
 
5.3%
T 3
 
5.3%
C 3
 
5.3%
S 3
 
5.3%
s 2
 
3.5%
E 2
 
3.5%
Other values (19) 23
40.4%
Common
ValueCountFrequency (%)
* 1847
47.5%
1673
43.0%
- 284
 
7.3%
1 16
 
0.4%
, 15
 
0.4%
2 9
 
0.2%
( 8
 
0.2%
) 8
 
0.2%
5 6
 
0.2%
3 6
 
0.2%
Other values (6) 18
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5627
58.8%
ASCII 3946
41.2%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1847
46.8%
1673
42.4%
- 284
 
7.2%
1 16
 
0.4%
, 15
 
0.4%
2 9
 
0.2%
( 8
 
0.2%
) 8
 
0.2%
5 6
 
0.2%
3 6
 
0.2%
Other values (34) 74
 
1.9%
Hangul
ValueCountFrequency (%)
447
 
7.9%
413
 
7.3%
374
 
6.6%
369
 
6.6%
361
 
6.4%
354
 
6.3%
354
 
6.3%
354
 
6.3%
352
 
6.3%
191
 
3.4%
Other values (208) 2058
36.6%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct261
Distinct (%)88.8%
Missing63
Missing (%)17.6%
Memory size2.9 KiB
2024-05-11T05:31:08.240113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length47
Mean length35.622449
Min length24

Characters and Unicode

Total characters10473
Distinct characters274
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

Unique234 ?
Unique (%)79.6%

Sample

1st row서울특별시 마포구 월드컵로**길 * (서교동, (*층))
2nd row서울특별시 마포구 동교로**길 * (동교동, 석진빌딩 *층)
3rd row서울특별시 마포구 잔다리로*길 *, *층 (서교동)
4th row서울특별시 마포구 대흥로 ** (대흥동, 신한빌딩 *층 ***호)
5th row서울특별시 마포구 양화로*길 ** (서교동, *층)
ValueCountFrequency (%)
서울특별시 294
14.2%
마포구 294
14.2%
290
14.0%
173
 
8.4%
133
 
6.4%
서교동 66
 
3.2%
마포대로 39
 
1.9%
도화동 38
 
1.8%
월드컵북로 26
 
1.3%
성산동 25
 
1.2%
Other values (279) 693
33.5%
2024-05-11T05:31:09.937737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1778
17.0%
* 1591
 
15.2%
, 383
 
3.7%
378
 
3.6%
366
 
3.5%
360
 
3.4%
357
 
3.4%
307
 
2.9%
) 304
 
2.9%
( 304
 
2.9%
Other values (264) 4345
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5919
56.5%
Other Punctuation 1975
 
18.9%
Space Separator 1778
 
17.0%
Close Punctuation 304
 
2.9%
Open Punctuation 304
 
2.9%
Dash Punctuation 64
 
0.6%
Uppercase Letter 57
 
0.5%
Decimal Number 56
 
0.5%
Lowercase Letter 12
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
378
 
6.4%
366
 
6.2%
360
 
6.1%
357
 
6.0%
307
 
5.2%
299
 
5.1%
297
 
5.0%
296
 
5.0%
294
 
5.0%
292
 
4.9%
Other values (216) 2673
45.2%
Uppercase Letter
ValueCountFrequency (%)
B 8
14.0%
A 8
14.0%
L 5
8.8%
C 5
8.8%
D 4
 
7.0%
P 4
 
7.0%
O 4
 
7.0%
K 3
 
5.3%
T 3
 
5.3%
S 2
 
3.5%
Other values (8) 11
19.3%
Lowercase Letter
ValueCountFrequency (%)
s 2
16.7%
u 1
8.3%
o 1
8.3%
p 1
8.3%
r 1
8.3%
i 1
8.3%
n 1
8.3%
e 1
8.3%
g 1
8.3%
h 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 15
26.8%
2 8
14.3%
0 7
12.5%
3 6
 
10.7%
6 5
 
8.9%
5 5
 
8.9%
8 4
 
7.1%
4 4
 
7.1%
9 1
 
1.8%
7 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
* 1591
80.6%
, 383
 
19.4%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1778
100.0%
Close Punctuation
ValueCountFrequency (%)
) 304
100.0%
Open Punctuation
ValueCountFrequency (%)
( 304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5919
56.5%
Common 4484
42.8%
Latin 70
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
378
 
6.4%
366
 
6.2%
360
 
6.1%
357
 
6.0%
307
 
5.2%
299
 
5.1%
297
 
5.0%
296
 
5.0%
294
 
5.0%
292
 
4.9%
Other values (216) 2673
45.2%
Latin
ValueCountFrequency (%)
B 8
 
11.4%
A 8
 
11.4%
L 5
 
7.1%
C 5
 
7.1%
D 4
 
5.7%
P 4
 
5.7%
O 4
 
5.7%
K 3
 
4.3%
T 3
 
4.3%
s 2
 
2.9%
Other values (20) 24
34.3%
Common
ValueCountFrequency (%)
1778
39.7%
* 1591
35.5%
, 383
 
8.5%
) 304
 
6.8%
( 304
 
6.8%
- 64
 
1.4%
1 15
 
0.3%
2 8
 
0.2%
0 7
 
0.2%
3 6
 
0.1%
Other values (8) 24
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5919
56.5%
ASCII 4553
43.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1778
39.1%
* 1591
34.9%
, 383
 
8.4%
) 304
 
6.7%
( 304
 
6.7%
- 64
 
1.4%
1 15
 
0.3%
B 8
 
0.2%
2 8
 
0.2%
A 8
 
0.2%
Other values (37) 90
 
2.0%
Hangul
ValueCountFrequency (%)
378
 
6.4%
366
 
6.2%
360
 
6.1%
357
 
6.0%
307
 
5.2%
299
 
5.1%
297
 
5.0%
296
 
5.0%
294
 
5.0%
292
 
4.9%
Other values (216) 2673
45.2%
Number Forms
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)40.3%
Missing64
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean4054.7884
Minimum3905
Maximum4214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:10.582485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3905
5-th percentile3925
Q13992
median4043
Q34137
95-th percentile4193.4
Maximum4214
Range309
Interquartile range (IQR)145

Descriptive statistics

Standard deviation81.523441
Coefficient of variation (CV)0.020105474
Kurtosis-0.9625601
Mean4054.7884
Median Absolute Deviation (MAD)57
Skewness0.2568413
Sum1188053
Variance6646.0715
MonotonicityNot monotonic
2024-05-11T05:31:11.310928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4168 12
 
3.4%
4158 10
 
2.8%
4029 10
 
2.8%
3925 9
 
2.5%
4157 9
 
2.5%
4038 7
 
2.0%
3991 7
 
2.0%
4043 6
 
1.7%
4195 6
 
1.7%
3992 5
 
1.4%
Other values (108) 212
59.4%
(Missing) 64
 
17.9%
ValueCountFrequency (%)
3905 3
 
0.8%
3914 3
 
0.8%
3918 1
 
0.3%
3923 1
 
0.3%
3925 9
2.5%
3926 1
 
0.3%
3927 2
 
0.6%
3929 2
 
0.6%
3938 2
 
0.6%
3949 2
 
0.6%
ValueCountFrequency (%)
4214 1
 
0.3%
4213 2
 
0.6%
4208 2
 
0.6%
4207 1
 
0.3%
4206 2
 
0.6%
4195 6
1.7%
4194 1
 
0.3%
4193 2
 
0.6%
4190 1
 
0.3%
4177 2
 
0.6%
Distinct349
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2024-05-11T05:31:12.226106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length16
Mean length8.1708683
Min length2

Characters and Unicode

Total characters2917
Distinct characters361
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

Unique341 ?
Unique (%)95.5%

Sample

1st row주식회사 씨케이바이오
2nd row주식회사 보령라인
3rd row주식회사 자연주의건강나라
4th row주식회사 보청메디칼
5th row(주)안국건강중앙연구소
ValueCountFrequency (%)
주식회사 82
 
17.6%
주)한국다원호간보 2
 
0.4%
주)고려홍삼중앙회 2
 
0.4%
혜당연구소 2
 
0.4%
원니스 2
 
0.4%
큐리온 2
 
0.4%
혜당한방대체의학연구소 2
 
0.4%
코퍼레이션 2
 
0.4%
코엑스리더스 2
 
0.4%
주)아스타라이프 2
 
0.4%
Other values (363) 365
78.5%
2024-05-11T05:31:13.264623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
8.7%
) 176
 
6.0%
( 172
 
5.9%
139
 
4.8%
109
 
3.7%
95
 
3.3%
93
 
3.2%
90
 
3.1%
84
 
2.9%
42
 
1.4%
Other values (351) 1662
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2379
81.6%
Close Punctuation 176
 
6.0%
Open Punctuation 172
 
5.9%
Space Separator 109
 
3.7%
Uppercase Letter 38
 
1.3%
Lowercase Letter 29
 
1.0%
Decimal Number 7
 
0.2%
Other Punctuation 5
 
0.2%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
255
 
10.7%
139
 
5.8%
95
 
4.0%
93
 
3.9%
90
 
3.8%
84
 
3.5%
42
 
1.8%
38
 
1.6%
38
 
1.6%
36
 
1.5%
Other values (309) 1469
61.7%
Uppercase Letter
ValueCountFrequency (%)
L 5
13.2%
D 4
10.5%
B 4
10.5%
C 3
 
7.9%
F 3
 
7.9%
A 2
 
5.3%
N 2
 
5.3%
H 2
 
5.3%
E 2
 
5.3%
G 2
 
5.3%
Other values (8) 9
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 6
20.7%
a 5
17.2%
l 5
17.2%
o 2
 
6.9%
n 2
 
6.9%
i 2
 
6.9%
p 1
 
3.4%
z 1
 
3.4%
b 1
 
3.4%
f 1
 
3.4%
Other values (3) 3
10.3%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
3 2
28.6%
6 1
14.3%
4 1
14.3%
5 1
14.3%
Other Punctuation
ValueCountFrequency (%)
& 3
60.0%
. 2
40.0%
Close Punctuation
ValueCountFrequency (%)
) 176
100.0%
Open Punctuation
ValueCountFrequency (%)
( 172
100.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2379
81.6%
Common 471
 
16.1%
Latin 67
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
255
 
10.7%
139
 
5.8%
95
 
4.0%
93
 
3.9%
90
 
3.8%
84
 
3.5%
42
 
1.8%
38
 
1.6%
38
 
1.6%
36
 
1.5%
Other values (309) 1469
61.7%
Latin
ValueCountFrequency (%)
e 6
 
9.0%
a 5
 
7.5%
L 5
 
7.5%
l 5
 
7.5%
D 4
 
6.0%
B 4
 
6.0%
C 3
 
4.5%
F 3
 
4.5%
o 2
 
3.0%
n 2
 
3.0%
Other values (21) 28
41.8%
Common
ValueCountFrequency (%)
) 176
37.4%
( 172
36.5%
109
23.1%
& 3
 
0.6%
- 2
 
0.4%
2 2
 
0.4%
. 2
 
0.4%
3 2
 
0.4%
6 1
 
0.2%
4 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2379
81.6%
ASCII 538
 
18.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
255
 
10.7%
139
 
5.8%
95
 
4.0%
93
 
3.9%
90
 
3.8%
84
 
3.5%
42
 
1.8%
38
 
1.6%
38
 
1.6%
36
 
1.5%
Other values (309) 1469
61.7%
ASCII
ValueCountFrequency (%)
) 176
32.7%
( 172
32.0%
109
20.3%
e 6
 
1.1%
a 5
 
0.9%
L 5
 
0.9%
l 5
 
0.9%
D 4
 
0.7%
B 4
 
0.7%
C 3
 
0.6%
Other values (32) 49
 
9.1%
Distinct345
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2004-05-18 00:00:00
Maximum2024-05-09 14:56:18
2024-05-11T05:31:13.729660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:31:14.182636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
I
205 
U
152 

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 205
57.4%
U 152
42.6%

Length

2024-05-11T05:31:14.756841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:15.060909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 205
57.4%
u 152
42.6%
Distinct212
Distinct (%)59.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T05:31:15.398543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T05:31:15.868087image/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 size2.9 KiB
건강기능식품유통전문판매업
357 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 357
100.0%

Length

2024-05-11T05:31:16.297233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:16.623029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 357
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct231
Distinct (%)66.2%
Missing8
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean193327.38
Minimum189392.98
Maximum196266.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:16.998647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189392.98
5-th percentile190642.17
Q1192390.67
median192907.93
Q3194974.59
95-th percentile195766.59
Maximum196266.95
Range6873.9783
Interquartile range (IQR)2583.9165

Descriptive statistics

Standard deviation1591.8564
Coefficient of variation (CV)0.0082339935
Kurtosis-0.68070213
Mean193327.38
Median Absolute Deviation (MAD)871.19164
Skewness0.059649258
Sum67471257
Variance2534006.9
MonotonicityNot monotonic
2024-05-11T05:31:17.453005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193166.430144679 6
 
1.7%
195237.642733133 6
 
1.7%
192708.961190151 5
 
1.4%
195748.06444032 4
 
1.1%
192408.728864108 4
 
1.1%
195766.588069694 4
 
1.1%
195310.825031788 4
 
1.1%
190125.564768858 4
 
1.1%
195568.006693886 4
 
1.1%
192332.918156777 4
 
1.1%
Other values (221) 304
85.2%
(Missing) 8
 
2.2%
ValueCountFrequency (%)
189392.975995366 3
0.8%
189624.641758403 1
 
0.3%
189954.316212248 1
 
0.3%
190125.564768858 4
1.1%
190182.067334395 3
0.8%
190250.875091908 2
0.6%
190417.746373575 1
 
0.3%
190555.014125261 1
 
0.3%
190631.340867741 2
0.6%
190658.42111541 1
 
0.3%
ValueCountFrequency (%)
196266.954308822 2
0.6%
196175.664369891 1
 
0.3%
196116.359505276 1
 
0.3%
196061.875299768 1
 
0.3%
196057.949965838 2
0.6%
196042.381344735 2
0.6%
196020.726290334 1
 
0.3%
195900.709427813 3
0.8%
195874.639172861 1
 
0.3%
195852.524254164 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct231
Distinct (%)66.2%
Missing8
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean450141.46
Minimum448229.06
Maximum453872.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:17.900896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448229.06
5-th percentile448692.79
Q1449345.04
median450095.47
Q3450677.87
95-th percentile452711.62
Maximum453872.43
Range5643.362
Interquartile range (IQR)1332.8261

Descriptive statistics

Standard deviation1081.2224
Coefficient of variation (CV)0.0024019615
Kurtosis1.0554525
Mean450141.46
Median Absolute Deviation (MAD)640.75026
Skewness0.90547933
Sum1.5709937 × 108
Variance1169042
MonotonicityNot monotonic
2024-05-11T05:31:18.318048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450425.852790862 6
 
1.7%
448733.404817253 6
 
1.7%
450716.539901068 5
 
1.4%
449145.578789461 4
 
1.1%
450178.048591944 4
 
1.1%
449083.306922623 4
 
1.1%
448677.797932004 4
 
1.1%
453090.149821248 4
 
1.1%
448931.294688013 4
 
1.1%
449461.477885688 4
 
1.1%
Other values (221) 304
85.2%
(Missing) 8
 
2.2%
ValueCountFrequency (%)
448229.063825491 3
0.8%
448407.752664604 1
 
0.3%
448540.434893446 1
 
0.3%
448572.253976483 2
0.6%
448575.779442887 1
 
0.3%
448575.956518546 2
0.6%
448607.075232254 1
 
0.3%
448634.756333949 1
 
0.3%
448669.284545862 1
 
0.3%
448677.797932004 4
1.1%
ValueCountFrequency (%)
453872.42578746 1
 
0.3%
453263.335891345 1
 
0.3%
453141.676626027 3
0.8%
453114.7324935 3
0.8%
453090.149821248 4
1.1%
453017.867202928 2
0.6%
452995.277230914 1
 
0.3%
452969.084027083 1
 
0.3%
452720.136638715 2
0.6%
452698.835447526 1
 
0.3%

위생업태명
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
건강기능식품유통전문판매업
214 
<NA>
143 

Length

Max length13
Median length13
Mean length9.394958
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품유통전문판매업 214
59.9%
<NA> 143
40.1%

Length

2024-05-11T05:31:18.660089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:19.002928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품유통전문판매업 214
59.9%
na 143
40.1%

남성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
336 
0
 
21

Length

Max length4
Median length4
Mean length3.8235294
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> 336
94.1%
0 21
 
5.9%

Length

2024-05-11T05:31:19.403545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:20.005935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 336
94.1%
0 21
 
5.9%

여성종사자수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
336 
0
 
21

Length

Max length4
Median length4
Mean length3.8235294
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> 336
94.1%
0 21
 
5.9%

Length

2024-05-11T05:31:20.381371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:20.738469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 336
94.1%
0 21
 
5.9%

영업장주변구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

등급구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

급수시설구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
345 
상수도전용
 
12

Length

Max length5
Median length4
Mean length4.0336134
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> 345
96.6%
상수도전용 12
 
3.4%

Length

2024-05-11T05:31:21.232637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:21.658121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 345
96.6%
상수도전용 12
 
3.4%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
337 
0
 
20

Length

Max length4
Median length4
Mean length3.8319328
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> 337
94.4%
0 20
 
5.6%

Length

2024-05-11T05:31:21.996208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:22.347645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 337
94.4%
0 20
 
5.6%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)10.0%
Missing267
Missing (%)74.8%
Infinite0
Infinite (%)0.0%
Mean10.844444
Minimum0
Maximum900
Zeros73
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:22.671515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7
Maximum900
Range900
Interquartile range (IQR)0

Descriptive statistics

Standard deviation94.802445
Coefficient of variation (CV)8.7420288
Kurtosis89.905279
Mean10.844444
Median Absolute Deviation (MAD)0
Skewness9.4794577
Sum976
Variance8987.5036
MonotonicityNot monotonic
2024-05-11T05:31:23.011244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 73
 
20.4%
4 3
 
0.8%
7 3
 
0.8%
5 3
 
0.8%
1 3
 
0.8%
3 2
 
0.6%
900 1
 
0.3%
10 1
 
0.3%
9 1
 
0.3%
(Missing) 267
74.8%
ValueCountFrequency (%)
0 73
20.4%
1 3
 
0.8%
3 2
 
0.6%
4 3
 
0.8%
5 3
 
0.8%
7 3
 
0.8%
9 1
 
0.3%
10 1
 
0.3%
900 1
 
0.3%
ValueCountFrequency (%)
900 1
 
0.3%
10 1
 
0.3%
9 1
 
0.3%
7 3
 
0.8%
5 3
 
0.8%
4 3
 
0.8%
3 2
 
0.6%
1 3
 
0.8%
0 73
20.4%

공장사무직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)12.0%
Missing265
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean4.4456522
Minimum0
Maximum200
Zeros54
Zeros (%)15.1%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:23.335197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6.45
Maximum200
Range200
Interquartile range (IQR)2

Descriptive statistics

Standard deviation22.646041
Coefficient of variation (CV)5.093975
Kurtosis64.060493
Mean4.4456522
Median Absolute Deviation (MAD)0
Skewness7.7470491
Sum409
Variance512.84317
MonotonicityNot monotonic
2024-05-11T05:31:23.730773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 54
 
15.1%
1 13
 
3.6%
3 8
 
2.2%
2 7
 
2.0%
4 3
 
0.8%
6 2
 
0.6%
7 1
 
0.3%
200 1
 
0.3%
28 1
 
0.3%
14 1
 
0.3%
(Missing) 265
74.2%
ValueCountFrequency (%)
0 54
15.1%
1 13
 
3.6%
2 7
 
2.0%
3 8
 
2.2%
4 3
 
0.8%
6 2
 
0.6%
7 1
 
0.3%
14 1
 
0.3%
28 1
 
0.3%
85 1
 
0.3%
ValueCountFrequency (%)
200 1
 
0.3%
85 1
 
0.3%
28 1
 
0.3%
14 1
 
0.3%
7 1
 
0.3%
6 2
 
0.6%
4 3
 
0.8%
3 8
2.2%
2 7
2.0%
1 13
3.6%

공장판매직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)11.2%
Missing268
Missing (%)75.1%
Infinite0
Infinite (%)0.0%
Mean3.8202247
Minimum0
Maximum200
Zeros62
Zeros (%)17.4%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:24.140954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4.6
Maximum200
Range200
Interquartile range (IQR)1

Descriptive statistics

Standard deviation21.96876
Coefficient of variation (CV)5.7506459
Kurtosis74.487805
Mean3.8202247
Median Absolute Deviation (MAD)0
Skewness8.3986315
Sum340
Variance482.6264
MonotonicityNot monotonic
2024-05-11T05:31:24.562200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 62
 
17.4%
1 11
 
3.1%
2 5
 
1.4%
3 4
 
1.1%
4 2
 
0.6%
5 1
 
0.3%
200 1
 
0.3%
10 1
 
0.3%
45 1
 
0.3%
39 1
 
0.3%
(Missing) 268
75.1%
ValueCountFrequency (%)
0 62
17.4%
1 11
 
3.1%
2 5
 
1.4%
3 4
 
1.1%
4 2
 
0.6%
5 1
 
0.3%
10 1
 
0.3%
39 1
 
0.3%
45 1
 
0.3%
200 1
 
0.3%
ValueCountFrequency (%)
200 1
 
0.3%
45 1
 
0.3%
39 1
 
0.3%
10 1
 
0.3%
5 1
 
0.3%
4 2
 
0.6%
3 4
 
1.1%
2 5
 
1.4%
1 11
 
3.1%
0 62
17.4%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
269 
0
81 
1
 
4
3
 
1
400
 
1

Length

Max length4
Median length4
Mean length3.2661064
Min length1

Unique

Unique3 ?
Unique (%)0.8%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 269
75.4%
0 81
 
22.7%
1 4
 
1.1%
3 1
 
0.3%
400 1
 
0.3%
5 1
 
0.3%

Length

2024-05-11T05:31:25.170243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:25.581118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 269
75.4%
0 81
 
22.7%
1 4
 
1.1%
3 1
 
0.3%
400 1
 
0.3%
5 1
 
0.3%
Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
228 
임대
95 
자가
34 

Length

Max length4
Median length4
Mean length3.2773109
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 228
63.9%
임대 95
26.6%
자가 34
 
9.5%

Length

2024-05-11T05:31:26.165164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:26.605150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
63.9%
임대 95
26.6%
자가 34
 
9.5%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)23.3%
Missing271
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean28173192
Minimum0
Maximum8.8825 × 108
Zeros34
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:27.130461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5000000
Q314750000
95-th percentile46250000
Maximum8.8825 × 108
Range8.8825 × 108
Interquartile range (IQR)14750000

Descriptive statistics

Standard deviation1.2160236 × 108
Coefficient of variation (CV)4.3162437
Kurtosis41.145345
Mean28173192
Median Absolute Deviation (MAD)5000000
Skewness6.4037381
Sum2.4228945 × 109
Variance1.4787135 × 1016
MonotonicityNot monotonic
2024-05-11T05:31:27.612282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 34
 
9.5%
20000000 12
 
3.4%
10000000 11
 
3.1%
5000000 9
 
2.5%
6000000 3
 
0.8%
7500000 2
 
0.6%
30000000 2
 
0.6%
7000000 1
 
0.3%
102804500 1
 
0.3%
712400000 1
 
0.3%
Other values (10) 10
 
2.8%
(Missing) 271
75.9%
ValueCountFrequency (%)
0 34
9.5%
300000 1
 
0.3%
1500000 1
 
0.3%
5000000 9
 
2.5%
6000000 3
 
0.8%
7000000 1
 
0.3%
7500000 2
 
0.6%
10000000 11
 
3.1%
12000000 1
 
0.3%
14000000 1
 
0.3%
ValueCountFrequency (%)
888250000 1
 
0.3%
712400000 1
 
0.3%
102804500 1
 
0.3%
70000000 1
 
0.3%
50000000 1
 
0.3%
35000000 1
 
0.3%
30000000 2
 
0.6%
26640000 1
 
0.3%
20000000 12
3.4%
15000000 1
 
0.3%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)36.0%
Missing271
Missing (%)75.9%
Infinite0
Infinite (%)0.0%
Mean917714.53
Minimum0
Maximum12028000
Zeros35
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-05-11T05:31:27.975108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median400000
Q31200000
95-th percentile2462500
Maximum12028000
Range12028000
Interquartile range (IQR)1200000

Descriptive statistics

Standard deviation1800821.9
Coefficient of variation (CV)1.9622898
Kurtosis24.535685
Mean917714.53
Median Absolute Deviation (MAD)400000
Skewness4.5502971
Sum78923450
Variance3.2429596 × 1012
MonotonicityNot monotonic
2024-05-11T05:31:28.507214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 35
 
9.8%
800000 5
 
1.4%
2000000 5
 
1.4%
600000 4
 
1.1%
500000 3
 
0.8%
400000 2
 
0.6%
1050000 2
 
0.6%
200000 2
 
0.6%
1200000 2
 
0.6%
2100000 2
 
0.6%
Other values (21) 24
 
6.7%
(Missing) 271
75.9%
ValueCountFrequency (%)
0 35
9.8%
50000 1
 
0.3%
100000 2
 
0.6%
150000 1
 
0.3%
200000 2
 
0.6%
350000 1
 
0.3%
400000 2
 
0.6%
500000 3
 
0.8%
550000 2
 
0.6%
600000 4
 
1.1%
ValueCountFrequency (%)
12028000 1
 
0.3%
10280450 1
 
0.3%
3400000 1
 
0.3%
2700000 1
 
0.3%
2500000 1
 
0.3%
2350000 1
 
0.3%
2300000 1
 
0.3%
2200000 2
 
0.6%
2100000 2
 
0.6%
2000000 5
1.4%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing143
Missing (%)40.1%
Memory size846.0 B
False
214 
(Missing)
143 
ValueCountFrequency (%)
False 214
59.9%
(Missing) 143
40.1%
2024-05-11T05:31:28.991839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
0.0
208 
<NA>
143 
16.5
 
2
35.9
 
2
9.0
 
1

Length

Max length5
Median length3
Mean length3.4173669
Min length3

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 208
58.3%
<NA> 143
40.1%
16.5 2
 
0.6%
35.9 2
 
0.6%
9.0 1
 
0.3%
214.2 1
 
0.3%

Length

2024-05-11T05:31:29.457330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T05:31:29.966754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 208
58.3%
na 143
40.1%
16.5 2
 
0.6%
35.9 2
 
0.6%
9.0 1
 
0.3%
214.2 1
 
0.3%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing357
Missing (%)100.0%
Memory size3.3 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031300003130000-135-2004-0000120040323<NA>3폐업2폐업20060614<NA><NA><NA>02 338290417.35121816서울특별시 마포구 동교동 ***-*번지 마젤란** ***호<NA><NA>주식회사 씨케이바이오2005-08-18 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업193248.820008450611.763042건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
131300003130000-135-2004-0000220040416<NA>3폐업2폐업20041122<NA><NA><NA><NA>85.00121050서울특별시 마포구 마포동 ***-*번지 강변한신코아 ****호<NA><NA>주식회사 보령라인2004-05-18 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업194974.587674448229.063825건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
231300003130000-135-2004-0000320040422<NA>3폐업2폐업20051230<NA><NA><NA>02 322598992.60121817서울특별시 마포구 동교동 ***-*번지 엘지팰리스빌딩 ****호<NA><NA>주식회사 자연주의건강나라2004-10-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업193166.430145450425.852791건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>3000임대<NA>200000N0.0<NA><NA><NA>
331300003130000-135-2004-0000420040428<NA>3폐업2폐업20130618<NA><NA><NA>02 3623271198.00121896서울특별시 마포구 서교동 ***-**번지 (*층)서울특별시 마포구 월드컵로**길 * (서교동, (*층))4004주식회사 보청메디칼2012-06-26 17:17:43I2018-08-31 23:59:59.0건강기능식품유통전문판매업192113.076506450351.200527건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0000자가00N0.0<NA><NA><NA>
431300003130000-135-2004-0000520040506<NA>3폐업2폐업20051230<NA><NA><NA>02 322863192.60121817서울특별시 마포구 동교동 ***-*번지 엘지팰리스 ****호<NA><NA>(주)안국건강중앙연구소2004-11-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업193166.430145450425.852791건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>4000임대200000002100000N0.0<NA><NA><NA>
531300003130000-135-2004-0000620040507<NA>3폐업2폐업20060221<NA><NA><NA>02 3346033223.21121150서울특별시 마포구 하중동 **번지 *층<NA><NA>한국그린팜2004-11-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업<NA><NA>건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>7000임대60000002000000N0.0<NA><NA><NA>
631300003130000-135-2004-0000720040507<NA>3폐업2폐업20071218<NA><NA><NA>02 3346033223.21121819서울특별시 마포구 동교동 ***-**번지 동서빌딩 ***호<NA><NA>그린팜신약(주)2006-02-23 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업192811.91326450565.429954건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>7000임대60000002000000N0.0<NA><NA><NA>
731300003130000-135-2004-0000820040602<NA>3폐업2폐업20071012<NA><NA><NA>02 7158568160.00121874서울특별시 마포구 염리동 ***-*번지 벤처비즈니스센터 동관 ***호<NA><NA>(주)에그바이오텍 서울영업소2004-11-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업195065.540737449233.236386건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>5123임대200000002000000N0.0<NA><NA><NA>
831300003130000-135-2004-0000920040614<NA>3폐업2폐업20081208<NA><NA><NA>02 3262766100.00121897서울특별시 마포구 합정동 ***-**번지 춘환빌딩 *층<NA><NA>와이비씨(주)2004-11-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업192429.092869449506.263822건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>1111임대100000002100000N0.0<NA><NA><NA>
931300003130000-135-2004-0001020040614<NA>3폐업2폐업20111013<NA><NA><NA>02 3331344106.00121885서울특별시 마포구 합정동 ***-**번지 흥교빌딩 ***호<NA><NA>동서바이오(주)2004-11-01 00:00:00I2018-08-31 23:59:59.0건강기능식품유통전문판매업<NA><NA>건강기능식품유통전문판매업<NA><NA><NA><NA><NA><NA>0301임대7500000800000N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
34731300003130000-135-2023-000282023-05-15<NA>1영업/정상1영업<NA><NA><NA><NA>070 78028952<NA>121-812서울특별시 마포구 도화동 *** 삼창프라자빌딩 ****호서울특별시 마포구 마포대로 **-*, 삼창프라자빌딩 ****호 (도화동)4157오로망 주식회사2024-01-24 13:30:03I2023-11-30 22:06:00.0건강기능식품유통전문판매업195324.793654448885.430093<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34831300003130000-135-2023-000292023-09-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.00121-763서울특별시 마포구 도화동 ** 창강빌딩 ***호서울특별시 마포구 마포대로 **, 창강빌딩 *층 ***호 (도화동)4168주식회사 인텐더2024-03-06 09:47:50I2023-12-03 00:08:00.0건강기능식품유통전문판매업195568.006694448931.294688<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
34931300003130000-135-2024-000012024-01-12<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-837서울특별시 마포구 서교동 ***-** 군봉빌딩서울특별시 마포구 와우산로 **, 군봉빌딩 *층 L*호 (서교동)4067샵플러2024-01-12 15:08:28I2023-11-30 23:04:00.0건강기능식품유통전문판매업193149.716268449820.686616<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35031300003130000-135-2024-000022024-01-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-715서울특별시 마포구 도화동 **-* 성우빌딩서울특별시 마포구 마포대로 **, 성우빌딩 *층 *호 (도화동)4158주식회사 윈드랩2024-05-02 15:14:04U2023-12-05 00:04:00.0건강기능식품유통전문판매업195237.642733448733.404817<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35131300003130000-135-2024-000032024-02-21<NA>1영업/정상1영업<NA><NA><NA><NA>02 22578883<NA>121-865서울특별시 마포구 연남동 ***-* 연남동고깔집서울특별시 마포구 동교로**길 **, *층 일부호 (연남동, 연남동고깔집)3983주식회사 아이테르글로벌2024-04-04 10:21:49U2023-12-04 00:06:00.0건강기능식품유통전문판매업193248.207821451316.937777<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35231300003130000-135-2024-000042024-02-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-844서울특별시 마포구 성산동 **-* A동 ***호서울특별시 마포구 월드컵북로**길 **, A동 ***호 (성산동)3966지원바이오2024-02-27 14:06:22I2023-12-01 22:09:00.0건강기능식품유통전문판매업192111.859208451277.354521<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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35431300003130000-135-2024-000062024-03-13<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>121-715서울특별시 마포구 도화동 **-* 성우빌딩서울특별시 마포구 마포대로 **, 성우빌딩 *층 *호 (도화동)4158주식회사 넥씨2024-04-24 11:14:16U2023-12-03 22:06:00.0건강기능식품유통전문판매업195237.642733448733.404817<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
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