Overview

Dataset statistics

Number of variables27
Number of observations22
Missing cells166
Missing cells (%)27.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory237.0 B

Variable types

Categorical8
Numeric6
DateTime2
Unsupported6
Text5

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),취급제품명,담배공급업체명
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-19879/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
데이터갱신구분 is highly imbalanced (56.1%)Imbalance
인허가취소일자 has 22 (100.0%) missing valuesMissing
폐업일자 has 11 (50.0%) missing valuesMissing
휴업시작일자 has 22 (100.0%) missing valuesMissing
휴업종료일자 has 22 (100.0%) missing valuesMissing
재개업일자 has 22 (100.0%) missing valuesMissing
전화번호 has 7 (31.8%) missing valuesMissing
소재지면적 has 22 (100.0%) missing valuesMissing
소재지우편번호 has 5 (22.7%) missing valuesMissing
도로명주소 has 1 (4.5%) missing valuesMissing
도로명우편번호 has 8 (36.4%) missing valuesMissing
업태구분명 has 22 (100.0%) missing valuesMissing
담배공급업체명 has 2 (9.1%) missing valuesMissing
관리번호 has unique valuesUnique
지번주소 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 13:12:02.094075
Analysis finished2024-04-06 13:12:02.600295
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
3020000
22 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 22
100.0%

Length

2024-04-06T22:12:02.676588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:02.829301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 22
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0123475 × 1018
Minimum2.001302 × 1018
Maximum2.023302 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:02.992606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001302 × 1018
5-th percentile2.008352 × 1018
Q12.009552 × 1018
median2.011302 × 1018
Q32.015052 × 1018
95-th percentile2.020302 × 1018
Maximum2.023302 × 1018
Range2.2000013 × 1016
Interquartile range (IQR)5.5000041 × 1015

Descriptive statistics

Standard deviation4.7155018 × 1015
Coefficient of variation (CV)0.0023432841
Kurtosis1.4160195
Mean2.0123475 × 1018
Median Absolute Deviation (MAD)2 × 1015
Skewness0.42728844
Sum7.3781561 × 1018
Variance2.2235957 × 1031
MonotonicityStrictly increasing
2024-04-06T22:12:03.201819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2001302007412500001 1
 
4.5%
2011302009515500005 1
 
4.5%
2023302020315500001 1
 
4.5%
2020302015015500002 1
 
4.5%
2020302015015500001 1
 
4.5%
2015302015015500003 1
 
4.5%
2015302015015500002 1
 
4.5%
2015302015015500001 1
 
4.5%
2014302009515500001 1
 
4.5%
2012302009515500001 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2001302007412500001 1
4.5%
2008302009515500001 1
4.5%
2009302009515500001 1
4.5%
2009302009515500002 1
4.5%
2009302009515500003 1
4.5%
2009302009515500004 1
4.5%
2010302009515500001 1
4.5%
2010302009515500002 1
4.5%
2011302009515500001 1
4.5%
2011302009515500002 1
4.5%
ValueCountFrequency (%)
2023302020315500001 1
4.5%
2020302015015500002 1
4.5%
2020302015015500001 1
4.5%
2015302015015500003 1
4.5%
2015302015015500002 1
4.5%
2015302015015500001 1
4.5%
2014302009515500001 1
4.5%
2012302009515500001 1
4.5%
2011302009515500006 1
4.5%
2011302009515500005 1
4.5%

인허가일자
Date

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2001-12-31 00:00:00
Maximum2023-10-04 00:00:00
2024-04-06T22:12:03.448197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:12:03.729987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

영업상태코드
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
11 
3
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 11
50.0%
3 11
50.0%

Length

2024-04-06T22:12:03.935198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:04.108015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
50.0%
3 11
50.0%

영업상태명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
영업/정상
11 
폐업
11 

Length

Max length5
Median length3.5
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 11
50.0%
폐업 11
50.0%

Length

2024-04-06T22:12:04.305581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:04.543645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 11
50.0%
폐업 11
50.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
11 
3
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 11
50.0%
3 11
50.0%

Length

2024-04-06T22:12:04.759348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:04.944052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
50.0%
3 11
50.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
정상영업
11 
폐업처리
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정상영업
2nd row폐업처리
3rd row폐업처리
4th row폐업처리
5th row폐업처리

Common Values

ValueCountFrequency (%)
정상영업 11
50.0%
폐업처리 11
50.0%

Length

2024-04-06T22:12:05.147600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:05.342419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 11
50.0%
폐업처리 11
50.0%

폐업일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)100.0%
Missing11
Missing (%)50.0%
Infinite0
Infinite (%)0.0%
Mean20142238
Minimum20100225
Maximum20180427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:05.541926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100225
5-th percentile20100276
Q120115622
median20150210
Q320165367
95-th percentile20175827
Maximum20180427
Range80202
Interquartile range (IQR)49745

Descriptive statistics

Standard deviation30295.328
Coefficient of variation (CV)0.0015040697
Kurtosis-1.3780856
Mean20142238
Median Absolute Deviation (MAD)20193
Skewness-0.46372189
Sum2.2156462 × 108
Variance9.1780693 × 108
MonotonicityNot monotonic
2024-04-06T22:12:05.795338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20100225 1
 
4.5%
20130329 1
 
4.5%
20140110 1
 
4.5%
20100326 1
 
4.5%
20100915 1
 
4.5%
20180427 1
 
4.5%
20171227 1
 
4.5%
20170403 1
 
4.5%
20150210 1
 
4.5%
20160331 1
 
4.5%
(Missing) 11
50.0%
ValueCountFrequency (%)
20100225 1
4.5%
20100326 1
4.5%
20100915 1
4.5%
20130329 1
4.5%
20140110 1
4.5%
20150210 1
4.5%
20160112 1
4.5%
20160331 1
4.5%
20170403 1
4.5%
20171227 1
4.5%
ValueCountFrequency (%)
20180427 1
4.5%
20171227 1
4.5%
20170403 1
4.5%
20160331 1
4.5%
20160112 1
4.5%
20150210 1
4.5%
20140110 1
4.5%
20130329 1
4.5%
20100915 1
4.5%
20100326 1
4.5%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

전화번호
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing7
Missing (%)31.8%
Memory size308.0 B
2024-04-06T22:12:06.138752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.7333333
Min length8

Characters and Unicode

Total characters146
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

Unique15 ?
Unique (%)100.0%

Sample

1st row790-4522
2nd row537-5510
3rd row701-6218
4th row070-7581-7111
5th row703-4558
ValueCountFrequency (%)
790-4522 1
 
6.7%
537-5510 1
 
6.7%
701-6218 1
 
6.7%
070-7581-7111 1
 
6.7%
703-4558 1
 
6.7%
714-8883 1
 
6.7%
2012-0889 1
 
6.7%
2012-2025 1
 
6.7%
790-2443 1
 
6.7%
701-5665 1
 
6.7%
Other values (5) 5
33.3%
2024-04-06T22:12:06.702927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 21
14.4%
0 20
13.7%
1 20
13.7%
7 18
12.3%
2 18
12.3%
8 14
9.6%
5 11
7.5%
4 7
 
4.8%
9 6
 
4.1%
3 6
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 125
85.6%
Dash Punctuation 21
 
14.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
16.0%
1 20
16.0%
7 18
14.4%
2 18
14.4%
8 14
11.2%
5 11
8.8%
4 7
 
5.6%
9 6
 
4.8%
3 6
 
4.8%
6 5
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 146
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 21
14.4%
0 20
13.7%
1 20
13.7%
7 18
12.3%
2 18
12.3%
8 14
9.6%
5 11
7.5%
4 7
 
4.8%
9 6
 
4.1%
3 6
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 21
14.4%
0 20
13.7%
1 20
13.7%
7 18
12.3%
2 18
12.3%
8 14
9.6%
5 11
7.5%
4 7
 
4.8%
9 6
 
4.1%
3 6
 
4.1%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)70.6%
Missing5
Missing (%)22.7%
Infinite0
Infinite (%)0.0%
Mean140353.06
Minimum140012
Maximum140879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:06.948231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum140012
5-th percentile140012.8
Q1140013
median140140
Q3140848
95-th percentile140878.2
Maximum140879
Range867
Interquartile range (IQR)835

Descriptive statistics

Standard deviation387.45701
Coefficient of variation (CV)0.0027605883
Kurtosis-1.7288903
Mean140353.06
Median Absolute Deviation (MAD)127
Skewness0.62588606
Sum2386002
Variance150122.93
MonotonicityNot monotonic
2024-04-06T22:12:07.161809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
140013 4
18.2%
140113 2
 
9.1%
140873 2
 
9.1%
140150 1
 
4.5%
140879 1
 
4.5%
140848 1
 
4.5%
140791 1
 
4.5%
140878 1
 
4.5%
140160 1
 
4.5%
140012 1
 
4.5%
Other values (2) 2
 
9.1%
(Missing) 5
22.7%
ValueCountFrequency (%)
140012 1
 
4.5%
140013 4
18.2%
140113 2
9.1%
140120 1
 
4.5%
140140 1
 
4.5%
140150 1
 
4.5%
140160 1
 
4.5%
140791 1
 
4.5%
140848 1
 
4.5%
140873 2
9.1%
ValueCountFrequency (%)
140879 1
4.5%
140878 1
4.5%
140873 2
9.1%
140848 1
4.5%
140791 1
4.5%
140160 1
4.5%
140150 1
4.5%
140140 1
4.5%
140120 1
4.5%
140113 2
9.1%

지번주소
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-06T22:12:07.590241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36.5
Mean length33.454545
Min length20

Characters and Unicode

Total characters736
Distinct characters75
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 이태원동 261-41
2nd row서울특별시 용산구 갈월동 103번지 15호
3rd row서울특별시 용산구 한강로3가 16번지 9호 전자랜드본관 C-118,119,122,123
4th row서울특별시 용산구 한강로3가 16번지 9호 전자랜드본관1층A-132
5th row서울특별시 용산구 원효로3가 51번지 30호 4동9열14호
ValueCountFrequency (%)
서울특별시 22
 
14.6%
용산구 22
 
14.6%
한강로3가 7
 
4.6%
16번지 6
 
4.0%
2층 4
 
2.6%
원효로3가 3
 
2.0%
1호 3
 
2.0%
30호 3
 
2.0%
51번지 3
 
2.0%
한강로2가 3
 
2.0%
Other values (65) 75
49.7%
2024-04-06T22:12:08.338336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
129
 
17.5%
1 43
 
5.8%
호 33
 
4.5%
2 27
 
3.7%
3 26
 
3.5%
구 23
 
3.1%
서 23
 
3.1%
특 23
 
3.1%
산 22
 
3.0%
별 22
 
3.0%
Other values (65) 365
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428
58.2%
Decimal Number 168
 
22.8%
Space Separator 129
 
17.5%
Dash Punctuation 4
 
0.5%
Uppercase Letter 4
 
0.5%
Other Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 33
 
7.7%
구 23
 
5.4%
서 23
 
5.4%
특 23
 
5.4%
산 22
 
5.1%
별 22
 
5.1%
시 22
 
5.1%
울 22
 
5.1%
용 22
 
5.1%
지 21
 
4.9%
Other values (48) 195
45.6%
Decimal Number
ValueCountFrequency (%)
1 43
25.6%
2 27
16.1%
3 26
15.5%
5 17
 
10.1%
0 12
 
7.1%
9 12
 
7.1%
6 11
 
6.5%
8 7
 
4.2%
4 7
 
4.2%
7 6
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
S 1
25.0%
G 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 428
58.2%
Common 304
41.3%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 33
 
7.7%
구 23
 
5.4%
서 23
 
5.4%
특 23
 
5.4%
산 22
 
5.1%
별 22
 
5.1%
시 22
 
5.1%
울 22
 
5.1%
용 22
 
5.1%
지 21
 
4.9%
Other values (48) 195
45.6%
Common
ValueCountFrequency (%)
129
42.4%
1 43
 
14.1%
2 27
 
8.9%
3 26
 
8.6%
5 17
 
5.6%
0 12
 
3.9%
9 12
 
3.9%
6 11
 
3.6%
8 7
 
2.3%
4 7
 
2.3%
Other values (3) 13
 
4.3%
Latin
ValueCountFrequency (%)
C 1
25.0%
S 1
25.0%
G 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428
58.2%
ASCII 308
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
129
41.9%
1 43
 
14.0%
2 27
 
8.8%
3 26
 
8.4%
5 17
 
5.5%
0 12
 
3.9%
9 12
 
3.9%
6 11
 
3.6%
8 7
 
2.3%
4 7
 
2.3%
Other values (7) 17
 
5.5%
Hangul
ValueCountFrequency (%)
호 33
 
7.7%
구 23
 
5.4%
서 23
 
5.4%
특 23
 
5.4%
산 22
 
5.1%
별 22
 
5.1%
시 22
 
5.1%
울 22
 
5.1%
용 22
 
5.1%
지 21
 
4.9%
Other values (48) 195
45.6%

도로명주소
Text

MISSING 

Distinct21
Distinct (%)100.0%
Missing1
Missing (%)4.5%
Memory size308.0 B
2024-04-06T22:12:08.661808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length37.47619
Min length24

Characters and Unicode

Total characters787
Distinct characters82
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row서울특별시 용산구 소월로38길 25, 2층동호 (이태원동)
2nd row서울특별시 용산구 한강대로 251 (갈월동)
3rd row서울특별시 용산구 청파로 74 (한강로3가,전자랜드본관 C-118,119,122,123)
4th row서울특별시 용산구 청파로 74 (한강로3가,전자랜드본관1층A-132)
5th row서울특별시 용산구 이촌로 1, 305호 (한강로3가,GS한강에클라트)
ValueCountFrequency (%)
서울특별시 21
 
14.3%
용산구 21
 
14.3%
청파로 8
 
5.4%
2층 6
 
4.1%
이태원동 3
 
2.0%
1층 3
 
2.0%
한강로2가 2
 
1.4%
한강로3가 2
 
1.4%
3층 2
 
1.4%
2
 
1.4%
Other values (68) 77
52.4%
2024-04-06T22:12:09.258306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
 
16.0%
1 36
 
4.6%
로 34
 
4.3%
2 31
 
3.9%
, 29
 
3.7%
서 22
 
2.8%
특 22
 
2.8%
구 22
 
2.8%
3 22
 
2.8%
울 21
 
2.7%
Other values (72) 422
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 434
55.1%
Decimal Number 148
 
18.8%
Space Separator 126
 
16.0%
Other Punctuation 29
 
3.7%
Open Punctuation 21
 
2.7%
Close Punctuation 21
 
2.7%
Dash Punctuation 4
 
0.5%
Uppercase Letter 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 34
 
7.8%
서 22
 
5.1%
특 22
 
5.1%
구 22
 
5.1%
울 21
 
4.8%
용 21
 
4.8%
시 21
 
4.8%
산 21
 
4.8%
별 21
 
4.8%
가 18
 
4.1%
Other values (53) 211
48.6%
Decimal Number
ValueCountFrequency (%)
1 36
24.3%
2 31
20.9%
3 22
14.9%
5 16
10.8%
7 12
 
8.1%
8 10
 
6.8%
0 8
 
5.4%
4 6
 
4.1%
6 5
 
3.4%
9 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
G 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 434
55.1%
Common 349
44.3%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 34
 
7.8%
서 22
 
5.1%
특 22
 
5.1%
구 22
 
5.1%
울 21
 
4.8%
용 21
 
4.8%
시 21
 
4.8%
산 21
 
4.8%
별 21
 
4.8%
가 18
 
4.1%
Other values (53) 211
48.6%
Common
ValueCountFrequency (%)
126
36.1%
1 36
 
10.3%
2 31
 
8.9%
, 29
 
8.3%
3 22
 
6.3%
( 21
 
6.0%
) 21
 
6.0%
5 16
 
4.6%
7 12
 
3.4%
8 10
 
2.9%
Other values (5) 25
 
7.2%
Latin
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
G 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 434
55.1%
ASCII 353
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
35.7%
1 36
 
10.2%
2 31
 
8.8%
, 29
 
8.2%
3 22
 
6.2%
( 21
 
5.9%
) 21
 
5.9%
5 16
 
4.5%
7 12
 
3.4%
8 10
 
2.8%
Other values (9) 29
 
8.2%
Hangul
ValueCountFrequency (%)
로 34
 
7.8%
서 22
 
5.1%
특 22
 
5.1%
구 22
 
5.1%
울 21
 
4.8%
용 21
 
4.8%
시 21
 
4.8%
산 21
 
4.8%
별 21
 
4.8%
가 18
 
4.1%
Other values (53) 211
48.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)85.7%
Missing8
Missing (%)36.4%
Infinite0
Infinite (%)0.0%
Mean91793.571
Minimum4342
Maximum140881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:09.580748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4342
5-th percentile4344.6
Q14384.25
median140113
Q3140155
95-th percentile140875.8
Maximum140881
Range136539
Interquartile range (IQR)135770.75

Descriptive statistics

Standard deviation67626.172
Coefficient of variation (CV)0.73672013
Kurtosis-1.8383648
Mean91793.571
Median Absolute Deviation (MAD)760
Skewness-0.67028996
Sum1285110
Variance4.5732991 × 109
MonotonicityNot monotonic
2024-04-06T22:12:09.824543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
140113 2
 
9.1%
140873 2
 
9.1%
4342 1
 
4.5%
140881 1
 
4.5%
140013 1
 
4.5%
140160 1
 
4.5%
140140 1
 
4.5%
140120 1
 
4.5%
4363 1
 
4.5%
4346 1
 
4.5%
Other values (2) 2
 
9.1%
(Missing) 8
36.4%
ValueCountFrequency (%)
4342 1
4.5%
4346 1
4.5%
4363 1
4.5%
4382 1
4.5%
4391 1
4.5%
140013 1
4.5%
140113 2
9.1%
140120 1
4.5%
140140 1
4.5%
140160 1
4.5%
ValueCountFrequency (%)
140881 1
4.5%
140873 2
9.1%
140160 1
4.5%
140140 1
4.5%
140120 1
4.5%
140113 2
9.1%
140013 1
4.5%
4391 1
4.5%
4382 1
4.5%
4363 1
4.5%

사업장명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-06T22:12:10.171687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.6363636
Min length3

Characters and Unicode

Total characters146
Distinct characters82
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row(주)피에르
2nd row삼미정보시스템(주)
3rd row가전마트
4th row세원랜드
5th row태양산업
ValueCountFrequency (%)
주식회사 2
 
7.7%
주)피에르 1
 
3.8%
뉴페이스 1
 
3.8%
주)더리셋컴퍼니 1
 
3.8%
주)서륭홀딩스 1
 
3.8%
코리아 1
 
3.8%
베이퍼파이 1
 
3.8%
메모렛에프엠 1
 
3.8%
월드모바일 1
 
3.8%
trading 1
 
3.8%
Other values (15) 15
57.7%
2024-04-06T22:12:10.671858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 11
 
7.5%
( 9
 
6.2%
) 9
 
6.2%
이 6
 
4.1%
스 4
 
2.7%
4
 
2.7%
서 3
 
2.1%
리 3
 
2.1%
코 3
 
2.1%
씨 3
 
2.1%
Other values (72) 91
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 115
78.8%
Open Punctuation 9
 
6.2%
Close Punctuation 9
 
6.2%
Uppercase Letter 9
 
6.2%
Space Separator 4
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 11
 
9.6%
이 6
 
5.2%
스 4
 
3.5%
서 3
 
2.6%
리 3
 
2.6%
코 3
 
2.6%
씨 3
 
2.6%
트 3
 
2.6%
사 3
 
2.6%
일 2
 
1.7%
Other values (61) 74
64.3%
Uppercase Letter
ValueCountFrequency (%)
J 2
22.2%
N 1
11.1%
G 1
11.1%
I 1
11.1%
D 1
11.1%
A 1
11.1%
T 1
11.1%
R 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 115
78.8%
Common 22
 
15.1%
Latin 9
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 11
 
9.6%
이 6
 
5.2%
스 4
 
3.5%
서 3
 
2.6%
리 3
 
2.6%
코 3
 
2.6%
씨 3
 
2.6%
트 3
 
2.6%
사 3
 
2.6%
일 2
 
1.7%
Other values (61) 74
64.3%
Latin
ValueCountFrequency (%)
J 2
22.2%
N 1
11.1%
G 1
11.1%
I 1
11.1%
D 1
11.1%
A 1
11.1%
T 1
11.1%
R 1
11.1%
Common
ValueCountFrequency (%)
( 9
40.9%
) 9
40.9%
4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 115
78.8%
ASCII 31
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 11
 
9.6%
이 6
 
5.2%
스 4
 
3.5%
서 3
 
2.6%
리 3
 
2.6%
코 3
 
2.6%
씨 3
 
2.6%
트 3
 
2.6%
사 3
 
2.6%
일 2
 
1.7%
Other values (61) 74
64.3%
ASCII
ValueCountFrequency (%)
( 9
29.0%
) 9
29.0%
4
12.9%
J 2
 
6.5%
N 1
 
3.2%
G 1
 
3.2%
I 1
 
3.2%
D 1
 
3.2%
A 1
 
3.2%
T 1
 
3.2%

최종수정일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2010-02-25 17:35:42
Maximum2023-10-04 16:30:20
2024-04-06T22:12:10.895380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:12:11.084530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
I
20 
U
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 20
90.9%
U 2
 
9.1%

Length

2024-04-06T22:12:11.319120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:11.470687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 20
90.9%
u 2
 
9.1%

데이터갱신일자
Categorical

Distinct6
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
2018-08-31 23:59:59.0
17 
2022-12-01 00:08:00.0
 
1
2018-10-20 02:38:03.0
 
1
2020-01-25 00:23:24.0
 
1
2020-04-03 00:23:21.0
 
1

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique5 ?
Unique (%)22.7%

Sample

1st row2022-12-01 00:08:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 17
77.3%
2022-12-01 00:08:00.0 1
 
4.5%
2018-10-20 02:38:03.0 1
 
4.5%
2020-01-25 00:23:24.0 1
 
4.5%
2020-04-03 00:23:21.0 1
 
4.5%
2022-10-31 00:06:00.0 1
 
4.5%

Length

2024-04-06T22:12:11.651960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:11.853878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 17
38.6%
23:59:59.0 17
38.6%
2022-12-01 1
 
2.3%
00:08:00.0 1
 
2.3%
2018-10-20 1
 
2.3%
02:38:03.0 1
 
2.3%
2020-01-25 1
 
2.3%
00:23:24.0 1
 
2.3%
2020-04-03 1
 
2.3%
00:23:21.0 1
 
2.3%
Other values (2) 2
 
4.5%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

좌표정보(X)
Real number (ℝ)

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean197058.53
Minimum196003.39
Maximum199400.14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:12.073800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196003.39
5-th percentile196008.57
Q1196385.23
median196772.06
Q3197433.46
95-th percentile199293.45
Maximum199400.14
Range3396.7512
Interquartile range (IQR)1048.232

Descriptive statistics

Standard deviation1008.4782
Coefficient of variation (CV)0.0051176581
Kurtosis1.237747
Mean197058.53
Median Absolute Deviation (MAD)398.51577
Skewness1.4195153
Sum4335287.6
Variance1017028.2
MonotonicityNot monotonic
2024-04-06T22:12:12.313545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
196385.232032928 3
13.6%
196370.746398773 2
 
9.1%
196762.077394917 2
 
9.1%
196893.277042114 2
 
9.1%
199080.297312228 1
 
4.5%
196782.051428934 1
 
4.5%
199304.665313377 1
 
4.5%
197625.004033597 1
 
4.5%
199400.138925466 1
 
4.5%
196003.387714155 1
 
4.5%
Other values (7) 7
31.8%
ValueCountFrequency (%)
196003.387714155 1
 
4.5%
196005.836412851 1
 
4.5%
196060.559012563 1
 
4.5%
196370.746398773 2
9.1%
196385.232032928 3
13.6%
196727.535753619 1
 
4.5%
196762.077394917 2
9.1%
196782.051428934 1
 
4.5%
196873.001604976 1
 
4.5%
196893.277042114 2
9.1%
ValueCountFrequency (%)
199400.138925466 1
4.5%
199304.665313377 1
4.5%
199080.297312228 1
4.5%
197625.004033597 1
4.5%
197527.373328357 1
4.5%
197522.026115161 1
4.5%
197167.777938912 1
4.5%
196893.277042114 2
9.1%
196873.001604976 1
4.5%
196782.051428934 1
4.5%

좌표정보(Y)
Real number (ℝ)

Distinct17
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean448170.35
Minimum447480.04
Maximum450288.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T22:12:12.505327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447480.04
5-th percentile447491.03
Q1447843.72
median447932.21
Q3448401.77
95-th percentile448997.38
Maximum450288.56
Range2808.5222
Interquartile range (IQR)558.05205

Descriptive statistics

Standard deviation654.40615
Coefficient of variation (CV)0.0014601728
Kurtosis4.1345608
Mean448170.35
Median Absolute Deviation (MAD)144.95381
Skewness1.8835609
Sum9859747.8
Variance428247.41
MonotonicityNot monotonic
2024-04-06T22:12:12.674381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
447938.19246116 3
13.6%
447841.698787531 2
 
9.1%
447480.039577359 2
 
9.1%
447852.583272453 2
 
9.1%
448997.8287628 1
 
4.5%
448884.157128816 1
 
4.5%
447926.22119855 1
 
4.5%
447849.769432346 1
 
4.5%
448471.798997026 1
 
4.5%
448191.676991839 1
 
4.5%
Other values (7) 7
31.8%
ValueCountFrequency (%)
447480.039577359 2
9.1%
447699.758814725 1
 
4.5%
447732.807254308 1
 
4.5%
447841.698787531 2
9.1%
447849.769432346 1
 
4.5%
447852.583272453 2
9.1%
447868.128308607 1
 
4.5%
447926.22119855 1
 
4.5%
447938.19246116 3
13.6%
447960.206197372 1
 
4.5%
ValueCountFrequency (%)
450288.561776513 1
 
4.5%
448997.8287628 1
 
4.5%
448988.800115619 1
 
4.5%
448884.157128816 1
 
4.5%
448724.835326921 1
 
4.5%
448471.798997026 1
 
4.5%
448191.676991839 1
 
4.5%
447960.206197372 1
 
4.5%
447938.19246116 3
13.6%
447926.22119855 1
 
4.5%

취급제품명
Categorical

Distinct10
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
전자담배
12 
<NA>
2 
담배(위고6종, 스윙2종 등 총 8종)
 
1
PEEL, DJ MIX
 
1
전자담배 액상
 
1
Other values (5)
5 

Length

Max length21
Median length4
Mean length6.5454545
Min length4

Unique

Unique8 ?
Unique (%)36.4%

Sample

1st row<NA>
2nd row담배(위고6종, 스윙2종 등 총 8종)
3rd row전자담배
4th row전자담배
5th row전자담배

Common Values

ValueCountFrequency (%)
전자담배 12
54.5%
<NA> 2
 
9.1%
담배(위고6종, 스윙2종 등 총 8종) 1
 
4.5%
PEEL, DJ MIX 1
 
4.5%
전자담배 액상 1
 
4.5%
(주)엘가 전자담배 1
 
4.5%
전자담배 니코틴 액상 1
 
4.5%
전자담배용 액상 1
 
4.5%
일회용 전자담배 외 5종 1
 
4.5%
액상전자담배 1
 
4.5%

Length

2024-04-06T22:12:12.908494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:12:13.166511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전자담배 16
44.4%
액상 3
 
8.3%
na 2
 
5.6%
5종 1
 
2.8%
외 1
 
2.8%
일회용 1
 
2.8%
전자담배용 1
 
2.8%
니코틴 1
 
2.8%
주)엘가 1
 
2.8%
mix 1
 
2.8%
Other values (8) 8
22.2%

담배공급업체명
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-04-06T22:12:13.482072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length8.35
Min length2

Characters and Unicode

Total characters167
Distinct characters79
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row우리담배
2nd row제로스, 아바테, 잔티
3rd row(주)잔티코리아
4th row한국전자담배
5th rowCNK Trading Company
ValueCountFrequency (%)
우리담배 1
 
3.7%
솔루션 1
 
3.7%
global 1
 
3.7%
ecs 1
 
3.7%
주)짚코리아 1
 
3.7%
베이퍼파이 1
 
3.7%
주)에바코생활건강 1
 
3.7%
스타버즈코리아 1
 
3.7%
lrider 1
 
3.7%
주)데캉 1
 
3.7%
Other values (17) 17
63.0%
2024-04-06T22:12:14.079399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 9
 
5.4%
) 9
 
5.4%
주 9
 
5.4%
7
 
4.2%
코 6
 
3.6%
C 6
 
3.6%
L 5
 
3.0%
아 5
 
3.0%
리 5
 
3.0%
, 3
 
1.8%
Other values (69) 103
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
53.9%
Uppercase Letter 29
 
17.4%
Lowercase Letter 17
 
10.2%
Open Punctuation 9
 
5.4%
Close Punctuation 9
 
5.4%
Space Separator 7
 
4.2%
Other Punctuation 6
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 9
 
10.0%
코 6
 
6.7%
아 5
 
5.6%
리 5
 
5.6%
이 3
 
3.3%
배 3
 
3.3%
담 3
 
3.3%
에 2
 
2.2%
캉 2
 
2.2%
디 2
 
2.2%
Other values (40) 50
55.6%
Uppercase Letter
ValueCountFrequency (%)
C 6
20.7%
L 5
17.2%
E 3
10.3%
T 3
10.3%
G 2
 
6.9%
A 2
 
6.9%
O 2
 
6.9%
S 1
 
3.4%
N 1
 
3.4%
K 1
 
3.4%
Other values (3) 3
10.3%
Lowercase Letter
ValueCountFrequency (%)
r 3
17.6%
n 2
11.8%
d 2
11.8%
i 2
11.8%
a 2
11.8%
e 1
 
5.9%
y 1
 
5.9%
g 1
 
5.9%
o 1
 
5.9%
m 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
. 3
50.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
53.9%
Latin 46
27.5%
Common 31
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 9
 
10.0%
코 6
 
6.7%
아 5
 
5.6%
리 5
 
5.6%
이 3
 
3.3%
배 3
 
3.3%
담 3
 
3.3%
에 2
 
2.2%
캉 2
 
2.2%
디 2
 
2.2%
Other values (40) 50
55.6%
Latin
ValueCountFrequency (%)
C 6
 
13.0%
L 5
 
10.9%
E 3
 
6.5%
T 3
 
6.5%
r 3
 
6.5%
n 2
 
4.3%
G 2
 
4.3%
A 2
 
4.3%
O 2
 
4.3%
d 2
 
4.3%
Other values (14) 16
34.8%
Common
ValueCountFrequency (%)
( 9
29.0%
) 9
29.0%
7
22.6%
, 3
 
9.7%
. 3
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
53.9%
ASCII 77
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 9
 
11.7%
) 9
 
11.7%
7
 
9.1%
C 6
 
7.8%
L 5
 
6.5%
, 3
 
3.9%
. 3
 
3.9%
E 3
 
3.9%
T 3
 
3.9%
r 3
 
3.9%
Other values (19) 26
33.8%
Hangul
ValueCountFrequency (%)
주 9
 
10.0%
코 6
 
6.7%
아 5
 
5.6%
리 5
 
5.6%
이 3
 
3.3%
배 3
 
3.3%
담 3
 
3.3%
에 2
 
2.2%
캉 2
 
2.2%
디 2
 
2.2%
Other values (40) 50
55.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)취급제품명담배공급업체명
03020000200130200741250000120011231<NA>1영업/정상1정상영업<NA><NA><NA><NA>790-4522<NA><NA>서울특별시 용산구 이태원동 261-41서울특별시 용산구 소월로38길 25, 2층동호 (이태원동)4342(주)피에르2023-01-06 17:50:38U2022-12-01 00:08:00.0<NA>199080.297312448997.828763<NA><NA>
13020000200830200951550000120080714<NA>3폐업3폐업처리20100225<NA><NA><NA>537-5510<NA>140150서울특별시 용산구 갈월동 103번지 15호서울특별시 용산구 한강대로 251 (갈월동)<NA>삼미정보시스템(주)2010-02-25 17:35:42I2018-08-31 23:59:59.0<NA>197522.026115448724.835327담배(위고6종, 스윙2종 등 총 8종)우리담배
23020000200930200951550000120090603<NA>3폐업3폐업처리20130329<NA><NA><NA><NA><NA>140013서울특별시 용산구 한강로3가 16번지 9호 전자랜드본관 C-118,119,122,123서울특별시 용산구 청파로 74 (한강로3가,전자랜드본관 C-118,119,122,123)<NA>가전마트2013-04-02 15:30:02I2018-08-31 23:59:59.0<NA>196370.746399447841.698788전자담배제로스, 아바테, 잔티
33020000200930200951550000220090603<NA>3폐업3폐업처리20140110<NA><NA><NA><NA><NA>140879서울특별시 용산구 한강로3가 16번지 9호 전자랜드본관1층A-132서울특별시 용산구 청파로 74 (한강로3가,전자랜드본관1층A-132)<NA>세원랜드2014-01-10 16:25:31I2018-08-31 23:59:59.0<NA>196370.746399447841.698788전자담배(주)잔티코리아
43020000200930200951550000320090611<NA>3폐업3폐업처리20100326<NA><NA><NA>701-6218<NA>140848서울특별시 용산구 원효로3가 51번지 30호 4동9열14호<NA><NA>태양산업2010-03-29 19:35:51I2018-08-31 23:59:59.0<NA>196385.232033447938.192461전자담배한국전자담배
53020000200930200951550000420091113<NA>3폐업3폐업처리20100915<NA><NA><NA>070-7581-7111<NA>140791서울특별시 용산구 한강로3가 16번지 85호 GS한강에클라트 305호서울특별시 용산구 이촌로 1, 305호 (한강로3가,GS한강에클라트)<NA>(주)디케이엔티2010-10-21 09:42:17I2018-08-31 23:59:59.0<NA>196005.836413447699.758815PEEL, DJ MIXCNK Trading Company
63020000201030200951550000120101021<NA>3폐업3폐업처리20180427<NA><NA><NA><NA><NA>140878서울특별시 용산구 한강로3가 3번지 23호 나진 15동 지하특1호서울특별시 용산구 청파로 112, 15동 지하특1호 (한강로3가,나진)<NA>(주)소울2018-10-18 11:35:26U2018-10-20 02:38:03.0<NA>196727.535754447868.128309전자담배(주)한국전자담배
73020000201030200951550000220101229<NA>3폐업3폐업처리20171227<NA><NA><NA>703-4558<NA>140113서울특별시 용산구 원효로3가 51번지 30호 원효전자상가 6동 2층 102호서울특별시 용산구 청파로 77, 6동 2층 102호 (원효로3가, 원효전자상가 )140113(주)헬씨코리아2017-12-27 16:20:38I2018-08-31 23:59:59.0<NA>196385.232033447938.192461전자담배EIGATE.CO.,LTD
83020000201130200951550000120110118<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA>140113서울특별시 용산구 원효로3가 51번지 30호 원효전자상가 6동 2층 57호서울특별시 용산구 청파로 77, 6동 2층 57호 (원효로3가, 원효전자상가 )140113세일종합상사2013-12-31 14:56:37I2018-08-31 23:59:59.0<NA>196385.232033447938.192461전자담배(주)에니코
93020000201130200951550000220110304<NA>1영업/정상1정상영업<NA><NA><NA><NA>714-8883<NA>140013서울특별시 용산구 한강로3가 16번지 49호 삼구빌딩 1811호서울특별시 용산구 청파로 40 (한강로3가,삼구빌딩 1811호)<NA>(주)와이투엔제이2011-03-07 10:16:07I2018-08-31 23:59:59.0<NA>196060.559013447732.807254전자담배(주)알론코리아
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)취급제품명담배공급업체명
123020000201130200951550000520110524<NA>1영업/정상1정상영업<NA><NA><NA><NA>790-2443<NA>140160서울특별시 용산구 남영동 65번지 5호 2층서울특별시 용산구 한강대로 278-2, 2층 (남영동)140160스마트존2011-10-31 17:36:51I2018-08-31 23:59:59.0<NA>197527.373328448988.800116전자담배데캉
133020000201130200951550000620110829<NA>1영업/정상1정상영업<NA><NA><NA><NA>701-5665<NA>140012서울특별시 용산구 한강로2가 15번지 2호 나진상가 17동 2층 나열 203호서울특별시 용산구 청파로 125 (한강로2가,나진상가 17동 2층 나열 203호)<NA>뉴페이스2011-08-30 12:15:07I2018-08-31 23:59:59.0<NA>196873.001605447960.206197(주)엘가 전자담배(주)엘가
143020000201230200951550000120120110<NA>3폐업3폐업처리20150210<NA><NA><NA>210-81-19478<NA>140140서울특별시 용산구 서계동 219번지 1호 창성빌딩 5층서울특별시 용산구 청파로 395 (서계동, 창성빌딩5층)140140(주)서연씨엠씨2015-02-17 11:02:46I2018-08-31 23:59:59.0<NA>197167.777939450288.561777전자담배(주)데캉
153020000201430200951550000120141113<NA>3폐업3폐업처리20160331<NA><NA><NA>070-8867-7941<NA>140120서울특별시 용산구 효창동 5번지 3호 2층좌측 가칭01호서울특별시 용산구 효창원로70길 46, 2층 (효창동, 좌측 가칭01호)140120JJ TRADING2016-03-31 11:22:37I2018-08-31 23:59:59.0<NA>196782.051429448884.157129전자담배Lrider
163020000201530201501550000120150211<NA>3폐업3폐업처리20160112<NA><NA><NA>02-2120-2318<NA>140873서울특별시 용산구 한강로2가 16번지 1호 선인상가 21동 35호서울특별시 용산구 새창로 181, 21동 2층 35호 (한강로2가)140873월드모바일2016-01-12 15:41:34I2018-08-31 23:59:59.0<NA>196893.277042447852.583272전자담배스타버즈코리아
173020000201530201501550000220150211<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA>140873서울특별시 용산구 한강로2가 16번지 1호 선인상가 21동 3153호서울특별시 용산구 새창로 181, 21동 3층 3153호 (한강로2가)140873주식회사 메모렛에프엠2015-02-11 17:55:54I2018-08-31 23:59:59.0<NA>196893.277042447852.583272전자담배 니코틴 액상(주)에바코생활건강
183020000201530201501550000320150504<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 신창동 77번지 73호서울특별시 용산구 효창원로 58, 1층 (신창동)4363베이퍼파이 코리아2015-11-12 15:17:44I2018-08-31 23:59:59.0<NA>196003.387714448191.676992전자담배용 액상베이퍼파이
193020000202030201501550000120200122<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-778-3161<NA><NA>서울특별시 용산구 이태원동 208번지 18호서울특별시 용산구 회나무로28길 62, 1층 (이태원동)4346(주)서륭홀딩스2020-01-23 09:02:59I2020-01-25 00:23:24.0<NA>199400.138925448471.798997일회용 전자담배 외 5종(주)짚코리아
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