Overview

Dataset statistics

Number of variables20
Number of observations357
Missing cells2405
Missing cells (%)33.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.4 KiB
Average record size in memory170.4 B

Variable types

Categorical6
Text6
DateTime2
Unsupported3
Numeric3

Dataset

Description담배 도매업 정보 현황_인허가
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=IPV2JFJMUQ0N0P6MKVEY14064142&infSeq=1

Alerts

Y좌표값 is highly overall correlated with 소재지우편번호 and 7 other fieldsHigh correlation
X좌표값 is highly overall correlated with 소재지우편번호 and 7 other fieldsHigh correlation
영업상태구분코드 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 6 other fieldsHigh correlation
영업상태명 is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
도로명우편번호 is highly overall correlated with 소재지우편번호 and 7 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84경도 and 5 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
영업상태구분코드 is highly imbalanced (95.1%)Imbalance
도로명우편번호 is highly imbalanced (95.8%)Imbalance
X좌표값 is highly imbalanced (96.5%)Imbalance
Y좌표값 is highly imbalanced (96.5%)Imbalance
인허가취소일자 has 357 (100.0%) missing valuesMissing
폐업일자 has 192 (53.8%) missing valuesMissing
소재지시설전화번호 has 355 (99.4%) missing valuesMissing
소재지면적정보 has 357 (100.0%) missing valuesMissing
소재지도로명주소 has 23 (6.4%) missing valuesMissing
WGS84위도 has 26 (7.3%) missing valuesMissing
WGS84경도 has 26 (7.3%) missing valuesMissing
업태구분명정보 has 357 (100.0%) missing valuesMissing
취급제품명정보 has 354 (99.2%) missing valuesMissing
담배공급업체명 has 354 (99.2%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:16:14.344679
Analysis finished2023-12-10 21:16:16.467005
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
성남시
52 
부천시
44 
고양시
29 
수원시
28 
안산시
23 
Other values (25)
181 

Length

Max length4
Median length3
Mean length3.0868347
Min length3

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
성남시 52
14.6%
부천시 44
12.3%
고양시 29
 
8.1%
수원시 28
 
7.8%
안산시 23
 
6.4%
남양주시 20
 
5.6%
안양시 17
 
4.8%
용인시 14
 
3.9%
화성시 13
 
3.6%
이천시 12
 
3.4%
Other values (20) 105
29.4%

Length

2023-12-11T06:16:16.539215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 52
14.6%
부천시 44
12.3%
고양시 29
 
8.1%
수원시 28
 
7.8%
안산시 23
 
6.4%
남양주시 20
 
5.6%
안양시 17
 
4.8%
용인시 14
 
3.9%
화성시 13
 
3.6%
이천시 12
 
3.4%
Other values (20) 105
29.4%

사업장명
Text

Distinct335
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
2023-12-11T06:16:16.795599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.7703081
Min length2

Characters and Unicode

Total characters2774
Distinct characters317
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

Unique324 ?
Unique (%)90.8%

Sample

1st row우리담배 가평점
2nd row우리담배
3rd row(주)레이벤엔터프라이즈
4th row유로스타
5th row트러스트베이비
ValueCountFrequency (%)
한국전자담배 20
 
4.4%
주식회사 20
 
4.4%
우리담배 11
 
2.4%
타박앤패밀리 7
 
1.5%
전자담배 6
 
1.3%
주)타박앤패밀리 4
 
0.9%
스누스맨 4
 
0.9%
파스타바코 4
 
0.9%
카토전자담배프라자 3
 
0.7%
에바코 3
 
0.7%
Other values (357) 373
82.0%
2023-12-11T06:16:17.204077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 128
 
4.6%
주 115
 
4.1%
98
 
3.5%
) 89
 
3.2%
( 89
 
3.2%
담 84
 
3.0%
배 84
 
3.0%
점 82
 
3.0%
스 73
 
2.6%
자 60
 
2.2%
Other values (307) 1872
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2424
87.4%
Space Separator 98
 
3.5%
Close Punctuation 89
 
3.2%
Open Punctuation 89
 
3.2%
Uppercase Letter 45
 
1.6%
Other Punctuation 11
 
0.4%
Decimal Number 11
 
0.4%
Lowercase Letter 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 128
 
5.3%
주 115
 
4.7%
담 84
 
3.5%
배 84
 
3.5%
점 82
 
3.4%
스 73
 
3.0%
자 60
 
2.5%
대 60
 
2.5%
전 57
 
2.4%
사 56
 
2.3%
Other values (275) 1625
67.0%
Uppercase Letter
ValueCountFrequency (%)
T 6
13.3%
D 5
11.1%
G 5
11.1%
L 4
8.9%
E 4
8.9%
F 3
 
6.7%
C 3
 
6.7%
S 3
 
6.7%
Y 2
 
4.4%
I 2
 
4.4%
Other values (6) 8
17.8%
Decimal Number
ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
4 2
18.2%
5 2
18.2%
0 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 3
42.9%
t 1
 
14.3%
i 1
 
14.3%
s 1
 
14.3%
r 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
& 5
45.5%
, 3
27.3%
. 3
27.3%
Space Separator
ValueCountFrequency (%)
98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Open Punctuation
ValueCountFrequency (%)
( 89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2424
87.4%
Common 298
 
10.7%
Latin 52
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 128
 
5.3%
주 115
 
4.7%
담 84
 
3.5%
배 84
 
3.5%
점 82
 
3.4%
스 73
 
3.0%
자 60
 
2.5%
대 60
 
2.5%
전 57
 
2.4%
사 56
 
2.3%
Other values (275) 1625
67.0%
Latin
ValueCountFrequency (%)
T 6
11.5%
D 5
 
9.6%
G 5
 
9.6%
L 4
 
7.7%
E 4
 
7.7%
o 3
 
5.8%
F 3
 
5.8%
C 3
 
5.8%
S 3
 
5.8%
Y 2
 
3.8%
Other values (11) 14
26.9%
Common
ValueCountFrequency (%)
98
32.9%
) 89
29.9%
( 89
29.9%
& 5
 
1.7%
2 4
 
1.3%
, 3
 
1.0%
. 3
 
1.0%
1 2
 
0.7%
4 2
 
0.7%
5 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2424
87.4%
ASCII 350
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 128
 
5.3%
주 115
 
4.7%
담 84
 
3.5%
배 84
 
3.5%
점 82
 
3.4%
스 73
 
3.0%
자 60
 
2.5%
대 60
 
2.5%
전 57
 
2.4%
사 56
 
2.3%
Other values (275) 1625
67.0%
ASCII
ValueCountFrequency (%)
98
28.0%
) 89
25.4%
( 89
25.4%
T 6
 
1.7%
& 5
 
1.4%
D 5
 
1.4%
G 5
 
1.4%
L 4
 
1.1%
E 4
 
1.1%
2 4
 
1.1%
Other values (22) 41
11.7%

인허가일자
Date

Distinct312
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
Minimum1995-06-02 00:00:00
Maximum2023-10-12 00:00:00
2023-12-11T06:16:17.342748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:17.462245image/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

영업상태구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
354 
1
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.9747899
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
99.2%
1 2
 
0.6%
3 1
 
0.3%

Length

2023-12-11T06:16:17.572588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:17.665394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 354
99.2%
1 2
 
0.6%
3 1
 
0.3%

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
폐업 등
186 
운영중
168 
정상영업
 
2
폐업처리
 
1

Length

Max length4
Median length4
Mean length3.5294118
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 등 186
52.1%
운영중 168
47.1%
정상영업 2
 
0.6%
폐업처리 1
 
0.3%

Length

2023-12-11T06:16:17.763630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:18.076246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 186
34.3%
등 186
34.3%
운영중 168
30.9%
정상영업 2
 
0.4%
폐업처리 1
 
0.2%

폐업일자
Date

MISSING 

Distinct144
Distinct (%)87.3%
Missing192
Missing (%)53.8%
Memory size2.9 KiB
Minimum2005-01-19 00:00:00
Maximum2023-10-16 00:00:00
2023-12-11T06:16:18.171275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:18.283215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing355
Missing (%)99.4%
Memory size2.9 KiB
2023-12-11T06:16:18.403021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12.5
Mean length12.5
Min length12

Characters and Unicode

Total characters25
Distinct characters10
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

Unique2 ?
Unique (%)100.0%

Sample

1st row070-8645-6864
2nd row031-723-8805
ValueCountFrequency (%)
070-8645-6864 1
50.0%
031-723-8805 1
50.0%
2023-12-11T06:16:18.613694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
16.0%
- 4
16.0%
8 4
16.0%
6 3
12.0%
7 2
8.0%
4 2
8.0%
5 2
8.0%
3 2
8.0%
1 1
 
4.0%
2 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
84.0%
Dash Punctuation 4
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
19.0%
8 4
19.0%
6 3
14.3%
7 2
9.5%
4 2
9.5%
5 2
9.5%
3 2
9.5%
1 1
 
4.8%
2 1
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
16.0%
- 4
16.0%
8 4
16.0%
6 3
12.0%
7 2
8.0%
4 2
8.0%
5 2
8.0%
3 2
8.0%
1 1
 
4.0%
2 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
16.0%
- 4
16.0%
8 4
16.0%
6 3
12.0%
7 2
8.0%
4 2
8.0%
5 2
8.0%
3 2
8.0%
1 1
 
4.0%
2 1
 
4.0%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

도로명우편번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
354 
12223
 
1
13443
 
1
10865
 
1

Length

Max length5
Median length4
Mean length4.0084034
Min length4

Unique

Unique3 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 354
99.2%
12223 1
 
0.3%
13443 1
 
0.3%
10865 1
 
0.3%

Length

2023-12-11T06:16:18.726344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:18.833923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 354
99.2%
12223 1
 
0.3%
13443 1
 
0.3%
10865 1
 
0.3%

소재지도로명주소
Text

MISSING 

Distinct324
Distinct (%)97.0%
Missing23
Missing (%)6.4%
Memory size2.9 KiB
2023-12-11T06:16:19.053656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length42
Mean length29.308383
Min length14

Characters and Unicode

Total characters9789
Distinct characters330
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

Unique315 ?
Unique (%)94.3%

Sample

1st row경기도 가평군 청평면 경춘로 807-12
2nd row경기도 고양시 덕양구 통일로 140, B동 B227호 (동산동, 삼송테크노벨리)
3rd row경기도 고양시 덕양구 통일로 140, b동 251층 1호 (동산동, 삼송테크노밸리)
4th row경기도 고양시 덕양구 고골길84번길 24, 가동 (관산동)
5th row경기도 고양시 덕양구 대덕로141번길 23, 2층 (현천동)
ValueCountFrequency (%)
경기도 334
 
16.3%
성남시 45
 
2.2%
부천시 44
 
2.2%
고양시 28
 
1.4%
수원시 27
 
1.3%
안산시 23
 
1.1%
수정구 19
 
0.9%
남양주시 18
 
0.9%
안양시 17
 
0.8%
단원구 16
 
0.8%
Other values (930) 1474
72.1%
2023-12-11T06:16:19.408631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1722
 
17.6%
1 398
 
4.1%
경 363
 
3.7%
기 351
 
3.6%
시 349
 
3.6%
도 346
 
3.5%
동 334
 
3.4%
로 312
 
3.2%
) 266
 
2.7%
( 266
 
2.7%
Other values (320) 5082
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5543
56.6%
Space Separator 1722
 
17.6%
Decimal Number 1666
 
17.0%
Close Punctuation 266
 
2.7%
Open Punctuation 266
 
2.7%
Other Punctuation 227
 
2.3%
Dash Punctuation 77
 
0.8%
Uppercase Letter 12
 
0.1%
Lowercase Letter 8
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 363
 
6.5%
기 351
 
6.3%
시 349
 
6.3%
도 346
 
6.2%
동 334
 
6.0%
로 312
 
5.6%
구 162
 
2.9%
길 141
 
2.5%
호 127
 
2.3%
번 109
 
2.0%
Other values (293) 2949
53.2%
Decimal Number
ValueCountFrequency (%)
1 398
23.9%
2 240
14.4%
0 200
12.0%
3 176
10.6%
4 139
 
8.3%
6 124
 
7.4%
5 123
 
7.4%
7 100
 
6.0%
8 87
 
5.2%
9 79
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 6
50.0%
S 2
 
16.7%
C 1
 
8.3%
I 1
 
8.3%
E 1
 
8.3%
F 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
k 3
37.5%
s 2
25.0%
b 1
 
12.5%
t 1
 
12.5%
n 1
 
12.5%
Space Separator
ValueCountFrequency (%)
1722
100.0%
Close Punctuation
ValueCountFrequency (%)
) 266
100.0%
Open Punctuation
ValueCountFrequency (%)
( 266
100.0%
Other Punctuation
ValueCountFrequency (%)
, 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5543
56.6%
Common 4226
43.2%
Latin 20
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 363
 
6.5%
기 351
 
6.3%
시 349
 
6.3%
도 346
 
6.2%
동 334
 
6.0%
로 312
 
5.6%
구 162
 
2.9%
길 141
 
2.5%
호 127
 
2.3%
번 109
 
2.0%
Other values (293) 2949
53.2%
Common
ValueCountFrequency (%)
1722
40.7%
1 398
 
9.4%
) 266
 
6.3%
( 266
 
6.3%
2 240
 
5.7%
, 227
 
5.4%
0 200
 
4.7%
3 176
 
4.2%
4 139
 
3.3%
6 124
 
2.9%
Other values (6) 468
 
11.1%
Latin
ValueCountFrequency (%)
B 6
30.0%
k 3
15.0%
S 2
 
10.0%
s 2
 
10.0%
C 1
 
5.0%
I 1
 
5.0%
E 1
 
5.0%
F 1
 
5.0%
b 1
 
5.0%
t 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5543
56.6%
ASCII 4246
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1722
40.6%
1 398
 
9.4%
) 266
 
6.3%
( 266
 
6.3%
2 240
 
5.7%
, 227
 
5.3%
0 200
 
4.7%
3 176
 
4.1%
4 139
 
3.3%
6 124
 
2.9%
Other values (17) 488
 
11.5%
Hangul
ValueCountFrequency (%)
경 363
 
6.5%
기 351
 
6.3%
시 349
 
6.3%
도 346
 
6.2%
동 334
 
6.0%
로 312
 
5.6%
구 162
 
2.9%
길 141
 
2.5%
호 127
 
2.3%
번 109
 
2.0%
Other values (293) 2949
53.2%

소재지지번주소
Text

Distinct346
Distinct (%)97.7%
Missing3
Missing (%)0.8%
Memory size2.9 KiB
2023-12-11T06:16:19.663079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length41
Mean length26.903955
Min length11

Characters and Unicode

Total characters9524
Distinct characters294
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

Unique339 ?
Unique (%)95.8%

Sample

1st row경기도 가평군 청평면 청평리 470번지 37호 청구아파트 상가 204호
2nd row경기도 가평군 가평읍 읍내리 495번지 32호
3rd row경기도 고양시 덕양구 동산동 376번지
4th row경기도 고양시 덕양구 동산동 376번지 삼송테크노밸리 B동 251층 1호
5th row경기도 고양시 덕양구 관산동 576번지 12호 가동
ValueCountFrequency (%)
경기도 354
 
16.5%
1호 50
 
2.3%
부천시 44
 
2.0%
2호 30
 
1.4%
1층 27
 
1.3%
성남시 23
 
1.1%
고양시 21
 
1.0%
남양주시 20
 
0.9%
수원시 20
 
0.9%
3호 19
 
0.9%
Other values (860) 1541
71.7%
2023-12-11T06:16:20.039855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1826
19.2%
1 487
 
5.1%
동 376
 
3.9%
지 368
 
3.9%
호 361
 
3.8%
도 361
 
3.8%
기 360
 
3.8%
경 360
 
3.8%
시 360
 
3.8%
번 344
 
3.6%
Other values (284) 4321
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5648
59.3%
Decimal Number 1973
 
20.7%
Space Separator 1826
 
19.2%
Dash Punctuation 38
 
0.4%
Uppercase Letter 14
 
0.1%
Lowercase Letter 7
 
0.1%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Other Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 376
 
6.7%
지 368
 
6.5%
호 361
 
6.4%
도 361
 
6.4%
기 360
 
6.4%
경 360
 
6.4%
시 360
 
6.4%
번 344
 
6.1%
구 170
 
3.0%
양 93
 
1.6%
Other values (257) 2495
44.2%
Decimal Number
ValueCountFrequency (%)
1 487
24.7%
2 242
12.3%
0 234
11.9%
3 184
 
9.3%
6 164
 
8.3%
4 164
 
8.3%
5 162
 
8.2%
7 142
 
7.2%
8 104
 
5.3%
9 90
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 6
42.9%
E 2
 
14.3%
S 2
 
14.3%
A 1
 
7.1%
I 1
 
7.1%
C 1
 
7.1%
F 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
k 3
42.9%
s 2
28.6%
t 1
 
14.3%
n 1
 
14.3%
Space Separator
ValueCountFrequency (%)
1826
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5648
59.3%
Common 3855
40.5%
Latin 21
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 376
 
6.7%
지 368
 
6.5%
호 361
 
6.4%
도 361
 
6.4%
기 360
 
6.4%
경 360
 
6.4%
시 360
 
6.4%
번 344
 
6.1%
구 170
 
3.0%
양 93
 
1.6%
Other values (257) 2495
44.2%
Common
ValueCountFrequency (%)
1826
47.4%
1 487
 
12.6%
2 242
 
6.3%
0 234
 
6.1%
3 184
 
4.8%
6 164
 
4.3%
4 164
 
4.3%
5 162
 
4.2%
7 142
 
3.7%
8 104
 
2.7%
Other values (6) 146
 
3.8%
Latin
ValueCountFrequency (%)
B 6
28.6%
k 3
14.3%
E 2
 
9.5%
s 2
 
9.5%
S 2
 
9.5%
A 1
 
4.8%
I 1
 
4.8%
C 1
 
4.8%
t 1
 
4.8%
F 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5648
59.3%
ASCII 3876
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1826
47.1%
1 487
 
12.6%
2 242
 
6.2%
0 234
 
6.0%
3 184
 
4.7%
6 164
 
4.2%
4 164
 
4.2%
5 162
 
4.2%
7 142
 
3.7%
8 104
 
2.7%
Other values (17) 167
 
4.3%
Hangul
ValueCountFrequency (%)
동 376
 
6.7%
지 368
 
6.5%
호 361
 
6.4%
도 361
 
6.4%
기 360
 
6.4%
경 360
 
6.4%
시 360
 
6.4%
번 344
 
6.1%
구 170
 
3.0%
양 93
 
1.6%
Other values (257) 2495
44.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)79.5%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean361809.52
Minimum10024
Maximum487826
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T06:16:20.156234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10024
5-th percentile12144
Q1412808.5
median430931
Q3461814.5
95-th percentile473862.5
Maximum487826
Range477802
Interquartile range (IQR)49006

Descriptive statistics

Standard deviation170476.17
Coefficient of variation (CV)0.47117656
Kurtosis0.4233559
Mean361809.52
Median Absolute Deviation (MAD)23391
Skewness-1.5286084
Sum1.2880419 × 108
Variance2.9062123 × 1010
MonotonicityNot monotonic
2023-12-11T06:16:20.264242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
410380 5
 
1.4%
420852 4
 
1.1%
461190 4
 
1.1%
430010 4
 
1.1%
467852 4
 
1.1%
467010 3
 
0.8%
431060 3
 
0.8%
462708 3
 
0.8%
425802 3
 
0.8%
471020 3
 
0.8%
Other values (273) 320
89.6%
ValueCountFrequency (%)
10024 1
0.3%
10125 1
0.3%
10126 1
0.3%
10239 1
0.3%
10265 1
0.3%
10403 1
0.3%
10517 1
0.3%
10541 1
0.3%
10594 1
0.3%
10844 1
0.3%
ValueCountFrequency (%)
487826 3
0.8%
487040 1
 
0.3%
486803 1
 
0.3%
483060 1
 
0.3%
482841 1
 
0.3%
482110 1
 
0.3%
482080 1
 
0.3%
482050 1
 
0.3%
480865 1
 
0.3%
480060 1
 
0.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct309
Distinct (%)93.4%
Missing26
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean37.434705
Minimum36.945818
Maximum38.103169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T06:16:20.367145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.945818
5-th percentile37.150726
Q137.3103
median37.437581
Q337.53572
95-th percentile37.738349
Maximum38.103169
Range1.1573508
Interquartile range (IQR)0.22542077

Descriptive statistics

Standard deviation0.18446277
Coefficient of variation (CV)0.004927587
Kurtosis0.13646742
Mean37.434705
Median Absolute Deviation (MAD)0.12658566
Skewness0.14288283
Sum12390.887
Variance0.034026512
MonotonicityNot monotonic
2023-12-11T06:16:20.488953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4464876393 4
 
1.1%
37.3124595232 3
 
0.8%
37.4375813159 3
 
0.8%
37.253965762 2
 
0.6%
37.4847529871 2
 
0.6%
37.5026236887 2
 
0.6%
37.5178248661 2
 
0.6%
37.4038838787 2
 
0.6%
37.395540011 2
 
0.6%
37.6034076993 2
 
0.6%
Other values (299) 307
86.0%
(Missing) 26
 
7.3%
ValueCountFrequency (%)
36.9458180686 1
0.3%
36.9898628732 1
0.3%
36.9916115733 1
0.3%
36.9923626736 1
0.3%
37.0074469648 1
0.3%
37.0366486537 2
0.6%
37.0389004806 1
0.3%
37.0441809663 1
0.3%
37.0509104053 1
0.3%
37.0572178152 1
0.3%
ValueCountFrequency (%)
38.1031688783 1
0.3%
37.9147702355 1
0.3%
37.8975432782 1
0.3%
37.8250235848 1
0.3%
37.8204585318 1
0.3%
37.8118196249 1
0.3%
37.7910936484 1
0.3%
37.7882702486 1
0.3%
37.7739219501 1
0.3%
37.7634069361 1
0.3%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct309
Distinct (%)93.4%
Missing26
Missing (%)7.3%
Infinite0
Infinite (%)0.0%
Mean127.00467
Minimum126.55857
Maximum127.63826
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2023-12-11T06:16:20.655283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55857
5-th percentile126.75379
Q1126.82097
median127.02622
Q3127.13603
95-th percentile127.38777
Maximum127.63826
Range1.079688
Interquartile range (IQR)0.31505378

Descriptive statistics

Standard deviation0.19499733
Coefficient of variation (CV)0.0015353556
Kurtosis0.0010994118
Mean127.00467
Median Absolute Deviation (MAD)0.13890177
Skewness0.51900172
Sum42038.545
Variance0.03802396
MonotonicityNot monotonic
2023-12-11T06:16:20.806885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1294315035 4
 
1.1%
126.8491227412 3
 
0.8%
127.1408585751 3
 
0.8%
127.0203178416 2
 
0.6%
126.7526867001 2
 
0.6%
126.7608015036 2
 
0.6%
126.7658569038 2
 
0.6%
126.9197414551 2
 
0.6%
126.9702722876 2
 
0.6%
126.7703412229 2
 
0.6%
Other values (299) 307
86.0%
(Missing) 26
 
7.3%
ValueCountFrequency (%)
126.5585703929 1
0.3%
126.7232107016 1
0.3%
126.7240825563 1
0.3%
126.7305531149 1
0.3%
126.7316325983 1
0.3%
126.7336777542 1
0.3%
126.7437186898 1
0.3%
126.7438732269 1
0.3%
126.7450164681 1
0.3%
126.7487684905 1
0.3%
ValueCountFrequency (%)
127.6382584085 1
0.3%
127.5481191635 1
0.3%
127.5244337477 1
0.3%
127.5105881226 1
0.3%
127.5025366752 1
0.3%
127.5019117665 1
0.3%
127.5013979764 1
0.3%
127.4931323694 1
0.3%
127.4769329342 2
0.6%
127.4646218859 1
0.3%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

X좌표값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
355 
220821.11917728
 
1
207303.10214361
 
1

Length

Max length15
Median length4
Mean length4.0616246
Min length4

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 355
99.4%
220821.11917728 1
 
0.3%
207303.10214361 1
 
0.3%

Length

2023-12-11T06:16:20.989528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:21.101708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 355
99.4%
220821.11917728 1
 
0.3%
207303.10214361 1
 
0.3%

Y좌표값
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.9 KiB
<NA>
355 
460582.820741139
 
1
436867.938163387
 
1

Length

Max length16
Median length4
Mean length4.0672269
Min length4

Unique

Unique2 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 355
99.4%
460582.820741139 1
 
0.3%
436867.938163387 1
 
0.3%

Length

2023-12-11T06:16:21.246083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:16:21.385145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 355
99.4%
460582.820741139 1
 
0.3%
436867.938163387 1
 
0.3%

취급제품명정보
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing354
Missing (%)99.2%
Memory size2.9 KiB
2023-12-11T06:16:21.558424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length6.6666667
Min length5

Characters and Unicode

Total characters20
Distinct characters18
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

Unique3 ?
Unique (%)100.0%

Sample

1st row전자담배액상
2nd row시가(Cigar)
3rd row중화 담배
ValueCountFrequency (%)
전자담배액상 1
25.0%
시가(cigar 1
25.0%
중화 1
25.0%
담배 1
25.0%
2023-12-11T06:16:21.830887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
담 2
 
10.0%
배 2
 
10.0%
전 1
 
5.0%
i 1
 
5.0%
화 1
 
5.0%
중 1
 
5.0%
) 1
 
5.0%
r 1
 
5.0%
a 1
 
5.0%
g 1
 
5.0%
Other values (8) 8
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12
60.0%
Lowercase Letter 4
 
20.0%
Close Punctuation 1
 
5.0%
Uppercase Letter 1
 
5.0%
Open Punctuation 1
 
5.0%
Space Separator 1
 
5.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
담 2
16.7%
배 2
16.7%
전 1
8.3%
화 1
8.3%
중 1
8.3%
자 1
8.3%
가 1
8.3%
시 1
8.3%
상 1
8.3%
액 1
8.3%
Lowercase Letter
ValueCountFrequency (%)
i 1
25.0%
r 1
25.0%
a 1
25.0%
g 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12
60.0%
Latin 5
25.0%
Common 3
 
15.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
담 2
16.7%
배 2
16.7%
전 1
8.3%
화 1
8.3%
중 1
8.3%
자 1
8.3%
가 1
8.3%
시 1
8.3%
상 1
8.3%
액 1
8.3%
Latin
ValueCountFrequency (%)
i 1
20.0%
r 1
20.0%
a 1
20.0%
g 1
20.0%
C 1
20.0%
Common
ValueCountFrequency (%)
) 1
33.3%
( 1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12
60.0%
ASCII 8
40.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
담 2
16.7%
배 2
16.7%
전 1
8.3%
화 1
8.3%
중 1
8.3%
자 1
8.3%
가 1
8.3%
시 1
8.3%
상 1
8.3%
액 1
8.3%
ASCII
ValueCountFrequency (%)
i 1
12.5%
) 1
12.5%
r 1
12.5%
a 1
12.5%
g 1
12.5%
C 1
12.5%
( 1
12.5%
1
12.5%

담배공급업체명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing354
Missing (%)99.2%
Memory size2.9 KiB
2023-12-11T06:16:22.004965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length19
Min length5

Characters and Unicode

Total characters57
Distinct characters26
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowvaporver biotech co., ltd
2nd rowOscar Valladares Tobacco&Co
3rd row씨케이티티
ValueCountFrequency (%)
vaporver 1
12.5%
biotech 1
12.5%
co 1
12.5%
ltd 1
12.5%
oscar 1
12.5%
valladares 1
12.5%
tobacco&co 1
12.5%
씨케이티티 1
12.5%
2023-12-11T06:16:22.344166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 6
 
10.5%
a 6
 
10.5%
c 5
 
8.8%
5
 
8.8%
r 4
 
7.0%
e 3
 
5.3%
l 3
 
5.3%
v 2
 
3.5%
s 2
 
3.5%
d 2
 
3.5%
Other values (16) 19
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40
70.2%
Space Separator 5
 
8.8%
Other Letter 5
 
8.8%
Uppercase Letter 4
 
7.0%
Other Punctuation 3
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.0%
a 6
15.0%
c 5
12.5%
r 4
10.0%
e 3
7.5%
l 3
7.5%
v 2
 
5.0%
s 2
 
5.0%
d 2
 
5.0%
t 2
 
5.0%
Other values (4) 5
12.5%
Other Letter
ValueCountFrequency (%)
티 2
40.0%
씨 1
20.0%
케 1
20.0%
이 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
25.0%
V 1
25.0%
T 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
& 1
33.3%
, 1
33.3%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44
77.2%
Common 8
 
14.0%
Hangul 5
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
13.6%
a 6
13.6%
c 5
11.4%
r 4
9.1%
e 3
 
6.8%
l 3
 
6.8%
v 2
 
4.5%
s 2
 
4.5%
d 2
 
4.5%
t 2
 
4.5%
Other values (8) 9
20.5%
Common
ValueCountFrequency (%)
5
62.5%
. 1
 
12.5%
& 1
 
12.5%
, 1
 
12.5%
Hangul
ValueCountFrequency (%)
티 2
40.0%
씨 1
20.0%
케 1
20.0%
이 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
91.2%
Hangul 5
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 6
11.5%
a 6
11.5%
c 5
 
9.6%
5
 
9.6%
r 4
 
7.7%
e 3
 
5.8%
l 3
 
5.8%
v 2
 
3.8%
s 2
 
3.8%
d 2
 
3.8%
Other values (12) 14
26.9%
Hangul
ValueCountFrequency (%)
티 2
40.0%
씨 1
20.0%
케 1
20.0%
이 1
20.0%

Interactions

2023-12-11T06:16:15.687996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.221410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.457550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.768531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.303679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.530683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.842668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.377297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:16:15.607107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:16:22.474574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태구분코드영업상태명소재지시설전화번호도로명우편번호소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값취급제품명정보담배공급업체명
시군명1.0001.0000.3750.0001.0000.8780.9910.9720.0000.0001.0001.000
영업상태구분코드1.0001.0000.000NaN1.000NaN0.0001.000NaNNaN1.0001.000
영업상태명0.3750.0001.000NaN1.0000.2090.0540.126NaNNaN1.0001.000
소재지시설전화번호0.000NaNNaN1.0000.000NaN0.0000.0000.0000.0000.0000.000
도로명우편번호1.0001.0001.0000.0001.000NaN1.0001.0000.0000.0001.0001.000
소재지우편번호0.878NaN0.209NaNNaN1.0000.4630.886NaNNaNNaNNaN
WGS84위도0.9910.0000.0540.0001.0000.4631.0000.6800.0000.0001.0001.000
WGS84경도0.9721.0000.1260.0001.0000.8860.6801.0000.0000.0001.0001.000
X좌표값0.000NaNNaN0.0000.000NaN0.0000.0001.0000.0000.0000.000
Y좌표값0.000NaNNaN0.0000.000NaN0.0000.0000.0001.0000.0000.000
취급제품명정보1.0001.0001.0000.0001.000NaN1.0001.0000.0000.0001.0001.000
담배공급업체명1.0001.0001.0000.0001.000NaN1.0001.0000.0000.0001.0001.000
2023-12-11T06:16:22.659783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Y좌표값X좌표값영업상태구분코드시군명영업상태명도로명우편번호
Y좌표값1.0001.0001.0001.0001.0001.000
X좌표값1.0001.0001.0001.0001.0001.000
영업상태구분코드1.0001.0001.0001.0000.0001.000
시군명1.0001.0001.0001.0000.1941.000
영업상태명1.0001.0000.0000.1941.0001.000
도로명우편번호1.0001.0001.0001.0001.0001.000
2023-12-11T06:16:22.761947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태구분코드영업상태명도로명우편번호X좌표값Y좌표값
소재지우편번호1.000-0.1460.5740.6251.0000.2001.0001.0001.000
WGS84위도-0.1461.000-0.2190.8200.0000.0311.0001.0001.000
WGS84경도0.574-0.2191.0000.7221.0000.0741.0001.0001.000
시군명0.6250.8200.7221.0001.0000.1941.0001.0001.000
영업상태구분코드1.0000.0001.0001.0001.0000.0001.0001.0001.000
영업상태명0.2000.0310.0740.1940.0001.0001.0001.0001.000
도로명우편번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
X좌표값1.0001.0001.0001.0001.0001.0001.0001.0001.000
Y좌표값1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T06:16:15.964896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:16:16.170634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T06:16:16.346620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값취급제품명정보담배공급업체명
0가평군우리담배 가평점20080314<NA><NA>폐업 등20090915<NA><NA><NA>경기도 가평군 청평면 경춘로 807-12경기도 가평군 청평면 청평리 470번지 37호 청구아파트 상가 204호47781537.738122127.417318<NA><NA><NA><NA><NA>
1가평군우리담배20070927<NA><NA>폐업 등20071128<NA><NA><NA><NA>경기도 가평군 가평읍 읍내리 495번지 32호477805<NA><NA><NA><NA><NA><NA><NA>
2고양시(주)레이벤엔터프라이즈20150331<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 통일로 140, B동 B227호 (동산동, 삼송테크노벨리)경기도 고양시 덕양구 동산동 376번지41209037.64907126.901901<NA><NA><NA><NA><NA>
3고양시유로스타20150828<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 통일로 140, b동 251층 1호 (동산동, 삼송테크노밸리)경기도 고양시 덕양구 동산동 376번지 삼송테크노밸리 B동 251층 1호1059437.64907126.901901<NA><NA><NA><NA><NA>
4고양시트러스트베이비20151102<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 고골길84번길 24, 가동 (관산동)경기도 고양시 덕양구 관산동 576번지 12호 가동1026537.71204126.861323<NA><NA><NA><NA><NA>
5고양시주식회사 와이티티월드20150528<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 덕양구 대덕로141번길 23, 2층 (현천동)경기도 고양시 덕양구 현천동 136번지 2호 2층1054137.59261126.86717<NA><NA><NA><NA><NA>
6고양시유닛코리아20110513<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산동구 중앙로1275번길 38-31경기도 고양시 일산동구 장항동 766번지 외3 일산라페스타 A동 218호41038037.660475126.769613<NA><NA><NA><NA><NA>
7고양시전자담배Y1020110506<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 중앙로 1376경기도 고양시 일산서구 주엽동 75번지 강선마을제상가동제비1층 12호41137037.667812126.766627<NA><NA><NA><NA><NA>
8고양시전자담배에바코(일산점)20090827<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 일현로 122경기도 고양시 일산서구 탄현동 1476번지 동성아파트상가 118호41132037.697615126.766061<NA><NA><NA><NA><NA>
9고양시카스피20090213<NA><NA>운영중<NA><NA><NA><NA>경기도 고양시 일산서구 킨텍스로 340경기도 고양시일산서구 주엽동 14번지 9통 2반 문촌마을 707동 1404호41174837.674915126.756714<NA><NA><NA><NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값취급제품명정보담배공급업체명
347화성시에프씨엠(FCM)20101110<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 장전길 82 (장전동)경기도 화성시 장전동 303번지 2호44514037.265401126.82537<NA><NA><NA><NA><NA>
348화성시농협중앙회 하나로마트분사20080602<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 동탄면 영천로 61경기도 화성시 동탄면 영천리 603번지 1호445813<NA><NA><NA><NA><NA><NA><NA>
349화성시GS25수원대후문점20090831<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 봉담읍 고시길 39경기도 화성시 봉담읍 수기리 1번지 61호44590437.206408126.979722<NA><NA><NA><NA><NA>
350화성시위라이프20110517<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 팔탄면 푸른들판로 892-46경기도 화성시 팔탄면 창곡리 436번지 16호44594937.187195126.888246<NA><NA><NA><NA><NA>
351화성시비전상사20110118<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 경기대로 1071 (진안동)경기도 화성시 진안동 544번지 41호 103호44539037.21054127.032438<NA><NA><NA><NA><NA>
352화성시예스마트20131105<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 향남읍 행정중앙2로 39경기도 화성시 향남읍 행정리 435-4번지1859837.129978126.919689<NA><NA><NA><NA><NA>
353화성시(주)이프지20070702<NA><NA>폐업 등20070824<NA><NA><NA>경기도 화성시 병점중앙로 155 (진안동,렉스몰 5층)경기도 화성시 진안동 514번지 2호 렉스몰 5층44539037.211446127.038157<NA><NA><NA><NA><NA>
354화성시비에스코리아20160823<NA><NA>폐업 등20170616<NA><NA><NA>경기도 화성시 매송면 매송로 116경기도 화성시 매송면 숙곡리 422번지 11호1828737.253067126.901979<NA><NA><NA><NA><NA>
355화성시한국전자담배20101223<NA><NA>폐업 등20121016<NA><NA><NA>경기도 화성시 영통로27번길 53경기도 화성시 반월동 868번지 신영통현대타운 214동 1606호44533037.231341127.057505<NA><NA><NA><NA><NA>
356화성시(주)드림네트웍스20150116<NA><NA>폐업 등20151222<NA><NA><NA>경기도 화성시 동탄지성로 14 (반송동)경기도 화성시 반송동 91번지 8호44516037.205149127.072961<NA><NA><NA><NA><NA>