Overview

Dataset statistics

Number of variables44
Number of observations483
Missing cells4321
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory177.0 KiB
Average record size in memory375.3 B

Variable types

Categorical21
Text7
DateTime4
Unsupported7
Numeric4
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18401/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
업태구분명 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
남성종사자수 is highly imbalanced (64.9%)Imbalance
여성종사자수 is highly imbalanced (66.7%)Imbalance
영업장주변구분명 is highly imbalanced (78.2%)Imbalance
등급구분명 is highly imbalanced (76.4%)Imbalance
총인원 is highly imbalanced (55.3%)Imbalance
본사종업원수 is highly imbalanced (55.9%)Imbalance
인허가취소일자 has 483 (100.0%) missing valuesMissing
폐업일자 has 161 (33.3%) missing valuesMissing
휴업시작일자 has 483 (100.0%) missing valuesMissing
휴업종료일자 has 483 (100.0%) missing valuesMissing
재개업일자 has 483 (100.0%) missing valuesMissing
전화번호 has 179 (37.1%) missing valuesMissing
소재지면적 has 28 (5.8%) missing valuesMissing
도로명주소 has 136 (28.2%) missing valuesMissing
도로명우편번호 has 138 (28.6%) missing valuesMissing
좌표정보(X) has 5 (1.0%) missing valuesMissing
좌표정보(Y) has 5 (1.0%) missing valuesMissing
다중이용업소여부 has 143 (29.6%) missing valuesMissing
시설총규모 has 143 (29.6%) missing valuesMissing
전통업소지정번호 has 483 (100.0%) missing valuesMissing
전통업소주된음식 has 483 (100.0%) missing valuesMissing
홈페이지 has 483 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설총규모 has 316 (65.4%) zerosZeros

Reproduction

Analysis started2024-05-10 23:03:39.145580
Analysis finished2024-05-10 23:03:41.111711
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3240000
483 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 483
100.0%

Length

2024-05-10T23:03:41.308040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:03:41.609465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 483
100.0%

관리번호
Text

UNIQUE 

Distinct483
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-05-10T23:03:42.024185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10626
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

Unique483 ?
Unique (%)100.0%

Sample

1st row3240000-113-1996-00455
2nd row3240000-113-1997-00454
3rd row3240000-113-1997-00752
4th row3240000-113-1997-00753
5th row3240000-113-1997-00754
ValueCountFrequency (%)
3240000-113-1996-00455 1
 
0.2%
3240000-113-2015-00025 1
 
0.2%
3240000-113-2020-00007 1
 
0.2%
3240000-113-2020-00006 1
 
0.2%
3240000-113-2020-00005 1
 
0.2%
3240000-113-2020-00004 1
 
0.2%
3240000-113-2020-00003 1
 
0.2%
3240000-113-2020-00002 1
 
0.2%
3240000-113-2020-00001 1
 
0.2%
3240000-113-2019-00023 1
 
0.2%
Other values (473) 473
97.9%
2024-05-10T23:03:42.932322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4197
39.5%
1 1481
 
13.9%
- 1449
 
13.6%
2 1313
 
12.4%
3 1117
 
10.5%
4 591
 
5.6%
9 129
 
1.2%
5 92
 
0.9%
8 88
 
0.8%
7 88
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9177
86.4%
Dash Punctuation 1449
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4197
45.7%
1 1481
 
16.1%
2 1313
 
14.3%
3 1117
 
12.2%
4 591
 
6.4%
9 129
 
1.4%
5 92
 
1.0%
8 88
 
1.0%
7 88
 
1.0%
6 81
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 1449
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10626
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4197
39.5%
1 1481
 
13.9%
- 1449
 
13.6%
2 1313
 
12.4%
3 1117
 
10.5%
4 591
 
5.6%
9 129
 
1.2%
5 92
 
0.9%
8 88
 
0.8%
7 88
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4197
39.5%
1 1481
 
13.9%
- 1449
 
13.6%
2 1313
 
12.4%
3 1117
 
10.5%
4 591
 
5.6%
9 129
 
1.2%
5 92
 
0.9%
8 88
 
0.8%
7 88
 
0.8%
Distinct452
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum1996-09-06 00:00:00
Maximum2024-05-09 00:00:00
2024-05-10T23:03:43.372616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:03:43.796484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
3
322 
1
161 

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 (%)
3 322
66.7%
1 161
33.3%

Length

2024-05-10T23:03:44.189835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:03:44.502746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 322
66.7%
1 161
33.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
322 
영업/정상
161 

Length

Max length5
Median length2
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 322
66.7%
영업/정상 161
33.3%

Length

2024-05-10T23:03:44.868497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:03:45.183754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 322
66.7%
영업/정상 161
33.3%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2
322 
1
161 

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 (%)
2 322
66.7%
1 161
33.3%

Length

2024-05-10T23:03:45.505944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:03:45.815087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 322
66.7%
1 161
33.3%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
폐업
322 
영업
161 

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 322
66.7%
영업 161
33.3%

Length

2024-05-10T23:03:46.131915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:03:46.424621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 322
66.7%
영업 161
33.3%

폐업일자
Date

MISSING 

Distinct275
Distinct (%)85.4%
Missing161
Missing (%)33.3%
Memory size3.9 KiB
Minimum2000-06-27 00:00:00
Maximum2024-03-22 00:00:00
2024-05-10T23:03:46.809178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:03:47.323625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

전화번호
Text

MISSING 

Distinct291
Distinct (%)95.7%
Missing179
Missing (%)37.1%
Memory size3.9 KiB
2024-05-10T23:03:48.064874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.930921
Min length2

Characters and Unicode

Total characters3323
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

Unique282 ?
Unique (%)92.8%

Sample

1st row02 4400783
2nd row02 4282091
3rd row02
4th row02 4299244
5th row02 4850622
ValueCountFrequency (%)
02 229
33.7%
070 33
 
4.9%
470 12
 
1.8%
031 7
 
1.0%
485 6
 
0.9%
471 5
 
0.7%
472 4
 
0.6%
487 4
 
0.6%
488 4
 
0.6%
473 4
 
0.6%
Other values (340) 372
54.7%
2024-05-10T23:03:49.292914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 535
16.1%
520
15.6%
2 468
14.1%
4 375
11.3%
7 269
8.1%
8 267
8.0%
5 207
 
6.2%
1 196
 
5.9%
3 189
 
5.7%
9 153
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2803
84.4%
Space Separator 520
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 535
19.1%
2 468
16.7%
4 375
13.4%
7 269
9.6%
8 267
9.5%
5 207
 
7.4%
1 196
 
7.0%
3 189
 
6.7%
9 153
 
5.5%
6 144
 
5.1%
Space Separator
ValueCountFrequency (%)
520
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 535
16.1%
520
15.6%
2 468
14.1%
4 375
11.3%
7 269
8.1%
8 267
8.0%
5 207
 
6.2%
1 196
 
5.9%
3 189
 
5.7%
9 153
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 535
16.1%
520
15.6%
2 468
14.1%
4 375
11.3%
7 269
8.1%
8 267
8.0%
5 207
 
6.2%
1 196
 
5.9%
3 189
 
5.7%
9 153
 
4.6%

소재지면적
Text

MISSING 

Distinct235
Distinct (%)51.6%
Missing28
Missing (%)5.8%
Memory size3.9 KiB
2024-05-10T23:03:50.082198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length5
Mean length4.9406593
Min length3

Characters and Unicode

Total characters2248
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

Unique185 ?
Unique (%)40.7%

Sample

1st row112.87
2nd row150.00
3rd row76.00
4th row26.90
5th row32.37
ValueCountFrequency (%)
33.00 28
 
6.2%
3.30 23
 
5.1%
9.90 19
 
4.2%
6.60 16
 
3.5%
66.00 15
 
3.3%
10.00 14
 
3.1%
16.50 8
 
1.8%
3.00 8
 
1.8%
26.40 7
 
1.5%
18.00 6
 
1.3%
Other values (225) 311
68.4%
2024-05-10T23:03:51.780136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 649
28.9%
. 455
20.2%
3 203
 
9.0%
1 169
 
7.5%
6 158
 
7.0%
2 130
 
5.8%
5 117
 
5.2%
4 113
 
5.0%
9 110
 
4.9%
8 78
 
3.5%
Other values (2) 66
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1792
79.7%
Other Punctuation 456
 
20.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 649
36.2%
3 203
 
11.3%
1 169
 
9.4%
6 158
 
8.8%
2 130
 
7.3%
5 117
 
6.5%
4 113
 
6.3%
9 110
 
6.1%
8 78
 
4.4%
7 65
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 455
99.8%
, 1
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 649
28.9%
. 455
20.2%
3 203
 
9.0%
1 169
 
7.5%
6 158
 
7.0%
2 130
 
5.8%
5 117
 
5.2%
4 113
 
5.0%
9 110
 
4.9%
8 78
 
3.5%
Other values (2) 66
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 649
28.9%
. 455
20.2%
3 203
 
9.0%
1 169
 
7.5%
6 158
 
7.0%
2 130
 
5.8%
5 117
 
5.2%
4 113
 
5.0%
9 110
 
4.9%
8 78
 
3.5%
Other values (2) 66
 
2.9%
Distinct108
Distinct (%)22.4%
Missing1
Missing (%)0.2%
Memory size3.9 KiB
2024-05-10T23:03:52.890667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2012448
Min length6

Characters and Unicode

Total characters2989
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

Unique34 ?
Unique (%)7.1%

Sample

1st row134825
2nd row134857
3rd row134851
4th row134838
5th row134817
ValueCountFrequency (%)
134814 31
 
6.4%
134-814 23
 
4.8%
134851 21
 
4.4%
134874 18
 
3.7%
134843 14
 
2.9%
134817 13
 
2.7%
134850 13
 
2.7%
134868 13
 
2.7%
134864 13
 
2.7%
134848 12
 
2.5%
Other values (98) 311
64.5%
2024-05-10T23:03:54.476649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 682
22.8%
1 651
21.8%
8 552
18.5%
3 545
18.2%
5 105
 
3.5%
0 100
 
3.3%
7 99
 
3.3%
- 97
 
3.2%
6 95
 
3.2%
2 39
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2892
96.8%
Dash Punctuation 97
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 682
23.6%
1 651
22.5%
8 552
19.1%
3 545
18.8%
5 105
 
3.6%
0 100
 
3.5%
7 99
 
3.4%
6 95
 
3.3%
2 39
 
1.3%
9 24
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2989
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 682
22.8%
1 651
21.8%
8 552
18.5%
3 545
18.2%
5 105
 
3.5%
0 100
 
3.3%
7 99
 
3.3%
- 97
 
3.2%
6 95
 
3.2%
2 39
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2989
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 682
22.8%
1 651
21.8%
8 552
18.5%
3 545
18.2%
5 105
 
3.5%
0 100
 
3.3%
7 99
 
3.3%
- 97
 
3.2%
6 95
 
3.2%
2 39
 
1.3%
Distinct423
Distinct (%)87.8%
Missing1
Missing (%)0.2%
Memory size3.9 KiB
2024-05-10T23:03:55.231664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length25.232365
Min length15

Characters and Unicode

Total characters12162
Distinct characters236
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)83.2%

Sample

1st row서울특별시 강동구 명일동 47-7
2nd row서울특별시 강동구 암사동 462-3
3rd row서울특별시 강동구 성내동 553-0
4th row서울특별시 강동구 상일동 329-1
5th row서울특별시 강동구 둔촌동 39-9
ValueCountFrequency (%)
서울특별시 482
19.8%
강동구 482
19.8%
성내동 154
 
6.3%
천호동 101
 
4.1%
길동 101
 
4.1%
암사동 43
 
1.8%
459-3 38
 
1.6%
강동그린타워 37
 
1.5%
둔촌동 27
 
1.1%
2층 22
 
0.9%
Other values (627) 952
39.0%
2024-05-10T23:03:56.344518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2232
18.4%
1035
 
8.5%
551
 
4.5%
492
 
4.0%
486
 
4.0%
484
 
4.0%
482
 
4.0%
482
 
4.0%
482
 
4.0%
- 450
 
3.7%
Other values (226) 4986
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6884
56.6%
Decimal Number 2531
 
20.8%
Space Separator 2232
 
18.4%
Dash Punctuation 450
 
3.7%
Close Punctuation 18
 
0.1%
Open Punctuation 18
 
0.1%
Uppercase Letter 16
 
0.1%
Lowercase Letter 7
 
0.1%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1035
15.0%
551
 
8.0%
492
 
7.1%
486
 
7.1%
484
 
7.0%
482
 
7.0%
482
 
7.0%
482
 
7.0%
229
 
3.3%
174
 
2.5%
Other values (195) 1987
28.9%
Decimal Number
ValueCountFrequency (%)
1 407
16.1%
4 406
16.0%
3 353
13.9%
2 318
12.6%
5 293
11.6%
0 223
8.8%
9 156
 
6.2%
6 147
 
5.8%
8 121
 
4.8%
7 107
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
25.0%
D 3
18.8%
R 2
12.5%
X 1
 
6.2%
K 1
 
6.2%
M 1
 
6.2%
V 1
 
6.2%
Y 1
 
6.2%
G 1
 
6.2%
S 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
i 2
28.6%
w 1
14.3%
r 1
14.3%
v 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
/ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
2232
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 450
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6883
56.6%
Common 5255
43.2%
Latin 23
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1035
15.0%
551
 
8.0%
492
 
7.1%
486
 
7.1%
484
 
7.0%
482
 
7.0%
482
 
7.0%
482
 
7.0%
229
 
3.3%
174
 
2.5%
Other values (194) 1986
28.9%
Common
ValueCountFrequency (%)
2232
42.5%
- 450
 
8.6%
1 407
 
7.7%
4 406
 
7.7%
3 353
 
6.7%
2 318
 
6.1%
5 293
 
5.6%
0 223
 
4.2%
9 156
 
3.0%
6 147
 
2.8%
Other values (6) 270
 
5.1%
Latin
ValueCountFrequency (%)
B 4
17.4%
D 3
13.0%
e 2
 
8.7%
R 2
 
8.7%
i 2
 
8.7%
X 1
 
4.3%
K 1
 
4.3%
M 1
 
4.3%
w 1
 
4.3%
V 1
 
4.3%
Other values (5) 5
21.7%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6883
56.6%
ASCII 5278
43.4%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2232
42.3%
- 450
 
8.5%
1 407
 
7.7%
4 406
 
7.7%
3 353
 
6.7%
2 318
 
6.0%
5 293
 
5.6%
0 223
 
4.2%
9 156
 
3.0%
6 147
 
2.8%
Other values (21) 293
 
5.6%
Hangul
ValueCountFrequency (%)
1035
15.0%
551
 
8.0%
492
 
7.1%
486
 
7.1%
484
 
7.0%
482
 
7.0%
482
 
7.0%
482
 
7.0%
229
 
3.3%
174
 
2.5%
Other values (194) 1986
28.9%
CJK
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct337
Distinct (%)97.1%
Missing136
Missing (%)28.2%
Memory size3.9 KiB
2024-05-10T23:03:57.045535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length47
Mean length35.14121
Min length22

Characters and Unicode

Total characters12194
Distinct characters233
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)94.2%

Sample

1st row서울특별시 강동구 올림픽로 820 (암사동)
2nd row서울특별시 강동구 고덕비즈밸리로2가길 27, 7~9층 (고덕동)
3rd row서울특별시 강동구 천호대로182길 46 (둔촌동)
4th row서울특별시 강동구 동남로71길 20, 청솔빌딩 5층 (명일동)
5th row서울특별시 강동구 올림픽로71길 81 (천호동,제이드빌딩4층)
ValueCountFrequency (%)
서울특별시 347
 
14.5%
강동구 347
 
14.5%
성내동 99
 
4.1%
길동 77
 
3.2%
천호동 70
 
2.9%
천호대로 61
 
2.5%
올림픽로 40
 
1.7%
2층 39
 
1.6%
강동그린타워 37
 
1.5%
1139 37
 
1.5%
Other values (607) 1239
51.8%
2024-05-10T23:03:58.123923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2046
 
16.8%
776
 
6.4%
1 531
 
4.4%
415
 
3.4%
, 412
 
3.4%
374
 
3.1%
364
 
3.0%
356
 
2.9%
) 354
 
2.9%
( 354
 
2.9%
Other values (223) 6212
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6807
55.8%
Decimal Number 2154
 
17.7%
Space Separator 2046
 
16.8%
Other Punctuation 412
 
3.4%
Close Punctuation 354
 
2.9%
Open Punctuation 354
 
2.9%
Dash Punctuation 39
 
0.3%
Uppercase Letter 20
 
0.2%
Lowercase Letter 7
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
776
 
11.4%
415
 
6.1%
374
 
5.5%
364
 
5.3%
356
 
5.2%
349
 
5.1%
347
 
5.1%
347
 
5.1%
347
 
5.1%
346
 
5.1%
Other values (191) 2786
40.9%
Uppercase Letter
ValueCountFrequency (%)
R 5
25.0%
B 4
20.0%
D 2
 
10.0%
A 2
 
10.0%
V 1
 
5.0%
X 1
 
5.0%
Y 1
 
5.0%
M 1
 
5.0%
K 1
 
5.0%
G 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 531
24.7%
2 265
12.3%
3 254
11.8%
0 227
10.5%
4 186
 
8.6%
9 184
 
8.5%
5 165
 
7.7%
6 127
 
5.9%
7 112
 
5.2%
8 103
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
i 2
28.6%
r 1
14.3%
w 1
14.3%
v 1
14.3%
Space Separator
ValueCountFrequency (%)
2046
100.0%
Other Punctuation
ValueCountFrequency (%)
, 412
100.0%
Close Punctuation
ValueCountFrequency (%)
) 354
100.0%
Open Punctuation
ValueCountFrequency (%)
( 354
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6806
55.8%
Common 5360
44.0%
Latin 27
 
0.2%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
776
 
11.4%
415
 
6.1%
374
 
5.5%
364
 
5.3%
356
 
5.2%
349
 
5.1%
347
 
5.1%
347
 
5.1%
347
 
5.1%
346
 
5.1%
Other values (190) 2785
40.9%
Common
ValueCountFrequency (%)
2046
38.2%
1 531
 
9.9%
, 412
 
7.7%
) 354
 
6.6%
( 354
 
6.6%
2 265
 
4.9%
3 254
 
4.7%
0 227
 
4.2%
4 186
 
3.5%
9 184
 
3.4%
Other values (6) 547
 
10.2%
Latin
ValueCountFrequency (%)
R 5
18.5%
B 4
14.8%
e 2
 
7.4%
D 2
 
7.4%
A 2
 
7.4%
i 2
 
7.4%
r 1
 
3.7%
w 1
 
3.7%
V 1
 
3.7%
v 1
 
3.7%
Other values (6) 6
22.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6806
55.8%
ASCII 5387
44.2%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2046
38.0%
1 531
 
9.9%
, 412
 
7.6%
) 354
 
6.6%
( 354
 
6.6%
2 265
 
4.9%
3 254
 
4.7%
0 227
 
4.2%
4 186
 
3.5%
9 184
 
3.4%
Other values (22) 574
 
10.7%
Hangul
ValueCountFrequency (%)
776
 
11.4%
415
 
6.1%
374
 
5.5%
364
 
5.3%
356
 
5.2%
349
 
5.1%
347
 
5.1%
347
 
5.1%
347
 
5.1%
346
 
5.1%
Other values (190) 2785
40.9%
CJK
ValueCountFrequency (%)
1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)34.2%
Missing138
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean5333.8435
Minimum5203
Maximum5409
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-10T23:03:58.506394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5203
5-th percentile5238
Q15303
median5353
Q35378
95-th percentile5403.8
Maximum5409
Range206
Interquartile range (IQR)75

Descriptive statistics

Standard deviation55.289133
Coefficient of variation (CV)0.010365721
Kurtosis-0.71557128
Mean5333.8435
Median Absolute Deviation (MAD)38
Skewness-0.61433458
Sum1840176
Variance3056.8882
MonotonicityNot monotonic
2024-05-10T23:03:59.036354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5355 44
 
9.1%
5328 14
 
2.9%
5398 11
 
2.3%
5238 10
 
2.1%
5385 10
 
2.1%
5396 8
 
1.7%
5373 8
 
1.7%
5251 8
 
1.7%
5303 6
 
1.2%
5405 6
 
1.2%
Other values (108) 220
45.5%
(Missing) 138
28.6%
ValueCountFrequency (%)
5203 3
 
0.6%
5210 1
 
0.2%
5211 3
 
0.6%
5220 1
 
0.2%
5221 2
 
0.4%
5222 2
 
0.4%
5230 1
 
0.2%
5236 1
 
0.2%
5237 1
 
0.2%
5238 10
2.1%
ValueCountFrequency (%)
5409 1
 
0.2%
5408 4
0.8%
5407 2
 
0.4%
5406 2
 
0.4%
5405 6
1.2%
5404 3
0.6%
5403 3
0.6%
5402 1
 
0.2%
5400 4
0.8%
5399 5
1.0%
Distinct471
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2024-05-10T23:03:59.671015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length7.1925466
Min length2

Characters and Unicode

Total characters3474
Distinct characters457
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

Unique459 ?
Unique (%)95.0%

Sample

1st row주)해태유통
2nd row(주)한길에스디
3rd row농협중앙회(죽산경제)
4th row한가람식품
5th row성진식품
ValueCountFrequency (%)
주식회사 54
 
9.6%
주)에이뷰 2
 
0.4%
진주식품 2
 
0.4%
온어스 2
 
0.4%
주)이든힐 2
 
0.4%
주)세이브씨앤라이프 2
 
0.4%
한국효모(주 2
 
0.4%
버틀 2
 
0.4%
에프시코리아 2
 
0.4%
지미앤잭 2
 
0.4%
Other values (486) 491
87.2%
2024-05-10T23:04:00.688202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
261
 
7.5%
) 204
 
5.9%
( 202
 
5.8%
136
 
3.9%
98
 
2.8%
89
 
2.6%
80
 
2.3%
78
 
2.2%
67
 
1.9%
65
 
1.9%
Other values (447) 2194
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2905
83.6%
Close Punctuation 204
 
5.9%
Open Punctuation 202
 
5.8%
Space Separator 80
 
2.3%
Lowercase Letter 35
 
1.0%
Uppercase Letter 34
 
1.0%
Decimal Number 7
 
0.2%
Other Punctuation 5
 
0.1%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
261
 
9.0%
136
 
4.7%
98
 
3.4%
89
 
3.1%
78
 
2.7%
67
 
2.3%
65
 
2.2%
58
 
2.0%
56
 
1.9%
45
 
1.5%
Other values (403) 1952
67.2%
Lowercase Letter
ValueCountFrequency (%)
o 8
22.9%
n 4
11.4%
e 2
 
5.7%
h 2
 
5.7%
d 2
 
5.7%
y 2
 
5.7%
a 2
 
5.7%
s 2
 
5.7%
t 2
 
5.7%
l 1
 
2.9%
Other values (8) 8
22.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
14.7%
G 4
11.8%
F 4
11.8%
M 3
8.8%
B 3
8.8%
U 2
 
5.9%
O 2
 
5.9%
T 2
 
5.9%
L 2
 
5.9%
H 1
 
2.9%
Other values (6) 6
17.6%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
1 2
28.6%
0 2
28.6%
2 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
& 2
40.0%
Close Punctuation
ValueCountFrequency (%)
) 204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 202
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2905
83.6%
Common 500
 
14.4%
Latin 69
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
261
 
9.0%
136
 
4.7%
98
 
3.4%
89
 
3.1%
78
 
2.7%
67
 
2.3%
65
 
2.2%
58
 
2.0%
56
 
1.9%
45
 
1.5%
Other values (403) 1952
67.2%
Latin
ValueCountFrequency (%)
o 8
 
11.6%
C 5
 
7.2%
G 4
 
5.8%
F 4
 
5.8%
n 4
 
5.8%
M 3
 
4.3%
B 3
 
4.3%
e 2
 
2.9%
U 2
 
2.9%
h 2
 
2.9%
Other values (24) 32
46.4%
Common
ValueCountFrequency (%)
) 204
40.8%
( 202
40.4%
80
 
16.0%
. 3
 
0.6%
4 2
 
0.4%
& 2
 
0.4%
- 2
 
0.4%
1 2
 
0.4%
0 2
 
0.4%
2 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2905
83.6%
ASCII 569
 
16.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
261
 
9.0%
136
 
4.7%
98
 
3.4%
89
 
3.1%
78
 
2.7%
67
 
2.3%
65
 
2.2%
58
 
2.0%
56
 
1.9%
45
 
1.5%
Other values (403) 1952
67.2%
ASCII
ValueCountFrequency (%)
) 204
35.9%
( 202
35.5%
80
 
14.1%
o 8
 
1.4%
C 5
 
0.9%
G 4
 
0.7%
F 4
 
0.7%
n 4
 
0.7%
M 3
 
0.5%
. 3
 
0.5%
Other values (34) 52
 
9.1%
Distinct469
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum1999-02-08 00:00:00
Maximum2024-05-09 15:37:09
2024-05-10T23:04:01.160654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:04:01.625699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
I
313 
U
170 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 313
64.8%
U 170
35.2%

Length

2024-05-10T23:04:02.040204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:02.321109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 313
64.8%
u 170
35.2%
Distinct208
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:04:00
2024-05-10T23:04:02.648467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T23:04:03.100318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
유통전문판매업
483 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 483
100.0%

Length

2024-05-10T23:04:03.466429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:03.729683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 483
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct330
Distinct (%)69.0%
Missing5
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean211967.84
Minimum210553.29
Maximum216068.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-10T23:04:04.054682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210553.29
5-th percentile210722.47
Q1211203.68
median211853.37
Q3212326.29
95-th percentile214844.26
Maximum216068.69
Range5515.4037
Interquartile range (IQR)1122.6105

Descriptive statistics

Standard deviation1085.402
Coefficient of variation (CV)0.0051205975
Kurtosis2.5347358
Mean211967.84
Median Absolute Deviation (MAD)557.70201
Skewness1.5041411
Sum1.0132063 × 108
Variance1178097.5
MonotonicityNot monotonic
2024-05-10T23:04:04.469793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
212143.778930005 37
 
7.7%
211458.648093395 9
 
1.9%
210970.75707265 7
 
1.4%
210935.038615054 5
 
1.0%
210744.81545375 5
 
1.0%
210830.134427385 4
 
0.8%
211333.659909016 4
 
0.8%
211547.884004591 3
 
0.6%
211296.408208918 3
 
0.6%
211387.261448627 3
 
0.6%
Other values (320) 398
82.4%
(Missing) 5
 
1.0%
ValueCountFrequency (%)
210553.290352325 1
 
0.2%
210558.095600946 2
0.4%
210613.801723814 1
 
0.2%
210621.954868934 2
0.4%
210632.575128544 1
 
0.2%
210633.27634857 1
 
0.2%
210634.358221322 2
0.4%
210669.722533894 1
 
0.2%
210670.369892293 3
0.6%
210670.952245602 3
0.6%
ValueCountFrequency (%)
216068.694008834 1
0.2%
216018.463725432 1
0.2%
215422.746119624 1
0.2%
215400.574803 1
0.2%
215379.100058 1
0.2%
215366.063352066 1
0.2%
215348.633292512 1
0.2%
215346.539174332 1
0.2%
215327.573332527 1
0.2%
215206.101435737 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct330
Distinct (%)69.0%
Missing5
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean448522.66
Minimum446598.59
Maximum451795.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-10T23:04:04.889385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446598.59
5-th percentile447154.26
Q1447743.33
median448314.08
Q3449328.92
95-th percentile450316.26
Maximum451795.6
Range5197.0066
Interquartile range (IQR)1585.5854

Descriptive statistics

Standard deviation1033.6891
Coefficient of variation (CV)0.0023046531
Kurtosis-0.11940664
Mean448522.66
Median Absolute Deviation (MAD)725.54311
Skewness0.621074
Sum2.1439383 × 108
Variance1068513.2
MonotonicityNot monotonic
2024-05-10T23:04:05.387581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
448048.253831401 37
 
7.7%
450316.255472825 9
 
1.9%
448713.31669728 7
 
1.4%
448663.480515858 5
 
1.0%
447427.034954557 5
 
1.0%
448618.9907646 4
 
0.8%
450146.941145682 4
 
0.8%
446812.537064604 3
 
0.6%
447520.782684761 3
 
0.6%
447200.708513892 3
 
0.6%
Other values (320) 398
82.4%
(Missing) 5
 
1.0%
ValueCountFrequency (%)
446598.591776331 1
 
0.2%
446680.303498539 1
 
0.2%
446732.640167362 2
0.4%
446748.493341691 1
 
0.2%
446812.537064604 3
0.6%
446857.032145865 1
 
0.2%
446882.690089639 1
 
0.2%
446899.812821946 2
0.4%
446940.608800863 1
 
0.2%
446959.181297857 1
 
0.2%
ValueCountFrequency (%)
451795.598336335 1
0.2%
451707.466249 1
0.2%
451691.505203 1
0.2%
451625.467060082 1
0.2%
451618.231227225 1
0.2%
451478.410475571 1
0.2%
451035.074054645 1
0.2%
451026.433073355 1
0.2%
450919.127020114 1
0.2%
450913.15929427 1
0.2%

위생업태명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
유통전문판매업
340 
<NA>
143 

Length

Max length7
Median length7
Mean length6.1118012
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 340
70.4%
<NA> 143
29.6%

Length

2024-05-10T23:04:05.825451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:06.151856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 340
70.4%
na 143
29.6%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
410 
0
65 
1
 
6
2
 
2

Length

Max length4
Median length4
Mean length3.5465839
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
84.9%
0 65
 
13.5%
1 6
 
1.2%
2 2
 
0.4%

Length

2024-05-10T23:04:06.609823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:06.895186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
84.9%
0 65
 
13.5%
1 6
 
1.2%
2 2
 
0.4%

여성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
410 
0
69 
1
 
3
2
 
1

Length

Max length4
Median length4
Mean length3.5465839
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 410
84.9%
0 69
 
14.3%
1 3
 
0.6%
2 1
 
0.2%

Length

2024-05-10T23:04:07.255553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:07.667737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 410
84.9%
0 69
 
14.3%
1 3
 
0.6%
2 1
 
0.2%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
444 
기타
 
22
주택가주변
 
15
아파트지역
 
1
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.9503106
Min length2

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 444
91.9%
기타 22
 
4.6%
주택가주변 15
 
3.1%
아파트지역 1
 
0.2%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-10T23:04:07.987395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:08.311131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 444
91.9%
기타 22
 
4.6%
주택가주변 15
 
3.1%
아파트지역 1
 
0.2%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
444 
자율
 
31
기타
 
7
관리
 
1

Length

Max length4
Median length4
Mean length3.8385093
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 444
91.9%
자율 31
 
6.4%
기타 7
 
1.4%
관리 1
 
0.2%

Length

2024-05-10T23:04:08.708246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:09.127657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 444
91.9%
자율 31
 
6.4%
기타 7
 
1.4%
관리 1
 
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
398 
상수도전용
85 

Length

Max length5
Median length4
Mean length4.1759834
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 398
82.4%
상수도전용 85
 
17.6%

Length

2024-05-10T23:04:09.376853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:09.786280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 398
82.4%
상수도전용 85
 
17.6%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
438 
0
45 

Length

Max length4
Median length4
Mean length3.7204969
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> 438
90.7%
0 45
 
9.3%

Length

2024-05-10T23:04:10.158350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:10.497265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 438
90.7%
0 45
 
9.3%

본사종업원수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
351 
0
130 
20
 
1
1
 
1

Length

Max length4
Median length4
Mean length3.1821946
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 351
72.7%
0 130
 
26.9%
20 1
 
0.2%
1 1
 
0.2%

Length

2024-05-10T23:04:10.859661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:11.230146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 351
72.7%
0 130
 
26.9%
20 1
 
0.2%
1 1
 
0.2%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
352 
0
130 
1
 
1

Length

Max length4
Median length4
Mean length3.1863354
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 352
72.9%
0 130
 
26.9%
1 1
 
0.2%

Length

2024-05-10T23:04:11.570369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:11.908978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 352
72.9%
0 130
 
26.9%
1 1
 
0.2%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
353 
0
130 

Length

Max length4
Median length4
Mean length3.1925466
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 353
73.1%
0 130
 
26.9%

Length

2024-05-10T23:04:12.319232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:12.638211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 353
73.1%
0 130
 
26.9%
Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
353 
0
130 

Length

Max length4
Median length4
Mean length3.1925466
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 353
73.1%
0 130
 
26.9%

Length

2024-05-10T23:04:12.975996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:13.308724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 353
73.1%
0 130
 
26.9%
Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
211 
임대
210 
자가
62 

Length

Max length4
Median length2
Mean length2.873706
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 211
43.7%
임대 210
43.5%
자가 62
 
12.8%

Length

2024-05-10T23:04:13.695251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:14.042977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 211
43.7%
임대 210
43.5%
자가 62
 
12.8%

보증액
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
390 
0
93 

Length

Max length4
Median length4
Mean length3.4223602
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> 390
80.7%
0 93
 
19.3%

Length

2024-05-10T23:04:14.459208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:14.768592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 390
80.7%
0 93
 
19.3%

월세액
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
<NA>
390 
0
93 

Length

Max length4
Median length4
Mean length3.4223602
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> 390
80.7%
0 93
 
19.3%

Length

2024-05-10T23:04:15.349491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T23:04:15.656682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 390
80.7%
0 93
 
19.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing143
Missing (%)29.6%
Memory size1.1 KiB
False
340 
(Missing)
143 
ValueCountFrequency (%)
False 340
70.4%
(Missing) 143
29.6%
2024-05-10T23:04:15.917378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)6.8%
Missing143
Missing (%)29.6%
Infinite0
Infinite (%)0.0%
Mean3.5282059
Minimum0
Maximum180.15
Zeros316
Zeros (%)65.4%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2024-05-10T23:04:16.212543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20
Maximum180.15
Range180.15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.524542
Coefficient of variation (CV)5.2504141
Kurtosis61.786123
Mean3.5282059
Median Absolute Deviation (MAD)0
Skewness7.4521875
Sum1199.59
Variance343.15865
MonotonicityNot monotonic
2024-05-10T23:04:16.615967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 316
65.4%
20.0 2
 
0.4%
16.5 2
 
0.4%
18.5 1
 
0.2%
28.0 1
 
0.2%
2.24 1
 
0.2%
33.0 1
 
0.2%
30.0 1
 
0.2%
180.15 1
 
0.2%
5.0 1
 
0.2%
Other values (13) 13
 
2.7%
(Missing) 143
29.6%
ValueCountFrequency (%)
0.0 316
65.4%
2.24 1
 
0.2%
5.0 1
 
0.2%
15.21 1
 
0.2%
16.5 2
 
0.4%
18.5 1
 
0.2%
20.0 2
 
0.4%
27.27 1
 
0.2%
28.0 1
 
0.2%
28.43 1
 
0.2%
ValueCountFrequency (%)
180.15 1
0.2%
170.0 1
0.2%
165.0 1
0.2%
99.8 1
0.2%
66.0 1
0.2%
49.93 1
0.2%
49.5 1
0.2%
48.0 1
0.2%
43.29 1
0.2%
36.0 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing483
Missing (%)100.0%
Memory size4.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-113-1996-0045519960906<NA>3폐업2폐업20080219<NA><NA><NA>02 4400783112.87134825서울특별시 강동구 명일동 47-7<NA><NA>주)해태유통2002-08-21 00:00:00I2018-08-31 23:59:59.0유통전문판매업213715.02802450204.740257유통전문판매업00아파트지역기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132400003240000-113-1997-0045419970721<NA>3폐업2폐업20210416<NA><NA><NA>02 4282091150.00134857서울특별시 강동구 암사동 462-3서울특별시 강동구 올림픽로 820 (암사동)5251(주)한길에스디2021-04-16 11:51:35U2021-04-18 02:40:00.0유통전문판매업211349.725354450207.018195유통전문판매업20주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
232400003240000-113-1997-0075219970526<NA>3폐업2폐업20010525<NA><NA><NA>0276.00134851서울특별시 강동구 성내동 553-0<NA><NA>농협중앙회(죽산경제)2001-05-25 00:00:00I2018-08-31 23:59:59.0유통전문판매업210613.801724447486.690483유통전문판매업00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
332400003240000-113-1997-0075319971120<NA>3폐업2폐업20051021<NA><NA><NA>02 429924426.90134838서울특별시 강동구 상일동 329-1<NA><NA>한가람식품2004-04-13 00:00:00I2018-08-31 23:59:59.0유통전문판매업215206.101436449506.919522유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
432400003240000-113-1997-0075419970306<NA>3폐업2폐업20040802<NA><NA><NA>02 485062232.37134817서울특별시 강동구 둔촌동 39-9<NA><NA>성진식품2004-04-13 00:00:00I2018-08-31 23:59:59.0유통전문판매업212726.127307447741.78085유통전문판매업<NA><NA><NA><NA>상수도전용<NA>0000임대<NA><NA>N0.0<NA><NA><NA>
532400003240000-113-1999-0049419990208<NA>3폐업2폐업20030317<NA><NA><NA>02 484533930.03134880서울특별시 강동구 길동 386-8 실버오피스텔 206호<NA><NA>(주)이슈메이커1999-02-08 00:00:00I2018-08-31 23:59:59.0유통전문판매업212068.530567448392.393404유통전문판매업00기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632400003240000-113-1999-0057319990621<NA>3폐업2폐업20010523<NA><NA><NA>0254.52134847서울특별시 강동구 성내동 449-20<NA><NA>케이에스엘통상2001-05-23 00:00:00I2018-08-31 23:59:59.0유통전문판매업<NA><NA>유통전문판매업00기타자율<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
732400003240000-113-1999-0057419990622<NA>3폐업2폐업20000627<NA><NA><NA>0276.76134858서울특별시 강동구 암사동 456-0<NA><NA>(주)엠에스푸드2000-06-27 00:00:00I2018-08-31 23:59:59.0유통전문판매업211774.016604450194.494846유통전문판매업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832400003240000-113-1999-0057519990622<NA>3폐업2폐업20051117<NA><NA><NA>02 486555159.96134885서울특별시 강동구 성내동 448-8 한국수자원기술공단2층<NA><NA>그린들1999-06-22 00:00:00I2018-08-31 23:59:59.0유통전문판매업211309.356542446899.812822유통전문판매업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-113-1999-0058819990712<NA>3폐업2폐업20030128<NA><NA><NA>02 427814072.86134858서울특별시 강동구 암사동 458-31<NA><NA>대명1999-07-12 00:00:00I2018-08-31 23:59:59.0유통전문판매업211747.994509450202.699709유통전문판매업00기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
47332400003240000-113-2024-000032024-01-18<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60134-090서울특별시 강동구 상일동 490 고덕리엔파크3단지아파트서울특별시 강동구 상일로 74, 323동 1304호 (상일동, 고덕리엔파크3단지아파트)5287주식회사 뉴트라이2024-01-18 15:40:28I2023-11-30 22:00:00.0유통전문판매업215422.74612450031.389223<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47432400003240000-113-2024-000052024-02-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60134-867서울특별시 강동구 천호동 309서울특별시 강동구 천중로15나길 2, 501호 (천호동)5322미소2024-02-15 14:57:05I2023-12-01 23:07:00.0유통전문판매업211285.422071449363.032685<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47532400003240000-113-2024-000062024-02-20<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30134-864서울특별시 강동구 천호동 447-17 강동역 신동아 파밀리에서울특별시 강동구 천호대로 1089, 1102동 3403호 (천호동, 강동역 신동아 파밀리에)5339텔노마드2024-02-20 09:28:05I2023-12-01 22:02:00.0유통전문판매업211712.429305448270.957716<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47632400003240000-113-2024-000072024-03-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>30.00134-856서울특별시 강동구 암사동 485-41서울특별시 강동구 구천면로47가길 12, 1층 (암사동)5260온도도시협동조합2024-03-04 11:59:01I2023-12-03 00:06:00.0유통전문판매업211784.047833449675.570437<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47732400003240000-113-2024-000082024-03-21<NA>1영업/정상1영업<NA><NA><NA><NA><NA>48.10134-818서울특별시 강동구 둔촌동 94-16 동아아파트서울특별시 강동구 진황도로61길 18, 8층 803호 (둔촌동, 동아아파트)5369닥터에이지이2024-03-21 10:34:13I2023-12-02 22:03:00.0유통전문판매업212677.702154447402.506351<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47832400003240000-113-2024-000092024-04-12<NA>1영업/정상1영업<NA><NA><NA><NA>02 326 387110.00134-855서울특별시 강동구 암사동 441-4 금강블루주택서울특별시 강동구 올림픽로104길 22, 금강블루주택 701호 (암사동)5238투핸즈(twohands)2024-04-12 17:38:17I2023-12-03 23:04:00.0유통전문판매업211494.278843450364.939156<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47932400003240000-113-2024-000102024-04-24<NA>1영업/정상1영업<NA><NA><NA><NA><NA>4.50134-809서울특별시 강동구 길동 172-3서울특별시 강동구 천호대로201길 18, 204호 (길동)5347온어스2024-04-24 13:33:08I2023-12-03 22:06:00.0유통전문판매업213247.524651448471.651054<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48032400003240000-113-2024-000112024-05-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>3.30134-814서울특별시 강동구 길동 412-12 부에노빌딩서울특별시 강동구 양재대로 1457, 부에노빌딩 5181호 (길동)5353리즈&Co2024-05-01 13:18:54I2023-12-05 00:03:00.0유통전문판매업212215.378259448196.85466<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48132400003240000-113-2024-000122024-05-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>22.68134-851서울특별시 강동구 성내동 556-2 청일 베르네서울특별시 강동구 성내로6길 20, 3층 303호 (성내동, 청일 베르네)5398(주)제이원웍스2024-05-02 15:51:57I2023-12-05 00:04:00.0유통전문판매업210744.815454447427.034955<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
48232400003240000-113-2024-000132024-05-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>6.60134-814서울특별시 강동구 길동 459-3 강동그린타워서울특별시 강동구 천호대로 1139, 강동그린타워 905호 (길동)5355주식회사 케이에프씨2024-05-09 15:37:09I2023-12-04 23:01:00.0유통전문판매업212143.77893448048.253831<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>