Overview

Dataset statistics

Number of variables44
Number of observations6874
Missing cells63234
Missing cells (%)20.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory375.0 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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-18445/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (50.2%)Imbalance
영업상태명 is highly imbalanced (50.2%)Imbalance
상세영업상태코드 is highly imbalanced (50.2%)Imbalance
상세영업상태명 is highly imbalanced (50.2%)Imbalance
업태구분명 is highly imbalanced (85.8%)Imbalance
남성종사자수 is highly imbalanced (77.5%)Imbalance
여성종사자수 is highly imbalanced (78.2%)Imbalance
영업장주변구분명 is highly imbalanced (86.3%)Imbalance
등급구분명 is highly imbalanced (82.0%)Imbalance
급수시설구분명 is highly imbalanced (86.0%)Imbalance
총인원 is highly imbalanced (65.5%)Imbalance
본사종업원수 is highly imbalanced (54.3%)Imbalance
공장사무직종업원수 is highly imbalanced (54.1%)Imbalance
공장판매직종업원수 is highly imbalanced (53.3%)Imbalance
공장생산직종업원수 is highly imbalanced (67.8%)Imbalance
보증액 is highly imbalanced (66.7%)Imbalance
월세액 is highly imbalanced (66.7%)Imbalance
인허가취소일자 has 6874 (100.0%) missing valuesMissing
폐업일자 has 751 (10.9%) missing valuesMissing
휴업시작일자 has 6874 (100.0%) missing valuesMissing
휴업종료일자 has 6874 (100.0%) missing valuesMissing
재개업일자 has 6874 (100.0%) missing valuesMissing
전화번호 has 3883 (56.5%) missing valuesMissing
소재지면적 has 3768 (54.8%) missing valuesMissing
도로명주소 has 1649 (24.0%) missing valuesMissing
도로명우편번호 has 1685 (24.5%) missing valuesMissing
좌표정보(X) has 242 (3.5%) missing valuesMissing
좌표정보(Y) has 242 (3.5%) missing valuesMissing
다중이용업소여부 has 1444 (21.0%) missing valuesMissing
시설총규모 has 1444 (21.0%) missing valuesMissing
전통업소지정번호 has 6874 (100.0%) missing valuesMissing
전통업소주된음식 has 6874 (100.0%) missing valuesMissing
홈페이지 has 6874 (100.0%) missing valuesMissing
도로명우편번호 is highly skewed (γ1 = 68.00203579)Skewed
좌표정보(Y) is highly skewed (γ1 = 23.19441047)Skewed
시설총규모 is highly skewed (γ1 = 38.83514065)Skewed
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 5422 (78.9%) zerosZeros

Reproduction

Analysis started2024-04-06 12:29:03.066285
Analysis finished2024-04-06 12:29:07.711251
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
3180000
6874 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 6874
100.0%

Length

2024-04-06T21:29:07.851907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:08.029265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 6874
100.0%

관리번호
Text

UNIQUE 

Distinct6874
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
2024-04-06T21:29:08.344852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters151228
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

Unique6874 ?
Unique (%)100.0%

Sample

1st row3180000-107-1970-00265
2nd row3180000-107-1970-00772
3rd row3180000-107-1972-00272
4th row3180000-107-1972-00281
5th row3180000-107-1972-00285
ValueCountFrequency (%)
3180000-107-1970-00265 1
 
< 0.1%
3180000-107-2020-00246 1
 
< 0.1%
3180000-107-2020-00244 1
 
< 0.1%
3180000-107-2020-00243 1
 
< 0.1%
3180000-107-2020-00242 1
 
< 0.1%
3180000-107-2020-00241 1
 
< 0.1%
3180000-107-2020-00240 1
 
< 0.1%
3180000-107-2020-00239 1
 
< 0.1%
3180000-107-2020-00238 1
 
< 0.1%
3180000-107-2020-00237 1
 
< 0.1%
Other values (6864) 6864
99.9%
2024-04-06T21:29:08.943150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 60595
40.1%
- 20622
 
13.6%
1 20488
 
13.5%
2 12078
 
8.0%
3 9861
 
6.5%
8 9180
 
6.1%
7 9007
 
6.0%
9 3104
 
2.1%
4 2386
 
1.6%
5 2017
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130606
86.4%
Dash Punctuation 20622
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 60595
46.4%
1 20488
 
15.7%
2 12078
 
9.2%
3 9861
 
7.6%
8 9180
 
7.0%
7 9007
 
6.9%
9 3104
 
2.4%
4 2386
 
1.8%
5 2017
 
1.5%
6 1890
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 20622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 60595
40.1%
- 20622
 
13.6%
1 20488
 
13.5%
2 12078
 
8.0%
3 9861
 
6.5%
8 9180
 
6.1%
7 9007
 
6.0%
9 3104
 
2.1%
4 2386
 
1.6%
5 2017
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 60595
40.1%
- 20622
 
13.6%
1 20488
 
13.5%
2 12078
 
8.0%
3 9861
 
6.5%
8 9180
 
6.1%
7 9007
 
6.0%
9 3104
 
2.1%
4 2386
 
1.6%
5 2017
 
1.3%
Distinct3487
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
Minimum1970-04-02 00:00:00
Maximum2024-04-04 00:00:00
2024-04-06T21:29:09.292104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:29:09.584387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
3
6123 
1
751 

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 6123
89.1%
1 751
 
10.9%

Length

2024-04-06T21:29:09.870273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:10.098881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6123
89.1%
1 751
 
10.9%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
폐업
6123 
영업/정상
751 

Length

Max length5
Median length2
Mean length2.3277568
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 6123
89.1%
영업/정상 751
 
10.9%

Length

2024-04-06T21:29:10.347942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:10.539739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6123
89.1%
영업/정상 751
 
10.9%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
2
6123 
1
751 

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 6123
89.1%
1 751
 
10.9%

Length

2024-04-06T21:29:10.774426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:10.985951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6123
89.1%
1 751
 
10.9%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
폐업
6123 
영업
751 

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 6123
89.1%
영업 751
 
10.9%

Length

2024-04-06T21:29:11.202322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:11.919416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 6123
89.1%
영업 751
 
10.9%

폐업일자
Date

MISSING 

Distinct3096
Distinct (%)50.6%
Missing751
Missing (%)10.9%
Memory size53.8 KiB
Minimum1991-11-01 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T21:29:12.246718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:29:12.648664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

전화번호
Text

MISSING 

Distinct1582
Distinct (%)52.9%
Missing3883
Missing (%)56.5%
Memory size53.8 KiB
2024-04-06T21:29:13.240964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.065864
Min length2

Characters and Unicode

Total characters30107
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

Unique1276 ?
Unique (%)42.7%

Sample

1st row02
2nd row0226346863
3rd row0226342543
4th row02 8325656
5th row02 8322770
ValueCountFrequency (%)
02 901
 
19.8%
031 258
 
5.7%
07043009589 89
 
2.0%
032 48
 
1.1%
070 47
 
1.0%
0222816340 43
 
0.9%
0318581226 42
 
0.9%
0313114992 41
 
0.9%
0429363040 33
 
0.7%
062 29
 
0.6%
Other values (1669) 3031
66.4%
2024-04-06T21:29:14.158384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5361
17.8%
2 4609
15.3%
3 3188
10.6%
1 2642
8.8%
8 2417
8.0%
6 2283
7.6%
4 2164
7.2%
5 2138
 
7.1%
7 1989
 
6.6%
1790
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28317
94.1%
Space Separator 1790
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5361
18.9%
2 4609
16.3%
3 3188
11.3%
1 2642
9.3%
8 2417
8.5%
6 2283
8.1%
4 2164
7.6%
5 2138
 
7.6%
7 1989
 
7.0%
9 1526
 
5.4%
Space Separator
ValueCountFrequency (%)
1790
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30107
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5361
17.8%
2 4609
15.3%
3 3188
10.6%
1 2642
8.8%
8 2417
8.0%
6 2283
7.6%
4 2164
7.2%
5 2138
 
7.1%
7 1989
 
6.6%
1790
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30107
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5361
17.8%
2 4609
15.3%
3 3188
10.6%
1 2642
8.8%
8 2417
8.0%
6 2283
7.6%
4 2164
7.2%
5 2138
 
7.1%
7 1989
 
6.6%
1790
 
5.9%

소재지면적
Text

MISSING 

Distinct843
Distinct (%)27.1%
Missing3768
Missing (%)54.8%
Memory size53.8 KiB
2024-04-06T21:29:14.722084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length4.4211204
Min length3

Characters and Unicode

Total characters13732
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

Unique630 ?
Unique (%)20.3%

Sample

1st row.00
2nd row12.95
3rd row21.00
4th row12.39
5th row13.22
ValueCountFrequency (%)
00 311
 
10.0%
0.00 226
 
7.3%
6.60 178
 
5.7%
3.30 157
 
5.1%
10.00 126
 
4.1%
6.00 95
 
3.1%
15.00 63
 
2.0%
33.00 58
 
1.9%
3.00 54
 
1.7%
5.00 46
 
1.5%
Other values (833) 1792
57.7%
2024-04-06T21:29:15.733688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4723
34.4%
. 3106
22.6%
3 965
 
7.0%
1 926
 
6.7%
6 903
 
6.6%
2 854
 
6.2%
5 605
 
4.4%
4 540
 
3.9%
8 411
 
3.0%
9 407
 
3.0%
Other values (2) 292
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10625
77.4%
Other Punctuation 3107
 
22.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4723
44.5%
3 965
 
9.1%
1 926
 
8.7%
6 903
 
8.5%
2 854
 
8.0%
5 605
 
5.7%
4 540
 
5.1%
8 411
 
3.9%
9 407
 
3.8%
7 291
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 3106
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 13732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4723
34.4%
. 3106
22.6%
3 965
 
7.0%
1 926
 
6.7%
6 903
 
6.6%
2 854
 
6.2%
5 605
 
4.4%
4 540
 
3.9%
8 411
 
3.0%
9 407
 
3.0%
Other values (2) 292
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4723
34.4%
. 3106
22.6%
3 965
 
7.0%
1 926
 
6.7%
6 903
 
6.6%
2 854
 
6.2%
5 605
 
4.4%
4 540
 
3.9%
8 411
 
3.0%
9 407
 
3.0%
Other values (2) 292
 
2.1%
Distinct231
Distinct (%)3.4%
Missing4
Missing (%)0.1%
Memory size53.8 KiB
2024-04-06T21:29:16.312001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1310044
Min length6

Characters and Unicode

Total characters42120
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

Unique53 ?
Unique (%)0.8%

Sample

1st row150839
2nd row150035
3rd row150035
4th row150841
5th row150-822
ValueCountFrequency (%)
150899 796
 
11.6%
150985 681
 
9.9%
150893 464
 
6.8%
150034 419
 
6.1%
150835 355
 
5.2%
150991 304
 
4.4%
150798 302
 
4.4%
150038 289
 
4.2%
150875 185
 
2.7%
150103 155
 
2.3%
Other values (221) 2920
42.5%
2024-04-06T21:29:17.253922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9138
21.7%
5 8807
20.9%
1 7908
18.8%
8 5383
12.8%
9 4755
11.3%
3 2397
 
5.7%
4 1018
 
2.4%
7 930
 
2.2%
- 900
 
2.1%
2 465
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 41220
97.9%
Dash Punctuation 900
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9138
22.2%
5 8807
21.4%
1 7908
19.2%
8 5383
13.1%
9 4755
11.5%
3 2397
 
5.8%
4 1018
 
2.5%
7 930
 
2.3%
2 465
 
1.1%
6 419
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 900
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9138
21.7%
5 8807
20.9%
1 7908
18.8%
8 5383
12.8%
9 4755
11.3%
3 2397
 
5.7%
4 1018
 
2.4%
7 930
 
2.2%
- 900
 
2.1%
2 465
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9138
21.7%
5 8807
20.9%
1 7908
18.8%
8 5383
12.8%
9 4755
11.3%
3 2397
 
5.7%
4 1018
 
2.4%
7 930
 
2.2%
- 900
 
2.1%
2 465
 
1.1%
Distinct2233
Distinct (%)32.5%
Missing4
Missing (%)0.1%
Memory size53.8 KiB
2024-04-06T21:29:18.009092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length43
Mean length27.615429
Min length18

Characters and Unicode

Total characters189718
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

Unique1851 ?
Unique (%)26.9%

Sample

1st row서울특별시 영등포구 신길동 116-2
2nd row서울특별시 영등포구 영등포동5가 276-0
3rd row서울특별시 영등포구 영등포동5가 116-0
4th row서울특별시 영등포구 신길동 259-104
5th row서울특별시 영등포구 대림동 967-7 제2호 내 제15호
ValueCountFrequency (%)
영등포구 6870
19.7%
서울특별시 6869
19.7%
영등포동4가 1593
 
4.6%
여의도동 1081
 
3.1%
434-5 970
 
2.8%
영등포동 946
 
2.7%
618-496 873
 
2.5%
문래동3가 788
 
2.3%
신세계백화점 783
 
2.2%
55-3 722
 
2.1%
Other values (2040) 13318
38.3%
2024-04-06T21:29:18.986077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33306
17.6%
10834
 
5.7%
10823
 
5.7%
10805
 
5.7%
4 7515
 
4.0%
6947
 
3.7%
6936
 
3.7%
6921
 
3.6%
6885
 
3.6%
6882
 
3.6%
Other values (320) 81864
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120051
63.3%
Space Separator 33306
 
17.6%
Decimal Number 31018
 
16.3%
Dash Punctuation 4816
 
2.5%
Uppercase Letter 197
 
0.1%
Close Punctuation 128
 
0.1%
Open Punctuation 128
 
0.1%
Other Punctuation 64
 
< 0.1%
Lowercase Letter 9
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10834
 
9.0%
10823
 
9.0%
10805
 
9.0%
6947
 
5.8%
6936
 
5.8%
6921
 
5.8%
6885
 
5.7%
6882
 
5.7%
6877
 
5.7%
6870
 
5.7%
Other values (274) 39271
32.7%
Uppercase Letter
ValueCountFrequency (%)
B 83
42.1%
A 27
 
13.7%
S 26
 
13.2%
G 15
 
7.6%
K 11
 
5.6%
F 10
 
5.1%
C 4
 
2.0%
D 3
 
1.5%
M 3
 
1.5%
I 2
 
1.0%
Other values (8) 13
 
6.6%
Decimal Number
ValueCountFrequency (%)
4 7515
24.2%
1 4544
14.6%
3 3794
12.2%
5 3520
11.3%
6 2995
 
9.7%
2 2959
 
9.5%
8 1794
 
5.8%
9 1637
 
5.3%
7 1266
 
4.1%
0 994
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
e 4
44.4%
n 1
 
11.1%
t 1
 
11.1%
r 1
 
11.1%
c 1
 
11.1%
b 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 51
79.7%
. 5
 
7.8%
? 4
 
6.2%
/ 2
 
3.1%
@ 2
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 127
99.2%
] 1
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 127
99.2%
[ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
33306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4816
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120051
63.3%
Common 69461
36.6%
Latin 206
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10834
 
9.0%
10823
 
9.0%
10805
 
9.0%
6947
 
5.8%
6936
 
5.8%
6921
 
5.8%
6885
 
5.7%
6882
 
5.7%
6877
 
5.7%
6870
 
5.7%
Other values (274) 39271
32.7%
Latin
ValueCountFrequency (%)
B 83
40.3%
A 27
 
13.1%
S 26
 
12.6%
G 15
 
7.3%
K 11
 
5.3%
F 10
 
4.9%
e 4
 
1.9%
C 4
 
1.9%
D 3
 
1.5%
M 3
 
1.5%
Other values (14) 20
 
9.7%
Common
ValueCountFrequency (%)
33306
47.9%
4 7515
 
10.8%
- 4816
 
6.9%
1 4544
 
6.5%
3 3794
 
5.5%
5 3520
 
5.1%
6 2995
 
4.3%
2 2959
 
4.3%
8 1794
 
2.6%
9 1637
 
2.4%
Other values (12) 2581
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120051
63.3%
ASCII 69667
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33306
47.8%
4 7515
 
10.8%
- 4816
 
6.9%
1 4544
 
6.5%
3 3794
 
5.4%
5 3520
 
5.1%
6 2995
 
4.3%
2 2959
 
4.2%
8 1794
 
2.6%
9 1637
 
2.3%
Other values (36) 2787
 
4.0%
Hangul
ValueCountFrequency (%)
10834
 
9.0%
10823
 
9.0%
10805
 
9.0%
6947
 
5.8%
6936
 
5.8%
6921
 
5.8%
6885
 
5.7%
6882
 
5.7%
6877
 
5.7%
6870
 
5.7%
Other values (274) 39271
32.7%

도로명주소
Text

MISSING 

Distinct1954
Distinct (%)37.4%
Missing1649
Missing (%)24.0%
Memory size53.8 KiB
2024-04-06T21:29:19.526896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length55
Mean length37.439809
Min length22

Characters and Unicode

Total characters195623
Distinct characters340
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1618 ?
Unique (%)31.0%

Sample

1st row서울특별시 영등포구 대림로8길 26 (대림동,제2호 내 제15호)
2nd row서울특별시 영등포구 양산로 96, 1층 A1-1호 (당산동2가)
3rd row서울특별시 영등포구 영등포로45길 17 (영등포동5가)
4th row서울특별시 영등포구 가마산로 468 (신길동)
5th row서울특별시 영등포구 여의대방로39길 9-3 (신길동)
ValueCountFrequency (%)
영등포구 5224
 
14.4%
서울특별시 5223
 
14.4%
지하1층 2377
 
6.6%
영중로 1545
 
4.3%
영등포동4가 1334
 
3.7%
여의도동 930
 
2.6%
9 877
 
2.4%
1층 764
 
2.1%
신세계백화점 682
 
1.9%
경인로 679
 
1.9%
Other values (1573) 16626
45.9%
2024-04-06T21:29:20.487939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31047
 
15.9%
10653
 
5.4%
9006
 
4.6%
8988
 
4.6%
1 6667
 
3.4%
, 5894
 
3.0%
5857
 
3.0%
5376
 
2.7%
5359
 
2.7%
5284
 
2.7%
Other values (330) 101492
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 125918
64.4%
Space Separator 31047
 
15.9%
Decimal Number 21569
 
11.0%
Other Punctuation 5905
 
3.0%
Close Punctuation 5277
 
2.7%
Open Punctuation 5277
 
2.7%
Uppercase Letter 304
 
0.2%
Dash Punctuation 271
 
0.1%
Lowercase Letter 50
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10653
 
8.5%
9006
 
7.2%
8988
 
7.1%
5857
 
4.7%
5376
 
4.3%
5359
 
4.3%
5284
 
4.2%
5277
 
4.2%
5234
 
4.2%
5227
 
4.2%
Other values (277) 59657
47.4%
Uppercase Letter
ValueCountFrequency (%)
B 149
49.0%
A 36
 
11.8%
S 28
 
9.2%
G 24
 
7.9%
F 14
 
4.6%
C 9
 
3.0%
K 8
 
2.6%
E 6
 
2.0%
I 6
 
2.0%
T 5
 
1.6%
Other values (10) 19
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 6667
30.9%
4 3206
14.9%
2 2246
 
10.4%
3 2160
 
10.0%
8 1567
 
7.3%
0 1406
 
6.5%
5 1355
 
6.3%
9 1251
 
5.8%
6 1191
 
5.5%
7 520
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
g 17
34.0%
b 16
32.0%
e 5
 
10.0%
c 3
 
6.0%
s 3
 
6.0%
r 2
 
4.0%
w 1
 
2.0%
o 1
 
2.0%
n 1
 
2.0%
t 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 5894
99.8%
? 6
 
0.1%
. 2
 
< 0.1%
@ 2
 
< 0.1%
/ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 5276
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5276
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
31047
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 271
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 125918
64.4%
Common 69351
35.5%
Latin 354
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10653
 
8.5%
9006
 
7.2%
8988
 
7.1%
5857
 
4.7%
5376
 
4.3%
5359
 
4.3%
5284
 
4.2%
5277
 
4.2%
5234
 
4.2%
5227
 
4.2%
Other values (277) 59657
47.4%
Latin
ValueCountFrequency (%)
B 149
42.1%
A 36
 
10.2%
S 28
 
7.9%
G 24
 
6.8%
g 17
 
4.8%
b 16
 
4.5%
F 14
 
4.0%
C 9
 
2.5%
K 8
 
2.3%
E 6
 
1.7%
Other values (20) 47
 
13.3%
Common
ValueCountFrequency (%)
31047
44.8%
1 6667
 
9.6%
, 5894
 
8.5%
) 5276
 
7.6%
( 5276
 
7.6%
4 3206
 
4.6%
2 2246
 
3.2%
3 2160
 
3.1%
8 1567
 
2.3%
0 1406
 
2.0%
Other values (13) 4606
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 125918
64.4%
ASCII 69705
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31047
44.5%
1 6667
 
9.6%
, 5894
 
8.5%
) 5276
 
7.6%
( 5276
 
7.6%
4 3206
 
4.6%
2 2246
 
3.2%
3 2160
 
3.1%
8 1567
 
2.2%
0 1406
 
2.0%
Other values (43) 4960
 
7.1%
Hangul
ValueCountFrequency (%)
10653
 
8.5%
9006
 
7.2%
8988
 
7.1%
5857
 
4.7%
5376
 
4.3%
5359
 
4.3%
5284
 
4.2%
5277
 
4.2%
5234
 
4.2%
5227
 
4.2%
Other values (277) 59657
47.4%

도로명우편번호
Real number (ℝ)

MISSING  SKEWED 

Distinct207
Distinct (%)4.0%
Missing1685
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean7315.3891
Minimum7202
Maximum24049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.5 KiB
2024-04-06T21:29:20.772747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7202
5-th percentile7228
Q17297
median7305
Q37324
95-th percentile7421
Maximum24049
Range16847
Interquartile range (IQR)27

Descriptive statistics

Standard deviation236.8526
Coefficient of variation (CV)0.032377307
Kurtosis4804.8263
Mean7315.3891
Median Absolute Deviation (MAD)9
Skewness68.002036
Sum37959554
Variance56099.152
MonotonicityNot monotonic
2024-04-06T21:29:21.140191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7305 1359
19.8%
7306 664
 
9.7%
7297 521
 
7.6%
7324 490
 
7.1%
7335 273
 
4.0%
7255 181
 
2.6%
7228 171
 
2.5%
7250 75
 
1.1%
7340 62
 
0.9%
7434 61
 
0.9%
Other values (197) 1332
19.4%
(Missing) 1685
24.5%
ValueCountFrequency (%)
7202 4
 
0.1%
7203 2
 
< 0.1%
7204 9
 
0.1%
7205 6
 
0.1%
7206 24
0.3%
7207 3
 
< 0.1%
7208 12
0.2%
7209 4
 
0.1%
7211 1
 
< 0.1%
7212 2
 
< 0.1%
ValueCountFrequency (%)
24049 1
 
< 0.1%
7447 2
 
< 0.1%
7446 2
 
< 0.1%
7445 3
 
< 0.1%
7444 4
 
0.1%
7443 7
 
0.1%
7442 7
 
0.1%
7440 59
0.9%
7439 7
 
0.1%
7438 4
 
0.1%
Distinct3276
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
2024-04-06T21:29:21.555395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length6.5465522
Min length1

Characters and Unicode

Total characters45001
Distinct characters783
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2549 ?
Unique (%)37.1%

Sample

1st row강원참기름
2nd row형제상회
3rd row도매기름집
4th row동아기름집
5th row동보기름집
ValueCountFrequency (%)
주식회사 363
 
4.6%
명류당티에프 130
 
1.6%
주)명류당티에프 68
 
0.9%
주)인네이처 66
 
0.8%
주)한울에프엔비 65
 
0.8%
수라원 61
 
0.8%
주)마켓인 59
 
0.7%
장원에프엔비 57
 
0.7%
주)동해식품 56
 
0.7%
주)미래식품 52
 
0.7%
Other values (3478) 6973
87.7%
2024-04-06T21:29:22.230878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2384
 
5.3%
) 2116
 
4.7%
( 2087
 
4.6%
1077
 
2.4%
988
 
2.2%
900
 
2.0%
857
 
1.9%
798
 
1.8%
771
 
1.7%
729
 
1.6%
Other values (773) 32294
71.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38634
85.9%
Close Punctuation 2116
 
4.7%
Open Punctuation 2087
 
4.6%
Space Separator 1077
 
2.4%
Uppercase Letter 499
 
1.1%
Lowercase Letter 419
 
0.9%
Other Punctuation 81
 
0.2%
Decimal Number 67
 
0.1%
Dash Punctuation 13
 
< 0.1%
Other Symbol 4
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2384
 
6.2%
988
 
2.6%
900
 
2.3%
857
 
2.2%
798
 
2.1%
771
 
2.0%
729
 
1.9%
720
 
1.9%
695
 
1.8%
635
 
1.6%
Other values (699) 29157
75.5%
Lowercase Letter
ValueCountFrequency (%)
e 56
13.4%
o 40
 
9.5%
a 35
 
8.4%
i 27
 
6.4%
l 25
 
6.0%
u 24
 
5.7%
s 24
 
5.7%
c 21
 
5.0%
r 20
 
4.8%
n 19
 
4.5%
Other values (15) 128
30.5%
Uppercase Letter
ValueCountFrequency (%)
E 44
 
8.8%
M 42
 
8.4%
S 40
 
8.0%
O 36
 
7.2%
F 35
 
7.0%
T 35
 
7.0%
B 34
 
6.8%
A 24
 
4.8%
H 23
 
4.6%
C 23
 
4.6%
Other values (14) 163
32.7%
Decimal Number
ValueCountFrequency (%)
2 20
29.9%
1 18
26.9%
5 7
 
10.4%
0 6
 
9.0%
9 4
 
6.0%
4 4
 
6.0%
3 3
 
4.5%
7 2
 
3.0%
8 2
 
3.0%
6 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
& 39
48.1%
. 13
 
16.0%
, 10
 
12.3%
? 8
 
9.9%
' 7
 
8.6%
2
 
2.5%
: 1
 
1.2%
; 1
 
1.2%
Close Punctuation
ValueCountFrequency (%)
) 2116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2087
100.0%
Space Separator
ValueCountFrequency (%)
1077
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38627
85.8%
Common 5445
 
12.1%
Latin 918
 
2.0%
Han 11
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2384
 
6.2%
988
 
2.6%
900
 
2.3%
857
 
2.2%
798
 
2.1%
771
 
2.0%
729
 
1.9%
720
 
1.9%
695
 
1.8%
635
 
1.6%
Other values (691) 29150
75.5%
Latin
ValueCountFrequency (%)
e 56
 
6.1%
E 44
 
4.8%
M 42
 
4.6%
o 40
 
4.4%
S 40
 
4.4%
O 36
 
3.9%
F 35
 
3.8%
a 35
 
3.8%
T 35
 
3.8%
B 34
 
3.7%
Other values (39) 521
56.8%
Common
ValueCountFrequency (%)
) 2116
38.9%
( 2087
38.3%
1077
19.8%
& 39
 
0.7%
2 20
 
0.4%
1 18
 
0.3%
- 13
 
0.2%
. 13
 
0.2%
, 10
 
0.2%
? 8
 
0.1%
Other values (14) 44
 
0.8%
Han
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38623
85.8%
ASCII 6361
 
14.1%
CJK 11
 
< 0.1%
None 6
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2384
 
6.2%
988
 
2.6%
900
 
2.3%
857
 
2.2%
798
 
2.1%
771
 
2.0%
729
 
1.9%
720
 
1.9%
695
 
1.8%
635
 
1.6%
Other values (690) 29146
75.5%
ASCII
ValueCountFrequency (%)
) 2116
33.3%
( 2087
32.8%
1077
16.9%
e 56
 
0.9%
E 44
 
0.7%
M 42
 
0.7%
o 40
 
0.6%
S 40
 
0.6%
& 39
 
0.6%
O 36
 
0.6%
Other values (62) 784
 
12.3%
None
ValueCountFrequency (%)
4
66.7%
2
33.3%
CJK
ValueCountFrequency (%)
2
18.2%
2
18.2%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
1
9.1%
Distinct4396
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
Minimum1999-07-23 00:00:00
Maximum2024-04-04 13:15:18
2024-04-06T21:29:22.498741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:29:22.783867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
I
3615 
U
3259 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3615
52.6%
U 3259
47.4%

Length

2024-04-06T21:29:23.036735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:23.228800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3615
52.6%
u 3259
47.4%
Distinct1419
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:06:00
2024-04-06T21:29:23.466793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:29:23.753121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
즉석판매제조가공업
6736 
<NA>
 
138

Length

Max length9
Median length9
Mean length8.8996218
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 6736
98.0%
<NA> 138
 
2.0%

Length

2024-04-06T21:29:24.062830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:24.268745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 6736
98.0%
na 138
 
2.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1212
Distinct (%)18.3%
Missing242
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean191754.54
Minimum189574.96
Maximum227095.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.5 KiB
2024-04-06T21:29:24.531268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189574.96
5-th percentile190408.51
Q1191177.58
median191581.5
Q3191813.54
95-th percentile193592
Maximum227095.01
Range37520.045
Interquartile range (IQR)635.95643

Descriptive statistics

Standard deviation1056.6585
Coefficient of variation (CV)0.0055104746
Kurtosis187.93997
Mean191754.54
Median Absolute Deviation (MAD)301.88124
Skewness6.2326475
Sum1.2717161 × 109
Variance1116527.2
MonotonicityNot monotonic
2024-04-06T21:29:24.800833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
191581.500265536 956
13.9%
191741.345847708 867
 
12.6%
190729.506453391 715
 
10.4%
193393.096553574 520
 
7.6%
191385.057392247 482
 
7.0%
191503.386111551 303
 
4.4%
193592.000380036 273
 
4.0%
190352.321686588 156
 
2.3%
191800.728214995 80
 
1.2%
194037.750337785 67
 
1.0%
Other values (1202) 2213
32.2%
(Missing) 242
 
3.5%
ValueCountFrequency (%)
189574.962072527 1
< 0.1%
189600.341227589 1
< 0.1%
189600.906705305 1
< 0.1%
189641.475801911 2
< 0.1%
189659.894354143 2
< 0.1%
189667.63984485 1
< 0.1%
189688.377997607 2
< 0.1%
189700.355755718 1
< 0.1%
189706.676879911 1
< 0.1%
189721.341115554 2
< 0.1%
ValueCountFrequency (%)
227095.007421196 1
 
< 0.1%
194632.526367463 3
 
< 0.1%
194592.276750438 2
 
< 0.1%
194530.535390096 2
 
< 0.1%
194504.656267957 1
 
< 0.1%
194370.32715363 10
0.1%
194294.277022719 1
 
< 0.1%
194124.497455922 20
0.3%
194084.264051974 4
 
0.1%
194068.648710367 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING  SKEWED 

Distinct1212
Distinct (%)18.3%
Missing242
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean446073.02
Minimum442710.66
Maximum515851.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size60.5 KiB
2024-04-06T21:29:25.073735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442710.66
5-th percentile443809.77
Q1445970.31
median446108.81
Q3446397.62
95-th percentile447289.55
Maximum515851.76
Range73141.094
Interquartile range (IQR)427.31099

Descriptive statistics

Standard deviation1295.3121
Coefficient of variation (CV)0.0029038118
Kurtosis1269.6755
Mean446073.02
Median Absolute Deviation (MAD)138.49955
Skewness23.19441
Sum2.9583563 × 109
Variance1677833.4
MonotonicityNot monotonic
2024-04-06T21:29:25.411085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446108.807192753 956
13.9%
445970.307641467 867
 
12.6%
446227.07504062 715
 
10.4%
446218.443828439 520
 
7.6%
446098.555926507 482
 
7.0%
447289.548355449 303
 
4.4%
447092.629432527 273
 
4.0%
447095.641206789 156
 
2.3%
443809.773854649 80
 
1.2%
446477.41713322 67
 
1.0%
Other values (1202) 2213
32.2%
(Missing) 242
 
3.5%
ValueCountFrequency (%)
442710.662421803 2
< 0.1%
442782.832508026 1
 
< 0.1%
442840.662812027 1
 
< 0.1%
442893.464178613 1
 
< 0.1%
442896.305792763 1
 
< 0.1%
442905.116903156 4
0.1%
442913.875052132 2
< 0.1%
442914.915088521 1
 
< 0.1%
442919.355163851 1
 
< 0.1%
442919.522195885 1
 
< 0.1%
ValueCountFrequency (%)
515851.756314017 1
 
< 0.1%
448980.024828564 1
 
< 0.1%
448937.07552692 1
 
< 0.1%
448890.062553303 1
 
< 0.1%
448779.57454276 1
 
< 0.1%
448770.443757 1
 
< 0.1%
448695.440171614 1
 
< 0.1%
448667.181702536 1
 
< 0.1%
448656.726986041 13
0.2%
448648.996039329 1
 
< 0.1%

위생업태명
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
즉석판매제조가공업
5293 
<NA>
1581 

Length

Max length9
Median length9
Mean length7.8500145
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 5293
77.0%
<NA> 1581
 
23.0%

Length

2024-04-06T21:29:25.732605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:25.924591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 5293
77.0%
na 1581
 
23.0%

남성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6203 
0
 
588
1
 
72
2
 
10
3
 
1

Length

Max length4
Median length4
Mean length3.7071574
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6203
90.2%
0 588
 
8.6%
1 72
 
1.0%
2 10
 
0.1%
3 1
 
< 0.1%

Length

2024-04-06T21:29:26.156150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:26.381273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6203
90.2%
0 588
 
8.6%
1 72
 
1.0%
2 10
 
0.1%
3 1
 
< 0.1%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6210 
0
 
599
1
 
61
2
 
3
3
 
1

Length

Max length4
Median length4
Mean length3.7102124
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6210
90.3%
0 599
 
8.7%
1 61
 
0.9%
2 3
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-06T21:29:26.653861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:26.902837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6210
90.3%
0 599
 
8.7%
1 61
 
0.9%
2 3
 
< 0.1%
3 1
 
< 0.1%

영업장주변구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6517 
기타
 
253
주택가주변
 
84
아파트지역
 
13
유흥업소밀집지역
 
6

Length

Max length8
Median length4
Mean length3.9445738
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6517
94.8%
기타 253
 
3.7%
주택가주변 84
 
1.2%
아파트지역 13
 
0.2%
유흥업소밀집지역 6
 
0.1%
학교정화(상대) 1
 
< 0.1%

Length

2024-04-06T21:29:27.128891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:27.368142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6517
94.8%
기타 253
 
3.7%
주택가주변 84
 
1.2%
아파트지역 13
 
0.2%
유흥업소밀집지역 6
 
0.1%
학교정화(상대 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6517 
기타
 
224
자율
 
99
우수
 
34

Length

Max length4
Median length4
Mean length3.8961303
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6517
94.8%
기타 224
 
3.3%
자율 99
 
1.4%
우수 34
 
0.5%

Length

2024-04-06T21:29:27.606936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:27.812224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6517
94.8%
기타 224
 
3.3%
자율 99
 
1.4%
우수 34
 
0.5%

급수시설구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6630 
상수도전용
 
243
상수도(음용)지하수(주방용)겸용
 
1

Length

Max length17
Median length4
Mean length4.0372418
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6630
96.5%
상수도전용 243
 
3.5%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

Length

2024-04-06T21:29:28.019519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:28.210441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6630
96.5%
상수도전용 243
 
3.5%
상수도(음용)지하수(주방용)겸용 1
 
< 0.1%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6431 
0
 
443

Length

Max length4
Median length4
Mean length3.8066628
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> 6431
93.6%
0 443
 
6.4%

Length

2024-04-06T21:29:29.058089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:29.283954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6431
93.6%
0 443
 
6.4%

본사종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
5499 
0
1374 
1
 
1

Length

Max length4
Median length4
Mean length3.3999127
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5499
80.0%
0 1374
 
20.0%
1 1
 
< 0.1%

Length

2024-04-06T21:29:29.472811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:29.693396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5499
80.0%
0 1374
 
20.0%
1 1
 
< 0.1%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
5498 
0
1373 
1
 
3

Length

Max length4
Median length4
Mean length3.3994763
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5498
80.0%
0 1373
 
20.0%
1 3
 
< 0.1%

Length

2024-04-06T21:29:29.912607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:30.118127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5498
80.0%
0 1373
 
20.0%
1 3
 
< 0.1%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
5499 
0
1359 
1
 
16

Length

Max length4
Median length4
Mean length3.3999127
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5499
80.0%
0 1359
 
19.8%
1 16
 
0.2%

Length

2024-04-06T21:29:30.327206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:30.519575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5499
80.0%
0 1359
 
19.8%
1 16
 
0.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
5497 
0
1357 
1
 
17
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.3990399
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5497
80.0%
0 1357
 
19.7%
1 17
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%

Length

2024-04-06T21:29:30.741261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:30.960646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5497
80.0%
0 1357
 
19.7%
1 17
 
0.2%
2 2
 
< 0.1%
3 1
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
4817 
자가
1228 
임대
829 

Length

Max length4
Median length4
Mean length3.4015129
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4817
70.1%
자가 1228
 
17.9%
임대 829
 
12.1%

Length

2024-04-06T21:29:31.236705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:31.467641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4817
70.1%
자가 1228
 
17.9%
임대 829
 
12.1%

보증액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6057 
0
816 
5000000
 
1

Length

Max length7
Median length4
Mean length3.6443119
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6057
88.1%
0 816
 
11.9%
5000000 1
 
< 0.1%

Length

2024-04-06T21:29:31.671319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:31.920466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6057
88.1%
0 816
 
11.9%
5000000 1
 
< 0.1%

월세액
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.8 KiB
<NA>
6057 
0
816 
350000
 
1

Length

Max length6
Median length4
Mean length3.6441664
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6057
88.1%
0 816
 
11.9%
350000 1
 
< 0.1%

Length

2024-04-06T21:29:32.120782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:29:32.339628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6057
88.1%
0 816
 
11.9%
350000 1
 
< 0.1%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1444
Missing (%)21.0%
Memory size13.6 KiB
False
5430 
(Missing)
1444 
ValueCountFrequency (%)
False 5430
79.0%
(Missing) 1444
 
21.0%
2024-04-06T21:29:32.524229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct8
Distinct (%)0.1%
Missing1444
Missing (%)21.0%
Infinite0
Infinite (%)0.0%
Mean0.018683241
Minimum0
Maximum30
Zeros5422
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size60.5 KiB
2024-04-06T21:29:32.694617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.57500864
Coefficient of variation (CV)30.776707
Kurtosis1723.0548
Mean0.018683241
Median Absolute Deviation (MAD)0
Skewness38.835141
Sum101.45
Variance0.33063494
MonotonicityNot monotonic
2024-04-06T21:29:32.889857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 5422
78.9%
12.0 2
 
< 0.1%
7.8 1
 
< 0.1%
20.0 1
 
< 0.1%
3.75 1
 
< 0.1%
6.0 1
 
< 0.1%
9.9 1
 
< 0.1%
30.0 1
 
< 0.1%
(Missing) 1444
 
21.0%
ValueCountFrequency (%)
0.0 5422
78.9%
3.75 1
 
< 0.1%
6.0 1
 
< 0.1%
7.8 1
 
< 0.1%
9.9 1
 
< 0.1%
12.0 2
 
< 0.1%
20.0 1
 
< 0.1%
30.0 1
 
< 0.1%
ValueCountFrequency (%)
30.0 1
 
< 0.1%
20.0 1
 
< 0.1%
12.0 2
 
< 0.1%
9.9 1
 
< 0.1%
7.8 1
 
< 0.1%
6.0 1
 
< 0.1%
3.75 1
 
< 0.1%
0.0 5422
78.9%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6874
Missing (%)100.0%
Memory size60.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
031800003180000-107-1970-0026519700407<NA>3폐업2폐업20100330<NA><NA><NA>02.00150839서울특별시 영등포구 신길동 116-2<NA><NA>강원참기름2005-02-02 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA>주택가주변기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
131800003180000-107-1970-0077219700402<NA>3폐업2폐업20071228<NA><NA><NA>022634686312.95150035서울특별시 영등포구 영등포동5가 276-0<NA><NA>형제상회2008-01-08 14:25:09I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업00기타기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
231800003180000-107-1972-0027219721103<NA>3폐업2폐업20040209<NA><NA><NA>022634254321.00150035서울특별시 영등포구 영등포동5가 116-0<NA><NA>도매기름집2003-04-18 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업191622.866992446596.190567즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
331800003180000-107-1972-0028119720703<NA>3폐업2폐업20070103<NA><NA><NA>02 832565612.39150841서울특별시 영등포구 신길동 259-104<NA><NA>동아기름집2007-01-03 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업<NA><NA>즉석판매제조가공업<NA><NA>주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
431800003180000-107-1972-002851972-05-15<NA>3폐업2폐업2023-03-02<NA><NA><NA>02 832277013.22150-822서울특별시 영등포구 대림동 967-7 제2호 내 제15호서울특별시 영등포구 대림로8길 26 (대림동,제2호 내 제15호)7442동보기름집2023-03-06 09:50:32U2022-12-03 00:08:00.0즉석판매제조가공업191661.176367443279.67336<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531800003180000-107-1972-0028719721202<NA>3폐업2폐업19991215<NA><NA><NA>02.00150839서울특별시 영등포구 신길동 116-15<NA><NA>대명제유소1999-12-15 00:00:00I2018-08-31 23:59:59.0<NA>192643.702398445431.520857<NA>00기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
631800003180000-107-1972-0028819720311<NA>3폐업2폐업20070703<NA><NA><NA><NA><NA>150832서울특별시 영등포구 도림동 168-13<NA><NA>황해기름집2006-05-22 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업190975.565177445323.360126즉석판매제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
731800003180000-107-1973-002551973-10-30<NA>1영업/정상1영업<NA><NA><NA><NA>022633834046.28150-042서울특별시 영등포구 당산동2가 47-4서울특별시 영등포구 양산로 96, 1층 A1-1호 (당산동2가)7264영동기름집2023-10-16 16:17:48U2022-10-30 23:08:00.0즉석판매제조가공업190522.614008446846.651846<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831800003180000-107-1973-0026419731004<NA>3폐업2폐업19960618<NA><NA><NA>0222.92150839서울특별시 영등포구 신길동 116-15<NA><NA>선양제유소2003-07-18 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업192643.702398445431.520857즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
931800003180000-107-1973-0026719731015<NA>3폐업2폐업20020423<NA><NA><NA>022634206715.30150035서울특별시 영등포구 영등포동5가 43-3<NA><NA>부산제유소2003-05-21 00:00:00I2018-08-31 23:59:59.0즉석판매제조가공업191714.631198446530.034494즉석판매제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
686431800003180000-107-2024-001312024-03-27<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.16150-094서울특별시 영등포구 문래동4가 21-24서울특별시 영등포구 도림로141길 14, 1층 (문래동4가)7288마이스페이스랩2024-03-27 16:59:49I2023-12-02 22:09:00.0즉석판매제조가공업190395.23504445779.80439<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
686531800003180000-107-2024-001322024-03-28<NA>3폐업2폐업2024-04-02<NA><NA><NA><NA>0.00150-010서울특별시 영등포구 여의도동 82-3 영등포여의도봄꽃축제 메인행사장<NA><NA>마파도떡집2024-04-03 04:15:10U2023-12-04 00:05:00.0즉석판매제조가공업192777.796182447953.45795<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
686631800003180000-107-2024-001332024-03-29<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00150-854서울특별시 영등포구 신길동 861 일이빌딩서울특별시 영등포구 여의대방로 203, 하나로마트 여의대방로점 101,102호 (신길동)7360(주)대산유통시스템2024-03-29 10:55:21I2023-12-02 21:01:00.0즉석판매제조가공업193034.345963444796.372058<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
686731800003180000-107-2024-001342024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00150-798서울특별시 영등포구 영등포동4가 442 타임스퀘어서울특별시 영등포구 영중로 15, 타임스퀘어 지하1층 (영등포동4가)7305더블에스푸드2024-04-01 10:50:15I2023-12-04 00:03:00.0즉석판매제조가공업191385.057392446098.555927<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
686831800003180000-107-2024-001352024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA>07043009589<NA>150-899서울특별시 영등포구 영등포동 618-496 영등포 민자역사서울특별시 영등포구 경인로 846, 영등포 민자역사 지하1층 (영등포동)7306(주)명류당티에프2024-04-01 15:01:47I2023-12-04 00:03:00.0즉석판매제조가공업191741.345848445970.307641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
686931800003180000-107-2024-001362024-04-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-899서울특별시 영등포구 영등포동 618-496 영등포 민자역사서울특별시 영등포구 경인로 846, 영등포 민자역사 지하1층 (영등포동)7306(주)신원씨푸드2024-04-01 15:04:11I2023-12-04 00:03:00.0즉석판매제조가공업191741.345848445970.307641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
687031800003180000-107-2024-001372024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-899서울특별시 영등포구 영등포동 618-496 영등포 민자역사서울특별시 영등포구 경인로 846, 영등포 민자역사 3층 (영등포동)7306하루온도2024-04-02 09:43:59I2023-12-04 00:04:00.0즉석판매제조가공업191741.345848445970.307641<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
687131800003180000-107-2024-001382024-04-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-985서울특별시 영등포구 영등포동4가 434-5 신세계백화점서울특별시 영등포구 영중로 9, 신세계백화점 지하1층 (영등포동4가)7305(주)벨라비지니스2024-04-02 18:29:53I2023-12-04 00:04:00.0즉석판매제조가공업191581.500266446108.807193<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
687231800003180000-107-2024-001392024-04-03<NA>1영업/정상1영업<NA><NA><NA><NA><NA>0.00150-991서울특별시 영등포구 문래동3가 55-3 홈플러스서울특별시 영등포구 당산로 42, 홈플러스 영등포점 2층 (문래동3가)7297(주)제이수산2024-04-03 15:31:25I2023-12-04 00:05:00.0즉석판매제조가공업190729.506453446227.075041<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
687331800003180000-107-2024-001402024-04-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA>150-823서울특별시 영등포구 대림동 990-86 태영빌딩서울특별시 영등포구 시흥대로177길 1, 태영빌딩 지하층 (대림동)7444백두산천지인2024-04-04 13:15:18I2023-12-04 00:06:00.0즉석판매제조가공업191572.800814442919.522196<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>