Overview

Dataset statistics

Number of variables44
Number of observations472
Missing cells4146
Missing cells (%)20.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory173.0 KiB
Average record size in memory375.3 B

Variable types

Categorical21
Text7
DateTime4
Unsupported6
Numeric5
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-18276/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
홈페이지 has constant value ""Constant
영업상태코드 is highly imbalanced (58.1%)Imbalance
영업상태명 is highly imbalanced (58.1%)Imbalance
상세영업상태코드 is highly imbalanced (58.1%)Imbalance
상세영업상태명 is highly imbalanced (58.1%)Imbalance
업태구분명 is highly imbalanced (51.2%)Imbalance
위생업태명 is highly imbalanced (58.4%)Imbalance
남성종사자수 is highly imbalanced (55.2%)Imbalance
여성종사자수 is highly imbalanced (58.8%)Imbalance
총인원 is highly imbalanced (85.2%)Imbalance
공장생산직종업원수 is highly imbalanced (53.5%)Imbalance
보증액 is highly imbalanced (67.0%)Imbalance
월세액 is highly imbalanced (62.7%)Imbalance
인허가취소일자 has 472 (100.0%) missing valuesMissing
폐업일자 has 40 (8.5%) missing valuesMissing
휴업시작일자 has 472 (100.0%) missing valuesMissing
휴업종료일자 has 472 (100.0%) missing valuesMissing
재개업일자 has 472 (100.0%) missing valuesMissing
전화번호 has 109 (23.1%) missing valuesMissing
소재지면적 has 7 (1.5%) missing valuesMissing
도로명주소 has 308 (65.3%) missing valuesMissing
도로명우편번호 has 309 (65.5%) missing valuesMissing
좌표정보(X) has 7 (1.5%) missing valuesMissing
좌표정보(Y) has 7 (1.5%) missing valuesMissing
다중이용업소여부 has 27 (5.7%) missing valuesMissing
시설총규모 has 27 (5.7%) missing valuesMissing
전통업소지정번호 has 472 (100.0%) missing valuesMissing
전통업소주된음식 has 472 (100.0%) missing valuesMissing
홈페이지 has 471 (99.8%) 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
소재지면적 has 5 (1.1%) zerosZeros
시설총규모 has 410 (86.9%) zerosZeros

Reproduction

Analysis started2024-04-17 22:12:53.960231
Analysis finished2024-04-17 22:12:54.620781
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3240000
472 

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 472
100.0%

Length

2024-04-18T07:12:54.666954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:12:54.732293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 472
100.0%

관리번호
Text

UNIQUE 

Distinct472
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-04-18T07:12:54.861178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters10384
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

Unique472 ?
Unique (%)100.0%

Sample

1st row3240000-106-1989-00001
2nd row3240000-106-1989-00012
3rd row3240000-106-1989-01064
4th row3240000-106-1990-00043
5th row3240000-106-1992-00016
ValueCountFrequency (%)
3240000-106-1989-00001 1
 
0.2%
3240000-106-2009-00009 1
 
0.2%
3240000-106-2010-00007 1
 
0.2%
3240000-106-2010-00006 1
 
0.2%
3240000-106-2010-00005 1
 
0.2%
3240000-106-2010-00004 1
 
0.2%
3240000-106-2010-00003 1
 
0.2%
3240000-106-2010-00002 1
 
0.2%
3240000-106-2010-00001 1
 
0.2%
3240000-106-2009-00014 1
 
0.2%
Other values (462) 462
97.9%
2024-04-18T07:12:55.125500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4474
43.1%
- 1416
 
13.6%
2 1048
 
10.1%
1 1019
 
9.8%
3 638
 
6.1%
4 591
 
5.7%
6 569
 
5.5%
9 305
 
2.9%
5 122
 
1.2%
8 108
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8968
86.4%
Dash Punctuation 1416
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4474
49.9%
2 1048
 
11.7%
1 1019
 
11.4%
3 638
 
7.1%
4 591
 
6.6%
6 569
 
6.3%
9 305
 
3.4%
5 122
 
1.4%
8 108
 
1.2%
7 94
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1416
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4474
43.1%
- 1416
 
13.6%
2 1048
 
10.1%
1 1019
 
9.8%
3 638
 
6.1%
4 591
 
5.7%
6 569
 
5.5%
9 305
 
2.9%
5 122
 
1.2%
8 108
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4474
43.1%
- 1416
 
13.6%
2 1048
 
10.1%
1 1019
 
9.8%
3 638
 
6.1%
4 591
 
5.7%
6 569
 
5.5%
9 305
 
2.9%
5 122
 
1.2%
8 108
 
1.0%

인허가일자
Date

Distinct446
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum1989-05-26 00:00:00
Maximum2024-02-02 00:00:00
2024-04-18T07:12:55.262020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:12:55.387803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
3
432 
1
 
40

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 (%)
3 432
91.5%
1 40
 
8.5%

Length

2024-04-18T07:12:55.487127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:12:55.566169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 432
91.5%
1 40
 
8.5%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
432 
영업/정상
 
40

Length

Max length5
Median length2
Mean length2.2542373
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 432
91.5%
영업/정상 40
 
8.5%

Length

2024-04-18T07:12:55.651354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:12:55.735091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 432
91.5%
영업/정상 40
 
8.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2
432 
1
 
40

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 (%)
2 432
91.5%
1 40
 
8.5%

Length

2024-04-18T07:12:55.826156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:12:55.915242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 432
91.5%
1 40
 
8.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
폐업
432 
영업
 
40

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 432
91.5%
영업 40
 
8.5%

Length

2024-04-18T07:12:55.990159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:12:56.062508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 432
91.5%
영업 40
 
8.5%

폐업일자
Date

MISSING 

Distinct385
Distinct (%)89.1%
Missing40
Missing (%)8.5%
Memory size3.8 KiB
Minimum1997-07-18 00:00:00
Maximum2024-03-04 00:00:00
2024-04-18T07:12:56.144785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:12:56.244066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

전화번호
Text

MISSING 

Distinct320
Distinct (%)88.2%
Missing109
Missing (%)23.1%
Memory size3.8 KiB
2024-04-18T07:12:56.483317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length9.785124
Min length2

Characters and Unicode

Total characters3552
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

Unique313 ?
Unique (%)86.2%

Sample

1st row02 4866748
2nd row02 4729693
3rd row02 4871841
4th row02 0
5th row02
ValueCountFrequency (%)
02 308
41.5%
070 15
 
2.0%
481 6
 
0.8%
473 5
 
0.7%
489 5
 
0.7%
471 5
 
0.7%
484 5
 
0.7%
442 4
 
0.5%
475 4
 
0.5%
0 4
 
0.5%
Other values (357) 382
51.4%
2024-04-18T07:12:56.813330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 599
16.9%
0 571
16.1%
497
14.0%
4 470
13.2%
8 287
8.1%
7 270
7.6%
1 190
 
5.3%
3 180
 
5.1%
6 173
 
4.9%
5 160
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3055
86.0%
Space Separator 497
 
14.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 599
19.6%
0 571
18.7%
4 470
15.4%
8 287
9.4%
7 270
8.8%
1 190
 
6.2%
3 180
 
5.9%
6 173
 
5.7%
5 160
 
5.2%
9 155
 
5.1%
Space Separator
ValueCountFrequency (%)
497
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 599
16.9%
0 571
16.1%
497
14.0%
4 470
13.2%
8 287
8.1%
7 270
7.6%
1 190
 
5.3%
3 180
 
5.1%
6 173
 
4.9%
5 160
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 599
16.9%
0 571
16.1%
497
14.0%
4 470
13.2%
8 287
8.1%
7 270
7.6%
1 190
 
5.3%
3 180
 
5.1%
6 173
 
4.9%
5 160
 
4.5%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct346
Distinct (%)74.4%
Missing7
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean78.225871
Minimum0
Maximum921.83
Zeros5
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-18T07:12:56.943680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.128
Q126.4
median59.28
Q3102
95-th percentile213.576
Maximum921.83
Range921.83
Interquartile range (IQR)75.6

Descriptive statistics

Standard deviation81.437275
Coefficient of variation (CV)1.041053
Kurtosis28.138414
Mean78.225871
Median Absolute Deviation (MAD)36.18
Skewness3.881275
Sum36375.03
Variance6632.0297
MonotonicityNot monotonic
2024-04-18T07:12:57.051076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.0 19
 
4.0%
66.0 8
 
1.7%
99.0 7
 
1.5%
30.0 6
 
1.3%
23.1 6
 
1.3%
0.0 5
 
1.1%
26.4 5
 
1.1%
20.0 5
 
1.1%
60.0 5
 
1.1%
45.0 4
 
0.8%
Other values (336) 395
83.7%
(Missing) 7
 
1.5%
ValueCountFrequency (%)
0.0 5
1.1%
3.3 1
 
0.2%
6.6 2
 
0.4%
7.34 1
 
0.2%
8.15 1
 
0.2%
8.58 1
 
0.2%
8.65 1
 
0.2%
9.2 1
 
0.2%
9.5 1
 
0.2%
9.9 1
 
0.2%
ValueCountFrequency (%)
921.83 1
0.2%
486.56 1
0.2%
458.0 1
0.2%
453.0 1
0.2%
428.4 1
0.2%
353.0 1
0.2%
323.0 1
0.2%
319.0 1
0.2%
317.9 1
0.2%
298.73 1
0.2%

소재지우편번호
Text

Distinct94
Distinct (%)20.0%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-04-18T07:12:57.238150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0403397
Min length6

Characters and Unicode

Total characters2845
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

Unique37 ?
Unique (%)7.9%

Sample

1st row134866
2nd row134830
3rd row134840
4th row134858
5th row134861
ValueCountFrequency (%)
134830 25
 
5.3%
134837 21
 
4.5%
134861 18
 
3.8%
134867 14
 
3.0%
134859 14
 
3.0%
134877 14
 
3.0%
134851 12
 
2.5%
134844 12
 
2.5%
134808 11
 
2.3%
134812 11
 
2.3%
Other values (84) 319
67.7%
2024-04-18T07:12:57.533031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 592
20.8%
4 580
20.4%
3 549
19.3%
8 539
18.9%
0 132
 
4.6%
7 124
 
4.4%
6 106
 
3.7%
5 105
 
3.7%
2 57
 
2.0%
9 42
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2826
99.3%
Dash Punctuation 19
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 592
20.9%
4 580
20.5%
3 549
19.4%
8 539
19.1%
0 132
 
4.7%
7 124
 
4.4%
6 106
 
3.8%
5 105
 
3.7%
2 57
 
2.0%
9 42
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2845
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 592
20.8%
4 580
20.4%
3 549
19.3%
8 539
18.9%
0 132
 
4.6%
7 124
 
4.4%
6 106
 
3.7%
5 105
 
3.7%
2 57
 
2.0%
9 42
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2845
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 592
20.8%
4 580
20.4%
3 549
19.3%
8 539
18.9%
0 132
 
4.6%
7 124
 
4.4%
6 106
 
3.7%
5 105
 
3.7%
2 57
 
2.0%
9 42
 
1.5%

지번주소
Text

Distinct440
Distinct (%)93.4%
Missing1
Missing (%)0.2%
Memory size3.8 KiB
2024-04-18T07:12:57.751968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length24.186837
Min length17

Characters and Unicode

Total characters11392
Distinct characters132
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

Unique412 ?
Unique (%)87.5%

Sample

1st row서울특별시 강동구 천호동 224-40번지
2nd row서울특별시 강동구 명일동 342-19번지
3rd row서울특별시 강동구 성내동 29-10번지
4th row서울특별시 강동구 암사동 456-84번지
5th row서울특별시 강동구 천호동 18-63번지
ValueCountFrequency (%)
서울특별시 471
22.3%
강동구 471
22.3%
성내동 109
 
5.2%
천호동 92
 
4.4%
암사동 69
 
3.3%
길동 64
 
3.0%
명일동 44
 
2.1%
상일동 34
 
1.6%
1층 31
 
1.5%
둔촌동 29
 
1.4%
Other values (522) 696
33.0%
2024-04-18T07:12:58.519045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2059
18.1%
동 959
 
8.4%
지 486
 
4.3%
시 476
 
4.2%
강 476
 
4.2%
서 472
 
4.1%
울 472
 
4.1%
특 471
 
4.1%
별 471
 
4.1%
구 471
 
4.1%
Other values (122) 4579
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6529
57.3%
Decimal Number 2294
 
20.1%
Space Separator 2059
 
18.1%
Dash Punctuation 437
 
3.8%
Close Punctuation 23
 
0.2%
Open Punctuation 23
 
0.2%
Other Punctuation 16
 
0.1%
Uppercase Letter 9
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 959
14.7%
지 486
 
7.4%
시 476
 
7.3%
강 476
 
7.3%
서 472
 
7.2%
울 472
 
7.2%
특 471
 
7.2%
별 471
 
7.2%
구 471
 
7.2%
번 421
 
6.4%
Other values (97) 1354
20.7%
Decimal Number
ValueCountFrequency (%)
1 453
19.7%
4 332
14.5%
2 308
13.4%
3 261
11.4%
5 226
9.9%
0 205
8.9%
8 132
 
5.8%
9 129
 
5.6%
7 128
 
5.6%
6 120
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
33.3%
M 1
 
11.1%
A 1
 
11.1%
K 1
 
11.1%
N 1
 
11.1%
P 1
 
11.1%
F 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 14
87.5%
@ 1
 
6.2%
. 1
 
6.2%
Space Separator
ValueCountFrequency (%)
2059
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 437
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6529
57.3%
Common 4854
42.6%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 959
14.7%
지 486
 
7.4%
시 476
 
7.3%
강 476
 
7.3%
서 472
 
7.2%
울 472
 
7.2%
특 471
 
7.2%
별 471
 
7.2%
구 471
 
7.2%
번 421
 
6.4%
Other values (97) 1354
20.7%
Common
ValueCountFrequency (%)
2059
42.4%
1 453
 
9.3%
- 437
 
9.0%
4 332
 
6.8%
2 308
 
6.3%
3 261
 
5.4%
5 226
 
4.7%
0 205
 
4.2%
8 132
 
2.7%
9 129
 
2.7%
Other values (8) 312
 
6.4%
Latin
ValueCountFrequency (%)
B 3
33.3%
M 1
 
11.1%
A 1
 
11.1%
K 1
 
11.1%
N 1
 
11.1%
P 1
 
11.1%
F 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6529
57.3%
ASCII 4863
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2059
42.3%
1 453
 
9.3%
- 437
 
9.0%
4 332
 
6.8%
2 308
 
6.3%
3 261
 
5.4%
5 226
 
4.6%
0 205
 
4.2%
8 132
 
2.7%
9 129
 
2.7%
Other values (15) 321
 
6.6%
Hangul
ValueCountFrequency (%)
동 959
14.7%
지 486
 
7.4%
시 476
 
7.3%
강 476
 
7.3%
서 472
 
7.2%
울 472
 
7.2%
특 471
 
7.2%
별 471
 
7.2%
구 471
 
7.2%
번 421
 
6.4%
Other values (97) 1354
20.7%

도로명주소
Text

MISSING 

Distinct162
Distinct (%)98.8%
Missing308
Missing (%)65.3%
Memory size3.8 KiB
2024-04-18T07:12:58.762357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length44
Mean length30.52439
Min length22

Characters and Unicode

Total characters5006
Distinct characters113
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

Unique160 ?
Unique (%)97.6%

Sample

1st row서울특별시 강동구 구천면로62길 33 (천호동)
2nd row서울특별시 강동구 상암로4길 43 (암사동,지층)
3rd row서울특별시 강동구 고덕로25길 12-7 (암사동)
4th row서울특별시 강동구 천중로 27-11, 지하, 1층 (천호동)
5th row서울특별시 강동구 고덕로23길 12 (암사동)
ValueCountFrequency (%)
서울특별시 164
 
16.6%
강동구 164
 
16.6%
1층 43
 
4.4%
성내동 41
 
4.2%
천호동 25
 
2.5%
암사동 18
 
1.8%
명일동 17
 
1.7%
둔촌동 17
 
1.7%
길동 17
 
1.7%
양재대로 12
 
1.2%
Other values (294) 468
47.5%
2024-04-18T07:12:59.137773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
822
 
16.4%
동 347
 
6.9%
1 246
 
4.9%
구 184
 
3.7%
( 171
 
3.4%
) 171
 
3.4%
강 170
 
3.4%
시 168
 
3.4%
울 165
 
3.3%
서 165
 
3.3%
Other values (103) 2397
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2833
56.6%
Decimal Number 841
 
16.8%
Space Separator 822
 
16.4%
Open Punctuation 171
 
3.4%
Close Punctuation 171
 
3.4%
Other Punctuation 138
 
2.8%
Dash Punctuation 23
 
0.5%
Uppercase Letter 5
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 347
 
12.2%
구 184
 
6.5%
강 170
 
6.0%
시 168
 
5.9%
울 165
 
5.8%
서 165
 
5.8%
별 164
 
5.8%
특 164
 
5.8%
로 162
 
5.7%
길 117
 
4.1%
Other values (84) 1027
36.3%
Decimal Number
ValueCountFrequency (%)
1 246
29.3%
2 112
13.3%
0 76
 
9.0%
3 72
 
8.6%
5 67
 
8.0%
6 59
 
7.0%
4 56
 
6.7%
7 55
 
6.5%
9 54
 
6.4%
8 44
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
F 1
 
20.0%
M 1
 
20.0%
Space Separator
ValueCountFrequency (%)
822
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Other Punctuation
ValueCountFrequency (%)
, 138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2833
56.6%
Common 2168
43.3%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 347
 
12.2%
구 184
 
6.5%
강 170
 
6.0%
시 168
 
5.9%
울 165
 
5.8%
서 165
 
5.8%
별 164
 
5.8%
특 164
 
5.8%
로 162
 
5.7%
길 117
 
4.1%
Other values (84) 1027
36.3%
Common
ValueCountFrequency (%)
822
37.9%
1 246
 
11.3%
( 171
 
7.9%
) 171
 
7.9%
, 138
 
6.4%
2 112
 
5.2%
0 76
 
3.5%
3 72
 
3.3%
5 67
 
3.1%
6 59
 
2.7%
Other values (6) 234
 
10.8%
Latin
ValueCountFrequency (%)
B 3
60.0%
F 1
 
20.0%
M 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2833
56.6%
ASCII 2173
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
822
37.8%
1 246
 
11.3%
( 171
 
7.9%
) 171
 
7.9%
, 138
 
6.4%
2 112
 
5.2%
0 76
 
3.5%
3 72
 
3.3%
5 67
 
3.1%
6 59
 
2.7%
Other values (9) 239
 
11.0%
Hangul
ValueCountFrequency (%)
동 347
 
12.2%
구 184
 
6.5%
강 170
 
6.0%
시 168
 
5.9%
울 165
 
5.8%
서 165
 
5.8%
별 164
 
5.8%
특 164
 
5.8%
로 162
 
5.7%
길 117
 
4.1%
Other values (84) 1027
36.3%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct96
Distinct (%)58.9%
Missing309
Missing (%)65.5%
Infinite0
Infinite (%)0.0%
Mean5322.8221
Minimum5211
Maximum5408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-18T07:12:59.257201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5211
5-th percentile5236.1
Q15268.5
median5326
Q35376.5
95-th percentile5402.9
Maximum5408
Range197
Interquartile range (IQR)108

Descriptive statistics

Standard deviation58.799085
Coefficient of variation (CV)0.0110466
Kurtosis-1.3574973
Mean5322.8221
Median Absolute Deviation (MAD)56
Skewness-0.13749622
Sum867620
Variance3457.3323
MonotonicityNot monotonic
2024-04-18T07:12:59.388166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5398 6
 
1.3%
5260 5
 
1.1%
5364 4
 
0.8%
5282 4
 
0.8%
5344 3
 
0.6%
5269 3
 
0.6%
5295 3
 
0.6%
5237 3
 
0.6%
5406 3
 
0.6%
5304 3
 
0.6%
Other values (86) 126
26.7%
(Missing) 309
65.5%
ValueCountFrequency (%)
5211 1
 
0.2%
5220 1
 
0.2%
5221 1
 
0.2%
5222 2
0.4%
5227 1
 
0.2%
5232 1
 
0.2%
5235 1
 
0.2%
5236 1
 
0.2%
5237 3
0.6%
5238 1
 
0.2%
ValueCountFrequency (%)
5408 2
 
0.4%
5407 1
 
0.2%
5406 3
0.6%
5404 2
 
0.4%
5403 1
 
0.2%
5402 2
 
0.4%
5401 1
 
0.2%
5400 1
 
0.2%
5399 3
0.6%
5398 6
1.3%

사업장명
Text

Distinct444
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
2024-04-18T07:12:59.623840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length5.565678
Min length1

Characters and Unicode

Total characters2627
Distinct characters428
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

Unique416 ?
Unique (%)88.1%

Sample

1st row고향유과
2nd row왕궁병과
3rd row대영식품
4th row서해식품
5th row연서식품
ValueCountFrequency (%)
주식회사 11
 
2.1%
통밀로만 2
 
0.4%
한강식품 2
 
0.4%
민들레 2
 
0.4%
원식품 2
 
0.4%
인크레더블 2
 
0.4%
덕산식품 2
 
0.4%
초코박스 2
 
0.4%
조은푸드 2
 
0.4%
청정식품 2
 
0.4%
Other values (466) 489
94.4%
2024-04-18T07:12:59.987212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 164
 
6.2%
품 149
 
5.7%
주 73
 
2.8%
( 62
 
2.4%
) 62
 
2.4%
스 51
 
1.9%
47
 
1.8%
드 46
 
1.8%
푸 43
 
1.6%
리 38
 
1.4%
Other values (418) 1892
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2353
89.6%
Open Punctuation 62
 
2.4%
Close Punctuation 62
 
2.4%
Uppercase Letter 49
 
1.9%
Space Separator 47
 
1.8%
Lowercase Letter 44
 
1.7%
Other Punctuation 6
 
0.2%
Decimal Number 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 164
 
7.0%
품 149
 
6.3%
주 73
 
3.1%
스 51
 
2.2%
드 46
 
2.0%
푸 43
 
1.8%
리 38
 
1.6%
이 35
 
1.5%
사 33
 
1.4%
피 28
 
1.2%
Other values (377) 1693
72.0%
Lowercase Letter
ValueCountFrequency (%)
e 11
25.0%
o 6
13.6%
s 5
11.4%
f 4
 
9.1%
r 3
 
6.8%
c 3
 
6.8%
i 2
 
4.5%
n 1
 
2.3%
t 1
 
2.3%
a 1
 
2.3%
Other values (7) 7
15.9%
Uppercase Letter
ValueCountFrequency (%)
O 7
14.3%
F 7
14.3%
A 5
10.2%
M 4
8.2%
J 4
8.2%
D 3
 
6.1%
B 3
 
6.1%
R 3
 
6.1%
C 2
 
4.1%
Y 2
 
4.1%
Other values (6) 9
18.4%
Other Punctuation
ValueCountFrequency (%)
& 3
50.0%
. 3
50.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
9 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Space Separator
ValueCountFrequency (%)
47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2353
89.6%
Common 181
 
6.9%
Latin 93
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 164
 
7.0%
품 149
 
6.3%
주 73
 
3.1%
스 51
 
2.2%
드 46
 
2.0%
푸 43
 
1.8%
리 38
 
1.6%
이 35
 
1.5%
사 33
 
1.4%
피 28
 
1.2%
Other values (377) 1693
72.0%
Latin
ValueCountFrequency (%)
e 11
 
11.8%
O 7
 
7.5%
F 7
 
7.5%
o 6
 
6.5%
A 5
 
5.4%
s 5
 
5.4%
M 4
 
4.3%
J 4
 
4.3%
f 4
 
4.3%
r 3
 
3.2%
Other values (23) 37
39.8%
Common
ValueCountFrequency (%)
( 62
34.3%
) 62
34.3%
47
26.0%
& 3
 
1.7%
. 3
 
1.7%
2 2
 
1.1%
9 1
 
0.6%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2353
89.6%
ASCII 274
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 164
 
7.0%
품 149
 
6.3%
주 73
 
3.1%
스 51
 
2.2%
드 46
 
2.0%
푸 43
 
1.8%
리 38
 
1.6%
이 35
 
1.5%
사 33
 
1.4%
피 28
 
1.2%
Other values (377) 1693
72.0%
ASCII
ValueCountFrequency (%)
( 62
22.6%
) 62
22.6%
47
17.2%
e 11
 
4.0%
O 7
 
2.6%
F 7
 
2.6%
o 6
 
2.2%
A 5
 
1.8%
s 5
 
1.8%
M 4
 
1.5%
Other values (31) 58
21.2%

최종수정일자
Date

Distinct334
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2002-06-24 00:00:00
Maximum2024-03-04 09:40:25
2024-04-18T07:13:00.102582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:13:00.216930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
I
413 
U
59 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 413
87.5%
U 59
 
12.5%

Length

2024-04-18T07:13:00.327429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:00.400123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 413
87.5%
u 59
 
12.5%

데이터갱신일자
Date

Distinct69
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-18T07:13:00.485976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T07:13:00.599768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식품제조가공업
422 
기타 식품제조가공업
50 

Length

Max length10
Median length7
Mean length7.3177966
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 422
89.4%
기타 식품제조가공업 50
 
10.6%

Length

2024-04-18T07:13:00.703129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:00.778913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 472
90.4%
기타 50
 
9.6%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct388
Distinct (%)83.4%
Missing7
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean212294.43
Minimum210553.29
Maximum215984.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-18T07:13:00.864219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210553.29
5-th percentile210810.87
Q1211417.69
median212002
Q3212747.77
95-th percentile215050.6
Maximum215984.38
Range5431.0848
Interquartile range (IQR)1330.0726

Descriptive statistics

Standard deviation1192.3219
Coefficient of variation (CV)0.0056163598
Kurtosis0.52631075
Mean212294.43
Median Absolute Deviation (MAD)669.74692
Skewness1.0628287
Sum98716911
Variance1421631.6
MonotonicityNot monotonic
2024-04-18T07:13:00.982105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211820.878022259 8
 
1.7%
215039.878759936 4
 
0.8%
211005.592615772 3
 
0.6%
215195.884311721 3
 
0.6%
211387.261448627 3
 
0.6%
214261.728538887 3
 
0.6%
212589.271821152 3
 
0.6%
211945.75150179 3
 
0.6%
211296.408208918 3
 
0.6%
211768.627508789 3
 
0.6%
Other values (378) 429
90.9%
(Missing) 7
 
1.5%
ValueCountFrequency (%)
210553.290352325 1
0.2%
210558.095600946 1
0.2%
210566.875626134 1
0.2%
210646.333780619 1
0.2%
210649.789630326 1
0.2%
210670.369892293 1
0.2%
210670.952245602 1
0.2%
210679.700401659 1
0.2%
210680.495550202 1
0.2%
210695.489462651 1
0.2%
ValueCountFrequency (%)
215984.375136997 1
 
0.2%
215383.034106 1
 
0.2%
215203.880915796 1
 
0.2%
215203.799066155 1
 
0.2%
215199.030430497 1
 
0.2%
215195.884311721 3
0.6%
215184.811228094 1
 
0.2%
215178.170771585 1
 
0.2%
215177.804033096 1
 
0.2%
215165.55837609 1
 
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct388
Distinct (%)83.4%
Missing7
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean448914.19
Minimum446598.59
Maximum451774.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-18T07:13:01.098622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446598.59
5-th percentile447243.08
Q1447902.39
median448996.3
Q3449773.29
95-th percentile450763.02
Maximum451774.81
Range5176.2221
Interquartile range (IQR)1870.8999

Descriptive statistics

Standard deviation1110.2847
Coefficient of variation (CV)0.0024732671
Kurtosis-0.94541581
Mean448914.19
Median Absolute Deviation (MAD)858.77263
Skewness-0.046904094
Sum2.087451 × 108
Variance1232732.1
MonotonicityNot monotonic
2024-04-18T07:13:01.212808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449831.785568227 8
 
1.7%
449718.935741553 4
 
0.8%
449849.487759525 3
 
0.6%
449734.105973658 3
 
0.6%
447200.708513892 3
 
0.6%
451120.470507797 3
 
0.6%
448309.859890034 3
 
0.6%
447499.664124657 3
 
0.6%
447520.782684761 3
 
0.6%
450044.412968518 3
 
0.6%
Other values (378) 429
90.9%
(Missing) 7
 
1.5%
ValueCountFrequency (%)
446598.591776331 2
0.4%
446761.604007505 1
0.2%
446766.631391106 1
0.2%
446778.592045172 1
0.2%
446852.349671616 1
0.2%
446929.529955121 1
0.2%
446973.81658404 1
0.2%
446997.779797512 2
0.4%
447018.474433978 2
0.4%
447096.587093501 1
0.2%
ValueCountFrequency (%)
451774.813888 1
 
0.2%
451176.800389109 1
 
0.2%
451120.470507797 3
0.6%
451105.958039247 1
 
0.2%
451089.512929808 1
 
0.2%
451070.983805542 1
 
0.2%
451056.41688458 1
 
0.2%
451038.254762313 1
 
0.2%
451010.585461397 1
 
0.2%
450999.756309109 1
 
0.2%

위생업태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
식품제조가공업
414 
기타 식품제조가공업
 
31
<NA>
 
27

Length

Max length10
Median length7
Mean length7.0254237
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 414
87.7%
기타 식품제조가공업 31
 
6.6%
<NA> 27
 
5.7%

Length

2024-04-18T07:13:01.321033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:01.403676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 445
88.5%
기타 31
 
6.2%
na 27
 
5.4%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
353 
0
68 
1
42 
2
 
6
3
 
2

Length

Max length4
Median length4
Mean length3.2457627
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 353
74.8%
0 68
 
14.4%
1 42
 
8.9%
2 6
 
1.3%
3 2
 
0.4%
10 1
 
0.2%

Length

2024-04-18T07:13:01.522523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:01.617105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 353
74.8%
0 68
 
14.4%
1 42
 
8.9%
2 6
 
1.3%
3 2
 
0.4%
10 1
 
0.2%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
367 
0
71 
1
 
22
2
 
8
3
 
3

Length

Max length4
Median length4
Mean length3.3326271
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
77.8%
0 71
 
15.0%
1 22
 
4.7%
2 8
 
1.7%
3 3
 
0.6%
4 1
 
0.2%

Length

2024-04-18T07:13:01.730888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:01.816206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
77.8%
0 71
 
15.0%
1 22
 
4.7%
2 8
 
1.7%
3 3
 
0.6%
4 1
 
0.2%

영업장주변구분명
Categorical

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
309 
주택가주변
94 
기타
61 
아파트지역
 
5
유흥업소밀집지역
 
3

Length

Max length8
Median length4
Mean length3.9766949
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주택가주변
2nd row주택가주변
3rd row기타
4th row유흥업소밀집지역
5th row주택가주변

Common Values

ValueCountFrequency (%)
<NA> 309
65.5%
주택가주변 94
 
19.9%
기타 61
 
12.9%
아파트지역 5
 
1.1%
유흥업소밀집지역 3
 
0.6%

Length

2024-04-18T07:13:01.917987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.001655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 309
65.5%
주택가주변 94
 
19.9%
기타 61
 
12.9%
아파트지역 5
 
1.1%
유흥업소밀집지역 3
 
0.6%

등급구분명
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
309 
자율
112 
기타
50 
지도
 
1

Length

Max length4
Median length4
Mean length3.309322
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 309
65.5%
자율 112
 
23.7%
기타 50
 
10.6%
지도 1
 
0.2%

Length

2024-04-18T07:13:02.101989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.186774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 309
65.5%
자율 112
 
23.7%
기타 50
 
10.6%
지도 1
 
0.2%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
상수도전용
260 
<NA>
212 

Length

Max length5
Median length5
Mean length4.5508475
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 260
55.1%
<NA> 212
44.9%

Length

2024-04-18T07:13:02.269053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.343547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 260
55.1%
na 212
44.9%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
462 
0
 
10

Length

Max length4
Median length4
Mean length3.9364407
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> 462
97.9%
0 10
 
2.1%

Length

2024-04-18T07:13:02.424718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.500295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 462
97.9%
0 10
 
2.1%

본사종업원수
Categorical

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
245 
<NA>
224 
1
 
2
4
 
1

Length

Max length4
Median length1
Mean length2.4237288
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 245
51.9%
<NA> 224
47.5%
1 2
 
0.4%
4 1
 
0.2%

Length

2024-04-18T07:13:02.598555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.716291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 245
51.9%
na 224
47.5%
1 2
 
0.4%
4 1
 
0.2%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
243 
<NA>
226 
1
 
3

Length

Max length4
Median length1
Mean length2.4364407
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 243
51.5%
<NA> 226
47.9%
1 3
 
0.6%

Length

2024-04-18T07:13:02.806515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:02.884980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 243
51.5%
na 226
47.9%
1 3
 
0.6%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
245 
<NA>
226 
2
 
1

Length

Max length4
Median length1
Mean length2.4364407
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 245
51.9%
<NA> 226
47.9%
2 1
 
0.2%

Length

2024-04-18T07:13:02.977605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:03.061479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 245
51.9%
na 226
47.9%
2 1
 
0.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
0
237 
<NA>
222 
2
 
5
1
 
5
4
 
2

Length

Max length4
Median length1
Mean length2.4110169
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 237
50.2%
<NA> 222
47.0%
2 5
 
1.1%
1 5
 
1.1%
4 2
 
0.4%
3 1
 
0.2%

Length

2024-04-18T07:13:03.143701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:03.228648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 237
50.2%
na 222
47.0%
2 5
 
1.1%
1 5
 
1.1%
4 2
 
0.4%
3 1
 
0.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
225 
임대
159 
자가
88 

Length

Max length4
Median length2
Mean length2.9533898
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> 225
47.7%
임대 159
33.7%
자가 88
 
18.6%

Length

2024-04-18T07:13:03.325124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:03.408650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 225
47.7%
임대 159
33.7%
자가 88
 
18.6%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
379 
0
90 
20000000
 
1
1200000000
 
1
10000000
 
1

Length

Max length10
Median length4
Mean length3.4576271
Min length1

Unique

Unique3 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 379
80.3%
0 90
 
19.1%
20000000 1
 
0.2%
1200000000 1
 
0.2%
10000000 1
 
0.2%

Length

2024-04-18T07:13:03.497977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:03.593553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 379
80.3%
0 90
 
19.1%
20000000 1
 
0.2%
1200000000 1
 
0.2%
10000000 1
 
0.2%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.8 KiB
<NA>
380 
0
90 
1650000
 
1
600000
 
1

Length

Max length7
Median length4
Mean length3.4385593
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 380
80.5%
0 90
 
19.1%
1650000 1
 
0.2%
600000 1
 
0.2%

Length

2024-04-18T07:13:03.690667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T07:13:03.794446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 380
80.5%
0 90
 
19.1%
1650000 1
 
0.2%
600000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing27
Missing (%)5.7%
Memory size1.1 KiB
False
445 
(Missing)
 
27
ValueCountFrequency (%)
False 445
94.3%
(Missing) 27
 
5.7%
2024-04-18T07:13:03.870218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct34
Distinct (%)7.6%
Missing27
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean3.4781573
Minimum0
Maximum149
Zeros410
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2024-04-18T07:13:03.952670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16.516
Maximum149
Range149
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.022169
Coefficient of variation (CV)4.6065108
Kurtosis33.420926
Mean3.4781573
Median Absolute Deviation (MAD)0
Skewness5.5795015
Sum1547.78
Variance256.7099
MonotonicityNot monotonic
2024-04-18T07:13:04.055192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.0 410
86.9%
33.0 2
 
0.4%
99.0 2
 
0.4%
13.25 1
 
0.2%
6.41 1
 
0.2%
18.6 1
 
0.2%
7.34 1
 
0.2%
35.48 1
 
0.2%
27.13 1
 
0.2%
71.22 1
 
0.2%
Other values (24) 24
 
5.1%
(Missing) 27
 
5.7%
ValueCountFrequency (%)
0.0 410
86.9%
4.6 1
 
0.2%
4.74 1
 
0.2%
6.41 1
 
0.2%
7.34 1
 
0.2%
8.01 1
 
0.2%
9.32 1
 
0.2%
9.46 1
 
0.2%
9.5 1
 
0.2%
9.79 1
 
0.2%
ValueCountFrequency (%)
149.0 1
0.2%
104.06 1
0.2%
99.0 2
0.4%
92.7 1
0.2%
90.39 1
0.2%
86.84 1
0.2%
86.2 1
0.2%
82.98 1
0.2%
73.51 1
0.2%
71.22 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing472
Missing (%)100.0%
Memory size4.3 KiB

홈페이지
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing471
Missing (%)99.8%
Memory size3.8 KiB
2024-04-18T07:13:04.163145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters6
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

Unique1 ?
Unique (%)100.0%

Sample

1st row070-4276-4200
ValueCountFrequency (%)
070-4276-4200 1
100.0%
2024-04-18T07:13:04.359285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
30.8%
7 2
15.4%
- 2
15.4%
4 2
15.4%
2 2
15.4%
6 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
84.6%
Dash Punctuation 2
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
36.4%
7 2
18.2%
4 2
18.2%
2 2
18.2%
6 1
 
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
30.8%
7 2
15.4%
- 2
15.4%
4 2
15.4%
2 2
15.4%
6 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
30.8%
7 2
15.4%
- 2
15.4%
4 2
15.4%
2 2
15.4%
6 1
 
7.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
032400003240000-106-1989-0000119890805<NA>3폐업2폐업20041108<NA><NA><NA>02 486674870.42134866서울특별시 강동구 천호동 224-40번지<NA><NA>고향유과2003-09-22 00:00:00I2018-08-31 23:59:59.0식품제조가공업211912.04413449379.629285식품제조가공업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
132400003240000-106-1989-0001219890526<NA>3폐업2폐업20030617<NA><NA><NA>02 4729693106.02134830서울특별시 강동구 명일동 342-19번지<NA><NA>왕궁병과2002-06-24 00:00:00I2018-08-31 23:59:59.0식품제조가공업212751.015247449450.35008식품제조가공업<NA><NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
232400003240000-106-1989-0106419891027<NA>3폐업2폐업20120503<NA><NA><NA>02 4871841486.56134840서울특별시 강동구 성내동 29-10번지<NA><NA>대영식품2005-11-15 00:00:00I2018-08-31 23:59:59.0식품제조가공업211190.200885448146.944246식품제조가공업1<NA>기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
332400003240000-106-1990-0004319900627<NA>3폐업2폐업19980424<NA><NA><NA>02 068.32134858서울특별시 강동구 암사동 456-84번지<NA><NA>서해식품2002-07-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업211768.627509450044.412969식품제조가공업<NA><NA>유흥업소밀집지역자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
432400003240000-106-1992-0001619921106<NA>3폐업2폐업20120126<NA><NA><NA><NA>116.15134861서울특별시 강동구 천호동 18-63번지<NA><NA>연서식품2011-03-14 13:54:02I2018-08-31 23:59:59.0식품제조가공업212220.607535449655.167095식품제조가공업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
532400003240000-106-1993-0001719930218<NA>3폐업2폐업20020114<NA><NA><NA>0286.1134830서울특별시 강동구 명일동 344-15번지<NA><NA>토산식품2002-07-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업212672.159203449388.425456식품제조가공업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
632400003240000-106-1993-0004419931025<NA>3폐업2폐업20040106<NA><NA><NA>02 481301125.6134837서울특별시 강동구 상일동 280-3번지<NA><NA>부림식품2002-07-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업215047.116818449674.836016식품제조가공업<NA><NA>주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
732400003240000-106-1993-0004919930428<NA>3폐업2폐업19971114<NA><NA><NA>02 065.88134859서울특별시 강동구 암사동 499-1번지<NA><NA>왕보식품2002-07-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업211374.444251449952.24447식품제조가공업<NA><NA>주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
832400003240000-106-1993-0006919930312<NA>3폐업2폐업20061214<NA><NA><NA>0234269800120.0134858서울특별시 강동구 암사동 456-84번지<NA><NA>미도식품2005-04-27 00:00:00I2018-08-31 23:59:59.0식품제조가공업211768.627509450044.412969식품제조가공업<NA><NA>주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
932400003240000-106-1993-0007019930830<NA>3폐업2폐업19971002<NA><NA><NA>02 474466878.78134850서울특별시 강동구 성내동 537-20번지<NA><NA>(주)두손식품2002-07-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업210810.122087447642.314319식품제조가공업<NA><NA>주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
46232400003240000-106-2021-0000720210823<NA>1영업/정상1영업<NA><NA><NA><NA><NA>23.0134844서울특별시 강동구 성내동 408-19서울특별시 강동구 성안로 79, 1층 (성내동)5390차이브커피 로스팅랩2021-08-23 11:26:15I2021-08-25 00:22:50.0기타 식품제조가공업211590.669921447616.484884기타 식품제조가공업00<NA><NA><NA>00000임대00N0.0<NA><NA><NA>
46332400003240000-106-2021-0000820210930<NA>3폐업2폐업20221229<NA><NA><NA>022036040774.48134888서울특별시 강동구 성내동 407-8서울특별시 강동구 성안로 91, 1층 (성내동)5389주식회사 위미트2022-12-29 16:36:10U2021-11-01 21:01:00.0기타 식품제조가공업211628.070179447716.603671<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46432400003240000-106-2021-000092021-10-19<NA>3폐업2폐업2024-02-29<NA><NA><NA>026015117630.0134-841서울특별시 강동구 성내동 127-12서울특별시 강동구 천호옛길 52, 지하층 (성내동)5386에이치푸드2024-02-29 17:14:16U2023-12-03 00:03:00.0기타 식품제조가공업210858.955354447948.157658<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46532400003240000-106-2021-000102021-11-03<NA>3폐업2폐업2023-09-20<NA><NA><NA><NA>95.16134-864서울특별시 강동구 천호동 123-24서울특별시 강동구 천중로 152, 2층 (천호동)5331알제이(RJ)2023-09-20 14:13:38U2022-12-08 22:02:00.0기타 식품제조가공업212028.149101448769.536781<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46632400003240000-106-2021-000112021-11-23<NA>3폐업2폐업2023-10-06<NA><NA><NA>0708777281143.88134-855서울특별시 강동구 암사동 450-29서울특별시 강동구 고덕로27길 33, 지하1층 (암사동)5237웨이틀로2023-10-06 17:26:21U2022-10-31 00:08:00.0기타 식품제조가공업212101.808494450452.436683<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46732400003240000-106-2022-0000120220302<NA>1영업/정상1영업<NA><NA><NA><NA><NA>49.2134837서울특별시 강동구 상일동 268-2서울특별시 강동구 상일로 29-1, 지하1층 (상일동)5282조은푸드2022-03-02 15:15:38I2022-03-04 00:22:37.0기타 식품제조가공업215195.884312449734.105974기타 식품제조가공업00<NA><NA>상수도전용00000임대10000000600000N0.0<NA><NA><NA>
46832400003240000-106-2022-000022022-12-05<NA>3폐업2폐업2023-11-13<NA><NA><NA><NA>16.12134-825서울특별시 강동구 명일동 47-12 고덕복합빌딩서울특별시 강동구 동남로73길 26, 15호 (명일동, 고덕복합빌딩)5269하박푸드2023-11-13 15:28:28U2022-10-31 23:05:00.0기타 식품제조가공업213607.080568450119.168257<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
46932400003240000-106-2023-000012023-06-02<NA>1영업/정상1영업<NA><NA><NA><NA>021544331838.46134-847서울특별시 강동구 성내동 446-23 M빌딩서울특별시 강동구 성안로 12, M빌딩 1층 (성내동)5407(주)미래푸드시스템2023-06-02 15:06:47I2022-12-06 00:04:00.0기타 식품제조가공업211384.144442446973.816584<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47032400003240000-106-2023-000022023-08-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>18.27134-786서울특별시 강동구 명일동 44 신동아아파트서울특별시 강동구 고덕로62길 48, 신동아아파트 상가지하1층 7호 (명일동)5268그래몽땅2023-08-11 18:01:27I2022-12-07 23:03:00.0기타 식품제조가공업213371.152528450173.900732<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47132400003240000-106-2024-000012024-02-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA>26.22134-814서울특별시 강동구 길동 459-2서울특별시 강동구 천호대로 1135, 1층 100-2호 (길동)5355흥남종합식품 주식회사2024-02-02 11:17:39I2023-12-02 00:04:00.0기타 식품제조가공업212111.336831448059.842031<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>