Overview

Dataset statistics

Number of variables44
Number of observations608
Missing cells6754
Missing cells (%)25.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory223.4 KiB
Average record size in memory376.2 B

Variable types

Categorical18
Text6
DateTime4
Unsupported7
Numeric8
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
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18257/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
업태구분명 is highly imbalanced (56.3%)Imbalance
여성종사자수 is highly imbalanced (63.1%)Imbalance
영업장주변구분명 is highly imbalanced (55.7%)Imbalance
등급구분명 is highly imbalanced (58.8%)Imbalance
총인원 is highly imbalanced (87.9%)Imbalance
인허가취소일자 has 608 (100.0%) missing valuesMissing
폐업일자 has 101 (16.6%) missing valuesMissing
휴업시작일자 has 608 (100.0%) missing valuesMissing
휴업종료일자 has 608 (100.0%) missing valuesMissing
재개업일자 has 608 (100.0%) missing valuesMissing
전화번호 has 140 (23.0%) missing valuesMissing
소재지면적 has 11 (1.8%) missing valuesMissing
도로명주소 has 263 (43.3%) missing valuesMissing
도로명우편번호 has 270 (44.4%) missing valuesMissing
좌표정보(X) has 26 (4.3%) missing valuesMissing
좌표정보(Y) has 26 (4.3%) missing valuesMissing
남성종사자수 has 495 (81.4%) missing valuesMissing
보증액 has 518 (85.2%) missing valuesMissing
월세액 has 522 (85.9%) missing valuesMissing
다중이용업소여부 has 63 (10.4%) missing valuesMissing
시설총규모 has 63 (10.4%) missing valuesMissing
전통업소지정번호 has 608 (100.0%) missing valuesMissing
전통업소주된음식 has 608 (100.0%) missing valuesMissing
홈페이지 has 608 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소지정번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 12 (2.0%) zerosZeros
남성종사자수 has 61 (10.0%) zerosZeros
보증액 has 45 (7.4%) zerosZeros
월세액 has 46 (7.6%) zerosZeros
시설총규모 has 485 (79.8%) zerosZeros

Reproduction

Analysis started2024-05-11 00:53:47.288140
Analysis finished2024-05-11 00:53:49.223096
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3050000
608 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3050000
2nd row3050000
3rd row3050000
4th row3050000
5th row3050000

Common Values

ValueCountFrequency (%)
3050000 608
100.0%

Length

2024-05-11T00:53:49.532164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:53:49.971360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 608
100.0%

관리번호
Text

UNIQUE 

Distinct608
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T00:53:50.430618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters13376
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

Unique608 ?
Unique (%)100.0%

Sample

1st row3050000-106-1968-00283
2nd row3050000-106-1970-00841
3rd row3050000-106-1972-00636
4th row3050000-106-1973-00031
5th row3050000-106-1974-00032
ValueCountFrequency (%)
3050000-106-1968-00283 1
 
0.2%
3050000-106-2012-00005 1
 
0.2%
3050000-106-2012-00014 1
 
0.2%
3050000-106-2011-00034 1
 
0.2%
3050000-106-2011-00035 1
 
0.2%
3050000-106-2012-00001 1
 
0.2%
3050000-106-2012-00002 1
 
0.2%
3050000-106-2012-00003 1
 
0.2%
3050000-106-2012-00004 1
 
0.2%
3050000-106-2012-00007 1
 
0.2%
Other values (598) 598
98.4%
2024-05-11T00:53:51.706671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6383
47.7%
- 1824
 
13.6%
1 1335
 
10.0%
2 813
 
6.1%
3 793
 
5.9%
5 757
 
5.7%
6 733
 
5.5%
9 311
 
2.3%
4 155
 
1.2%
8 145
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11552
86.4%
Dash Punctuation 1824
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6383
55.3%
1 1335
 
11.6%
2 813
 
7.0%
3 793
 
6.9%
5 757
 
6.6%
6 733
 
6.3%
9 311
 
2.7%
4 155
 
1.3%
8 145
 
1.3%
7 127
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 1824
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13376
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6383
47.7%
- 1824
 
13.6%
1 1335
 
10.0%
2 813
 
6.1%
3 793
 
5.9%
5 757
 
5.7%
6 733
 
5.5%
9 311
 
2.3%
4 155
 
1.2%
8 145
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6383
47.7%
- 1824
 
13.6%
1 1335
 
10.0%
2 813
 
6.1%
3 793
 
5.9%
5 757
 
5.7%
6 733
 
5.5%
9 311
 
2.3%
4 155
 
1.2%
8 145
 
1.1%

인허가일자
Date

Distinct565
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1968-05-15 00:00:00
Maximum2024-02-01 00:00:00
2024-05-11T00:53:52.414174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:53:52.879440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
3
507 
1
101 

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 (%)
3 507
83.4%
1 101
 
16.6%

Length

2024-05-11T00:53:53.364458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:53:53.750573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 507
83.4%
1 101
 
16.6%

영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
507 
영업/정상
101 

Length

Max length5
Median length2
Mean length2.4983553
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 507
83.4%
영업/정상 101
 
16.6%

Length

2024-05-11T00:53:54.262181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:53:54.754993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 507
83.4%
영업/정상 101
 
16.6%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2
507 
1
101 

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 (%)
2 507
83.4%
1 101
 
16.6%

Length

2024-05-11T00:53:55.384479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:53:56.004362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 507
83.4%
1 101
 
16.6%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
폐업
507 
영업
101 

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 507
83.4%
영업 101
 
16.6%

Length

2024-05-11T00:53:56.381088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:53:56.741750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 507
83.4%
영업 101
 
16.6%

폐업일자
Date

MISSING 

Distinct452
Distinct (%)89.2%
Missing101
Missing (%)16.6%
Memory size4.9 KiB
Minimum1997-02-06 00:00:00
Maximum2024-04-15 00:00:00
2024-05-11T00:53:57.078592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:53:57.480044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

전화번호
Text

MISSING 

Distinct448
Distinct (%)95.7%
Missing140
Missing (%)23.0%
Memory size4.9 KiB
2024-05-11T00:53:58.336313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.504274
Min length2

Characters and Unicode

Total characters4916
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

Unique429 ?
Unique (%)91.7%

Sample

1st row0222122289
2nd row02 9536425
3rd row02 9620232
4th row02 9677069
5th row02 9677307
ValueCountFrequency (%)
02 301
34.4%
960 13
 
1.5%
070 12
 
1.4%
966 8
 
0.9%
959 7
 
0.8%
969 6
 
0.7%
968 6
 
0.7%
963 5
 
0.6%
957 4
 
0.5%
22324701 3
 
0.3%
Other values (470) 509
58.2%
2024-05-11T00:53:59.866047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 990
20.1%
0 767
15.6%
527
10.7%
9 503
10.2%
6 415
8.4%
5 314
 
6.4%
4 313
 
6.4%
3 290
 
5.9%
1 271
 
5.5%
7 267
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4389
89.3%
Space Separator 527
 
10.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 990
22.6%
0 767
17.5%
9 503
11.5%
6 415
9.5%
5 314
 
7.2%
4 313
 
7.1%
3 290
 
6.6%
1 271
 
6.2%
7 267
 
6.1%
8 259
 
5.9%
Space Separator
ValueCountFrequency (%)
527
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4916
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 990
20.1%
0 767
15.6%
527
10.7%
9 503
10.2%
6 415
8.4%
5 314
 
6.4%
4 313
 
6.4%
3 290
 
5.9%
1 271
 
5.5%
7 267
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4916
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 990
20.1%
0 767
15.6%
527
10.7%
9 503
10.2%
6 415
8.4%
5 314
 
6.4%
4 313
 
6.4%
3 290
 
5.9%
1 271
 
5.5%
7 267
 
5.4%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct467
Distinct (%)78.2%
Missing11
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean66.900251
Minimum0
Maximum824.04
Zeros12
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:00.509907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.802
Q126.4
median49.32
Q380.6
95-th percentile170.982
Maximum824.04
Range824.04
Interquartile range (IQR)54.2

Descriptive statistics

Standard deviation70.763382
Coefficient of variation (CV)1.0577446
Kurtosis32.070855
Mean66.900251
Median Absolute Deviation (MAD)25.42
Skewness4.4048259
Sum39939.45
Variance5007.4563
MonotonicityNot monotonic
2024-05-11T00:54:01.048491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 12
 
2.0%
30.0 9
 
1.5%
33.0 8
 
1.3%
66.0 7
 
1.2%
25.0 5
 
0.8%
15.0 5
 
0.8%
33.05 5
 
0.8%
60.0 5
 
0.8%
49.5 5
 
0.8%
26.0 4
 
0.7%
Other values (457) 532
87.5%
(Missing) 11
 
1.8%
ValueCountFrequency (%)
0.0 12
2.0%
4.28 1
 
0.2%
4.64 1
 
0.2%
5.25 1
 
0.2%
6.6 1
 
0.2%
7.5 1
 
0.2%
7.62 1
 
0.2%
8.51 1
 
0.2%
9.0 1
 
0.2%
9.18 1
 
0.2%
ValueCountFrequency (%)
824.04 1
0.2%
596.24 1
0.2%
471.74 1
0.2%
418.28 2
0.3%
418.0 1
0.2%
399.31 1
0.2%
384.7 1
0.2%
306.0 1
0.2%
285.15 1
0.2%
267.71 1
0.2%

소재지우편번호
Text

Distinct84
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T00:54:01.813999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0723684
Min length6

Characters and Unicode

Total characters3692
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

Unique22 ?
Unique (%)3.6%

Sample

1st row130859
2nd row130821
3rd row130826
4th row130862
5th row130810
ValueCountFrequency (%)
130864 161
26.5%
130863 33
 
5.4%
130862 26
 
4.3%
130820 22
 
3.6%
130-864 20
 
3.3%
130817 20
 
3.3%
130854 13
 
2.1%
130865 11
 
1.8%
130823 10
 
1.6%
130875 10
 
1.6%
Other values (74) 282
46.4%
2024-05-11T00:54:03.137355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 741
20.1%
3 712
19.3%
1 682
18.5%
8 620
16.8%
6 307
8.3%
4 271
 
7.3%
2 121
 
3.3%
7 97
 
2.6%
5 76
 
2.1%
- 44
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3648
98.8%
Dash Punctuation 44
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 741
20.3%
3 712
19.5%
1 682
18.7%
8 620
17.0%
6 307
8.4%
4 271
 
7.4%
2 121
 
3.3%
7 97
 
2.7%
5 76
 
2.1%
9 21
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 741
20.1%
3 712
19.3%
1 682
18.5%
8 620
16.8%
6 307
8.3%
4 271
 
7.3%
2 121
 
3.3%
7 97
 
2.6%
5 76
 
2.1%
- 44
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 741
20.1%
3 712
19.3%
1 682
18.5%
8 620
16.8%
6 307
8.3%
4 271
 
7.3%
2 121
 
3.3%
7 97
 
2.6%
5 76
 
2.1%
- 44
 
1.2%

지번주소
Text

Distinct582
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T00:54:03.994770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length45
Mean length26.383224
Min length18

Characters and Unicode

Total characters16041
Distinct characters166
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

Unique558 ?
Unique (%)91.8%

Sample

1st row서울특별시 동대문구 전농동 647-51번지 (간데메서2길5)
2nd row서울특별시 동대문구 용두동 129-20번지 외1필지
3rd row서울특별시 동대문구 이문동 292-87번지
4th row서울특별시 동대문구 제기동 620번지
5th row서울특별시 동대문구 신설동 39-44번지
ValueCountFrequency (%)
서울특별시 608
21.9%
동대문구 608
21.9%
제기동 269
 
9.7%
장안동 84
 
3.0%
용두동 67
 
2.4%
1층 59
 
2.1%
전농동 46
 
1.7%
답십리동 45
 
1.6%
지하1층 38
 
1.4%
휘경동 25
 
0.9%
Other values (719) 933
33.5%
2024-05-11T00:54:05.863744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2723
 
17.0%
동 1233
 
7.7%
1 786
 
4.9%
문 631
 
3.9%
시 616
 
3.8%
대 616
 
3.8%
서 612
 
3.8%
울 610
 
3.8%
별 609
 
3.8%
구 609
 
3.8%
Other values (156) 6996
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9268
57.8%
Decimal Number 3196
 
19.9%
Space Separator 2723
 
17.0%
Dash Punctuation 549
 
3.4%
Open Punctuation 144
 
0.9%
Close Punctuation 144
 
0.9%
Math Symbol 7
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1233
13.3%
문 631
 
6.8%
시 616
 
6.6%
대 616
 
6.6%
서 612
 
6.6%
울 610
 
6.6%
별 609
 
6.6%
구 609
 
6.6%
특 608
 
6.6%
지 591
 
6.4%
Other values (134) 2533
27.3%
Decimal Number
ValueCountFrequency (%)
1 786
24.6%
2 425
13.3%
3 333
10.4%
4 268
 
8.4%
8 259
 
8.1%
0 255
 
8.0%
9 253
 
7.9%
5 226
 
7.1%
6 199
 
6.2%
7 192
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
C 1
25.0%
K 1
25.0%
S 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 136
94.4%
[ 8
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 136
94.4%
] 8
 
5.6%
Space Separator
ValueCountFrequency (%)
2723
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 549
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9268
57.8%
Common 6769
42.2%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1233
13.3%
문 631
 
6.8%
시 616
 
6.6%
대 616
 
6.6%
서 612
 
6.6%
울 610
 
6.6%
별 609
 
6.6%
구 609
 
6.6%
특 608
 
6.6%
지 591
 
6.4%
Other values (134) 2533
27.3%
Common
ValueCountFrequency (%)
2723
40.2%
1 786
 
11.6%
- 549
 
8.1%
2 425
 
6.3%
3 333
 
4.9%
4 268
 
4.0%
8 259
 
3.8%
0 255
 
3.8%
9 253
 
3.7%
5 226
 
3.3%
Other values (8) 692
 
10.2%
Latin
ValueCountFrequency (%)
M 1
25.0%
C 1
25.0%
K 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9268
57.8%
ASCII 6773
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2723
40.2%
1 786
 
11.6%
- 549
 
8.1%
2 425
 
6.3%
3 333
 
4.9%
4 268
 
4.0%
8 259
 
3.8%
0 255
 
3.8%
9 253
 
3.7%
5 226
 
3.3%
Other values (12) 696
 
10.3%
Hangul
ValueCountFrequency (%)
동 1233
13.3%
문 631
 
6.8%
시 616
 
6.6%
대 616
 
6.6%
서 612
 
6.6%
울 610
 
6.6%
별 609
 
6.6%
구 609
 
6.6%
특 608
 
6.6%
지 591
 
6.4%
Other values (134) 2533
27.3%

도로명주소
Text

MISSING 

Distinct332
Distinct (%)96.2%
Missing263
Missing (%)43.3%
Memory size4.9 KiB
2024-05-11T00:54:06.700974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length30.747826
Min length23

Characters and Unicode

Total characters10608
Distinct characters131
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

Unique321 ?
Unique (%)93.0%

Sample

1st row서울특별시 동대문구 답십리로64길 67 (장안동)
2nd row서울특별시 동대문구 한천로18길 24 (장안동)
3rd row서울특별시 동대문구 망우로21가길 5 (휘경동)
4th row서울특별시 동대문구 답십리로40길 18 (답십리동)
5th row서울특별시 동대문구 고산자로38길 15-13 (제기동)
ValueCountFrequency (%)
서울특별시 345
17.0%
동대문구 345
17.0%
제기동 189
 
9.3%
1층 93
 
4.6%
약령중앙로 46
 
2.3%
지하1층 39
 
1.9%
장안동 34
 
1.7%
고산자로 28
 
1.4%
용두동 25
 
1.2%
답십리동 25
 
1.2%
Other values (410) 862
42.4%
2024-05-11T00:54:08.261781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1686
 
15.9%
동 736
 
6.9%
1 445
 
4.2%
시 383
 
3.6%
대 370
 
3.5%
서 367
 
3.5%
문 358
 
3.4%
) 351
 
3.3%
( 351
 
3.3%
울 351
 
3.3%
Other values (121) 5210
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6384
60.2%
Space Separator 1686
 
15.9%
Decimal Number 1477
 
13.9%
Close Punctuation 351
 
3.3%
Open Punctuation 351
 
3.3%
Other Punctuation 267
 
2.5%
Dash Punctuation 72
 
0.7%
Math Symbol 15
 
0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 736
 
11.5%
시 383
 
6.0%
대 370
 
5.8%
서 367
 
5.7%
문 358
 
5.6%
울 351
 
5.5%
별 345
 
5.4%
구 345
 
5.4%
특 345
 
5.4%
로 312
 
4.9%
Other values (100) 2472
38.7%
Decimal Number
ValueCountFrequency (%)
1 445
30.1%
2 199
13.5%
4 170
 
11.5%
3 150
 
10.2%
0 105
 
7.1%
5 92
 
6.2%
7 90
 
6.1%
6 83
 
5.6%
8 79
 
5.3%
9 64
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
20.0%
S 1
20.0%
A 1
20.0%
C 1
20.0%
M 1
20.0%
Space Separator
ValueCountFrequency (%)
1686
100.0%
Close Punctuation
ValueCountFrequency (%)
) 351
100.0%
Open Punctuation
ValueCountFrequency (%)
( 351
100.0%
Other Punctuation
ValueCountFrequency (%)
, 267
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Math Symbol
ValueCountFrequency (%)
~ 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6384
60.2%
Common 4219
39.8%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 736
 
11.5%
시 383
 
6.0%
대 370
 
5.8%
서 367
 
5.7%
문 358
 
5.6%
울 351
 
5.5%
별 345
 
5.4%
구 345
 
5.4%
특 345
 
5.4%
로 312
 
4.9%
Other values (100) 2472
38.7%
Common
ValueCountFrequency (%)
1686
40.0%
1 445
 
10.5%
) 351
 
8.3%
( 351
 
8.3%
, 267
 
6.3%
2 199
 
4.7%
4 170
 
4.0%
3 150
 
3.6%
0 105
 
2.5%
5 92
 
2.2%
Other values (6) 403
 
9.6%
Latin
ValueCountFrequency (%)
K 1
20.0%
S 1
20.0%
A 1
20.0%
C 1
20.0%
M 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6384
60.2%
ASCII 4224
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1686
39.9%
1 445
 
10.5%
) 351
 
8.3%
( 351
 
8.3%
, 267
 
6.3%
2 199
 
4.7%
4 170
 
4.0%
3 150
 
3.6%
0 105
 
2.5%
5 92
 
2.2%
Other values (11) 408
 
9.7%
Hangul
ValueCountFrequency (%)
동 736
 
11.5%
시 383
 
6.0%
대 370
 
5.8%
서 367
 
5.7%
문 358
 
5.6%
울 351
 
5.5%
별 345
 
5.4%
구 345
 
5.4%
특 345
 
5.4%
로 312
 
4.9%
Other values (100) 2472
38.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct101
Distinct (%)29.9%
Missing270
Missing (%)44.4%
Infinite0
Infinite (%)0.0%
Mean2544.6183
Minimum2403
Maximum2644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:09.031682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2403
5-th percentile2443.25
Q12501.5
median2569
Q32571
95-th percentile2616.65
Maximum2644
Range241
Interquartile range (IQR)69.5

Descriptive statistics

Standard deviation52.200361
Coefficient of variation (CV)0.020514024
Kurtosis-0.18228379
Mean2544.6183
Median Absolute Deviation (MAD)15
Skewness-0.70587168
Sum860081
Variance2724.8776
MonotonicityNot monotonic
2024-05-11T00:54:09.703564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2570 68
 
11.2%
2478 38
 
6.2%
2569 31
 
5.1%
2571 21
 
3.5%
2572 18
 
3.0%
2596 5
 
0.8%
2560 5
 
0.8%
2573 4
 
0.7%
2479 4
 
0.7%
2503 3
 
0.5%
Other values (91) 141
23.2%
(Missing) 270
44.4%
ValueCountFrequency (%)
2403 1
0.2%
2405 1
0.2%
2406 1
0.2%
2414 1
0.2%
2419 1
0.2%
2423 2
0.3%
2426 1
0.2%
2428 2
0.3%
2431 2
0.3%
2432 1
0.2%
ValueCountFrequency (%)
2644 3
0.5%
2643 2
0.3%
2640 1
 
0.2%
2639 1
 
0.2%
2638 1
 
0.2%
2636 2
0.3%
2631 1
 
0.2%
2628 3
0.5%
2626 3
0.5%
2615 1
 
0.2%

사업장명
Text

Distinct566
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-05-11T00:54:10.475601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length30
Mean length5.8848684
Min length2

Characters and Unicode

Total characters3578
Distinct characters454
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique530 ?
Unique (%)87.2%

Sample

1st row제일식품
2nd row백광식품
3rd row영남기름집
4th row광성상회
5th row삼풍식품
ValueCountFrequency (%)
주식회사 11
 
1.7%
미래식품 4
 
0.6%
식품사업부 4
 
0.6%
제일식품 3
 
0.5%
용식품 3
 
0.5%
백미식품 3
 
0.5%
대성식품 3
 
0.5%
장수샘식품 2
 
0.3%
하나식품 2
 
0.3%
민성푸드시스템(주 2
 
0.3%
Other values (589) 620
94.4%
2024-05-11T00:54:11.858901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 229
 
6.4%
품 210
 
5.9%
주 118
 
3.3%
) 110
 
3.1%
( 109
 
3.0%
이 69
 
1.9%
스 58
 
1.6%
드 53
 
1.5%
사 51
 
1.4%
49
 
1.4%
Other values (444) 2522
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3102
86.7%
Close Punctuation 110
 
3.1%
Open Punctuation 109
 
3.0%
Lowercase Letter 104
 
2.9%
Uppercase Letter 81
 
2.3%
Space Separator 49
 
1.4%
Decimal Number 17
 
0.5%
Other Punctuation 4
 
0.1%
Letter Number 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 229
 
7.4%
품 210
 
6.8%
주 118
 
3.8%
이 69
 
2.2%
스 58
 
1.9%
드 53
 
1.7%
사 51
 
1.6%
푸 45
 
1.5%
한 39
 
1.3%
원 39
 
1.3%
Other values (386) 2191
70.6%
Lowercase Letter
ValueCountFrequency (%)
e 14
13.5%
o 12
11.5%
a 10
9.6%
n 10
9.6%
i 8
 
7.7%
r 8
 
7.7%
t 7
 
6.7%
s 7
 
6.7%
f 4
 
3.8%
d 3
 
2.9%
Other values (11) 21
20.2%
Uppercase Letter
ValueCountFrequency (%)
O 12
14.8%
C 10
12.3%
F 9
11.1%
N 5
 
6.2%
S 5
 
6.2%
B 4
 
4.9%
D 4
 
4.9%
P 4
 
4.9%
I 4
 
4.9%
R 4
 
4.9%
Other values (10) 20
24.7%
Decimal Number
ValueCountFrequency (%)
2 3
17.6%
4 3
17.6%
7 2
11.8%
6 2
11.8%
9 2
11.8%
1 2
11.8%
5 1
 
5.9%
3 1
 
5.9%
8 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
/ 1
25.0%
& 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3102
86.7%
Common 290
 
8.1%
Latin 186
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 229
 
7.4%
품 210
 
6.8%
주 118
 
3.8%
이 69
 
2.2%
스 58
 
1.9%
드 53
 
1.7%
사 51
 
1.6%
푸 45
 
1.5%
한 39
 
1.3%
원 39
 
1.3%
Other values (386) 2191
70.6%
Latin
ValueCountFrequency (%)
e 14
 
7.5%
o 12
 
6.5%
O 12
 
6.5%
a 10
 
5.4%
n 10
 
5.4%
C 10
 
5.4%
F 9
 
4.8%
i 8
 
4.3%
r 8
 
4.3%
t 7
 
3.8%
Other values (32) 86
46.2%
Common
ValueCountFrequency (%)
) 110
37.9%
( 109
37.6%
49
16.9%
2 3
 
1.0%
4 3
 
1.0%
7 2
 
0.7%
6 2
 
0.7%
9 2
 
0.7%
. 2
 
0.7%
1 2
 
0.7%
Other values (6) 6
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3102
86.7%
ASCII 475
 
13.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 229
 
7.4%
품 210
 
6.8%
주 118
 
3.8%
이 69
 
2.2%
스 58
 
1.9%
드 53
 
1.7%
사 51
 
1.6%
푸 45
 
1.5%
한 39
 
1.3%
원 39
 
1.3%
Other values (386) 2191
70.6%
ASCII
ValueCountFrequency (%)
) 110
23.2%
( 109
22.9%
49
 
10.3%
e 14
 
2.9%
o 12
 
2.5%
O 12
 
2.5%
a 10
 
2.1%
n 10
 
2.1%
C 10
 
2.1%
F 9
 
1.9%
Other values (47) 130
27.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

최종수정일자
Date

Distinct548
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum1999-01-05 00:00:00
Maximum2024-04-17 14:52:33
2024-05-11T00:54:12.501177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:54:12.963508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
I
469 
U
139 

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 469
77.1%
U 139
 
22.9%

Length

2024-05-11T00:54:13.396726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:13.726739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 469
77.1%
u 139
 
22.9%

데이터갱신일자
Date

Distinct146
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:07:00
2024-05-11T00:54:14.125580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:54:14.577938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
식품제조가공업
499 
기타 식품제조가공업
108 
PB제품 제조업체
 
1

Length

Max length10
Median length7
Mean length7.5361842
Min length7

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 499
82.1%
기타 식품제조가공업 108
 
17.8%
PB제품 제조업체 1
 
0.2%

Length

2024-05-11T00:54:15.016955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:15.294344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 607
84.7%
기타 108
 
15.1%
pb제품 1
 
0.1%
제조업체 1
 
0.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct474
Distinct (%)81.4%
Missing26
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean204100.8
Minimum202078.86
Maximum206618.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:15.578635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202078.86
5-th percentile202692.06
Q1203233.52
median203499.9
Q3205236.02
95-th percentile206207.09
Maximum206618.08
Range4539.2265
Interquartile range (IQR)2002.5077

Descriptive statistics

Standard deviation1187.3749
Coefficient of variation (CV)0.0058175909
Kurtosis-1.0189119
Mean204100.8
Median Absolute Deviation (MAD)472.21007
Skewness0.62898649
Sum1.1878666 × 108
Variance1409859.3
MonotonicityNot monotonic
2024-05-11T00:54:15.945803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
203301.309635065 6
 
1.0%
203113.350776675 6
 
1.0%
203296.617875766 5
 
0.8%
203270.810199668 5
 
0.8%
203312.172511544 4
 
0.7%
205868.49590043 4
 
0.7%
203235.764275634 3
 
0.5%
203265.323954112 3
 
0.5%
203262.562734529 3
 
0.5%
203289.24962427 3
 
0.5%
Other values (464) 540
88.8%
(Missing) 26
 
4.3%
ValueCountFrequency (%)
202078.855745629 1
0.2%
202138.449721245 2
0.3%
202159.285360366 1
0.2%
202187.929731637 1
0.2%
202203.755478871 2
0.3%
202222.268368605 1
0.2%
202321.748118565 1
0.2%
202422.107855499 1
0.2%
202431.217826593 1
0.2%
202446.518228179 1
0.2%
ValueCountFrequency (%)
206618.082278385 1
0.2%
206543.156690365 1
0.2%
206538.84863498 2
0.3%
206521.405320134 1
0.2%
206506.011771819 1
0.2%
206477.23276128 1
0.2%
206471.793495096 2
0.3%
206461.164033582 1
0.2%
206448.775564554 1
0.2%
206428.347543061 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct474
Distinct (%)81.4%
Missing26
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean453078.26
Minimum450987.05
Maximum455808.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:16.355540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450987.05
5-th percentile451696.32
Q1452668.15
median453109.58
Q3453452.76
95-th percentile454526.13
Maximum455808.42
Range4821.3708
Interquartile range (IQR)784.60918

Descriptive statistics

Standard deviation800.82654
Coefficient of variation (CV)0.0017675237
Kurtosis1.0230314
Mean453078.26
Median Absolute Deviation (MAD)401.02678
Skewness0.24925507
Sum2.6369154 × 108
Variance641323.14
MonotonicityNot monotonic
2024-05-11T00:54:16.909269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453367.754990357 6
 
1.0%
453599.892036286 6
 
1.0%
453535.343603526 5
 
0.8%
453322.241878592 5
 
0.8%
453290.730639305 4
 
0.7%
453723.126590653 4
 
0.7%
453335.364037599 3
 
0.5%
453735.357072092 3
 
0.5%
453605.062458519 3
 
0.5%
452971.167975053 3
 
0.5%
Other values (464) 540
88.8%
(Missing) 26
 
4.3%
ValueCountFrequency (%)
450987.048392613 1
0.2%
451110.245309908 1
0.2%
451116.622867751 1
0.2%
451158.623469156 1
0.2%
451160.978337791 1
0.2%
451166.645720652 1
0.2%
451174.369738707 1
0.2%
451178.252649445 1
0.2%
451239.135324238 1
0.2%
451254.607903514 2
0.3%
ValueCountFrequency (%)
455808.419175247 1
0.2%
455685.889846904 1
0.2%
455589.954211999 1
0.2%
455464.88282512 1
0.2%
455348.624569616 1
0.2%
455320.011455821 1
0.2%
455315.044626227 1
0.2%
455275.835949587 1
0.2%
455237.015807014 1
0.2%
455192.474346949 1
0.2%

위생업태명
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
식품제조가공업
471 
기타 식품제조가공업
73 
<NA>
63 
PB제품 제조업체
 
1

Length

Max length10
Median length7
Mean length7.0526316
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 471
77.5%
기타 식품제조가공업 73
 
12.0%
<NA> 63
 
10.4%
PB제품 제조업체 1
 
0.2%

Length

2024-05-11T00:54:17.302687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:17.648989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 544
79.8%
기타 73
 
10.7%
na 63
 
9.2%
pb제품 1
 
0.1%
제조업체 1
 
0.1%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)6.2%
Missing495
Missing (%)81.4%
Infinite0
Infinite (%)0.0%
Mean0.86725664
Minimum0
Maximum7
Zeros61
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:17.999275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2356637
Coefficient of variation (CV)1.4247959
Kurtosis5.3514673
Mean0.86725664
Median Absolute Deviation (MAD)0
Skewness1.962549
Sum98
Variance1.5268647
MonotonicityNot monotonic
2024-05-11T00:54:18.488880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 61
 
10.0%
1 24
 
3.9%
2 18
 
3.0%
3 6
 
1.0%
4 2
 
0.3%
5 1
 
0.2%
7 1
 
0.2%
(Missing) 495
81.4%
ValueCountFrequency (%)
0 61
10.0%
1 24
 
3.9%
2 18
 
3.0%
3 6
 
1.0%
4 2
 
0.3%
5 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
5 1
 
0.2%
4 2
 
0.3%
3 6
 
1.0%
2 18
 
3.0%
1 24
 
3.9%
0 61
10.0%

여성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
499 
0
70 
2
 
16
1
 
16
3
 
4

Length

Max length4
Median length4
Mean length3.4621711
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row<NA>
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 499
82.1%
0 70
 
11.5%
2 16
 
2.6%
1 16
 
2.6%
3 4
 
0.7%
4 3
 
0.5%

Length

2024-05-11T00:54:18.976422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:19.373126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 499
82.1%
0 70
 
11.5%
2 16
 
2.6%
1 16
 
2.6%
3 4
 
0.7%
4 3
 
0.5%

영업장주변구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
476 
기타
72 
주택가주변
53 
아파트지역
 
6
유흥업소밀집지역
 
1

Length

Max length8
Median length4
Mean length3.8667763
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 476
78.3%
기타 72
 
11.8%
주택가주변 53
 
8.7%
아파트지역 6
 
1.0%
유흥업소밀집지역 1
 
0.2%

Length

2024-05-11T00:54:19.756248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:20.124707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 476
78.3%
기타 72
 
11.8%
주택가주변 53
 
8.7%
아파트지역 6
 
1.0%
유흥업소밀집지역 1
 
0.2%

등급구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
476 
기타
97 
관리
 
33
지도
 
1
을
 
1

Length

Max length4
Median length4
Mean length3.5641447
Min length1

Unique

Unique2 ?
Unique (%)0.3%

Sample

1st row관리
2nd row관리
3rd row기타
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
<NA> 476
78.3%
기타 97
 
16.0%
관리 33
 
5.4%
지도 1
 
0.2%
을 1
 
0.2%

Length

2024-05-11T00:54:20.641045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:21.117972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 476
78.3%
기타 97
 
16.0%
관리 33
 
5.4%
지도 1
 
0.2%
을 1
 
0.2%

급수시설구분명
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
383 
상수도전용
225 

Length

Max length5
Median length4
Mean length4.3700658
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 383
63.0%
상수도전용 225
37.0%

Length

2024-05-11T00:54:21.521146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:21.850529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 383
63.0%
상수도전용 225
37.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
598 
0
 
10

Length

Max length4
Median length4
Mean length3.9506579
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> 598
98.4%
0 10
 
1.6%

Length

2024-05-11T00:54:22.303545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:22.771508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 598
98.4%
0 10
 
1.6%

본사종업원수
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
313 
0
294 
2
 
1

Length

Max length4
Median length4
Mean length2.5444079
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 313
51.5%
0 294
48.4%
2 1
 
0.2%

Length

2024-05-11T00:54:23.219362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:23.737950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 313
51.5%
0 294
48.4%
2 1
 
0.2%

공장사무직종업원수
Categorical

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
296 
0
289 
1
 
21
2
 
2

Length

Max length4
Median length1
Mean length2.4605263
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 296
48.7%
0 289
47.5%
1 21
 
3.5%
2 2
 
0.3%

Length

2024-05-11T00:54:24.139005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:24.498579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 296
48.7%
0 289
47.5%
1 21
 
3.5%
2 2
 
0.3%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
312 
0
295 
1
 
1

Length

Max length4
Median length4
Mean length2.5394737
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 312
51.3%
0 295
48.5%
1 1
 
0.2%

Length

2024-05-11T00:54:24.996578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:25.417794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 312
51.3%
0 295
48.5%
1 1
 
0.2%

공장생산직종업원수
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
286 
0
282 
1
 
23
2
 
11
3
 
5

Length

Max length4
Median length1
Mean length2.4111842
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 286
47.0%
0 282
46.4%
1 23
 
3.8%
2 11
 
1.8%
3 5
 
0.8%
4 1
 
0.2%

Length

2024-05-11T00:54:25.978577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:26.518378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 286
47.0%
0 282
46.4%
1 23
 
3.8%
2 11
 
1.8%
3 5
 
0.8%
4 1
 
0.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
<NA>
327 
임대
167 
자가
114 

Length

Max length4
Median length4
Mean length3.0756579
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> 327
53.8%
임대 167
27.5%
자가 114
 
18.8%

Length

2024-05-11T00:54:26.973190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:54:27.422740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 327
53.8%
임대 167
27.5%
자가 114
 
18.8%

보증액
Real number (ℝ)

MISSING  ZEROS 

Distinct17
Distinct (%)18.9%
Missing518
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean11700000
Minimum0
Maximum1 × 108
Zeros45
Zeros (%)7.4%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:27.907186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1000000
Q320000000
95-th percentile47750000
Maximum1 × 108
Range1 × 108
Interquartile range (IQR)20000000

Descriptive statistics

Standard deviation17939004
Coefficient of variation (CV)1.5332482
Kurtosis6.0954907
Mean11700000
Median Absolute Deviation (MAD)1000000
Skewness2.1786822
Sum1.053 × 109
Variance3.2180787 × 1014
MonotonicityNot monotonic
2024-05-11T00:54:28.470507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 45
 
7.4%
10000000 13
 
2.1%
20000000 7
 
1.2%
30000000 6
 
1.0%
45000000 3
 
0.5%
50000000 3
 
0.5%
7000000 2
 
0.3%
40000000 2
 
0.3%
100000000 1
 
0.2%
15000000 1
 
0.2%
Other values (7) 7
 
1.2%
(Missing) 518
85.2%
ValueCountFrequency (%)
0 45
7.4%
2000000 1
 
0.2%
3000000 1
 
0.2%
5000000 1
 
0.2%
6000000 1
 
0.2%
7000000 2
 
0.3%
8000000 1
 
0.2%
10000000 13
 
2.1%
15000000 1
 
0.2%
20000000 7
 
1.2%
ValueCountFrequency (%)
100000000 1
 
0.2%
60000000 1
 
0.2%
50000000 3
 
0.5%
45000000 3
 
0.5%
40000000 2
 
0.3%
30000000 6
1.0%
25000000 1
 
0.2%
20000000 7
1.2%
15000000 1
 
0.2%
10000000 13
2.1%

월세액
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)25.6%
Missing522
Missing (%)85.9%
Infinite0
Infinite (%)0.0%
Mean663953.49
Minimum0
Maximum4500000
Zeros46
Zeros (%)7.6%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:29.427349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31000000
95-th percentile2400000
Maximum4500000
Range4500000
Interquartile range (IQR)1000000

Descriptive statistics

Standard deviation1004011.1
Coefficient of variation (CV)1.5121708
Kurtosis3.7312212
Mean663953.49
Median Absolute Deviation (MAD)0
Skewness1.9216334
Sum57100000
Variance1.0080383 × 1012
MonotonicityNot monotonic
2024-05-11T00:54:30.055392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 46
 
7.6%
600000 6
 
1.0%
1000000 5
 
0.8%
500000 3
 
0.5%
2400000 3
 
0.5%
700000 2
 
0.3%
1200000 2
 
0.3%
2200000 2
 
0.3%
4000000 2
 
0.3%
1700000 2
 
0.3%
Other values (12) 13
 
2.1%
(Missing) 522
85.9%
ValueCountFrequency (%)
0 46
7.6%
300000 1
 
0.2%
400000 1
 
0.2%
500000 3
 
0.5%
600000 6
 
1.0%
700000 2
 
0.3%
750000 1
 
0.2%
800000 1
 
0.2%
900000 1
 
0.2%
1000000 5
 
0.8%
ValueCountFrequency (%)
4500000 1
 
0.2%
4000000 2
0.3%
3000000 1
 
0.2%
2400000 3
0.5%
2200000 2
0.3%
2000000 1
 
0.2%
1850000 1
 
0.2%
1700000 2
0.3%
1500000 2
0.3%
1400000 1
 
0.2%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing63
Missing (%)10.4%
Memory size1.3 KiB
False
545 
(Missing)
63 
ValueCountFrequency (%)
False 545
89.6%
(Missing) 63
 
10.4%
2024-05-11T00:54:30.521999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct56
Distinct (%)10.3%
Missing63
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean4.2224954
Minimum0
Maximum285.15
Zeros485
Zeros (%)79.8%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-05-11T00:54:30.870794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile26.156
Maximum285.15
Range285.15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.471188
Coefficient of variation (CV)4.8481256
Kurtosis86.755866
Mean4.2224954
Median Absolute Deviation (MAD)0
Skewness8.222792
Sum2301.26
Variance419.06954
MonotonicityNot monotonic
2024-05-11T00:54:31.395112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 485
79.8%
30.0 4
 
0.7%
15.0 2
 
0.3%
3.0 2
 
0.3%
40.82 1
 
0.2%
3.5 1
 
0.2%
6.0 1
 
0.2%
197.0 1
 
0.2%
2.26 1
 
0.2%
132.44 1
 
0.2%
Other values (46) 46
 
7.6%
(Missing) 63
 
10.4%
ValueCountFrequency (%)
0.0 485
79.8%
1.08 1
 
0.2%
2.26 1
 
0.2%
2.62 1
 
0.2%
2.7 1
 
0.2%
3.0 2
 
0.3%
3.44 1
 
0.2%
3.5 1
 
0.2%
4.07 1
 
0.2%
4.64 1
 
0.2%
ValueCountFrequency (%)
285.15 1
0.2%
197.0 1
0.2%
132.44 1
0.2%
109.09 1
0.2%
104.0 1
0.2%
103.86 1
0.2%
102.07 1
0.2%
90.2 1
0.2%
89.0 1
0.2%
77.4 1
0.2%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing608
Missing (%)100.0%
Memory size5.5 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030500003050000-106-1968-0028319680515<NA>3폐업2폐업20090814<NA><NA><NA>022212228998.0130859서울특별시 동대문구 전농동 647-51번지 (간데메서2길5)<NA><NA>제일식품2009-05-10 19:46:21I2018-08-31 23:59:59.0식품제조가공업204134.68682452405.215958식품제조가공업22주택가주변관리상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
130500003050000-106-1970-0084119701030<NA>3폐업2폐업20100823<NA><NA><NA>02 9536425120.0130821서울특별시 동대문구 용두동 129-20번지 외1필지<NA><NA>백광식품2009-12-02 11:32:39I2018-08-31 23:59:59.0식품제조가공업202690.433512452151.421374식품제조가공업11기타관리상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230500003050000-106-1972-0063619720523<NA>3폐업2폐업19990122<NA><NA><NA>02 962023215.5130826서울특별시 동대문구 이문동 292-87번지<NA><NA>영남기름집1999-02-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330500003050000-106-1973-0003119730130<NA>3폐업2폐업20001228<NA><NA><NA>02 967706947.01130862서울특별시 동대문구 제기동 620번지<NA><NA>광성상회2002-02-21 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업22기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430500003050000-106-1974-0003219740506<NA>3폐업2폐업19970206<NA><NA><NA>02 967730776.1130810서울특별시 동대문구 신설동 39-44번지<NA><NA>삼풍식품2003-08-13 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530500003050000-106-1974-002821974-12-04<NA>1영업/정상1영업<NA><NA><NA><NA>022245961160.96130-837서울특별시 동대문구 장안동 167-38서울특별시 동대문구 답십리로64길 67 (장안동)2626장안식품2023-01-31 09:58:34U2022-12-02 00:02:00.0식품제조가공업205761.59175451955.498149<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
630500003050000-106-1977-0028019771123<NA>3폐업2폐업20130129<NA><NA><NA>0222447028144.79130837서울특별시 동대문구 장안동 183-16번지서울특별시 동대문구 한천로18길 24 (장안동)<NA>아폴로제과2011-10-31 16:32:57I2018-08-31 23:59:59.0식품제조가공업205693.581059451805.069376식품제조가공업00주택가주변기타<NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730500003050000-106-1980-0063519801018<NA>3폐업2폐업19990203<NA><NA><NA>022244318114.82130800서울특별시 동대문구 답십리동 2-77번지 728<NA><NA>송도기름집1999-02-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830500003050000-106-1981-0003319810609<NA>3폐업2폐업20010525<NA><NA><NA>02221288530.0130800서울특별시 동대문구 답십리동 2-11번지<NA><NA>정다운식품2001-05-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업205524.689914451914.922245식품제조가공업22주택가주변관리상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930500003050000-106-1982-0082819820408<NA>3폐업2폐업20190628<NA><NA><NA>0222454966107.94130876서울특별시 동대문구 휘경동 246번지서울특별시 동대문구 망우로21가길 5 (휘경동)2436영창식품2019-06-28 10:49:36U2019-06-30 02:40:00.0식품제조가공업205410.814457454267.127897식품제조가공업21주택가주변관리상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
59830500003050000-106-2022-0000520220708<NA>1영업/정상1영업<NA><NA><NA><NA><NA>80.09130864서울특별시 동대문구 제기동 886-15 지하1층서울특별시 동대문구 약령중앙로 57-1, 지하1층 (제기동)2478해피물산2022-07-08 14:28:43I2021-12-06 23:02:00.0기타 식품제조가공업203212.340448453471.185899<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59930500003050000-106-2022-000062022-08-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>138.01130-850서울특별시 동대문구 전농동 38-18 지하1층서울특별시 동대문구 사가정로 143, 지하1층 (전농동)2508(주)조선한방2023-12-21 15:11:48U2022-11-01 22:03:00.0기타 식품제조가공업205302.095159452866.662645<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60030500003050000-106-2022-0000720220907<NA>1영업/정상1영업<NA><NA><NA><NA>02 555688067.3130851서울특별시 동대문구 전농동 597-2 2층서울특별시 동대문구 왕산로 254, 2층 (전농동)2554(주)한방제국2022-09-07 16:13:24I2021-12-09 00:09:00.0기타 식품제조가공업204323.818575453460.832617<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60130500003050000-106-2022-0000820221122<NA>1영업/정상1영업<NA><NA><NA><NA>02 959885466.46130864서울특별시 동대문구 제기동 705-3 2층서울특별시 동대문구 제기로 44-4, 2층 (제기동)2478(주)정우당바이오 제1공장2022-11-22 13:59:23I2021-10-31 22:04:00.0기타 식품제조가공업203258.724895453777.598481<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60230500003050000-106-2023-000012023-02-15<NA>1영업/정상1영업<NA><NA><NA><NA>02922 809895.92130-811서울특별시 동대문구 신설동 92-5서울특별시 동대문구 하정로6길 14, 1층 (신설동)2582풍원2023-02-15 10:23:56I2022-12-01 23:07:00.0기타 식품제조가공업202321.748119452650.066305<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60330500003050000-106-2023-000022023-05-04<NA>1영업/정상1영업<NA><NA><NA><NA><NA>69.42130-862서울특별시 동대문구 제기동 486-6서울특별시 동대문구 왕산로35길 42, 1층 (제기동)2573주식회사 제주미향(Jejumihyang Inc.)2024-03-28 14:25:54U2023-12-02 21:00:00.0기타 식품제조가공업203725.476586453252.24143<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60430500003050000-106-2023-000032023-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA>35.0130-840서울특별시 동대문구 장안동 331-10서울특별시 동대문구 장한로28길 50, 1층 107호 (장안동)2524주식회사 아하푸드2023-05-08 10:42:39I2022-12-04 23:00:00.0기타 식품제조가공업206538.848635452264.045196<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60530500003050000-106-2023-000042023-05-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>51.66130-070서울특별시 동대문구 용두동 792-3 래미안 허브리츠서울특별시 동대문구 왕산로26길 35, 래미안 허브리츠 2층 204호 (용두동)2567마라전설2023-05-30 13:13:52I2022-12-06 00:01:00.0기타 식품제조가공업203164.661789452691.906487<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60630500003050000-106-2023-000052023-10-25<NA>1영업/정상1영업<NA><NA><NA><NA>02925 4243170.4130-824서울특별시 동대문구 용두동 750-18 성은빌딩서울특별시 동대문구 무학로43길 18, 성은빌딩 지하1층 (용두동)2578주식회사 혜민당2024-01-26 13:39:11U2023-11-30 22:08:00.0기타 식품제조가공업202493.63537453153.386416<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60730500003050000-106-2024-000012024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>20.1130-863서울특별시 동대문구 제기동 842서울특별시 동대문구 고산자로44길 11, 1층 (제기동)2571무궁화푸드2024-02-21 10:42:56U2023-12-01 22:03:00.0기타 식품제조가공업203414.238282453369.18127<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>