Overview

Dataset statistics

Number of variables44
Number of observations367
Missing cells3923
Missing cells (%)24.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory134.9 KiB
Average record size in memory376.4 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
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-18258/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
총인원 is highly imbalanced (83.4%)Imbalance
공장사무직종업원수 is highly imbalanced (56.4%)Imbalance
보증액 is highly imbalanced (72.2%)Imbalance
월세액 is highly imbalanced (74.8%)Imbalance
인허가취소일자 has 367 (100.0%) missing valuesMissing
폐업일자 has 57 (15.5%) missing valuesMissing
휴업시작일자 has 367 (100.0%) missing valuesMissing
휴업종료일자 has 367 (100.0%) missing valuesMissing
재개업일자 has 367 (100.0%) missing valuesMissing
전화번호 has 77 (21.0%) missing valuesMissing
소재지면적 has 16 (4.4%) missing valuesMissing
도로명주소 has 179 (48.8%) missing valuesMissing
도로명우편번호 has 180 (49.0%) missing valuesMissing
좌표정보(X) has 14 (3.8%) missing valuesMissing
좌표정보(Y) has 14 (3.8%) missing valuesMissing
남성종사자수 has 271 (73.8%) missing valuesMissing
여성종사자수 has 278 (75.7%) missing valuesMissing
공장생산직종업원수 has 184 (50.1%) missing valuesMissing
다중이용업소여부 has 42 (11.4%) missing valuesMissing
시설총규모 has 42 (11.4%) missing valuesMissing
전통업소지정번호 has 367 (100.0%) missing valuesMissing
전통업소주된음식 has 367 (100.0%) missing valuesMissing
홈페이지 has 367 (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 4 (1.1%) zerosZeros
남성종사자수 has 31 (8.4%) zerosZeros
여성종사자수 has 43 (11.7%) zerosZeros
공장생산직종업원수 has 144 (39.2%) zerosZeros
시설총규모 has 317 (86.4%) zerosZeros

Reproduction

Analysis started2024-05-11 01:03:10.125135
Analysis finished2024-05-11 01:03:11.570954
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3060000
367 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3060000
2nd row3060000
3rd row3060000
4th row3060000
5th row3060000

Common Values

ValueCountFrequency (%)
3060000 367
100.0%

Length

2024-05-11T01:03:11.778464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:12.082603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3060000 367
100.0%

관리번호
Text

UNIQUE 

Distinct367
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T01:03:12.498084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8074
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

Unique367 ?
Unique (%)100.0%

Sample

1st row3060000-106-1968-00002
2nd row3060000-106-1971-00001
3rd row3060000-106-1982-00003
4th row3060000-106-1982-00230
5th row3060000-106-1985-00038
ValueCountFrequency (%)
3060000-106-1968-00002 1
 
0.3%
3060000-106-2010-00006 1
 
0.3%
3060000-106-2011-00007 1
 
0.3%
3060000-106-2011-00006 1
 
0.3%
3060000-106-2011-00005 1
 
0.3%
3060000-106-2011-00004 1
 
0.3%
3060000-106-2011-00003 1
 
0.3%
3060000-106-2011-00002 1
 
0.3%
3060000-106-2011-00001 1
 
0.3%
3060000-106-2010-00019 1
 
0.3%
Other values (357) 357
97.3%
2024-05-11T01:03:13.626680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3927
48.6%
- 1101
 
13.6%
6 819
 
10.1%
1 753
 
9.3%
3 494
 
6.1%
2 421
 
5.2%
9 238
 
2.9%
4 99
 
1.2%
5 77
 
1.0%
8 76
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6973
86.4%
Dash Punctuation 1101
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3927
56.3%
6 819
 
11.7%
1 753
 
10.8%
3 494
 
7.1%
2 421
 
6.0%
9 238
 
3.4%
4 99
 
1.4%
5 77
 
1.1%
8 76
 
1.1%
7 69
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 1101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8074
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3927
48.6%
- 1101
 
13.6%
6 819
 
10.1%
1 753
 
9.3%
3 494
 
6.1%
2 421
 
5.2%
9 238
 
2.9%
4 99
 
1.2%
5 77
 
1.0%
8 76
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8074
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3927
48.6%
- 1101
 
13.6%
6 819
 
10.1%
1 753
 
9.3%
3 494
 
6.1%
2 421
 
5.2%
9 238
 
2.9%
4 99
 
1.2%
5 77
 
1.0%
8 76
 
0.9%

인허가일자
Date

Distinct346
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum1968-11-04 00:00:00
Maximum2024-04-30 00:00:00
2024-05-11T01:03:14.304868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:03:15.037118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
3
310 
1
57 

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 (%)
3 310
84.5%
1 57
 
15.5%

Length

2024-05-11T01:03:15.542109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:15.993475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 310
84.5%
1 57
 
15.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
폐업
310 
영업/정상
57 

Length

Max length5
Median length2
Mean length2.4659401
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 310
84.5%
영업/정상 57
 
15.5%

Length

2024-05-11T01:03:16.527363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:16.933078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 310
84.5%
영업/정상 57
 
15.5%

상세영업상태코드
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2
310 
1
57 

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 (%)
2 310
84.5%
1 57
 
15.5%

Length

2024-05-11T01:03:17.315748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:17.652588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 310
84.5%
1 57
 
15.5%

상세영업상태명
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
폐업
310 
영업
57 

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 310
84.5%
영업 57
 
15.5%

Length

2024-05-11T01:03:18.004356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:18.309092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 310
84.5%
영업 57
 
15.5%

폐업일자
Date

MISSING 

Distinct289
Distinct (%)93.2%
Missing57
Missing (%)15.5%
Memory size3.0 KiB
Minimum1994-05-02 00:00:00
Maximum2024-01-24 00:00:00
2024-05-11T01:03:18.659131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:03:19.110512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

전화번호
Text

MISSING 

Distinct274
Distinct (%)94.5%
Missing77
Missing (%)21.0%
Memory size3.0 KiB
2024-05-11T01:03:19.895453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.255172
Min length2

Characters and Unicode

Total characters2974
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

Unique271 ?
Unique (%)93.4%

Sample

1st row02
2nd row02 4348976
3rd row02492 4992
4th row02
5th row02 9730051
ValueCountFrequency (%)
02 215
38.6%
070 17
 
3.1%
433 8
 
1.4%
434 4
 
0.7%
496 3
 
0.5%
438 3
 
0.5%
4330017 2
 
0.4%
439 2
 
0.4%
20377500 2
 
0.4%
60803552 2
 
0.4%
Other values (294) 299
53.7%
2024-05-11T01:03:21.222126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 520
17.5%
2 511
17.2%
338
11.4%
4 290
9.8%
3 285
9.6%
9 232
7.8%
7 187
 
6.3%
1 162
 
5.4%
6 155
 
5.2%
8 155
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2636
88.6%
Space Separator 338
 
11.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 520
19.7%
2 511
19.4%
4 290
11.0%
3 285
10.8%
9 232
8.8%
7 187
 
7.1%
1 162
 
6.1%
6 155
 
5.9%
8 155
 
5.9%
5 139
 
5.3%
Space Separator
ValueCountFrequency (%)
338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2974
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 520
17.5%
2 511
17.2%
338
11.4%
4 290
9.8%
3 285
9.6%
9 232
7.8%
7 187
 
6.3%
1 162
 
5.4%
6 155
 
5.2%
8 155
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2974
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 520
17.5%
2 511
17.2%
338
11.4%
4 290
9.8%
3 285
9.6%
9 232
7.8%
7 187
 
6.3%
1 162
 
5.4%
6 155
 
5.2%
8 155
 
5.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct283
Distinct (%)80.6%
Missing16
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean70.818034
Minimum0
Maximum680.16
Zeros4
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:21.755986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.255
Q124.535
median48.16
Q383.495
95-th percentile208.975
Maximum680.16
Range680.16
Interquartile range (IQR)58.96

Descriptive statistics

Standard deviation80.986118
Coefficient of variation (CV)1.1435804
Kurtosis16.419663
Mean70.818034
Median Absolute Deviation (MAD)27.96
Skewness3.4573659
Sum24857.13
Variance6558.7513
MonotonicityNot monotonic
2024-05-11T01:03:22.263183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.0 6
 
1.6%
99.0 6
 
1.6%
33.0 6
 
1.6%
27.0 6
 
1.6%
26.4 5
 
1.4%
49.5 5
 
1.4%
82.5 5
 
1.4%
20.0 5
 
1.4%
40.0 5
 
1.4%
50.0 4
 
1.1%
Other values (273) 298
81.2%
(Missing) 16
 
4.4%
ValueCountFrequency (%)
0.0 4
1.1%
3.78 1
 
0.3%
4.59 1
 
0.3%
6.16 1
 
0.3%
6.48 1
 
0.3%
6.6 1
 
0.3%
6.9 1
 
0.3%
8.0 1
 
0.3%
8.25 1
 
0.3%
9.0 2
0.5%
ValueCountFrequency (%)
680.16 1
0.3%
528.0 1
0.3%
471.0 1
0.3%
459.87 1
0.3%
448.3 1
0.3%
387.82 1
0.3%
377.44 1
0.3%
300.0 2
0.5%
292.0 1
0.3%
266.0 1
0.3%

소재지우편번호
Text

Distinct85
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T01:03:23.063543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0762943
Min length6

Characters and Unicode

Total characters2230
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

Unique21 ?
Unique (%)5.7%

Sample

1st row131852
2nd row131856
3rd row131817
4th row131831
5th row131852
ValueCountFrequency (%)
131802 13
 
3.5%
131861 12
 
3.3%
131811 12
 
3.3%
131806 11
 
3.0%
131-865 11
 
3.0%
131865 11
 
3.0%
131848 10
 
2.7%
131815 9
 
2.5%
131856 9
 
2.5%
131827 9
 
2.5%
Other values (75) 260
70.8%
2024-05-11T01:03:24.349456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 849
38.1%
3 416
18.7%
8 411
18.4%
2 106
 
4.8%
0 105
 
4.7%
6 99
 
4.4%
5 78
 
3.5%
7 72
 
3.2%
9 36
 
1.6%
4 30
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2202
98.7%
Dash Punctuation 28
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 849
38.6%
3 416
18.9%
8 411
18.7%
2 106
 
4.8%
0 105
 
4.8%
6 99
 
4.5%
5 78
 
3.5%
7 72
 
3.3%
9 36
 
1.6%
4 30
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 849
38.1%
3 416
18.7%
8 411
18.4%
2 106
 
4.8%
0 105
 
4.7%
6 99
 
4.4%
5 78
 
3.5%
7 72
 
3.2%
9 36
 
1.6%
4 30
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 849
38.1%
3 416
18.7%
8 411
18.4%
2 106
 
4.8%
0 105
 
4.7%
6 99
 
4.4%
5 78
 
3.5%
7 72
 
3.2%
9 36
 
1.6%
4 30
 
1.3%

지번주소
Text

Distinct347
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T01:03:25.474077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length38
Mean length24.623978
Min length14

Characters and Unicode

Total characters9037
Distinct characters116
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

Unique332 ?
Unique (%)90.5%

Sample

1st row서울특별시 중랑구 묵동 241-20번지
2nd row서울특별시 중랑구 상봉동 237-1번지
3rd row서울특별시 중랑구 면목동 228번지
4th row서울특별시 중랑구 면목동 497-7번지
5th row서울특별시 중랑구 묵동 241-20번지
ValueCountFrequency (%)
서울특별시 367
21.7%
중랑구 367
21.7%
면목동 138
 
8.2%
망우동 73
 
4.3%
상봉동 47
 
2.8%
신내동 41
 
2.4%
중화동 38
 
2.3%
묵동 30
 
1.8%
1층 26
 
1.5%
지상1층 22
 
1.3%
Other values (407) 539
31.9%
2024-05-11T01:03:27.257393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1636
18.1%
1 445
 
4.9%
중 407
 
4.5%
동 386
 
4.3%
지 371
 
4.1%
시 370
 
4.1%
구 367
 
4.1%
울 367
 
4.1%
서 367
 
4.1%
랑 367
 
4.1%
Other values (106) 3954
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5118
56.6%
Decimal Number 1810
 
20.0%
Space Separator 1636
 
18.1%
Dash Punctuation 339
 
3.8%
Lowercase Letter 42
 
0.5%
Uppercase Letter 30
 
0.3%
Close Punctuation 28
 
0.3%
Open Punctuation 28
 
0.3%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 407
 
8.0%
동 386
 
7.5%
지 371
 
7.2%
시 370
 
7.2%
구 367
 
7.2%
울 367
 
7.2%
서 367
 
7.2%
랑 367
 
7.2%
별 367
 
7.2%
특 367
 
7.2%
Other values (81) 1382
27.0%
Decimal Number
ValueCountFrequency (%)
1 445
24.6%
2 257
14.2%
3 221
12.2%
4 180
9.9%
6 147
 
8.1%
5 138
 
7.6%
0 126
 
7.0%
7 109
 
6.0%
8 106
 
5.9%
9 81
 
4.5%
Lowercase Letter
ValueCountFrequency (%)
e 14
33.3%
t 7
16.7%
c 7
16.7%
n 7
16.7%
r 7
16.7%
Uppercase Letter
ValueCountFrequency (%)
S 8
26.7%
K 7
23.3%
B 7
23.3%
V 7
23.3%
A 1
 
3.3%
Space Separator
ValueCountFrequency (%)
1636
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 339
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5118
56.6%
Common 3847
42.6%
Latin 72
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 407
 
8.0%
동 386
 
7.5%
지 371
 
7.2%
시 370
 
7.2%
구 367
 
7.2%
울 367
 
7.2%
서 367
 
7.2%
랑 367
 
7.2%
별 367
 
7.2%
특 367
 
7.2%
Other values (81) 1382
27.0%
Common
ValueCountFrequency (%)
1636
42.5%
1 445
 
11.6%
- 339
 
8.8%
2 257
 
6.7%
3 221
 
5.7%
4 180
 
4.7%
6 147
 
3.8%
5 138
 
3.6%
0 126
 
3.3%
7 109
 
2.8%
Other values (5) 249
 
6.5%
Latin
ValueCountFrequency (%)
e 14
19.4%
S 8
11.1%
K 7
9.7%
B 7
9.7%
V 7
9.7%
t 7
9.7%
c 7
9.7%
n 7
9.7%
r 7
9.7%
A 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5118
56.6%
ASCII 3919
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1636
41.7%
1 445
 
11.4%
- 339
 
8.7%
2 257
 
6.6%
3 221
 
5.6%
4 180
 
4.6%
6 147
 
3.8%
5 138
 
3.5%
0 126
 
3.2%
7 109
 
2.8%
Other values (15) 321
 
8.2%
Hangul
ValueCountFrequency (%)
중 407
 
8.0%
동 386
 
7.5%
지 371
 
7.2%
시 370
 
7.2%
구 367
 
7.2%
울 367
 
7.2%
서 367
 
7.2%
랑 367
 
7.2%
별 367
 
7.2%
특 367
 
7.2%
Other values (81) 1382
27.0%

도로명주소
Text

MISSING 

Distinct184
Distinct (%)97.9%
Missing179
Missing (%)48.8%
Memory size3.0 KiB
2024-05-11T01:03:28.162509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length50
Mean length31.271277
Min length21

Characters and Unicode

Total characters5879
Distinct characters133
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

Unique180 ?
Unique (%)95.7%

Sample

1st row서울특별시 중랑구 면목로84길 20 (면목동)
2nd row서울특별시 중랑구 면목천로23길 33, 지상1층, 지하1층 (면목동)
3rd row서울특별시 중랑구 봉화산로 123 (상봉동,신내테크노타운 302호)
4th row서울특별시 중랑구 사가정로31길 59 (면목동)
5th row서울특별시 중랑구 중랑천로20길 18 (중화동)
ValueCountFrequency (%)
서울특별시 188
 
16.4%
중랑구 188
 
16.4%
면목동 55
 
4.8%
지상1층 31
 
2.7%
망우동 31
 
2.7%
신내동 28
 
2.4%
상봉동 24
 
2.1%
1층 20
 
1.7%
중화동 18
 
1.6%
묵동 12
 
1.0%
Other values (316) 551
48.1%
2024-05-11T01:03:29.797042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
958
 
16.3%
1 284
 
4.8%
동 229
 
3.9%
중 227
 
3.9%
랑 200
 
3.4%
( 194
 
3.3%
) 194
 
3.3%
시 192
 
3.3%
별 188
 
3.2%
특 188
 
3.2%
Other values (123) 3025
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3334
56.7%
Space Separator 958
 
16.3%
Decimal Number 941
 
16.0%
Open Punctuation 194
 
3.3%
Close Punctuation 194
 
3.3%
Other Punctuation 151
 
2.6%
Uppercase Letter 46
 
0.8%
Lowercase Letter 42
 
0.7%
Dash Punctuation 19
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 229
 
6.9%
중 227
 
6.8%
랑 200
 
6.0%
시 192
 
5.8%
별 188
 
5.6%
특 188
 
5.6%
구 188
 
5.6%
울 188
 
5.6%
서 188
 
5.6%
로 185
 
5.5%
Other values (97) 1361
40.8%
Decimal Number
ValueCountFrequency (%)
1 284
30.2%
2 129
13.7%
3 102
 
10.8%
4 74
 
7.9%
6 73
 
7.8%
9 65
 
6.9%
0 62
 
6.6%
5 58
 
6.2%
7 51
 
5.4%
8 43
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 15
32.6%
S 9
19.6%
K 8
17.4%
V 8
17.4%
A 5
 
10.9%
F 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e 14
33.3%
c 7
16.7%
n 7
16.7%
t 7
16.7%
r 7
16.7%
Space Separator
ValueCountFrequency (%)
958
100.0%
Open Punctuation
ValueCountFrequency (%)
( 194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 194
100.0%
Other Punctuation
ValueCountFrequency (%)
, 151
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3334
56.7%
Common 2457
41.8%
Latin 88
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 229
 
6.9%
중 227
 
6.8%
랑 200
 
6.0%
시 192
 
5.8%
별 188
 
5.6%
특 188
 
5.6%
구 188
 
5.6%
울 188
 
5.6%
서 188
 
5.6%
로 185
 
5.5%
Other values (97) 1361
40.8%
Common
ValueCountFrequency (%)
958
39.0%
1 284
 
11.6%
( 194
 
7.9%
) 194
 
7.9%
, 151
 
6.1%
2 129
 
5.3%
3 102
 
4.2%
4 74
 
3.0%
6 73
 
3.0%
9 65
 
2.6%
Other values (5) 233
 
9.5%
Latin
ValueCountFrequency (%)
B 15
17.0%
e 14
15.9%
S 9
10.2%
K 8
9.1%
V 8
9.1%
c 7
8.0%
n 7
8.0%
t 7
8.0%
r 7
8.0%
A 5
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3334
56.7%
ASCII 2545
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
958
37.6%
1 284
 
11.2%
( 194
 
7.6%
) 194
 
7.6%
, 151
 
5.9%
2 129
 
5.1%
3 102
 
4.0%
4 74
 
2.9%
6 73
 
2.9%
9 65
 
2.6%
Other values (16) 321
 
12.6%
Hangul
ValueCountFrequency (%)
동 229
 
6.9%
중 227
 
6.8%
랑 200
 
6.0%
시 192
 
5.8%
별 188
 
5.6%
특 188
 
5.6%
구 188
 
5.6%
울 188
 
5.6%
서 188
 
5.6%
로 185
 
5.5%
Other values (97) 1361
40.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct107
Distinct (%)57.2%
Missing180
Missing (%)49.0%
Infinite0
Infinite (%)0.0%
Mean2135.2299
Minimum2002
Maximum2262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:30.358694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2029.3
Q12066
median2129
Q32195.5
95-th percentile2255.7
Maximum2262
Range260
Interquartile range (IQR)129.5

Descriptive statistics

Standard deviation73.374614
Coefficient of variation (CV)0.034363799
Kurtosis-1.1693841
Mean2135.2299
Median Absolute Deviation (MAD)65
Skewness0.11098664
Sum399288
Variance5383.8339
MonotonicityNot monotonic
2024-05-11T01:03:31.020212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2262 9
 
2.5%
2060 5
 
1.4%
2057 4
 
1.1%
2136 4
 
1.1%
2202 4
 
1.1%
2179 4
 
1.1%
2215 4
 
1.1%
2201 4
 
1.1%
2189 4
 
1.1%
2055 3
 
0.8%
Other values (97) 142
38.7%
(Missing) 180
49.0%
ValueCountFrequency (%)
2002 1
0.3%
2005 1
0.3%
2009 1
0.3%
2015 1
0.3%
2018 1
0.3%
2019 2
0.5%
2024 2
0.5%
2029 1
0.3%
2030 1
0.3%
2031 1
0.3%
ValueCountFrequency (%)
2262 9
2.5%
2256 1
 
0.3%
2255 2
 
0.5%
2253 1
 
0.3%
2252 1
 
0.3%
2248 1
 
0.3%
2246 1
 
0.3%
2244 2
 
0.5%
2240 1
 
0.3%
2239 2
 
0.5%

사업장명
Text

Distinct354
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-05-11T01:03:31.707239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length5.852861
Min length2

Characters and Unicode

Total characters2148
Distinct characters401
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique342 ?
Unique (%)93.2%

Sample

1st row크라운제과
2nd row진흥제과
3rd row동일식품
4th row대성식품
5th row(주)크라운제과
ValueCountFrequency (%)
주식회사 10
 
2.4%
대풍식품 3
 
0.7%
찜나라(주 2
 
0.5%
고향식품 2
 
0.5%
카페 2
 
0.5%
자연식품 2
 
0.5%
그린푸드 2
 
0.5%
명품김치 2
 
0.5%
만강생명공학 2
 
0.5%
커피로스터스 2
 
0.5%
Other values (375) 382
92.9%
2024-05-11T01:03:33.139937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 129
 
6.0%
품 121
 
5.6%
( 58
 
2.7%
) 58
 
2.7%
주 57
 
2.7%
스 47
 
2.2%
44
 
2.0%
드 42
 
2.0%
이 42
 
2.0%
푸 38
 
1.8%
Other values (391) 1512
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1865
86.8%
Open Punctuation 58
 
2.7%
Close Punctuation 58
 
2.7%
Uppercase Letter 54
 
2.5%
Lowercase Letter 48
 
2.2%
Space Separator 44
 
2.0%
Other Punctuation 12
 
0.6%
Decimal Number 9
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 129
 
6.9%
품 121
 
6.5%
주 57
 
3.1%
스 47
 
2.5%
드 42
 
2.3%
이 42
 
2.3%
푸 38
 
2.0%
사 26
 
1.4%
리 23
 
1.2%
커 21
 
1.1%
Other values (347) 1319
70.7%
Lowercase Letter
ValueCountFrequency (%)
e 11
22.9%
a 6
12.5%
f 5
10.4%
o 5
10.4%
r 4
 
8.3%
n 3
 
6.2%
h 2
 
4.2%
d 2
 
4.2%
v 2
 
4.2%
s 2
 
4.2%
Other values (6) 6
12.5%
Uppercase Letter
ValueCountFrequency (%)
F 8
14.8%
S 7
13.0%
A 7
13.0%
E 5
9.3%
C 4
7.4%
H 3
 
5.6%
B 3
 
5.6%
L 3
 
5.6%
K 3
 
5.6%
T 2
 
3.7%
Other values (6) 9
16.7%
Decimal Number
ValueCountFrequency (%)
2 3
33.3%
5 3
33.3%
4 1
 
11.1%
6 1
 
11.1%
3 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
& 5
41.7%
. 5
41.7%
, 1
 
8.3%
' 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1864
86.8%
Common 181
 
8.4%
Latin 102
 
4.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 129
 
6.9%
품 121
 
6.5%
주 57
 
3.1%
스 47
 
2.5%
드 42
 
2.3%
이 42
 
2.3%
푸 38
 
2.0%
사 26
 
1.4%
리 23
 
1.2%
커 21
 
1.1%
Other values (346) 1318
70.7%
Latin
ValueCountFrequency (%)
e 11
 
10.8%
F 8
 
7.8%
S 7
 
6.9%
A 7
 
6.9%
a 6
 
5.9%
f 5
 
4.9%
o 5
 
4.9%
E 5
 
4.9%
C 4
 
3.9%
r 4
 
3.9%
Other values (22) 40
39.2%
Common
ValueCountFrequency (%)
( 58
32.0%
) 58
32.0%
44
24.3%
& 5
 
2.8%
. 5
 
2.8%
2 3
 
1.7%
5 3
 
1.7%
, 1
 
0.6%
4 1
 
0.6%
6 1
 
0.6%
Other values (2) 2
 
1.1%
Han
ValueCountFrequency (%)
味 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1864
86.8%
ASCII 283
 
13.2%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 129
 
6.9%
품 121
 
6.5%
주 57
 
3.1%
스 47
 
2.5%
드 42
 
2.3%
이 42
 
2.3%
푸 38
 
2.0%
사 26
 
1.4%
리 23
 
1.2%
커 21
 
1.1%
Other values (346) 1318
70.7%
ASCII
ValueCountFrequency (%)
( 58
20.5%
) 58
20.5%
44
15.5%
e 11
 
3.9%
F 8
 
2.8%
S 7
 
2.5%
A 7
 
2.5%
a 6
 
2.1%
f 5
 
1.8%
& 5
 
1.8%
Other values (34) 74
26.1%
CJK
ValueCountFrequency (%)
味 1
100.0%

최종수정일자
Date

Distinct318
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum1999-05-18 00:00:00
Maximum2024-04-30 14:53:13
2024-05-11T01:03:33.884272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:03:34.460403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
I
283 
U
84 

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 283
77.1%
U 84
 
22.9%

Length

2024-05-11T01:03:35.043064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:35.446808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 283
77.1%
u 84
 
22.9%

데이터갱신일자
Date

Distinct82
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T01:03:36.063763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T01:03:36.606490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
식품제조가공업
247 
기타 식품제조가공업
87 
<NA>
30 
도시락제조업
 
3

Length

Max length10
Median length7
Mean length7.4577657
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 247
67.3%
기타 식품제조가공업 87
 
23.7%
<NA> 30
 
8.2%
도시락제조업 3
 
0.8%

Length

2024-05-11T01:03:37.143153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:37.565376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 334
73.6%
기타 87
 
19.2%
na 30
 
6.6%
도시락제조업 3
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct303
Distinct (%)85.8%
Missing14
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean207852.04
Minimum206205.86
Maximum209971.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:37.942838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206205.86
5-th percentile206488.43
Q1207045.85
median207781.19
Q3208603.61
95-th percentile209285.07
Maximum209971.43
Range3765.5656
Interquartile range (IQR)1557.7577

Descriptive statistics

Standard deviation917.15578
Coefficient of variation (CV)0.0044125417
Kurtosis-0.88759896
Mean207852.04
Median Absolute Deviation (MAD)766.61545
Skewness0.20892967
Sum73371769
Variance841174.72
MonotonicityNot monotonic
2024-05-11T01:03:38.513388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209856.1161416 8
 
2.2%
208295.099818379 5
 
1.4%
206912.458822482 4
 
1.1%
207681.1842276 3
 
0.8%
209085.926142332 3
 
0.8%
208206.911743153 3
 
0.8%
208721.642162806 3
 
0.8%
208688.609555165 2
 
0.5%
208543.327358667 2
 
0.5%
206924.12609435 2
 
0.5%
Other values (293) 318
86.6%
(Missing) 14
 
3.8%
ValueCountFrequency (%)
206205.863069274 1
0.3%
206221.834183749 1
0.3%
206260.298575831 1
0.3%
206264.85197789 1
0.3%
206285.912434623 1
0.3%
206297.016274369 1
0.3%
206297.841470404 1
0.3%
206322.77963775 1
0.3%
206373.441217193 1
0.3%
206386.730871323 1
0.3%
ValueCountFrequency (%)
209971.428647885 1
 
0.3%
209962.62104219 1
 
0.3%
209856.1161416 8
2.2%
209640.285276983 1
 
0.3%
209508.281405411 1
 
0.3%
209467.964473312 1
 
0.3%
209438.885311392 1
 
0.3%
209394.785345905 1
 
0.3%
209346.050897608 1
 
0.3%
209309.582070404 1
 
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct303
Distinct (%)85.8%
Missing14
Missing (%)3.8%
Infinite0
Infinite (%)0.0%
Mean454800.23
Minimum452098.77
Maximum457293.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:39.044142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum452098.77
5-th percentile452834.46
Q1454062.33
median454708.82
Q3455555.8
95-th percentile456969.91
Maximum457293.05
Range5194.2805
Interquartile range (IQR)1493.4735

Descriptive statistics

Standard deviation1221.2281
Coefficient of variation (CV)0.0026851967
Kurtosis-0.44887499
Mean454800.23
Median Absolute Deviation (MAD)799.23604
Skewness0.0796153
Sum1.6054448 × 108
Variance1491398
MonotonicityNot monotonic
2024-05-11T01:03:39.497757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
456761.921129526 8
 
2.2%
456014.999180519 5
 
1.4%
453177.317399649 4
 
1.1%
455748.848749807 3
 
0.8%
457283.215342184 3
 
0.8%
454062.329059485 3
 
0.8%
454002.69435428 3
 
0.8%
454181.631115481 2
 
0.5%
455535.39598378 2
 
0.5%
454543.074634929 2
 
0.5%
Other values (293) 318
86.6%
(Missing) 14
 
3.8%
ValueCountFrequency (%)
452098.766989799 1
0.3%
452101.45277602 1
0.3%
452146.66493964 1
0.3%
452149.719131363 1
0.3%
452192.158991451 2
0.5%
452208.729385467 1
0.3%
452225.242912252 1
0.3%
452226.040112475 1
0.3%
452239.15979783 1
0.3%
452632.532909779 1
0.3%
ValueCountFrequency (%)
457293.047459164 1
 
0.3%
457288.079083435 2
0.5%
457283.748995714 1
 
0.3%
457283.215342184 3
0.8%
457282.566032636 1
 
0.3%
457196.644834 1
 
0.3%
457193.033227 1
 
0.3%
457183.637796144 2
0.5%
457139.911315989 1
 
0.3%
457122.700436003 1
 
0.3%

위생업태명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
식품제조가공업
243 
<NA>
72 
기타 식품제조가공업
51 
도시락제조업
 
1

Length

Max length10
Median length7
Mean length6.8256131
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 243
66.2%
<NA> 72
 
19.6%
기타 식품제조가공업 51
 
13.9%
도시락제조업 1
 
0.3%

Length

2024-05-11T01:03:39.952017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:40.343605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 294
70.3%
na 72
 
17.2%
기타 51
 
12.2%
도시락제조업 1
 
0.2%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)8.3%
Missing271
Missing (%)73.8%
Infinite0
Infinite (%)0.0%
Mean1.5520833
Minimum0
Maximum50
Zeros31
Zeros (%)8.4%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:40.716054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3.25
Maximum50
Range50
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.14806
Coefficient of variation (CV)3.3168709
Kurtosis84.888534
Mean1.5520833
Median Absolute Deviation (MAD)1
Skewness8.980132
Sum149
Variance26.502522
MonotonicityNot monotonic
2024-05-11T01:03:41.215317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 47
 
12.8%
0 31
 
8.4%
2 9
 
2.5%
3 4
 
1.1%
5 2
 
0.5%
50 1
 
0.3%
8 1
 
0.3%
4 1
 
0.3%
(Missing) 271
73.8%
ValueCountFrequency (%)
0 31
8.4%
1 47
12.8%
2 9
 
2.5%
3 4
 
1.1%
4 1
 
0.3%
5 2
 
0.5%
8 1
 
0.3%
50 1
 
0.3%
ValueCountFrequency (%)
50 1
 
0.3%
8 1
 
0.3%
5 2
 
0.5%
4 1
 
0.3%
3 4
 
1.1%
2 9
 
2.5%
1 47
12.8%
0 31
8.4%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)6.7%
Missing278
Missing (%)75.7%
Infinite0
Infinite (%)0.0%
Mean0.7752809
Minimum0
Maximum5
Zeros43
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:41.599470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0197238
Coefficient of variation (CV)1.3152959
Kurtosis4.0922489
Mean0.7752809
Median Absolute Deviation (MAD)1
Skewness1.8494958
Sum69
Variance1.0398366
MonotonicityNot monotonic
2024-05-11T01:03:42.060675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 43
 
11.7%
1 33
 
9.0%
2 7
 
1.9%
3 3
 
0.8%
4 2
 
0.5%
5 1
 
0.3%
(Missing) 278
75.7%
ValueCountFrequency (%)
0 43
11.7%
1 33
9.0%
2 7
 
1.9%
3 3
 
0.8%
4 2
 
0.5%
5 1
 
0.3%
ValueCountFrequency (%)
5 1
 
0.3%
4 2
 
0.5%
3 3
 
0.8%
2 7
 
1.9%
1 33
9.0%
0 43
11.7%

영업장주변구분명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
275 
주택가주변
52 
기타
38 
아파트지역
 
2

Length

Max length5
Median length4
Mean length3.9400545
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
74.9%
주택가주변 52
 
14.2%
기타 38
 
10.4%
아파트지역 2
 
0.5%

Length

2024-05-11T01:03:42.540992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:43.081707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
74.9%
주택가주변 52
 
14.2%
기타 38
 
10.4%
아파트지역 2
 
0.5%

등급구분명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
275 
기타
52 
자율
39 
관리
 
1

Length

Max length4
Median length4
Mean length3.4986376
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 275
74.9%
기타 52
 
14.2%
자율 39
 
10.6%
관리 1
 
0.3%

Length

2024-05-11T01:03:43.706279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:44.312638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 275
74.9%
기타 52
 
14.2%
자율 39
 
10.6%
관리 1
 
0.3%

급수시설구분명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
198 
상수도전용
167 
상수도(음용)지하수(주방용)겸용
 
2

Length

Max length17
Median length4
Mean length4.5258856
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 198
54.0%
상수도전용 167
45.5%
상수도(음용)지하수(주방용)겸용 2
 
0.5%

Length

2024-05-11T01:03:44.757421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:45.470774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
54.0%
상수도전용 167
45.5%
상수도(음용)지하수(주방용)겸용 2
 
0.5%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
358 
0
 
9

Length

Max length4
Median length4
Mean length3.9264305
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> 358
97.5%
0 9
 
2.5%

Length

2024-05-11T01:03:45.880193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:46.280073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 358
97.5%
0 9
 
2.5%

본사종업원수
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
204 
0
163 

Length

Max length4
Median length4
Mean length2.6675749
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 204
55.6%
0 163
44.4%

Length

2024-05-11T01:03:47.057421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:47.632873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 204
55.6%
0 163
44.4%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
201 
0
160 
2
 
2
1
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.6430518
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 201
54.8%
0 160
43.6%
2 2
 
0.5%
1 2
 
0.5%
4 1
 
0.3%
7 1
 
0.3%

Length

2024-05-11T01:03:48.227680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:48.638470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 201
54.8%
0 160
43.6%
2 2
 
0.5%
1 2
 
0.5%
4 1
 
0.3%
7 1
 
0.3%

공장판매직종업원수
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
203 
0
162 
6
 
1
1
 
1

Length

Max length4
Median length4
Mean length2.6594005
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 203
55.3%
0 162
44.1%
6 1
 
0.3%
1 1
 
0.3%

Length

2024-05-11T01:03:49.273500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:49.945032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 203
55.3%
0 162
44.1%
6 1
 
0.3%
1 1
 
0.3%

공장생산직종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)5.5%
Missing184
Missing (%)50.1%
Infinite0
Infinite (%)0.0%
Mean0.57377049
Minimum0
Maximum18
Zeros144
Zeros (%)39.2%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:50.697807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum18
Range18
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.0498648
Coefficient of variation (CV)3.5726215
Kurtosis39.255192
Mean0.57377049
Median Absolute Deviation (MAD)0
Skewness5.8600421
Sum105
Variance4.2019456
MonotonicityNot monotonic
2024-05-11T01:03:51.129693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 144
39.2%
1 27
 
7.4%
2 4
 
1.1%
5 2
 
0.5%
18 1
 
0.3%
3 1
 
0.3%
13 1
 
0.3%
7 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
(Missing) 184
50.1%
ValueCountFrequency (%)
0 144
39.2%
1 27
 
7.4%
2 4
 
1.1%
3 1
 
0.3%
5 2
 
0.5%
7 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
13 1
 
0.3%
18 1
 
0.3%
ValueCountFrequency (%)
18 1
 
0.3%
13 1
 
0.3%
10 1
 
0.3%
9 1
 
0.3%
7 1
 
0.3%
5 2
 
0.5%
3 1
 
0.3%
2 4
 
1.1%
1 27
 
7.4%
0 144
39.2%

건물소유구분명
Categorical

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
193 
임대
129 
자가
45 

Length

Max length4
Median length4
Mean length3.0517711
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> 193
52.6%
임대 129
35.1%
자가 45
 
12.3%

Length

2024-05-11T01:03:51.776912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:52.272518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 193
52.6%
임대 129
35.1%
자가 45
 
12.3%

보증액
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
317 
0
46 
10000000
 
2
5000000
 
1
4000000
 
1

Length

Max length8
Median length4
Mean length3.6621253
Min length1

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 317
86.4%
0 46
 
12.5%
10000000 2
 
0.5%
5000000 1
 
0.3%
4000000 1
 
0.3%

Length

2024-05-11T01:03:52.755987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:53.197755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 317
86.4%
0 46
 
12.5%
10000000 2
 
0.5%
5000000 1
 
0.3%
4000000 1
 
0.3%

월세액
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
317 
0
46 
1500000
 
1
2300000
 
1
500000
 
1

Length

Max length7
Median length4
Mean length3.653951
Min length1

Unique

Unique4 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 317
86.4%
0 46
 
12.5%
1500000 1
 
0.3%
2300000 1
 
0.3%
500000 1
 
0.3%
1000000 1
 
0.3%

Length

2024-05-11T01:03:53.657638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T01:03:54.213210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 317
86.4%
0 46
 
12.5%
1500000 1
 
0.3%
2300000 1
 
0.3%
500000 1
 
0.3%
1000000 1
 
0.3%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing42
Missing (%)11.4%
Memory size866.0 B
False
325 
(Missing)
42 
ValueCountFrequency (%)
False 325
88.6%
(Missing) 42
 
11.4%
2024-05-11T01:03:54.495828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)2.8%
Missing42
Missing (%)11.4%
Infinite0
Infinite (%)0.0%
Mean0.45815385
Minimum0
Maximum57.26
Zeros317
Zeros (%)86.4%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-05-11T01:03:54.823971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum57.26
Range57.26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9785973
Coefficient of variation (CV)8.6839765
Kurtosis144.00077
Mean0.45815385
Median Absolute Deviation (MAD)0
Skewness11.372588
Sum148.9
Variance15.829236
MonotonicityNot monotonic
2024-05-11T01:03:55.353647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 317
86.4%
6.68 1
 
0.3%
6.96 1
 
0.3%
11.0 1
 
0.3%
5.4 1
 
0.3%
28.6 1
 
0.3%
57.26 1
 
0.3%
29.0 1
 
0.3%
4.0 1
 
0.3%
(Missing) 42
 
11.4%
ValueCountFrequency (%)
0.0 317
86.4%
4.0 1
 
0.3%
5.4 1
 
0.3%
6.68 1
 
0.3%
6.96 1
 
0.3%
11.0 1
 
0.3%
28.6 1
 
0.3%
29.0 1
 
0.3%
57.26 1
 
0.3%
ValueCountFrequency (%)
57.26 1
 
0.3%
29.0 1
 
0.3%
28.6 1
 
0.3%
11.0 1
 
0.3%
6.96 1
 
0.3%
6.68 1
 
0.3%
5.4 1
 
0.3%
4.0 1
 
0.3%
0.0 317
86.4%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing367
Missing (%)100.0%
Memory size3.4 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030600003060000-106-1968-0000219681104<NA>3폐업2폐업19990318<NA><NA><NA>020.0131852서울특별시 중랑구 묵동 241-20번지<NA><NA>크라운제과2001-10-04 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업500주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130600003060000-106-1971-0000119710814<NA>3폐업2폐업19960502<NA><NA><NA>02 434897661.14131856서울특별시 중랑구 상봉동 237-1번지<NA><NA>진흥제과2001-10-04 00:00:00I2018-08-31 23:59:59.0식품제조가공업207781.186639455508.058398식품제조가공업32주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
230600003060000-106-1982-0000319820910<NA>3폐업2폐업20140407<NA><NA><NA>02492 499269.25131817서울특별시 중랑구 면목동 228번지서울특별시 중랑구 면목로84길 20 (면목동)2160동일식품2011-10-30 14:05:25I2018-08-31 23:59:59.0식품제조가공업207687.293763454400.511256식품제조가공업23주택가주변기타상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
330600003060000-106-1982-0023019821024<NA>3폐업2폐업20000522<NA><NA><NA>020.0131831서울특별시 중랑구 면목동 497-7번지<NA><NA>대성식품2000-05-22 00:00:00I2018-08-31 23:59:59.0식품제조가공업207729.17566453342.232542식품제조가공업51주택가주변자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430600003060000-106-1985-0003819850921<NA>3폐업2폐업19990318<NA><NA><NA>02 9730051235.12131852서울특별시 중랑구 묵동 241-20번지<NA><NA>(주)크라운제과2001-10-04 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA>85주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
530600003060000-106-1987-0003119960410<NA>3폐업2폐업20070718<NA><NA><NA>02 494856363.63131838서울특별시 중랑구 면목동 1340-1번지<NA><NA>한양식품2002-04-22 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업21주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
630600003060000-106-1991-0000419910520<NA>3폐업2폐업19951101<NA><NA><NA>02 4926392177.0131860서울특별시 중랑구 상봉동 120-13번지<NA><NA>리리식품2001-10-04 00:00:00I2018-08-31 23:59:59.0식품제조가공업207038.500653454606.91695식품제조가공업33기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
730600003060000-106-1991-0031419910403<NA>3폐업2폐업20000119<NA><NA><NA>0246.89131817서울특별시 중랑구 면목동 89-46번지<NA><NA>동방유통2000-01-19 00:00:00I2018-08-31 23:59:59.0<NA>208064.84629454555.213025<NA>00기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
830600003060000-106-1991-0031519910228<NA>3폐업2폐업20070221<NA><NA><NA>02 4372222<NA>131824서울특별시 중랑구 면목동 190-45번지<NA><NA>내명종합제분2002-04-18 00:00:00I2018-08-31 23:59:59.0식품제조가공업206393.683473453995.288309식품제조가공업<NA><NA><NA><NA>상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
930600003060000-106-1992-0000719921104<NA>3폐업2폐업19940502<NA><NA><NA>0204388391157.22131814서울특별시 중랑구 면목동 62-33번지<NA><NA>남경식품2001-10-04 00:00:00I2018-08-31 23:59:59.0식품제조가공업<NA><NA>식품제조가공업22주택가주변기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
35730600003060000-106-2022-000022022-06-08<NA>1영업/정상1영업<NA><NA><NA><NA>02 432 816561.73131-856서울특별시 중랑구 상봉동 263-11서울특별시 중랑구 상봉중앙로 40, 2층 (상봉동)2082파블로프 커피 로스팅2023-08-16 12:52:35U2022-12-07 23:08:00.0기타 식품제조가공업207674.78842455373.166294<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35830600003060000-106-2022-000032022-06-08<NA>1영업/정상1영업<NA><NA><NA><NA>070 7798122998.11131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center 303호 (신내동)2262맹글담2023-08-18 13:06:35U2022-12-07 22:00:00.0기타 식품제조가공업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
35930600003060000-106-2022-000042022-11-11<NA>1영업/정상1영업<NA><NA><NA><NA>070 7954378376.44131-865서울특별시 중랑구 신내동 262-1 B1209호서울특별시 중랑구 신내역로3길 40-36, B1209호 (신내동)2055주식회사 이퀄테이블2023-08-14 16:57:30U2022-12-07 23:07:00.0기타 식품제조가공업209085.926142457283.215342<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36030600003060000-106-2023-000012023-06-28<NA>1영업/정상1영업<NA><NA><NA><NA><NA>147.0131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center 215호서울특별시 중랑구 신내역로 111, 신내 SK V1 center 215호 (신내동)2262(주)우리꽃연구소 제2공장2023-06-28 17:52:34I2022-12-05 21:00:00.0기타 식품제조가공업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36130600003060000-106-2023-000022023-09-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA>33.0131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center A동 906호 (신내동)2262유포리아 커피로스터스2024-01-23 10:41:47U2023-11-30 22:05:00.0기타 식품제조가공업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36230600003060000-106-2023-000032023-11-16<NA>1영업/정상1영업<NA><NA><NA><NA><NA>116.6131-806서울특별시 중랑구 망우동 411-8서울특별시 중랑구 용마산로 474, 1층 (망우동)2183국대푸드협동조합2023-11-16 16:09:58I2022-10-31 23:08:00.0도시락제조업208692.777245454559.965249<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36330600003060000-106-2024-000012024-01-11<NA>1영업/정상1영업<NA><NA><NA><NA><NA>100.62131-865서울특별시 중랑구 신내동 666 신아타운서울특별시 중랑구 봉화산로 194, 신아타운 6층 614호 (신내동)2076도쿄베이커리 분점2024-01-11 11:23:02I2023-11-30 23:03:00.0기타 식품제조가공업208295.099818456014.999181<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36430600003060000-106-2024-000022024-02-01<NA>1영업/정상1영업<NA><NA><NA><NA><NA>42.24131-821서울특별시 중랑구 면목동 150-32서울특별시 중랑구 겸재로18길 9, 1층 (면목동)2215마하피플2024-02-01 09:23:50I2023-12-02 00:03:00.0기타 식품제조가공업207070.613561453792.708565<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36530600003060000-106-2024-000032024-04-09<NA>1영업/정상1영업<NA><NA><NA><NA>02 2217299968.06131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center A동 2층 238호 (신내동)2262(주)플레이버3652024-04-09 17:11:38I2023-12-03 23:01:00.0기타 식품제조가공업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
36630600003060000-106-2024-000042024-04-30<NA>1영업/정상1영업<NA><NA><NA><NA><NA>63.84131-865서울특별시 중랑구 신내동 821-2 신내 SK V1 center서울특별시 중랑구 신내역로 111, 신내 SK V1 center B동 지하1층 141호 (신내동)2262주식회사 모흐2024-04-30 14:53:13I2023-12-05 00:02:00.0기타 식품제조가공업209856.116142456761.92113<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>