Overview

Dataset statistics

Number of variables44
Number of observations193
Missing cells1918
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory71.0 KiB
Average record size in memory376.7 B

Variable types

Categorical20
Text6
DateTime4
Unsupported7
Numeric6
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
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-18252/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
다중이용업소여부 has constant value ""Constant
영업상태코드 is highly imbalanced (52.0%)Imbalance
영업상태명 is highly imbalanced (52.0%)Imbalance
상세영업상태코드 is highly imbalanced (52.0%)Imbalance
상세영업상태명 is highly imbalanced (52.0%)Imbalance
남성종사자수 is highly imbalanced (55.1%)Imbalance
여성종사자수 is highly imbalanced (61.1%)Imbalance
총인원 is highly imbalanced (72.8%)Imbalance
보증액 is highly imbalanced (66.2%)Imbalance
월세액 is highly imbalanced (66.2%)Imbalance
인허가취소일자 has 193 (100.0%) missing valuesMissing
폐업일자 has 20 (10.4%) missing valuesMissing
휴업시작일자 has 193 (100.0%) missing valuesMissing
휴업종료일자 has 193 (100.0%) missing valuesMissing
재개업일자 has 193 (100.0%) missing valuesMissing
전화번호 has 47 (24.4%) missing valuesMissing
소재지면적 has 151 (78.2%) missing valuesMissing
도로명주소 has 100 (51.8%) missing valuesMissing
도로명우편번호 has 102 (52.8%) missing valuesMissing
좌표정보(X) has 8 (4.1%) missing valuesMissing
좌표정보(Y) has 8 (4.1%) missing valuesMissing
본사종업원수 has 97 (50.3%) missing valuesMissing
다중이용업소여부 has 16 (8.3%) missing valuesMissing
시설총규모 has 16 (8.3%) missing valuesMissing
전통업소지정번호 has 193 (100.0%) missing valuesMissing
전통업소주된음식 has 193 (100.0%) missing valuesMissing
홈페이지 has 193 (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
본사종업원수 has 85 (44.0%) zerosZeros
시설총규모 has 169 (87.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:42:00.913271
Analysis finished2024-05-11 06:42:02.432629
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3000000
193 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000
2nd row3000000
3rd row3000000
4th row3000000
5th row3000000

Common Values

ValueCountFrequency (%)
3000000 193
100.0%

Length

2024-05-11T15:42:02.523089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:02.664645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000 193
100.0%

관리번호
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T15:42:02.879130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4246
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

Unique193 ?
Unique (%)100.0%

Sample

1st row3000000-106-1969-00004
2nd row3000000-106-1975-00001
3rd row3000000-106-1985-00002
4th row3000000-106-1986-00003
5th row3000000-106-1995-00005
ValueCountFrequency (%)
3000000-106-1969-00004 1
 
0.5%
3000000-106-2009-00008 1
 
0.5%
3000000-106-2013-00004 1
 
0.5%
3000000-106-2012-00005 1
 
0.5%
3000000-106-2012-00006 1
 
0.5%
3000000-106-2012-00007 1
 
0.5%
3000000-106-2012-00008 1
 
0.5%
3000000-106-2012-00009 1
 
0.5%
3000000-106-2012-00010 1
 
0.5%
3000000-106-2013-00001 1
 
0.5%
Other values (183) 183
94.8%
2024-05-11T15:42:03.360517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2319
54.6%
- 579
 
13.6%
1 394
 
9.3%
3 240
 
5.7%
2 231
 
5.4%
6 229
 
5.4%
9 105
 
2.5%
5 45
 
1.1%
4 38
 
0.9%
7 33
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3667
86.4%
Dash Punctuation 579
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2319
63.2%
1 394
 
10.7%
3 240
 
6.5%
2 231
 
6.3%
6 229
 
6.2%
9 105
 
2.9%
5 45
 
1.2%
4 38
 
1.0%
7 33
 
0.9%
8 33
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 579
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4246
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2319
54.6%
- 579
 
13.6%
1 394
 
9.3%
3 240
 
5.7%
2 231
 
5.4%
6 229
 
5.4%
9 105
 
2.5%
5 45
 
1.1%
4 38
 
0.9%
7 33
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4246
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2319
54.6%
- 579
 
13.6%
1 394
 
9.3%
3 240
 
5.7%
2 231
 
5.4%
6 229
 
5.4%
9 105
 
2.5%
5 45
 
1.1%
4 38
 
0.9%
7 33
 
0.8%

인허가일자
Date

Distinct191
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1969-08-18 00:00:00
Maximum2023-04-10 00:00:00
2024-05-11T15:42:03.690108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:04.011507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
3
173 
1
20 

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 (%)
3 173
89.6%
1 20
 
10.4%

Length

2024-05-11T15:42:04.284540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:04.449467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 173
89.6%
1 20
 
10.4%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
173 
영업/정상
20 

Length

Max length5
Median length2
Mean length2.3108808
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 173
89.6%
영업/정상 20
 
10.4%

Length

2024-05-11T15:42:04.631809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:04.786154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 173
89.6%
영업/정상 20
 
10.4%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2
173 
1
20 

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 (%)
2 173
89.6%
1 20
 
10.4%

Length

2024-05-11T15:42:05.001804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:05.260197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 173
89.6%
1 20
 
10.4%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
폐업
173 
영업
20 

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 173
89.6%
영업 20
 
10.4%

Length

2024-05-11T15:42:05.439732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:05.602974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 173
89.6%
영업 20
 
10.4%

폐업일자
Date

MISSING 

Distinct163
Distinct (%)94.2%
Missing20
Missing (%)10.4%
Memory size1.6 KiB
Minimum1994-12-28 00:00:00
Maximum2023-07-31 00:00:00
2024-05-11T15:42:05.799971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:06.010655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

전화번호
Text

MISSING 

Distinct143
Distinct (%)97.9%
Missing47
Missing (%)24.4%
Memory size1.6 KiB
2024-05-11T15:42:06.440433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.924658
Min length6

Characters and Unicode

Total characters1595
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

Unique141 ?
Unique (%)96.6%

Sample

1st row0200000000
2nd row0207459936
3rd row0200000000
4th row02 1001000
5th row02 3958686
ValueCountFrequency (%)
02 107
35.7%
743 4
 
1.3%
730 3
 
1.0%
070 3
 
1.0%
733 3
 
1.0%
0215448592 3
 
1.0%
737 2
 
0.7%
747 2
 
0.7%
723 2
 
0.7%
0200000000 2
 
0.7%
Other values (168) 169
56.3%
2024-05-11T15:42:07.135864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 296
18.6%
2 283
17.7%
207
13.0%
7 164
10.3%
3 124
7.8%
5 114
 
7.1%
4 89
 
5.6%
6 87
 
5.5%
1 82
 
5.1%
9 77
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1388
87.0%
Space Separator 207
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 296
21.3%
2 283
20.4%
7 164
11.8%
3 124
8.9%
5 114
 
8.2%
4 89
 
6.4%
6 87
 
6.3%
1 82
 
5.9%
9 77
 
5.5%
8 72
 
5.2%
Space Separator
ValueCountFrequency (%)
207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1595
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 296
18.6%
2 283
17.7%
207
13.0%
7 164
10.3%
3 124
7.8%
5 114
 
7.1%
4 89
 
5.6%
6 87
 
5.5%
1 82
 
5.1%
9 77
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1595
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 296
18.6%
2 283
17.7%
207
13.0%
7 164
10.3%
3 124
7.8%
5 114
 
7.1%
4 89
 
5.6%
6 87
 
5.5%
1 82
 
5.1%
9 77
 
4.8%

소재지면적
Real number (ℝ)

MISSING 

Distinct42
Distinct (%)100.0%
Missing151
Missing (%)78.2%
Infinite0
Infinite (%)0.0%
Mean61.380714
Minimum6.18
Maximum499.62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:07.391381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.18
5-th percentile8.36
Q118.85
median39.405
Q365.255
95-th percentile94.325
Maximum499.62
Range493.44
Interquartile range (IQR)46.405

Descriptive statistics

Standard deviation96.617762
Coefficient of variation (CV)1.5740736
Kurtosis15.641481
Mean61.380714
Median Absolute Deviation (MAD)23.48
Skewness3.9228892
Sum2577.99
Variance9334.992
MonotonicityNot monotonic
2024-05-11T15:42:07.638203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
82.18 1
 
0.5%
57.91 1
 
0.5%
38.81 1
 
0.5%
68.0 1
 
0.5%
14.92 1
 
0.5%
85.0 1
 
0.5%
21.4 1
 
0.5%
14.51 1
 
0.5%
32.0 1
 
0.5%
27.78 1
 
0.5%
Other values (32) 32
 
16.6%
(Missing) 151
78.2%
ValueCountFrequency (%)
6.18 1
0.5%
7.68 1
0.5%
8.3 1
0.5%
9.5 1
0.5%
9.9 1
0.5%
11.58 1
0.5%
12.0 1
0.5%
12.81 1
0.5%
14.51 1
0.5%
14.92 1
0.5%
ValueCountFrequency (%)
499.62 1
0.5%
443.3 1
0.5%
94.4 1
0.5%
92.9 1
0.5%
85.0 1
0.5%
82.18 1
0.5%
80.26 1
0.5%
80.0 1
0.5%
75.21 1
0.5%
68.0 1
0.5%

소재지우편번호
Text

Distinct94
Distinct (%)49.0%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-05-11T15:42:08.097790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.046875
Min length6

Characters and Unicode

Total characters1161
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

Unique49 ?
Unique (%)25.5%

Sample

1st row110043
2nd row110842
3rd row110122
4th row110290
5th row110847
ValueCountFrequency (%)
110522 8
 
4.2%
110847 7
 
3.6%
110530 6
 
3.1%
110817 5
 
2.6%
110111 4
 
2.1%
110816 4
 
2.1%
110809 4
 
2.1%
110044 4
 
2.1%
110320 4
 
2.1%
110837 4
 
2.1%
Other values (84) 142
74.0%
2024-05-11T15:42:08.840689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 460
39.6%
0 314
27.0%
8 75
 
6.5%
2 72
 
6.2%
4 55
 
4.7%
5 50
 
4.3%
3 49
 
4.2%
7 37
 
3.2%
6 23
 
2.0%
9 17
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1152
99.2%
Dash Punctuation 9
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 460
39.9%
0 314
27.3%
8 75
 
6.5%
2 72
 
6.2%
4 55
 
4.8%
5 50
 
4.3%
3 49
 
4.3%
7 37
 
3.2%
6 23
 
2.0%
9 17
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 460
39.6%
0 314
27.0%
8 75
 
6.5%
2 72
 
6.2%
4 55
 
4.7%
5 50
 
4.3%
3 49
 
4.2%
7 37
 
3.2%
6 23
 
2.0%
9 17
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 460
39.6%
0 314
27.0%
8 75
 
6.5%
2 72
 
6.2%
4 55
 
4.7%
5 50
 
4.3%
3 49
 
4.2%
7 37
 
3.2%
6 23
 
2.0%
9 17
 
1.5%

지번주소
Text

Distinct191
Distinct (%)99.5%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-05-11T15:42:09.277371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length24.666667
Min length17

Characters and Unicode

Total characters4736
Distinct characters156
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

Unique190 ?
Unique (%)99.0%

Sample

1st row서울특별시 종로구 통인동 137-2번지
2nd row서울특별시 종로구 창신동 447-2번지
3rd row서울특별시 종로구 종로2가 56-24번지
4th row서울특별시 종로구 인사동 137-2번지
5th row서울특별시 종로구 평창동 245번지
ValueCountFrequency (%)
서울특별시 192
20.8%
종로구 192
20.8%
1층 30
 
3.2%
창신동 19
 
2.1%
지하1층 17
 
1.8%
숭인동 12
 
1.3%
평창동 10
 
1.1%
부암동 9
 
1.0%
2층 9
 
1.0%
명륜2가 8
 
0.9%
Other values (308) 426
46.1%
2024-05-11T15:42:09.940826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
901
19.0%
1 241
 
5.1%
로 207
 
4.4%
종 205
 
4.3%
지 198
 
4.2%
서 197
 
4.2%
구 192
 
4.1%
울 192
 
4.1%
시 192
 
4.1%
별 192
 
4.1%
Other values (146) 2019
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2800
59.1%
Space Separator 901
 
19.0%
Decimal Number 853
 
18.0%
Dash Punctuation 148
 
3.1%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%
Uppercase Letter 10
 
0.2%
Other Punctuation 3
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 207
 
7.4%
종 205
 
7.3%
지 198
 
7.1%
서 197
 
7.0%
구 192
 
6.9%
울 192
 
6.9%
시 192
 
6.9%
별 192
 
6.9%
특 192
 
6.9%
동 186
 
6.6%
Other values (126) 847
30.2%
Decimal Number
ValueCountFrequency (%)
1 241
28.3%
2 143
16.8%
4 77
 
9.0%
3 77
 
9.0%
0 65
 
7.6%
5 62
 
7.3%
8 57
 
6.7%
7 48
 
5.6%
6 42
 
4.9%
9 41
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
60.0%
A 2
 
20.0%
D 2
 
20.0%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
901
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 148
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2800
59.1%
Common 1926
40.7%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 207
 
7.4%
종 205
 
7.3%
지 198
 
7.1%
서 197
 
7.0%
구 192
 
6.9%
울 192
 
6.9%
시 192
 
6.9%
별 192
 
6.9%
특 192
 
6.9%
동 186
 
6.6%
Other values (126) 847
30.2%
Common
ValueCountFrequency (%)
901
46.8%
1 241
 
12.5%
- 148
 
7.7%
2 143
 
7.4%
4 77
 
4.0%
3 77
 
4.0%
0 65
 
3.4%
5 62
 
3.2%
8 57
 
3.0%
7 48
 
2.5%
Other values (7) 107
 
5.6%
Latin
ValueCountFrequency (%)
B 6
60.0%
A 2
 
20.0%
D 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2800
59.1%
ASCII 1936
40.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
901
46.5%
1 241
 
12.4%
- 148
 
7.6%
2 143
 
7.4%
4 77
 
4.0%
3 77
 
4.0%
0 65
 
3.4%
5 62
 
3.2%
8 57
 
2.9%
7 48
 
2.5%
Other values (10) 117
 
6.0%
Hangul
ValueCountFrequency (%)
로 207
 
7.4%
종 205
 
7.3%
지 198
 
7.1%
서 197
 
7.0%
구 192
 
6.9%
울 192
 
6.9%
시 192
 
6.9%
별 192
 
6.9%
특 192
 
6.9%
동 186
 
6.6%
Other values (126) 847
30.2%

도로명주소
Text

MISSING 

Distinct92
Distinct (%)98.9%
Missing100
Missing (%)51.8%
Memory size1.6 KiB
2024-05-11T15:42:10.405130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length42
Mean length31.419355
Min length21

Characters and Unicode

Total characters2922
Distinct characters150
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)97.8%

Sample

1st row서울특별시 종로구 종로58가길 9 (숭인동)
2nd row서울특별시 종로구 돈화문로 71 (와룡동)
3rd row서울특별시 종로구 옥인길 8, 201호 (옥인동)
4th row서울특별시 종로구 창의문로 132 (부암동,2층)
5th row서울특별시 종로구 대학로11길 43 (명륜4가,3층)
ValueCountFrequency (%)
서울특별시 93
 
15.7%
종로구 93
 
15.7%
1층 27
 
4.6%
지하1층 14
 
2.4%
창신동 9
 
1.5%
3층 7
 
1.2%
종로 7
 
1.2%
혜화동 7
 
1.2%
19 7
 
1.2%
2층 6
 
1.0%
Other values (223) 322
54.4%
2024-05-11T15:42:11.214324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
499
 
17.1%
로 176
 
6.0%
1 136
 
4.7%
종 112
 
3.8%
동 106
 
3.6%
, 97
 
3.3%
서 96
 
3.3%
) 94
 
3.2%
( 94
 
3.2%
특 93
 
3.2%
Other values (140) 1419
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1673
57.3%
Space Separator 499
 
17.1%
Decimal Number 436
 
14.9%
Other Punctuation 98
 
3.4%
Close Punctuation 94
 
3.2%
Open Punctuation 94
 
3.2%
Dash Punctuation 19
 
0.7%
Uppercase Letter 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 176
 
10.5%
종 112
 
6.7%
동 106
 
6.3%
서 96
 
5.7%
특 93
 
5.6%
별 93
 
5.6%
시 93
 
5.6%
구 93
 
5.6%
울 93
 
5.6%
층 68
 
4.1%
Other values (121) 650
38.9%
Decimal Number
ValueCountFrequency (%)
1 136
31.2%
2 67
15.4%
3 49
 
11.2%
4 34
 
7.8%
5 33
 
7.6%
0 33
 
7.6%
8 25
 
5.7%
9 22
 
5.0%
6 21
 
4.8%
7 16
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 7
77.8%
D 1
 
11.1%
A 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 97
99.0%
. 1
 
1.0%
Space Separator
ValueCountFrequency (%)
499
100.0%
Close Punctuation
ValueCountFrequency (%)
) 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1673
57.3%
Common 1240
42.4%
Latin 9
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 176
 
10.5%
종 112
 
6.7%
동 106
 
6.3%
서 96
 
5.7%
특 93
 
5.6%
별 93
 
5.6%
시 93
 
5.6%
구 93
 
5.6%
울 93
 
5.6%
층 68
 
4.1%
Other values (121) 650
38.9%
Common
ValueCountFrequency (%)
499
40.2%
1 136
 
11.0%
, 97
 
7.8%
) 94
 
7.6%
( 94
 
7.6%
2 67
 
5.4%
3 49
 
4.0%
4 34
 
2.7%
5 33
 
2.7%
0 33
 
2.7%
Other values (6) 104
 
8.4%
Latin
ValueCountFrequency (%)
B 7
77.8%
D 1
 
11.1%
A 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1673
57.3%
ASCII 1249
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
499
40.0%
1 136
 
10.9%
, 97
 
7.8%
) 94
 
7.5%
( 94
 
7.5%
2 67
 
5.4%
3 49
 
3.9%
4 34
 
2.7%
5 33
 
2.6%
0 33
 
2.6%
Other values (9) 113
 
9.0%
Hangul
ValueCountFrequency (%)
로 176
 
10.5%
종 112
 
6.7%
동 106
 
6.3%
서 96
 
5.7%
특 93
 
5.6%
별 93
 
5.6%
시 93
 
5.6%
구 93
 
5.6%
울 93
 
5.6%
층 68
 
4.1%
Other values (121) 650
38.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct60
Distinct (%)65.9%
Missing102
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean3106.6044
Minimum3011
Maximum3197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:11.472338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3011
5-th percentile3021
Q13073.5
median3108
Q33147
95-th percentile3180
Maximum3197
Range186
Interquartile range (IQR)73.5

Descriptive statistics

Standard deviation51.452649
Coefficient of variation (CV)0.016562343
Kurtosis-1.0795329
Mean3106.6044
Median Absolute Deviation (MAD)37
Skewness-0.11958647
Sum282701
Variance2647.3751
MonotonicityNot monotonic
2024-05-11T15:42:11.748894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3093 4
 
2.1%
3041 3
 
1.6%
3157 3
 
1.6%
3020 3
 
1.6%
3174 3
 
1.6%
3128 3
 
1.6%
3076 3
 
1.6%
3139 3
 
1.6%
3126 3
 
1.6%
3180 3
 
1.6%
Other values (50) 60
31.1%
(Missing) 102
52.8%
ValueCountFrequency (%)
3011 1
 
0.5%
3014 1
 
0.5%
3020 3
1.6%
3022 1
 
0.5%
3025 1
 
0.5%
3034 1
 
0.5%
3035 1
 
0.5%
3037 1
 
0.5%
3040 1
 
0.5%
3041 3
1.6%
ValueCountFrequency (%)
3197 1
 
0.5%
3191 2
1.0%
3188 1
 
0.5%
3180 3
1.6%
3175 1
 
0.5%
3174 3
1.6%
3173 1
 
0.5%
3169 2
1.0%
3168 1
 
0.5%
3167 1
 
0.5%

사업장명
Text

Distinct192
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-05-11T15:42:12.204072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length6.9326425
Min length2

Characters and Unicode

Total characters1338
Distinct characters343
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique191 ?
Unique (%)99.0%

Sample

1st row숙경제과
2nd row창신식품
3rd row(주)쁘라떼후드
4th row이조병과
5th row톰스코리아
ValueCountFrequency (%)
주식회사 7
 
2.7%
커피 4
 
1.6%
주)신씨화로 3
 
1.2%
광화문점 3
 
1.2%
에스프레소 2
 
0.8%
미스터도넛 2
 
0.8%
카페 2
 
0.8%
제일식품 2
 
0.8%
로스팅 2
 
0.8%
뎀셀브즈 2
 
0.8%
Other values (228) 228
88.7%
2024-05-11T15:42:12.868668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
4.8%
주 50
 
3.7%
) 47
 
3.5%
( 47
 
3.5%
스 45
 
3.4%
식 34
 
2.5%
리 26
 
1.9%
이 24
 
1.8%
품 24
 
1.8%
피 23
 
1.7%
Other values (333) 954
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1111
83.0%
Space Separator 64
 
4.8%
Close Punctuation 47
 
3.5%
Open Punctuation 47
 
3.5%
Uppercase Letter 33
 
2.5%
Lowercase Letter 19
 
1.4%
Decimal Number 11
 
0.8%
Other Punctuation 5
 
0.4%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 50
 
4.5%
스 45
 
4.1%
식 34
 
3.1%
리 26
 
2.3%
이 24
 
2.2%
품 24
 
2.2%
피 23
 
2.1%
커 19
 
1.7%
아 18
 
1.6%
로 16
 
1.4%
Other values (292) 832
74.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
15.2%
F 4
12.1%
O 3
 
9.1%
U 2
 
6.1%
A 2
 
6.1%
N 2
 
6.1%
S 2
 
6.1%
G 2
 
6.1%
M 2
 
6.1%
P 1
 
3.0%
Other values (8) 8
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 5
26.3%
o 5
26.3%
f 2
 
10.5%
d 1
 
5.3%
r 1
 
5.3%
t 1
 
5.3%
n 1
 
5.3%
v 1
 
5.3%
a 1
 
5.3%
i 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 3
27.3%
2 2
18.2%
5 2
18.2%
3 2
18.2%
4 1
 
9.1%
9 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
& 2
40.0%
. 2
40.0%
, 1
20.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1112
83.1%
Common 174
 
13.0%
Latin 52
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 50
 
4.5%
스 45
 
4.0%
식 34
 
3.1%
리 26
 
2.3%
이 24
 
2.2%
품 24
 
2.2%
피 23
 
2.1%
커 19
 
1.7%
아 18
 
1.6%
로 16
 
1.4%
Other values (293) 833
74.9%
Latin
ValueCountFrequency (%)
C 5
 
9.6%
e 5
 
9.6%
o 5
 
9.6%
F 4
 
7.7%
O 3
 
5.8%
U 2
 
3.8%
A 2
 
3.8%
f 2
 
3.8%
N 2
 
3.8%
S 2
 
3.8%
Other values (18) 20
38.5%
Common
ValueCountFrequency (%)
64
36.8%
) 47
27.0%
( 47
27.0%
1 3
 
1.7%
& 2
 
1.1%
. 2
 
1.1%
2 2
 
1.1%
5 2
 
1.1%
3 2
 
1.1%
4 1
 
0.6%
Other values (2) 2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1111
83.0%
ASCII 226
 
16.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
28.3%
) 47
20.8%
( 47
20.8%
C 5
 
2.2%
e 5
 
2.2%
o 5
 
2.2%
F 4
 
1.8%
1 3
 
1.3%
O 3
 
1.3%
U 2
 
0.9%
Other values (30) 41
18.1%
Hangul
ValueCountFrequency (%)
주 50
 
4.5%
스 45
 
4.1%
식 34
 
3.1%
리 26
 
2.3%
이 24
 
2.2%
품 24
 
2.2%
피 23
 
2.1%
커 19
 
1.7%
아 18
 
1.6%
로 16
 
1.4%
Other values (292) 832
74.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

Distinct183
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1999-06-16 00:00:00
Maximum2024-04-30 14:15:59
2024-05-11T15:42:13.156336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:13.461819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
I
148 
U
45 

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 148
76.7%
U 45
 
23.3%

Length

2024-05-11T15:42:13.724090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:13.893162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 148
76.7%
u 45
 
23.3%

데이터갱신일자
Date

Distinct46
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:02:00
2024-05-11T15:42:14.053931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:42:14.230944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

업태구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
식품제조가공업
157 
기타 식품제조가공업
36 

Length

Max length10
Median length7
Mean length7.5595855
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 157
81.3%
기타 식품제조가공업 36
 
18.7%

Length

2024-05-11T15:42:14.454829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:14.632390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 193
84.3%
기타 36
 
15.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct170
Distinct (%)91.9%
Missing8
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean198791.87
Minimum196220.97
Maximum201946.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:14.803185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196220.97
5-th percentile196630.26
Q1197329.9
median198697.71
Q3200098.26
95-th percentile201359.49
Maximum201946.77
Range5725.7971
Interquartile range (IQR)2768.3592

Descriptive statistics

Standard deviation1591.7457
Coefficient of variation (CV)0.0080070962
Kurtosis-1.1558245
Mean198791.87
Median Absolute Deviation (MAD)1396.3024
Skewness0.23446131
Sum36776497
Variance2533654.2
MonotonicityNot monotonic
2024-05-11T15:42:15.502482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201168.350187013 4
 
2.1%
198150.300374121 3
 
1.6%
198690.658978281 3
 
1.6%
197437.066489123 2
 
1.0%
198261.536982652 2
 
1.0%
196925.848272668 2
 
1.0%
198101.593328721 2
 
1.0%
196986.931657005 2
 
1.0%
197478.53747014 2
 
1.0%
200902.807232242 2
 
1.0%
Other values (160) 161
83.4%
(Missing) 8
 
4.1%
ValueCountFrequency (%)
196220.971484333 1
0.5%
196267.469544277 1
0.5%
196318.153259189 1
0.5%
196467.975088253 1
0.5%
196482.293818835 1
0.5%
196484.939679671 1
0.5%
196551.235959785 1
0.5%
196559.568468364 1
0.5%
196591.371816919 1
0.5%
196623.363076751 1
0.5%
ValueCountFrequency (%)
201946.768574808 1
0.5%
201918.529659409 1
0.5%
201875.67290602 1
0.5%
201862.008296867 1
0.5%
201853.268380126 1
0.5%
201721.406524629 1
0.5%
201598.591516663 1
0.5%
201477.153255557 1
0.5%
201382.237182182 1
0.5%
201364.824499615 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct170
Distinct (%)91.9%
Missing8
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean452979.23
Minimum451754.85
Maximum456478.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:15.792112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451754.85
5-th percentile451951.03
Q1452259.33
median452655.4
Q3453350.95
95-th percentile455701.66
Maximum456478.44
Range4723.5909
Interquartile range (IQR)1091.6171

Descriptive statistics

Standard deviation1045.372
Coefficient of variation (CV)0.0023077702
Kurtosis2.144258
Mean452979.23
Median Absolute Deviation (MAD)489.80224
Skewness1.577633
Sum83801157
Variance1092802.5
MonotonicityNot monotonic
2024-05-11T15:42:16.046373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
453134.920223381 4
 
2.1%
452019.212642931 3
 
1.6%
452665.844737685 3
 
1.6%
452768.364990344 2
 
1.0%
451951.026373194 2
 
1.0%
454483.196631026 2
 
1.0%
452496.362099822 2
 
1.0%
456038.650926234 2
 
1.0%
452259.334813912 2
 
1.0%
452137.584346747 2
 
1.0%
Other values (160) 161
83.4%
(Missing) 8
 
4.1%
ValueCountFrequency (%)
451754.845934195 1
0.5%
451768.310660153 1
0.5%
451784.633626517 1
0.5%
451813.489945391 1
0.5%
451814.424196043 1
0.5%
451860.352943313 1
0.5%
451880.352199907 1
0.5%
451895.357292033 1
0.5%
451897.834324531 1
0.5%
451951.026373194 2
1.0%
ValueCountFrequency (%)
456478.436790904 1
0.5%
456142.715416274 1
0.5%
456048.716300069 1
0.5%
456038.650926234 2
1.0%
456027.024165155 1
0.5%
456018.751573648 1
0.5%
455976.172515929 1
0.5%
455768.143392833 1
0.5%
455741.684403427 1
0.5%
455541.583046049 1
0.5%

위생업태명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
식품제조가공업
152 
기타 식품제조가공업
25 
<NA>
16 

Length

Max length10
Median length7
Mean length7.1398964
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조가공업 152
78.8%
기타 식품제조가공업 25
 
13.0%
<NA> 16
 
8.3%

Length

2024-05-11T15:42:16.267251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:16.441544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 177
81.2%
기타 25
 
11.5%
na 16
 
7.3%

남성종사자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
157 
0
26 
1
 
7
2
 
3

Length

Max length4
Median length4
Mean length3.4404145
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 157
81.3%
0 26
 
13.5%
1 7
 
3.6%
2 3
 
1.6%

Length

2024-05-11T15:42:16.624049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:16.800959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
81.3%
0 26
 
13.5%
1 7
 
3.6%
2 3
 
1.6%

여성종사자수
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
157 
0
27 
1
 
6
2
 
2
3
 
1

Length

Max length4
Median length4
Mean length3.4404145
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row2
2nd row1
3rd row2
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 157
81.3%
0 27
 
14.0%
1 6
 
3.1%
2 2
 
1.0%
3 1
 
0.5%

Length

2024-05-11T15:42:17.005388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:17.214636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 157
81.3%
0 27
 
14.0%
1 6
 
3.1%
2 2
 
1.0%
3 1
 
0.5%

영업장주변구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
156 
기타
33 
주택가주변
 
4

Length

Max length5
Median length4
Mean length3.6787565
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 156
80.8%
기타 33
 
17.1%
주택가주변 4
 
2.1%

Length

2024-05-11T15:42:17.407792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:17.587012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 156
80.8%
기타 33
 
17.1%
주택가주변 4
 
2.1%

등급구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
156 
기타
29 
자율
 
8

Length

Max length4
Median length4
Mean length3.6165803
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 156
80.8%
기타 29
 
15.0%
자율 8
 
4.1%

Length

2024-05-11T15:42:17.832129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:18.052845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 156
80.8%
기타 29
 
15.0%
자율 8
 
4.1%

급수시설구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
112 
상수도전용
81 

Length

Max length5
Median length4
Mean length4.4196891
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 112
58.0%
상수도전용 81
42.0%

Length

2024-05-11T15:42:18.278990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:18.470038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 112
58.0%
상수도전용 81
42.0%

총인원
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
184 
0
 
9

Length

Max length4
Median length4
Mean length3.8601036
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> 184
95.3%
0 9
 
4.7%

Length

2024-05-11T15:42:18.685474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:18.863638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 184
95.3%
0 9
 
4.7%

본사종업원수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)6.2%
Missing97
Missing (%)50.3%
Infinite0
Infinite (%)0.0%
Mean0.3125
Minimum0
Maximum5
Zeros85
Zeros (%)44.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:19.023966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.96586476
Coefficient of variation (CV)3.0907672
Kurtosis10.233411
Mean0.3125
Median Absolute Deviation (MAD)0
Skewness3.2688621
Sum30
Variance0.93289474
MonotonicityNot monotonic
2024-05-11T15:42:19.223142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 85
44.0%
2 3
 
1.6%
3 3
 
1.6%
4 2
 
1.0%
1 2
 
1.0%
5 1
 
0.5%
(Missing) 97
50.3%
ValueCountFrequency (%)
0 85
44.0%
1 2
 
1.0%
2 3
 
1.6%
3 3
 
1.6%
4 2
 
1.0%
5 1
 
0.5%
ValueCountFrequency (%)
5 1
 
0.5%
4 2
 
1.0%
3 3
 
1.6%
2 3
 
1.6%
1 2
 
1.0%
0 85
44.0%

공장사무직종업원수
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
106 
0
86 
1
 
1

Length

Max length4
Median length4
Mean length2.6476684
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
54.9%
0 86
44.6%
1 1
 
0.5%

Length

2024-05-11T15:42:19.442284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:19.650797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
54.9%
0 86
44.6%
1 1
 
0.5%

공장판매직종업원수
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
106 
0
86 
1
 
1

Length

Max length4
Median length4
Mean length2.6476684
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 106
54.9%
0 86
44.6%
1 1
 
0.5%

Length

2024-05-11T15:42:19.830418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:20.006662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 106
54.9%
0 86
44.6%
1 1
 
0.5%

공장생산직종업원수
Categorical

Distinct6
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
102 
0
80 
1
 
5
2
 
3
3
 
2

Length

Max length4
Median length4
Mean length2.5854922
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 102
52.8%
0 80
41.5%
1 5
 
2.6%
2 3
 
1.6%
3 2
 
1.0%
5 1
 
0.5%

Length

2024-05-11T15:42:20.198521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:20.416755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 102
52.8%
0 80
41.5%
1 5
 
2.6%
2 3
 
1.6%
3 2
 
1.0%
5 1
 
0.5%

건물소유구분명
Categorical

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
83 
임대
70 
자가
40 

Length

Max length4
Median length2
Mean length2.8601036
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> 83
43.0%
임대 70
36.3%
자가 40
20.7%

Length

2024-05-11T15:42:20.630124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:20.795133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 83
43.0%
임대 70
36.3%
자가 40
20.7%

보증액
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
164 
0
27 
90
 
1
45000000
 
1

Length

Max length8
Median length4
Mean length3.5906736
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 164
85.0%
0 27
 
14.0%
90 1
 
0.5%
45000000 1
 
0.5%

Length

2024-05-11T15:42:20.965084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:21.175584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 164
85.0%
0 27
 
14.0%
90 1
 
0.5%
45000000 1
 
0.5%

월세액
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
<NA>
164 
0
27 
18
 
1
4000000
 
1

Length

Max length7
Median length4
Mean length3.5854922
Min length1

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 164
85.0%
0 27
 
14.0%
18 1
 
0.5%
4000000 1
 
0.5%

Length

2024-05-11T15:42:21.406364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:42:21.646375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 164
85.0%
0 27
 
14.0%
18 1
 
0.5%
4000000 1
 
0.5%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing16
Missing (%)8.3%
Memory size518.0 B
False
177 
(Missing)
 
16
ValueCountFrequency (%)
False 177
91.7%
(Missing) 16
 
8.3%
2024-05-11T15:42:21.853325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)4.5%
Missing16
Missing (%)8.3%
Infinite0
Infinite (%)0.0%
Mean0.49853107
Minimum0
Maximum46.48
Zeros169
Zeros (%)87.6%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-05-11T15:42:21.997689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum46.48
Range46.48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.7093996
Coefficient of variation (CV)7.4406588
Kurtosis136.32714
Mean0.49853107
Median Absolute Deviation (MAD)0
Skewness11.183496
Sum88.24
Variance13.759646
MonotonicityNot monotonic
2024-05-11T15:42:22.183506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 169
87.6%
3.3 2
 
1.0%
46.48 1
 
0.5%
9.6 1
 
0.5%
3.0 1
 
0.5%
5.3 1
 
0.5%
7.0 1
 
0.5%
10.26 1
 
0.5%
(Missing) 16
 
8.3%
ValueCountFrequency (%)
0.0 169
87.6%
3.0 1
 
0.5%
3.3 2
 
1.0%
5.3 1
 
0.5%
7.0 1
 
0.5%
9.6 1
 
0.5%
10.26 1
 
0.5%
46.48 1
 
0.5%
ValueCountFrequency (%)
46.48 1
 
0.5%
10.26 1
 
0.5%
9.6 1
 
0.5%
7.0 1
 
0.5%
5.3 1
 
0.5%
3.3 2
 
1.0%
3.0 1
 
0.5%
0.0 169
87.6%

전통업소지정번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing193
Missing (%)100.0%
Memory size1.8 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
030000003000000-106-1969-0000419690818<NA>3폐업2폐업19950920<NA><NA><NA>0200000000<NA>110043서울특별시 종로구 통인동 137-2번지<NA><NA>숙경제과2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업197331.642551453032.830691식품제조가공업12기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
130000003000000-106-1975-0000119751223<NA>3폐업2폐업20120809<NA><NA><NA>0207459936<NA>110842서울특별시 종로구 창신동 447-2번지<NA><NA>창신식품2011-02-15 11:14:28I2018-08-31 23:59:59.0식품제조가공업200909.454784452070.38729식품제조가공업11기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
230000003000000-106-1985-0000219851016<NA>3폐업2폐업19941228<NA><NA><NA>0200000000<NA>110122서울특별시 종로구 종로2가 56-24번지<NA><NA>(주)쁘라떼후드2001-11-20 00:00:00I2018-08-31 23:59:59.0식품제조가공업198870.651316451952.481831식품제조가공업12기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
330000003000000-106-1986-0000319860922<NA>3폐업2폐업20010808<NA><NA><NA>02 1001000<NA>110290서울특별시 종로구 인사동 137-2번지<NA><NA>이조병과2001-08-08 00:00:00I2018-08-31 23:59:59.0식품제조가공업198763.56076452151.87525식품제조가공업11기타자율상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
430000003000000-106-1995-0000519951229<NA>3폐업2폐업20080324<NA><NA><NA>02 3958686<NA>110847서울특별시 종로구 평창동 245번지<NA><NA>톰스코리아2006-05-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업197039.223135455768.143393식품제조가공업11주택가주변자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
530000003000000-106-1995-0000919951017<NA>3폐업2폐업19970227<NA><NA><NA>02 0<NA>110122서울특별시 종로구 종로2가 40-0번지<NA><NA>(주)전원도시락1999-08-04 00:00:00I2018-08-31 23:59:59.0식품제조가공업198966.805968452027.574754식품제조가공업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
630000003000000-106-1996-0015119960320<NA>3폐업2폐업20140304<NA><NA><NA>0222345530<NA>110826서울특별시 종로구 숭인동 243-0번지서울특별시 종로구 종로58가길 9 (숭인동)3114보령식품2014-03-04 17:04:31I2018-08-31 23:59:59.0식품제조가공업201477.153256452257.387137식품제조가공업23기타자율상수도전용<NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
730000003000000-106-1996-0015219960320<NA>3폐업2폐업20090629<NA><NA><NA>0222528116<NA>110829서울특별시 종로구 숭인동 1429번지<NA><NA>여주식품2002-03-25 00:00:00I2018-08-31 23:59:59.0식품제조가공업201918.529659452260.721221식품제조가공업<NA><NA><NA><NA><NA><NA>0000<NA><NA><NA>N0.0<NA><NA><NA>
830000003000000-106-1997-0000819970724<NA>3폐업2폐업19981204<NA><NA><NA>02 7341678<NA>110340서울특별시 종로구 익선동 58-2번지<NA><NA>(주)이조식품2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업199068.636617452579.070011식품제조가공업<NA><NA>기타기타<NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
930000003000000-106-1997-0001019970108<NA>3폐업2폐업19970509<NA><NA><NA>02 2383893<NA>110825서울특별시 종로구 숭인동 201-20번지<NA><NA>진강2001-09-29 00:00:00I2018-08-31 23:59:59.0식품제조가공업201853.26838452392.927257식품제조가공업2<NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총인원본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지
18330000003000000-106-2019-0000220190122<NA>3폐업2폐업20210906<NA><NA><NA><NA>82.18110816서울특별시 종로구 부암동 44-2서울특별시 종로구 백석동길 61, 지층 (부암동)3020누오바 이탈리아2021-09-06 16:27:28U2021-09-08 02:40:00.0기타 식품제조가공업197096.455448454652.302244기타 식품제조가공업00<NA><NA><NA>00000<NA>00N0.0<NA><NA><NA>
18430000003000000-106-2019-0000320190226<NA>3폐업2폐업20191223<NA><NA><NA><NA>27.78110034서울특별시 종로구 창성동 17-1번지 온지음서울특별시 종로구 효자로 49, 온지음 4층 (창성동)3043주식회사 다보중앙(온지음)2019-12-23 17:08:18U2019-12-25 02:40:00.0기타 식품제조가공업197579.120246453134.579956기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA>
18530000003000000-106-2019-0000420190415<NA>3폐업2폐업20200227<NA><NA><NA><NA>80.26110850서울특별시 종로구 효제동 197-2번지 승진빌딩서울특별시 종로구 종로35가길 7-6, 승진빌딩 3층 (효제동)3126현대내츄럴타운2020-02-27 12:03:56U2020-02-29 02:40:00.0기타 식품제조가공업200321.078613452208.138934기타 식품제조가공업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N10.26<NA><NA><NA>
18630000003000000-106-2019-0000520190711<NA>3폐업2폐업20211022<NA><NA><NA><NA>22.7110873서울특별시 종로구 내수동 73 경희궁의 아침 4단지서울특별시 종로구 새문안로3길 23, 경희궁의 아침 4단지 B138, 139호 (내수동)3174(주)윗상2021-10-22 17:40:49U2021-10-24 02:40:00.0기타 식품제조가공업197478.53747452259.334814기타 식품제조가공업00<NA><NA>상수도전용00000임대00N0.0<NA><NA><NA>
18730000003000000-106-2021-0000120210121<NA>3폐업2폐업20220621<NA><NA><NA>02 730 6789499.62110054서울특별시 종로구 사직동 9 광화문 풍림스페이스본 301동 B208호서울특별시 종로구 사직로8길 4, 301동 지하2층 B208호 (사직동, 광화문 풍림스페이스본)3168(주)제이현푸드시스템2022-06-21 10:49:55U2021-12-05 22:03:00.0기타 식품제조가공업197181.393302452458.826652<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18830000003000000-106-2021-0000220210820<NA>3폐업2폐업20220728<NA><NA><NA>02 733 777147.03110816서울특별시 종로구 부암동 148-24 1층서울특별시 종로구 자하문로 254, 1층 (부암동)3020프레시럭2022-07-28 13:42:37U2021-12-06 21:00:00.0기타 식품제조가공업196748.13425454960.560461<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18930000003000000-106-2021-0000320211104<NA>3폐업2폐업20221130<NA><NA><NA>02 568 751021.5110410서울특별시 종로구 인의동 101-1 재향군인회관 2층서울특별시 종로구 창경궁로 119, 재향군인회관 2층 (인의동)3137예풍2022-11-30 14:38:45U2021-11-02 00:02:00.0기타 식품제조가공업199695.444372452315.032343<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19030000003000000-106-2022-0000120220810<NA>1영업/정상1영업<NA><NA><NA><NA><NA>66.38110530서울특별시 종로구 혜화동 78-3서울특별시 종로구 혜화로2길 10, 1층 (혜화동)3076(재)아름다운커피2022-08-10 10:15:54I2021-12-07 23:03:00.0기타 식품제조가공업200012.738692453800.300365<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19130000003000000-106-2023-000012023-02-09<NA>1영업/정상1영업<NA><NA><NA><NA><NA>41.35110-844서울특별시 종로구 충신동 53-6서울특별시 종로구 율곡로19길 5, 1층 (충신동)3100보통의 커피 로스팅 랩2023-02-09 15:50:36I2022-12-01 23:01:00.0기타 식품제조가공업200395.411228452625.607617<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19230000003000000-106-2023-000022023-04-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA>8.3110-102서울특별시 종로구 평동 233 경희궁자이 3단지 3120호서울특별시 종로구 경교장길 35, 3120호 (평동, 경희궁자이 3단지)3180합심2023-04-10 15:42:09I2022-12-03 23:02:00.0기타 식품제조가공업196931.854196451813.489945<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>