Overview

Dataset statistics

Number of variables30
Number of observations87
Missing cells1035
Missing cells (%)39.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory259.5 B

Variable types

Categorical8
Numeric6
Unsupported9
Text5
DateTime2

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),업소구분명,소재지,지정일자,신청일자,항목값1
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-19462/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 has constant value ""Constant
영업상태명 has constant value ""Constant
상세영업상태코드 has constant value ""Constant
상세영업상태명 has constant value ""Constant
데이터갱신구분 has constant value ""Constant
데이터갱신일자 has constant value ""Constant
업소구분명 has constant value ""Constant
항목값1 has constant value ""Constant
인허가취소일자 has 87 (100.0%) missing valuesMissing
폐업일자 has 87 (100.0%) missing valuesMissing
휴업시작일자 has 87 (100.0%) missing valuesMissing
휴업종료일자 has 87 (100.0%) missing valuesMissing
재개업일자 has 87 (100.0%) missing valuesMissing
전화번호 has 7 (8.0%) missing valuesMissing
소재지면적 has 87 (100.0%) missing valuesMissing
소재지우편번호 has 3 (3.4%) missing valuesMissing
도로명주소 has 82 (94.3%) missing valuesMissing
도로명우편번호 has 87 (100.0%) missing valuesMissing
업태구분명 has 87 (100.0%) missing valuesMissing
좌표정보(X) has 80 (92.0%) missing valuesMissing
좌표정보(Y) has 80 (92.0%) missing valuesMissing
지정일자 has 87 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐업일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
도로명우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
지정일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 10:05:24.356077
Analysis finished2024-04-06 10:05:25.097669
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
3100000
87 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3100000
2nd row3100000
3rd row3100000
4th row3100000
5th row3100000

Common Values

ValueCountFrequency (%)
3100000 87
100.0%

Length

2024-04-06T19:05:25.198764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:25.359284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3100000 87
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct87
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1000001 × 1017
Minimum3.1000001 × 1017
Maximum3.1000001 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:25.525826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1000001 × 1017
5-th percentile3.1000001 × 1017
Q13.1000001 × 1017
median3.1000001 × 1017
Q33.1000001 × 1017
95-th percentile3.1000001 × 1017
Maximum3.1000001 × 1017
Range86
Interquartile range (IQR)64

Descriptive statistics

Standard deviation39.039634
Coefficient of variation (CV)1.259343 × 10-16
Kurtosis-0.22584034
Mean3.1000001 × 1017
Median Absolute Deviation (MAD)0
Skewness-1.6779328
Sum8.5232572 × 1018
Variance1524.093
MonotonicityStrictly increasing
2024-04-06T19:05:25.878303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310000014200000001 1
 
1.1%
310000014200000002 1
 
1.1%
310000014200000065 1
 
1.1%
310000014200000064 1
 
1.1%
310000014200000063 1
 
1.1%
310000014200000062 1
 
1.1%
310000014200000061 1
 
1.1%
310000014200000060 1
 
1.1%
310000014200000059 1
 
1.1%
310000014200000058 1
 
1.1%
Other values (77) 77
88.5%
ValueCountFrequency (%)
310000014200000001 1
1.1%
310000014200000002 1
1.1%
310000014200000003 1
1.1%
310000014200000004 1
1.1%
310000014200000005 1
1.1%
310000014200000006 1
1.1%
310000014200000007 1
1.1%
310000014200000008 1
1.1%
310000014200000009 1
1.1%
310000014200000010 1
1.1%
ValueCountFrequency (%)
310000014200000087 1
1.1%
310000014200000086 1
1.1%
310000014200000085 1
1.1%
310000014200000084 1
1.1%
310000014200000083 1
1.1%
310000014200000082 1
1.1%
310000014200000081 1
1.1%
310000014200000080 1
1.1%
310000014200000079 1
1.1%
310000014200000078 1
1.1%

인허가일자
Real number (ℝ)

Distinct43
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19993904
Minimum19980925
Maximum20000905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:26.137460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980925
5-th percentile19981231
Q119990115
median19991231
Q320000111
95-th percentile20000722
Maximum20000905
Range19980
Interquartile range (IQR)9996

Descriptive statistics

Standard deviation6372.0348
Coefficient of variation (CV)0.00031869888
Kurtosis-0.80357108
Mean19993904
Median Absolute Deviation (MAD)8870
Skewness-0.46340504
Sum1.7394696 × 109
Variance40602827
MonotonicityNot monotonic
2024-04-06T19:05:26.502616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
20000101 13
 
14.9%
19981231 8
 
9.2%
20000201 6
 
6.9%
19991231 5
 
5.7%
19990111 5
 
5.7%
20000905 4
 
4.6%
19990101 4
 
4.6%
20000321 2
 
2.3%
19990120 2
 
2.3%
19990115 2
 
2.3%
Other values (33) 36
41.4%
ValueCountFrequency (%)
19980925 1
 
1.1%
19981231 8
9.2%
19990101 4
4.6%
19990106 1
 
1.1%
19990107 1
 
1.1%
19990111 5
5.7%
19990113 1
 
1.1%
19990115 2
 
2.3%
19990116 1
 
1.1%
19990120 2
 
2.3%
ValueCountFrequency (%)
20000905 4
4.6%
20000811 1
 
1.1%
20000513 1
 
1.1%
20000321 2
 
2.3%
20000311 1
 
1.1%
20000309 1
 
1.1%
20000201 6
6.9%
20000127 1
 
1.1%
20000124 1
 
1.1%
20000122 1
 
1.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
1
87 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 87
100.0%

Length

2024-04-06T19:05:26.742757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:26.900402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 87
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
영업/정상
87 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 87
100.0%

Length

2024-04-06T19:05:27.104918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:27.259924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 87
100.0%

상세영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
11
87 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 87
100.0%

Length

2024-04-06T19:05:27.519115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:27.690752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 87
100.0%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
영업
87 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 87
100.0%

Length

2024-04-06T19:05:27.851306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:28.009873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 87
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

전화번호
Text

MISSING 

Distinct79
Distinct (%)98.8%
Missing7
Missing (%)8.0%
Memory size828.0 B
2024-04-06T19:05:28.440292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.6625
Min length10

Characters and Unicode

Total characters853
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

Unique78 ?
Unique (%)97.5%

Sample

1st row02 915 4100
2nd row02 974 9922
3rd row02 915 8062
4th row02 917 0777
5th row02 979 6719
ValueCountFrequency (%)
02 46
 
22.7%
02977 8
 
3.9%
974 4
 
2.0%
02972 4
 
2.0%
917 4
 
2.0%
977 4
 
2.0%
02975 4
 
2.0%
02974 3
 
1.5%
949 3
 
1.5%
02930 3
 
1.5%
Other values (106) 120
59.1%
2024-04-06T19:05:29.125263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
15.5%
9 128
15.0%
2 116
13.6%
0 113
13.2%
7 88
10.3%
1 61
7.2%
4 48
 
5.6%
3 47
 
5.5%
5 44
 
5.2%
8 39
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 721
84.5%
Space Separator 132
 
15.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 128
17.8%
2 116
16.1%
0 113
15.7%
7 88
12.2%
1 61
8.5%
4 48
 
6.7%
3 47
 
6.5%
5 44
 
6.1%
8 39
 
5.4%
6 37
 
5.1%
Space Separator
ValueCountFrequency (%)
132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 853
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
132
15.5%
9 128
15.0%
2 116
13.6%
0 113
13.2%
7 88
10.3%
1 61
7.2%
4 48
 
5.6%
3 47
 
5.5%
5 44
 
5.2%
8 39
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 853
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
15.5%
9 128
15.0%
2 116
13.6%
0 113
13.2%
7 88
10.3%
1 61
7.2%
4 48
 
5.6%
3 47
 
5.5%
5 44
 
5.2%
8 39
 
4.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)8.3%
Missing3
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean139177.73
Minimum139051
Maximum139243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:29.375957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139051
5-th percentile139051
Q1139054
median139241
Q3139242
95-th percentile139242.85
Maximum139243
Range192
Interquartile range (IQR)188

Descriptive statistics

Standard deviation86.908808
Coefficient of variation (CV)0.00062444481
Kurtosis-1.4395637
Mean139177.73
Median Absolute Deviation (MAD)2
Skewness-0.74732524
Sum11690929
Variance7553.141
MonotonicityNot monotonic
2024-04-06T19:05:29.761773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
139242 22
25.3%
139054 17
19.5%
139241 17
19.5%
139051 10
11.5%
139229 9
10.3%
139243 5
 
5.7%
139201 4
 
4.6%
(Missing) 3
 
3.4%
ValueCountFrequency (%)
139051 10
11.5%
139054 17
19.5%
139201 4
 
4.6%
139229 9
10.3%
139241 17
19.5%
139242 22
25.3%
139243 5
 
5.7%
ValueCountFrequency (%)
139243 5
 
5.7%
139242 22
25.3%
139241 17
19.5%
139229 9
10.3%
139201 4
 
4.6%
139054 17
19.5%
139051 10
11.5%

지번주소
Text

Distinct84
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T19:05:30.298967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length24.402299
Min length19

Characters and Unicode

Total characters2123
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)93.1%

Sample

1st row서울특별시 노원구 월계동 436번지
2nd row서울특별시 노원구 월계동 20번지
3rd row서울특별시 노원구 월계동 435-9번지
4th row서울특별시 노원구 월계동 59-3번지
5th row서울특별시 노원구 월계동 31-1 번지
ValueCountFrequency (%)
서울특별시 87
20.5%
노원구 87
20.5%
번지 77
18.1%
공릉동 44
10.4%
월계동 30
 
7.1%
중계동 9
 
2.1%
상계동 4
 
0.9%
435-2 2
 
0.5%
383-12 2
 
0.5%
208-5 2
 
0.5%
Other values (81) 81
19.1%
2024-04-06T19:05:31.018579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
525
24.7%
서 87
 
4.1%
특 87
 
4.1%
별 87
 
4.1%
시 87
 
4.1%
노 87
 
4.1%
원 87
 
4.1%
구 87
 
4.1%
지 87
 
4.1%
동 87
 
4.1%
Other values (19) 815
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1131
53.3%
Space Separator 525
24.7%
Decimal Number 387
 
18.2%
Dash Punctuation 80
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 87
 
7.7%
특 87
 
7.7%
별 87
 
7.7%
시 87
 
7.7%
노 87
 
7.7%
원 87
 
7.7%
구 87
 
7.7%
지 87
 
7.7%
동 87
 
7.7%
번 87
 
7.7%
Other values (7) 261
23.1%
Decimal Number
ValueCountFrequency (%)
1 67
17.3%
2 61
15.8%
3 53
13.7%
4 40
10.3%
5 38
9.8%
8 28
7.2%
0 25
 
6.5%
7 25
 
6.5%
9 25
 
6.5%
6 25
 
6.5%
Space Separator
ValueCountFrequency (%)
525
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1131
53.3%
Common 992
46.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 87
 
7.7%
특 87
 
7.7%
별 87
 
7.7%
시 87
 
7.7%
노 87
 
7.7%
원 87
 
7.7%
구 87
 
7.7%
지 87
 
7.7%
동 87
 
7.7%
번 87
 
7.7%
Other values (7) 261
23.1%
Common
ValueCountFrequency (%)
525
52.9%
- 80
 
8.1%
1 67
 
6.8%
2 61
 
6.1%
3 53
 
5.3%
4 40
 
4.0%
5 38
 
3.8%
8 28
 
2.8%
0 25
 
2.5%
7 25
 
2.5%
Other values (2) 50
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1131
53.3%
ASCII 992
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
525
52.9%
- 80
 
8.1%
1 67
 
6.8%
2 61
 
6.1%
3 53
 
5.3%
4 40
 
4.0%
5 38
 
3.8%
8 28
 
2.8%
0 25
 
2.5%
7 25
 
2.5%
Other values (2) 50
 
5.0%
Hangul
ValueCountFrequency (%)
서 87
 
7.7%
특 87
 
7.7%
별 87
 
7.7%
시 87
 
7.7%
노 87
 
7.7%
원 87
 
7.7%
구 87
 
7.7%
지 87
 
7.7%
동 87
 
7.7%
번 87
 
7.7%
Other values (7) 261
23.1%

도로명주소
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing82
Missing (%)94.3%
Memory size828.0 B
2024-04-06T19:05:31.283237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length24.2
Min length22

Characters and Unicode

Total characters121
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row서울특별시 노원구 광운로2나길 30 (월계동)
2nd row서울특별시 노원구 석계로 9 (월계동)
3rd row서울특별시 노원구 광운로 46 (월계동)
4th row서울특별시 노원구 광운로 39 (월계동)
5th row서울특별시 노원구 공릉로34길 109 (공릉동)
ValueCountFrequency (%)
서울특별시 5
20.0%
노원구 5
20.0%
월계동 4
16.0%
광운로 2
 
8.0%
광운로2나길 1
 
4.0%
30 1
 
4.0%
석계로 1
 
4.0%
9 1
 
4.0%
46 1
 
4.0%
39 1
 
4.0%
Other values (3) 3
12.0%
2024-04-06T19:05:31.785041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
20.7%
서 5
 
4.1%
구 5
 
4.1%
동 5
 
4.1%
계 5
 
4.1%
( 5
 
4.1%
울 5
 
4.1%
로 5
 
4.1%
원 5
 
4.1%
노 5
 
4.1%
Other values (19) 51
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
60.3%
Space Separator 25
 
20.7%
Decimal Number 13
 
10.7%
Open Punctuation 5
 
4.1%
Close Punctuation 5
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 5
 
6.8%
구 5
 
6.8%
동 5
 
6.8%
계 5
 
6.8%
울 5
 
6.8%
로 5
 
6.8%
원 5
 
6.8%
노 5
 
6.8%
시 5
 
6.8%
별 5
 
6.8%
Other values (9) 23
31.5%
Decimal Number
ValueCountFrequency (%)
9 3
23.1%
3 3
23.1%
4 2
15.4%
0 2
15.4%
6 1
 
7.7%
2 1
 
7.7%
1 1
 
7.7%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
60.3%
Common 48
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 5
 
6.8%
구 5
 
6.8%
동 5
 
6.8%
계 5
 
6.8%
울 5
 
6.8%
로 5
 
6.8%
원 5
 
6.8%
노 5
 
6.8%
시 5
 
6.8%
별 5
 
6.8%
Other values (9) 23
31.5%
Common
ValueCountFrequency (%)
25
52.1%
( 5
 
10.4%
) 5
 
10.4%
9 3
 
6.2%
3 3
 
6.2%
4 2
 
4.2%
0 2
 
4.2%
6 1
 
2.1%
2 1
 
2.1%
1 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
60.3%
ASCII 48
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
52.1%
( 5
 
10.4%
) 5
 
10.4%
9 3
 
6.2%
3 3
 
6.2%
4 2
 
4.2%
0 2
 
4.2%
6 1
 
2.1%
2 1
 
2.1%
1 1
 
2.1%
Hangul
ValueCountFrequency (%)
서 5
 
6.8%
구 5
 
6.8%
동 5
 
6.8%
계 5
 
6.8%
울 5
 
6.8%
로 5
 
6.8%
원 5
 
6.8%
노 5
 
6.8%
시 5
 
6.8%
별 5
 
6.8%
Other values (9) 23
31.5%

도로명우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

사업장명
Text

Distinct81
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T19:05:32.231575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.2988506
Min length4

Characters and Unicode

Total characters374
Distinct characters120
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)86.2%

Sample

1st row삼양마트
2nd row현대슈퍼
3rd row만물슈퍼
4th row동양마트
5th row월계슈퍼
ValueCountFrequency (%)
훼미리마트 2
 
2.3%
소망하이퍼 2
 
2.3%
청운슈퍼 2
 
2.3%
동명슈퍼 2
 
2.3%
현대슈퍼 2
 
2.3%
월계슈퍼 2
 
2.3%
드림마트 1
 
1.1%
엘지슈퍼렛 1
 
1.1%
동부양곡 1
 
1.1%
대아마트 1
 
1.1%
Other values (71) 71
81.6%
2024-04-06T19:05:32.964175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
퍼 50
 
13.4%
슈 46
 
12.3%
마 20
 
5.3%
트 15
 
4.0%
상 11
 
2.9%
회 10
 
2.7%
이 7
 
1.9%
일 6
 
1.6%
동 6
 
1.6%
양 5
 
1.3%
Other values (110) 198
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
99.5%
Decimal Number 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
퍼 50
 
13.4%
슈 46
 
12.4%
마 20
 
5.4%
트 15
 
4.0%
상 11
 
3.0%
회 10
 
2.7%
이 7
 
1.9%
일 6
 
1.6%
동 6
 
1.6%
양 5
 
1.3%
Other values (108) 196
52.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
99.5%
Common 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
퍼 50
 
13.4%
슈 46
 
12.4%
마 20
 
5.4%
트 15
 
4.0%
상 11
 
3.0%
회 10
 
2.7%
이 7
 
1.9%
일 6
 
1.6%
동 6
 
1.6%
양 5
 
1.3%
Other values (108) 196
52.7%
Common
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
99.5%
ASCII 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
퍼 50
 
13.4%
슈 46
 
12.4%
마 20
 
5.4%
트 15
 
4.0%
상 11
 
3.0%
회 10
 
2.7%
이 7
 
1.9%
일 6
 
1.6%
동 6
 
1.6%
양 5
 
1.3%
Other values (108) 196
52.7%
ASCII
ValueCountFrequency (%)
2 1
50.0%
4 1
50.0%

최종수정일자
Date

Distinct79
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size828.0 B
Minimum2007-06-30 10:13:37
Maximum2013-12-30 17:09:53
2024-04-06T19:05:33.752248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:05:34.006606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
I
87 

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 87
100.0%

Length

2024-04-06T19:05:34.248638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:34.558616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 87
100.0%

데이터갱신일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
Minimum2018-08-31 23:59:59
Maximum2018-08-31 23:59:59
2024-04-06T19:05:34.722120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T19:05:34.948603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing80
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean205782.34
Minimum205129.12
Maximum207074.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:35.161833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum205129.12
5-th percentile205133.25
Q1205204.29
median205339.51
Q3206262.1
95-th percentile207024.4
Maximum207074.99
Range1945.866
Interquartile range (IQR)1057.8166

Descriptive statistics

Standard deviation842.61884
Coefficient of variation (CV)0.0040947091
Kurtosis-0.91214262
Mean205782.34
Median Absolute Deviation (MAD)210.38799
Skewness1.0961856
Sum1440476.4
Variance710006.5
MonotonicityNot monotonic
2024-04-06T19:05:35.406588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
205339.508691698 1
 
1.1%
205617.846778226 1
 
1.1%
205265.683586801 1
 
1.1%
205129.120699118 1
 
1.1%
205142.8895517 1
 
1.1%
207074.98665308 1
 
1.1%
206906.359523849 1
 
1.1%
(Missing) 80
92.0%
ValueCountFrequency (%)
205129.120699118 1
1.1%
205142.8895517 1
1.1%
205265.683586801 1
1.1%
205339.508691698 1
1.1%
205617.846778226 1
1.1%
206906.359523849 1
1.1%
207074.98665308 1
1.1%
ValueCountFrequency (%)
207074.98665308 1
1.1%
206906.359523849 1
1.1%
205617.846778226 1
1.1%
205339.508691698 1
1.1%
205265.683586801 1
1.1%
205142.8895517 1
1.1%
205129.120699118 1
1.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing80
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean457636.51
Minimum457041.35
Maximum458148.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:35.585958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum457041.35
5-th percentile457103.22
Q1457443.15
median457700.42
Q3457839.57
95-th percentile458092.83
Maximum458148.39
Range1107.0358
Interquartile range (IQR)396.42254

Descriptive statistics

Standard deviation383.97694
Coefficient of variation (CV)0.00083904349
Kurtosis-0.49562627
Mean457636.51
Median Absolute Deviation (MAD)262.77698
Skewness-0.41180052
Sum3203455.6
Variance147438.29
MonotonicityNot monotonic
2024-04-06T19:05:35.789022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
457247.570869701 1
 
1.1%
457041.349875739 1
 
1.1%
457715.946602513 1
 
1.1%
457638.727453242 1
 
1.1%
457700.419829693 1
 
1.1%
458148.38566155 1
 
1.1%
457963.196810318 1
 
1.1%
(Missing) 80
92.0%
ValueCountFrequency (%)
457041.349875739 1
1.1%
457247.570869701 1
1.1%
457638.727453242 1
1.1%
457700.419829693 1
1.1%
457715.946602513 1
1.1%
457963.196810318 1
1.1%
458148.38566155 1
1.1%
ValueCountFrequency (%)
458148.38566155 1
1.1%
457963.196810318 1
1.1%
457715.946602513 1
1.1%
457700.419829693 1
1.1%
457638.727453242 1
1.1%
457247.570869701 1
1.1%
457041.349875739 1
1.1%

업소구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
지정
87 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 87
100.0%

Length

2024-04-06T19:05:36.006462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:36.172161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 87
100.0%

소재지
Text

Distinct84
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size828.0 B
2024-04-06T19:05:36.654528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length20.735632
Min length18

Characters and Unicode

Total characters1804
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)93.1%

Sample

1st row서울특별시 노원구 월계제1동 436번지 동신상가지하29
2nd row서울특별시 노원구 월계1동 20번지
3rd row서울특별시 노원구 월계동 435-9번지
4th row서울특별시 노원구 월계1동 59-3(선호1층 1호)
5th row서울특별시 노원구 월계1동 31-1
ValueCountFrequency (%)
노원구 87
24.8%
서울특별시 86
24.5%
공릉2동 22
 
6.3%
월계4동 18
 
5.1%
공릉1동 16
 
4.6%
월계1동 9
 
2.6%
중계본동 9
 
2.6%
공릉3동 6
 
1.7%
상계1동 4
 
1.1%
208-5 2
 
0.6%
Other values (90) 92
26.2%
2024-04-06T19:05:37.357984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
 
14.6%
1 101
 
5.6%
동 89
 
4.9%
서 87
 
4.8%
노 87
 
4.8%
원 87
 
4.8%
구 87
 
4.8%
시 87
 
4.8%
별 87
 
4.8%
특 87
 
4.8%
Other values (32) 741
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 987
54.7%
Decimal Number 471
26.1%
Space Separator 264
 
14.6%
Dash Punctuation 80
 
4.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 89
9.0%
서 87
8.8%
노 87
8.8%
원 87
8.8%
구 87
8.8%
시 87
8.8%
별 87
8.8%
특 87
8.8%
울 86
8.7%
공 44
 
4.5%
Other values (18) 159
16.1%
Decimal Number
ValueCountFrequency (%)
1 101
21.4%
2 84
17.8%
4 59
12.5%
3 59
12.5%
5 38
 
8.1%
8 27
 
5.7%
9 27
 
5.7%
0 26
 
5.5%
6 25
 
5.3%
7 25
 
5.3%
Space Separator
ValueCountFrequency (%)
264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 987
54.7%
Common 817
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 89
9.0%
서 87
8.8%
노 87
8.8%
원 87
8.8%
구 87
8.8%
시 87
8.8%
별 87
8.8%
특 87
8.8%
울 86
8.7%
공 44
 
4.5%
Other values (18) 159
16.1%
Common
ValueCountFrequency (%)
264
32.3%
1 101
 
12.4%
2 84
 
10.3%
- 80
 
9.8%
4 59
 
7.2%
3 59
 
7.2%
5 38
 
4.7%
8 27
 
3.3%
9 27
 
3.3%
0 26
 
3.2%
Other values (4) 52
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 987
54.7%
ASCII 817
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
32.3%
1 101
 
12.4%
2 84
 
10.3%
- 80
 
9.8%
4 59
 
7.2%
3 59
 
7.2%
5 38
 
4.7%
8 27
 
3.3%
9 27
 
3.3%
0 26
 
3.2%
Other values (4) 52
 
6.4%
Hangul
ValueCountFrequency (%)
동 89
9.0%
서 87
8.8%
노 87
8.8%
원 87
8.8%
구 87
8.8%
시 87
8.8%
별 87
8.8%
특 87
8.8%
울 86
8.7%
공 44
 
4.5%
Other values (18) 159
16.1%

지정일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing87
Missing (%)100.0%
Memory size915.0 B

신청일자
Real number (ℝ)

Distinct42
Distinct (%)48.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19993902
Minimum19980925
Maximum20000905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size915.0 B
2024-04-06T19:05:37.667294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980925
5-th percentile19981231
Q119990116
median19991231
Q320000111
95-th percentile20000722
Maximum20000905
Range19980
Interquartile range (IQR)9995.5

Descriptive statistics

Standard deviation6373.1562
Coefficient of variation (CV)0.000318755
Kurtosis-0.80571064
Mean19993902
Median Absolute Deviation (MAD)8870
Skewness-0.46234456
Sum1.7394694 × 109
Variance40617120
MonotonicityNot monotonic
2024-04-06T19:05:37.927932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
20000101 13
 
14.9%
19981231 8
 
9.2%
20000201 6
 
6.9%
19991231 5
 
5.7%
19990111 5
 
5.7%
19990101 4
 
4.6%
20000905 4
 
4.6%
20000321 2
 
2.3%
19990120 2
 
2.3%
19990122 2
 
2.3%
Other values (32) 36
41.4%
ValueCountFrequency (%)
19980925 1
 
1.1%
19981231 8
9.2%
19990101 4
4.6%
19990106 1
 
1.1%
19990107 1
 
1.1%
19990111 5
5.7%
19990113 1
 
1.1%
19990115 1
 
1.1%
19990116 2
 
2.3%
19990120 2
 
2.3%
ValueCountFrequency (%)
20000905 4
4.6%
20000811 1
 
1.1%
20000513 1
 
1.1%
20000321 2
 
2.3%
20000311 1
 
1.1%
20000309 1
 
1.1%
20000201 6
6.9%
20000127 1
 
1.1%
20000124 1
 
1.1%
20000122 1
 
1.1%

항목값1
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size828.0 B
관급봉투
87 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관급봉투 87
100.0%

Length

2024-04-06T19:05:38.136089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T19:05:38.326143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관급봉투 87
100.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
0310000031000001420000000120000201<NA>1영업/정상11영업<NA><NA><NA><NA>02 915 4100<NA>139051서울특별시 노원구 월계동 436번지서울특별시 노원구 광운로2나길 30 (월계동)<NA>삼양마트2007-06-30 10:13:37I2018-08-31 23:59:59.0<NA>205339.508692457247.57087지정서울특별시 노원구 월계제1동 436번지 동신상가지하29<NA>20000201관급봉투
1310000031000001420000000220000108<NA>1영업/정상11영업<NA><NA><NA><NA>02 974 9922<NA>139051서울특별시 노원구 월계동 20번지<NA><NA>현대슈퍼2007-06-30 10:13:37I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 20번지<NA>20000108관급봉투
2310000031000001420000000320000127<NA>1영업/정상11영업<NA><NA><NA><NA>02 915 8062<NA>139051서울특별시 노원구 월계동 435-9번지<NA><NA>만물슈퍼2013-12-30 16:13:10I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계동 435-9번지<NA>20000127관급봉투
3310000031000001420000000420000201<NA>1영업/정상11영업<NA><NA><NA><NA>02 917 0777<NA>139051서울특별시 노원구 월계동 59-3번지서울특별시 노원구 석계로 9 (월계동)<NA>동양마트2007-06-30 10:13:37I2018-08-31 23:59:59.0<NA>205617.846778457041.349876지정서울특별시 노원구 월계1동 59-3(선호1층 1호)<NA>20000201관급봉투
4310000031000001420000000520000124<NA>1영업/정상11영업<NA><NA><NA><NA>02 979 6719<NA>139051서울특별시 노원구 월계동 31-1 번지<NA><NA>월계슈퍼2007-06-30 10:13:37I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 31-1<NA>20000124관급봉투
5310000031000001420000000620000201<NA>1영업/정상11영업<NA><NA><NA><NA>02914 3168<NA>139051서울특별시 노원구 월계동 476-1 번지<NA><NA>유미슈퍼2013-12-30 16:13:59I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 476-1<NA>20000201관급봉투
6310000031000001420000000720000201<NA>1영업/정상11영업<NA><NA><NA><NA>02977 6969<NA>139051서울특별시 노원구 월계동 26-13 번지<NA><NA>보령슈퍼2013-12-30 16:14:21I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 26-13<NA>20000201관급봉투
7310000031000001420000000819990907<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>139051서울특별시 노원구 월계동 480-1 번지<NA><NA>희망슈퍼2013-12-30 16:14:58I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 480-1<NA>19990907관급봉투
8310000031000001420000000919991122<NA>1영업/정상11영업<NA><NA><NA><NA>02 941 0125<NA>139051서울특별시 노원구 월계동 55-2 번지<NA><NA>두일한우2013-12-30 16:15:19I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 55-2<NA>19991122관급봉투
9310000031000001420000001020000309<NA>1영업/정상11영업<NA><NA><NA><NA>02917 5254<NA>139051서울특별시 노원구 월계동 383-42 번지<NA><NA>광장슈퍼2013-12-30 16:15:43I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 월계1동 383-42<NA>20000309관급봉투
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업소구분명소재지지정일자신청일자항목값1
77310000031000001420000007820000101<NA>1영업/정상11영업<NA><NA><NA><NA>02930 8216<NA>139229서울특별시 노원구 중계동 22-19 번지<NA><NA>신양상회2013-12-30 17:04:33I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 22-19<NA>20000101관급봉투
78310000031000001420000007919990818<NA>1영업/정상11영업<NA><NA><NA><NA>02930 9588<NA>139229서울특별시 노원구 중계동 311-14 번지<NA><NA>노원우체국2013-12-30 17:05:14I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 311-14<NA>19990818관급봉투
79310000031000001420000008020000101<NA>1영업/정상11영업<NA><NA><NA><NA>02931 3868<NA>139229서울특별시 노원구 중계동 578-101 번지<NA><NA>금강슈퍼2007-06-30 10:13:37I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 579-101<NA>20000101관급봉투
80310000031000001420000008120000311<NA>1영업/정상11영업<NA><NA><NA><NA>02934 1933<NA>139229서울특별시 노원구 중계동 43-36 번지<NA><NA>제이마트2013-12-30 17:05:56I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 43-36<NA>20000311관급봉투
81310000031000001420000008220000905<NA>1영업/정상11영업<NA><NA><NA><NA>02951 0533<NA>139229서울특별시 노원구 중계동 27-26 번지<NA><NA>돌리상회2013-12-30 17:06:24I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 27-26<NA>20000905관급봉투
82310000031000001420000008320000101<NA>1영업/정상11영업<NA><NA><NA><NA>02 930 5382<NA>139229서울특별시 노원구 중계동 44-1 번지<NA><NA>현대종합슈퍼2013-12-30 17:06:52I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 중계본동 44-1<NA>20000101관급봉투
83310000031000001420000008419990106<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>139201서울특별시 노원구 상계동 1010번지<NA><NA>중앙상회2013-12-30 17:07:17I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 상계1동 1010<NA>19990106관급봉투
84310000031000001420000008520000513<NA>1영업/정상11영업<NA><NA><NA><NA>02 939 6252<NA>139201서울특별시 노원구 상계동 1121-25 번지<NA><NA>부부상회2013-12-30 17:07:39I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 상계1동 1121-25<NA>20000513관급봉투
85310000031000001420000008620000104<NA>1영업/정상11영업<NA><NA><NA><NA>02 938 7201<NA>139201서울특별시 노원구 상계동 1132-28 번지<NA><NA>광주상회2013-12-30 17:08:03I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 상계1동 1132-28<NA>20000104관급봉투
86310000031000001420000008719990120<NA>1영업/정상11영업<NA><NA><NA><NA>02 931 1742<NA>139201서울특별시 노원구 상계동 1048-10 번지<NA><NA>으뜸장터2013-12-30 17:08:24I2018-08-31 23:59:59.0<NA><NA><NA>지정서울특별시 노원구 상계1동 1048-10<NA>19990120관급봉투