Overview

Dataset statistics

Number of variables26
Number of observations54
Missing cells323
Missing cells (%)23.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.7 KiB
Average record size in memory222.4 B

Variable types

Categorical9
Numeric5
DateTime2
Unsupported4
Text6

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),점포구분명
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-18707/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 54 (100.0%) missing valuesMissing
폐업일자 has 37 (68.5%) missing valuesMissing
휴업시작일자 has 54 (100.0%) missing valuesMissing
휴업종료일자 has 54 (100.0%) missing valuesMissing
재개업일자 has 54 (100.0%) missing valuesMissing
전화번호 has 2 (3.7%) missing valuesMissing
소재지면적 has 1 (1.9%) missing valuesMissing
소재지우편번호 has 26 (48.1%) missing valuesMissing
지번주소 has 1 (1.9%) missing valuesMissing
도로명주소 has 18 (33.3%) missing valuesMissing
도로명우편번호 has 18 (33.3%) missing valuesMissing
좌표정보(X) has 2 (3.7%) missing valuesMissing
좌표정보(Y) has 2 (3.7%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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
소재지면적 has 14 (25.9%) zerosZeros

Reproduction

Analysis started2024-05-11 06:39:23.549377
Analysis finished2024-05-11 06:39:24.218047
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
3050000
54 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3050000 54
100.0%

Length

2024-05-11T15:39:24.336359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:24.537027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3050000 54
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0066569 × 1018
Minimum1.979305 × 1018
Maximum2.023305 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-05-11T15:39:24.752893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.979305 × 1018
5-th percentile2.000305 × 1018
Q12.000305 × 1018
median2.005305 × 1018
Q32.011305 × 1018
95-th percentile2.019705 × 1018
Maximum2.023305 × 1018
Range4.4000011 × 1016
Interquartile range (IQR)1.1000006 × 1016

Descriptive statistics

Standard deviation7.5938368 × 1015
Coefficient of variation (CV)0.0037843225
Kurtosis2.2165762
Mean2.0066569 × 1018
Median Absolute Deviation (MAD)5 × 1015
Skewness-0.28830273
Sum-2.3209939 × 1018
Variance5.7666357 × 1031
MonotonicityStrictly increasing
2024-05-11T15:39:25.038529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1979305010007500001 1
 
1.9%
2011305014007500006 1
 
1.9%
2007305010007500002 1
 
1.9%
2007305010007500003 1
 
1.9%
2009305010007500001 1
 
1.9%
2010305010007500001 1
 
1.9%
2010305010007500002 1
 
1.9%
2011305010007500001 1
 
1.9%
2011305014007500001 1
 
1.9%
2011305014007500002 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
1979305010007500001 1
1.9%
2000305008207500001 1
1.9%
2000305008207500002 1
1.9%
2000305008207500003 1
1.9%
2000305008207500004 1
1.9%
2000305008207500005 1
1.9%
2000305008207500007 1
1.9%
2000305008207500008 1
1.9%
2000305008207500009 1
1.9%
2000305008207500010 1
1.9%
ValueCountFrequency (%)
2023305021007500002 1
1.9%
2023305021007500001 1
1.9%
2022305014007500001 1
1.9%
2018305014007500001 1
1.9%
2016305014807500001 1
1.9%
2014305014007500003 1
1.9%
2014305014007500002 1
1.9%
2014305014007500001 1
1.9%
2013305014007500002 1
1.9%
2013305014007500001 1
1.9%

인허가일자
Date

Distinct47
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum1948-09-21 00:00:00
Maximum2023-03-14 00:00:00
2024-05-11T15:39:25.234185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:25.471856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

영업상태코드
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
34 
3
17 
4
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row3
2nd row1
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 34
63.0%
3 17
31.5%
4 2
 
3.7%
2 1
 
1.9%

Length

2024-05-11T15:39:25.710368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:25.887738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 34
63.0%
3 17
31.5%
4 2
 
3.7%
2 1
 
1.9%

영업상태명
Categorical

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
영업/정상
34 
폐업
17 
취소/말소/만료/정지/중지
 
2
휴업
 
1

Length

Max length14
Median length5
Mean length4.3333333
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 34
63.0%
폐업 17
31.5%
취소/말소/만료/정지/중지 2
 
3.7%
휴업 1
 
1.9%

Length

2024-05-11T15:39:26.101027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:26.294074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 34
63.0%
폐업 17
31.5%
취소/말소/만료/정지/중지 2
 
3.7%
휴업 1
 
1.9%

상세영업상태코드
Categorical

Distinct5
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
33 
3
17 
4
 
2
2
 
1
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)3.7%

Sample

1st row3
2nd row1
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 33
61.1%
3 17
31.5%
4 2
 
3.7%
2 1
 
1.9%
5 1
 
1.9%

Length

2024-05-11T15:39:26.541965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:26.798223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 33
61.1%
3 17
31.5%
4 2
 
3.7%
2 1
 
1.9%
5 1
 
1.9%

상세영업상태명
Categorical

Distinct5
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
정상영업
33 
폐업처리
17 
직권취소
 
2
휴업처리
 
1
영업개시전
 
1

Length

Max length5
Median length4
Mean length4.0185185
Min length4

Unique

Unique2 ?
Unique (%)3.7%

Sample

1st row폐업처리
2nd row정상영업
3rd row폐업처리
4th row정상영업
5th row정상영업

Common Values

ValueCountFrequency (%)
정상영업 33
61.1%
폐업처리 17
31.5%
직권취소 2
 
3.7%
휴업처리 1
 
1.9%
영업개시전 1
 
1.9%

Length

2024-05-11T15:39:27.011254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:27.348213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 33
61.1%
폐업처리 17
31.5%
직권취소 2
 
3.7%
휴업처리 1
 
1.9%
영업개시전 1
 
1.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)76.5%
Missing37
Missing (%)68.5%
Infinite0
Infinite (%)0.0%
Mean20088248
Minimum20010205
Maximum20211101
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-05-11T15:39:27.521814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010205
5-th percentile20010443
Q120050302
median20071128
Q320141231
95-th percentile20179202
Maximum20211101
Range200896
Interquartile range (IQR)90929

Descriptive statistics

Standard deviation59949.902
Coefficient of variation (CV)0.002984327
Kurtosis-0.73231883
Mean20088248
Median Absolute Deviation (MAD)40727
Skewness0.53806511
Sum3.4150022 × 108
Variance3.5939907 × 109
MonotonicityNot monotonic
2024-05-11T15:39:27.735497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
20080114 2
 
3.7%
20030401 2
 
3.7%
20050302 2
 
3.7%
20141231 2
 
3.7%
20171227 1
 
1.9%
20150724 1
 
1.9%
20010502 1
 
1.9%
20071128 1
 
1.9%
20060302 1
 
1.9%
20010205 1
 
1.9%
Other values (3) 3
 
5.6%
(Missing) 37
68.5%
ValueCountFrequency (%)
20010205 1
1.9%
20010502 1
1.9%
20030401 2
3.7%
20050302 2
3.7%
20060302 1
1.9%
20070102 1
1.9%
20071128 1
1.9%
20080114 2
3.7%
20140828 1
1.9%
20141231 2
3.7%
ValueCountFrequency (%)
20211101 1
1.9%
20171227 1
1.9%
20150724 1
1.9%
20141231 2
3.7%
20140828 1
1.9%
20080114 2
3.7%
20071128 1
1.9%
20070102 1
1.9%
20060302 1
1.9%
20050302 2
3.7%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

전화번호
Text

MISSING 

Distinct48
Distinct (%)92.3%
Missing2
Missing (%)3.7%
Memory size564.0 B
2024-05-11T15:39:28.072069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.480769
Min length7

Characters and Unicode

Total characters545
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)84.6%

Sample

1st row02-3707-2500
2nd row02 9263751
3rd row000209282608
4th row02-967-8721
5th row02-967-8169
ValueCountFrequency (%)
02 14
 
20.9%
0222151000 2
 
3.0%
9670094 2
 
3.0%
02-2006-2364 2
 
3.0%
9602222 2
 
3.0%
02-2242-5611 1
 
1.5%
02-721-8286 1
 
1.5%
9599981 1
 
1.5%
0222157200 1
 
1.5%
957-9090 1
 
1.5%
Other values (40) 40
59.7%
2024-05-11T15:39:28.686559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 118
21.7%
0 113
20.7%
6 45
 
8.3%
9 44
 
8.1%
7 35
 
6.4%
- 35
 
6.4%
1 34
 
6.2%
4 30
 
5.5%
3 29
 
5.3%
5 23
 
4.2%
Other values (2) 39
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 489
89.7%
Dash Punctuation 35
 
6.4%
Space Separator 21
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 118
24.1%
0 113
23.1%
6 45
 
9.2%
9 44
 
9.0%
7 35
 
7.2%
1 34
 
7.0%
4 30
 
6.1%
3 29
 
5.9%
5 23
 
4.7%
8 18
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 545
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 118
21.7%
0 113
20.7%
6 45
 
8.3%
9 44
 
8.1%
7 35
 
6.4%
- 35
 
6.4%
1 34
 
6.2%
4 30
 
5.5%
3 29
 
5.3%
5 23
 
4.2%
Other values (2) 39
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 545
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 118
21.7%
0 113
20.7%
6 45
 
8.3%
9 44
 
8.1%
7 35
 
6.4%
- 35
 
6.4%
1 34
 
6.2%
4 30
 
5.5%
3 29
 
5.3%
5 23
 
4.2%
Other values (2) 39
 
7.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct38
Distinct (%)71.7%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean4646.7698
Minimum0
Maximum40346.6
Zeros14
Zeros (%)25.9%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-05-11T15:39:28.927512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1478.96
Q37377.08
95-th percentile17236.48
Maximum40346.6
Range40346.6
Interquartile range (IQR)7377.08

Descriptive statistics

Standard deviation7444.9453
Coefficient of variation (CV)1.6021765
Kurtosis9.621049
Mean4646.7698
Median Absolute Deviation (MAD)1478.96
Skewness2.7188128
Sum246278.8
Variance55427210
MonotonicityNot monotonic
2024-05-11T15:39:29.172653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0.0 14
25.9%
8286.24 2
 
3.7%
307.23 2
 
3.7%
475.2 1
 
1.9%
5746.45 1
 
1.9%
2260.6 1
 
1.9%
1701.2 1
 
1.9%
769.5 1
 
1.9%
967.51 1
 
1.9%
410.9 1
 
1.9%
Other values (28) 28
51.9%
ValueCountFrequency (%)
0.0 14
25.9%
130.8 1
 
1.9%
141.0 1
 
1.9%
307.23 2
 
3.7%
410.9 1
 
1.9%
441.1 1
 
1.9%
475.2 1
 
1.9%
769.5 1
 
1.9%
809.0 1
 
1.9%
967.51 1
 
1.9%
ValueCountFrequency (%)
40346.6 1
1.9%
22487.6 1
1.9%
19780.15 1
1.9%
15540.7 1
1.9%
13762.35 1
1.9%
12979.73 1
1.9%
12010.0 1
1.9%
11167.69 1
1.9%
10910.6 1
1.9%
10431.44 1
1.9%

소재지우편번호
Text

MISSING 

Distinct22
Distinct (%)78.6%
Missing26
Missing (%)48.1%
Memory size564.0 B
2024-05-11T15:39:29.491949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1071429
Min length6

Characters and Unicode

Total characters171
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

Unique16 ?
Unique (%)57.1%

Sample

1st row130020
2nd row130860
3rd row130870
4th row130859
5th row130854
ValueCountFrequency (%)
130826 2
 
7.1%
130851 2
 
7.1%
130864 2
 
7.1%
130081 2
 
7.1%
130020 2
 
7.1%
130080 2
 
7.1%
130860 1
 
3.6%
130-817 1
 
3.6%
130854 1
 
3.6%
130840 1
 
3.6%
Other values (12) 12
42.9%
2024-05-11T15:39:30.056846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51
29.8%
1 42
24.6%
3 32
18.7%
8 18
 
10.5%
2 6
 
3.5%
5 6
 
3.5%
6 5
 
2.9%
4 4
 
2.3%
- 3
 
1.8%
7 3
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 168
98.2%
Dash Punctuation 3
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
30.4%
1 42
25.0%
3 32
19.0%
8 18
 
10.7%
2 6
 
3.6%
5 6
 
3.6%
6 5
 
3.0%
4 4
 
2.4%
7 3
 
1.8%
9 1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 171
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51
29.8%
1 42
24.6%
3 32
18.7%
8 18
 
10.5%
2 6
 
3.5%
5 6
 
3.5%
6 5
 
2.9%
4 4
 
2.3%
- 3
 
1.8%
7 3
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51
29.8%
1 42
24.6%
3 32
18.7%
8 18
 
10.5%
2 6
 
3.5%
5 6
 
3.5%
6 5
 
2.9%
4 4
 
2.3%
- 3
 
1.8%
7 3
 
1.8%

지번주소
Text

MISSING 

Distinct42
Distinct (%)79.2%
Missing1
Missing (%)1.9%
Memory size564.0 B
2024-05-11T15:39:30.512776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length24.584906
Min length7

Characters and Unicode

Total characters1303
Distinct characters86
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

Unique35 ?
Unique (%)66.0%

Sample

1st row서울특별시 동대문구 전농동 620번지 69호
2nd row서울특별시 동대문구 용두동 231-5
3rd row서울특별시 동대문구 제기동 135번지 90호
4th row서울특별시 동대문구 제기동 1019 경동시장
5th row서울특별시 동대문구 제기동 650호
ValueCountFrequency (%)
서울특별시 52
19.5%
동대문구 52
19.5%
장안동 11
 
4.1%
10호 8
 
3.0%
제기동 8
 
3.0%
이문동 7
 
2.6%
292번지 7
 
2.6%
1호 7
 
2.6%
용두동 6
 
2.3%
368번지 4
 
1.5%
Other values (75) 104
39.1%
2024-05-11T15:39:31.144235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
220
16.9%
동 108
 
8.3%
문 63
 
4.8%
1 56
 
4.3%
시 54
 
4.1%
서 52
 
4.0%
울 52
 
4.0%
구 52
 
4.0%
대 52
 
4.0%
별 52
 
4.0%
Other values (76) 542
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 837
64.2%
Decimal Number 234
 
18.0%
Space Separator 220
 
16.9%
Dash Punctuation 7
 
0.5%
Lowercase Letter 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 108
12.9%
문 63
 
7.5%
시 54
 
6.5%
서 52
 
6.2%
울 52
 
6.2%
구 52
 
6.2%
대 52
 
6.2%
별 52
 
6.2%
특 52
 
6.2%
지 46
 
5.5%
Other values (59) 254
30.3%
Decimal Number
ValueCountFrequency (%)
1 56
23.9%
2 30
12.8%
0 26
11.1%
9 23
9.8%
3 23
9.8%
5 21
 
9.0%
8 19
 
8.1%
7 14
 
6.0%
6 13
 
5.6%
4 9
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
220
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 837
64.2%
Common 464
35.6%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 108
12.9%
문 63
 
7.5%
시 54
 
6.5%
서 52
 
6.2%
울 52
 
6.2%
구 52
 
6.2%
대 52
 
6.2%
별 52
 
6.2%
특 52
 
6.2%
지 46
 
5.5%
Other values (59) 254
30.3%
Common
ValueCountFrequency (%)
220
47.4%
1 56
 
12.1%
2 30
 
6.5%
0 26
 
5.6%
9 23
 
5.0%
3 23
 
5.0%
5 21
 
4.5%
8 19
 
4.1%
7 14
 
3.0%
6 13
 
2.8%
Other values (5) 19
 
4.1%
Latin
ValueCountFrequency (%)
s 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 837
64.2%
ASCII 466
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
220
47.2%
1 56
 
12.0%
2 30
 
6.4%
0 26
 
5.6%
9 23
 
4.9%
3 23
 
4.9%
5 21
 
4.5%
8 19
 
4.1%
7 14
 
3.0%
6 13
 
2.8%
Other values (7) 21
 
4.5%
Hangul
ValueCountFrequency (%)
동 108
12.9%
문 63
 
7.5%
시 54
 
6.5%
서 52
 
6.2%
울 52
 
6.2%
구 52
 
6.2%
대 52
 
6.2%
별 52
 
6.2%
특 52
 
6.2%
지 46
 
5.5%
Other values (59) 254
30.3%

도로명주소
Text

MISSING 

Distinct30
Distinct (%)83.3%
Missing18
Missing (%)33.3%
Memory size564.0 B
2024-05-11T15:39:31.513345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length26.638889
Min length22

Characters and Unicode

Total characters959
Distinct characters86
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

Unique25 ?
Unique (%)69.4%

Sample

1st row서울특별시 동대문구 왕산로 205-0 (전농동, 롯데백화점(청량리점))
2nd row서울특별시 동대문구 무학로37길 12(용두동)
3rd row서울특별시 동대문구 제기로 18 (제기동)
4th row서울특별시 동대문구 고산자로36길 3, 경동시장 (제기동)
5th row서울특별시 동대문구 홍릉로 13 (청량리동)
ValueCountFrequency (%)
서울특별시 36
19.6%
동대문구 36
19.6%
장안동 8
 
4.3%
이문로 6
 
3.3%
전농동 6
 
3.3%
이문동 5
 
2.7%
제기동 5
 
2.7%
왕산로 5
 
2.7%
답십리로 3
 
1.6%
42 3
 
1.6%
Other values (55) 71
38.6%
2024-05-11T15:39:32.241594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
152
 
15.8%
동 74
 
7.7%
문 47
 
4.9%
대 41
 
4.3%
시 40
 
4.2%
서 37
 
3.9%
울 37
 
3.9%
) 37
 
3.9%
( 37
 
3.9%
특 36
 
3.8%
Other values (76) 421
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 616
64.2%
Space Separator 152
 
15.8%
Decimal Number 106
 
11.1%
Close Punctuation 37
 
3.9%
Open Punctuation 37
 
3.9%
Other Punctuation 8
 
0.8%
Uppercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 74
 
12.0%
문 47
 
7.6%
대 41
 
6.7%
시 40
 
6.5%
서 37
 
6.0%
울 37
 
6.0%
특 36
 
5.8%
별 36
 
5.8%
구 36
 
5.8%
로 36
 
5.8%
Other values (59) 196
31.8%
Decimal Number
ValueCountFrequency (%)
2 18
17.0%
1 18
17.0%
3 16
15.1%
4 15
14.2%
8 14
13.2%
6 8
7.5%
7 5
 
4.7%
0 5
 
4.7%
5 4
 
3.8%
9 3
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
152
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 616
64.2%
Common 341
35.6%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 74
 
12.0%
문 47
 
7.6%
대 41
 
6.7%
시 40
 
6.5%
서 37
 
6.0%
울 37
 
6.0%
특 36
 
5.8%
별 36
 
5.8%
구 36
 
5.8%
로 36
 
5.8%
Other values (59) 196
31.8%
Common
ValueCountFrequency (%)
152
44.6%
) 37
 
10.9%
( 37
 
10.9%
2 18
 
5.3%
1 18
 
5.3%
3 16
 
4.7%
4 15
 
4.4%
8 14
 
4.1%
, 8
 
2.3%
6 8
 
2.3%
Other values (5) 18
 
5.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 616
64.2%
ASCII 343
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
152
44.3%
) 37
 
10.8%
( 37
 
10.8%
2 18
 
5.2%
1 18
 
5.2%
3 16
 
4.7%
4 15
 
4.4%
8 14
 
4.1%
, 8
 
2.3%
6 8
 
2.3%
Other values (7) 20
 
5.8%
Hangul
ValueCountFrequency (%)
동 74
 
12.0%
문 47
 
7.6%
대 41
 
6.7%
시 40
 
6.5%
서 37
 
6.0%
울 37
 
6.0%
특 36
 
5.8%
별 36
 
5.8%
구 36
 
5.8%
로 36
 
5.8%
Other values (59) 196
31.8%

도로명우편번호
Text

MISSING 

Distinct28
Distinct (%)77.8%
Missing18
Missing (%)33.3%
Memory size564.0 B
2024-05-11T15:39:32.553310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8333333
Min length5

Characters and Unicode

Total characters210
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 (%)58.3%

Sample

1st row130796
2nd row02579
3rd row130860
4th row02571
5th row130870
ValueCountFrequency (%)
130826 3
 
8.3%
130851 2
 
5.6%
02561 2
 
5.6%
130864 2
 
5.6%
02523 2
 
5.6%
02571 2
 
5.6%
130840 2
 
5.6%
130050 1
 
2.8%
130080 1
 
2.8%
130-837 1
 
2.8%
Other values (18) 18
50.0%
2024-05-11T15:39:33.093083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 49
23.3%
1 38
18.1%
3 32
15.2%
8 22
10.5%
2 18
 
8.6%
5 16
 
7.6%
6 11
 
5.2%
7 9
 
4.3%
4 7
 
3.3%
9 4
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206
98.1%
Dash Punctuation 4
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 49
23.8%
1 38
18.4%
3 32
15.5%
8 22
10.7%
2 18
 
8.7%
5 16
 
7.8%
6 11
 
5.3%
7 9
 
4.4%
4 7
 
3.4%
9 4
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 49
23.3%
1 38
18.1%
3 32
15.2%
8 22
10.5%
2 18
 
8.6%
5 16
 
7.6%
6 11
 
5.2%
7 9
 
4.3%
4 7
 
3.3%
9 4
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 49
23.3%
1 38
18.1%
3 32
15.2%
8 22
10.5%
2 18
 
8.6%
5 16
 
7.6%
6 11
 
5.2%
7 9
 
4.3%
4 7
 
3.3%
9 4
 
1.9%

사업장명
Text

Distinct50
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-05-11T15:39:33.518860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.5555556
Min length4

Characters and Unicode

Total characters516
Distinct characters131
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)85.2%

Sample

1st row롯데백화점 청량리플라자
2nd row용두시장
3rd row제기시장
4th row경동시장
5th row동서시장
ValueCountFrequency (%)
롯데쇼핑(주 5
 
5.3%
롯데슈퍼 4
 
4.3%
이문점 3
 
3.2%
장안점 3
 
3.2%
gs 2
 
2.1%
홈플러스(주 2
 
2.1%
노브랜드 2
 
2.1%
롯데백화점 2
 
2.1%
주)이마트에브리데이 2
 
2.1%
the 2
 
2.1%
Other values (60) 67
71.3%
2024-05-11T15:39:34.398165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
7.8%
장 27
 
5.2%
점 23
 
4.5%
시 19
 
3.7%
데 16
 
3.1%
주 15
 
2.9%
동 15
 
2.9%
롯 14
 
2.7%
( 13
 
2.5%
) 13
 
2.5%
Other values (121) 321
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 423
82.0%
Space Separator 40
 
7.8%
Uppercase Letter 20
 
3.9%
Open Punctuation 13
 
2.5%
Close Punctuation 13
 
2.5%
Decimal Number 5
 
1.0%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 27
 
6.4%
점 23
 
5.4%
시 19
 
4.5%
데 16
 
3.8%
주 15
 
3.5%
동 15
 
3.5%
롯 14
 
3.3%
이 13
 
3.1%
문 12
 
2.8%
리 11
 
2.6%
Other values (108) 258
61.0%
Uppercase Letter
ValueCountFrequency (%)
E 4
20.0%
H 4
20.0%
S 4
20.0%
G 2
10.0%
R 2
10.0%
F 2
10.0%
T 2
10.0%
Decimal Number
ValueCountFrequency (%)
9 3
60.0%
2 2
40.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 423
82.0%
Common 73
 
14.1%
Latin 20
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 27
 
6.4%
점 23
 
5.4%
시 19
 
4.5%
데 16
 
3.8%
주 15
 
3.5%
동 15
 
3.5%
롯 14
 
3.3%
이 13
 
3.1%
문 12
 
2.8%
리 11
 
2.6%
Other values (108) 258
61.0%
Latin
ValueCountFrequency (%)
E 4
20.0%
H 4
20.0%
S 4
20.0%
G 2
10.0%
R 2
10.0%
F 2
10.0%
T 2
10.0%
Common
ValueCountFrequency (%)
40
54.8%
( 13
 
17.8%
) 13
 
17.8%
9 3
 
4.1%
2 2
 
2.7%
- 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 423
82.0%
ASCII 93
 
18.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
43.0%
( 13
 
14.0%
) 13
 
14.0%
E 4
 
4.3%
H 4
 
4.3%
S 4
 
4.3%
9 3
 
3.2%
2 2
 
2.2%
G 2
 
2.2%
- 2
 
2.2%
Other values (3) 6
 
6.5%
Hangul
ValueCountFrequency (%)
장 27
 
6.4%
점 23
 
5.4%
시 19
 
4.5%
데 16
 
3.8%
주 15
 
3.5%
동 15
 
3.5%
롯 14
 
3.3%
이 13
 
3.1%
문 12
 
2.8%
리 11
 
2.6%
Other values (108) 258
61.0%

최종수정일자
Date

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2007-07-21 10:33:30
Maximum2024-04-30 16:41:33
2024-05-11T15:39:34.671866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:39:34.936965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
I
28 
U
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 28
51.9%
U 26
48.1%

Length

2024-05-11T15:39:35.149069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:35.292284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 28
51.9%
u 26
48.1%

데이터갱신일자
Categorical

Distinct17
Distinct (%)31.5%
Missing0
Missing (%)0.0%
Memory size564.0 B
2018-08-31 23:59:59.0
27 
2021-12-07 02:40:00.0
8 
2021-12-04 23:00:00.0
3 
2021-10-30 22:02:00.0
 
2
2023-12-05 00:02:00.0
 
2
Other values (12)
12 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique12 ?
Unique (%)22.2%

Sample

1st row2018-08-31 23:59:59.0
2nd row2021-12-07 02:40:00.0
3rd row2018-08-31 23:59:59.0
4th row2021-12-03 22:03:00.0
5th row2021-12-07 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 27
50.0%
2021-12-07 02:40:00.0 8
 
14.8%
2021-12-04 23:00:00.0 3
 
5.6%
2021-10-30 22:02:00.0 2
 
3.7%
2023-12-05 00:02:00.0 2
 
3.7%
2021-12-04 00:08:00.0 1
 
1.9%
2022-12-02 23:06:00.0 1
 
1.9%
2022-12-07 00:01:00.0 1
 
1.9%
2023-12-02 22:07:00.0 1
 
1.9%
2023-11-30 22:01:00.0 1
 
1.9%
Other values (7) 7
 
13.0%

Length

2024-05-11T15:39:35.450538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 27
25.0%
23:59:59.0 27
25.0%
02:40:00.0 12
11.1%
2021-12-07 8
 
7.4%
2021-12-04 4
 
3.7%
23:00:00.0 3
 
2.8%
2023-12-05 2
 
1.9%
00:02:00.0 2
 
1.9%
22:02:00.0 2
 
1.9%
2021-10-30 2
 
1.9%
Other values (19) 19
17.6%

업태구분명
Categorical

Distinct7
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
그 밖의 대규모점포
22 
구분없음
10 
시장
9 
대형마트
6 
전문점
4 
Other values (2)
3 

Length

Max length10
Median length5
Mean length6.0185185
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row백화점
2nd row시장
3rd row그 밖의 대규모점포
4th row시장
5th row시장

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 22
40.7%
구분없음 10
18.5%
시장 9
16.7%
대형마트 6
 
11.1%
전문점 4
 
7.4%
백화점 2
 
3.7%
복합쇼핑몰 1
 
1.9%

Length

2024-05-11T15:39:35.679895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:36.232450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 22
22.4%
밖의 22
22.4%
대규모점포 22
22.4%
구분없음 10
10.2%
시장 9
9.2%
대형마트 6
 
6.1%
전문점 4
 
4.1%
백화점 2
 
2.0%
복합쇼핑몰 1
 
1.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)61.5%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean204608.37
Minimum202186.47
Maximum206341.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-05-11T15:39:36.480285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum202186.47
5-th percentile202797.16
Q1203549.15
median204886.02
Q3205396.36
95-th percentile206325.35
Maximum206341.54
Range4155.0707
Interquartile range (IQR)1847.2167

Descriptive statistics

Standard deviation1193.0856
Coefficient of variation (CV)0.0058310694
Kurtosis-0.97656898
Mean204608.37
Median Absolute Deviation (MAD)962.32944
Skewness-0.27440048
Sum10639635
Variance1423453.2
MonotonicityNot monotonic
2024-05-11T15:39:36.777096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
205396.363734301 7
 
13.0%
206325.349431713 4
 
7.4%
204881.313219146 3
 
5.6%
203075.098504907 3
 
5.6%
205006.074911385 2
 
3.7%
203258.377206168 2
 
3.7%
205423.969491537 2
 
3.7%
202186.468072494 2
 
3.7%
203403.019535366 2
 
3.7%
206341.538776724 2
 
3.7%
Other values (22) 23
42.6%
ValueCountFrequency (%)
202186.468072494 2
3.7%
202538.011840845 1
 
1.9%
203009.188734992 1
 
1.9%
203075.098504907 3
5.6%
203155.504921512 1
 
1.9%
203258.377206168 2
3.7%
203356.957362754 1
 
1.9%
203403.019535366 2
3.7%
203597.856176904 1
 
1.9%
203728.022004023 1
 
1.9%
ValueCountFrequency (%)
206341.538776724 2
 
3.7%
206325.349431713 4
7.4%
206176.178625746 1
 
1.9%
206101.9138443 1
 
1.9%
205987.345607556 1
 
1.9%
205423.969491537 2
 
3.7%
205403.77766039 1
 
1.9%
205396.363734301 7
13.0%
205271.704936121 1
 
1.9%
205170.935816792 1
 
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)61.5%
Missing2
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean453205.93
Minimum451556.21
Maximum455220.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-05-11T15:39:37.017721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum451556.21
5-th percentile451762.78
Q1452432.55
median452916.72
Q3454280.04
95-th percentile455131.68
Maximum455220.26
Range3664.0468
Interquartile range (IQR)1847.4901

Descriptive statistics

Standard deviation1104.0093
Coefficient of variation (CV)0.0024359993
Kurtosis-0.76381594
Mean453205.93
Median Absolute Deviation (MAD)634.11459
Skewness0.63270886
Sum23566708
Variance1218836.6
MonotonicityNot monotonic
2024-05-11T15:39:37.296664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
455131.683241064 7
 
13.0%
452184.2101607 4
 
7.4%
454280.040555974 3
 
5.6%
452918.836458244 3
 
5.6%
451814.33240199 2
 
3.7%
452834.064124525 2
 
3.7%
451556.210578255 2
 
3.7%
452282.607415166 2
 
3.7%
452985.725419514 2
 
3.7%
452530.018811546 2
 
3.7%
Other values (22) 23
42.6%
ValueCountFrequency (%)
451556.210578255 2
3.7%
451699.765836365 1
 
1.9%
451814.33240199 2
3.7%
452155.691148899 1
 
1.9%
452184.2101607 4
7.4%
452282.607415166 2
3.7%
452322.301296488 1
 
1.9%
452469.300221465 1
 
1.9%
452472.990548179 1
 
1.9%
452530.018811546 2
3.7%
ValueCountFrequency (%)
455220.257356121 1
 
1.9%
455131.683241064 7
13.0%
454707.524142172 1
 
1.9%
454552.779662883 1
 
1.9%
454315.0261032 1
 
1.9%
454280.040555974 3
5.6%
453776.829188234 1
 
1.9%
453248.09724644 1
 
1.9%
453238.594217594 1
 
1.9%
453187.395154017 2
 
3.7%

점포구분명
Categorical

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
28 
대규모점포
21 
준대규모점포
5 

Length

Max length6
Median length4
Mean length4.5740741
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
51.9%
대규모점포 21
38.9%
준대규모점포 5
 
9.3%

Length

2024-05-11T15:39:37.553772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:39:37.736660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
51.9%
대규모점포 21
38.9%
준대규모점포 5
 
9.3%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03050000197930501000750000119790913<NA>3폐업3폐업처리20171227<NA><NA><NA>02-3707-250012979.73130020서울특별시 동대문구 전농동 620번지 69호서울특별시 동대문구 왕산로 205-0 (전농동, 롯데백화점(청량리점))130796롯데백화점 청량리플라자2017-12-29 08:42:21I2018-08-31 23:59:59.0백화점203996.013918453058.665829대규모점포
13050000200030500820750000119771226<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 92637511250.85<NA>서울특별시 동대문구 용두동 231-5서울특별시 동대문구 무학로37길 12(용두동)02579용두시장2021-12-04 15:48:17U2021-12-07 02:40:00.0시장202538.011841452901.185284대규모점포
23050000200030500820750000219630131<NA>3폐업3폐업처리20150724<NA><NA><NA>0002092826081576.4130860서울특별시 동대문구 제기동 135번지 90호서울특별시 동대문구 제기로 18 (제기동)130860제기시장2015-07-24 11:13:07I2018-08-31 23:59:59.0그 밖의 대규모점포203009.188735453776.829188대규모점포
33050000200030500820750000319600629<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-967-872115540.7<NA>서울특별시 동대문구 제기동 1019 경동시장서울특별시 동대문구 고산자로36길 3, 경동시장 (제기동)02571경동시장2022-04-21 09:11:11U2021-12-03 22:03:00.0시장203403.019535452985.72542<NA>
43050000200030500820750000419721012<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-967-81691813.0<NA>서울특별시 동대문구 제기동 650호<NA><NA>동서시장2021-12-04 15:45:28U2021-12-07 02:40:00.0시장203597.856177453055.908738대규모점포
53050000200030500820750000519480921<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 959998119780.15130870서울특별시 동대문구 청량리동 738번지서울특별시 동대문구 홍릉로 13 (청량리동)130870청량리현대코아2014-10-29 15:46:42I2018-08-31 23:59:59.0그 밖의 대규모점포203851.375425453238.594218대규모점포
63050000200030500820750000719781228<NA>1영업/정상1정상영업<NA><NA><NA><NA>022215720010431.44130859서울특별시 동대문구 전농동 647번지 1호서울특별시 동대문구 서울시립대로 36 (전농동)130859전농프라자2014-10-29 18:12:19I2018-08-31 23:59:59.0그 밖의 대규모점포204082.111844452472.990548대규모점포
73050000200030500820750000819740402<NA>1영업/정상1정상영업<NA><NA><NA><NA>02221712314244.0130854서울특별시 동대문구 전농동 295번지 52호서울특별시 동대문구 전농로 147 (전농동)130854전농로타리시장2021-12-04 14:55:15U2021-12-07 02:40:00.0시장204970.901636452852.821037대규모점포
83050000200030500820750000919720901<NA>3폐업3폐업처리20010502<NA><NA><NA>02224496360.0<NA>서울특별시 동대문구 답십리동 265번지 5호<NA><NA>답십리중앙시장2007-08-13 15:34:30I2018-08-31 23:59:59.0그 밖의 대규모점포205006.074911451814.332402<NA>
93050000200030500820750001019710311<NA>1영업/정상1정상영업<NA><NA><NA><NA>02224444511655.9<NA>서울특별시 동대문구 답십리동 495-1서울특별시 동대문구 천호대로 281(답십리동)02604동부시장2021-12-04 14:28:11U2021-12-07 02:40:00.0시장205006.074911451814.332402대규모점포
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
443050000201330501400750000120130814<NA>3폐업3폐업처리20141231<NA><NA><NA><NA>0.0130101서울특별시 동대문구 장안동 368번지 1호 바우하우스서울특별시 동대문구 답십리로 288 (장안동)130101롯데쇼핑(주) 롯데슈퍼 장안 2동점2015-01-13 13:38:28I2018-08-31 23:59:59.0구분없음206325.349432452184.210161준대규모점포
453050000201330501400750000220131127<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-957-21163824.55130050서울특별시 동대문구 회기동 346번지 18호서울특별시 동대문구 이문로 37 (회기동)130050베라체캠퍼스 에비뉴2022-04-06 11:28:46U2021-12-04 00:08:00.0그 밖의 대규모점포204881.313219454280.040556<NA>
46305000020143050140075000012008-08-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>2238-26002448.0130-813서울특별시 동대문구 신설동 109번지 5호서울특별시 동대문구 천호대로4길 21 (신설동)130-813서울풍물시장2024-01-19 17:46:11U2023-11-30 22:01:00.0그 밖의 대규모점포202186.468072452282.607415<NA>
473050000201430501400750000220090320<NA>1영업/정상1정상영업<NA><NA><NA><NA>962-30048286.24130826서울특별시 동대문구 이문동 292번지 10호서울특별시 동대문구 이문로 136 (이문동)130826이문동웰츠타워2014-09-26 13:26:40I2018-08-31 23:59:59.0그 밖의 대규모점포205396.363734455131.683241대규모점포
48305000020143050140075000032014-09-25<NA>1영업/정상1정상영업<NA><NA><NA><NA>029598545141.0<NA><NA>서울특별시 동대문구 경희대로 20 (회기동)130-872홈플러스 익스프레스 서울회기점2024-03-25 09:56:13U2023-12-02 22:07:00.0구분없음204599.373004454552.779663<NA>
493050000201630501480750000120161230<NA>1영업/정상1정상영업<NA><NA><NA><NA>2232-33677377.08130110서울특별시 동대문구 신설동 109번지 5호<NA><NA>서울특별시장2016-12-30 10:32:18I2018-08-31 23:59:59.0그 밖의 대규모점포202186.468072452282.607415<NA>
50305000020183050140075000012018-01-25<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-9461441.1<NA>서울특별시 동대문구 제기동 1019번지 신관 2층서울특별시 동대문구 고산자로36길 3, 2층 (제기동)02571노브랜드 경동시장점2024-04-30 16:41:21U2023-12-05 00:02:00.0구분없음203403.019535452985.72542<NA>
51305000020223050140075000012022-07-11<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-721-828622487.6<NA>서울특별시 동대문구 용두동 39-1 청량리역한양수자인그라시엘서울특별시 동대문구 고산자로32길 78 (용두동, 청량리역한양수자인그라시엘)02561청량리역 한양수자인 그라시엘 판매시설2023-06-29 10:04:00U2022-12-07 00:01:00.0그 밖의 대규모점포203728.022004452778.965235<NA>
52305000020233050210075000012023-03-14<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-2006-2364307.23<NA>서울특별시 동대문구 장안동 310-8 희헌빌딩서울특별시 동대문구 장한로28가길 45, 희헌빌딩 (장안동)02523GS THE FRESH 동대문장안점2023-03-14 09:57:17I2022-12-02 23:06:00.0구분없음206341.538777452530.018812<NA>
53305000020233050210075000022023-03-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2364307.23<NA>서울특별시 동대문구 장안동 310-8 희헌빌딩서울특별시 동대문구 장한로28가길 45, 희헌빌딩 (장안동)02523GS THE FRESH 동대문장안점2023-07-10 09:11:32U2022-12-06 23:03:00.0구분없음206341.538777452530.018812<NA>