Overview

Dataset statistics

Number of variables26
Number of observations60
Missing cells353
Missing cells (%)22.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory221.2 B

Variable types

Categorical10
Numeric4
DateTime3
Unsupported3
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
Author성북구
URLhttps://data.seoul.go.kr/dataList/OA-18709/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 is highly imbalanced (87.8%)Imbalance
인허가취소일자 has 60 (100.0%) missing valuesMissing
폐업일자 has 49 (81.7%) missing valuesMissing
휴업시작일자 has 60 (100.0%) missing valuesMissing
휴업종료일자 has 60 (100.0%) missing valuesMissing
전화번호 has 2 (3.3%) missing valuesMissing
소재지면적 has 9 (15.0%) missing valuesMissing
소재지우편번호 has 40 (66.7%) missing valuesMissing
지번주소 has 5 (8.3%) missing valuesMissing
도로명주소 has 24 (40.0%) missing valuesMissing
도로명우편번호 has 24 (40.0%) missing valuesMissing
좌표정보(X) has 10 (16.7%) missing valuesMissing
좌표정보(Y) has 10 (16.7%) 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
소재지면적 has 5 (8.3%) zerosZeros

Reproduction

Analysis started2024-04-29 19:47:14.747934
Analysis finished2024-04-29 19:47:15.363845
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
3070000
60 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3070000
2nd row3070000
3rd row3070000
4th row3070000
5th row3070000

Common Values

ValueCountFrequency (%)
3070000 60
100.0%

Length

2024-04-30T04:47:15.428209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:15.501894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3070000 60
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0088519 × 1018
Minimum1.968307 × 1018
Maximum2.023307 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-30T04:47:15.597231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.968307 × 1018
5-th percentile2.000307 × 1018
Q12.000307 × 1018
median2.011807 × 1018
Q32.012307 × 1018
95-th percentile2.022357 × 1018
Maximum2.023307 × 1018
Range5.500002 × 1016
Interquartile range (IQR)1.200001 × 1016

Descriptive statistics

Standard deviation9.2162591 × 1015
Coefficient of variation (CV)0.0045878241
Kurtosis4.8684188
Mean2.0088519 × 1018
Median Absolute Deviation (MAD)7.5000027 × 1015
Skewness-1.2521227
Sum-8.5960945 × 1018
Variance8.4939431 × 1031
MonotonicityStrictly increasing
2024-04-30T04:47:15.715039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1968307009907500001 1
 
1.7%
2012307018907500002 1
 
1.7%
2012307018907500006 1
 
1.7%
2012307018907500007 1
 
1.7%
2012307018907500008 1
 
1.7%
2012307018907500009 1
 
1.7%
2012307018907500010 1
 
1.7%
2012307018907500011 1
 
1.7%
2012307018907500012 1
 
1.7%
2012307018907500013 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1968307009907500001 1
1.7%
1998000000007500002 1
1.7%
2000307009907500001 1
1.7%
2000307009907500002 1
1.7%
2000307009907500003 1
1.7%
2000307009907500004 1
1.7%
2000307009907500006 1
1.7%
2000307009907500007 1
1.7%
2000307009907500008 1
1.7%
2000307009907500009 1
1.7%
ValueCountFrequency (%)
2023307029907500003 1
1.7%
2023307029907500002 1
1.7%
2023307029907500001 1
1.7%
2022307028607500002 1
1.7%
2022307028607500001 1
1.7%
2021307028607500001 1
1.7%
2020307028607500001 1
1.7%
2019307021607500003 1
1.7%
2019307021607500002 1
1.7%
2019307021607500001 1
1.7%

인허가일자
Date

Distinct50
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum1961-12-04 00:00:00
Maximum2023-06-08 00:00:00
2024-04-30T04:47:15.849034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:15.974660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
1
45 
3
11 
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 45
75.0%
3 11
 
18.3%
2 4
 
6.7%

Length

2024-04-30T04:47:16.086565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:16.181717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
75.0%
3 11
 
18.3%
2 4
 
6.7%

영업상태명
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
영업/정상
45 
폐업
11 
휴업
 
4

Length

Max length5
Median length5
Mean length4.25
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 45
75.0%
폐업 11
 
18.3%
휴업 4
 
6.7%

Length

2024-04-30T04:47:16.283958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:16.383193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 45
75.0%
폐업 11
 
18.3%
휴업 4
 
6.7%

상세영업상태코드
Categorical

Distinct4
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
1
42 
3
11 
2
 
4
5
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row1
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 42
70.0%
3 11
 
18.3%
2 4
 
6.7%
5 3
 
5.0%

Length

2024-04-30T04:47:16.486438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:16.566841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 42
70.0%
3 11
 
18.3%
2 4
 
6.7%
5 3
 
5.0%

상세영업상태명
Categorical

Distinct4
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
정상영업
42 
폐업처리
11 
휴업처리
 
4
영업개시전
 
3

Length

Max length5
Median length4
Mean length4.05
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 42
70.0%
폐업처리 11
 
18.3%
휴업처리 4
 
6.7%
영업개시전 3
 
5.0%

Length

2024-04-30T04:47:16.675601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:16.762155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 42
70.0%
폐업처리 11
 
18.3%
휴업처리 4
 
6.7%
영업개시전 3
 
5.0%

폐업일자
Date

MISSING 

Distinct10
Distinct (%)90.9%
Missing49
Missing (%)81.7%
Memory size612.0 B
Minimum2007-02-13 00:00:00
Maximum2024-04-08 00:00:00
2024-04-30T04:47:16.839737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:16.945776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing60
Missing (%)100.0%
Memory size672.0 B

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
59 
20030210
 
1

Length

Max length8
Median length4
Mean length4.0666667
Min length4

Unique

Unique1 ?
Unique (%)1.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
98.3%
20030210 1
 
1.7%

Length

2024-04-30T04:47:17.074870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:17.174064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
98.3%
20030210 1
 
1.7%

전화번호
Text

MISSING 

Distinct52
Distinct (%)89.7%
Missing2
Missing (%)3.3%
Memory size612.0 B
2024-04-30T04:47:17.314903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.551724
Min length7

Characters and Unicode

Total characters612
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

Unique46 ?
Unique (%)79.3%

Sample

1st row02 9151254
2nd row02 9434044
3rd row02-941-3506
4th row9266122
5th row02 9135724
ValueCountFrequency (%)
02 27
30.7%
9436563 2
 
2.3%
9675571 2
 
2.3%
02-380-5042 2
 
2.3%
02-926-6405 2
 
2.3%
02-912-9110 2
 
2.3%
9620580 2
 
2.3%
9434044 2
 
2.3%
9151254 1
 
1.1%
0236758549 1
 
1.1%
Other values (45) 45
51.1%
2024-04-30T04:47:17.593698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 104
17.0%
2 95
15.5%
9 60
9.8%
1 55
9.0%
5 51
8.3%
4 46
7.5%
- 42
6.9%
6 40
 
6.5%
40
 
6.5%
3 38
 
6.2%
Other values (2) 41
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 530
86.6%
Dash Punctuation 42
 
6.9%
Space Separator 40
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 104
19.6%
2 95
17.9%
9 60
11.3%
1 55
10.4%
5 51
9.6%
4 46
8.7%
6 40
 
7.5%
3 38
 
7.2%
8 22
 
4.2%
7 19
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 612
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 104
17.0%
2 95
15.5%
9 60
9.8%
1 55
9.0%
5 51
8.3%
4 46
7.5%
- 42
6.9%
6 40
 
6.5%
40
 
6.5%
3 38
 
6.2%
Other values (2) 41
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 612
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 104
17.0%
2 95
15.5%
9 60
9.8%
1 55
9.0%
5 51
8.3%
4 46
7.5%
- 42
6.9%
6 40
 
6.5%
40
 
6.5%
3 38
 
6.2%
Other values (2) 41
 
6.7%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)80.4%
Missing9
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean4861.7241
Minimum0
Maximum36583
Zeros5
Zeros (%)8.3%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-30T04:47:17.723348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1208.5
median1845
Q36626.19
95-th percentile18390.5
Maximum36583
Range36583
Interquartile range (IQR)6417.69

Descriptive statistics

Standard deviation7118.8533
Coefficient of variation (CV)1.4642652
Kurtosis7.0692987
Mean4861.7241
Median Absolute Deviation (MAD)1764.51
Skewness2.36725
Sum247947.93
Variance50678072
MonotonicityNot monotonic
2024-04-30T04:47:17.834287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 5
 
8.3%
10006.0 4
 
6.7%
80.49 3
 
5.0%
828.69 2
 
3.3%
1426.32 1
 
1.7%
14370.0 1
 
1.7%
292.56 1
 
1.7%
685.6 1
 
1.7%
257.0 1
 
1.7%
215.0 1
 
1.7%
Other values (31) 31
51.7%
(Missing) 9
 
15.0%
ValueCountFrequency (%)
0.0 5
8.3%
80.49 3
5.0%
149.49 1
 
1.7%
186.6 1
 
1.7%
189.0 1
 
1.7%
198.0 1
 
1.7%
202.0 1
 
1.7%
215.0 1
 
1.7%
257.0 1
 
1.7%
292.56 1
 
1.7%
ValueCountFrequency (%)
36583.0 1
 
1.7%
19201.0 1
 
1.7%
18964.0 1
 
1.7%
17817.0 1
 
1.7%
17056.0 1
 
1.7%
14370.0 1
 
1.7%
10745.0 1
 
1.7%
10006.0 4
6.7%
9954.0 1
 
1.7%
7194.0 1
 
1.7%

소재지우편번호
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing40
Missing (%)66.7%
Memory size612.0 B
2024-04-30T04:47:17.975016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.35
Min length6

Characters and Unicode

Total characters127
Distinct characters10
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

Unique18 ?
Unique (%)90.0%

Sample

1st row136802
2nd row136111
3rd row136143
4th row136735
5th row136062
ValueCountFrequency (%)
136111 2
 
10.0%
136-140 1
 
5.0%
136110 1
 
5.0%
136-800 1
 
5.0%
136751 1
 
5.0%
136150 1
 
5.0%
136-732 1
 
5.0%
136-087 1
 
5.0%
136-854 1
 
5.0%
136-111 1
 
5.0%
Other values (9) 9
45.0%
2024-04-30T04:47:18.233287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 38
29.9%
3 26
20.5%
6 21
16.5%
0 11
 
8.7%
5 7
 
5.5%
- 7
 
5.5%
7 6
 
4.7%
2 4
 
3.1%
8 4
 
3.1%
4 3
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 120
94.5%
Dash Punctuation 7
 
5.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 38
31.7%
3 26
21.7%
6 21
17.5%
0 11
 
9.2%
5 7
 
5.8%
7 6
 
5.0%
2 4
 
3.3%
8 4
 
3.3%
4 3
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 127
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 38
29.9%
3 26
20.5%
6 21
16.5%
0 11
 
8.7%
5 7
 
5.5%
- 7
 
5.5%
7 6
 
4.7%
2 4
 
3.1%
8 4
 
3.1%
4 3
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 38
29.9%
3 26
20.5%
6 21
16.5%
0 11
 
8.7%
5 7
 
5.5%
- 7
 
5.5%
7 6
 
4.7%
2 4
 
3.1%
8 4
 
3.1%
4 3
 
2.4%

지번주소
Text

MISSING 

Distinct50
Distinct (%)90.9%
Missing5
Missing (%)8.3%
Memory size612.0 B
2024-04-30T04:47:18.467198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length25.290909
Min length18

Characters and Unicode

Total characters1391
Distinct characters84
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

Unique46 ?
Unique (%)83.6%

Sample

1st row서울특별시 성북구 장위동 60번지 1호
2nd row서울특별시 성북구 장위동 68번지 1014호
3rd row서울특별시 성북구 보문동4가 1번지 1 호
4th row서울특별시 성북구 종암동 3번지 75 호
5th row서울특별시 성북구 삼선동5가 55번지 1 호
ValueCountFrequency (%)
서울특별시 55
19.6%
성북구 55
19.6%
길음동 16
 
5.7%
장위동 9
 
3.2%
2호 8
 
2.8%
호 8
 
2.8%
1호 7
 
2.5%
25번지 6
 
2.1%
하월곡동 5
 
1.8%
1 5
 
1.8%
Other values (82) 107
38.1%
2024-04-30T04:47:18.800505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
267
19.2%
동 60
 
4.3%
시 60
 
4.3%
성 56
 
4.0%
서 55
 
4.0%
북 55
 
4.0%
울 55
 
4.0%
구 55
 
4.0%
별 55
 
4.0%
특 55
 
4.0%
Other values (74) 618
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 858
61.7%
Space Separator 267
 
19.2%
Decimal Number 250
 
18.0%
Dash Punctuation 11
 
0.8%
Other Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 60
 
7.0%
시 60
 
7.0%
성 56
 
6.5%
서 55
 
6.4%
북 55
 
6.4%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
지 47
 
5.5%
Other values (61) 305
35.5%
Decimal Number
ValueCountFrequency (%)
1 45
18.0%
2 41
16.4%
5 35
14.0%
6 24
9.6%
0 24
9.6%
3 23
9.2%
8 19
7.6%
4 16
 
6.4%
9 12
 
4.8%
7 11
 
4.4%
Space Separator
ValueCountFrequency (%)
267
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 858
61.7%
Common 533
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 60
 
7.0%
시 60
 
7.0%
성 56
 
6.5%
서 55
 
6.4%
북 55
 
6.4%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
지 47
 
5.5%
Other values (61) 305
35.5%
Common
ValueCountFrequency (%)
267
50.1%
1 45
 
8.4%
2 41
 
7.7%
5 35
 
6.6%
6 24
 
4.5%
0 24
 
4.5%
3 23
 
4.3%
8 19
 
3.6%
4 16
 
3.0%
9 12
 
2.3%
Other values (3) 27
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 858
61.7%
ASCII 533
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
267
50.1%
1 45
 
8.4%
2 41
 
7.7%
5 35
 
6.6%
6 24
 
4.5%
0 24
 
4.5%
3 23
 
4.3%
8 19
 
3.6%
4 16
 
3.0%
9 12
 
2.3%
Other values (3) 27
 
5.1%
Hangul
ValueCountFrequency (%)
동 60
 
7.0%
시 60
 
7.0%
성 56
 
6.5%
서 55
 
6.4%
북 55
 
6.4%
울 55
 
6.4%
구 55
 
6.4%
별 55
 
6.4%
특 55
 
6.4%
지 47
 
5.5%
Other values (61) 305
35.5%

도로명주소
Text

MISSING 

Distinct34
Distinct (%)94.4%
Missing24
Missing (%)40.0%
Memory size612.0 B
2024-04-30T04:47:19.024824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length31.611111
Min length22

Characters and Unicode

Total characters1138
Distinct characters125
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

Unique32 ?
Unique (%)88.9%

Sample

1st row서울특별시 성북구 동소문로 315 (길음동, 현대백화점미아점)
2nd row서울특별시 성북구 동소문로 227 (길음동)
3rd row서울특별시 성북구 도봉로 17 (길음동)
4th row서울특별시 성북구 종암로 132 (종암동, 종암우림카이저팰리스)
5th row서울특별시 성북구 도봉로 17, 신세계 이마트 미아점 (길음동)
ValueCountFrequency (%)
서울특별시 36
 
17.1%
성북구 36
 
17.1%
길음동 12
 
5.7%
하월곡동 5
 
2.4%
17 5
 
2.4%
동소문로 4
 
1.9%
돈암동 4
 
1.9%
상가 3
 
1.4%
성북로4길 3
 
1.4%
6 3
 
1.4%
Other values (78) 100
47.4%
2024-04-30T04:47:19.341132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
15.6%
동 46
 
4.0%
시 42
 
3.7%
길 41
 
3.6%
북 40
 
3.5%
성 39
 
3.4%
1 36
 
3.2%
) 36
 
3.2%
울 36
 
3.2%
서 36
 
3.2%
Other values (115) 608
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 724
63.6%
Space Separator 178
 
15.6%
Decimal Number 136
 
12.0%
Close Punctuation 36
 
3.2%
Open Punctuation 36
 
3.2%
Other Punctuation 18
 
1.6%
Uppercase Letter 4
 
0.4%
Dash Punctuation 3
 
0.3%
Math Symbol 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 46
 
6.4%
시 42
 
5.8%
길 41
 
5.7%
북 40
 
5.5%
성 39
 
5.4%
울 36
 
5.0%
서 36
 
5.0%
구 36
 
5.0%
별 36
 
5.0%
특 36
 
5.0%
Other values (98) 336
46.4%
Decimal Number
ValueCountFrequency (%)
1 36
26.5%
7 18
13.2%
2 17
12.5%
4 14
 
10.3%
0 11
 
8.1%
3 10
 
7.4%
8 10
 
7.4%
6 10
 
7.4%
5 6
 
4.4%
9 4
 
2.9%
Space Separator
ValueCountFrequency (%)
178
100.0%
Close Punctuation
ValueCountFrequency (%)
) 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 724
63.6%
Common 410
36.0%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 46
 
6.4%
시 42
 
5.8%
길 41
 
5.7%
북 40
 
5.5%
성 39
 
5.4%
울 36
 
5.0%
서 36
 
5.0%
구 36
 
5.0%
별 36
 
5.0%
특 36
 
5.0%
Other values (98) 336
46.4%
Common
ValueCountFrequency (%)
178
43.4%
1 36
 
8.8%
) 36
 
8.8%
( 36
 
8.8%
7 18
 
4.4%
, 18
 
4.4%
2 17
 
4.1%
4 14
 
3.4%
0 11
 
2.7%
3 10
 
2.4%
Other values (6) 36
 
8.8%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 724
63.6%
ASCII 414
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
43.0%
1 36
 
8.7%
) 36
 
8.7%
( 36
 
8.7%
7 18
 
4.3%
, 18
 
4.3%
2 17
 
4.1%
4 14
 
3.4%
0 11
 
2.7%
3 10
 
2.4%
Other values (7) 40
 
9.7%
Hangul
ValueCountFrequency (%)
동 46
 
6.4%
시 42
 
5.8%
길 41
 
5.7%
북 40
 
5.5%
성 39
 
5.4%
울 36
 
5.0%
서 36
 
5.0%
구 36
 
5.0%
별 36
 
5.0%
특 36
 
5.0%
Other values (98) 336
46.4%

도로명우편번호
Text

MISSING 

Distinct34
Distinct (%)94.4%
Missing24
Missing (%)40.0%
Memory size612.0 B
2024-04-30T04:47:19.526250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8611111
Min length5

Characters and Unicode

Total characters211
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

Unique32 ?
Unique (%)88.9%

Sample

1st row136-719
2nd row136802
3rd row136111
4th row02797
5th row02729
ValueCountFrequency (%)
02721 2
 
5.6%
02751 2
 
5.6%
02874 1
 
2.8%
136084 1
 
2.8%
136150 1
 
2.8%
136751 1
 
2.8%
136829 1
 
2.8%
136-800 1
 
2.8%
136-735 1
 
2.8%
02831 1
 
2.8%
Other values (24) 24
66.7%
2024-04-30T04:47:19.808006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 43
20.4%
3 34
16.1%
0 29
13.7%
6 27
12.8%
2 20
9.5%
7 20
9.5%
8 11
 
5.2%
5 8
 
3.8%
- 8
 
3.8%
9 7
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 203
96.2%
Dash Punctuation 8
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43
21.2%
3 34
16.7%
0 29
14.3%
6 27
13.3%
2 20
9.9%
7 20
9.9%
8 11
 
5.4%
5 8
 
3.9%
9 7
 
3.4%
4 4
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 211
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 43
20.4%
3 34
16.1%
0 29
13.7%
6 27
12.8%
2 20
9.5%
7 20
9.5%
8 11
 
5.2%
5 8
 
3.8%
- 8
 
3.8%
9 7
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 211
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 43
20.4%
3 34
16.1%
0 29
13.7%
6 27
12.8%
2 20
9.5%
7 20
9.5%
8 11
 
5.2%
5 8
 
3.8%
- 8
 
3.8%
9 7
 
3.3%

사업장명
Text

Distinct47
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-30T04:47:20.015443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.7333333
Min length4

Characters and Unicode

Total characters464
Distinct characters96
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)65.0%

Sample

1st row장석시장
2nd row코코마트
3rd row보문시장
4th row종암시장
5th row돈암시장
ValueCountFrequency (%)
길음시장 5
 
5.7%
미아점 5
 
5.7%
길음점 5
 
5.7%
이마트 5
 
5.7%
롯데마이슈퍼 4
 
4.5%
하월곡점 4
 
4.5%
코코마트 3
 
3.4%
홈플러스익스프레스 3
 
3.4%
gs슈퍼마켓 3
 
3.4%
동소문점 2
 
2.3%
Other values (45) 49
55.7%
2024-04-30T04:47:20.332218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 29
 
6.2%
점 29
 
6.2%
28
 
6.0%
시 25
 
5.4%
마 21
 
4.5%
이 18
 
3.9%
스 15
 
3.2%
트 12
 
2.6%
길 11
 
2.4%
음 11
 
2.4%
Other values (86) 265
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 408
87.9%
Space Separator 28
 
6.0%
Uppercase Letter 18
 
3.9%
Decimal Number 6
 
1.3%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 29
 
7.1%
점 29
 
7.1%
시 25
 
6.1%
마 21
 
5.1%
이 18
 
4.4%
스 15
 
3.7%
트 12
 
2.9%
길 11
 
2.7%
음 11
 
2.7%
퍼 9
 
2.2%
Other values (75) 228
55.9%
Uppercase Letter
ValueCountFrequency (%)
S 6
33.3%
G 5
27.8%
E 2
 
11.1%
H 2
 
11.1%
T 1
 
5.6%
F 1
 
5.6%
R 1
 
5.6%
Space Separator
ValueCountFrequency (%)
28
100.0%
Decimal Number
ValueCountFrequency (%)
9 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 408
87.9%
Common 38
 
8.2%
Latin 18
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 29
 
7.1%
점 29
 
7.1%
시 25
 
6.1%
마 21
 
5.1%
이 18
 
4.4%
스 15
 
3.7%
트 12
 
2.9%
길 11
 
2.7%
음 11
 
2.7%
퍼 9
 
2.2%
Other values (75) 228
55.9%
Latin
ValueCountFrequency (%)
S 6
33.3%
G 5
27.8%
E 2
 
11.1%
H 2
 
11.1%
T 1
 
5.6%
F 1
 
5.6%
R 1
 
5.6%
Common
ValueCountFrequency (%)
28
73.7%
9 6
 
15.8%
( 2
 
5.3%
) 2
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 408
87.9%
ASCII 56
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 29
 
7.1%
점 29
 
7.1%
시 25
 
6.1%
마 21
 
5.1%
이 18
 
4.4%
스 15
 
3.7%
트 12
 
2.9%
길 11
 
2.7%
음 11
 
2.7%
퍼 9
 
2.2%
Other values (75) 228
55.9%
ASCII
ValueCountFrequency (%)
28
50.0%
S 6
 
10.7%
9 6
 
10.7%
G 5
 
8.9%
E 2
 
3.6%
H 2
 
3.6%
( 2
 
3.6%
) 2
 
3.6%
T 1
 
1.8%
F 1
 
1.8%

최종수정일자
Date

Distinct51
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
Minimum2007-07-07 10:47:37
Maximum2024-04-17 13:37:54
2024-04-30T04:47:20.457693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T04:47:20.578326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
I
45 
U
15 

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 45
75.0%
U 15
 
25.0%

Length

2024-04-30T04:47:20.688645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:20.768024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 45
75.0%
u 15
 
25.0%

데이터갱신일자
Categorical

Distinct21
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2018-08-31 23:59:59.0
36 
2022-12-04 22:01:00.0
 
2
2022-02-26 02:40:00.0
 
2
2022-12-06 22:09:00.0
 
2
2023-12-04 00:04:00.0
 
2
Other values (16)
16 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique16 ?
Unique (%)26.7%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 36
60.0%
2022-12-04 22:01:00.0 2
 
3.3%
2022-02-26 02:40:00.0 2
 
3.3%
2022-12-06 22:09:00.0 2
 
3.3%
2023-12-04 00:04:00.0 2
 
3.3%
2019-06-15 02:21:11.0 1
 
1.7%
2022-12-03 22:03:00.0 1
 
1.7%
2022-12-03 22:00:00.0 1
 
1.7%
2021-12-03 22:00:00.0 1
 
1.7%
2021-12-03 23:05:00.0 1
 
1.7%
Other values (11) 11
 
18.3%

Length

2024-04-30T04:47:21.025582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 36
30.0%
23:59:59.0 36
30.0%
02:40:00.0 4
 
3.3%
2023-12-04 3
 
2.5%
23:00:00.0 3
 
2.5%
2022-02-26 2
 
1.7%
2022-12-03 2
 
1.7%
2023-12-03 2
 
1.7%
2022-12-04 2
 
1.7%
2021-12-03 2
 
1.7%
Other values (23) 28
23.3%

업태구분명
Categorical

Distinct8
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
그 밖의 대규모점포
19 
시장
16 
구분없음
14 
대형마트
6 
백화점
2 
Other values (3)
3 

Length

Max length10
Median length5
Mean length5.35
Min length2

Unique

Unique3 ?
Unique (%)5.0%

Sample

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

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 19
31.7%
시장 16
26.7%
구분없음 14
23.3%
대형마트 6
 
10.0%
백화점 2
 
3.3%
<NA> 1
 
1.7%
쇼핑센터 1
 
1.7%
복합쇼핑몰 1
 
1.7%

Length

2024-04-30T04:47:21.142125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:21.248250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 19
19.4%
밖의 19
19.4%
대규모점포 19
19.4%
시장 16
16.3%
구분없음 14
14.3%
대형마트 6
 
6.1%
백화점 2
 
2.0%
na 1
 
1.0%
쇼핑센터 1
 
1.0%
복합쇼핑몰 1
 
1.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)74.0%
Missing10
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean202578.37
Minimum200509.66
Maximum205365.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-30T04:47:21.375995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200509.66
5-th percentile200735.24
Q1201515.58
median202397.67
Q3203997.58
95-th percentile205020.61
Maximum205365.36
Range4855.6975
Interquartile range (IQR)2482.0009

Descriptive statistics

Standard deviation1411.6983
Coefficient of variation (CV)0.0069686528
Kurtosis-0.98908251
Mean202578.37
Median Absolute Deviation (MAD)953.19008
Skewness0.47376923
Sum10128918
Variance1992892.1
MonotonicityNot monotonic
2024-04-30T04:47:21.493030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
202555.30089577 5
 
8.3%
204367.347787613 3
 
5.0%
200841.726990037 3
 
5.0%
202667.468802014 2
 
3.3%
201912.435615622 2
 
3.3%
204407.250844173 2
 
3.3%
203353.798850162 2
 
3.3%
205020.608686581 2
 
3.3%
201852.588541848 1
 
1.7%
204208.631200867 1
 
1.7%
Other values (27) 27
45.0%
(Missing) 10
 
16.7%
ValueCountFrequency (%)
200509.660547343 1
 
1.7%
200571.15381745 1
 
1.7%
200729.859590291 1
 
1.7%
200741.814526594 1
 
1.7%
200841.726990037 3
5.0%
201336.750500414 1
 
1.7%
201358.893989884 1
 
1.7%
201447.418693099 1
 
1.7%
201501.474496909 1
 
1.7%
201509.0 1
 
1.7%
ValueCountFrequency (%)
205365.358044271 1
 
1.7%
205254.262597746 1
 
1.7%
205020.608686581 2
3.3%
204582.680269555 1
 
1.7%
204411.779055457 1
 
1.7%
204407.250844173 2
3.3%
204367.347787613 3
5.0%
204208.631200867 1
 
1.7%
204162.777672643 1
 
1.7%
203502.004139568 1
 
1.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct39
Distinct (%)78.0%
Missing10
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean455830.7
Minimum453158
Maximum457844.35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-30T04:47:21.614030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453158
5-th percentile453905.58
Q1455504.48
median456219.2
Q3456504.19
95-th percentile456783.77
Maximum457844.35
Range4686.348
Interquartile range (IQR)999.71044

Descriptive statistics

Standard deviation1053.4998
Coefficient of variation (CV)0.0023111645
Kurtosis0.35583955
Mean455830.7
Median Absolute Deviation (MAD)513.74102
Skewness-0.8414674
Sum22791535
Variance1109861.7
MonotonicityNot monotonic
2024-04-30T04:47:21.730934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
456503.066230481 4
 
6.7%
456732.945005445 3
 
5.0%
455858.920803881 2
 
3.3%
455775.861032353 2
 
3.3%
456638.194541249 2
 
3.3%
454721.505180141 2
 
3.3%
455765.417145198 2
 
3.3%
456783.766604012 2
 
3.3%
455598.947533777 1
 
1.7%
457844.348010616 1
 
1.7%
Other values (29) 29
48.3%
(Missing) 10
 
16.7%
ValueCountFrequency (%)
453158.0 1
1.7%
453162.376311852 1
1.7%
453868.720308 1
1.7%
453950.640893998 1
1.7%
454098.610861527 1
1.7%
454358.426908509 1
1.7%
454439.085102224 1
1.7%
454477.103343093 1
1.7%
454721.505180141 2
3.3%
454873.825379802 1
1.7%
ValueCountFrequency (%)
457844.348010616 1
 
1.7%
457664.961911112 1
 
1.7%
456783.766604012 2
3.3%
456753.565643 1
 
1.7%
456753.488817165 1
 
1.7%
456732.945005445 3
5.0%
456638.194541249 2
3.3%
456508.495239726 1
 
1.7%
456504.561867278 1
 
1.7%
456503.066230481 4
6.7%

점포구분명
Categorical

Distinct3
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
<NA>
36 
대규모점포
15 
준대규모점포
9 

Length

Max length6
Median length4
Mean length4.55
Min length4

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> 36
60.0%
대규모점포 15
25.0%
준대규모점포 9
 
15.0%

Length

2024-04-30T04:47:21.866427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T04:47:21.961114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
60.0%
대규모점포 15
25.0%
준대규모점포 9
 
15.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03070000196830700990750000119680814<NA>3폐업3폐업처리20080422<NA><NA><NA>02 91512543583.4<NA>서울특별시 성북구 장위동 60번지 1호<NA><NA>장석시장2008-10-07 11:10:31I2018-08-31 23:59:59.0시장205020.608687456783.766604<NA>
13070000199800000000750000219980522<NA>2휴업2휴업처리<NA><NA><NA><NA>02 9434044<NA><NA>서울특별시 성북구 장위동 68번지 1014호<NA><NA>코코마트2007-07-07 10:47:37I2018-08-31 23:59:59.0그 밖의 대규모점포204367.347788456732.945005<NA>
23070000200030700990750000119611204<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 성북구 보문동4가 1번지 1 호<NA><NA>보문시장2007-07-07 10:47:37I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
33070000200030700990750000219611224<NA>3폐업3폐업처리20081006<NA><NA><NA>02-941-35063701.61<NA>서울특별시 성북구 종암동 3번지 75 호<NA><NA>종암시장2008-10-07 10:21:30I2018-08-31 23:59:59.0시장<NA><NA><NA>
43070000200030700990750000319991207<NA>3폐업3폐업처리20080107<NA><NA><NA>92661221845.0<NA>서울특별시 성북구 삼선동5가 55번지 1 호<NA><NA>돈암시장2008-10-07 11:00:47I2018-08-31 23:59:59.0시장<NA><NA><NA>
53070000200030700990750000419990225<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 9135724<NA><NA>서울특별시 성북구 하월곡동 88번지 345호<NA><NA>미아시장2007-07-07 10:47:37I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
63070000200030700990750000619690219<NA>3폐업3폐업처리20080222<NA><NA><NA>02 91329822597.0<NA>서울특별시 성북구 하월곡동 16번지 1 호<NA><NA>월곡시장2008-10-07 11:05:21I2018-08-31 23:59:59.0시장<NA><NA><NA>
73070000200030700990750000719990121<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 9675571<NA><NA>서울특별시 성북구 석관동 270호<NA><NA>석관시장2007-07-07 10:47:37I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
83070000200030700990750000819700227<NA>3폐업3폐업처리20070330<NA><NA><NA>02 91448511426.32<NA>서울특별시 성북구 정릉동 405번지 1 호<NA><NA>정릉시장2008-10-07 10:55:58I2018-08-31 23:59:59.0시장200741.814527456247.253686<NA>
93070000200030700990750000919710522<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 9620580<NA><NA>서울특별시 성북구 석관동 338번지 18호<NA><NA>새석관시장2007-07-07 10:47:37I2018-08-31 23:59:59.0그 밖의 대규모점포204582.68027456210.836258<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
503070000201930702160750000120190524<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-926-64050.0<NA>서울특별시 성북구 돈암동 609번지 1호 스카이프라자상가서울특별시 성북구 성북로4길 52 (돈암동, 한신한진아파트)02831동소문스카이상가2019-05-24 17:01:59I2019-05-26 02:20:55.0그 밖의 대규모점포200841.72699454721.50518대규모점포
513070000201930702160750000220190529<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-912-91104612.41<NA>서울특별시 성북구 길음동 535번지8호, 535번지26호, 540번지2호<NA><NA>길음시장2019-05-29 17:30:00I2019-05-31 02:20:59.0그 밖의 대규모점포<NA><NA>대규모점포
523070000201930702160750000320190613<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-912-91105022.21<NA>서울특별시 성북구 길음동 535-8,535-26,540-2,540-7<NA><NA>길음시장2019-06-13 08:58:32I2019-06-15 02:21:11.0그 밖의 대규모점포<NA><NA>대규모점포
533070000202030702860750000120090907<NA>1영업/정상1정상영업<NA><NA><NA><NA>0292651330.0<NA>서울특별시 성북구 동소문동5가 59번지 2호 돈암제일시장 고객편의센터서울특별시 성북구 동소문로18길 18, 돈암제일시장 고객편의센터 (동소문동5가)02846돈암시장2020-06-10 13:03:30I2020-06-12 00:23:18.0시장201336.7505454358.426909대규모점포
543070000202130702860750000120140117<NA>1영업/정상1정상영업<NA><NA><NA><NA>070779991297194.0<NA>서울특별시 성북구 장위동 68-225서울특별시 성북구 장월로12길 41-1, 장위전통시장 상인회 (장위동)02769장위전통시장상인회2021-02-16 10:05:38I2021-02-18 00:23:22.0시장204407.250844456638.194541준대규모점포
553070000202230702860750000120100315<NA>1영업/정상1정상영업<NA><NA><NA><NA>070-4126-00989954.0<NA>서울특별시 성북구 정릉동 397-9 정릉시장 고객편의시설서울특별시 성북구 보국문로11길 18-19, 정릉시장 고객편의시설 (정릉동)02709정릉시장상인회2022-04-13 09:11:11U2021-12-03 23:05:00.0시장200729.85959456347.644835<NA>
563070000202230702860750000220220418<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-2006-2678186.6<NA>서울특별시 성북구 길음동 508-16서울특별시 성북구 숭인로8길 80, 롯데캐슬클라시아 상가 101~104호 (길음동)02730GS THE FRESH 성북클라시아점2022-04-18 14:16:02I2021-12-03 22:00:00.0구분없음202328.542538456302.296413<NA>
57307000020233070299075000012023-04-18<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-380-5042828.69<NA>서울특별시 성북구 길음동 1286-10 길음뉴타운9단지래미안 상가서울특별시 성북구 길음로7길 6, 길음뉴타운9단지래미안 상가 지하1층 B04~B08호 (길음동)02721이마트에브리데이 길음점2023-04-18 18:22:17I2022-12-03 22:00:00.0구분없음201912.435616455775.861032<NA>
58307000020233070299075000022023-04-18<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-380-5042828.69<NA>서울특별시 성북구 길음동 1286-10 길음뉴타운9단지래미안 상가서울특별시 성북구 길음로7길 6, 길음뉴타운9단지래미안 상가 지하1층 B04~B08호 (길음동)02721이마트에브리데이 길음점2023-04-20 09:38:33I2022-12-03 22:03:00.0구분없음201912.435616455775.861032<NA>
59307000020233070299075000032023-06-08<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-918-565180.49<NA>서울특별시 성북구 하월곡동 62-1서울특별시 성북구 오패산로4길 17 (하월곡동)02751롯데마켓 999 하월곡점2023-06-08 17:43:48I2022-12-05 23:00:00.0구분없음203353.79885455765.417145<NA>