Overview

Dataset statistics

Number of variables26
Number of observations42
Missing cells297
Missing cells (%)27.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory222.1 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
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-18713/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 42 (100.0%) missing valuesMissing
폐업일자 has 34 (81.0%) missing valuesMissing
휴업시작일자 has 42 (100.0%) missing valuesMissing
휴업종료일자 has 42 (100.0%) missing valuesMissing
재개업일자 has 42 (100.0%) missing valuesMissing
전화번호 has 1 (2.4%) missing valuesMissing
소재지면적 has 8 (19.0%) missing valuesMissing
소재지우편번호 has 26 (61.9%) missing valuesMissing
도로명주소 has 12 (28.6%) missing valuesMissing
도로명우편번호 has 30 (71.4%) missing valuesMissing
좌표정보(X) has 9 (21.4%) missing valuesMissing
좌표정보(Y) has 9 (21.4%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 6 (14.3%) zerosZeros

Reproduction

Analysis started2024-05-11 05:57:23.021506
Analysis finished2024-05-11 05:57:23.541101
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
3110000
42 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3110000
2nd row3110000
3rd row3110000
4th row3110000
5th row3110000

Common Values

ValueCountFrequency (%)
3110000 42
100.0%

Length

2024-05-11T14:57:23.625903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:23.811639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3110000 42
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0063824 × 1018
Minimum2.001311 × 1018
Maximum2.024311 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T14:57:24.004106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.001311 × 1018
5-th percentile2.001311 × 1018
Q12.001311 × 1018
median2.004811 × 1018
Q32.011311 × 1018
95-th percentile2.012311 × 1018
Maximum2.024311 × 1018
Range2.3000013 × 1016
Interquartile range (IQR)1.0000004 × 1016

Descriptive statistics

Standard deviation5.7100402 × 1015
Coefficient of variation (CV)0.0028459381
Kurtosis0.44497378
Mean2.0063824 × 1018
Median Absolute Deviation (MAD)3.5000011 × 1015
Skewness0.88292596
Sum-7.9656579 × 1018
Variance3.2604559 × 1031
MonotonicityStrictly increasing
2024-05-11T14:57:24.291310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
2001311008807500001 1
 
2.4%
2012311013107500001 1
 
2.4%
2007311011107500002 1
 
2.4%
2007311011107500003 1
 
2.4%
2009311013107500001 1
 
2.4%
2010311013107500001 1
 
2.4%
2011311013107500001 1
 
2.4%
2011311013107500002 1
 
2.4%
2011311013107500003 1
 
2.4%
2011311013107500004 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
2001311008807500001 1
2.4%
2001311008807500002 1
2.4%
2001311008807500003 1
2.4%
2001311008807500004 1
2.4%
2001311008807500005 1
2.4%
2001311008807500006 1
2.4%
2001311008807500007 1
2.4%
2001311008807500008 1
2.4%
2001311008807500009 1
2.4%
2001311008807500010 1
2.4%
ValueCountFrequency (%)
2024311021707500001 1
2.4%
2016311013107500001 1
2.4%
2012311013107500008 1
2.4%
2012311013107500007 1
2.4%
2012311013107500006 1
2.4%
2012311013107500005 1
2.4%
2012311013107500004 1
2.4%
2012311013107500003 1
2.4%
2012311013107500002 1
2.4%
2012311013107500001 1
2.4%

인허가일자
Date

Distinct38
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum1960-02-16 00:00:00
Maximum2024-05-01 00:00:00
2024-05-11T14:57:24.475832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:24.712781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
28 
3
8 
2
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
66.7%
3 8
 
19.0%
2 6
 
14.3%

Length

2024-05-11T14:57:24.987820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:25.164755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
66.7%
3 8
 
19.0%
2 6
 
14.3%

영업상태명
Categorical

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
영업/정상
28 
폐업
8 
휴업
6 

Length

Max length5
Median length5
Mean length4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 28
66.7%
폐업 8
 
19.0%
휴업 6
 
14.3%

Length

2024-05-11T14:57:25.334444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:25.540581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 28
66.7%
폐업 8
 
19.0%
휴업 6
 
14.3%

상세영업상태코드
Categorical

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
1
25 
3
8 
2
6 
BBBB
 
2
5
 
1

Length

Max length4
Median length1
Mean length1.1428571
Min length1

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
1 25
59.5%
3 8
 
19.0%
2 6
 
14.3%
BBBB 2
 
4.8%
5 1
 
2.4%

Length

2024-05-11T14:57:25.751808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:25.961792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
59.5%
3 8
 
19.0%
2 6
 
14.3%
bbbb 2
 
4.8%
5 1
 
2.4%

상세영업상태명
Categorical

Distinct5
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size468.0 B
정상영업
25 
폐업처리
8 
휴업처리
6 
<NA>
 
2
영업개시전
 
1

Length

Max length5
Median length4
Mean length4.0238095
Min length4

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 25
59.5%
폐업처리 8
 
19.0%
휴업처리 6
 
14.3%
<NA> 2
 
4.8%
영업개시전 1
 
2.4%

Length

2024-05-11T14:57:26.171096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:26.379472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 25
59.5%
폐업처리 8
 
19.0%
휴업처리 6
 
14.3%
na 2
 
4.8%
영업개시전 1
 
2.4%

폐업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing34
Missing (%)81.0%
Infinite0
Infinite (%)0.0%
Mean20165617
Minimum20091026
Maximum20220405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T14:57:26.583943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20091026
5-th percentile20101518
Q120150947
median20170517
Q320187843
95-th percentile20216806
Maximum20220405
Range129379
Interquartile range (IQR)36896

Descriptive statistics

Standard deviation42804.439
Coefficient of variation (CV)0.0021226447
Kurtosis-0.0079125632
Mean20165617
Median Absolute Deviation (MAD)24752
Skewness-0.60188644
Sum1.6132494 × 108
Variance1.83222 × 109
MonotonicityNot monotonic
2024-05-11T14:57:26.817112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20180417 1
 
2.4%
20170404 1
 
2.4%
20220405 1
 
2.4%
20091026 1
 
2.4%
20121004 1
 
2.4%
20170630 1
 
2.4%
20160928 1
 
2.4%
20210121 1
 
2.4%
(Missing) 34
81.0%
ValueCountFrequency (%)
20091026 1
2.4%
20121004 1
2.4%
20160928 1
2.4%
20170404 1
2.4%
20170630 1
2.4%
20180417 1
2.4%
20210121 1
2.4%
20220405 1
2.4%
ValueCountFrequency (%)
20220405 1
2.4%
20210121 1
2.4%
20180417 1
2.4%
20170630 1
2.4%
20170404 1
2.4%
20160928 1
2.4%
20121004 1
2.4%
20091026 1
2.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing42
Missing (%)100.0%
Memory size510.0 B

전화번호
Text

MISSING 

Distinct38
Distinct (%)92.7%
Missing1
Missing (%)2.4%
Memory size468.0 B
2024-05-11T14:57:27.139377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.536585
Min length7

Characters and Unicode

Total characters432
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

Unique35 ?
Unique (%)85.4%

Sample

1st row02 3025798
2nd row02 3855071
3rd row02 3868773
4th row02 3599323
5th row02 3557450
ValueCountFrequency (%)
02 22
32.4%
302-1666 2
 
2.9%
34845153 2
 
2.9%
22905853 2
 
2.9%
8546 1
 
1.5%
3025798 1
 
1.5%
386 1
 
1.5%
8547 1
 
1.5%
02-3417-2001 1
 
1.5%
69431052 1
 
1.5%
Other values (34) 34
50.0%
2024-05-11T14:57:27.680836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 66
15.3%
2 64
14.8%
5 54
12.5%
3 48
11.1%
33
7.6%
- 29
6.7%
6 29
6.7%
8 27
6.2%
1 25
 
5.8%
4 23
 
5.3%
Other values (2) 34
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
85.6%
Space Separator 33
 
7.6%
Dash Punctuation 29
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 66
17.8%
2 64
17.3%
5 54
14.6%
3 48
13.0%
6 29
7.8%
8 27
7.3%
1 25
 
6.8%
4 23
 
6.2%
9 17
 
4.6%
7 17
 
4.6%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 66
15.3%
2 64
14.8%
5 54
12.5%
3 48
11.1%
33
7.6%
- 29
6.7%
6 29
6.7%
8 27
6.2%
1 25
 
5.8%
4 23
 
5.3%
Other values (2) 34
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 66
15.3%
2 64
14.8%
5 54
12.5%
3 48
11.1%
33
7.6%
- 29
6.7%
6 29
6.7%
8 27
6.2%
1 25
 
5.8%
4 23
 
5.3%
Other values (2) 34
7.9%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct29
Distinct (%)85.3%
Missing8
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean4607.3926
Minimum0
Maximum57505
Zeros6
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T14:57:27.912004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1194.15
median667.225
Q33770.1925
95-th percentile16408.989
Maximum57505
Range57505
Interquartile range (IQR)3576.0425

Descriptive statistics

Standard deviation10336.341
Coefficient of variation (CV)2.2434253
Kurtosis21.799836
Mean4607.3926
Median Absolute Deviation (MAD)667.225
Skewness4.3799096
Sum156651.35
Variance1.0683995 × 108
MonotonicityNot monotonic
2024-05-11T14:57:28.148400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 6
 
14.3%
3417.4 1
 
2.4%
3887.79 1
 
2.4%
186.21 1
 
2.4%
57505.0 1
 
2.4%
191.9 1
 
2.4%
246.18 1
 
2.4%
330.0 1
 
2.4%
189.1 1
 
2.4%
255.8 1
 
2.4%
Other values (19) 19
45.2%
(Missing) 8
19.0%
ValueCountFrequency (%)
0.0 6
14.3%
186.21 1
 
2.4%
189.1 1
 
2.4%
191.9 1
 
2.4%
200.9 1
 
2.4%
246.18 1
 
2.4%
255.8 1
 
2.4%
272.0 1
 
2.4%
330.0 1
 
2.4%
434.1 1
 
2.4%
ValueCountFrequency (%)
57505.0 1
2.4%
16972.65 1
2.4%
16105.48 1
2.4%
10966.73 1
2.4%
9350.53 1
2.4%
6881.2 1
2.4%
6172.36 1
2.4%
5042.9 1
2.4%
3887.79 1
2.4%
3417.4 1
2.4%

소재지우편번호
Text

MISSING 

Distinct15
Distinct (%)93.8%
Missing26
Missing (%)61.9%
Memory size468.0 B
2024-05-11T14:57:28.417397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.375
Min length6

Characters and Unicode

Total characters102
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

Unique14 ?
Unique (%)87.5%

Sample

1st row122010
2nd row122010
3rd row122-090
4th row122-010
5th row122070
ValueCountFrequency (%)
122010 2
 
12.5%
122-090 1
 
6.2%
122-010 1
 
6.2%
122070 1
 
6.2%
122-819 1
 
6.2%
122-923 1
 
6.2%
122870 1
 
6.2%
122859 1
 
6.2%
122-856 1
 
6.2%
122959 1
 
6.2%
Other values (5) 5
31.2%
2024-05-11T14:57:28.930256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 33
32.4%
1 22
21.6%
0 12
 
11.8%
8 11
 
10.8%
9 8
 
7.8%
- 6
 
5.9%
5 4
 
3.9%
6 3
 
2.9%
7 2
 
2.0%
3 1
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
94.1%
Dash Punctuation 6
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 33
34.4%
1 22
22.9%
0 12
 
12.5%
8 11
 
11.5%
9 8
 
8.3%
5 4
 
4.2%
6 3
 
3.1%
7 2
 
2.1%
3 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 33
32.4%
1 22
21.6%
0 12
 
11.8%
8 11
 
10.8%
9 8
 
7.8%
- 6
 
5.9%
5 4
 
3.9%
6 3
 
2.9%
7 2
 
2.0%
3 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 33
32.4%
1 22
21.6%
0 12
 
11.8%
8 11
 
10.8%
9 8
 
7.8%
- 6
 
5.9%
5 4
 
3.9%
6 3
 
2.9%
7 2
 
2.0%
3 1
 
1.0%

지번주소
Text

Distinct38
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T14:57:29.347694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length23.333333
Min length18

Characters and Unicode

Total characters980
Distinct characters52
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

Unique34 ?
Unique (%)81.0%

Sample

1st row서울특별시 은평구 수색동 205번지 21 호
2nd row서울특별시 은평구 대조동 14번지 37 호
3rd row서울특별시 은평구 갈현동 424번지 16 호
4th row서울특별시 은평구 진관외동 424번지 1호
5th row서울특별시 은평구 대조동 14번지 24호
ValueCountFrequency (%)
서울특별시 42
19.4%
은평구 42
19.4%
1호 11
 
5.1%
호 10
 
4.6%
응암동 9
 
4.2%
불광동 5
 
2.3%
대조동 5
 
2.3%
역촌동 4
 
1.9%
14번지 4
 
1.9%
불광1동 3
 
1.4%
Other values (64) 81
37.5%
2024-05-11T14:57:30.109787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
22.3%
1 44
 
4.5%
구 44
 
4.5%
서 42
 
4.3%
평 42
 
4.3%
울 42
 
4.3%
동 42
 
4.3%
은 42
 
4.3%
시 42
 
4.3%
별 42
 
4.3%
Other values (42) 379
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 586
59.8%
Space Separator 219
 
22.3%
Decimal Number 173
 
17.7%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 44
 
7.5%
서 42
 
7.2%
평 42
 
7.2%
울 42
 
7.2%
동 42
 
7.2%
은 42
 
7.2%
시 42
 
7.2%
별 42
 
7.2%
특 42
 
7.2%
호 39
 
6.7%
Other values (30) 167
28.5%
Decimal Number
ValueCountFrequency (%)
1 44
25.4%
4 23
13.3%
2 23
13.3%
0 17
 
9.8%
3 16
 
9.2%
7 15
 
8.7%
5 12
 
6.9%
6 9
 
5.2%
9 8
 
4.6%
8 6
 
3.5%
Space Separator
ValueCountFrequency (%)
219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 586
59.8%
Common 394
40.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 44
 
7.5%
서 42
 
7.2%
평 42
 
7.2%
울 42
 
7.2%
동 42
 
7.2%
은 42
 
7.2%
시 42
 
7.2%
별 42
 
7.2%
특 42
 
7.2%
호 39
 
6.7%
Other values (30) 167
28.5%
Common
ValueCountFrequency (%)
219
55.6%
1 44
 
11.2%
4 23
 
5.8%
2 23
 
5.8%
0 17
 
4.3%
3 16
 
4.1%
7 15
 
3.8%
5 12
 
3.0%
6 9
 
2.3%
9 8
 
2.0%
Other values (2) 8
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 586
59.8%
ASCII 394
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
55.6%
1 44
 
11.2%
4 23
 
5.8%
2 23
 
5.8%
0 17
 
4.3%
3 16
 
4.1%
7 15
 
3.8%
5 12
 
3.0%
6 9
 
2.3%
9 8
 
2.0%
Other values (2) 8
 
2.0%
Hangul
ValueCountFrequency (%)
구 44
 
7.5%
서 42
 
7.2%
평 42
 
7.2%
울 42
 
7.2%
동 42
 
7.2%
은 42
 
7.2%
시 42
 
7.2%
별 42
 
7.2%
특 42
 
7.2%
호 39
 
6.7%
Other values (30) 167
28.5%

도로명주소
Text

MISSING 

Distinct26
Distinct (%)86.7%
Missing12
Missing (%)28.6%
Memory size468.0 B
2024-05-11T14:57:30.543153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length23
Mean length24
Min length22

Characters and Unicode

Total characters720
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)76.7%

Sample

1st row서울특별시 은평구 갈현로 300 (갈현동)
2nd row서울특별시 은평구 응암로 252 (응암동)
3rd row서울특별시 은평구 연서로17길 18-6 (갈현동)
4th row서울특별시 은평구 불광로 90-0 (불광동)
5th row서울특별시 은평구 진흥로1길 28(역촌동, 아그네스 풍림아이원)
ValueCountFrequency (%)
서울특별시 30
19.6%
은평구 30
19.6%
불광동 8
 
5.2%
통일로 7
 
4.6%
갈현동 5
 
3.3%
응암동 5
 
3.3%
불광로 5
 
3.3%
역촌동 3
 
2.0%
111 3
 
2.0%
은평로 3
 
2.0%
Other values (45) 54
35.3%
2024-05-11T14:57:31.233399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
 
17.1%
서 35
 
4.9%
평 34
 
4.7%
은 34
 
4.7%
구 31
 
4.3%
시 30
 
4.2%
별 30
 
4.2%
특 30
 
4.2%
로 30
 
4.2%
( 30
 
4.2%
Other values (55) 313
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 443
61.5%
Space Separator 123
 
17.1%
Decimal Number 89
 
12.4%
Open Punctuation 30
 
4.2%
Close Punctuation 30
 
4.2%
Other Punctuation 3
 
0.4%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 35
 
7.9%
평 34
 
7.7%
은 34
 
7.7%
구 31
 
7.0%
시 30
 
6.8%
별 30
 
6.8%
특 30
 
6.8%
로 30
 
6.8%
울 30
 
6.8%
동 30
 
6.8%
Other values (40) 129
29.1%
Decimal Number
ValueCountFrequency (%)
1 24
27.0%
2 16
18.0%
0 13
14.6%
8 9
 
10.1%
5 7
 
7.9%
7 5
 
5.6%
3 5
 
5.6%
4 4
 
4.5%
6 4
 
4.5%
9 2
 
2.2%
Space Separator
ValueCountFrequency (%)
123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 443
61.5%
Common 277
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 35
 
7.9%
평 34
 
7.7%
은 34
 
7.7%
구 31
 
7.0%
시 30
 
6.8%
별 30
 
6.8%
특 30
 
6.8%
로 30
 
6.8%
울 30
 
6.8%
동 30
 
6.8%
Other values (40) 129
29.1%
Common
ValueCountFrequency (%)
123
44.4%
( 30
 
10.8%
) 30
 
10.8%
1 24
 
8.7%
2 16
 
5.8%
0 13
 
4.7%
8 9
 
3.2%
5 7
 
2.5%
7 5
 
1.8%
3 5
 
1.8%
Other values (5) 15
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 443
61.5%
ASCII 277
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
44.4%
( 30
 
10.8%
) 30
 
10.8%
1 24
 
8.7%
2 16
 
5.8%
0 13
 
4.7%
8 9
 
3.2%
5 7
 
2.5%
7 5
 
1.8%
3 5
 
1.8%
Other values (5) 15
 
5.4%
Hangul
ValueCountFrequency (%)
서 35
 
7.9%
평 34
 
7.7%
은 34
 
7.7%
구 31
 
7.0%
시 30
 
6.8%
별 30
 
6.8%
특 30
 
6.8%
로 30
 
6.8%
울 30
 
6.8%
동 30
 
6.8%
Other values (40) 129
29.1%

도로명우편번호
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing30
Missing (%)71.4%
Memory size468.0 B
2024-05-11T14:57:31.534448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9166667
Min length5

Characters and Unicode

Total characters71
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

Unique12 ?
Unique (%)100.0%

Sample

1st row03405
2nd row122860
3rd row122897
4th row122-923
5th row122859
ValueCountFrequency (%)
03405 1
8.3%
122860 1
8.3%
122897 1
8.3%
122-923 1
8.3%
122859 1
8.3%
122-856 1
8.3%
122959 1
8.3%
122895 1
8.3%
122816 1
8.3%
122896 1
8.3%
Other values (2) 2
16.7%
2024-05-11T14:57:32.180901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 19
26.8%
1 10
14.1%
0 7
 
9.9%
8 7
 
9.9%
9 7
 
9.9%
3 5
 
7.0%
5 5
 
7.0%
6 5
 
7.0%
4 3
 
4.2%
- 2
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
97.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19
27.5%
1 10
14.5%
0 7
 
10.1%
8 7
 
10.1%
9 7
 
10.1%
3 5
 
7.2%
5 5
 
7.2%
6 5
 
7.2%
4 3
 
4.3%
7 1
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19
26.8%
1 10
14.1%
0 7
 
9.9%
8 7
 
9.9%
9 7
 
9.9%
3 5
 
7.0%
5 5
 
7.0%
6 5
 
7.0%
4 3
 
4.2%
- 2
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19
26.8%
1 10
14.1%
0 7
 
9.9%
8 7
 
9.9%
9 7
 
9.9%
3 5
 
7.0%
5 5
 
7.0%
6 5
 
7.0%
4 3
 
4.2%
- 2
 
2.8%

사업장명
Text

Distinct38
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
2024-05-11T14:57:32.551340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9
Min length3

Characters and Unicode

Total characters378
Distinct characters101
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

Unique35 ?
Unique (%)83.3%

Sample

1st row수일시장
2nd row대조시장
3rd row갈현시장
4th row진관시장
5th row불광시장(주)
ValueCountFrequency (%)
대림시장 3
 
4.8%
은평점 3
 
4.8%
주)이마트 3
 
4.8%
신세계이마트 2
 
3.2%
익스프레스 2
 
3.2%
서부종합시장 2
 
3.2%
불광점 2
 
3.2%
홈플러스(주)익스프레스 2
 
3.2%
역촌점 2
 
3.2%
홈플러스 1
 
1.6%
Other values (41) 41
65.1%
2024-05-11T14:57:33.133789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
 
5.6%
스 19
 
5.0%
점 18
 
4.8%
시 17
 
4.5%
장 17
 
4.5%
) 16
 
4.2%
( 16
 
4.2%
주 15
 
4.0%
데 10
 
2.6%
롯 9
 
2.4%
Other values (91) 220
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 313
82.8%
Space Separator 21
 
5.6%
Close Punctuation 16
 
4.2%
Open Punctuation 16
 
4.2%
Uppercase Letter 10
 
2.6%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 19
 
6.1%
점 18
 
5.8%
시 17
 
5.4%
장 17
 
5.4%
주 15
 
4.8%
데 10
 
3.2%
롯 9
 
2.9%
프 7
 
2.2%
대 7
 
2.2%
불 6
 
1.9%
Other values (80) 188
60.1%
Uppercase Letter
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
T 1
10.0%
G 1
10.0%
F 1
10.0%
R 1
10.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 313
82.8%
Common 55
 
14.6%
Latin 10
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 19
 
6.1%
점 18
 
5.8%
시 17
 
5.4%
장 17
 
5.4%
주 15
 
4.8%
데 10
 
3.2%
롯 9
 
2.9%
프 7
 
2.2%
대 7
 
2.2%
불 6
 
1.9%
Other values (80) 188
60.1%
Latin
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
T 1
10.0%
G 1
10.0%
F 1
10.0%
R 1
10.0%
Common
ValueCountFrequency (%)
21
38.2%
) 16
29.1%
( 16
29.1%
, 2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 313
82.8%
ASCII 65
 
17.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
32.3%
) 16
24.6%
( 16
24.6%
E 2
 
3.1%
, 2
 
3.1%
H 2
 
3.1%
S 2
 
3.1%
T 1
 
1.5%
G 1
 
1.5%
F 1
 
1.5%
Hangul
ValueCountFrequency (%)
스 19
 
6.1%
점 18
 
5.8%
시 17
 
5.4%
장 17
 
5.4%
주 15
 
4.8%
데 10
 
3.2%
롯 9
 
2.9%
프 7
 
2.2%
대 7
 
2.2%
불 6
 
1.9%
Other values (80) 188
60.1%

최종수정일자
Date

Distinct31
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2007-07-14 10:16:27
Maximum2024-05-01 15:22:20
2024-05-11T14:57:33.323758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:57:33.552113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size468.0 B
I
24 
U
18 

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 24
57.1%
U 18
42.9%

Length

2024-05-11T14:57:33.756392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:33.938125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 24
57.1%
u 18
42.9%

데이터갱신일자
Categorical

Distinct15
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
2018-08-31 23:59:59.0
23 
2023-12-02 22:09:00.0
4 
2021-11-01 22:04:00.0
 
2
2023-12-03 23:08:00.0
 
2
2021-12-18 02:40:00.0
 
1
Other values (10)
10 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique11 ?
Unique (%)26.2%

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 23
54.8%
2023-12-02 22:09:00.0 4
 
9.5%
2021-11-01 22:04:00.0 2
 
4.8%
2023-12-03 23:08:00.0 2
 
4.8%
2021-12-18 02:40:00.0 1
 
2.4%
2021-12-03 23:03:00.0 1
 
2.4%
2021-12-08 22:03:00.0 1
 
2.4%
2021-01-14 02:40:00.0 1
 
2.4%
2021-10-31 23:07:00.0 1
 
2.4%
2021-12-25 02:40:00.0 1
 
2.4%
Other values (5) 5
 
11.9%

Length

2024-05-11T14:57:34.112988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 23
27.4%
23:59:59.0 23
27.4%
02:40:00.0 5
 
6.0%
2023-12-02 4
 
4.8%
22:09:00.0 4
 
4.8%
2021-11-01 2
 
2.4%
22:04:00.0 2
 
2.4%
2023-12-03 2
 
2.4%
23:08:00.0 2
 
2.4%
2021-12-04 2
 
2.4%
Other values (15) 15
17.9%

업태구분명
Categorical

Distinct6
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size468.0 B
그 밖의 대규모점포
26 
대형마트
6 
쇼핑센터
5 
시장
3 
복합쇼핑몰
 
1

Length

Max length10
Median length10
Mean length7.5952381
Min length2

Unique

Unique2 ?
Unique (%)4.8%

Sample

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

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 26
61.9%
대형마트 6
 
14.3%
쇼핑센터 5
 
11.9%
시장 3
 
7.1%
복합쇼핑몰 1
 
2.4%
구분없음 1
 
2.4%

Length

2024-05-11T14:57:34.359117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:34.630907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 26
27.7%
밖의 26
27.7%
대규모점포 26
27.7%
대형마트 6
 
6.4%
쇼핑센터 5
 
5.3%
시장 3
 
3.2%
복합쇼핑몰 1
 
1.1%
구분없음 1
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)81.8%
Missing9
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean192851.67
Minimum190977.85
Maximum194003.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T14:57:34.797980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum190977.85
5-th percentile191724.97
Q1192655.76
median192859.34
Q3193042.52
95-th percentile193962.76
Maximum194003.88
Range3026.0333
Interquartile range (IQR)386.76291

Descriptive statistics

Standard deviation682.7055
Coefficient of variation (CV)0.0035400549
Kurtosis0.91583137
Mean192851.67
Median Absolute Deviation (MAD)203.58489
Skewness-0.47640105
Sum6364105.2
Variance466086.81
MonotonicityNot monotonic
2024-05-11T14:57:34.968775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
192882.837727443 3
 
7.1%
192773.974598512 2
 
4.8%
193035.279146132 2
 
4.8%
193661.732383169 2
 
4.8%
192661.661318718 2
 
4.8%
193936.125681025 1
 
2.4%
191844.913712646 1
 
2.4%
192655.756373115 1
 
2.4%
193083.765685506 1
 
2.4%
191953.940215578 1
 
2.4%
Other values (17) 17
40.5%
(Missing) 9
21.4%
ValueCountFrequency (%)
190977.850603548 1
2.4%
191545.050373675 1
2.4%
191844.913712646 1
2.4%
191953.940215578 1
2.4%
192012.208564616 1
2.4%
192534.656897366 1
2.4%
192563.874496397 1
2.4%
192640.073875 1
2.4%
192655.756373115 1
2.4%
192661.661318718 2
4.8%
ValueCountFrequency (%)
194003.88391829 1
2.4%
194002.701726955 1
2.4%
193936.125681025 1
2.4%
193792.984914301 1
2.4%
193661.732383169 2
4.8%
193600.888431741 1
2.4%
193083.765685506 1
2.4%
193042.519283201 1
2.4%
193035.279146132 2
4.8%
192998.202204135 1
2.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)81.8%
Missing9
Missing (%)21.4%
Infinite0
Infinite (%)0.0%
Mean456090.95
Minimum453037.79
Maximum459477.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2024-05-11T14:57:35.177725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453037.79
5-th percentile453594.84
Q1455340.54
median456379.19
Q3457260.74
95-th percentile457695.94
Maximum459477.21
Range6439.4214
Interquartile range (IQR)1920.1959

Descriptive statistics

Standard deviation1444.4597
Coefficient of variation (CV)0.0031670432
Kurtosis0.010517232
Mean456090.95
Median Absolute Deviation (MAD)1008.5801
Skewness-0.23602326
Sum15051002
Variance2086464
MonotonicityNot monotonic
2024-05-11T14:57:35.346294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
455340.54056388 3
 
7.1%
455630.884111772 2
 
4.8%
457365.911737494 2
 
4.8%
456379.193899276 2
 
4.8%
453828.585982771 2
 
4.8%
456673.805557751 1
 
2.4%
454908.495429711 1
 
2.4%
459477.20943887 1
 
2.4%
455978.010581693 1
 
2.4%
456960.687756827 1
 
2.4%
Other values (17) 17
40.5%
(Missing) 9
21.4%
ValueCountFrequency (%)
453037.787995874 1
 
2.4%
453244.229758597 1
 
2.4%
453828.585982771 2
4.8%
454664.166810326 1
 
2.4%
454678.898500315 1
 
2.4%
454908.495429711 1
 
2.4%
455177.704494531 1
 
2.4%
455340.54056388 3
7.1%
455370.61376951 1
 
2.4%
455630.884111772 2
4.8%
ValueCountFrequency (%)
459477.20943887 1
2.4%
457921.155872 1
2.4%
457545.793599332 1
2.4%
457479.99522553 1
2.4%
457459.367971725 1
2.4%
457365.911737494 2
4.8%
457275.285596868 1
2.4%
457260.736492005 1
2.4%
456960.687756827 1
2.4%
456957.233580498 1
2.4%

점포구분명
Categorical

Distinct3
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
<NA>
28 
대규모점포
8 
준대규모점포
6 

Length

Max length6
Median length4
Mean length4.4761905
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 28
66.7%
대규모점포 8
 
19.0%
준대규모점포 6
 
14.3%

Length

2024-05-11T14:57:35.559924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:57:35.735437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
66.7%
대규모점포 8
 
19.0%
준대규모점포 6
 
14.3%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03110000200131100880750000119600216<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 3025798<NA><NA>서울특별시 은평구 수색동 205번지 21 호<NA><NA>수일시장2007-07-14 10:16:27I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
13110000200131100880750000219630527<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>02 3855071<NA><NA>서울특별시 은평구 대조동 14번지 37 호<NA><NA>대조시장2007-07-14 10:16:27I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
23110000200131100880750000319650531<NA>3폐업3폐업처리20180417<NA><NA><NA>02 38687730.0<NA>서울특별시 은평구 갈현동 424번지 16 호서울특별시 은평구 갈현로 300 (갈현동)<NA>갈현시장2018-04-17 17:49:39I2018-08-31 23:59:59.0그 밖의 대규모점포192640.073875457921.155872대규모점포
33110000200131100880750000419681014<NA>2휴업2휴업처리<NA><NA><NA><NA>02 35993230.0<NA>서울특별시 은평구 진관외동 424번지 1호<NA><NA>진관시장2007-07-14 10:16:27I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
43110000200131100880750000519700123<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>02 3557450<NA><NA>서울특별시 은평구 대조동 14번지 24호<NA><NA>불광시장(주)2007-07-14 10:16:27I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
53110000200131100880750000619661207<NA>3폐업3폐업처리20170404<NA><NA><NA>11111110.0<NA>서울특별시 은평구 응암동 74번지 7 호<NA><NA>녹번시장2017-04-05 10:58:55I2018-08-31 23:59:59.0그 밖의 대규모점포193792.984914455370.61377대규모점포
63110000200131100880750000719700912<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-355-0727649.0<NA>서울특별시 은평구 응암동 427번지 126호서울특별시 은평구 응암로 252 (응암동)<NA>응암시장2021-12-16 18:26:52U2021-12-18 02:40:00.0그 밖의 대규모점포192738.381117454678.8985대규모점포
73110000200131100880750000820220404<NA>3폐업3폐업처리20220405<NA><NA><NA>02-352-80403417.4<NA>서울특별시 은평구 갈현동 467번지 1호서울특별시 은평구 연서로17길 18-6 (갈현동)<NA>역촌중앙시장2022-04-11 13:10:32U2021-12-03 23:03:00.0그 밖의 대규모점포192534.656897456773.714885<NA>
83110000200131100880750000919701224<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3157-15663887.79<NA>서울특별시 은평구 불광동 631번지 1호서울특별시 은평구 불광로 90-0 (불광동)<NA>대호프라자상가2022-09-21 10:33:14U2021-12-08 22:03:00.0복합쇼핑몰194002.701727456937.54251<NA>
93110000200131100880750001019710923<NA>3폐업3폐업처리20091026<NA><NA><NA>02 35964660.0<NA>서울특별시 은평구 역촌동 31-6 아그네스 풍림아이원서울특별시 은평구 진흥로1길 28(역촌동, 아그네스 풍림아이원)03405서부종합시장2022-12-22 14:27:34U2021-11-01 22:04:00.0시장192773.974599455630.884112<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
323110000201231101310750000120110916<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 229058531508.4122859서울특별시 은평구 불광1동 308번지 1호서울특별시 은평구 통일로 842 (불광동)122859롯데쇼핑(주)롯데슈퍼범서점2021-12-23 19:38:07U2021-12-25 02:40:00.0그 밖의 대규모점포193035.279146457365.911737준대규모점포
33311000020123110131075000022011-12-19<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-356-8545200.9122-856서울특별시 은평구 불광1동 239번지 9호서울특별시 은평구 불광로 121 (불광동)122-856홈플러스(주)익스프레스 불광점2024-03-27 14:01:00U2023-12-02 22:09:00.0그 밖의 대규모점포194003.883918457260.736492<NA>
343110000201231101310750000320110916<NA>3폐업3폐업처리20170630<NA><NA><NA>02-388-5601434.1122959서울특별시 은평구 갈현2동 456번지 27호서울특별시 은평구 연서로 215 (갈현동)122959롯데쇼핑(주)롯데슈퍼갈현점2017-07-31 09:17:13I2018-08-31 23:59:59.0그 밖의 대규모점포192809.366974457275.285597준대규모점포
353110000201231101310750000420110916<NA>3폐업3폐업처리20160928<NA><NA><NA>352-5601255.8122808서울특별시 은평구 갈현1동 395번지 6호서울특별시 은평구 통일로 867 (갈현동)<NA>롯데쇼핑(주)롯데슈퍼연신내점2016-09-28 16:27:37I2018-08-31 23:59:59.0그 밖의 대규모점포192859.341264457545.793599준대규모점포
36311000020123110131075000052012-02-06<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-352-8546189.1122-881서울특별시 은평구 신사1동 20번지 7호서울특별시 은평구 갈현로 10 (신사동)<NA>홈플러스(주)익스프레스 신사점2024-03-27 14:55:29U2023-12-02 22:09:00.0그 밖의 대규모점포192012.208565455177.704495<NA>
373110000201231101310750000620120321<NA>3폐업3폐업처리20210121<NA><NA><NA>02 383 8546330.0122895서울특별시 은평구 역촌동 14번지 7호서울특별시 은평구 서오릉로 95 (역촌동)122895홈플러스(주) 익스프레스 역촌점2021-01-25 13:31:27U2021-01-27 02:40:00.0그 밖의 대규모점포192920.728013456218.21595준대규모점포
383110000201231101310750000720120323<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-359-8547246.18122816서울특별시 은평구 갈현2동 527번지 13호서울특별시 은평구 서오릉로 222 (갈현동)122816홈플러스 익스프레스 갈현점2021-04-30 14:23:03U2021-05-02 02:40:00.0그 밖의 대규모점포191953.940216456960.687757준대규모점포
393110000201231101310750000820120320<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 22905853191.9122896서울특별시 은평구 역촌동 17번지 1호서울특별시 은평구 진흥로 103 (역촌동)122896롯데쇼핑(주) 롯데슈퍼 역촌점2022-05-13 16:53:17U2021-12-04 23:05:00.0그 밖의 대규모점포193083.765686455978.010582<NA>
403110000201631101310750000120160427<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6975-590157505.0<NA>서울특별시 은평구 진관동 79번지 15호서울특별시 은평구 통일로 1050 (진관동, 롯데몰은평점)03306롯데몰 은평2022-05-23 16:29:49U2021-12-04 22:05:00.0쇼핑센터192655.756373459477.209439<NA>
41311000020243110217075000012024-05-01<NA>1영업/정상5영업개시전<NA><NA><NA><NA><NA>186.21<NA>서울특별시 은평구 신사동 228-5서울특별시 은평구 가좌로 331, 1층 (신사동)03440GS THE FRESH 은평가좌점2024-05-01 15:22:20I2023-12-05 00:03:00.0구분없음191844.913713454908.49543<NA>