Overview

Dataset statistics

Number of variables26
Number of observations46
Missing cells236
Missing cells (%)19.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory222.9 B

Variable types

Categorical9
Numeric5
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
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-18717/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 is highly imbalanced (84.9%)Imbalance
인허가취소일자 has 46 (100.0%) missing valuesMissing
폐업일자 has 35 (76.1%) missing valuesMissing
휴업시작일자 has 46 (100.0%) missing valuesMissing
휴업종료일자 has 46 (100.0%) missing valuesMissing
전화번호 has 3 (6.5%) missing valuesMissing
소재지면적 has 3 (6.5%) missing valuesMissing
소재지우편번호 has 24 (52.2%) missing valuesMissing
지번주소 has 2 (4.3%) missing valuesMissing
도로명주소 has 12 (26.1%) missing valuesMissing
도로명우편번호 has 13 (28.3%) missing valuesMissing
좌표정보(X) has 3 (6.5%) missing valuesMissing
좌표정보(Y) has 3 (6.5%) 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 9 (19.6%) zerosZeros

Reproduction

Analysis started2024-05-11 03:41:37.941940
Analysis finished2024-05-11 03:41:38.804213
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
3150000
46 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3150000
2nd row3150000
3rd row3150000
4th row3150000
5th row3150000

Common Values

ValueCountFrequency (%)
3150000 46
100.0%

Length

2024-05-11T03:41:38.936097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:39.234541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3150000 46
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0104889 × 1018
Minimum1.987315 × 1018
Maximum2.024315 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T03:41:39.565015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.987315 × 1018
5-th percentile1.999565 × 1018
Q12.005565 × 1018
median2.011315 × 1018
Q32.014065 × 1018
95-th percentile2.023315 × 1018
Maximum2.024315 × 1018
Range3.7000003 × 1016
Interquartile range (IQR)8.5000045 × 1015

Descriptive statistics

Standard deviation7.276462 × 1015
Coefficient of variation (CV)0.00361925
Kurtosis1.4449391
Mean2.0104889 × 1018
Median Absolute Deviation (MAD)4.5000033 × 1015
Skewness-0.58247715
Sum2.4877026 × 1017
Variance5.2946899 × 1031
MonotonicityStrictly increasing
2024-05-11T03:41:40.030665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1987315016607500006 1
 
2.2%
2014315014507500002 1
 
2.2%
2012315014507500001 1
 
2.2%
2012315014507500002 1
 
2.2%
2012315014507500003 1
 
2.2%
2012315014507500004 1
 
2.2%
2012315014507500005 1
 
2.2%
2012315014507500006 1
 
2.2%
2012315014507500007 1
 
2.2%
2013315014507500001 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1987315016607500006 1
2.2%
1995315007407500001 1
2.2%
1999315010007500001 1
2.2%
2000315010007500001 1
2.2%
2002315007407500001 1
2.2%
2003315010007500030 1
2.2%
2004315010007500001 1
2.2%
2004315010007500033 1
2.2%
2004315010007500034 1
2.2%
2004315010007500035 1
2.2%
ValueCountFrequency (%)
2024315020007500001 1
2.2%
2023315020007500003 1
2.2%
2023315020007500002 1
2.2%
2023315020007500001 1
2.2%
2018315018607500001 1
2.2%
2017315018607500004 1
2.2%
2017315018607500003 1
2.2%
2017315018607500002 1
2.2%
2017315018607500001 1
2.2%
2015315016607500001 1
2.2%

인허가일자
Date

Distinct40
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum1970-08-20 00:00:00
Maximum2024-01-10 00:00:00
2024-05-11T03:41:40.438376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:41:40.820387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
1
28 
3
11 
2
7 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
60.9%
3 11
 
23.9%
2 7
 
15.2%

Length

2024-05-11T03:41:41.160563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:41.428167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
60.9%
3 11
 
23.9%
2 7
 
15.2%

영업상태명
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
영업/정상
28 
폐업
11 
휴업
7 

Length

Max length5
Median length5
Mean length3.826087
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 28
60.9%
폐업 11
 
23.9%
휴업 7
 
15.2%

Length

2024-05-11T03:41:41.766018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:42.096292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 28
60.9%
폐업 11
 
23.9%
휴업 7
 
15.2%

상세영업상태코드
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
1
27 
3
11 
2
7 
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
1 27
58.7%
3 11
23.9%
2 7
 
15.2%
5 1
 
2.2%

Length

2024-05-11T03:41:42.456273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:42.833399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 27
58.7%
3 11
23.9%
2 7
 
15.2%
5 1
 
2.2%

상세영업상태명
Categorical

Distinct4
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
정상영업
27 
폐업처리
11 
휴업처리
7 
영업개시전
 
1

Length

Max length5
Median length4
Mean length4.0217391
Min length4

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 27
58.7%
폐업처리 11
23.9%
휴업처리 7
 
15.2%
영업개시전 1
 
2.2%

Length

2024-05-11T03:41:43.370862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:43.803561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 27
58.7%
폐업처리 11
23.9%
휴업처리 7
 
15.2%
영업개시전 1
 
2.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)100.0%
Missing35
Missing (%)76.1%
Infinite0
Infinite (%)0.0%
Mean20165306
Minimum20120201
Maximum20221004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T03:41:44.185148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20120201
5-th percentile20120464
Q120130776
median20160401
Q320196169
95-th percentile20220966
Maximum20221004
Range100803
Interquartile range (IQR)65393

Descriptive statistics

Standard deviation39989.695
Coefficient of variation (CV)0.0019830939
Kurtosis-1.5532328
Mean20165306
Median Absolute Deviation (MAD)39671
Skewness0.2871648
Sum2.2181837 × 108
Variance1.5991757 × 109
MonotonicityNot monotonic
2024-05-11T03:41:44.643877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20221004 1
 
2.2%
20220927 1
 
2.2%
20120201 1
 
2.2%
20141016 1
 
2.2%
20181226 1
 
2.2%
20120727 1
 
2.2%
20120730 1
 
2.2%
20211112 1
 
2.2%
20140822 1
 
2.2%
20160401 1
 
2.2%
(Missing) 35
76.1%
ValueCountFrequency (%)
20120201 1
2.2%
20120727 1
2.2%
20120730 1
2.2%
20140822 1
2.2%
20141016 1
2.2%
20160401 1
2.2%
20180201 1
2.2%
20181226 1
2.2%
20211112 1
2.2%
20220927 1
2.2%
ValueCountFrequency (%)
20221004 1
2.2%
20220927 1
2.2%
20211112 1
2.2%
20181226 1
2.2%
20180201 1
2.2%
20160401 1
2.2%
20141016 1
2.2%
20140822 1
2.2%
20120730 1
2.2%
20120727 1
2.2%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing46
Missing (%)100.0%
Memory size546.0 B

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
45 
20030403
 
1

Length

Max length8
Median length4
Mean length4.0869565
Min length4

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 45
97.8%
20030403 1
 
2.2%

Length

2024-05-11T03:41:45.307500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:45.693887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 45
97.8%
20030403 1
 
2.2%

전화번호
Text

MISSING 

Distinct43
Distinct (%)100.0%
Missing3
Missing (%)6.5%
Memory size500.0 B
2024-05-11T03:41:46.175784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.465116
Min length9

Characters and Unicode

Total characters493
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

Unique43 ?
Unique (%)100.0%

Sample

1st row02-2602-5757
2nd row0226002002
3rd row02 26622751
4th row0236649400
5th row0221661052
ValueCountFrequency (%)
02 2
 
4.3%
02-2602-5757 1
 
2.2%
02-6343-5000 1
 
2.2%
0002-2698-8550 1
 
2.2%
02-2605-3334 1
 
2.2%
000226055602 1
 
2.2%
000226623651 1
 
2.2%
000222813651 1
 
2.2%
000226595601 1
 
2.2%
000236625605 1
 
2.2%
Other values (35) 35
76.1%
2024-05-11T03:41:47.396829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 126
25.6%
2 97
19.7%
6 85
17.2%
1 36
 
7.3%
- 35
 
7.1%
5 34
 
6.9%
3 29
 
5.9%
4 13
 
2.6%
7 12
 
2.4%
8 12
 
2.4%
Other values (2) 14
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 454
92.1%
Dash Punctuation 35
 
7.1%
Space Separator 4
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 126
27.8%
2 97
21.4%
6 85
18.7%
1 36
 
7.9%
5 34
 
7.5%
3 29
 
6.4%
4 13
 
2.9%
7 12
 
2.6%
8 12
 
2.6%
9 10
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 126
25.6%
2 97
19.7%
6 85
17.2%
1 36
 
7.3%
- 35
 
7.1%
5 34
 
6.9%
3 29
 
5.9%
4 13
 
2.6%
7 12
 
2.4%
8 12
 
2.4%
Other values (2) 14
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 126
25.6%
2 97
19.7%
6 85
17.2%
1 36
 
7.3%
- 35
 
7.1%
5 34
 
6.9%
3 29
 
5.9%
4 13
 
2.6%
7 12
 
2.4%
8 12
 
2.4%
Other values (2) 14
 
2.8%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)81.4%
Missing3
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean6997.0107
Minimum0
Maximum77670
Zeros9
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T03:41:47.990415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1199.2
median735.3
Q34363.15
95-th percentile33309.789
Maximum77670
Range77670
Interquartile range (IQR)4163.95

Descriptive statistics

Standard deviation14729.313
Coefficient of variation (CV)2.1050866
Kurtosis12.997526
Mean6997.0107
Median Absolute Deviation (MAD)735.3
Skewness3.3560633
Sum300871.46
Variance2.1695267 × 108
MonotonicityNot monotonic
2024-05-11T03:41:48.573196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 9
 
19.6%
330.0 1
 
2.2%
317.0 1
 
2.2%
476.0 1
 
2.2%
348.4 1
 
2.2%
461.2 1
 
2.2%
847.4 1
 
2.2%
244.6 1
 
2.2%
3385.1 1
 
2.2%
15317.0 1
 
2.2%
Other values (25) 25
54.3%
(Missing) 3
 
6.5%
ValueCountFrequency (%)
0.0 9
19.6%
117.0 1
 
2.2%
162.4 1
 
2.2%
236.0 1
 
2.2%
244.6 1
 
2.2%
286.2 1
 
2.2%
317.0 1
 
2.2%
330.0 1
 
2.2%
348.4 1
 
2.2%
410.0 1
 
2.2%
ValueCountFrequency (%)
77670.0 1
2.2%
45186.22 1
2.2%
34547.21 1
2.2%
22173.0 1
2.2%
18461.49 1
2.2%
17623.04 1
2.2%
17262.29 1
2.2%
15317.0 1
2.2%
10037.0 1
2.2%
8762.0 1
2.2%

소재지우편번호
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing24
Missing (%)52.2%
Memory size500.0 B
2024-05-11T03:41:49.229746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3636364
Min length6

Characters and Unicode

Total characters140
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

Unique22 ?
Unique (%)100.0%

Sample

1st row157-840
2nd row157847
3rd row157-202
4th row157835
5th row157823
ValueCountFrequency (%)
157-840 1
 
4.5%
157847 1
 
4.5%
157220 1
 
4.5%
157925 1
 
4.5%
157914 1
 
4.5%
157-846 1
 
4.5%
157-703 1
 
4.5%
157040 1
 
4.5%
157863 1
 
4.5%
157-881 1
 
4.5%
Other values (12) 12
54.5%
2024-05-11T03:41:50.175406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 26
18.6%
5 26
18.6%
7 24
17.1%
0 12
8.6%
2 12
8.6%
8 11
7.9%
- 8
 
5.7%
4 6
 
4.3%
3 6
 
4.3%
9 6
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132
94.3%
Dash Punctuation 8
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 26
19.7%
5 26
19.7%
7 24
18.2%
0 12
9.1%
2 12
9.1%
8 11
8.3%
4 6
 
4.5%
3 6
 
4.5%
9 6
 
4.5%
6 3
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 140
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 26
18.6%
5 26
18.6%
7 24
17.1%
0 12
8.6%
2 12
8.6%
8 11
7.9%
- 8
 
5.7%
4 6
 
4.3%
3 6
 
4.3%
9 6
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 26
18.6%
5 26
18.6%
7 24
17.1%
0 12
8.6%
2 12
8.6%
8 11
7.9%
- 8
 
5.7%
4 6
 
4.3%
3 6
 
4.3%
9 6
 
4.3%

지번주소
Text

MISSING 

Distinct42
Distinct (%)95.5%
Missing2
Missing (%)4.3%
Memory size500.0 B
2024-05-11T03:41:50.804055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length28
Mean length23.590909
Min length17

Characters and Unicode

Total characters1038
Distinct characters69
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)90.9%

Sample

1st row서울특별시 강서구 화곡동 370번지 76호
2nd row서울특별시 강서구 화곡동 1095호
3rd row서울특별시 강서구 방화동 620호
4th row서울특별시 강서구 가양동 18번지 24호
5th row서울특별시 강서구 방화동 567번지 4호
ValueCountFrequency (%)
서울특별시 44
20.1%
강서구 44
20.1%
등촌동 6
 
2.7%
염창동 5
 
2.3%
화곡동 5
 
2.3%
가양동 5
 
2.3%
방화동 5
 
2.3%
마곡동 4
 
1.8%
1호 4
 
1.8%
8호 3
 
1.4%
Other values (74) 94
42.9%
2024-05-11T03:41:51.969399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
197
19.0%
서 88
 
8.5%
동 46
 
4.4%
시 45
 
4.3%
울 44
 
4.2%
특 44
 
4.2%
별 44
 
4.2%
강 44
 
4.2%
구 44
 
4.2%
지 37
 
3.6%
Other values (59) 405
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 643
61.9%
Space Separator 197
 
19.0%
Decimal Number 194
 
18.7%
Dash Punctuation 3
 
0.3%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 88
13.7%
동 46
 
7.2%
시 45
 
7.0%
울 44
 
6.8%
특 44
 
6.8%
별 44
 
6.8%
강 44
 
6.8%
구 44
 
6.8%
지 37
 
5.8%
번 35
 
5.4%
Other values (46) 172
26.7%
Decimal Number
ValueCountFrequency (%)
1 34
17.5%
7 25
12.9%
2 24
12.4%
6 23
11.9%
9 17
8.8%
8 16
8.2%
5 15
7.7%
3 15
7.7%
4 14
7.2%
0 11
 
5.7%
Space Separator
ValueCountFrequency (%)
197
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 643
61.9%
Common 394
38.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 88
13.7%
동 46
 
7.2%
시 45
 
7.0%
울 44
 
6.8%
특 44
 
6.8%
별 44
 
6.8%
강 44
 
6.8%
구 44
 
6.8%
지 37
 
5.8%
번 35
 
5.4%
Other values (46) 172
26.7%
Common
ValueCountFrequency (%)
197
50.0%
1 34
 
8.6%
7 25
 
6.3%
2 24
 
6.1%
6 23
 
5.8%
9 17
 
4.3%
8 16
 
4.1%
5 15
 
3.8%
3 15
 
3.8%
4 14
 
3.6%
Other values (2) 14
 
3.6%
Latin
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 643
61.9%
ASCII 394
38.0%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
197
50.0%
1 34
 
8.6%
7 25
 
6.3%
2 24
 
6.1%
6 23
 
5.8%
9 17
 
4.3%
8 16
 
4.1%
5 15
 
3.8%
3 15
 
3.8%
4 14
 
3.6%
Other values (2) 14
 
3.6%
Hangul
ValueCountFrequency (%)
서 88
13.7%
동 46
 
7.2%
시 45
 
7.0%
울 44
 
6.8%
특 44
 
6.8%
별 44
 
6.8%
강 44
 
6.8%
구 44
 
6.8%
지 37
 
5.8%
번 35
 
5.4%
Other values (46) 172
26.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct33
Distinct (%)97.1%
Missing12
Missing (%)26.1%
Memory size500.0 B
2024-05-11T03:41:52.771722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length36
Mean length29.970588
Min length14

Characters and Unicode

Total characters1019
Distinct characters115
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)94.1%

Sample

1st row서울특별시 강서구 월정로30길 69 (화곡동)
2nd row서울특별시 양천로 559 (가양이마트(E-MART))
3rd row서울특별시 강서구 화곡로 398 (등촌동)
4th row서울특별시 강서구 방화동로 126 (방화동)
5th row서울특별시 강서구 공항대로71길 49 (염창동)
ValueCountFrequency (%)
서울특별시 34
 
17.1%
강서구 32
 
16.1%
화곡동 8
 
4.0%
양천로 6
 
3.0%
강서로 5
 
2.5%
마곡동 5
 
2.5%
염창동 5
 
2.5%
등촌동 4
 
2.0%
방화동 4
 
2.0%
1층 4
 
2.0%
Other values (78) 92
46.2%
2024-05-11T03:41:53.840271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
176
 
17.3%
서 76
 
7.5%
강 40
 
3.9%
1 36
 
3.5%
동 36
 
3.5%
( 36
 
3.5%
) 36
 
3.5%
시 35
 
3.4%
특 35
 
3.4%
별 35
 
3.4%
Other values (105) 478
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
58.1%
Space Separator 176
 
17.3%
Decimal Number 145
 
14.2%
Open Punctuation 37
 
3.6%
Close Punctuation 37
 
3.6%
Other Punctuation 18
 
1.8%
Uppercase Letter 7
 
0.7%
Dash Punctuation 4
 
0.4%
Math Symbol 2
 
0.2%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 76
 
12.8%
강 40
 
6.8%
동 36
 
6.1%
시 35
 
5.9%
특 35
 
5.9%
별 35
 
5.9%
구 34
 
5.7%
울 34
 
5.7%
로 31
 
5.2%
곡 22
 
3.7%
Other values (79) 214
36.1%
Decimal Number
ValueCountFrequency (%)
1 36
24.8%
6 16
11.0%
7 14
 
9.7%
4 13
 
9.0%
3 12
 
8.3%
9 12
 
8.3%
8 11
 
7.6%
0 11
 
7.6%
5 10
 
6.9%
2 10
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
C 1
14.3%
P 1
14.3%
E 1
14.3%
M 1
14.3%
A 1
14.3%
R 1
14.3%
T 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 36
97.3%
[ 1
 
2.7%
Close Punctuation
ValueCountFrequency (%)
) 36
97.3%
] 1
 
2.7%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
58.1%
Common 419
41.1%
Latin 8
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 76
 
12.8%
강 40
 
6.8%
동 36
 
6.1%
시 35
 
5.9%
특 35
 
5.9%
별 35
 
5.9%
구 34
 
5.7%
울 34
 
5.7%
로 31
 
5.2%
곡 22
 
3.7%
Other values (79) 214
36.1%
Common
ValueCountFrequency (%)
176
42.0%
1 36
 
8.6%
( 36
 
8.6%
) 36
 
8.6%
, 18
 
4.3%
6 16
 
3.8%
7 14
 
3.3%
4 13
 
3.1%
3 12
 
2.9%
9 12
 
2.9%
Other values (8) 50
 
11.9%
Latin
ValueCountFrequency (%)
Ⅱ 1
12.5%
C 1
12.5%
P 1
12.5%
E 1
12.5%
M 1
12.5%
A 1
12.5%
R 1
12.5%
T 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
58.1%
ASCII 426
41.8%
Number Forms 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
176
41.3%
1 36
 
8.5%
( 36
 
8.5%
) 36
 
8.5%
, 18
 
4.2%
6 16
 
3.8%
7 14
 
3.3%
4 13
 
3.1%
3 12
 
2.8%
9 12
 
2.8%
Other values (15) 57
 
13.4%
Hangul
ValueCountFrequency (%)
서 76
 
12.8%
강 40
 
6.8%
동 36
 
6.1%
시 35
 
5.9%
특 35
 
5.9%
별 35
 
5.9%
구 34
 
5.7%
울 34
 
5.7%
로 31
 
5.2%
곡 22
 
3.7%
Other values (79) 214
36.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct31
Distinct (%)93.9%
Missing13
Missing (%)28.3%
Memory size500.0 B
2024-05-11T03:41:54.411344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.969697
Min length5

Characters and Unicode

Total characters197
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

Unique29 ?
Unique (%)87.9%

Sample

1st row07765
2nd row157804
3rd row157-840
4th row157847
5th row157861
ValueCountFrequency (%)
157861 2
 
6.1%
157220 2
 
6.1%
07788 1
 
3.0%
157859 1
 
3.0%
157-280 1
 
3.0%
157-846 1
 
3.0%
157914 1
 
3.0%
157925 1
 
3.0%
07573 1
 
3.0%
07765 1
 
3.0%
Other values (21) 21
63.6%
2024-05-11T03:41:55.450783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 40
20.3%
5 36
18.3%
1 32
16.2%
0 24
12.2%
8 20
10.2%
9 10
 
5.1%
2 9
 
4.6%
- 8
 
4.1%
4 7
 
3.6%
3 6
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
95.9%
Dash Punctuation 8
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 40
21.2%
5 36
19.0%
1 32
16.9%
0 24
12.7%
8 20
10.6%
9 10
 
5.3%
2 9
 
4.8%
4 7
 
3.7%
3 6
 
3.2%
6 5
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 197
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 40
20.3%
5 36
18.3%
1 32
16.2%
0 24
12.2%
8 20
10.2%
9 10
 
5.1%
2 9
 
4.6%
- 8
 
4.1%
4 7
 
3.6%
3 6
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 40
20.3%
5 36
18.3%
1 32
16.2%
0 24
12.2%
8 20
10.2%
9 10
 
5.1%
2 9
 
4.6%
- 8
 
4.1%
4 7
 
3.6%
3 6
 
3.0%

사업장명
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-05-11T03:41:56.161132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15.5
Mean length11.956522
Min length4

Characters and Unicode

Total characters550
Distinct characters116
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)95.7%

Sample

1st row화곡중앙시장
2nd row그랜드패션아울렛
3rd row(주)공항시장
4th row(주)이랜드리테일홈에버가양점
5th row방신종합시장 재건축조합
ValueCountFrequency (%)
롯데쇼핑(주)롯데슈퍼 4
 
5.0%
홈플러스(주 3
 
3.8%
주)공항시장 2
 
2.5%
주)이마트에브리데이 2
 
2.5%
염창점 2
 
2.5%
주)이마트 2
 
2.5%
가양점 2
 
2.5%
노브랜드 2
 
2.5%
강서점 2
 
2.5%
화곡2점 1
 
1.2%
Other values (58) 58
72.5%
2024-05-11T03:41:57.413236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
6.2%
점 33
 
6.0%
( 25
 
4.5%
) 25
 
4.5%
주 23
 
4.2%
데 22
 
4.0%
롯 17
 
3.1%
이 17
 
3.1%
스 17
 
3.1%
화 15
 
2.7%
Other values (106) 322
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
80.9%
Space Separator 34
 
6.2%
Open Punctuation 25
 
4.5%
Close Punctuation 25
 
4.5%
Uppercase Letter 12
 
2.2%
Decimal Number 7
 
1.3%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 33
 
7.4%
주 23
 
5.2%
데 22
 
4.9%
롯 17
 
3.8%
이 17
 
3.8%
스 17
 
3.8%
화 15
 
3.4%
마 13
 
2.9%
곡 11
 
2.5%
리 10
 
2.2%
Other values (92) 267
60.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
25.0%
G 2
16.7%
H 2
16.7%
E 2
16.7%
T 1
 
8.3%
F 1
 
8.3%
R 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
9 3
42.9%
3 1
 
14.3%
Space Separator
ValueCountFrequency (%)
34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 447
81.3%
Common 91
 
16.5%
Latin 12
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 33
 
7.4%
주 23
 
5.1%
데 22
 
4.9%
롯 17
 
3.8%
이 17
 
3.8%
스 17
 
3.8%
화 15
 
3.4%
마 13
 
2.9%
곡 11
 
2.5%
리 10
 
2.2%
Other values (93) 269
60.2%
Latin
ValueCountFrequency (%)
S 3
25.0%
G 2
16.7%
H 2
16.7%
E 2
16.7%
T 1
 
8.3%
F 1
 
8.3%
R 1
 
8.3%
Common
ValueCountFrequency (%)
34
37.4%
( 25
27.5%
) 25
27.5%
2 3
 
3.3%
9 3
 
3.3%
3 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
80.9%
ASCII 103
 
18.7%
None 2
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
33.0%
( 25
24.3%
) 25
24.3%
S 3
 
2.9%
2 3
 
2.9%
9 3
 
2.9%
G 2
 
1.9%
H 2
 
1.9%
E 2
 
1.9%
3 1
 
1.0%
Other values (3) 3
 
2.9%
Hangul
ValueCountFrequency (%)
점 33
 
7.4%
주 23
 
5.2%
데 22
 
4.9%
롯 17
 
3.8%
이 17
 
3.8%
스 17
 
3.8%
화 15
 
3.4%
마 13
 
2.9%
곡 11
 
2.5%
리 10
 
2.2%
Other values (92) 267
60.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정일자
Date

Distinct40
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2007-07-14 13:55:24
Maximum2024-05-07 13:03:30
2024-05-11T03:41:57.954390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:41:58.395637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

데이터갱신구분
Categorical

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
I
27 
U
19 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 27
58.7%
U 19
41.3%

Length

2024-05-11T03:41:59.157723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:41:59.508954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 27
58.7%
u 19
41.3%

데이터갱신일자
Date

Distinct19
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T03:41:59.932672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T03:42:00.487198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

업태구분명
Categorical

Distinct7
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
그 밖의 대규모점포
24 
대형마트
8 
구분없음
7 
쇼핑센터
3 
시장
 
2
Other values (2)
 
2

Length

Max length10
Median length10
Mean length7
Min length2

Unique

Unique2 ?
Unique (%)4.3%

Sample

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

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 24
52.2%
대형마트 8
 
17.4%
구분없음 7
 
15.2%
쇼핑센터 3
 
6.5%
시장 2
 
4.3%
전문점 1
 
2.2%
백화점 1
 
2.2%

Length

2024-05-11T03:42:01.105429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:42:01.637305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 24
25.5%
밖의 24
25.5%
대규모점포 24
25.5%
대형마트 8
 
8.5%
구분없음 7
 
7.4%
쇼핑센터 3
 
3.2%
시장 2
 
2.1%
전문점 1
 
1.1%
백화점 1
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)83.7%
Missing3
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean185820.07
Minimum182141.21
Maximum188692.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T03:42:02.259819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182141.21
5-th percentile182756.68
Q1184941.16
median185824.43
Q3186876.33
95-th percentile188540.01
Maximum188692.03
Range6550.8278
Interquartile range (IQR)1935.168

Descriptive statistics

Standard deviation1724.8442
Coefficient of variation (CV)0.0092823354
Kurtosis-0.40113866
Mean185820.07
Median Absolute Deviation (MAD)1141.6077
Skewness-0.39921495
Sum7990262.9
Variance2975087.5
MonotonicityNot monotonic
2024-05-11T03:42:02.929429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
187119.948165892 2
 
4.3%
186786.622461585 2
 
4.3%
186966.036176588 2
 
4.3%
185431.066605778 2
 
4.3%
185745.73257287 2
 
4.3%
183315.556652953 2
 
4.3%
186687.131804431 2
 
4.3%
185732.424363656 1
 
2.2%
184102.782470646 1
 
2.2%
184473.320124105 1
 
2.2%
Other values (26) 26
56.5%
(Missing) 3
 
6.5%
ValueCountFrequency (%)
182141.205465089 1
2.2%
182524.823835629 1
2.2%
182735.786874703 1
2.2%
182944.731406147 1
2.2%
183124.298223484 1
2.2%
183315.556652953 2
4.3%
184102.782470646 1
2.2%
184345.724012817 1
2.2%
184473.320124105 1
2.2%
184498.0 1
2.2%
ValueCountFrequency (%)
188692.033242329 1
2.2%
188680.48304204 1
2.2%
188564.428051183 1
2.2%
188320.272052969 1
2.2%
188237.941732745 1
2.2%
187761.194273879 1
2.2%
187464.403178638 1
2.2%
187119.948165892 2
4.3%
186966.036176588 2
4.3%
186786.622461585 2
4.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)83.7%
Missing3
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean450499.34
Minimum447719.84
Maximum452207.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-05-11T03:42:03.459875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum447719.84
5-th percentile448140.29
Q1449714.81
median450691.59
Q3451434.75
95-th percentile452193.49
Maximum452207.43
Range4487.5906
Interquartile range (IQR)1719.9372

Descriptive statistics

Standard deviation1247.0433
Coefficient of variation (CV)0.0027681356
Kurtosis-0.37268055
Mean450499.34
Median Absolute Deviation (MAD)900.01764
Skewness-0.65296657
Sum19371472
Variance1555116.9
MonotonicityNot monotonic
2024-05-11T03:42:03.971625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
450691.593173724 2
 
4.3%
450297.70265223 2
 
4.3%
451047.287263879 2
 
4.3%
449714.813765198 2
 
4.3%
448140.292711073 2
 
4.3%
452204.165533971 2
 
4.3%
451342.773451086 2
 
4.3%
450884.528795882 1
 
2.2%
452097.370050563 1
 
2.2%
450901.978104789 1
 
2.2%
Other values (26) 26
56.5%
(Missing) 3
 
6.5%
ValueCountFrequency (%)
447719.836723478 1
2.2%
447877.710664426 1
2.2%
448140.292711073 2
4.3%
448552.124723353 1
2.2%
448813.441620263 1
2.2%
448913.76093431 1
2.2%
449481.253638067 1
2.2%
449645.45192818 1
2.2%
449699.83258499 1
2.2%
449714.813765198 2
4.3%
ValueCountFrequency (%)
452207.427296372 1
2.2%
452204.165533971 2
4.3%
452097.370050563 1
2.2%
451971.178722228 1
2.2%
451786.0 1
2.2%
451778.0 1
2.2%
451762.949220308 1
2.2%
451596.45849391 1
2.2%
451591.610813727 1
2.2%
451438.25089679 1
2.2%

점포구분명
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
<NA>
24 
준대규모점포
12 
대규모점포
10 

Length

Max length6
Median length4
Mean length4.7391304
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> 24
52.2%
준대규모점포 12
26.1%
대규모점포 10
21.7%

Length

2024-05-11T03:42:04.517510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T03:42:04.877635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
52.2%
준대규모점포 12
26.1%
대규모점포 10
21.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03150000198731501660750000619871030<NA>3폐업3폐업처리20221004<NA><NA><NA>02-2602-57571568.0<NA>서울특별시 강서구 화곡동 370번지 76호서울특별시 강서구 월정로30길 69 (화곡동)07765화곡중앙시장2022-10-04 15:31:32U2021-10-31 00:06:00.0시장185745.732573448140.292711<NA>
13150000199531500740750000119950501<NA>2휴업2휴업처리<NA><NA><NA><NA>02260020020.0<NA>서울특별시 강서구 화곡동 1095호<NA><NA>그랜드패션아울렛2007-07-14 13:55:24I2018-08-31 23:59:59.0그 밖의 대규모점포186786.622462450297.702652<NA>
23150000199931501000750000119700820<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 266227512702.0<NA>서울특별시 강서구 방화동 620호<NA><NA>(주)공항시장2013-05-01 09:03:04I2018-08-31 23:59:59.0시장<NA><NA>대규모점포
33150000200031501000750000120001006<NA>2휴업2휴업처리<NA><NA><NA><NA>02366494000.0<NA>서울특별시 강서구 가양동 18번지 24호<NA><NA>(주)이랜드리테일홈에버가양점2007-07-14 13:55:24I2018-08-31 23:59:59.0쇼핑센터186687.131804451342.773451<NA>
43150000200231500740750000120020801<NA>2휴업2휴업처리<NA><NA><NA><NA><NA>0.0<NA>서울특별시 강서구 방화동 567번지 4호<NA><NA>방신종합시장 재건축조합2007-07-14 13:55:24I2018-08-31 23:59:59.0그 밖의 대규모점포183315.556653452204.165534<NA>
53150000200331501000750003020030123<NA>2휴업2휴업처리<NA><NA><NA><NA>0221661052<NA><NA>서울특별시 강서구 과해동 272호<NA><NA>신세계이마트(공항점)2007-07-14 13:55:24I2018-08-31 23:59:59.0대형마트<NA><NA><NA>
63150000200431501000750000120040219<NA>2휴업2휴업처리<NA><NA><NA><NA>0226622751<NA><NA>서울특별시 강서구 방화동 620호<NA><NA>(주)공항시장2007-07-14 13:55:24I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
73150000200431501000750003319991228<NA>3폐업3폐업처리20220927<NA><NA><NA>02 2101 105317262.29<NA>서울특별시 강서구 가양동 449번지 19 호서울특별시 양천로 559 (가양이마트(E-MART))157804(주)이마트 가양점2022-09-27 15:44:47U2021-12-08 22:09:00.0대형마트187761.194274450640.214509<NA>
83150000200431501000750003420040503<NA>2휴업2휴업처리<NA><NA><NA><NA>0226060101<NA><NA>서울특별시 강서구 화곡동 1095호<NA><NA>그랜드백화점(주)마트화곡점2007-07-14 13:55:24I2018-08-31 23:59:59.0대형마트186786.622462450297.702652<NA>
93150000200431501000750003519991216<NA>3폐업3폐업처리20120201<NA><NA><NA>02265721268762.0<NA>서울특별시 강서구 등촌동 678번지 14호<NA><NA>그랜드백화점(주)마트강서점2012-02-10 10:47:31I2018-08-31 23:59:59.0대형마트185732.424364450884.528796대규모점포
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
363150000201531501660750000120150323<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3665-7255286.2157861서울특별시 강서구 염창동 249번지 8호 1층서울특별시 강서구 양천로 687, 1층 (염창동)157861(주)지에스리테일 염창점2016-02-17 16:52:25I2018-08-31 23:59:59.0그 밖의 대규모점포188680.483042449829.694259준대규모점포
373150000201731501860750000120170330<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3665-76610.0<NA>서울특별시 강서구 가양동 54번지 5호서울특별시 강서구 양천로 410 (가양동)07573노브랜드 강서가양점2019-01-22 11:08:38I2019-01-24 02:20:58.0구분없음186374.463683451431.251131준대규모점포
383150000201731501860750000220170617<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2039-83370.0<NA>서울특별시 강서구 마곡동 759번지 마곡센트럴타워Ⅱ서울특별시 강서구 마곡서로 158, 마곡센트럴타워Ⅱ 103~110, 118, 119호 (마곡동)07788이마트에브리데이 마곡점2019-01-22 11:23:35I2019-01-24 02:20:58.0구분없음184498.0451786.0준대규모점포
393150000201731501860750000320170814<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3664-66000.0<NA>서울특별시 강서구 마곡동 776번지 2호 마곡센트럴대방디엠시티오피스텔서울특별시 강서구 양천로 344, 마곡센트럴대방디엠시티오피스텔 121-1,2호 (마곡동)07791롯데쇼핑㈜ 마켓999 양천향교역가맹점2019-01-22 13:16:25I2019-01-24 02:20:58.0구분없음185798.0451778.0준대규모점포
403150000201731501860750000420171011<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2063-36900.0<NA>서울특별시 강서구 가양동 1458번지 9호 동남빌딩서울특별시 강서구 허준로 16-12, 동남빌딩 (가양동)07529㈜이마트에브리데이 양천향교역점2019-01-22 13:23:37I2019-01-24 02:20:58.0구분없음186080.902017451971.178722준대규모점포
41315000020183150186075000012018-07-30<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2667-01510.0<NA>서울특별시 강서구 마곡동 768번지 2호 동익드미라벨복합빌딩서울특별시 강서구 마곡서로 101, 동익드미라벨복합빌딩 (마곡동)07798노브랜드 강서마곡점2024-04-24 17:26:27U2023-12-03 22:06:00.0구분없음184345.724013451171.287709<NA>
42315000020233150200075000012023-01-27<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA>876.0<NA>서울특별시 강서구 등촌동 73-1 금부빌딩서울특별시 강서구 양천로 476, 금부빌딩 (등촌동)07575(주)이마트에브리데이 가양역점2024-05-07 13:03:30U2023-12-05 00:09:00.0구분없음186966.036177451047.287264<NA>
43315000020233150200075000022023-09-07<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA>3015.0<NA>서울특별시 강서구 화곡동 370-76<NA><NA>화곡 더리브스카이2023-09-07 12:16:10I2022-12-09 00:09:00.0그 밖의 대규모점포185745.732573448140.292711<NA>
44315000020233150200075000032023-12-28<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3662-4171673.32<NA>서울특별시 강서구 염창동 242-11 한희빌딩서울특별시 강서구 양천로67길 15, 한희빌딩 1층 (염창동)07545GS THE FRESH 강서증미역점2023-12-29 09:08:19I2022-11-01 21:01:00.0구분없음188237.941733450314.087913<NA>
45315000020243150200075000012024-01-10<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-6925-251845186.22<NA>서울특별시 강서구 마곡동 769서울특별시 강서구 공항대로 165, (마곡동 769 및 769-1) [마곡지구 특별계획구역 CP4블록] (마곡동)07800원 웨스트 몰2024-04-04 09:53:36U2023-12-04 00:07:00.0쇼핑센터184473.320124450901.978105<NA>