Overview

Dataset statistics

Number of variables26
Number of observations53
Missing cells249
Missing cells (%)18.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory220.5 B

Variable types

Categorical12
Numeric4
DateTime3
Unsupported2
Text5

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
Author구로구
URLhttps://data.seoul.go.kr/dataList/OA-18718/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
휴업시작일자 is highly imbalanced (86.5%)Imbalance
휴업종료일자 is highly imbalanced (86.5%)Imbalance
인허가취소일자 has 53 (100.0%) missing valuesMissing
폐업일자 has 49 (92.5%) missing valuesMissing
재개업일자 has 53 (100.0%) missing valuesMissing
전화번호 has 3 (5.7%) missing valuesMissing
소재지면적 has 13 (24.5%) missing valuesMissing
도로명주소 has 13 (24.5%) missing valuesMissing
도로명우편번호 has 43 (81.1%) missing valuesMissing
좌표정보(X) has 11 (20.8%) missing valuesMissing
좌표정보(Y) has 11 (20.8%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 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 1 (1.9%) zerosZeros

Reproduction

Analysis started2024-05-11 05:58:03.224150
Analysis finished2024-05-11 05:58:04.676562
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
3160000
53 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3160000
2nd row3160000
3rd row3160000
4th row3160000
5th row3160000

Common Values

ValueCountFrequency (%)
3160000 53
100.0%

Length

2024-05-11T14:58:04.818630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:05.046363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3160000 53
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.000882 × 1018
Minimum1.962316 × 1018
Maximum2.022316 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T14:58:05.268813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.962316 × 1018
5-th percentile1.971916 × 1018
Q11.996316 × 1018
median2.007316 × 1018
Q32.007316 × 1018
95-th percentile2.012316 × 1018
Maximum2.022316 × 1018
Range6.0000009 × 1016
Interquartile range (IQR)1.1000005 × 1016

Descriptive statistics

Standard deviation1.294591 × 1016
Coefficient of variation (CV)0.0064701013
Kurtosis1.4930371
Mean2.000882 × 1018
Median Absolute Deviation (MAD)2.0000024 × 1015
Skewness-1.3818157
Sum-4.6337159 × 1018
Variance1.6759658 × 1032
MonotonicityStrictly increasing
2024-05-11T14:58:05.520651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1962316007107500001 1
 
1.9%
2007316011707500016 1
 
1.9%
2007316011707500005 1
 
1.9%
2007316011707500006 1
 
1.9%
2007316011707500007 1
 
1.9%
2007316011707500008 1
 
1.9%
2007316011707500009 1
 
1.9%
2007316011707500010 1
 
1.9%
2007316011707500011 1
 
1.9%
2007316011707500012 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1962316007107500001 1
1.9%
1968316007107500002 1
1.9%
1971316007107500001 1
1.9%
1972316007107500005 1
1.9%
1976316007107500001 1
1.9%
1976316007107500002 1
1.9%
1986316007107500001 1
1.9%
1986316007107500015 1
1.9%
1989316007107500020 1
1.9%
1993316007107500001 1
1.9%
ValueCountFrequency (%)
2022316015907500001 1
1.9%
2020316015907500001 1
1.9%
2012316015907500003 1
1.9%
2012316015907500002 1
1.9%
2012316015907500001 1
1.9%
2011316015907500002 1
1.9%
2011316015907500001 1
1.9%
2007316011707500021 1
1.9%
2007316011707500020 1
1.9%
2007316011707500019 1
1.9%

인허가일자
Date

Distinct35
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum1962-09-25 00:00:00
Maximum2022-03-18 00:00:00
2024-05-11T14:58:05.745526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:58:06.025874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
1
38 
2
11 
3
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 38
71.7%
2 11
 
20.8%
3 4
 
7.5%

Length

2024-05-11T14:58:06.265574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:06.451453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 38
71.7%
2 11
 
20.8%
3 4
 
7.5%

영업상태명
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
영업/정상
38 
휴업
11 
폐업
4 

Length

Max length5
Median length5
Mean length4.1509434
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 38
71.7%
휴업 11
 
20.8%
폐업 4
 
7.5%

Length

2024-05-11T14:58:06.679984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:06.894480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 38
71.7%
휴업 11
 
20.8%
폐업 4
 
7.5%

상세영업상태코드
Categorical

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
1
37 
2
11 
3
4 
BBBB
 
1

Length

Max length4
Median length1
Mean length1.0566038
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 37
69.8%
2 11
 
20.8%
3 4
 
7.5%
BBBB 1
 
1.9%

Length

2024-05-11T14:58:07.076852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:07.280462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 37
69.8%
2 11
 
20.8%
3 4
 
7.5%
bbbb 1
 
1.9%

상세영업상태명
Categorical

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
정상영업
37 
휴업처리
11 
폐업처리
4 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 37
69.8%
휴업처리 11
 
20.8%
폐업처리 4
 
7.5%
<NA> 1
 
1.9%

Length

2024-05-11T14:58:07.485784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:07.650600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 37
69.8%
휴업처리 11
 
20.8%
폐업처리 4
 
7.5%
na 1
 
1.9%

폐업일자
Date

MISSING 

Distinct4
Distinct (%)100.0%
Missing49
Missing (%)92.5%
Memory size556.0 B
Minimum2012-05-02 00:00:00
Maximum2024-02-08 00:00:00
2024-05-11T14:58:07.805605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:58:07.988586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
20170704
 
1

Length

Max length8
Median length4
Mean length4.0754717
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
20170704 1
 
1.9%

Length

2024-05-11T14:58:08.227154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:08.437141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20170704 1
 
1.9%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
99991231
 
1

Length

Max length8
Median length4
Mean length4.0754717
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 52
98.1%
99991231 1
 
1.9%

Length

2024-05-11T14:58:08.632460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:08.811908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
99991231 1
 
1.9%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing53
Missing (%)100.0%
Memory size609.0 B

전화번호
Text

MISSING 

Distinct48
Distinct (%)96.0%
Missing3
Missing (%)5.7%
Memory size556.0 B
2024-05-11T14:58:09.115482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.26
Min length7

Characters and Unicode

Total characters513
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)94.0%

Sample

1st row02 8542709
2nd row0226113888
3rd row02 6170617
4th row02 8551036
5th row02 6136162
ValueCountFrequency (%)
02 17
24.3%
26392500 3
 
4.3%
02-323-0456 1
 
1.4%
2681-1364 1
 
1.4%
8542709 1
 
1.4%
000226177914 1
 
1.4%
02818 1
 
1.4%
0812 1
 
1.4%
000220935072 1
 
1.4%
8373764 1
 
1.4%
Other values (42) 42
60.0%
2024-05-11T14:58:09.789312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 95
18.5%
2 94
18.3%
6 57
11.1%
1 48
9.4%
8 44
8.6%
3 37
 
7.2%
26
 
5.1%
5 24
 
4.7%
- 23
 
4.5%
4 23
 
4.5%
Other values (3) 42
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 463
90.3%
Space Separator 26
 
5.1%
Dash Punctuation 23
 
4.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 95
20.5%
2 94
20.3%
6 57
12.3%
1 48
10.4%
8 44
9.5%
3 37
 
8.0%
5 24
 
5.2%
4 23
 
5.0%
7 22
 
4.8%
9 19
 
4.1%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 95
18.5%
2 94
18.3%
6 57
11.1%
1 48
9.4%
8 44
8.6%
3 37
 
7.2%
26
 
5.1%
5 24
 
4.7%
- 23
 
4.5%
4 23
 
4.5%
Other values (3) 42
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 95
18.5%
2 94
18.3%
6 57
11.1%
1 48
9.4%
8 44
8.6%
3 37
 
7.2%
26
 
5.1%
5 24
 
4.7%
- 23
 
4.5%
4 23
 
4.5%
Other values (3) 42
8.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct37
Distinct (%)92.5%
Missing13
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean13648.849
Minimum0
Maximum70845
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T14:58:10.013392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile182.1
Q13285.25
median9133
Q315681.075
95-th percentile45917.839
Maximum70845
Range70845
Interquartile range (IQR)12395.825

Descriptive statistics

Standard deviation15708.393
Coefficient of variation (CV)1.150895
Kurtosis3.9536709
Mean13648.849
Median Absolute Deviation (MAD)6209.5
Skewness1.9577059
Sum545953.97
Variance2.4675361 × 108
MonotonicityNot monotonic
2024-05-11T14:58:10.237927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
8555.0 2
 
3.8%
10502.0 2
 
3.8%
10705.0 2
 
3.8%
228.69 1
 
1.9%
49220.79 1
 
1.9%
40883.22 1
 
1.9%
191.0 1
 
1.9%
246.0 1
 
1.9%
860.0 1
 
1.9%
70845.0 1
 
1.9%
Other values (27) 27
50.9%
(Missing) 13
24.5%
ValueCountFrequency (%)
0.0 1
1.9%
13.0 1
1.9%
191.0 1
1.9%
228.69 1
1.9%
246.0 1
1.9%
860.0 1
1.9%
1582.0 1
1.9%
2464.0 1
1.9%
2762.0 1
1.9%
3085.0 1
1.9%
ValueCountFrequency (%)
70845.0 1
1.9%
49220.79 1
1.9%
45744.0 1
1.9%
40883.22 1
1.9%
38414.15 1
1.9%
27535.0 1
1.9%
24862.71 1
1.9%
24362.0 1
1.9%
19634.51 1
1.9%
15852.3 1
1.9%

소재지우편번호
Categorical

Distinct12
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
30 
152050
8 
152080
4 
152-050
 
2
152081
 
2
Other values (7)
7 

Length

Max length7
Median length4
Mean length4.9811321
Min length4

Unique

Unique7 ?
Unique (%)13.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
56.6%
152050 8
 
15.1%
152080 4
 
7.5%
152-050 2
 
3.8%
152081 2
 
3.8%
152-100 1
 
1.9%
152090 1
 
1.9%
152-888 1
 
1.9%
152814 1
 
1.9%
152-897 1
 
1.9%
Other values (2) 2
 
3.8%

Length

2024-05-11T14:58:10.590998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 30
56.6%
152050 8
 
15.1%
152080 4
 
7.5%
152-050 2
 
3.8%
152081 2
 
3.8%
152-100 1
 
1.9%
152090 1
 
1.9%
152-888 1
 
1.9%
152814 1
 
1.9%
152-897 1
 
1.9%
Other values (2) 2
 
3.8%

지번주소
Text

Distinct48
Distinct (%)90.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-05-11T14:58:10.993079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length33
Mean length25.566038
Min length17

Characters and Unicode

Total characters1355
Distinct characters56
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)83.0%

Sample

1st row서울특별시 구로구 구로동 736번지 1 호
2nd row서울특별시 구로구 오류동 38번지 7 호
3rd row서울특별시 구로구 고척동 50번지 48 호
4th row서울특별시 구로구 구로동 169번지 2 호
5th row서울특별시 구로구 개봉동 324번지 1 호
ValueCountFrequency (%)
서울특별시 53
18.6%
구로구 53
18.6%
구로동 27
 
9.5%
고척동 14
 
4.9%
호 13
 
4.6%
636번지 7
 
2.5%
1 6
 
2.1%
89호 5
 
1.8%
1호 5
 
1.8%
188번지 4
 
1.4%
Other values (68) 98
34.4%
2024-05-11T14:58:11.770761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
322
23.8%
구 134
 
9.9%
로 81
 
6.0%
지 54
 
4.0%
1 54
 
4.0%
동 54
 
4.0%
울 53
 
3.9%
서 53
 
3.9%
시 53
 
3.9%
특 53
 
3.9%
Other values (46) 444
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 771
56.9%
Space Separator 322
23.8%
Decimal Number 250
 
18.5%
Other Punctuation 4
 
0.3%
Dash Punctuation 4
 
0.3%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 134
17.4%
로 81
10.5%
지 54
7.0%
동 54
7.0%
울 53
 
6.9%
서 53
 
6.9%
시 53
 
6.9%
특 53
 
6.9%
별 53
 
6.9%
호 49
 
6.4%
Other values (29) 134
17.4%
Decimal Number
ValueCountFrequency (%)
1 54
21.6%
6 41
16.4%
3 37
14.8%
8 24
9.6%
2 22
8.8%
4 19
 
7.6%
5 15
 
6.0%
7 14
 
5.6%
0 14
 
5.6%
9 10
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
K 1
33.3%
S 1
33.3%
Space Separator
ValueCountFrequency (%)
322
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 771
56.9%
Common 581
42.9%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 134
17.4%
로 81
10.5%
지 54
7.0%
동 54
7.0%
울 53
 
6.9%
서 53
 
6.9%
시 53
 
6.9%
특 53
 
6.9%
별 53
 
6.9%
호 49
 
6.4%
Other values (29) 134
17.4%
Common
ValueCountFrequency (%)
322
55.4%
1 54
 
9.3%
6 41
 
7.1%
3 37
 
6.4%
8 24
 
4.1%
2 22
 
3.8%
4 19
 
3.3%
5 15
 
2.6%
7 14
 
2.4%
0 14
 
2.4%
Other values (4) 19
 
3.3%
Latin
ValueCountFrequency (%)
B 1
33.3%
K 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 771
56.9%
ASCII 584
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
322
55.1%
1 54
 
9.2%
6 41
 
7.0%
3 37
 
6.3%
8 24
 
4.1%
2 22
 
3.8%
4 19
 
3.3%
5 15
 
2.6%
7 14
 
2.4%
0 14
 
2.4%
Other values (7) 22
 
3.8%
Hangul
ValueCountFrequency (%)
구 134
17.4%
로 81
10.5%
지 54
7.0%
동 54
7.0%
울 53
 
6.9%
서 53
 
6.9%
시 53
 
6.9%
특 53
 
6.9%
별 53
 
6.9%
호 49
 
6.4%
Other values (29) 134
17.4%

도로명주소
Text

MISSING 

Distinct28
Distinct (%)70.0%
Missing13
Missing (%)24.5%
Memory size556.0 B
2024-05-11T14:58:12.127824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length27.05
Min length22

Characters and Unicode

Total characters1082
Distinct characters75
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

Unique20 ?
Unique (%)50.0%

Sample

1st row서울특별시 구로구 중앙로3길 50 (고척동, 고척산업용품종합상가)
2nd row서울특별시 구로구 구일로10길 93 (구로동)
3rd row서울특별시 구로구 구로중앙로 152 (구로동)
4th row서울특별시 구로구 중앙로3길 49 (고척동)
5th row서울특별시 구로구 경인로53길 15 (구로동)
ValueCountFrequency (%)
서울특별시 40
18.9%
구로구 39
18.4%
구로동 18
 
8.5%
경인로 11
 
5.2%
고척동 11
 
5.2%
구로중앙로 6
 
2.8%
482 5
 
2.4%
중앙로3길 3
 
1.4%
중앙로1길 3
 
1.4%
구일로10길 3
 
1.4%
Other values (54) 73
34.4%
2024-05-11T14:58:12.702682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
173
16.0%
구 108
 
10.0%
로 106
 
9.8%
서 41
 
3.8%
( 40
 
3.7%
특 40
 
3.7%
별 40
 
3.7%
시 40
 
3.7%
울 40
 
3.7%
) 40
 
3.7%
Other values (65) 414
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 655
60.5%
Space Separator 173
 
16.0%
Decimal Number 158
 
14.6%
Open Punctuation 40
 
3.7%
Close Punctuation 40
 
3.7%
Other Punctuation 12
 
1.1%
Dash Punctuation 2
 
0.2%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 108
16.5%
로 106
16.2%
서 41
 
6.3%
특 40
 
6.1%
별 40
 
6.1%
시 40
 
6.1%
울 40
 
6.1%
동 40
 
6.1%
길 19
 
2.9%
경 15
 
2.3%
Other values (48) 166
25.3%
Decimal Number
ValueCountFrequency (%)
1 35
22.2%
3 29
18.4%
2 23
14.6%
4 19
12.0%
9 14
 
8.9%
5 10
 
6.3%
6 8
 
5.1%
8 7
 
4.4%
7 7
 
4.4%
0 6
 
3.8%
Space Separator
ValueCountFrequency (%)
173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 655
60.5%
Common 426
39.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 108
16.5%
로 106
16.2%
서 41
 
6.3%
특 40
 
6.1%
별 40
 
6.1%
시 40
 
6.1%
울 40
 
6.1%
동 40
 
6.1%
길 19
 
2.9%
경 15
 
2.3%
Other values (48) 166
25.3%
Common
ValueCountFrequency (%)
173
40.6%
( 40
 
9.4%
) 40
 
9.4%
1 35
 
8.2%
3 29
 
6.8%
2 23
 
5.4%
4 19
 
4.5%
9 14
 
3.3%
, 12
 
2.8%
5 10
 
2.3%
Other values (6) 31
 
7.3%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 655
60.5%
ASCII 427
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
40.5%
( 40
 
9.4%
) 40
 
9.4%
1 35
 
8.2%
3 29
 
6.8%
2 23
 
5.4%
4 19
 
4.4%
9 14
 
3.3%
, 12
 
2.8%
5 10
 
2.3%
Other values (7) 32
 
7.5%
Hangul
ValueCountFrequency (%)
구 108
16.5%
로 106
16.2%
서 41
 
6.3%
특 40
 
6.1%
별 40
 
6.1%
시 40
 
6.1%
울 40
 
6.1%
동 40
 
6.1%
길 19
 
2.9%
경 15
 
2.3%
Other values (48) 166
25.3%

도로명우편번호
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing43
Missing (%)81.1%
Memory size556.0 B
2024-05-11T14:58:12.954436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.8
Min length5

Characters and Unicode

Total characters58
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

Unique10 ?
Unique (%)100.0%

Sample

1st row08225
2nd row152722
3rd row08208
4th row152864
5th row152757
ValueCountFrequency (%)
08225 1
10.0%
152722 1
10.0%
08208 1
10.0%
152864 1
10.0%
152757 1
10.0%
152824 1
10.0%
152-888 1
10.0%
152814 1
10.0%
152720 1
10.0%
08292 1
10.0%
2024-05-11T14:58:13.485567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
27.6%
8 10
17.2%
5 9
15.5%
1 8
13.8%
0 5
 
8.6%
7 4
 
6.9%
4 3
 
5.2%
6 1
 
1.7%
- 1
 
1.7%
9 1
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
98.3%
Dash Punctuation 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16
28.1%
8 10
17.5%
5 9
15.8%
1 8
14.0%
0 5
 
8.8%
7 4
 
7.0%
4 3
 
5.3%
6 1
 
1.8%
9 1
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
27.6%
8 10
17.2%
5 9
15.5%
1 8
13.8%
0 5
 
8.6%
7 4
 
6.9%
4 3
 
5.2%
6 1
 
1.7%
- 1
 
1.7%
9 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
27.6%
8 10
17.2%
5 9
15.5%
1 8
13.8%
0 5
 
8.6%
7 4
 
6.9%
4 3
 
5.2%
6 1
 
1.7%
- 1
 
1.7%
9 1
 
1.7%

사업장명
Text

Distinct42
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-05-11T14:58:13.932709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length8.7169811
Min length4

Characters and Unicode

Total characters462
Distinct characters110
Distinct categories5 ?
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 (%)60.4%

Sample

1st row구로시장
2nd row오류시장
3rd row고척시장
4th row배영설비(주)
5th row개봉중앙시장
ValueCountFrequency (%)
구로점 5
 
6.6%
일이삼전자타운 3
 
3.9%
롯데마트 3
 
3.9%
홈플러스 3
 
3.9%
익스프레스 3
 
3.9%
동국종합상가 2
 
2.6%
개봉프라자 2
 
2.6%
사모아종합상가 2
 
2.6%
고척산업용품상가 2
 
2.6%
중앙유통단지 2
 
2.6%
Other values (44) 49
64.5%
2024-05-11T14:58:14.574401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
5.0%
구 22
 
4.8%
점 20
 
4.3%
이 17
 
3.7%
로 16
 
3.5%
스 12
 
2.6%
가 12
 
2.6%
상 12
 
2.6%
주 10
 
2.2%
) 10
 
2.2%
Other values (100) 308
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 407
88.1%
Space Separator 23
 
5.0%
Uppercase Letter 12
 
2.6%
Close Punctuation 10
 
2.2%
Open Punctuation 10
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 22
 
5.4%
점 20
 
4.9%
이 17
 
4.2%
로 16
 
3.9%
스 12
 
2.9%
가 12
 
2.9%
상 12
 
2.9%
주 10
 
2.5%
일 10
 
2.5%
트 10
 
2.5%
Other values (87) 266
65.4%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
R 1
 
8.3%
T 1
 
8.3%
U 1
 
8.3%
K 1
 
8.3%
P 1
 
8.3%
L 1
 
8.3%
Z 1
 
8.3%
C 1
 
8.3%
N 1
 
8.3%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 407
88.1%
Common 43
 
9.3%
Latin 12
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 22
 
5.4%
점 20
 
4.9%
이 17
 
4.2%
로 16
 
3.9%
스 12
 
2.9%
가 12
 
2.9%
상 12
 
2.9%
주 10
 
2.5%
일 10
 
2.5%
트 10
 
2.5%
Other values (87) 266
65.4%
Latin
ValueCountFrequency (%)
A 3
25.0%
R 1
 
8.3%
T 1
 
8.3%
U 1
 
8.3%
K 1
 
8.3%
P 1
 
8.3%
L 1
 
8.3%
Z 1
 
8.3%
C 1
 
8.3%
N 1
 
8.3%
Common
ValueCountFrequency (%)
23
53.5%
) 10
23.3%
( 10
23.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 407
88.1%
ASCII 55
 
11.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
41.8%
) 10
18.2%
( 10
18.2%
A 3
 
5.5%
R 1
 
1.8%
T 1
 
1.8%
U 1
 
1.8%
K 1
 
1.8%
P 1
 
1.8%
L 1
 
1.8%
Other values (3) 3
 
5.5%
Hangul
ValueCountFrequency (%)
구 22
 
5.4%
점 20
 
4.9%
이 17
 
4.2%
로 16
 
3.9%
스 12
 
2.9%
가 12
 
2.9%
상 12
 
2.9%
주 10
 
2.5%
일 10
 
2.5%
트 10
 
2.5%
Other values (87) 266
65.4%

최종수정일자
Date

Distinct32
Distinct (%)60.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2007-07-07 09:54:17
Maximum2024-04-24 09:39:06
2024-05-11T14:58:14.788406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:58:15.037196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
I
37 
U
16 

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 37
69.8%
U 16
30.2%

Length

2024-05-11T14:58:15.227075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:15.375139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 37
69.8%
u 16
30.2%

데이터갱신일자
Categorical

Distinct14
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
2018-08-31 23:59:59.0
37 
2023-12-03 22:07:00.0
 
2
2021-11-01 23:01:00.0
 
2
2023-12-03 23:08:00.0
 
2
2019-04-04 02:40:00.0
 
1
Other values (9)
9 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique10 ?
Unique (%)18.9%

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 37
69.8%
2023-12-03 22:07:00.0 2
 
3.8%
2021-11-01 23:01:00.0 2
 
3.8%
2023-12-03 23:08:00.0 2
 
3.8%
2019-04-04 02:40:00.0 1
 
1.9%
2023-12-03 00:07:00.0 1
 
1.9%
2021-01-01 02:40:00.0 1
 
1.9%
2019-10-17 02:40:00.0 1
 
1.9%
2023-12-01 22:05:00.0 1
 
1.9%
2023-12-03 23:09:00.0 1
 
1.9%
Other values (4) 4
 
7.5%

Length

2024-05-11T14:58:15.522007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 37
34.9%
23:59:59.0 37
34.9%
2023-12-03 6
 
5.7%
02:40:00.0 5
 
4.7%
22:07:00.0 2
 
1.9%
2021-11-01 2
 
1.9%
23:01:00.0 2
 
1.9%
23:08:00.0 2
 
1.9%
23:09:00.0 1
 
0.9%
2022-10-30 1
 
0.9%
Other values (11) 11
 
10.4%

업태구분명
Categorical

Distinct8
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
그 밖의 대규모점포
28 
대형마트
10 
백화점
4 
쇼핑센터
3 
복합쇼핑몰
3 
Other values (3)
5 

Length

Max length10
Median length10
Mean length7.0943396
Min length2

Unique

Unique2 ?
Unique (%)3.8%

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 28
52.8%
대형마트 10
 
18.9%
백화점 4
 
7.5%
쇼핑센터 3
 
5.7%
복합쇼핑몰 3
 
5.7%
구분없음 3
 
5.7%
전문점 1
 
1.9%
시장 1
 
1.9%

Length

2024-05-11T14:58:15.746186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:15.964136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 28
25.7%
밖의 28
25.7%
대규모점포 28
25.7%
대형마트 10
 
9.2%
백화점 4
 
3.7%
쇼핑센터 3
 
2.8%
복합쇼핑몰 3
 
2.8%
구분없음 3
 
2.8%
전문점 1
 
0.9%
시장 1
 
0.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)61.9%
Missing11
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean188510.32
Minimum185756.17
Maximum190901.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T14:58:16.195363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185756.17
5-th percentile186053.43
Q1187718.8
median188669.48
Q3189497.21
95-th percentile190868.51
Maximum190901.98
Range5145.803
Interquartile range (IQR)1778.41

Descriptive statistics

Standard deviation1317.7931
Coefficient of variation (CV)0.0069905618
Kurtosis-0.45536689
Mean188510.32
Median Absolute Deviation (MAD)906.72074
Skewness-0.08278595
Sum7917433.6
Variance1736578.6
MonotonicityNot monotonic
2024-05-11T14:58:16.845045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
188669.484398215 5
 
9.4%
190901.977946718 3
 
5.7%
189570.360930049 3
 
5.7%
187619.596959162 2
 
3.8%
190232.524534335 2
 
3.8%
187785.840457798 2
 
3.8%
186015.738369848 2
 
3.8%
187826.698183821 2
 
3.8%
188840.515865617 2
 
3.8%
187718.801171032 2
 
3.8%
Other values (16) 17
32.1%
(Missing) 11
20.8%
ValueCountFrequency (%)
185756.174922711 1
1.9%
186015.738369848 2
3.8%
186769.616926353 1
1.9%
186968.288544829 1
1.9%
187009.804317689 1
1.9%
187158.443830013 1
1.9%
187477.579440706 1
1.9%
187619.596959162 2
3.8%
187718.801171032 2
3.8%
187756.919450472 1
1.9%
ValueCountFrequency (%)
190901.977946718 3
5.7%
190232.524534335 2
3.8%
190107.045415333 1
 
1.9%
190005.132500398 1
 
1.9%
189682.799434964 1
 
1.9%
189570.360930049 3
5.7%
189277.761702183 1
 
1.9%
189134.15447044 1
 
1.9%
189052.101789082 2
3.8%
188907.966108621 1
 
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)61.9%
Missing11
Missing (%)20.8%
Infinite0
Infinite (%)0.0%
Mean444014.77
Minimum442466.81
Maximum445250.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T14:58:17.064272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum442466.81
5-th percentile442476.07
Q1443793.51
median444010.74
Q3444328.73
95-th percentile444978.68
Maximum445250.54
Range2783.7255
Interquartile range (IQR)535.22284

Descriptive statistics

Standard deviation657.07758
Coefficient of variation (CV)0.0014798552
Kurtosis1.0205169
Mean444014.77
Median Absolute Deviation (MAD)280.01211
Skewness-0.71793897
Sum18648621
Variance431750.95
MonotonicityNot monotonic
2024-05-11T14:58:17.275373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
444010.738380277 5
 
9.4%
442466.813410528 3
 
5.7%
444336.051330144 3
 
5.7%
444186.923109714 2
 
3.8%
444978.682746138 2
 
3.8%
443997.135869884 2
 
3.8%
443657.614265375 2
 
3.8%
443925.52468616 2
 
3.8%
444306.771104527 2
 
3.8%
444056.996752313 2
 
3.8%
Other values (16) 17
32.1%
(Missing) 11
20.8%
ValueCountFrequency (%)
442466.813410528 3
5.7%
442651.907780511 1
 
1.9%
443268.099008657 1
 
1.9%
443302.607792578 1
 
1.9%
443657.614265375 2
3.8%
443748.279289935 2
3.8%
443749.503020388 1
 
1.9%
443925.52468616 2
3.8%
443952.561879682 1
 
1.9%
443962.832747371 1
 
1.9%
ValueCountFrequency (%)
445250.538868558 1
 
1.9%
445157.626366229 1
 
1.9%
444978.682746138 2
3.8%
444898.367647601 1
 
1.9%
444671.551731639 1
 
1.9%
444629.704821749 1
 
1.9%
444433.221606826 1
 
1.9%
444336.051330144 3
5.7%
444306.771104527 2
3.8%
444274.729874348 1
 
1.9%

점포구분명
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
33 
대규모점포
18 
준대규모점포
 
2

Length

Max length6
Median length4
Mean length4.4150943
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> 33
62.3%
대규모점포 18
34.0%
준대규모점포 2
 
3.8%

Length

2024-05-11T14:58:17.520990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:58:17.693724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 33
62.3%
대규모점포 18
34.0%
준대규모점포 2
 
3.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03160000196231600710750000119620925<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8542709<NA><NA>서울특별시 구로구 구로동 736번지 1 호<NA><NA>구로시장2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
13160000196831600710750000219681023<NA>1영업/정상1정상영업<NA><NA><NA><NA>0226113888<NA><NA>서울특별시 구로구 오류동 38번지 7 호<NA><NA>오류시장2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
23160000197131600710750000119711019<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 6170617<NA><NA>서울특별시 구로구 고척동 50번지 48 호<NA><NA>고척시장2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
33160000197231600710750000519720121<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8551036<NA><NA>서울특별시 구로구 구로동 169번지 2 호<NA><NA>배영설비(주)2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
43160000197631600710750000119760806<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 6136162<NA><NA>서울특별시 구로구 개봉동 324번지 1 호<NA><NA>개봉중앙시장2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
53160000197631600710750000219761228<NA>1영업/정상1정상영업<NA><NA><NA><NA>0226172661<NA><NA>서울특별시 구로구 개봉동 361번지 1 호<NA><NA>개봉제일시장2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
63160000198631600710750000119861210<NA>2휴업2휴업처리<NA>2017070499991231<NA>02 686998213.0<NA>서울특별시 구로구 오류동 47번지 1 호<NA><NA>삼익쇼핑센터2017-07-04 13:08:29I2018-08-31 23:59:59.0쇼핑센터186015.73837443657.614265대규모점포
73160000198631600710750001519861101<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 2681-113310705.0<NA>서울특별시 구로구 고척동 103번지 4호서울특별시 구로구 중앙로3길 50 (고척동, 고척산업용품종합상가)08225고척산업용품상가2019-04-02 20:36:54U2019-04-04 02:40:00.0그 밖의 대규모점포187619.596959444186.92311대규모점포
83160000198931600710750002019890320<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8613891<NA><NA>서울특별시 구로구 구로동 685번지 140호서울특별시 구로구 구일로10길 93 (구로동)<NA>사모아종합상가2007-07-07 09:54:17I2018-08-31 23:59:59.0그 밖의 대규모점포189052.101789443748.27929<NA>
93160000199331600710750000119930830<NA>2휴업2휴업처리<NA><NA><NA><NA>02 818100024362.0<NA>서울특별시 구로구 구로동 573호서울특별시 구로구 구로중앙로 152 (구로동)<NA>애경백화점2007-07-07 09:54:17I2018-08-31 23:59:59.0백화점189570.36093444336.05133<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
433160000200731601170750001919930527<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2619-80683085.0152080서울특별시 구로구 고척동 269번지 1호서울특별시 구로구 고척로40길 19 (고척동)<NA>개봉프라자2017-07-04 13:11:54I2018-08-31 23:59:59.0시장186769.616926444433.221607대규모점포
443160000200731601170750002019711019<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 45281406992.0152081서울특별시 구로구 고척동 50번지 48호서울특별시 구로구 중앙로 64 (고척동)152824고척스카이프라자2018-08-30 09:12:25I2018-08-31 23:59:59.0그 밖의 대규모점포187798.869265444629.704822대규모점포
453160000200731601170750002119761228<NA>1영업/정상1정상영업<NA><NA><NA><NA>2683-87922464.0152090서울특별시 구로구 개봉동 361번지 1호서울특별시 구로구 개봉로3길 51 (개봉동)<NA>개봉제일시장2013-12-20 10:56:01I2018-08-31 23:59:59.0그 밖의 대규모점포186968.288545442651.907781대규모점포
46316000020113160159075000012011-08-10<NA>1영업/정상1정상영업<NA><NA><NA><NA>00023416528238414.15152-888서울특별시 구로구 신도림동 692번지서울특별시 구로구 경인로 662 (신도림동)152-888주식회사 현대백화점 디큐브시티2024-03-08 11:43:41U2023-12-02 23:00:00.0백화점190107.045415445157.626366<NA>
473160000201131601590750000220110919<NA>1영업/정상1정상영업<NA><NA><NA><NA>000226842013860.0152814서울특별시 구로구 개봉동 324-1, 324-11,324-13 1층서울특별시 구로구 개봉로17길 34 (개봉동)152814(주)이마트에브리데이 개봉동점2021-05-02 10:15:50U2021-05-04 02:40:00.0구분없음187009.804318443302.607793준대규모점포
48316000020123160159075000012012-04-20<NA>1영업/정상1정상영업<NA><NA><NA><NA>3459-8000246.0152-897서울특별시 구로구 오류2동 160번지 외 2필지서울특별시 구로구 서해안로 2293 (오류동,외 2필지)<NA>홈플러스 익스프레스 서울오류점2024-04-16 13:51:13U2023-12-03 23:08:00.0복합쇼핑몰185756.174923443268.099009<NA>
49316000020123160159075000022012-04-20<NA>1영업/정상1정상영업<NA><NA><NA><NA>2683-8545191.0152-805서울특별시 구로구 개봉1동 156번지 18호 외 1필지 대림프라자 101호서울특별시 구로구 경인로 319 (개봉동,외 1필지 대림프라자 101호)<NA>홈플러스 익스프레스 개봉점2024-04-16 13:55:11U2023-12-03 23:08:00.0구분없음187158.44383443952.56188<NA>
503160000201231601590750000320120620<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-868-8726228.69152720서울특별시 구로구 구로1동 650번지 4호 SK허브수 제B동 제118호,제119호,제121호~126호서울특별시 구일로10길 27, B동 1층 (제118호,제119호,제121호~126호)152720홈플러스 익스프레스 서울구로점2020-06-03 10:20:07U2020-06-05 02:40:00.0구분없음188674.995072443749.50302준대규모점포
513160000202031601590750000120200626<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-323-045649220.79<NA>서울특별시 구로구 구로동 573서울특별시 구로구 구로중앙로 152 (구로동)08292이랜드리테일 NC구로점2022-12-09 09:45:43U2021-11-01 23:01:00.0백화점189570.36093444336.05133<NA>
52316000020223160159075000012022-03-18<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-528-045040883.22<NA>서울특별시 구로구 고척동 100-7<NA><NA>고척아이파크쇼핑센터2023-10-12 17:09:57U2022-10-30 23:04:00.0쇼핑센터187477.579441444045.294922<NA>