Overview

Dataset statistics

Number of variables26
Number of observations53
Missing cells111
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory220.5 B

Variable types

Categorical12
Numeric4
DateTime4
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
Author강동구
URLhttps://data.seoul.go.kr/dataList/OA-18726/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (86.5%)Imbalance
휴업시작일자 is highly imbalanced (86.5%)Imbalance
휴업종료일자 is highly imbalanced (86.5%)Imbalance
재개업일자 is highly imbalanced (86.5%)Imbalance
폐업일자 has 39 (73.6%) missing valuesMissing
전화번호 has 1 (1.9%) missing valuesMissing
소재지면적 has 3 (5.7%) missing valuesMissing
소재지우편번호 has 23 (43.4%) missing valuesMissing
지번주소 has 1 (1.9%) missing valuesMissing
도로명주소 has 21 (39.6%) missing valuesMissing
도로명우편번호 has 21 (39.6%) missing valuesMissing
좌표정보(X) has 1 (1.9%) missing valuesMissing
좌표정보(Y) has 1 (1.9%) missing valuesMissing
관리번호 has unique valuesUnique
소재지면적 has 1 (1.9%) zerosZeros

Reproduction

Analysis started2024-05-11 08:01:19.542339
Analysis finished2024-05-11 08:01:19.976236
Duration0.43 seconds
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
3240000
53 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3240000
2nd row3240000
3rd row3240000
4th row3240000
5th row3240000

Common Values

ValueCountFrequency (%)
3240000 53
100.0%

Length

2024-05-11T17:01:20.051788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:20.148092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3240000 53
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0072674 × 1018
Minimum1.968324 × 1018
Maximum2.019324 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T17:01:20.262139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.968324 × 1018
5-th percentile1.995724 × 1018
Q12.005324 × 1018
median2.008324 × 1018
Q32.011324 × 1018
95-th percentile2.014324 × 1018
Maximum2.019324 × 1018
Range5.1000013 × 1016
Interquartile range (IQR)6.000002 × 1015

Descriptive statistics

Standard deviation7.8137354 × 1015
Coefficient of variation (CV)0.0038927227
Kurtosis11.479848
Mean2.0072674 × 1018
Median Absolute Deviation (MAD)3.000002 × 1015
Skewness-2.6755232
Sum-4.2952917 × 1018
Variance6.105446 × 1031
MonotonicityStrictly increasing
2024-05-11T17:01:20.428026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1968324010907500001 1
 
1.9%
2011324013907500012 1
 
1.9%
2011324013907500001 1
 
1.9%
2011324013907500002 1
 
1.9%
2011324013907500003 1
 
1.9%
2011324013907500004 1
 
1.9%
2011324013907500005 1
 
1.9%
2011324013907500006 1
 
1.9%
2011324013907500007 1
 
1.9%
2011324013907500008 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1968324010907500001 1
1.9%
1990324007307500003 1
1.9%
1990324013907500001 1
1.9%
1999324013907500001 1
1.9%
2000324007307500002 1
1.9%
2001324010607500001 1
1.9%
2002324007307500000 1
1.9%
2002324007307500001 1
1.9%
2004324010607500001 1
1.9%
2005324010607500001 1
1.9%
ValueCountFrequency (%)
2019324023607500002 1
1.9%
2019324023607500001 1
1.9%
2014324018907500003 1
1.9%
2014324018907500002 1
1.9%
2014324018907500001 1
1.9%
2013324018907500003 1
1.9%
2013324018907500002 1
1.9%
2013324018907500001 1
1.9%
2011324017507500001 1
1.9%
2011324013907500015 1
1.9%

인허가일자
Date

Distinct29
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum1968-10-23 00:00:00
Maximum2019-10-30 00:00:00
2024-05-11T17:01:20.593301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:20.732107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
20081107
 
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%
20081107 1
 
1.9%

Length

2024-05-11T17:01:20.895963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:21.029906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20081107 1
 
1.9%

영업상태코드
Categorical

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
1
23 
2
15 
3
14 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 23
43.4%
2 15
28.3%
3 14
26.4%
4 1
 
1.9%

Length

2024-05-11T17:01:21.133753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:21.241792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 23
43.4%
2 15
28.3%
3 14
26.4%
4 1
 
1.9%

영업상태명
Categorical

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
영업/정상
23 
휴업
15 
폐업
14 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length3.5283019
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 23
43.4%
휴업 15
28.3%
폐업 14
26.4%
취소/말소/만료/정지/중지 1
 
1.9%

Length

2024-05-11T17:01:21.377873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:21.489953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 23
43.4%
휴업 15
28.3%
폐업 14
26.4%
취소/말소/만료/정지/중지 1
 
1.9%

상세영업상태코드
Categorical

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
1
20 
2
15 
3
14 
BBBB
 
2
4
 
1

Length

Max length4
Median length1
Mean length1.1132075
Min length1

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 20
37.7%
2 15
28.3%
3 14
26.4%
BBBB 2
 
3.8%
4 1
 
1.9%
5 1
 
1.9%

Length

2024-05-11T17:01:21.630072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:21.764638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 20
37.7%
2 15
28.3%
3 14
26.4%
bbbb 2
 
3.8%
4 1
 
1.9%
5 1
 
1.9%

상세영업상태명
Categorical

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
정상영업
20 
휴업처리
15 
폐업처리
14 
<NA>
 
2
직권취소
 
1

Length

Max length5
Median length4
Mean length4.0188679
Min length4

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 20
37.7%
휴업처리 15
28.3%
폐업처리 14
26.4%
<NA> 2
 
3.8%
직권취소 1
 
1.9%
영업개시전 1
 
1.9%

Length

2024-05-11T17:01:21.910791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:22.048033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 20
37.7%
휴업처리 15
28.3%
폐업처리 14
26.4%
na 2
 
3.8%
직권취소 1
 
1.9%
영업개시전 1
 
1.9%

폐업일자
Date

MISSING 

Distinct14
Distinct (%)100.0%
Missing39
Missing (%)73.6%
Memory size556.0 B
Minimum2012-03-22 00:00:00
Maximum2023-04-14 00:00:00
2024-05-11T17:01:22.207132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:22.342664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
20130725
 
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%
20130725 1
 
1.9%

Length

2024-05-11T17:01:22.485878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:22.611209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20130725 1
 
1.9%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
20140724
 
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%
20140724 1
 
1.9%

Length

2024-05-11T17:01:22.734237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:22.861048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20140724 1
 
1.9%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
52 
20060531
 
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%
20060531 1
 
1.9%

Length

2024-05-11T17:01:22.985248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:23.108405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
98.1%
20060531 1
 
1.9%

전화번호
Text

MISSING 

Distinct47
Distinct (%)90.4%
Missing1
Missing (%)1.9%
Memory size556.0 B
2024-05-11T17:01:23.327413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.019231
Min length4

Characters and Unicode

Total characters521
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)88.5%

Sample

1st row02-478-2191
2nd row0204793424
3rd row02-485-6644
4th row02-2225-8702
5th row000204887244
ValueCountFrequency (%)
02 11
 
14.9%
485 7
 
9.5%
9001 6
 
8.1%
4850731 2
 
2.7%
478 2
 
2.7%
4269122 1
 
1.4%
69332502 1
 
1.4%
4410671 1
 
1.4%
4758546 1
 
1.4%
4400785 1
 
1.4%
Other values (41) 41
55.4%
2024-05-11T17:01:23.756862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 112
21.5%
2 82
15.7%
4 68
13.1%
5 35
 
6.7%
1 33
 
6.3%
8 32
 
6.1%
31
 
6.0%
- 31
 
6.0%
7 27
 
5.2%
3 27
 
5.2%
Other values (2) 43
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 459
88.1%
Space Separator 31
 
6.0%
Dash Punctuation 31
 
6.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 112
24.4%
2 82
17.9%
4 68
14.8%
5 35
 
7.6%
1 33
 
7.2%
8 32
 
7.0%
7 27
 
5.9%
3 27
 
5.9%
6 23
 
5.0%
9 20
 
4.4%
Space Separator
ValueCountFrequency (%)
31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 521
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 112
21.5%
2 82
15.7%
4 68
13.1%
5 35
 
6.7%
1 33
 
6.3%
8 32
 
6.1%
31
 
6.0%
- 31
 
6.0%
7 27
 
5.2%
3 27
 
5.2%
Other values (2) 43
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 521
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 112
21.5%
2 82
15.7%
4 68
13.1%
5 35
 
6.7%
1 33
 
6.3%
8 32
 
6.1%
31
 
6.0%
- 31
 
6.0%
7 27
 
5.2%
3 27
 
5.2%
Other values (2) 43
 
8.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)82.0%
Missing3
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean5033.7718
Minimum0
Maximum36175
Zeros1
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T17:01:23.941647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile221.5945
Q11105.7525
median3223.68
Q36749.585
95-th percentile16454.862
Maximum36175
Range36175
Interquartile range (IQR)5643.8325

Descriptive statistics

Standard deviation6521.2779
Coefficient of variation (CV)1.2955053
Kurtosis9.8665472
Mean5033.7718
Median Absolute Deviation (MAD)2159.08
Skewness2.7129378
Sum251688.59
Variance42527065
MonotonicityNot monotonic
2024-05-11T17:01:24.126922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
3223.68 6
 
11.3%
8659.0 2
 
3.8%
4310.62 2
 
3.8%
14176.0 2
 
3.8%
17600.0 2
 
3.8%
363.69 1
 
1.9%
252.4 1
 
1.9%
1103.74 1
 
1.9%
1649.43 1
 
1.9%
196.39 1
 
1.9%
Other values (31) 31
58.5%
(Missing) 3
 
5.7%
ValueCountFrequency (%)
0.0 1
1.9%
189.1 1
1.9%
196.39 1
1.9%
252.4 1
1.9%
282.65 1
1.9%
324.0 1
1.9%
363.69 1
1.9%
369.0 1
1.9%
530.68 1
1.9%
585.01 1
1.9%
ValueCountFrequency (%)
36175.0 1
1.9%
17600.0 2
3.8%
15055.25 1
1.9%
14176.0 2
3.8%
10180.74 1
1.9%
9484.37 1
1.9%
9081.0 1
1.9%
8659.77 1
1.9%
8659.0 2
3.8%
7207.95 1
1.9%

소재지우편번호
Text

MISSING 

Distinct23
Distinct (%)76.7%
Missing23
Missing (%)43.4%
Memory size556.0 B
2024-05-11T17:01:24.341989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1333333
Min length6

Characters and Unicode

Total characters184
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

Unique17 ?
Unique (%)56.7%

Sample

1st row134873
2nd row134871
3rd row134890
4th row134873
5th row134840
ValueCountFrequency (%)
134873 3
 
10.0%
134855 2
 
6.7%
134031 2
 
6.7%
134771 2
 
6.7%
134832 2
 
6.7%
134871 2
 
6.7%
134-850 1
 
3.3%
134-857 1
 
3.3%
134061 1
 
3.3%
134813 1
 
3.3%
Other values (13) 13
43.3%
2024-05-11T17:01:24.676751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 45
24.5%
3 39
21.2%
4 32
17.4%
8 22
12.0%
7 12
 
6.5%
0 11
 
6.0%
5 9
 
4.9%
2 4
 
2.2%
- 4
 
2.2%
9 3
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
97.8%
Dash Punctuation 4
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 45
25.0%
3 39
21.7%
4 32
17.8%
8 22
12.2%
7 12
 
6.7%
0 11
 
6.1%
5 9
 
5.0%
2 4
 
2.2%
9 3
 
1.7%
6 3
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 45
24.5%
3 39
21.2%
4 32
17.4%
8 22
12.0%
7 12
 
6.5%
0 11
 
6.0%
5 9
 
4.9%
2 4
 
2.2%
- 4
 
2.2%
9 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 45
24.5%
3 39
21.2%
4 32
17.4%
8 22
12.0%
7 12
 
6.5%
0 11
 
6.0%
5 9
 
4.9%
2 4
 
2.2%
- 4
 
2.2%
9 3
 
1.6%

지번주소
Text

MISSING 

Distinct43
Distinct (%)82.7%
Missing1
Missing (%)1.9%
Memory size556.0 B
2024-05-11T17:01:24.907818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length23.519231
Min length18

Characters and Unicode

Total characters1223
Distinct characters66
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)75.0%

Sample

1st row서울특별시 강동구 천호동 421번지 1호
2nd row서울특별시 강동구 천호동 410번지 105호
3rd row서울특별시 강동구 천호동 410번지 105호
4th row서울특별시 강동구 천호동 455번지 8호
5th row서울특별시 강동구 천호동 565호
ValueCountFrequency (%)
서울특별시 52
20.6%
강동구 52
20.6%
천호동 24
 
9.5%
1호 12
 
4.8%
563호 7
 
2.8%
명일동 5
 
2.0%
2호 5
 
2.0%
422번지 5
 
2.0%
길동 4
 
1.6%
암사3동 3
 
1.2%
Other values (60) 83
32.9%
2024-05-11T17:01:25.618360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
248
20.3%
동 107
 
8.7%
호 64
 
5.2%
1 53
 
4.3%
시 53
 
4.3%
강 53
 
4.3%
서 52
 
4.3%
울 52
 
4.3%
구 52
 
4.3%
별 52
 
4.3%
Other values (56) 437
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 753
61.6%
Space Separator 248
 
20.3%
Decimal Number 218
 
17.8%
Other Punctuation 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 107
14.2%
호 64
 
8.5%
시 53
 
7.0%
강 53
 
7.0%
서 52
 
6.9%
울 52
 
6.9%
구 52
 
6.9%
별 52
 
6.9%
특 52
 
6.9%
지 48
 
6.4%
Other values (42) 168
22.3%
Decimal Number
ValueCountFrequency (%)
1 53
24.3%
4 39
17.9%
2 35
16.1%
5 27
12.4%
3 19
 
8.7%
6 16
 
7.3%
0 11
 
5.0%
8 8
 
3.7%
9 5
 
2.3%
7 5
 
2.3%
Space Separator
ValueCountFrequency (%)
248
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 753
61.6%
Common 470
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 107
14.2%
호 64
 
8.5%
시 53
 
7.0%
강 53
 
7.0%
서 52
 
6.9%
울 52
 
6.9%
구 52
 
6.9%
별 52
 
6.9%
특 52
 
6.9%
지 48
 
6.4%
Other values (42) 168
22.3%
Common
ValueCountFrequency (%)
248
52.8%
1 53
 
11.3%
4 39
 
8.3%
2 35
 
7.4%
5 27
 
5.7%
3 19
 
4.0%
6 16
 
3.4%
0 11
 
2.3%
8 8
 
1.7%
9 5
 
1.1%
Other values (4) 9
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 753
61.6%
ASCII 470
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
248
52.8%
1 53
 
11.3%
4 39
 
8.3%
2 35
 
7.4%
5 27
 
5.7%
3 19
 
4.0%
6 16
 
3.4%
0 11
 
2.3%
8 8
 
1.7%
9 5
 
1.1%
Other values (4) 9
 
1.9%
Hangul
ValueCountFrequency (%)
동 107
14.2%
호 64
 
8.5%
시 53
 
7.0%
강 53
 
7.0%
서 52
 
6.9%
울 52
 
6.9%
구 52
 
6.9%
별 52
 
6.9%
특 52
 
6.9%
지 48
 
6.4%
Other values (42) 168
22.3%

도로명주소
Text

MISSING 

Distinct31
Distinct (%)96.9%
Missing21
Missing (%)39.6%
Memory size556.0 B
2024-05-11T17:01:25.837735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length39
Mean length27.125
Min length22

Characters and Unicode

Total characters868
Distinct characters70
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

Unique30 ?
Unique (%)93.8%

Sample

1st row서울특별시 강동구 구천면로 205 (천호동)
2nd row서울특별시 강동구 진황도로 18 (천호동)
3rd row서울특별시 강동구 천호대로 1005 (천호동, 현대백화점)
4th row서울특별시 강동구 고덕로 276 (명일동)
5th row서울특별시 강동구 양재대로89길 16 (성내동)
ValueCountFrequency (%)
서울특별시 32
18.6%
강동구 32
18.6%
천호동 8
 
4.7%
양재대로 6
 
3.5%
성내동 6
 
3.5%
고덕로 5
 
2.9%
명일동 5
 
2.9%
둔촌동 4
 
2.3%
길동 4
 
2.3%
암사동 4
 
2.3%
Other values (52) 66
38.4%
2024-05-11T17:01:26.198561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
16.4%
동 66
 
7.6%
구 35
 
4.0%
1 34
 
3.9%
( 33
 
3.8%
시 33
 
3.8%
) 33
 
3.8%
서 32
 
3.7%
특 32
 
3.7%
별 32
 
3.7%
Other values (60) 396
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 518
59.7%
Space Separator 142
 
16.4%
Decimal Number 132
 
15.2%
Open Punctuation 33
 
3.8%
Close Punctuation 33
 
3.8%
Other Punctuation 9
 
1.0%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
 
12.7%
구 35
 
6.8%
시 33
 
6.4%
서 32
 
6.2%
특 32
 
6.2%
별 32
 
6.2%
강 32
 
6.2%
울 32
 
6.2%
로 32
 
6.2%
천 15
 
2.9%
Other values (45) 177
34.2%
Decimal Number
ValueCountFrequency (%)
1 34
25.8%
3 16
12.1%
2 15
11.4%
0 15
11.4%
8 12
 
9.1%
5 12
 
9.1%
6 9
 
6.8%
9 7
 
5.3%
7 7
 
5.3%
4 5
 
3.8%
Space Separator
ValueCountFrequency (%)
142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 518
59.7%
Common 350
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
 
12.7%
구 35
 
6.8%
시 33
 
6.4%
서 32
 
6.2%
특 32
 
6.2%
별 32
 
6.2%
강 32
 
6.2%
울 32
 
6.2%
로 32
 
6.2%
천 15
 
2.9%
Other values (45) 177
34.2%
Common
ValueCountFrequency (%)
142
40.6%
1 34
 
9.7%
( 33
 
9.4%
) 33
 
9.4%
3 16
 
4.6%
2 15
 
4.3%
0 15
 
4.3%
8 12
 
3.4%
5 12
 
3.4%
6 9
 
2.6%
Other values (5) 29
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 518
59.7%
ASCII 350
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
40.6%
1 34
 
9.7%
( 33
 
9.4%
) 33
 
9.4%
3 16
 
4.6%
2 15
 
4.3%
0 15
 
4.3%
8 12
 
3.4%
5 12
 
3.4%
6 9
 
2.6%
Other values (5) 29
 
8.3%
Hangul
ValueCountFrequency (%)
동 66
 
12.7%
구 35
 
6.8%
시 33
 
6.4%
서 32
 
6.2%
특 32
 
6.2%
별 32
 
6.2%
강 32
 
6.2%
울 32
 
6.2%
로 32
 
6.2%
천 15
 
2.9%
Other values (45) 177
34.2%

도로명우편번호
Text

MISSING 

Distinct28
Distinct (%)87.5%
Missing21
Missing (%)39.6%
Memory size556.0 B
2024-05-11T17:01:26.392975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1875
Min length5

Characters and Unicode

Total characters198
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

Unique25 ?
Unique (%)78.1%

Sample

1st row134873
2nd row134871
3rd row134-779
4th row134-825
5th row134890
ValueCountFrequency (%)
134873 3
 
9.4%
134771 2
 
6.2%
134871 2
 
6.2%
134-850 1
 
3.1%
134-854 1
 
3.1%
05224 1
 
3.1%
134825 1
 
3.1%
134-855 1
 
3.1%
134822 1
 
3.1%
134813 1
 
3.1%
Other values (18) 18
56.2%
2024-05-11T17:01:26.715170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 44
22.2%
4 37
18.7%
3 36
18.2%
8 26
13.1%
7 14
 
7.1%
5 10
 
5.1%
0 10
 
5.1%
2 8
 
4.0%
- 8
 
4.0%
9 3
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
96.0%
Dash Punctuation 8
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
23.2%
4 37
19.5%
3 36
18.9%
8 26
13.7%
7 14
 
7.4%
5 10
 
5.3%
0 10
 
5.3%
2 8
 
4.2%
9 3
 
1.6%
6 2
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 198
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 44
22.2%
4 37
18.7%
3 36
18.2%
8 26
13.1%
7 14
 
7.1%
5 10
 
5.1%
0 10
 
5.1%
2 8
 
4.0%
- 8
 
4.0%
9 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 44
22.2%
4 37
18.7%
3 36
18.2%
8 26
13.1%
7 14
 
7.1%
5 10
 
5.1%
0 10
 
5.1%
2 8
 
4.0%
- 8
 
4.0%
9 3
 
1.5%

사업장명
Text

Distinct41
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Memory size556.0 B
2024-05-11T17:01:26.973197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length14
Mean length9.4716981
Min length4

Characters and Unicode

Total characters502
Distinct characters98
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)64.2%

Sample

1st row천호시장
2nd row현대프라자
3rd row현대프라자
4th row현대백화점 천호점
5th row킴스클럽
ValueCountFrequency (%)
동아코아 6
 
7.4%
주)지에스리테일 5
 
6.2%
성내점 3
 
3.7%
천호신시장 3
 
3.7%
천호점 3
 
3.7%
주)이마트에브리데이 2
 
2.5%
둔촌점 2
 
2.5%
암사점 2
 
2.5%
홈플러스(주 2
 
2.5%
명일점 2
 
2.5%
Other values (43) 51
63.0%
2024-05-11T17:01:27.366112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 29
 
5.8%
28
 
5.6%
스 19
 
3.8%
주 19
 
3.8%
동 18
 
3.6%
( 17
 
3.4%
) 17
 
3.4%
이 14
 
2.8%
천 14
 
2.8%
아 14
 
2.8%
Other values (88) 313
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 428
85.3%
Space Separator 28
 
5.6%
Open Punctuation 17
 
3.4%
Close Punctuation 17
 
3.4%
Uppercase Letter 10
 
2.0%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 29
 
6.8%
스 19
 
4.4%
주 19
 
4.4%
동 18
 
4.2%
이 14
 
3.3%
천 14
 
3.3%
아 14
 
3.3%
호 12
 
2.8%
시 11
 
2.6%
일 11
 
2.6%
Other values (77) 267
62.4%
Uppercase Letter
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
G 1
10.0%
T 1
10.0%
F 1
10.0%
R 1
10.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 430
85.7%
Common 62
 
12.4%
Latin 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 29
 
6.7%
스 19
 
4.4%
주 19
 
4.4%
동 18
 
4.2%
이 14
 
3.3%
천 14
 
3.3%
아 14
 
3.3%
호 12
 
2.8%
시 11
 
2.6%
일 11
 
2.6%
Other values (78) 269
62.6%
Latin
ValueCountFrequency (%)
E 2
20.0%
H 2
20.0%
S 2
20.0%
G 1
10.0%
T 1
10.0%
F 1
10.0%
R 1
10.0%
Common
ValueCountFrequency (%)
28
45.2%
( 17
27.4%
) 17
27.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 428
85.3%
ASCII 72
 
14.3%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 29
 
6.8%
스 19
 
4.4%
주 19
 
4.4%
동 18
 
4.2%
이 14
 
3.3%
천 14
 
3.3%
아 14
 
3.3%
호 12
 
2.8%
시 11
 
2.6%
일 11
 
2.6%
Other values (77) 267
62.4%
ASCII
ValueCountFrequency (%)
28
38.9%
( 17
23.6%
) 17
23.6%
E 2
 
2.8%
H 2
 
2.8%
S 2
 
2.8%
G 1
 
1.4%
T 1
 
1.4%
F 1
 
1.4%
R 1
 
1.4%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정일자
Date

Distinct38
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2007-06-30 10:04:31
Maximum2024-04-02 21:47:55
2024-05-11T17:01:27.509330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:27.661291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
I
35 
U
18 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 35
66.0%
U 18
34.0%

Length

2024-05-11T17:01:27.784252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:27.878932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 35
66.0%
u 18
34.0%

데이터갱신일자
Date

Distinct16
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:04:00
2024-05-11T17:01:27.969893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:28.080192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

업태구분명
Categorical

Distinct6
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size556.0 B
그 밖의 대규모점포
18 
구분없음
15 
대형마트
9 
쇼핑센터
6 
시장
4 

Length

Max length10
Median length4
Mean length5.8679245
Min length2

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 18
34.0%
구분없음 15
28.3%
대형마트 9
17.0%
쇼핑센터 6
 
11.3%
시장 4
 
7.5%
백화점 1
 
1.9%

Length

2024-05-11T17:01:28.233781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:28.398409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 18
20.2%
밖의 18
20.2%
대규모점포 18
20.2%
구분없음 15
16.9%
대형마트 9
10.1%
쇼핑센터 6
 
6.7%
시장 4
 
4.5%
백화점 1
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)63.5%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean211793.24
Minimum210566.88
Maximum214293.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T17:01:28.627253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum210566.88
5-th percentile210982.72
Q1211152.99
median211499.62
Q3212145.19
95-th percentile213587.04
Maximum214293.09
Range3726.2097
Interquartile range (IQR)992.19056

Descriptive statistics

Standard deviation855.89416
Coefficient of variation (CV)0.0040411778
Kurtosis0.72150159
Mean211793.24
Median Absolute Deviation (MAD)457.31683
Skewness1.1056061
Sum11013249
Variance732554.81
MonotonicityNot monotonic
2024-05-11T17:01:28.777885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
211055.486155787 8
 
15.1%
211979.520569314 3
 
5.7%
211252.735515916 3
 
5.7%
211196.195653708 2
 
3.8%
211265.331889504 2
 
3.8%
211336.172451748 2
 
3.8%
213493.90717524 2
 
3.8%
212501.369116329 2
 
3.8%
212082.014198045 2
 
3.8%
213700.877714971 2
 
3.8%
Other values (23) 24
45.3%
ValueCountFrequency (%)
210566.875626134 1
 
1.9%
210694.989265395 1
 
1.9%
210929.919693661 1
 
1.9%
211025.924972294 2
 
3.8%
211055.486155787 8
15.1%
211185.497701374 1
 
1.9%
211196.195653708 2
 
3.8%
211238.661063855 1
 
1.9%
211252.735515916 3
 
5.7%
211265.331889504 2
 
3.8%
ValueCountFrequency (%)
214293.085340515 1
1.9%
213700.877714971 2
3.8%
213493.90717524 2
3.8%
213048.692179757 1
1.9%
212676.162193508 1
1.9%
212624.891449347 1
1.9%
212501.369116329 2
3.8%
212349.37381605 1
1.9%
212334.9584644 1
1.9%
212334.69890736 1
1.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)63.5%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean448874.33
Minimum446932.65
Maximum450636.63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2024-05-11T17:01:28.918435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446932.65
5-th percentile447077.32
Q1448479.44
median448786.7
Q3449633.22
95-th percentile450347.69
Maximum450636.63
Range3703.9727
Interquartile range (IQR)1153.7725

Descriptive statistics

Standard deviation972.24855
Coefficient of variation (CV)0.0021659705
Kurtosis-0.46543727
Mean448874.33
Median Absolute Deviation (MAD)536.59278
Skewness-0.035466294
Sum23341465
Variance945267.24
MonotonicityNot monotonic
2024-05-11T17:01:29.064172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
448786.697371515 8
 
15.1%
446932.653730601 3
 
5.7%
448823.39875114 3
 
5.7%
448722.851784118 2
 
3.8%
448886.316858581 2
 
3.8%
448556.794492412 2
 
3.8%
450038.847319845 2
 
3.8%
449282.31038379 2
 
3.8%
450348.793644384 2
 
3.8%
450278.100930843 2
 
3.8%
Other values (23) 24
45.3%
ValueCountFrequency (%)
446932.653730601 3
5.7%
447195.676766748 1
 
1.9%
447402.629676369 1
 
1.9%
447670.852055872 1
 
1.9%
447728.865137096 1
 
1.9%
447815.986328694 1
 
1.9%
448150.595848877 1
 
1.9%
448182.588454494 1
 
1.9%
448202.632546787 1
 
1.9%
448209.124823551 1
 
1.9%
ValueCountFrequency (%)
450636.626425939 1
1.9%
450348.793644384 2
3.8%
450346.790651613 1
1.9%
450308.559655461 1
1.9%
450278.100930843 2
3.8%
450264.276387605 1
1.9%
450124.105734971 1
1.9%
450038.847319845 2
3.8%
450020.355211693 1
1.9%
449910.881572138 1
1.9%

점포구분명
Categorical

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
<NA>
29 
대규모점포
13 
준대규모점포
11 

Length

Max length6
Median length4
Mean length4.6603774
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 29
54.7%
대규모점포 13
24.5%
준대규모점포 11
 
20.8%

Length

2024-05-11T17:01:29.259613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:29.394148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
54.7%
대규모점포 13
24.5%
준대규모점포 11
 
20.8%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03240000196832401090750000119681023<NA>3폐업3폐업처리20190201<NA><NA><NA>02-478-21911735.5134873서울특별시 강동구 천호동 421번지 1호서울특별시 강동구 구천면로 205 (천호동)134873천호시장2019-02-06 12:27:14U2019-02-08 02:40:00.0그 밖의 대규모점포211196.195654448722.851784대규모점포
13240000199032400730750000319900528<NA>2휴업2휴업처리<NA><NA><NA><NA>0204793424<NA><NA>서울특별시 강동구 천호동 410번지 105호<NA><NA>현대프라자2007-06-30 10:04:31I2018-08-31 23:59:59.0그 밖의 대규모점포211336.172452448556.794492<NA>
23240000199032401390750000119900528<NA>3폐업3폐업처리20200514<NA><NA><NA>02-485-664415055.25134871서울특별시 강동구 천호동 410번지 105호서울특별시 강동구 진황도로 18 (천호동)134871현대프라자2020-05-15 09:38:40U2020-05-17 02:40:00.0그 밖의 대규모점포211336.172452448556.794492대규모점포
3324000019993240139075000011999-04-12<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2225-870236175.0<NA>서울특별시 강동구 천호동 455번지 8호서울특별시 강동구 천호대로 1005 (천호동, 현대백화점)134-779현대백화점 천호점2024-03-11 17:26:40U2023-12-02 23:03:00.0백화점210929.919694448537.406728<NA>
43240000200032400730750000220000614<NA>2휴업2휴업처리<NA><NA><NA><NA>000204887244<NA><NA>서울특별시 강동구 천호동 565호<NA><NA>킴스클럽2007-06-30 10:04:31I2018-08-31 23:59:59.0대형마트211750.896224448202.632547<NA>
53240000200132401060750000120010327<NA>2휴업2휴업처리<NA><NA><NA><NA>000222241053<NA><NA>서울특별시 강동구 천호동 454번지 0001호<NA><NA>이마트천호점2007-06-30 10:04:31I2018-08-31 23:59:59.0대형마트211025.924972448495.189152<NA>
6324000020023240073075000002002-11-20<NA>1영업/정상1정상영업<NA><NA><NA><NA>02214510518659.0<NA>서울특별시 강동구 명일동 46번지 4 호서울특별시 강동구 고덕로 276 (명일동)134-825(주)이마트명일점2023-07-20 09:28:46U2022-12-06 22:02:00.0그 밖의 대규모점포213700.877715450278.100931<NA>
73240000200232400730750000120021120<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>0002042962408659.77<NA>서울특별시 강동구 명일동 46번지 4호<NA><NA>신세계 이마트 명일점2007-06-30 10:04:31I2018-08-31 23:59:59.0대형마트213700.877715450278.100931<NA>
83240000200432401060750000120040524<NA>1영업/정상1정상영업<NA><NA><NA><NA>0002047826354075.83134890서울특별시 강동구 성내동 428번지 2호서울특별시 강동구 양재대로89길 16 (성내동)134890파크프라자 상가2014-10-15 14:25:41I2018-08-31 23:59:59.0그 밖의 대규모점포211838.35431447195.676767대규모점포
93240000200532401060750000120050112<NA>2휴업2휴업처리<NA><NA><NA><NA>02 485 07314310.62<NA>서울특별시 강동구 천호동 422번지 2호<NA><NA>천호신시장2007-06-30 10:04:31I2018-08-31 23:59:59.0그 밖의 대규모점포211252.735516448823.398751<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
433240000201132401390750001520111007<NA>3폐업3폐업처리20140531<NA><NA><NA>02-474-56011128.0134061서울특별시 강동구 둔촌1동 444번지서울특별시 강동구 풍성로63길 84 (둔촌동)134822롯데쇼핑(주)롯데슈퍼둔촌점2014-06-16 08:05:17I2018-08-31 23:59:59.0대형마트212334.698907447728.865137준대규모점포
44324000020113240175075000012011-11-28<NA>3폐업3폐업처리2023-03-24<NA><NA><NA>0222963651363.69<NA><NA>서울특별시 강동구 고덕로 99 (암사동)134-855(주)이마트에브리데이 암사동점2023-03-21 18:54:48U2022-12-04 22:06:00.0구분없음211970.119823450308.559655<NA>
453240000201332401890750000119820527<NA>1영업/정상BBBB<NA><NA><NA><NA><NA>00000.0134855서울특별시 강동구 암사3동 451번지 16호<NA><NA>양지종합시장2013-02-13 10:17:42I2018-08-31 23:59:59.0시장212082.014198450348.793644대규모점포
463240000201332401890750000220070704<NA>3폐업3폐업처리201310292013072520140724<NA>44160001324.0134855서울특별시 강동구 암사3동 451번지 16호<NA><NA>양지종합시장2013-10-29 18:39:00I2018-08-31 23:59:59.0시장212082.014198450348.793644대규모점포
473240000201332401890750000319920502<NA>1영업/정상1정상영업<NA><NA><NA><NA>428-77449484.37134825서울특별시 강동구 명일동 48번지서울특별시 강동구 고덕로62길 55 (명일동)134825주양쇼핑2013-12-23 15:10:48I2018-08-31 23:59:59.0그 밖의 대규모점포213493.907175450038.84732대규모점포
483240000201432401890750000119961212<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-477-122310180.74134871서울특별시 강동구 천호동 410번지 100호서울특별시 강동구 진황도로 12 (천호동)134871천호코오롱상가2022-01-20 14:27:20U2022-01-22 02:40:00.0그 밖의 대규모점포211279.030242448548.819717대규모점포
493240000201432401890750000219701231<NA>3폐업3폐업처리20190826<NA><NA><NA>02-478-14434348.7134873서울특별시 강동구 천호동 422번지 1호서울특별시 강동구 올림픽로80길 58 (천호동)134873동서울시장2019-08-26 17:57:25U2019-08-28 02:40:00.0시장211265.33189448886.316859대규모점포
503240000201432401890750000319820118<NA>3폐업3폐업처리20180529<NA><NA><NA>02-476-31547207.95134771서울특별시 강동구 둔촌동 172번지 1호서울특별시 강동구 양재대로 1330 (둔촌동)134771둔촌종합상가2018-07-03 16:08:22I2018-08-31 23:59:59.0그 밖의 대규모점포211979.520569446932.653731대규모점포
513240000201932402360750000120190604<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2422719.46<NA>서울특별시 강동구 고덕동 217번지 고덕그라시움아파트(상가1동)서울특별시 강동구 고덕로 353, 고덕그라시움아파트(상가1동) 지하1층 108-119,128호 (고덕동)05224지에스 더프레시(GS THE FRESH) 고덕그라시움점2020-04-24 10:10:40U2020-04-26 02:40:00.0구분없음214293.085341450636.626426준대규모점포
52324000020193240236075000022019-10-30<NA>3폐업3폐업처리2023-04-14<NA><NA><NA>02-380-5554530.68<NA>서울특별시 강동구 성내동 595번지 코오롱 2차아파트서울특별시 강동구 올림픽로 572, 상가동 1층 101,102호 (성내동, 코오롱 2차아파트)05391이마트에브리데이 성내점2023-04-28 17:58:50U2022-12-03 21:00:00.0구분없음210694.989265447815.986329<NA>