Overview

Dataset statistics

Number of variables26
Number of observations22
Missing cells88
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory225.0 B

Variable types

Categorical10
Numeric4
DateTime4
Unsupported1
Text7

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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-18714/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
재개업일자 has constant value ""Constant
영업상태코드 is highly imbalanced (73.3%)Imbalance
영업상태명 is highly imbalanced (73.3%)Imbalance
상세영업상태코드 is highly imbalanced (73.3%)Imbalance
상세영업상태명 is highly imbalanced (73.3%)Imbalance
폐업일자 is highly imbalanced (73.3%)Imbalance
휴업시작일자 is highly imbalanced (73.3%)Imbalance
휴업종료일자 is highly imbalanced (73.3%)Imbalance
인허가취소일자 has 22 (100.0%) missing valuesMissing
재개업일자 has 21 (95.5%) missing valuesMissing
전화번호 has 1 (4.5%) missing valuesMissing
소재지우편번호 has 17 (77.3%) missing valuesMissing
지번주소 has 2 (9.1%) missing valuesMissing
도로명우편번호 has 6 (27.3%) missing valuesMissing
점포구분명 has 19 (86.4%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 1 (4.5%) zerosZeros

Reproduction

Analysis started2024-05-11 06:44:08.397623
Analysis finished2024-05-11 06:44:09.429046
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
3120000
22 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3120000
2nd row3120000
3rd row3120000
4th row3120000
5th row3120000

Common Values

ValueCountFrequency (%)
3120000 22
100.0%

Length

2024-05-11T06:44:09.652427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:10.000942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 22
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0118575 × 1018
Minimum1.970312 × 1018
Maximum2.024312 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-11T06:44:10.454396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.970312 × 1018
5-th percentile1.987312 × 1018
Q12.008312 × 1018
median2.018312 × 1018
Q32.021312 × 1018
95-th percentile2.024212 × 1018
Maximum2.024312 × 1018
Range5.4000013 × 1016
Interquartile range (IQR)1.3000008 × 1016

Descriptive statistics

Standard deviation1.4653875 × 1016
Coefficient of variation (CV)0.0072837539
Kurtosis1.979475
Mean2.0118575 × 1018
Median Absolute Deviation (MAD)4.5000024 × 1015
Skewness-1.624052
Sum7.3673762 × 1018
Variance2.1473604 × 1032
MonotonicityStrictly increasing
2024-05-11T06:44:11.075379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1970312009307500001 1
 
4.5%
2018312018307500004 1
 
4.5%
2024312021907500002 1
 
4.5%
2024312021907500001 1
 
4.5%
2022312019207500002 1
 
4.5%
2022312019207500001 1
 
4.5%
2021312019207500005 1
 
4.5%
2021312019207500004 1
 
4.5%
2021312019207500003 1
 
4.5%
2021312019207500002 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1970312009307500001 1
4.5%
1987312009307500001 1
4.5%
1987312009307500002 1
4.5%
1992312010707500001 1
4.5%
2006312009307500001 1
4.5%
2007312010707500001 1
4.5%
2011312014507500001 1
4.5%
2012312018307500002 1
4.5%
2013312014507500001 1
4.5%
2018312018307500001 1
4.5%
ValueCountFrequency (%)
2024312021907500002 1
4.5%
2024312021907500001 1
4.5%
2022312019207500002 1
4.5%
2022312019207500001 1
4.5%
2021312019207500005 1
4.5%
2021312019207500004 1
4.5%
2021312019207500003 1
4.5%
2021312019207500002 1
4.5%
2021312019207500001 1
4.5%
2018312018307500004 1
4.5%

인허가일자
Date

Distinct18
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum1970-08-14 00:00:00
Maximum2024-01-31 00:00:00
2024-05-11T06:44:11.435031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:44:11.846776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)100.0%
Memory size330.0 B

영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
21 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 21
95.5%
3 1
 
4.5%

Length

2024-05-11T06:44:12.356405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:12.826764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
95.5%
3 1
 
4.5%

영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
영업/정상
21 
폐업
 
1

Length

Max length5
Median length5
Mean length4.8636364
Min length2

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 21
95.5%
폐업 1
 
4.5%

Length

2024-05-11T06:44:13.212783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:13.561786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 21
95.5%
폐업 1
 
4.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
1
21 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
1 21
95.5%
3 1
 
4.5%

Length

2024-05-11T06:44:13.873989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:14.213289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
95.5%
3 1
 
4.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
정상영업
21 
폐업처리
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 21
95.5%
폐업처리 1
 
4.5%

Length

2024-05-11T06:44:14.670652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:15.027952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 21
95.5%
폐업처리 1
 
4.5%

폐업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
20221011
 
1

Length

Max length8
Median length4
Mean length4.1818182
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
20221011 1
 
4.5%

Length

2024-05-11T06:44:15.366519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:15.691113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
20221011 1
 
4.5%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
20220317
 
1

Length

Max length8
Median length4
Mean length4.1818182
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
20220317 1
 
4.5%

Length

2024-05-11T06:44:16.192623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:16.678254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
20220317 1
 
4.5%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
21 
20221231
 
1

Length

Max length8
Median length4
Mean length4.1818182
Min length4

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 21
95.5%
20221231 1
 
4.5%

Length

2024-05-11T06:44:17.164052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:17.595620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 21
95.5%
20221231 1
 
4.5%

재개업일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing21
Missing (%)95.5%
Memory size308.0 B
Minimum2007-06-28 00:00:00
Maximum2007-06-28 00:00:00
2024-05-11T06:44:18.065883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:44:18.558930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

전화번호
Text

MISSING 

Distinct20
Distinct (%)95.2%
Missing1
Missing (%)4.5%
Memory size308.0 B
2024-05-11T06:44:19.125459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.809524
Min length7

Characters and Unicode

Total characters227
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

Unique19 ?
Unique (%)90.5%

Sample

1st row02-3216-9393
2nd row02-373-7571
3rd row373-4914
4th row02-3145-3154
5th row02-2124-2148
ValueCountFrequency (%)
02-380-5042 2
 
9.5%
02-373-7571 1
 
4.8%
02-2006-2364 1
 
4.8%
02-380-5124 1
 
4.8%
02-338-5601 1
 
4.8%
02-391-5601 1
 
4.8%
02-373-5601 1
 
4.8%
02-373-9993 1
 
4.8%
02-2290-5704 1
 
4.8%
02-3216-9393 1
 
4.8%
Other values (10) 10
47.6%
2024-05-11T06:44:20.098931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39
17.2%
- 38
16.7%
3 32
14.1%
2 31
13.7%
4 14
 
6.2%
7 14
 
6.2%
1 13
 
5.7%
9 13
 
5.7%
5 12
 
5.3%
6 11
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39
20.6%
3 32
16.9%
2 31
16.4%
4 14
 
7.4%
7 14
 
7.4%
1 13
 
6.9%
9 13
 
6.9%
5 12
 
6.3%
6 11
 
5.8%
8 10
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 227
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39
17.2%
- 38
16.7%
3 32
14.1%
2 31
13.7%
4 14
 
6.2%
7 14
 
6.2%
1 13
 
5.7%
9 13
 
5.7%
5 12
 
5.3%
6 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39
17.2%
- 38
16.7%
3 32
14.1%
2 31
13.7%
4 14
 
6.2%
7 14
 
6.2%
1 13
 
5.7%
9 13
 
5.7%
5 12
 
5.3%
6 11
 
4.8%

소재지면적
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3895.9586
Minimum0
Maximum35471.76
Zeros1
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-11T06:44:20.648149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile180.379
Q1278.355
median1049.135
Q31992.5
95-th percentile14098.189
Maximum35471.76
Range35471.76
Interquartile range (IQR)1714.145

Descriptive statistics

Standard deviation8092.6148
Coefficient of variation (CV)2.0771819
Kurtosis11.530318
Mean3895.9586
Median Absolute Deviation (MAD)787.48
Skewness3.2471976
Sum85711.09
Variance65490415
MonotonicityNot monotonic
2024-05-11T06:44:21.067044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
275.04 2
 
9.1%
6606.0 1
 
4.5%
1100.0 1
 
4.5%
1133.21 1
 
4.5%
998.27 1
 
4.5%
357.0 1
 
4.5%
484.6 1
 
4.5%
178.5 1
 
4.5%
483.79 1
 
4.5%
216.08 1
 
4.5%
Other values (11) 11
50.0%
ValueCountFrequency (%)
0.0 1
4.5%
178.5 1
4.5%
216.08 1
4.5%
232.7 1
4.5%
275.04 2
9.1%
288.3 1
4.5%
357.0 1
4.5%
483.79 1
4.5%
484.6 1
4.5%
998.27 1
4.5%
ValueCountFrequency (%)
35471.76 1
4.5%
14133.01 1
4.5%
13436.59 1
4.5%
6606.0 1
4.5%
3305.0 1
4.5%
2040.0 1
4.5%
1850.0 1
4.5%
1573.0 1
4.5%
1273.2 1
4.5%
1133.21 1
4.5%

소재지우편번호
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing17
Missing (%)77.3%
Memory size308.0 B
2024-05-11T06:44:21.515353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.6
Min length6

Characters and Unicode

Total characters33
Distinct characters9
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

Unique5 ?
Unique (%)100.0%

Sample

1st row120-857
2nd row120-834
3rd row120808
4th row120110
5th row120-130
ValueCountFrequency (%)
120-857 1
20.0%
120-834 1
20.0%
120808 1
20.0%
120110 1
20.0%
120-130 1
20.0%
2024-05-11T06:44:22.523564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
24.2%
0 8
24.2%
2 5
15.2%
8 4
12.1%
- 3
 
9.1%
3 2
 
6.1%
5 1
 
3.0%
7 1
 
3.0%
4 1
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
90.9%
Dash Punctuation 3
 
9.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
26.7%
0 8
26.7%
2 5
16.7%
8 4
13.3%
3 2
 
6.7%
5 1
 
3.3%
7 1
 
3.3%
4 1
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
24.2%
0 8
24.2%
2 5
15.2%
8 4
12.1%
- 3
 
9.1%
3 2
 
6.1%
5 1
 
3.0%
7 1
 
3.0%
4 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
24.2%
0 8
24.2%
2 5
15.2%
8 4
12.1%
- 3
 
9.1%
3 2
 
6.1%
5 1
 
3.0%
7 1
 
3.0%
4 1
 
3.0%

지번주소
Text

MISSING 

Distinct18
Distinct (%)90.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-05-11T06:44:23.464612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27.5
Mean length26.8
Min length20

Characters and Unicode

Total characters536
Distinct characters77
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

Unique16 ?
Unique (%)80.0%

Sample

1st row서울특별시 서대문구 홍제3동 294번지 6호
2nd row서울특별시 서대문구 남가좌동 290번지 2 호
3rd row서울특별시 서대문구 창천동 30번지 33호
4th row서울특별시 서대문구 신촌동 74번지 12 호
5th row서울특별시 서대문구 대현동 145번지
ValueCountFrequency (%)
서울특별시 20
18.7%
서대문구 20
18.7%
남가좌동 5
 
4.7%
홍제동 4
 
3.7%
294번지 3
 
2.8%
대현동 3
 
2.8%
101호 2
 
1.9%
호 2
 
1.9%
창천동 2
 
1.9%
홍은동 2
 
1.9%
Other values (39) 44
41.1%
2024-05-11T06:44:24.965528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
16.8%
서 40
 
7.5%
대 24
 
4.5%
시 22
 
4.1%
동 22
 
4.1%
별 20
 
3.7%
울 20
 
3.7%
특 20
 
3.7%
1 20
 
3.7%
구 20
 
3.7%
Other values (67) 238
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 345
64.4%
Space Separator 90
 
16.8%
Decimal Number 89
 
16.6%
Dash Punctuation 6
 
1.1%
Uppercase Letter 6
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 40
 
11.6%
대 24
 
7.0%
시 22
 
6.4%
동 22
 
6.4%
별 20
 
5.8%
울 20
 
5.8%
특 20
 
5.8%
구 20
 
5.8%
문 20
 
5.8%
지 11
 
3.2%
Other values (52) 126
36.5%
Decimal Number
ValueCountFrequency (%)
1 20
22.5%
4 15
16.9%
2 11
12.4%
3 10
11.2%
0 10
11.2%
9 8
 
9.0%
6 6
 
6.7%
5 4
 
4.5%
8 3
 
3.4%
7 2
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
M 2
33.3%
D 2
33.3%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 345
64.4%
Common 185
34.5%
Latin 6
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 40
 
11.6%
대 24
 
7.0%
시 22
 
6.4%
동 22
 
6.4%
별 20
 
5.8%
울 20
 
5.8%
특 20
 
5.8%
구 20
 
5.8%
문 20
 
5.8%
지 11
 
3.2%
Other values (52) 126
36.5%
Common
ValueCountFrequency (%)
90
48.6%
1 20
 
10.8%
4 15
 
8.1%
2 11
 
5.9%
3 10
 
5.4%
0 10
 
5.4%
9 8
 
4.3%
- 6
 
3.2%
6 6
 
3.2%
5 4
 
2.2%
Other values (2) 5
 
2.7%
Latin
ValueCountFrequency (%)
C 2
33.3%
M 2
33.3%
D 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 345
64.4%
ASCII 191
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
47.1%
1 20
 
10.5%
4 15
 
7.9%
2 11
 
5.8%
3 10
 
5.2%
0 10
 
5.2%
9 8
 
4.2%
- 6
 
3.1%
6 6
 
3.1%
5 4
 
2.1%
Other values (5) 11
 
5.8%
Hangul
ValueCountFrequency (%)
서 40
 
11.6%
대 24
 
7.0%
시 22
 
6.4%
동 22
 
6.4%
별 20
 
5.8%
울 20
 
5.8%
특 20
 
5.8%
구 20
 
5.8%
문 20
 
5.8%
지 11
 
3.2%
Other values (52) 126
36.5%

도로명주소
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-05-11T06:44:25.861793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length35
Mean length31.272727
Min length20

Characters and Unicode

Total characters688
Distinct characters97
Distinct categories8 ?
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 (%)90.9%

Sample

1st row서울특별시 통일로 484 (유진상가)
2nd row서울특별시 서대문구 수색로2길 45 (남가좌동)
3rd row서울특별시 서대문구 수색로2길 47 (남가좌동)
4th row서울특별시 서대문구 신촌로 83 (창천동)
5th row서울특별시 서대문구 신촌역로 30 (신촌동)
ValueCountFrequency (%)
서울특별시 22
 
17.2%
서대문구 21
 
16.4%
통일로 5
 
3.9%
홍제동 4
 
3.1%
남가좌동 4
 
3.1%
거북골로 3
 
2.3%
1층 3
 
2.3%
유진상가 3
 
2.3%
대현동 3
 
2.3%
484 3
 
2.3%
Other values (46) 57
44.5%
2024-05-11T06:44:27.526779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
15.4%
서 43
 
6.2%
대 28
 
4.1%
시 24
 
3.5%
동 23
 
3.3%
별 22
 
3.2%
특 22
 
3.2%
울 22
 
3.2%
) 22
 
3.2%
( 22
 
3.2%
Other values (87) 354
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
62.6%
Space Separator 106
 
15.4%
Decimal Number 81
 
11.8%
Close Punctuation 22
 
3.2%
Open Punctuation 22
 
3.2%
Other Punctuation 18
 
2.6%
Uppercase Letter 6
 
0.9%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 43
 
10.0%
대 28
 
6.5%
시 24
 
5.6%
동 23
 
5.3%
별 22
 
5.1%
특 22
 
5.1%
울 22
 
5.1%
문 21
 
4.9%
구 21
 
4.9%
로 19
 
4.4%
Other values (70) 186
43.2%
Decimal Number
ValueCountFrequency (%)
1 17
21.0%
3 14
17.3%
4 14
17.3%
2 10
12.3%
0 9
11.1%
8 5
 
6.2%
9 5
 
6.2%
5 5
 
6.2%
7 2
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
M 2
33.3%
D 2
33.3%
Space Separator
ValueCountFrequency (%)
106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
62.6%
Common 251
36.5%
Latin 6
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 43
 
10.0%
대 28
 
6.5%
시 24
 
5.6%
동 23
 
5.3%
별 22
 
5.1%
특 22
 
5.1%
울 22
 
5.1%
문 21
 
4.9%
구 21
 
4.9%
로 19
 
4.4%
Other values (70) 186
43.2%
Common
ValueCountFrequency (%)
106
42.2%
) 22
 
8.8%
( 22
 
8.8%
, 18
 
7.2%
1 17
 
6.8%
3 14
 
5.6%
4 14
 
5.6%
2 10
 
4.0%
0 9
 
3.6%
8 5
 
2.0%
Other values (4) 14
 
5.6%
Latin
ValueCountFrequency (%)
C 2
33.3%
M 2
33.3%
D 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
62.6%
ASCII 257
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
41.2%
) 22
 
8.6%
( 22
 
8.6%
, 18
 
7.0%
1 17
 
6.6%
3 14
 
5.4%
4 14
 
5.4%
2 10
 
3.9%
0 9
 
3.5%
8 5
 
1.9%
Other values (7) 20
 
7.8%
Hangul
ValueCountFrequency (%)
서 43
 
10.0%
대 28
 
6.5%
시 24
 
5.6%
동 23
 
5.3%
별 22
 
5.1%
특 22
 
5.1%
울 22
 
5.1%
문 21
 
4.9%
구 21
 
4.9%
로 19
 
4.4%
Other values (70) 186
43.2%

도로명우편번호
Text

MISSING 

Distinct14
Distinct (%)87.5%
Missing6
Missing (%)27.3%
Memory size308.0 B
2024-05-11T06:44:28.122208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.25
Min length5

Characters and Unicode

Total characters84
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)75.0%

Sample

1st row120-760
2nd row120805
3rd row120813
4th row03730
5th row03628
ValueCountFrequency (%)
03628 2
12.5%
03764 2
12.5%
120-760 1
 
6.2%
120805 1
 
6.2%
120813 1
 
6.2%
03730 1
 
6.2%
03690 1
 
6.2%
03689 1
 
6.2%
03604 1
 
6.2%
03675 1
 
6.2%
Other values (4) 4
25.0%
2024-05-11T06:44:29.315297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21
25.0%
3 15
17.9%
6 12
14.3%
7 8
 
9.5%
2 6
 
7.1%
8 6
 
7.1%
4 5
 
6.0%
1 5
 
6.0%
5 3
 
3.6%
9 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
98.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
25.3%
3 15
18.1%
6 12
14.5%
7 8
 
9.6%
2 6
 
7.2%
8 6
 
7.2%
4 5
 
6.0%
1 5
 
6.0%
5 3
 
3.6%
9 2
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 21
25.0%
3 15
17.9%
6 12
14.3%
7 8
 
9.5%
2 6
 
7.1%
8 6
 
7.1%
4 5
 
6.0%
1 5
 
6.0%
5 3
 
3.6%
9 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21
25.0%
3 15
17.9%
6 12
14.3%
7 8
 
9.5%
2 6
 
7.1%
8 6
 
7.1%
4 5
 
6.0%
1 5
 
6.0%
5 3
 
3.6%
9 2
 
2.4%

사업장명
Text

Distinct21
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-05-11T06:44:30.000278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15.5
Mean length10.590909
Min length4

Characters and Unicode

Total characters233
Distinct characters71
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)90.9%

Sample

1st row유진상가
2nd row모래내시장(주)
3rd row서중시장
4th row현대백화점 신촌점
5th row신촌 밀리오레
ValueCountFrequency (%)
롯데슈퍼 6
 
13.0%
이마트에브리데이 3
 
6.5%
the 3
 
6.5%
gs 3
 
6.5%
fresh 3
 
6.5%
신촌이대역점 2
 
4.3%
남가좌점 2
 
4.3%
북가좌점 2
 
4.3%
홍은점 2
 
4.3%
명지대점 1
 
2.2%
Other values (19) 19
41.3%
2024-05-11T06:44:31.338698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
10.3%
점 17
 
7.3%
데 10
 
4.3%
이 9
 
3.9%
퍼 7
 
3.0%
슈 7
 
3.0%
롯 7
 
3.0%
S 7
 
3.0%
가 6
 
2.6%
E 6
 
2.6%
Other values (61) 133
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 167
71.7%
Uppercase Letter 33
 
14.2%
Space Separator 24
 
10.3%
Close Punctuation 4
 
1.7%
Open Punctuation 4
 
1.7%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 17
 
10.2%
데 10
 
6.0%
이 9
 
5.4%
퍼 7
 
4.2%
슈 7
 
4.2%
롯 7
 
4.2%
가 6
 
3.6%
좌 5
 
3.0%
리 5
 
3.0%
스 4
 
2.4%
Other values (49) 90
53.9%
Uppercase Letter
ValueCountFrequency (%)
S 7
21.2%
E 6
18.2%
H 6
18.2%
G 4
12.1%
T 3
9.1%
F 3
9.1%
R 3
9.1%
X 1
 
3.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 167
71.7%
Common 33
 
14.2%
Latin 33
 
14.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 17
 
10.2%
데 10
 
6.0%
이 9
 
5.4%
퍼 7
 
4.2%
슈 7
 
4.2%
롯 7
 
4.2%
가 6
 
3.6%
좌 5
 
3.0%
리 5
 
3.0%
스 4
 
2.4%
Other values (49) 90
53.9%
Latin
ValueCountFrequency (%)
S 7
21.2%
E 6
18.2%
H 6
18.2%
G 4
12.1%
T 3
9.1%
F 3
9.1%
R 3
9.1%
X 1
 
3.0%
Common
ValueCountFrequency (%)
24
72.7%
) 4
 
12.1%
( 4
 
12.1%
2 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 167
71.7%
ASCII 66
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
36.4%
S 7
 
10.6%
E 6
 
9.1%
H 6
 
9.1%
) 4
 
6.1%
G 4
 
6.1%
( 4
 
6.1%
T 3
 
4.5%
F 3
 
4.5%
R 3
 
4.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
점 17
 
10.2%
데 10
 
6.0%
이 9
 
5.4%
퍼 7
 
4.2%
슈 7
 
4.2%
롯 7
 
4.2%
가 6
 
3.6%
좌 5
 
3.0%
리 5
 
3.0%
스 4
 
2.4%
Other values (49) 90
53.9%

최종수정일자
Date

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2008-02-11 14:26:13
Maximum2024-05-09 10:15:49
2024-05-11T06:44:31.761323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:44:32.269873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
U
16 
I
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 16
72.7%
I 6
 
27.3%

Length

2024-05-11T06:44:32.710325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:33.096229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 16
72.7%
i 6
 
27.3%

데이터갱신일자
Date

Distinct10
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-04 23:01:00
2024-05-11T06:44:33.494025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T06:44:33.889587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

업태구분명
Categorical

Distinct4
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size308.0 B
구분없음
13 
시장
4 
그 밖의 대규모점포
4 
백화점
 
1

Length

Max length10
Median length4
Mean length4.6818182
Min length2

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
구분없음 13
59.1%
시장 4
 
18.2%
그 밖의 대규모점포 4
 
18.2%
백화점 1
 
4.5%

Length

2024-05-11T06:44:34.836426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T06:44:35.506321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구분없음 13
43.3%
시장 4
 
13.3%
그 4
 
13.3%
밖의 4
 
13.3%
대규모점포 4
 
13.3%
백화점 1
 
3.3%

좌표정보(X)
Real number (ℝ)

Distinct20
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean193908.98
Minimum192000.95
Maximum195332.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-11T06:44:36.029440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192000.95
5-th percentile192310.08
Q1192570.46
median193990.7
Q3195010.46
95-th percentile195329.59
Maximum195332.12
Range3331.1774
Interquartile range (IQR)2439.9909

Descriptive statistics

Standard deviation1212.0499
Coefficient of variation (CV)0.0062506128
Kurtosis-1.6909662
Mean193908.98
Median Absolute Deviation (MAD)1233.8775
Skewness-0.20204724
Sum4265997.5
Variance1469065.1
MonotonicityNot monotonic
2024-05-11T06:44:36.753706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
194850.361025035 2
 
9.1%
195332.123380254 2
 
9.1%
192480.02944094 1
 
4.5%
192482.416512858 1
 
4.5%
193139.52394401 1
 
4.5%
193624.014939084 1
 
4.5%
195196.693652181 1
 
4.5%
193440.549915639 1
 
4.5%
195280.710219904 1
 
4.5%
192728.938667675 1
 
4.5%
Other values (10) 10
45.5%
ValueCountFrequency (%)
192000.945942229 1
4.5%
192301.135452392 1
4.5%
192480.02944094 1
4.5%
192482.416512858 1
4.5%
192503.128282531 1
4.5%
192517.640245956 1
4.5%
192728.938667675 1
4.5%
193139.52394401 1
4.5%
193440.549915639 1
4.5%
193624.014939084 1
4.5%
ValueCountFrequency (%)
195332.123380254 2
9.1%
195281.395461663 1
4.5%
195280.710219904 1
4.5%
195196.693652181 1
4.5%
195063.820722531 1
4.5%
194850.361025035 2
9.1%
194811.756333333 1
4.5%
194798.458435966 1
4.5%
194265.067639805 1
4.5%
193716.339877929 1
4.5%

좌표정보(Y)
Real number (ℝ)

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean452525.4
Minimum450433.69
Maximum455193.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-05-11T06:44:37.364885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450433.69
5-th percentile450602.82
Q1451041.18
median452610.05
Q3453581.67
95-th percentile454344.43
Maximum455193.01
Range4759.3237
Interquartile range (IQR)2540.4878

Descriptive statistics

Standard deviation1428.538
Coefficient of variation (CV)0.0031568129
Kurtosis-1.0795947
Mean452525.4
Median Absolute Deviation (MAD)1101.0709
Skewness0.051661588
Sum9955558.8
Variance2040720.8
MonotonicityNot monotonic
2024-05-11T06:44:38.037329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
454344.432517428 2
 
9.1%
452143.491541077 2
 
9.1%
450806.05844472 2
 
9.1%
452634.55767379 1
 
4.5%
453106.002592232 1
 
4.5%
450696.745009002 1
 
4.5%
453764.706268517 1
 
4.5%
453256.425998955 1
 
4.5%
455193.014698844 1
 
4.5%
452585.54164581 1
 
4.5%
Other values (9) 9
40.9%
ValueCountFrequency (%)
450433.691021245 1
4.5%
450597.874088644 1
4.5%
450696.745009002 1
4.5%
450806.05844472 2
9.1%
450837.051726331 1
4.5%
451653.563671802 1
4.5%
452051.272452155 1
4.5%
452143.491541077 2
9.1%
452585.54164581 1
4.5%
452634.55767379 1
4.5%
ValueCountFrequency (%)
455193.014698844 1
4.5%
454344.432517428 2
9.1%
454300.739666667 1
4.5%
453764.706268517 1
4.5%
453657.534811024 1
4.5%
453354.065487403 1
4.5%
453256.425998955 1
4.5%
453106.002592232 1
4.5%
452848.009128439 1
4.5%
452634.55767379 1
4.5%

점포구분명
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing19
Missing (%)86.4%
Memory size308.0 B
2024-05-11T06:44:38.537903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.3333333
Min length5

Characters and Unicode

Total characters16
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row대규모점포
2nd row대규모점포
3rd row준대규모점포
ValueCountFrequency (%)
대규모점포 2
66.7%
준대규모점포 1
33.3%
2024-05-11T06:44:39.563637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 3
18.8%
규 3
18.8%
모 3
18.8%
점 3
18.8%
포 3
18.8%
준 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 3
18.8%
규 3
18.8%
모 3
18.8%
점 3
18.8%
포 3
18.8%
준 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 3
18.8%
규 3
18.8%
모 3
18.8%
점 3
18.8%
포 3
18.8%
준 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 3
18.8%
규 3
18.8%
모 3
18.8%
점 3
18.8%
포 3
18.8%
준 1
 
6.2%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
0312000019703120093075000011970-08-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3216-93936606.0120-857서울특별시 서대문구 홍제3동 294번지 6호서울특별시 통일로 484 (유진상가)120-760유진상가2023-03-15 09:20:00U2022-12-02 23:07:00.0시장194811.756333454300.739667<NA>
13120000198731200930750000119871024<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-373-75711100.0<NA>서울특별시 서대문구 남가좌동 290번지 2 호서울특별시 서대문구 수색로2길 45 (남가좌동)<NA>모래내시장(주)2009-04-03 17:09:28I2018-08-31 23:59:59.0시장192503.128283452051.272452<NA>
23120000198731200930750000219871024<NA>1영업/정상1정상영업<NA><NA><NA><NA>373-49141850.0<NA><NA>서울특별시 서대문구 수색로2길 47 (남가좌동)120805서중시장2012-03-30 10:14:18I2018-08-31 23:59:59.0시장192517.640246452143.491541대규모점포
3312000019923120107075000011992-11-19<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3145-315435471.76120-834서울특별시 서대문구 창천동 30번지 33호서울특별시 서대문구 신촌로 83 (창천동)<NA>현대백화점 신촌점2024-04-17 18:52:52U2023-12-03 23:09:00.0백화점194265.06764450433.691021<NA>
43120000200631200930750000120060919<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2124-214813436.59<NA>서울특별시 서대문구 신촌동 74번지 12 호서울특별시 서대문구 신촌역로 30 (신촌동)<NA>신촌 밀리오레2008-02-11 14:26:13I2018-08-31 23:59:59.0그 밖의 대규모점포194798.458436450837.051726<NA>
53120000200731201070750000120070809<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6373-700914133.01120808서울특별시 서대문구 대현동 145번지서울특별시 서대문구 이화여대1길 10 (대현동)<NA>예스에이피엠2008-09-18 17:17:57I2018-08-31 23:59:59.0그 밖의 대규모점포195063.820723450597.874089<NA>
63120000201131201450750000119990429<NA>1영업/정상1정상영업<NA><NA><NA><NA>83489003305.0120110서울특별시 서대문구 연희동 131번지 1호서울특별시 서대문구 연희맛로 23 (연희동)<NA>연희슈퍼마켓2017-10-31 16:46:32I2018-08-31 23:59:59.0시장193716.339878451653.563672대규모점포
73120000201231201830750000220120326<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-376-43971273.2<NA><NA>서울특별시 서대문구 응암로 54 (북가좌동)120813(주)GS리테일 북가좌점2016-02-25 15:45:33I2018-08-31 23:59:59.0구분없음192000.945942452848.009128준대규모점포
8312000020133120145075000012013-06-16<NA>1영업/정상1정상영업<NA><NA><NA>2007-06-28302-8023232.7120-130서울특별시 서대문구 북가좌동 279번지 11호서울특별시 서대문구 응암로 112 (북가좌동)<NA>홈플러스(주) 익스프레스 북가좌점2024-03-20 08:28:21U2023-12-02 22:02:00.0구분없음192301.135452453354.065487<NA>
9312000020183120183075000012012-02-07<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-739-67801573.0<NA>서울특별시 서대문구 홍제동 469번지 인왕산 한신휴플러스서울특별시 서대문구 통일로 397, 지4층 (홍제동, 인왕산 한신휴플러스)03730롯데슈퍼 홍제2점2023-03-15 09:23:03U2022-12-02 23:07:00.0구분없음195281.395462453657.534811<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
123120000201831201830750000420180412<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2290-57040.0<NA>서울특별시 서대문구 홍제동 294번지 46호 유진상가서울특별시 서대문구 통일로 484, 유진상가 (홍제동)03628롯데슈퍼 유진점(X)2022-08-30 10:27:10U2021-12-09 00:01:00.0구분없음194850.361025454344.432517<NA>
133120000202131201920750000120210716<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-373-9993216.08<NA>서울특별시 서대문구 남가좌동 390 래미안 루센티아서울특별시 서대문구 거북골로 100, 지하3층 32,33,34,35호 (남가좌동, 래미안 루센티아)03689GS THE FRESH 남가좌디엠씨점2022-08-30 10:23:24U2021-12-09 00:01:00.0구분없음192728.938668452585.541646<NA>
14312000020213120192075000022021-07-29<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-5042483.79<NA>서울특별시 서대문구 홍은동 11-419서울특별시 서대문구 홍은중앙로 89(홍은동)03604이마트에브리데이 홍은점2024-05-09 10:15:32U2023-12-04 23:01:00.0구분없음195280.71022455193.014699<NA>
15312000020213120192075000032021-12-20<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-373-5601178.5<NA>서울특별시 서대문구 홍은동 400-12서울특별시 서대문구 가좌로 99(홍은동)03675롯데프레시 홍은점2023-08-25 17:54:37U2022-12-07 22:07:00.0구분없음193440.549916453256.425999<NA>
163120000202131201920750000420211220<NA>3폐업3폐업처리202210112022031720221231<NA>02-391-5601484.6<NA>서울특별시 서대문구 홍제동 158-33 연세24시사우나서울특별시 서대문구 통일로 413, 연세24시사우나 (홍제동)03646롯데슈퍼 홍제점2022-10-20 18:02:31U2021-10-30 22:02:00.0구분없음195196.693652453764.706269<NA>
173120000202131201920750000520211220<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-338-5601357.0<NA>서울특별시 서대문구 창천동 506-20 아륭빌딩서울특별시 서대문구 신촌로 13, 아륭빌딩 (창천동)03785롯데슈퍼 창천점2022-04-26 13:45:04U2021-12-03 22:08:00.0구분없음193624.014939450696.745009<NA>
18312000020223120192075000012022-04-05<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-5042998.27<NA>서울특별시 서대문구 남가좌동 50-3 명지대학교서울특별시 서대문구 거북골로 34, 명지대학교 (남가좌동)03674이마트에브리데이 명지대점2024-05-09 10:15:49U2023-12-04 23:01:00.0구분없음193139.523944453106.002592<NA>
19312000020223120192075000022022-08-16<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-380-51241133.21<NA>서울특별시 서대문구 남가좌동 286-1 DMC금호리첸시아서울특별시 서대문구 수색로2길 39(남가좌동, DMC금호리첸시아)03712이마트에브리데이 남가좌점2024-05-09 10:14:51U2023-12-04 23:01:00.0구분없음192482.416513452143.491541<NA>
20312000020243120219075000012024-01-31<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2006-2364275.04<NA>서울특별시 서대문구 대현동 144 신촌럭키아파트 상가동 101호서울특별시 서대문구 이화여대길 50-12, 상가동 1층 101호 (대현동, 신촌럭키아파트)03764GS THE FRESH 신촌이대역점2024-04-26 14:11:56U2023-12-03 22:08:00.0그 밖의 대규모점포195332.12338450806.058445<NA>
21312000020243120219075000022024-01-31<NA>1영업/정상1정상영업<NA><NA><NA><NA><NA>275.04<NA>서울특별시 서대문구 대현동 144 신촌럭키아파트 상가동 101호서울특별시 서대문구 이화여대길 50-12, 상가동 1층 101호 (대현동, 신촌럭키아파트)03764GS THE FRESH 신촌이대역점2024-04-26 14:11:45U2023-12-03 22:08:00.0그 밖의 대규모점포195332.12338450806.058445<NA>