Overview

Dataset statistics

Number of variables26
Number of observations31
Missing cells193
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory223.3 B

Variable types

Categorical9
Numeric4
DateTime3
Unsupported4
Text6

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),점포구분명
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-18722/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 31 (100.0%) missing valuesMissing
폐업일자 has 28 (90.3%) missing valuesMissing
휴업시작일자 has 31 (100.0%) missing valuesMissing
휴업종료일자 has 31 (100.0%) missing valuesMissing
재개업일자 has 31 (100.0%) missing valuesMissing
소재지면적 has 3 (9.7%) missing valuesMissing
소재지우편번호 has 18 (58.1%) missing valuesMissing
지번주소 has 2 (6.5%) missing valuesMissing
도로명주소 has 8 (25.8%) missing valuesMissing
도로명우편번호 has 8 (25.8%) missing valuesMissing
좌표정보(X) has 1 (3.2%) missing valuesMissing
좌표정보(Y) has 1 (3.2%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 1 (3.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:49:53.110264
Analysis finished2024-05-11 05:49:53.752757
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
3200000
31 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 31
100.0%

Length

2024-05-11T14:49:53.885682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:54.061818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 31
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0022232 × 1018
Minimum1.96932 × 1018
Maximum2.02432 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T14:49:54.223038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.96932 × 1018
5-th percentile1.97082 × 1018
Q11.99282 × 1018
median2.01132 × 1018
Q32.01282 × 1018
95-th percentile2.01682 × 1018
Maximum2.02432 × 1018
Range5.5000014 × 1016
Interquartile range (IQR)2.0000011 × 1016

Descriptive statistics

Standard deviation1.6468873 × 1016
Coefficient of variation (CV)0.0082252932
Kurtosis-0.33927673
Mean2.0022232 × 1018
Median Absolute Deviation (MAD)5.0000111 × 1015
Skewness-1.038
Sum6.7286882 × 1018
Variance2.7122378 × 1032
MonotonicityStrictly increasing
2024-05-11T14:49:54.448068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1969320008007500006 1
 
3.2%
1970320008007500004 1
 
3.2%
2024320022507500001 1
 
3.2%
2018320021707500001 1
 
3.2%
2015320021107500002 1
 
3.2%
2015320021107500001 1
 
3.2%
2014320019107500003 1
 
3.2%
2014320019107500002 1
 
3.2%
2014320019107500001 1
 
3.2%
2013320019107500001 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1969320008007500006 1
3.2%
1970320008007500004 1
3.2%
1971320008007500002 1
3.2%
1972320008007500015 1
3.2%
1975320008007500013 1
3.2%
1977320022507500001 1
3.2%
1988320008007500019 1
3.2%
1992320008007500020 1
3.2%
1993320008007500021 1
3.2%
2004320008007500001 1
3.2%
ValueCountFrequency (%)
2024320022507500001 1
3.2%
2018320021707500001 1
3.2%
2015320021107500002 1
3.2%
2015320021107500001 1
3.2%
2014320019107500003 1
3.2%
2014320019107500002 1
3.2%
2014320019107500001 1
3.2%
2013320019107500001 1
3.2%
2012320019107500003 1
3.2%
2012320019107500002 1
3.2%

인허가일자
Date

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1969-10-15 00:00:00
Maximum2024-01-30 00:00:00
2024-05-11T14:49:54.639716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:54.869221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
25 
3
3 
2
3 

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 25
80.6%
3 3
 
9.7%
2 3
 
9.7%

Length

2024-05-11T14:49:55.132629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:55.315143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
80.6%
3 3
 
9.7%
2 3
 
9.7%

영업상태명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업/정상
25 
폐업
3 
휴업
3 

Length

Max length5
Median length5
Mean length4.4193548
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 25
80.6%
폐업 3
 
9.7%
휴업 3
 
9.7%

Length

2024-05-11T14:49:55.506390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:55.697263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 25
80.6%
폐업 3
 
9.7%
휴업 3
 
9.7%

상세영업상태코드
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
25 
3
3 
2
3 

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 25
80.6%
3 3
 
9.7%
2 3
 
9.7%

Length

2024-05-11T14:49:55.891781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:56.045625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
80.6%
3 3
 
9.7%
2 3
 
9.7%

상세영업상태명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
정상영업
25 
폐업처리
3 
휴업처리
3 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 25
80.6%
폐업처리 3
 
9.7%
휴업처리 3
 
9.7%

Length

2024-05-11T14:49:56.228406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:49:56.397901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 25
80.6%
폐업처리 3
 
9.7%
휴업처리 3
 
9.7%

폐업일자
Date

MISSING 

Distinct3
Distinct (%)100.0%
Missing28
Missing (%)90.3%
Memory size380.0 B
Minimum2016-09-26 00:00:00
Maximum2024-03-19 00:00:00
2024-05-11T14:49:56.611917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:49:56.803531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing31
Missing (%)100.0%
Memory size411.0 B

전화번호
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-05-11T14:49:57.077702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.612903
Min length8

Characters and Unicode

Total characters329
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

Unique25 ?
Unique (%)80.6%

Sample

1st row02 8564355
2nd row02 8782184
3rd row02 8782184
4th row02-882-0492
5th row02 8788001
ValueCountFrequency (%)
02 9
21.4%
8782184 2
 
4.8%
02889 2
 
4.8%
2003 2
 
4.8%
8564355 2
 
4.8%
02-889-8188 1
 
2.4%
02-3289-8728 1
 
2.4%
02-523-5691 1
 
2.4%
02-6948-8121 1
 
2.4%
02-865-7577 1
 
2.4%
Other values (20) 20
47.6%
2024-05-11T14:49:57.695214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 60
18.2%
0 57
17.3%
2 52
15.8%
- 30
9.1%
5 23
 
7.0%
6 20
 
6.1%
3 17
 
5.2%
1 17
 
5.2%
7 16
 
4.9%
13
 
4.0%
Other values (3) 24
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 285
86.6%
Dash Punctuation 30
 
9.1%
Space Separator 13
 
4.0%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 60
21.1%
0 57
20.0%
2 52
18.2%
5 23
 
8.1%
6 20
 
7.0%
3 17
 
6.0%
1 17
 
6.0%
7 16
 
5.6%
4 12
 
4.2%
9 11
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 329
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 60
18.2%
0 57
17.3%
2 52
15.8%
- 30
9.1%
5 23
 
7.0%
6 20
 
6.1%
3 17
 
5.2%
1 17
 
5.2%
7 16
 
4.9%
13
 
4.0%
Other values (3) 24
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 60
18.2%
0 57
17.3%
2 52
15.8%
- 30
9.1%
5 23
 
7.0%
6 20
 
6.1%
3 17
 
5.2%
1 17
 
5.2%
7 16
 
4.9%
13
 
4.0%
Other values (3) 24
 
7.3%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct27
Distinct (%)96.4%
Missing3
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean3989.4082
Minimum0
Maximum21711.05
Zeros1
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T14:49:57.928023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile143.62
Q1565.15
median1893
Q34874.9175
95-th percentile15591.04
Maximum21711.05
Range21711.05
Interquartile range (IQR)4309.7675

Descriptive statistics

Standard deviation5312.2314
Coefficient of variation (CV)1.3315838
Kurtosis4.4965105
Mean3989.4082
Median Absolute Deviation (MAD)1723.015
Skewness2.1454583
Sum111703.43
Variance28219803
MonotonicityNot monotonic
2024-05-11T14:49:58.135982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
5697.0 2
 
6.5%
156.1 1
 
3.2%
162.48 1
 
3.2%
1294.0 1
 
3.2%
4096.65 1
 
3.2%
925.0 1
 
3.2%
634.45 1
 
3.2%
4379.68 1
 
3.2%
0.0 1
 
3.2%
14784.0 1
 
3.2%
Other values (17) 17
54.8%
(Missing) 3
 
9.7%
ValueCountFrequency (%)
0.0 1
3.2%
136.9 1
3.2%
156.1 1
3.2%
162.48 1
3.2%
288.0 1
3.2%
414.86 1
3.2%
529.0 1
3.2%
577.2 1
3.2%
634.45 1
3.2%
925.0 1
3.2%
ValueCountFrequency (%)
21711.05 1
3.2%
16025.6 1
3.2%
14784.0 1
3.2%
7081.47 1
3.2%
6516.61 1
3.2%
5697.0 2
6.5%
4600.89 1
3.2%
4379.68 1
3.2%
4096.65 1
3.2%
3608.51 1
3.2%

소재지우편번호
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing18
Missing (%)58.1%
Memory size380.0 B
2024-05-11T14:49:58.407679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.1538462
Min length6

Characters and Unicode

Total characters80
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

Unique13 ?
Unique (%)100.0%

Sample

1st row151725
2nd row151930
3rd row151836
4th row151818
5th row151-823
ValueCountFrequency (%)
151725 1
 
7.7%
151930 1
 
7.7%
151836 1
 
7.7%
151818 1
 
7.7%
151-823 1
 
7.7%
151826 1
 
7.7%
151858 1
 
7.7%
151888 1
 
7.7%
151718 1
 
7.7%
151802 1
 
7.7%
Other values (3) 3
23.1%
2024-05-11T14:49:58.893281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 28
35.0%
5 16
20.0%
8 15
18.8%
0 5
 
6.2%
2 4
 
5.0%
3 4
 
5.0%
7 2
 
2.5%
9 2
 
2.5%
6 2
 
2.5%
- 2
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
97.5%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 28
35.9%
5 16
20.5%
8 15
19.2%
0 5
 
6.4%
2 4
 
5.1%
3 4
 
5.1%
7 2
 
2.6%
9 2
 
2.6%
6 2
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 28
35.0%
5 16
20.0%
8 15
18.8%
0 5
 
6.2%
2 4
 
5.0%
3 4
 
5.0%
7 2
 
2.5%
9 2
 
2.5%
6 2
 
2.5%
- 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 28
35.0%
5 16
20.0%
8 15
18.8%
0 5
 
6.2%
2 4
 
5.0%
3 4
 
5.0%
7 2
 
2.5%
9 2
 
2.5%
6 2
 
2.5%
- 2
 
2.5%

지번주소
Text

MISSING 

Distinct27
Distinct (%)93.1%
Missing2
Missing (%)6.5%
Memory size380.0 B
2024-05-11T14:49:59.239331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length23.275862
Min length7

Characters and Unicode

Total characters675
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)86.2%

Sample

1st row 호
2nd row서울특별시 관악구 봉천동 951번지 25호
3rd row서울특별시 관악구 봉천동 951번지 25호
4th row서울특별시 관악구 봉천동 502번지 4호
5th row서울특별시 관악구 신림동 1426번지 7호
ValueCountFrequency (%)
서울특별시 28
19.6%
관악구 28
19.6%
봉천동 12
 
8.4%
신림동 7
 
4.9%
4호 4
 
2.8%
2호 4
 
2.8%
5호 3
 
2.1%
1호 3
 
2.1%
1422번지 3
 
2.1%
25호 2
 
1.4%
Other values (46) 49
34.3%
2024-05-11T14:49:59.848430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
20.0%
서 29
 
4.3%
관 29
 
4.3%
악 29
 
4.3%
동 29
 
4.3%
1 29
 
4.3%
특 28
 
4.1%
별 28
 
4.1%
시 28
 
4.1%
구 28
 
4.1%
Other values (53) 283
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 407
60.3%
Space Separator 135
 
20.0%
Decimal Number 130
 
19.3%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 29
 
7.1%
관 29
 
7.1%
악 29
 
7.1%
동 29
 
7.1%
특 28
 
6.9%
별 28
 
6.9%
시 28
 
6.9%
구 28
 
6.9%
울 28
 
6.9%
지 25
 
6.1%
Other values (41) 126
31.0%
Decimal Number
ValueCountFrequency (%)
1 29
22.3%
2 24
18.5%
5 14
10.8%
4 13
10.0%
6 12
9.2%
0 11
 
8.5%
7 9
 
6.9%
9 8
 
6.2%
3 7
 
5.4%
8 3
 
2.3%
Space Separator
ValueCountFrequency (%)
135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 407
60.3%
Common 268
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 29
 
7.1%
관 29
 
7.1%
악 29
 
7.1%
동 29
 
7.1%
특 28
 
6.9%
별 28
 
6.9%
시 28
 
6.9%
구 28
 
6.9%
울 28
 
6.9%
지 25
 
6.1%
Other values (41) 126
31.0%
Common
ValueCountFrequency (%)
135
50.4%
1 29
 
10.8%
2 24
 
9.0%
5 14
 
5.2%
4 13
 
4.9%
6 12
 
4.5%
0 11
 
4.1%
7 9
 
3.4%
9 8
 
3.0%
3 7
 
2.6%
Other values (2) 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 407
60.3%
ASCII 268
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
50.4%
1 29
 
10.8%
2 24
 
9.0%
5 14
 
5.2%
4 13
 
4.9%
6 12
 
4.5%
0 11
 
4.1%
7 9
 
3.4%
9 8
 
3.0%
3 7
 
2.6%
Other values (2) 6
 
2.2%
Hangul
ValueCountFrequency (%)
서 29
 
7.1%
관 29
 
7.1%
악 29
 
7.1%
동 29
 
7.1%
특 28
 
6.9%
별 28
 
6.9%
시 28
 
6.9%
구 28
 
6.9%
울 28
 
6.9%
지 25
 
6.1%
Other values (41) 126
31.0%

도로명주소
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing8
Missing (%)25.8%
Memory size380.0 B
2024-05-11T14:50:00.225651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length27
Mean length24.434783
Min length14

Characters and Unicode

Total characters562
Distinct characters58
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

Unique23 ?
Unique (%)100.0%

Sample

1st row서울특별시 관악구 양녕로 49 (봉천동)
2nd row서울특별시 관악구 관악로 212 (봉천동)
3rd row서울특별시 관악구 관악로40길 47 (봉천동)
4th row서울특별시 관악구 신림로29길 8 (신림동)
5th row서울특별시 관악구 신림로 340 (신림동)
ValueCountFrequency (%)
서울특별시 23
19.7%
관악구 22
18.8%
봉천동 12
 
10.3%
신림동 8
 
6.8%
신림로 3
 
2.6%
봉천로 2
 
1.7%
남현동 2
 
1.7%
양녕로 2
 
1.7%
남부순환로248길 1
 
0.9%
청림6길 1
 
0.9%
Other values (41) 41
35.0%
2024-05-11T14:50:00.847138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
16.9%
악 25
 
4.4%
관 25
 
4.4%
서 23
 
4.1%
울 23
 
4.1%
동 23
 
4.1%
시 23
 
4.1%
특 23
 
4.1%
별 23
 
4.1%
( 22
 
3.9%
Other values (48) 257
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 341
60.7%
Space Separator 95
 
16.9%
Decimal Number 78
 
13.9%
Open Punctuation 22
 
3.9%
Close Punctuation 22
 
3.9%
Other Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
악 25
 
7.3%
관 25
 
7.3%
서 23
 
6.7%
울 23
 
6.7%
동 23
 
6.7%
시 23
 
6.7%
특 23
 
6.7%
별 23
 
6.7%
구 22
 
6.5%
로 19
 
5.6%
Other values (34) 112
32.8%
Decimal Number
ValueCountFrequency (%)
1 18
23.1%
2 11
14.1%
0 10
12.8%
3 8
10.3%
4 8
10.3%
9 6
 
7.7%
6 6
 
7.7%
7 5
 
6.4%
8 3
 
3.8%
5 3
 
3.8%
Space Separator
ValueCountFrequency (%)
95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 341
60.7%
Common 221
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
악 25
 
7.3%
관 25
 
7.3%
서 23
 
6.7%
울 23
 
6.7%
동 23
 
6.7%
시 23
 
6.7%
특 23
 
6.7%
별 23
 
6.7%
구 22
 
6.5%
로 19
 
5.6%
Other values (34) 112
32.8%
Common
ValueCountFrequency (%)
95
43.0%
( 22
 
10.0%
) 22
 
10.0%
1 18
 
8.1%
2 11
 
5.0%
0 10
 
4.5%
3 8
 
3.6%
4 8
 
3.6%
9 6
 
2.7%
6 6
 
2.7%
Other values (4) 15
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 341
60.7%
ASCII 221
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
43.0%
( 22
 
10.0%
) 22
 
10.0%
1 18
 
8.1%
2 11
 
5.0%
0 10
 
4.5%
3 8
 
3.6%
4 8
 
3.6%
9 6
 
2.7%
6 6
 
2.7%
Other values (4) 15
 
6.8%
Hangul
ValueCountFrequency (%)
악 25
 
7.3%
관 25
 
7.3%
서 23
 
6.7%
울 23
 
6.7%
동 23
 
6.7%
시 23
 
6.7%
특 23
 
6.7%
별 23
 
6.7%
구 22
 
6.5%
로 19
 
5.6%
Other values (34) 112
32.8%

도로명우편번호
Text

MISSING 

Distinct19
Distinct (%)82.6%
Missing8
Missing (%)25.8%
Memory size380.0 B
2024-05-11T14:50:01.136225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.9565217
Min length5

Characters and Unicode

Total characters137
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 (%)73.9%

Sample

1st row151840
2nd row151725
3rd row151050
4th row151761
5th row151890
ValueCountFrequency (%)
151015 4
17.4%
151836 2
 
8.7%
151826 1
 
4.3%
08793 1
 
4.3%
151803 1
 
4.3%
08734 1
 
4.3%
151-801 1
 
4.3%
151802 1
 
4.3%
151718 1
 
4.3%
151750 1
 
4.3%
Other values (9) 9
39.1%
2024-05-11T14:50:01.667848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49
35.8%
5 27
19.7%
0 16
 
11.7%
8 15
 
10.9%
7 8
 
5.8%
3 7
 
5.1%
6 4
 
2.9%
2 4
 
2.9%
9 3
 
2.2%
4 2
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
98.5%
Dash Punctuation 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
36.3%
5 27
20.0%
0 16
 
11.9%
8 15
 
11.1%
7 8
 
5.9%
3 7
 
5.2%
6 4
 
3.0%
2 4
 
3.0%
9 3
 
2.2%
4 2
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 137
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
35.8%
5 27
19.7%
0 16
 
11.7%
8 15
 
10.9%
7 8
 
5.8%
3 7
 
5.1%
6 4
 
2.9%
2 4
 
2.9%
9 3
 
2.2%
4 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 49
35.8%
5 27
19.7%
0 16
 
11.7%
8 15
 
10.9%
7 8
 
5.8%
3 7
 
5.1%
6 4
 
2.9%
2 4
 
2.9%
9 3
 
2.2%
4 2
 
1.5%

사업장명
Text

Distinct27
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-05-11T14:50:02.110898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length9.2580645
Min length4

Characters and Unicode

Total characters287
Distinct characters77
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

Unique24 ?
Unique (%)77.4%

Sample

1st row관악종합시장
2nd row봉일시장
3rd row봉일시장
4th row봉천현대시장
5th row가야쇼핑
ValueCountFrequency (%)
르네상스쇼핑몰(주 3
 
6.1%
홈플러스 3
 
6.1%
주)지에스리테일 2
 
4.1%
관악종합시장 2
 
4.1%
봉일시장 2
 
4.1%
익스프레스 2
 
4.1%
fresh 2
 
4.1%
the 2
 
4.1%
관악점 2
 
4.1%
신림중앙시장 1
 
2.0%
Other values (28) 28
57.1%
2024-05-11T14:50:02.815768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
6.3%
스 14
 
4.9%
시 10
 
3.5%
점 10
 
3.5%
( 10
 
3.5%
) 10
 
3.5%
주 9
 
3.1%
장 9
 
3.1%
관 9
 
3.1%
악 9
 
3.1%
Other values (67) 179
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 228
79.4%
Uppercase Letter 20
 
7.0%
Space Separator 18
 
6.3%
Open Punctuation 10
 
3.5%
Close Punctuation 10
 
3.5%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 14
 
6.1%
시 10
 
4.4%
점 10
 
4.4%
주 9
 
3.9%
장 9
 
3.9%
관 9
 
3.9%
악 9
 
3.9%
쇼 7
 
3.1%
핑 7
 
3.1%
림 7
 
3.1%
Other values (56) 137
60.1%
Uppercase Letter
ValueCountFrequency (%)
H 4
20.0%
E 4
20.0%
S 4
20.0%
R 2
10.0%
F 2
10.0%
T 2
10.0%
G 2
10.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 228
79.4%
Common 39
 
13.6%
Latin 20
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 14
 
6.1%
시 10
 
4.4%
점 10
 
4.4%
주 9
 
3.9%
장 9
 
3.9%
관 9
 
3.9%
악 9
 
3.9%
쇼 7
 
3.1%
핑 7
 
3.1%
림 7
 
3.1%
Other values (56) 137
60.1%
Latin
ValueCountFrequency (%)
H 4
20.0%
E 4
20.0%
S 4
20.0%
R 2
10.0%
F 2
10.0%
T 2
10.0%
G 2
10.0%
Common
ValueCountFrequency (%)
18
46.2%
( 10
25.6%
) 10
25.6%
2 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 228
79.4%
ASCII 59
 
20.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
30.5%
( 10
16.9%
) 10
16.9%
H 4
 
6.8%
E 4
 
6.8%
S 4
 
6.8%
R 2
 
3.4%
F 2
 
3.4%
T 2
 
3.4%
G 2
 
3.4%
Hangul
ValueCountFrequency (%)
스 14
 
6.1%
시 10
 
4.4%
점 10
 
4.4%
주 9
 
3.9%
장 9
 
3.9%
관 9
 
3.9%
악 9
 
3.9%
쇼 7
 
3.1%
핑 7
 
3.1%
림 7
 
3.1%
Other values (56) 137
60.1%

최종수정일자
Date

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2007-06-30 10:48:16
Maximum2024-04-04 09:48:14
2024-05-11T14:50:03.034385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:50:03.231370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)

데이터갱신구분
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
I
22 
U
9 

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 22
71.0%
U 9
29.0%

Length

2024-05-11T14:50:03.448173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:03.630346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 22
71.0%
u 9
29.0%

데이터갱신일자
Categorical

Distinct10
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2018-08-31 23:59:59.0
22 
2023-12-02 22:07:00.0
 
1
2021-10-20 02:40:00.0
 
1
2023-12-04 00:06:00.0
 
1
2021-05-16 02:40:00.0
 
1
Other values (5)
5 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique9 ?
Unique (%)29.0%

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 22
71.0%
2023-12-02 22:07:00.0 1
 
3.2%
2021-10-20 02:40:00.0 1
 
3.2%
2023-12-04 00:06:00.0 1
 
3.2%
2021-05-16 02:40:00.0 1
 
3.2%
2020-03-11 02:40:00.0 1
 
3.2%
2021-12-04 23:02:00.0 1
 
3.2%
2023-12-02 23:04:00.0 1
 
3.2%
2021-12-04 00:03:00.0 1
 
3.2%
2023-12-02 00:03:00.0 1
 
3.2%

Length

2024-05-11T14:50:03.833767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:04.048359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 22
35.5%
23:59:59.0 22
35.5%
2023-12-02 3
 
4.8%
02:40:00.0 3
 
4.8%
2021-12-04 2
 
3.2%
00:03:00.0 2
 
3.2%
22:07:00.0 1
 
1.6%
2021-10-20 1
 
1.6%
2023-12-04 1
 
1.6%
00:06:00.0 1
 
1.6%
Other values (4) 4
 
6.5%

업태구분명
Categorical

Distinct7
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size380.0 B
그 밖의 대규모점포
11 
구분없음
7 
시장
4 
쇼핑센터
3 
복합쇼핑몰
3 
Other values (2)
3 

Length

Max length10
Median length5
Mean length5.9354839
Min length2

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 11
35.5%
구분없음 7
22.6%
시장 4
 
12.9%
쇼핑센터 3
 
9.7%
복합쇼핑몰 3
 
9.7%
대형마트 2
 
6.5%
백화점 1
 
3.2%

Length

2024-05-11T14:50:04.313759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:04.582478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
그 11
20.8%
밖의 11
20.8%
대규모점포 11
20.8%
구분없음 7
13.2%
시장 4
 
7.5%
쇼핑센터 3
 
5.7%
복합쇼핑몰 3
 
5.7%
대형마트 2
 
3.8%
백화점 1
 
1.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)90.0%
Missing1
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean194764.77
Minimum192096.35
Maximum198374.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T14:50:04.799685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum192096.35
5-th percentile192632.27
Q1193746.83
median194486.27
Q3195898.26
95-th percentile197395.32
Maximum198374.47
Range6278.1237
Interquartile range (IQR)2151.4285

Descriptive statistics

Standard deviation1553.6742
Coefficient of variation (CV)0.0079771825
Kurtosis-0.26831963
Mean194764.77
Median Absolute Deviation (MAD)925.54946
Skewness0.48001328
Sum5842943.2
Variance2413903.4
MonotonicityNot monotonic
2024-05-11T14:50:05.027346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
193746.833837509 3
 
9.7%
194486.270488664 2
 
6.5%
194457.492960109 1
 
3.2%
194553.838438621 1
 
3.2%
196912.833572618 1
 
3.2%
196338.0 1
 
3.2%
192893.347466833 1
 
3.2%
196384.544308046 1
 
3.2%
194203.825172 1
 
3.2%
192096.349629652 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
192096.349629652 1
 
3.2%
192597.407974484 1
 
3.2%
192674.885947244 1
 
3.2%
192893.347466833 1
 
3.2%
193301.885808714 1
 
3.2%
193580.366498464 1
 
3.2%
193746.833837509 3
9.7%
193750.825947451 1
 
3.2%
193754.427350029 1
 
3.2%
193957.944323928 1
 
3.2%
ValueCountFrequency (%)
198374.473281221 1
3.2%
197790.079787758 1
3.2%
196912.833572618 1
3.2%
196501.159765837 1
3.2%
196384.544308046 1
3.2%
196338.0 1
3.2%
196257.833652996 1
3.2%
195963.335274799 1
3.2%
195703.043681259 1
3.2%
195431.465419568 1
3.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)90.0%
Missing1
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean442181.83
Minimum440903.82
Maximum443341.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-05-11T14:50:05.263454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum440903.82
5-th percentile440965.89
Q1441488.55
median442452.91
Q3442673.5
95-th percentile443061.31
Maximum443341.38
Range2437.5598
Interquartile range (IQR)1184.9468

Descriptive statistics

Standard deviation701.99111
Coefficient of variation (CV)0.0015875621
Kurtosis-0.94181738
Mean442181.83
Median Absolute Deviation (MAD)333.53114
Skewness-0.51646173
Sum13265455
Variance492791.51
MonotonicityNot monotonic
2024-05-11T14:50:05.468137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
442510.775085572 3
 
9.7%
442632.469540589 2
 
6.5%
440910.563872941 1
 
3.2%
442719.413175605 1
 
3.2%
441358.893188526 1
 
3.2%
442951.0 1
 
3.2%
440903.81963928 1
 
3.2%
442822.980265735 1
 
3.2%
441229.929157 1
 
3.2%
442339.213626523 1
 
3.2%
Other values (17) 17
54.8%
ValueCountFrequency (%)
440903.81963928 1
3.2%
440910.563872941 1
3.2%
441033.513044892 1
3.2%
441229.929157 1
3.2%
441231.59187991 1
3.2%
441352.743493574 1
3.2%
441358.893188526 1
3.2%
441437.774867372 1
3.2%
441640.881044209 1
3.2%
441896.302934956 1
3.2%
ValueCountFrequency (%)
443341.379446435 1
3.2%
443151.561302292 1
3.2%
442951.0 1
3.2%
442822.980265735 1
3.2%
442753.219280937 1
3.2%
442719.413175605 1
3.2%
442716.301708689 1
3.2%
442676.831360439 1
3.2%
442663.498606503 1
3.2%
442632.469540589 2
6.5%

점포구분명
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
13 
대규모점포
13 
준대규모점포
5 

Length

Max length6
Median length5
Mean length4.7419355
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 13
41.9%
대규모점포 13
41.9%
준대규모점포 5
 
16.1%

Length

2024-05-11T14:50:05.684141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:50:05.886093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
41.9%
대규모점포 13
41.9%
준대규모점포 5
 
16.1%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03200000196932000800750000619691015<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8564355<NA><NA>호<NA><NA>관악종합시장2007-06-30 10:48:16I2018-08-31 23:59:59.0그 밖의 대규모점포<NA><NA><NA>
13200000197032000800750000419701203<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8782184<NA><NA>서울특별시 관악구 봉천동 951번지 25호<NA><NA>봉일시장2007-06-30 10:48:16I2018-08-31 23:59:59.0그 밖의 대규모점포194486.270489442632.469541<NA>
23200000197132000800750000219711222<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8782184<NA><NA>서울특별시 관악구 봉천동 951번지 25호<NA><NA>봉일시장2007-06-30 10:48:16I2018-08-31 23:59:59.0그 밖의 대규모점포194486.270489442632.469541<NA>
33200000197232000800750001519720129<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-882-04921714.0<NA>서울특별시 관악구 봉천동 502번지 4호서울특별시 관악구 양녕로 49 (봉천동)151840봉천현대시장2017-10-24 13:20:26I2018-08-31 23:59:59.0시장195206.056917442716.301709대규모점포
43200000197532000800750001319751226<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 8788001288.0<NA>서울특별시 관악구 신림동 1426번지 7호<NA><NA>가야쇼핑2010-02-17 10:43:44I2018-08-31 23:59:59.0시장193750.825947442753.219281<NA>
5320000019773200225075000011977-05-26<NA>3폐업3폐업처리2024-03-19<NA><NA><NA>02-0000-00002740.0<NA>서울특별시 관악구 신림동 505-1<NA><NA>신림종합시장2024-03-25 17:13:27U2023-12-02 22:07:00.0그 밖의 대규모점포192597.407974442498.61759<NA>
63200000198832000800750001919881023<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 88718717081.47151725서울특별시 관악구 봉천동 31번지 1호서울특별시 관악구 관악로 212 (봉천동)151725관악프라자2014-10-17 10:36:45I2018-08-31 23:59:59.0쇼핑센터195963.335275442381.53601대규모점포
73200000199232000800750002019920826<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 88209244600.89<NA>서울특별시 관악구 봉천동 1000호서울특별시 관악구 관악로40길 47 (봉천동)151050관악현대상가2014-09-24 08:54:47I2018-08-31 23:59:59.0그 밖의 대규모점포196257.833653443341.379446대규모점포
83200000199332000800750002119930701<NA>1영업/정상1정상영업<NA><NA><NA><NA>02 88542712072.0<NA>서울특별시 관악구 신림동 1694호서울특별시 관악구 신림로29길 8 (신림동)151761신림현대종합상가2015-03-03 11:53:12I2018-08-31 23:59:59.0시장193957.944324441437.774867대규모점포
93200000200432000800750000120040922<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-888-06306516.61<NA>서울특별시 관악구 신림동 1422번지 5호서울특별시 관악구 신림로 340 (신림동)151890르네상스쇼핑몰(주)2016-11-17 17:15:18I2018-08-31 23:59:59.0복합쇼핑몰193746.833838442510.775086대규모점포
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
213200000201232001910750000219971107<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-3289-872821711.05151718서울특별시 관악구 보라매동 729호 22통 롯데백화점서울특별시 봉천로 209151718롯데쇼핑(주) 관악점2022-05-10 15:03:14U2021-12-04 23:02:00.0백화점193301.885809443151.561302<NA>
223200000201232001910750000320120521<NA>3폐업3폐업처리20160926<NA><NA><NA>02-523-5691136.9151802서울특별시 관악구 남현동 1078번지 2호서울특별시 관악구 남현길 79 (남현동)151802롯데쇼핑(주)롯데슈퍼 남현2점2016-09-26 18:08:15I2018-08-31 23:59:59.0구분없음197790.079788441231.59188준대규모점포
23320000020133200191075000012013-06-27<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6948-812114784.0151-080서울특별시 관악구 남현동 산 69번지 51호서울특별시 관악구 과천대로 909 (남현동)151-801홈플러스 서울남현점2024-03-12 10:28:27U2023-12-02 23:04:00.0대형마트198374.473281441033.513045<NA>
243200000201432001910750000119780807<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-865-75770.0<NA><NA>서울특별시 관악구 조원로16길 27 (신림동)151015신림중앙시장2016-12-28 13:20:17I2018-08-31 23:59:59.0시장192096.34963442339.213627대규모점포
253200000201432001910750000220140123<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-889-81884379.68151895서울특별시 관악구 대학동 1523번지서울특별시 관악구 신림로23길 16 (신림동)151015일성트루엘상가2016-02-03 10:17:30I2018-08-31 23:59:59.0그 밖의 대규모점포194203.825172441229.929157대규모점포
263200000201432001910750000320220325<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-877-6661634.45<NA>서울특별시 관악구 봉천동 1717-3 관악푸르지오서울특별시 관악구 청림6길 3, 관악푸르지오 상가동 110,113,114호 (봉천동)08734지에스 더 프레시(GS THE FRESH) 관악청림점2022-04-01 11:03:22U2021-12-04 00:03:00.0구분없음196384.544308442822.980266<NA>
273200000201532002110750000119770108<NA>1영업/정상1정상영업<NA><NA><NA><NA>028531866925.0<NA><NA>서울특별시 관악구 난곡로26길 4 (신림동)151015우림시장2015-09-16 16:45:52I2018-08-31 23:59:59.0그 밖의 대규모점포192893.347467440903.819639대규모점포
283200000201532002110750000220150709<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-885-45794096.65151803서울특별시 관악구 봉천동 10번지 4호 외14필지서울특별시 관악구 청림3길 10 (봉천동)151803관악쇼핑2016-07-20 18:06:16I2018-08-31 23:59:59.0그 밖의 대규모점포196338.0442951.0대규모점포
293200000201832002170750000119800828<NA>1영업/정상1정상영업<NA><NA><NA><NA>888-09301294.0<NA>서울특별시 관악구 봉천동 1638번지 20호서울특별시 관악구 남부순환로248길 35 (봉천동)08793원당종합시장2018-03-05 17:08:19I2018-08-31 23:59:59.0그 밖의 대규모점포196912.833573441358.893189대규모점포
30320000020243200225075000012024-01-30<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-882-4458162.48<NA>서울특별시 관악구 봉천동 952-1서울특별시 관악구 국회단지길 7, 1층 (봉천동)08717GS THE FRESH 관악은천점2024-02-01 16:42:24U2023-12-02 00:03:00.0구분없음194553.838439442719.413176<NA>