Overview

Dataset statistics

Number of variables26
Number of observations36
Missing cells226
Missing cells (%)24.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory223.7 B

Variable types

Categorical8
Numeric6
DateTime3
Unsupported3
Text6

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),점포구분명
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-18716/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 36 (100.0%) missing valuesMissing
폐업일자 has 27 (75.0%) missing valuesMissing
휴업시작일자 has 36 (100.0%) missing valuesMissing
휴업종료일자 has 36 (100.0%) missing valuesMissing
재개업일자 has 28 (77.8%) missing valuesMissing
전화번호 has 1 (2.8%) missing valuesMissing
소재지우편번호 has 14 (38.9%) missing valuesMissing
지번주소 has 1 (2.8%) missing valuesMissing
도로명주소 has 6 (16.7%) missing valuesMissing
도로명우편번호 has 27 (75.0%) missing valuesMissing
좌표정보(X) has 7 (19.4%) missing valuesMissing
좌표정보(Y) has 7 (19.4%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 7 (19.4%) zerosZeros

Reproduction

Analysis started2024-04-06 11:57:58.430674
Analysis finished2024-04-06 11:57:59.000191
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
3140000
36 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3140000
2nd row3140000
3rd row3140000
4th row3140000
5th row3140000

Common Values

ValueCountFrequency (%)
3140000 36
100.0%

Length

2024-04-06T20:57:59.118761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:57:59.279442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 36
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0102307 × 1018
Minimum1.981314 × 1018
Maximum2.022314 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:57:59.460953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.981314 × 1018
5-th percentile1.998814 × 1018
Q12.009314 × 1018
median2.011314 × 1018
Q32.012314 × 1018
95-th percentile2.021564 × 1018
Maximum2.022314 × 1018
Range4.1000005 × 1016
Interquartile range (IQR)3 × 1015

Descriptive statistics

Standard deviation7.8207611 × 1015
Coefficient of variation (CV)0.0038904794
Kurtosis5.9252572
Mean2.0102307 × 1018
Median Absolute Deviation (MAD)2 × 1015
Skewness-1.7964507
Sum-1.4186719 × 1018
Variance6.1164305 × 1031
MonotonicityStrictly increasing
2024-04-06T20:57:59.702847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1981314011407500001 1
 
2.8%
2011314011407500004 1
 
2.8%
2011314011407500006 1
 
2.8%
2011314011407500007 1
 
2.8%
2012314011407500001 1
 
2.8%
2012314011407500002 1
 
2.8%
2012314011407500003 1
 
2.8%
2012314011407500004 1
 
2.8%
2012314011407500005 1
 
2.8%
2012314011407500006 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
1981314011407500001 1
2.8%
1988314011407500001 1
2.8%
2002314011407500001 1
2.8%
2004314010207599100 1
2.8%
2006314010207500001 1
2.8%
2006314011407500001 1
2.8%
2008314011407500001 1
2.8%
2008314011407500002 1
2.8%
2009314011407500001 1
2.8%
2009314011407500002 1
2.8%
ValueCountFrequency (%)
2022314016707500002 1
2.8%
2022314016707500001 1
2.8%
2021314016707500001 1
2.8%
2020314016707500002 1
2.8%
2020314016707500001 1
2.8%
2015314016707500001 1
2.8%
2012314011407500007 1
2.8%
2012314011407500006 1
2.8%
2012314011407500005 1
2.8%
2012314011407500004 1
2.8%

인허가일자
Date

Distinct28
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum1976-06-16 00:00:00
Maximum2022-10-04 00:00:00
2024-04-06T20:57:59.912999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:58:00.149131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
1
26 
3
9 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 26
72.2%
3 9
 
25.0%
2 1
 
2.8%

Length

2024-04-06T20:58:00.431497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:00.652766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 26
72.2%
3 9
 
25.0%
2 1
 
2.8%

영업상태명
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
영업/정상
26 
폐업
9 
휴업
 
1

Length

Max length5
Median length5
Mean length4.1666667
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 26
72.2%
폐업 9
 
25.0%
휴업 1
 
2.8%

Length

2024-04-06T20:58:00.880443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:01.055152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 26
72.2%
폐업 9
 
25.0%
휴업 1
 
2.8%

상세영업상태코드
Categorical

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
1
24 
3
9 
5
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
1 24
66.7%
3 9
 
25.0%
5 2
 
5.6%
2 1
 
2.8%

Length

2024-04-06T20:58:01.249527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:01.431721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
66.7%
3 9
 
25.0%
5 2
 
5.6%
2 1
 
2.8%

상세영업상태명
Categorical

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
정상영업
24 
폐업처리
9 
영업개시전
 
2
휴업처리
 
1

Length

Max length5
Median length4
Mean length4.0555556
Min length4

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
정상영업 24
66.7%
폐업처리 9
 
25.0%
영업개시전 2
 
5.6%
휴업처리 1
 
2.8%

Length

2024-04-06T20:58:01.659909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:01.856983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 24
66.7%
폐업처리 9
 
25.0%
영업개시전 2
 
5.6%
휴업처리 1
 
2.8%

폐업일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)88.9%
Missing27
Missing (%)75.0%
Infinite0
Infinite (%)0.0%
Mean20154068
Minimum20081031
Maximum20220413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:58:02.131811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081031
5-th percentile20092826
Q120110519
median20141130
Q320200930
95-th percentile20216619
Maximum20220413
Range139382
Interquartile range (IQR)90411

Descriptive statistics

Standard deviation50418.695
Coefficient of variation (CV)0.0025016634
Kurtosis-1.6254447
Mean20154068
Median Absolute Deviation (MAD)39001
Skewness0.034163322
Sum1.8138662 × 108
Variance2.5420448 × 109
MonotonicityNot monotonic
2024-04-06T20:58:02.408668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20110519 2
 
5.6%
20081031 1
 
2.8%
20200930 1
 
2.8%
20141130 1
 
2.8%
20220413 1
 
2.8%
20131014 1
 
2.8%
20180131 1
 
2.8%
20210928 1
 
2.8%
(Missing) 27
75.0%
ValueCountFrequency (%)
20081031 1
2.8%
20110519 2
5.6%
20131014 1
2.8%
20141130 1
2.8%
20180131 1
2.8%
20200930 1
2.8%
20210928 1
2.8%
20220413 1
2.8%
ValueCountFrequency (%)
20220413 1
2.8%
20210928 1
2.8%
20200930 1
2.8%
20180131 1
2.8%
20141130 1
2.8%
20131014 1
2.8%
20110519 2
5.6%
20081031 1
2.8%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing36
Missing (%)100.0%
Memory size456.0 B

재개업일자
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)87.5%
Missing28
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean20033076
Minimum19880919
Maximum20070226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:58:02.680191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19880919
5-th percentile19929880
Q120043080
median20055556
Q320063212
95-th percentile20070192
Maximum20070226
Range189307
Interquartile range (IQR)20131.5

Descriptive statistics

Standard deviation63465.643
Coefficient of variation (CV)0.0031680429
Kurtosis6.5364347
Mean20033076
Median Absolute Deviation (MAD)9962
Skewness-2.5105636
Sum1.602646 × 108
Variance4.0278878 × 109
MonotonicityNot monotonic
2024-04-06T20:58:03.107576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20050504 2
 
5.6%
20070226 1
 
2.8%
19880919 1
 
2.8%
20020809 1
 
2.8%
20070129 1
 
2.8%
20060906 1
 
2.8%
20060607 1
 
2.8%
(Missing) 28
77.8%
ValueCountFrequency (%)
19880919 1
2.8%
20020809 1
2.8%
20050504 2
5.6%
20060607 1
2.8%
20060906 1
2.8%
20070129 1
2.8%
20070226 1
2.8%
ValueCountFrequency (%)
20070226 1
2.8%
20070129 1
2.8%
20060906 1
2.8%
20060607 1
2.8%
20050504 2
5.6%
20020809 1
2.8%
19880919 1
2.8%

전화번호
Text

MISSING 

Distinct34
Distinct (%)97.1%
Missing1
Missing (%)2.8%
Memory size420.0 B
2024-04-06T20:58:03.482104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.4
Min length8

Characters and Unicode

Total characters364
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

Unique33 ?
Unique (%)94.3%

Sample

1st row02 26432767
2nd row02 26931241
3rd row0221632233
4th row0266789236
5th row02 26424071
ValueCountFrequency (%)
02 4
 
10.3%
0222905853 2
 
5.1%
0226975602 1
 
2.6%
0226515602 1
 
2.6%
2692-5600 1
 
2.6%
2695-6131 1
 
2.6%
2062-8546 1
 
2.6%
0226470824 1
 
2.6%
2644-8720 1
 
2.6%
02-6716-1234 1
 
2.6%
Other values (25) 25
64.1%
2024-04-06T20:58:04.217445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 77
21.2%
0 55
15.1%
6 44
12.1%
- 31
8.5%
3 29
 
8.0%
4 27
 
7.4%
9 24
 
6.6%
5 21
 
5.8%
1 21
 
5.8%
8 16
 
4.4%
Other values (2) 19
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 327
89.8%
Dash Punctuation 31
 
8.5%
Space Separator 6
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 77
23.5%
0 55
16.8%
6 44
13.5%
3 29
 
8.9%
4 27
 
8.3%
9 24
 
7.3%
5 21
 
6.4%
1 21
 
6.4%
8 16
 
4.9%
7 13
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 364
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 77
21.2%
0 55
15.1%
6 44
12.1%
- 31
8.5%
3 29
 
8.0%
4 27
 
7.4%
9 24
 
6.6%
5 21
 
5.8%
1 21
 
5.8%
8 16
 
4.4%
Other values (2) 19
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 364
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 77
21.2%
0 55
15.1%
6 44
12.1%
- 31
8.5%
3 29
 
8.0%
4 27
 
7.4%
9 24
 
6.6%
5 21
 
5.8%
1 21
 
5.8%
8 16
 
4.4%
Other values (2) 19
 
5.2%

소재지면적
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4233.3647
Minimum0
Maximum38258
Zeros7
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:58:04.455108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1189.8175
median401.545
Q33046.4125
95-th percentile20903.53
Maximum38258
Range38258
Interquartile range (IQR)2856.595

Descriptive statistics

Standard deviation8394.022
Coefficient of variation (CV)1.9828251
Kurtosis7.6232333
Mean4233.3647
Median Absolute Deviation (MAD)401.545
Skewness2.6920862
Sum152401.13
Variance70459606
MonotonicityNot monotonic
2024-04-06T20:58:04.808994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 7
19.4%
14074.76 3
 
8.3%
2734.89 2
 
5.6%
3014.0 1
 
2.8%
496.0 1
 
2.8%
254.4 1
 
2.8%
225.64 1
 
2.8%
396.88 1
 
2.8%
3666.81 1
 
2.8%
468.92 1
 
2.8%
Other values (17) 17
47.2%
ValueCountFrequency (%)
0.0 7
19.4%
123.0 1
 
2.8%
161.37 1
 
2.8%
199.3 1
 
2.8%
213.0 1
 
2.8%
225.64 1
 
2.8%
240.66 1
 
2.8%
244.9 1
 
2.8%
254.4 1
 
2.8%
263.0 1
 
2.8%
ValueCountFrequency (%)
38258.0 1
 
2.8%
24319.0 1
 
2.8%
19765.04 1
 
2.8%
14074.76 3
8.3%
3666.81 1
 
2.8%
3636.42 1
 
2.8%
3143.65 1
 
2.8%
3014.0 1
 
2.8%
2734.89 2
5.6%
2247.0 1
 
2.8%

소재지우편번호
Text

MISSING 

Distinct19
Distinct (%)86.4%
Missing14
Missing (%)38.9%
Memory size420.0 B
2024-04-06T20:58:05.170772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.3181818
Min length6

Characters and Unicode

Total characters139
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 (%)77.3%

Sample

1st row158077
2nd row158-051
3rd row158051
4th row158053
5th row158808
ValueCountFrequency (%)
158074 3
 
13.6%
158051 2
 
9.1%
158-766 1
 
4.5%
158-073 1
 
4.5%
158-822 1
 
4.5%
158861 1
 
4.5%
158095 1
 
4.5%
158-077 1
 
4.5%
158-753 1
 
4.5%
158-053 1
 
4.5%
Other values (9) 9
40.9%
2024-04-06T20:58:05.685389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 30
21.6%
8 30
21.6%
1 29
20.9%
0 13
9.4%
7 12
 
8.6%
- 7
 
5.0%
4 6
 
4.3%
3 5
 
3.6%
2 3
 
2.2%
6 3
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132
95.0%
Dash Punctuation 7
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 30
22.7%
8 30
22.7%
1 29
22.0%
0 13
9.8%
7 12
 
9.1%
4 6
 
4.5%
3 5
 
3.8%
2 3
 
2.3%
6 3
 
2.3%
9 1
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 30
21.6%
8 30
21.6%
1 29
20.9%
0 13
9.4%
7 12
 
8.6%
- 7
 
5.0%
4 6
 
4.3%
3 5
 
3.6%
2 3
 
2.2%
6 3
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 30
21.6%
8 30
21.6%
1 29
20.9%
0 13
9.4%
7 12
 
8.6%
- 7
 
5.0%
4 6
 
4.3%
3 5
 
3.6%
2 3
 
2.2%
6 3
 
2.2%

지번주소
Text

MISSING 

Distinct33
Distinct (%)94.3%
Missing1
Missing (%)2.8%
Memory size420.0 B
2024-04-06T20:58:06.052212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length28.457143
Min length17

Characters and Unicode

Total characters996
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)88.6%

Sample

1st row서울특별시 양천구 목동 739번지 1호
2nd row서울특별시 양천구 신월동 928번지 1 호
3rd row서울특별시 양천구 목동 916호
4th row서울특별시 양천구 목동 917번지 6호
5th row서울특별시 양천구 목동 960호
ValueCountFrequency (%)
서울특별시 35
18.8%
양천구 35
18.8%
목동 8
 
4.3%
신정동 6
 
3.2%
1호 5
 
2.7%
7호 3
 
1.6%
목3동 3
 
1.6%
신정4동 3
 
1.6%
목1동 3
 
1.6%
목동트라팰리스 3
 
1.6%
Other values (72) 82
44.1%
2024-04-06T20:58:06.674586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
15.7%
1 52
 
5.2%
동 45
 
4.5%
지 37
 
3.7%
양 36
 
3.6%
서 35
 
3.5%
특 35
 
3.5%
별 35
 
3.5%
시 35
 
3.5%
천 35
 
3.5%
Other values (57) 495
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 554
55.6%
Decimal Number 253
25.4%
Space Separator 156
 
15.7%
Other Punctuation 26
 
2.6%
Dash Punctuation 3
 
0.3%
Math Symbol 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 45
 
8.1%
지 37
 
6.7%
양 36
 
6.5%
서 35
 
6.3%
특 35
 
6.3%
별 35
 
6.3%
시 35
 
6.3%
천 35
 
6.3%
구 35
 
6.3%
울 35
 
6.3%
Other values (41) 191
34.5%
Decimal Number
ValueCountFrequency (%)
1 52
20.6%
2 33
13.0%
9 30
11.9%
6 24
9.5%
4 22
8.7%
5 21
8.3%
7 20
 
7.9%
0 19
 
7.5%
3 18
 
7.1%
8 14
 
5.5%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 554
55.6%
Common 442
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 45
 
8.1%
지 37
 
6.7%
양 36
 
6.5%
서 35
 
6.3%
특 35
 
6.3%
별 35
 
6.3%
시 35
 
6.3%
천 35
 
6.3%
구 35
 
6.3%
울 35
 
6.3%
Other values (41) 191
34.5%
Common
ValueCountFrequency (%)
156
35.3%
1 52
 
11.8%
2 33
 
7.5%
9 30
 
6.8%
, 26
 
5.9%
6 24
 
5.4%
4 22
 
5.0%
5 21
 
4.8%
7 20
 
4.5%
0 19
 
4.3%
Other values (6) 39
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 554
55.6%
ASCII 442
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
35.3%
1 52
 
11.8%
2 33
 
7.5%
9 30
 
6.8%
, 26
 
5.9%
6 24
 
5.4%
4 22
 
5.0%
5 21
 
4.8%
7 20
 
4.5%
0 19
 
4.3%
Other values (6) 39
 
8.8%
Hangul
ValueCountFrequency (%)
동 45
 
8.1%
지 37
 
6.7%
양 36
 
6.5%
서 35
 
6.3%
특 35
 
6.3%
별 35
 
6.3%
시 35
 
6.3%
천 35
 
6.3%
구 35
 
6.3%
울 35
 
6.3%
Other values (41) 191
34.5%

도로명주소
Text

MISSING 

Distinct27
Distinct (%)90.0%
Missing6
Missing (%)16.7%
Memory size420.0 B
2024-04-06T20:58:07.099233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length29.066667
Min length22

Characters and Unicode

Total characters872
Distinct characters91
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row서울특별시 양천구 목동중앙본로7길 45 (목동)
2nd row서울특별시 양천구 지양로 78 (신월동)
3rd row서울특별시 양천구 목동동로 257 (목동)
4th row서울특별시 양천구 목동동로 309 (목동)
5th row서울특별시 양천구 목동중앙북로 7 (목동)
ValueCountFrequency (%)
서울특별시 30
18.5%
양천구 30
18.5%
목동 12
 
7.4%
신정동 7
 
4.3%
목동동로 5
 
3.1%
오목로 4
 
2.5%
목동중앙북로 4
 
2.5%
목동서로 4
 
2.5%
68 2
 
1.2%
2 2
 
1.2%
Other values (54) 62
38.3%
2024-04-06T20:58:07.726164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
 
15.1%
동 61
 
7.0%
목 44
 
5.0%
서 34
 
3.9%
양 32
 
3.7%
로 31
 
3.6%
울 30
 
3.4%
( 30
 
3.4%
) 30
 
3.4%
구 30
 
3.4%
Other values (81) 418
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 531
60.9%
Space Separator 132
 
15.1%
Decimal Number 124
 
14.2%
Open Punctuation 30
 
3.4%
Close Punctuation 30
 
3.4%
Other Punctuation 22
 
2.5%
Math Symbol 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 61
 
11.5%
목 44
 
8.3%
서 34
 
6.4%
양 32
 
6.0%
로 31
 
5.8%
울 30
 
5.6%
구 30
 
5.6%
시 30
 
5.6%
별 30
 
5.6%
특 30
 
5.6%
Other values (65) 179
33.7%
Decimal Number
ValueCountFrequency (%)
1 23
18.5%
5 19
15.3%
2 16
12.9%
0 15
12.1%
3 13
10.5%
4 9
 
7.3%
7 9
 
7.3%
9 8
 
6.5%
8 6
 
4.8%
6 6
 
4.8%
Space Separator
ValueCountFrequency (%)
132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 531
60.9%
Common 341
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 61
 
11.5%
목 44
 
8.3%
서 34
 
6.4%
양 32
 
6.0%
로 31
 
5.8%
울 30
 
5.6%
구 30
 
5.6%
시 30
 
5.6%
별 30
 
5.6%
특 30
 
5.6%
Other values (65) 179
33.7%
Common
ValueCountFrequency (%)
132
38.7%
( 30
 
8.8%
) 30
 
8.8%
1 23
 
6.7%
, 22
 
6.5%
5 19
 
5.6%
2 16
 
4.7%
0 15
 
4.4%
3 13
 
3.8%
4 9
 
2.6%
Other values (6) 32
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 531
60.9%
ASCII 341
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
38.7%
( 30
 
8.8%
) 30
 
8.8%
1 23
 
6.7%
, 22
 
6.5%
5 19
 
5.6%
2 16
 
4.7%
0 15
 
4.4%
3 13
 
3.8%
4 9
 
2.6%
Other values (6) 32
 
9.4%
Hangul
ValueCountFrequency (%)
동 61
 
11.5%
목 44
 
8.3%
서 34
 
6.4%
양 32
 
6.0%
로 31
 
5.8%
울 30
 
5.6%
구 30
 
5.6%
시 30
 
5.6%
별 30
 
5.6%
특 30
 
5.6%
Other values (65) 179
33.7%

도로명우편번호
Text

MISSING 

Distinct7
Distinct (%)77.8%
Missing27
Missing (%)75.0%
Memory size420.0 B
2024-04-06T20:58:08.076194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2222222
Min length5

Characters and Unicode

Total characters47
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

Unique5 ?
Unique (%)55.6%

Sample

1st row158-766
2nd row08104
3rd row08081
4th row08007
5th row07948
ValueCountFrequency (%)
07948 2
22.2%
08010 2
22.2%
158-766 1
11.1%
08104 1
11.1%
08081 1
11.1%
08007 1
11.1%
08022 1
11.1%
2024-04-06T20:58:08.666482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
36.2%
8 10
21.3%
1 5
 
10.6%
7 4
 
8.5%
4 3
 
6.4%
9 2
 
4.3%
6 2
 
4.3%
2 2
 
4.3%
5 1
 
2.1%
- 1
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
97.9%
Dash Punctuation 1
 
2.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
37.0%
8 10
21.7%
1 5
 
10.9%
7 4
 
8.7%
4 3
 
6.5%
9 2
 
4.3%
6 2
 
4.3%
2 2
 
4.3%
5 1
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
36.2%
8 10
21.3%
1 5
 
10.6%
7 4
 
8.5%
4 3
 
6.4%
9 2
 
4.3%
6 2
 
4.3%
2 2
 
4.3%
5 1
 
2.1%
- 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
36.2%
8 10
21.3%
1 5
 
10.6%
7 4
 
8.5%
4 3
 
6.4%
9 2
 
4.3%
6 2
 
4.3%
2 2
 
4.3%
5 1
 
2.1%
- 1
 
2.1%

사업장명
Text

Distinct34
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
2024-04-06T20:58:09.043766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length11.194444
Min length6

Characters and Unicode

Total characters403
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

Unique32 ?
Unique (%)88.9%

Sample

1st row목동시장아울렛
2nd row우성상가시장
3rd row현대백화점목동점
4th row행복한백화점
5th row신한이모르젠상가
ValueCountFrequency (%)
목동점 4
 
7.0%
홈플러스(주)익스프레스 3
 
5.3%
신한이모르젠상가 2
 
3.5%
목동2점 2
 
3.5%
주)지에스리테일 2
 
3.5%
목동에버하임 2
 
3.5%
주)이마트에브리데이 2
 
3.5%
신월점 2
 
3.5%
롯데쇼핑(주)롯데슈퍼 2
 
3.5%
익스프레스 2
 
3.5%
Other values (31) 34
59.6%
2024-04-06T20:58:09.800390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 24
 
6.0%
21
 
5.2%
목 20
 
5.0%
동 20
 
5.0%
스 18
 
4.5%
) 17
 
4.2%
주 17
 
4.2%
( 17
 
4.2%
신 15
 
3.7%
이 12
 
3.0%
Other values (67) 222
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
82.9%
Space Separator 21
 
5.2%
Close Punctuation 17
 
4.2%
Open Punctuation 17
 
4.2%
Decimal Number 9
 
2.2%
Uppercase Letter 5
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 24
 
7.2%
목 20
 
6.0%
동 20
 
6.0%
스 18
 
5.4%
주 17
 
5.1%
신 15
 
4.5%
이 12
 
3.6%
데 12
 
3.6%
롯 10
 
3.0%
상 9
 
2.7%
Other values (59) 177
53.0%
Decimal Number
ValueCountFrequency (%)
2 5
55.6%
4 2
 
22.2%
3 2
 
22.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
60.0%
G 2
40.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 334
82.9%
Common 64
 
15.9%
Latin 5
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 24
 
7.2%
목 20
 
6.0%
동 20
 
6.0%
스 18
 
5.4%
주 17
 
5.1%
신 15
 
4.5%
이 12
 
3.6%
데 12
 
3.6%
롯 10
 
3.0%
상 9
 
2.7%
Other values (59) 177
53.0%
Common
ValueCountFrequency (%)
21
32.8%
) 17
26.6%
( 17
26.6%
2 5
 
7.8%
4 2
 
3.1%
3 2
 
3.1%
Latin
ValueCountFrequency (%)
S 3
60.0%
G 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
82.9%
ASCII 69
 
17.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 24
 
7.2%
목 20
 
6.0%
동 20
 
6.0%
스 18
 
5.4%
주 17
 
5.1%
신 15
 
4.5%
이 12
 
3.6%
데 12
 
3.6%
롯 10
 
3.0%
상 9
 
2.7%
Other values (59) 177
53.0%
ASCII
ValueCountFrequency (%)
21
30.4%
) 17
24.6%
( 17
24.6%
2 5
 
7.2%
S 3
 
4.3%
4 2
 
2.9%
G 2
 
2.9%
3 2
 
2.9%

최종수정일자
Date

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2007-07-21 10:47:58
Maximum2024-03-22 08:51:42
2024-04-06T20:58:10.065120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:58:10.284287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

데이터갱신구분
Categorical

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
I
20 
U
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 20
55.6%
U 16
44.4%

Length

2024-04-06T20:58:10.533146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:10.729862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 20
55.6%
u 16
44.4%

데이터갱신일자
Date

Distinct19
Distinct (%)52.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:07:00
2024-04-06T20:58:10.922675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:58:11.141904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

업태구분명
Categorical

Distinct7
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
구분없음
13 
그 밖의 대규모점포
8 
시장
6 
백화점
3 
대형마트
3 
Other values (2)
3 

Length

Max length10
Median length4
Mean length4.9166667
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
구분없음 13
36.1%
그 밖의 대규모점포 8
22.2%
시장 6
16.7%
백화점 3
 
8.3%
대형마트 3
 
8.3%
쇼핑센터 2
 
5.6%
<NA> 1
 
2.8%

Length

2024-04-06T20:58:11.754821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:11.946585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구분없음 13
25.0%
그 8
15.4%
밖의 8
15.4%
대규모점포 8
15.4%
시장 6
11.5%
백화점 3
 
5.8%
대형마트 3
 
5.8%
쇼핑센터 2
 
3.8%
na 1
 
1.9%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)86.2%
Missing7
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean187822
Minimum184797
Maximum189062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:58:12.132481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum184797
5-th percentile185187.52
Q1187670.42
median187955.12
Q3188580.48
95-th percentile188939.93
Maximum189062
Range4265.0009
Interquartile range (IQR)910.06724

Descriptive statistics

Standard deviation1148.9464
Coefficient of variation (CV)0.0061172092
Kurtosis1.6944549
Mean187822
Median Absolute Deviation (MAD)599.81876
Skewness-1.5355323
Sum5446837.9
Variance1320077.9
MonotonicityNot monotonic
2024-04-06T20:58:12.322129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
187955.121454906 2
 
5.6%
188729.190478822 2
 
5.6%
187954.189632117 2
 
5.6%
188551.299139509 2
 
5.6%
187619.993071747 1
 
2.8%
188565.074701959 1
 
2.8%
188554.940218695 1
 
2.8%
187929.395106977 1
 
2.8%
189062.0 1
 
2.8%
188580.483661607 1
 
2.8%
Other values (15) 15
41.7%
(Missing) 7
19.4%
ValueCountFrequency (%)
184796.999053109 1
2.8%
185164.559946017 1
2.8%
185221.95790954 1
2.8%
186071.979697827 1
2.8%
186934.14769332 1
2.8%
187523.574256064 1
2.8%
187619.993071747 1
2.8%
187670.416423662 1
2.8%
187769.95711697 1
2.8%
187788.82257199 1
2.8%
ValueCountFrequency (%)
189062.0 1
2.8%
188977.171050288 1
2.8%
188884.075622342 1
2.8%
188729.190478822 2
5.6%
188700.851169641 1
2.8%
188635.230900983 1
2.8%
188580.483661607 1
2.8%
188565.074701959 1
2.8%
188554.940218695 1
2.8%
188551.299139509 2
5.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct25
Distinct (%)86.2%
Missing7
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean447350.25
Minimum445124.13
Maximum449649.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2024-04-06T20:58:12.519636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum445124.13
5-th percentile445193.67
Q1446727.35
median447076.29
Q3448020.09
95-th percentile449548.13
Maximum449649.02
Range4524.8846
Interquartile range (IQR)1292.736

Descriptive statistics

Standard deviation1255.0053
Coefficient of variation (CV)0.0028054199
Kurtosis-0.35222138
Mean447350.25
Median Absolute Deviation (MAD)667.6547
Skewness0.18318521
Sum12973157
Variance1575038.3
MonotonicityNot monotonic
2024-04-06T20:58:12.781247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
449649.016215774 2
 
5.6%
447572.610039376 2
 
5.6%
445124.131588947 2
 
5.6%
447076.288051741 2
 
5.6%
445879.054862903 1
 
2.8%
446750.881633578 1
 
2.8%
446701.745114511 1
 
2.8%
446964.609090888 1
 
2.8%
446850.0 1
 
2.8%
447750.845210817 1
 
2.8%
Other values (15) 15
41.7%
(Missing) 7
19.4%
ValueCountFrequency (%)
445124.131588947 2
5.6%
445297.986765501 1
2.8%
445879.054862903 1
2.8%
446336.680481997 1
2.8%
446408.633352149 1
2.8%
446701.745114511 1
2.8%
446727.354964214 1
2.8%
446750.881633578 1
2.8%
446850.0 1
2.8%
446964.609090888 1
2.8%
ValueCountFrequency (%)
449649.016215774 2
5.6%
449396.806374349 1
2.8%
449204.635182585 1
2.8%
448756.033565786 1
2.8%
448625.389554748 1
2.8%
448552.989897945 1
2.8%
448020.090999138 1
2.8%
447750.845210817 1
2.8%
447572.610039376 2
5.6%
447466.355031447 1
2.8%

점포구분명
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size420.0 B
<NA>
19 
대규모점포
10 
준대규모점포
7 

Length

Max length6
Median length4
Mean length4.6666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 19
52.8%
대규모점포 10
27.8%
준대규모점포 7
 
19.4%

Length

2024-04-06T20:58:13.053133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:58:13.285561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 19
52.8%
대규모점포 10
27.8%
준대규모점포 7
 
19.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
03140000198131401140750000119810923<NA>1영업/정상1정상영업<NA><NA><NA>2007022602 264327673014.0<NA>서울특별시 양천구 목동 739번지 1호서울특별시 양천구 목동중앙본로7길 45 (목동)<NA>목동시장아울렛2014-08-18 16:38:35I2018-08-31 23:59:59.0그 밖의 대규모점포188117.351836448552.989898대규모점포
13140000198831401140750000119880919<NA>1영업/정상1정상영업<NA><NA><NA>1988091902 269312412247.0<NA>서울특별시 양천구 신월동 928번지 1 호서울특별시 양천구 지양로 78 (신월동)<NA>우성상가시장2011-08-16 16:01:43I2018-08-31 23:59:59.0시장185221.95791446727.354964대규모점포
23140000200231401140750000120020809<NA>1영업/정상1정상영업<NA><NA><NA>20020809022163223338258.0<NA>서울특별시 양천구 목동 916호서울특별시 양천구 목동동로 257 (목동)<NA>현대백화점목동점2020-04-24 08:54:36U2020-04-26 02:40:00.0백화점188884.075622447186.888604대규모점포
3314000020043140102075991002004-06-04<NA>1영업/정상1정상영업<NA><NA><NA><NA>026678923624319.0<NA>서울특별시 양천구 목동 917번지 6호서울특별시 양천구 목동동로 309 (목동)<NA>행복한백화점2023-05-04 10:21:49U2022-12-05 00:07:00.0백화점188977.17105447466.355031<NA>
43140000200631401020750000120060328<NA>2휴업2휴업처리<NA><NA><NA><NA>02 264240710.0<NA>서울특별시 양천구 목동 960호서울특별시 양천구 목동중앙북로 7 (목동)<NA>신한이모르젠상가2007-07-21 10:47:58I2018-08-31 23:59:59.0그 밖의 대규모점포187955.121455449649.016216<NA>
53140000200631401140750000120061101<NA>3폐업3폐업처리20081031<NA><NA><NA>02 301615000.0<NA>서울특별시 양천구 목동 919번지 7호서울특별시 양천구 목동서로 170 (목동)<NA>(주)이랜드리테일2014-02-18 14:29:22I2018-08-31 23:59:59.0쇼핑센터188729.190479447572.610039대규모점포
63140000200831401140750000120081016<NA>1영업/정상1정상영업<NA><NA><NA><NA>780-90513143.65158077서울특별시 양천구 신정동 201번지 1호서울특별시 양천구 목동남로4길 2 (신정동)<NA>신정동세양청마루2차상가2008-10-22 15:13:32I2018-08-31 23:59:59.0그 밖의 대규모점포187954.189632445124.131589<NA>
7314000020083140114075000022008-11-03<NA>1영업/정상1정상영업<NA><NA><NA><NA>022644208019765.04158-051서울특별시 양천구 목동 919번지 7호서울특별시 양천구 목동서로 170 (목동)<NA>홈플러스(주)목동점2024-03-05 08:49:10U2023-12-03 00:07:00.0쇼핑센터188729.190479447572.610039<NA>
83140000200931401140750000120090323<NA>3폐업3폐업처리20110519<NA><NA><NA>380-942614074.76158051서울특별시 양천구 목1동 926번지 9261호 목동트라팰리스 내(지하1,2층)<NA><NA>신세계 이마트 목동점2014-02-18 11:01:29I2018-08-31 23:59:59.0대형마트<NA><NA>대규모점포
93140000200931401140750000219760616<NA>1영업/정상1정상영업<NA><NA><NA><NA>265459593636.42158053서울특별시 양천구 목3동 960번지서울특별시 양천구 목동중앙북로 7 (목동)<NA>신한이모르젠상가2014-09-30 10:06:50I2018-08-31 23:59:59.0그 밖의 대규모점포187955.121455449649.016216대규모점포
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
263140000201231401140750000420120523<NA>3폐업3폐업처리20131014<NA><NA><NA>0226515602674.0158861서울특별시 양천구 신정1동 1022번지 9호서울특별시 양천구 중앙로32길 55 (신정동)<NA>롯데쇼핑(주)롯데슈퍼 신목동점2013-10-14 17:29:47I2018-08-31 23:59:59.0<NA>187523.574256446408.633352준대규모점포
273140000201231401140750000520120523<NA>1영업/정상1정상영업<NA><NA><NA><NA>2692-5600240.66<NA>서울특별시 양천구 신정동 1290-4 대우미래사랑5차아파트서울특별시 양천구 신정로13길 3, 대우미래사랑5차아파트 103~105호 (신정동)08081롯데프레시 신정점2021-02-15 17:53:34U2021-02-17 02:40:00.0그 밖의 대규모점포186071.979698445297.986766준대규모점포
28314000020123140114075000062012-05-31<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6716-12341943.87158-822서울특별시 양천구 신월5동 26번지서울특별시 양천구 화곡로 59 (신월동)<NA>(주)이마트 신월점2023-07-11 09:44:05U2022-12-06 23:03:00.0백화점184796.999053448625.389555<NA>
293140000201231401140750000720120531<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2646-4331468.92158754서울특별시 양천구 목5동 904번지 목동4단지아파트 관리동 105호서울특별시 양천구 목동서로 130, 관리동 105호 (목동,목동4단지아파트)<NA>(주)이마트에브리데이 목동점2021-05-25 10:09:40U2021-05-27 02:40:00.0구분없음188580.483662447750.845211준대규모점포
303140000201531401670750000120150422<NA>3폐업3폐업처리20180131<NA><NA><NA>02-727-14053666.81<NA><NA>서울특별시 양천구 오목로 354, 지하1층 (목동, 목동센트럴푸르지오)08007(주)이마트SSG목동점2018-02-12 17:17:48I2018-08-31 23:59:59.0그 밖의 대규모점포189062.0446850.0대규모점포
313140000202031401670750000120200526<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2643-32092734.89<NA>서울특별시 양천구 목동 966번지 목동에버하임서울특별시 양천구 목동중앙북로 68 (목동, 목동에버하임)07948목동에버하임2020-06-17 13:01:15U2020-06-19 02:40:00.0그 밖의 대규모점포<NA><NA>대규모점포
323140000202031401670750000220200529<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02264332092734.89<NA>서울특별시 양천구 목동 966번지 목동에버하임서울특별시 양천구 목동중앙북로 68 (목동, 목동에버하임)07948목동에버하임2020-05-29 09:20:09I2020-05-31 00:23:29.0그 밖의 대규모점포<NA><NA>대규모점포
333140000202131401670750000120210826<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-2039-0818396.88<NA>서울특별시 양천구 신정동 995-2서울특별시 양천구 목동로 183(신정동)08022(주)이마트에브리데이 목동역점2021-08-30 20:10:43U2021-09-01 02:40:00.0구분없음187929.395107446964.609091준대규모점포
343140000202231401670750000120010301<NA>3폐업3폐업처리20210928<NA><NA><NA><NA>225.64<NA>서울특별시 양천구 신정동 1297서울특별시 양천구 목동동로 190(신정동, 길훈로즈빌)08010홈플러스 익스프레스 신정4점2022-04-13 11:37:49I2021-12-03 23:05:00.0구분없음188554.940219446701.745115<NA>
353140000202231401670750000220221004<NA>1영업/정상5영업개시전<NA><NA><NA><NA>02-3459-8016254.4<NA>서울특별시 양천구 신정동 86-1서울특별시 양천구 목동동로 196(신정동)08010홈플러스 익스프레스 오목교점2022-10-05 13:25:45I2021-10-31 00:07:00.0구분없음188565.074702446750.881634<NA>