Overview

Dataset statistics

Number of variables27
Number of observations250
Missing cells2227
Missing cells (%)33.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory56.0 KiB
Average record size in memory229.5 B

Variable types

Categorical8
Numeric4
DateTime4
Unsupported6
Text5

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),법인구분명,구분명
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20216/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
영업상태코드 is highly imbalanced (56.9%)Imbalance
영업상태명 is highly imbalanced (56.9%)Imbalance
상세영업상태코드 is highly imbalanced (56.9%)Imbalance
상세영업상태명 is highly imbalanced (56.9%)Imbalance
인허가취소일자 has 250 (100.0%) missing valuesMissing
폐업일자 has 155 (62.0%) missing valuesMissing
휴업시작일자 has 250 (100.0%) missing valuesMissing
휴업종료일자 has 250 (100.0%) missing valuesMissing
재개업일자 has 250 (100.0%) missing valuesMissing
전화번호 has 162 (64.8%) missing valuesMissing
소재지면적 has 250 (100.0%) missing valuesMissing
소재지우편번호 has 200 (80.0%) missing valuesMissing
지번주소 has 3 (1.2%) missing valuesMissing
도로명주소 has 28 (11.2%) missing valuesMissing
도로명우편번호 has 139 (55.6%) missing valuesMissing
업태구분명 has 250 (100.0%) missing valuesMissing
좌표정보(X) has 20 (8.0%) missing valuesMissing
좌표정보(Y) has 20 (8.0%) 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
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 has 4 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-11 06:58:24.539088
Analysis finished2024-05-11 06:58:25.097420
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3140000
250 

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 250
100.0%

Length

2024-05-11T15:58:25.158842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:25.249808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3140000 250
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct250
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.00799 × 1018
Minimum1.990314 × 1018
Maximum2.024314 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:58:25.356033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.990314 × 1018
5-th percentile1.999314 × 1018
Q12.002314 × 1018
median2.006314 × 1018
Q32.012314 × 1018
95-th percentile2.021864 × 1018
Maximum2.024314 × 1018
Range3.400001 × 1016
Interquartile range (IQR)1.0000008 × 1016

Descriptive statistics

Standard deviation7.1834167 × 1015
Coefficient of variation (CV)0.0035774166
Kurtosis-0.37618758
Mean2.00799 × 1018
Median Absolute Deviation (MAD)4.0000032 × 1015
Skewness0.53030512
Sum3.9354129 × 1018
Variance5.1601476 × 1031
MonotonicityStrictly increasing
2024-05-11T15:58:25.556136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1990314007011500001 1
 
0.4%
2011314014514500024 1
 
0.4%
2009314011414500006 1
 
0.4%
2009314011414500008 1
 
0.4%
2010314011414500001 1
 
0.4%
2010314011414500002 1
 
0.4%
2010314011414500003 1
 
0.4%
2010314011414500004 1
 
0.4%
2010314011414500005 1
 
0.4%
2010314011414500006 1
 
0.4%
Other values (240) 240
96.0%
ValueCountFrequency (%)
1990314007011500001 1
0.4%
1990314010211500001 1
0.4%
1992314007011500001 1
0.4%
1993314010211500001 1
0.4%
1996314007011500001 1
0.4%
1997314007011500001 1
0.4%
1998314007011500001 1
0.4%
1999314007011500001 1
0.4%
1999314007011500002 1
0.4%
1999314007011500003 1
0.4%
ValueCountFrequency (%)
2024314016714500002 1
0.4%
2024314016714500001 1
0.4%
2023314016714522225 1
0.4%
2023314016714522224 1
0.4%
2023314016714522223 1
0.4%
2023314016714500006 1
0.4%
2023314016714500005 1
0.4%
2023314016714500004 1
0.4%
2023314016714500003 1
0.4%
2023314016714500002 1
0.4%

인허가일자
Date

Distinct236
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1990-02-15 00:00:00
Maximum2024-02-14 00:00:00
2024-05-11T15:58:25.732707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:25.887001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
3
202 
1
40 
4
 
4
5
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row4
5th row3

Common Values

ValueCountFrequency (%)
3 202
80.8%
1 40
 
16.0%
4 4
 
1.6%
5 4
 
1.6%

Length

2024-05-11T15:58:26.030629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:26.140472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 202
80.8%
1 40
 
16.0%
4 4
 
1.6%
5 4
 
1.6%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
202 
영업/정상
40 
취소/말소/만료/정지/중지
 
4
제외/삭제/전출
 
4

Length

Max length14
Median length2
Mean length2.768
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row취소/말소/만료/정지/중지
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 202
80.8%
영업/정상 40
 
16.0%
취소/말소/만료/정지/중지 4
 
1.6%
제외/삭제/전출 4
 
1.6%

Length

2024-05-11T15:58:26.251602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:26.360462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 202
80.8%
영업/정상 40
 
16.0%
취소/말소/만료/정지/중지 4
 
1.6%
제외/삭제/전출 4
 
1.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
40
202 
20
40 
70
 
4
50
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40
2nd row40
3rd row40
4th row70
5th row40

Common Values

ValueCountFrequency (%)
40 202
80.8%
20 40
 
16.0%
70 4
 
1.6%
50 4
 
1.6%

Length

2024-05-11T15:58:26.480200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:26.644443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 202
80.8%
20 40
 
16.0%
70 4
 
1.6%
50 4
 
1.6%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
폐업
202 
영업중
40 
등록취소
 
4
타시군구이관
 
4

Length

Max length6
Median length2
Mean length2.256
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row폐업
3rd row폐업
4th row등록취소
5th row폐업

Common Values

ValueCountFrequency (%)
폐업 202
80.8%
영업중 40
 
16.0%
등록취소 4
 
1.6%
타시군구이관 4
 
1.6%

Length

2024-05-11T15:58:26.828508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:26.958274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 202
80.8%
영업중 40
 
16.0%
등록취소 4
 
1.6%
타시군구이관 4
 
1.6%

폐업일자
Date

MISSING 

Distinct91
Distinct (%)95.8%
Missing155
Missing (%)62.0%
Memory size2.1 KiB
Minimum2007-08-21 00:00:00
Maximum2024-04-22 00:00:00
2024-05-11T15:58:27.109987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:27.294260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct88
Distinct (%)100.0%
Missing162
Missing (%)64.8%
Memory size2.1 KiB
2024-05-11T15:58:27.610699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.045455
Min length7

Characters and Unicode

Total characters884
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

Unique88 ?
Unique (%)100.0%

Sample

1st row02 26531919
2nd row26477370
3rd row26999733
4th row02 26548960
5th row02 26022227
ValueCountFrequency (%)
02 32
 
25.0%
070 2
 
1.6%
26020018 2
 
1.6%
549 1
 
0.8%
26548774 1
 
0.8%
63481929 1
 
0.8%
6675 1
 
0.8%
839 1
 
0.8%
20610030 1
 
0.8%
0216709722 1
 
0.8%
Other values (85) 85
66.4%
2024-05-11T15:58:28.087080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 169
19.1%
0 156
17.6%
6 116
13.1%
71
8.0%
1 59
 
6.7%
4 55
 
6.2%
9 53
 
6.0%
8 53
 
6.0%
5 51
 
5.8%
3 51
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 813
92.0%
Space Separator 71
 
8.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 169
20.8%
0 156
19.2%
6 116
14.3%
1 59
 
7.3%
4 55
 
6.8%
9 53
 
6.5%
8 53
 
6.5%
5 51
 
6.3%
3 51
 
6.3%
7 50
 
6.2%
Space Separator
ValueCountFrequency (%)
71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 884
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 169
19.1%
0 156
17.6%
6 116
13.1%
71
8.0%
1 59
 
6.7%
4 55
 
6.2%
9 53
 
6.0%
8 53
 
6.0%
5 51
 
5.8%
3 51
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 884
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 169
19.1%
0 156
17.6%
6 116
13.1%
71
8.0%
1 59
 
6.7%
4 55
 
6.2%
9 53
 
6.0%
8 53
 
6.0%
5 51
 
5.8%
3 51
 
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

소재지우편번호
Real number (ℝ)

MISSING  ZEROS 

Distinct31
Distinct (%)62.0%
Missing200
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean145068.82
Minimum0
Maximum158885
Zeros4
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:58:28.264314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1158723.25
median158824
Q3158859
95-th percentile158874.2
Maximum158885
Range158885
Interquartile range (IQR)135.75

Descriptive statistics

Standard deviation43746.453
Coefficient of variation (CV)0.30155655
Kurtosis7.984111
Mean145068.82
Median Absolute Deviation (MAD)35
Skewness-3.0821641
Sum7253441
Variance1.9137521 × 109
MonotonicityNot monotonic
2024-05-11T15:58:28.433606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
158859 7
 
2.8%
0 4
 
1.6%
158885 3
 
1.2%
158852 3
 
1.2%
158860 3
 
1.2%
158819 2
 
0.8%
158857 2
 
0.8%
158811 2
 
0.8%
158856 2
 
0.8%
158861 1
 
0.4%
Other values (21) 21
 
8.4%
(Missing) 200
80.0%
ValueCountFrequency (%)
0 4
1.6%
110550 1
 
0.4%
158050 1
 
0.4%
158051 1
 
0.4%
158070 1
 
0.4%
158073 1
 
0.4%
158091 1
 
0.4%
158095 1
 
0.4%
158718 1
 
0.4%
158723 1
 
0.4%
ValueCountFrequency (%)
158885 3
1.2%
158861 1
 
0.4%
158860 3
1.2%
158859 7
2.8%
158857 2
 
0.8%
158856 2
 
0.8%
158852 3
1.2%
158842 1
 
0.4%
158833 1
 
0.4%
158829 1
 
0.4%

지번주소
Text

MISSING 

Distinct246
Distinct (%)99.6%
Missing3
Missing (%)1.2%
Memory size2.1 KiB
2024-05-11T15:58:28.921193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length40
Mean length31.437247
Min length16

Characters and Unicode

Total characters7765
Distinct characters218
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

Unique245 ?
Unique (%)99.2%

Sample

1st row서울특별시 양천구 목4동 795번지 1호 4층
2nd row경기도 고양시덕양구 화정동 870호 은빛마을 563 1301
3rd row서울특별시 강서구 화곡동 산70번지 1호 우신아파트 27 502
4th row서울특별시 강서구 등촌동 654번지 43호 동선연립 가
5th row경기도 부천시원미구 심곡동 336번지 12호 10통 3반
ValueCountFrequency (%)
서울특별시 208
 
12.1%
양천구 163
 
9.4%
신정동 52
 
3.0%
신월동 40
 
2.3%
목동 30
 
1.7%
3반 24
 
1.4%
경기도 23
 
1.3%
1호 19
 
1.1%
2반 17
 
1.0%
4반 16
 
0.9%
Other values (637) 1134
65.7%
2024-05-11T15:58:29.652305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1623
20.9%
1 393
 
5.1%
2 264
 
3.4%
동 261
 
3.4%
호 256
 
3.3%
구 250
 
3.2%
시 248
 
3.2%
0 235
 
3.0%
서 228
 
2.9%
3 211
 
2.7%
Other values (208) 3796
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4173
53.7%
Decimal Number 1936
24.9%
Space Separator 1623
 
20.9%
Dash Punctuation 25
 
0.3%
Uppercase Letter 4
 
0.1%
Other Punctuation 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 261
 
6.3%
호 256
 
6.1%
구 250
 
6.0%
시 248
 
5.9%
서 228
 
5.5%
울 209
 
5.0%
별 208
 
5.0%
특 208
 
5.0%
지 190
 
4.6%
천 189
 
4.5%
Other values (191) 1926
46.2%
Decimal Number
ValueCountFrequency (%)
1 393
20.3%
2 264
13.6%
0 235
12.1%
3 211
10.9%
4 180
9.3%
5 159
8.2%
9 144
 
7.4%
6 127
 
6.6%
8 116
 
6.0%
7 107
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
R 2
50.0%
B 2
50.0%
Space Separator
ValueCountFrequency (%)
1623
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4173
53.7%
Common 3588
46.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 261
 
6.3%
호 256
 
6.1%
구 250
 
6.0%
시 248
 
5.9%
서 228
 
5.5%
울 209
 
5.0%
별 208
 
5.0%
특 208
 
5.0%
지 190
 
4.6%
천 189
 
4.5%
Other values (191) 1926
46.2%
Common
ValueCountFrequency (%)
1623
45.2%
1 393
 
11.0%
2 264
 
7.4%
0 235
 
6.5%
3 211
 
5.9%
4 180
 
5.0%
5 159
 
4.4%
9 144
 
4.0%
6 127
 
3.5%
8 116
 
3.2%
Other values (5) 136
 
3.8%
Latin
ValueCountFrequency (%)
R 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4173
53.7%
ASCII 3592
46.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1623
45.2%
1 393
 
10.9%
2 264
 
7.3%
0 235
 
6.5%
3 211
 
5.9%
4 180
 
5.0%
5 159
 
4.4%
9 144
 
4.0%
6 127
 
3.5%
8 116
 
3.2%
Other values (7) 140
 
3.9%
Hangul
ValueCountFrequency (%)
동 261
 
6.3%
호 256
 
6.1%
구 250
 
6.0%
시 248
 
5.9%
서 228
 
5.5%
울 209
 
5.0%
별 208
 
5.0%
특 208
 
5.0%
지 190
 
4.6%
천 189
 
4.5%
Other values (191) 1926
46.2%

도로명주소
Text

MISSING 

Distinct218
Distinct (%)98.2%
Missing28
Missing (%)11.2%
Memory size2.1 KiB
2024-05-11T15:58:30.000635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length41
Mean length32.54955
Min length21

Characters and Unicode

Total characters7226
Distinct characters220
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

Unique214 ?
Unique (%)96.4%

Sample

1st row서울특별시 양천구 목동중앙서로 12, 4층 (목동)
2nd row서울특별시 강서구 공항대로45나길 28, 가동 (등촌동,동선연립)
3rd row경기도 부천시 원미구 심중로68번길 27-7 (심곡동)
4th row서울특별시 양천구 중앙로 308 (신정동,4층)
5th row서울특별시 양천구 목동동로 257, 102동 5105호 (목동)
ValueCountFrequency (%)
서울특별시 199
 
14.4%
양천구 161
 
11.6%
신정동 56
 
4.0%
신월동 42
 
3.0%
목동 36
 
2.6%
2층 32
 
2.3%
오목로 22
 
1.6%
중앙로 15
 
1.1%
경기도 14
 
1.0%
강서구 13
 
0.9%
Other values (542) 793
57.3%
2024-05-11T15:58:30.534954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1161
 
16.1%
동 325
 
4.5%
1 258
 
3.6%
, 243
 
3.4%
로 242
 
3.3%
2 235
 
3.3%
구 231
 
3.2%
서 230
 
3.2%
시 225
 
3.1%
) 222
 
3.1%
Other values (210) 3854
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4047
56.0%
Decimal Number 1281
 
17.7%
Space Separator 1161
 
16.1%
Other Punctuation 243
 
3.4%
Close Punctuation 222
 
3.1%
Open Punctuation 222
 
3.1%
Dash Punctuation 48
 
0.7%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 325
 
8.0%
로 242
 
6.0%
구 231
 
5.7%
서 230
 
5.7%
시 225
 
5.6%
울 201
 
5.0%
특 199
 
4.9%
별 199
 
4.9%
천 184
 
4.5%
양 172
 
4.3%
Other values (194) 1839
45.4%
Decimal Number
ValueCountFrequency (%)
1 258
20.1%
2 235
18.3%
0 179
14.0%
3 160
12.5%
4 111
8.7%
6 77
 
6.0%
5 75
 
5.9%
8 66
 
5.2%
7 65
 
5.1%
9 55
 
4.3%
Space Separator
ValueCountFrequency (%)
1161
100.0%
Other Punctuation
ValueCountFrequency (%)
, 243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4047
56.0%
Common 3177
44.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 325
 
8.0%
로 242
 
6.0%
구 231
 
5.7%
서 230
 
5.7%
시 225
 
5.6%
울 201
 
5.0%
특 199
 
4.9%
별 199
 
4.9%
천 184
 
4.5%
양 172
 
4.3%
Other values (194) 1839
45.4%
Common
ValueCountFrequency (%)
1161
36.5%
1 258
 
8.1%
, 243
 
7.6%
2 235
 
7.4%
) 222
 
7.0%
( 222
 
7.0%
0 179
 
5.6%
3 160
 
5.0%
4 111
 
3.5%
6 77
 
2.4%
Other values (5) 309
 
9.7%
Latin
ValueCountFrequency (%)
B 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4047
56.0%
ASCII 3179
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1161
36.5%
1 258
 
8.1%
, 243
 
7.6%
2 235
 
7.4%
) 222
 
7.0%
( 222
 
7.0%
0 179
 
5.6%
3 160
 
5.0%
4 111
 
3.5%
6 77
 
2.4%
Other values (6) 311
 
9.8%
Hangul
ValueCountFrequency (%)
동 325
 
8.0%
로 242
 
6.0%
구 231
 
5.7%
서 230
 
5.7%
시 225
 
5.6%
울 201
 
5.0%
특 199
 
4.9%
별 199
 
4.9%
천 184
 
4.5%
양 172
 
4.3%
Other values (194) 1839
45.4%

도로명우편번호
Text

MISSING 

Distinct73
Distinct (%)65.8%
Missing139
Missing (%)55.6%
Memory size2.1 KiB
2024-05-11T15:58:30.851277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.5495495
Min length5

Characters and Unicode

Total characters616
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

Unique50 ?
Unique (%)45.0%

Sample

1st row158-819
2nd row158724
3rd row08028
4th row158862
5th row07942
ValueCountFrequency (%)
07909 5
 
4.5%
08028 4
 
3.6%
07906 4
 
3.6%
158859 4
 
3.6%
158857 3
 
2.7%
158811 3
 
2.7%
08082 3
 
2.7%
158822 3
 
2.7%
07942 3
 
2.7%
07944 3
 
2.7%
Other values (63) 76
68.5%
2024-05-11T15:58:31.399314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 135
21.9%
0 115
18.7%
5 80
13.0%
1 74
12.0%
7 61
9.9%
9 57
9.3%
2 37
 
6.0%
6 18
 
2.9%
4 18
 
2.9%
3 11
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 606
98.4%
Dash Punctuation 10
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 135
22.3%
0 115
19.0%
5 80
13.2%
1 74
12.2%
7 61
10.1%
9 57
9.4%
2 37
 
6.1%
6 18
 
3.0%
4 18
 
3.0%
3 11
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 135
21.9%
0 115
18.7%
5 80
13.0%
1 74
12.0%
7 61
9.9%
9 57
9.3%
2 37
 
6.0%
6 18
 
2.9%
4 18
 
2.9%
3 11
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 135
21.9%
0 115
18.7%
5 80
13.0%
1 74
12.0%
7 61
9.9%
9 57
9.3%
2 37
 
6.0%
6 18
 
2.9%
4 18
 
2.9%
3 11
 
1.8%

사업장명
Text

Distinct236
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-05-11T15:58:31.715722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length6.976
Min length2

Characters and Unicode

Total characters1744
Distinct characters259
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

Unique224 ?
Unique (%)89.6%

Sample

1st row양천사
2nd row(주)양천직업소개소
3rd row(주)요한인력개발직업소개소
4th row코리아인력개발(주)
5th row(주)아름인력
ValueCountFrequency (%)
직업소개소 4
 
1.4%
세기인력 3
 
1.1%
주식회사 3
 
1.1%
신월직업소개소 3
 
1.1%
양천점 3
 
1.1%
목동점 2
 
0.7%
컨설팅 2
 
0.7%
영진인력개발 2
 
0.7%
세화파출박사목동점 2
 
0.7%
개미인력 2
 
0.7%
Other values (239) 251
90.6%
2024-05-11T15:58:32.191159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 133
 
7.6%
인 128
 
7.3%
력 109
 
6.2%
개 103
 
5.9%
업 72
 
4.1%
직 62
 
3.6%
발 34
 
1.9%
주 33
 
1.9%
) 31
 
1.8%
( 31
 
1.8%
Other values (249) 1008
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1614
92.5%
Close Punctuation 31
 
1.8%
Open Punctuation 31
 
1.8%
Space Separator 27
 
1.5%
Uppercase Letter 16
 
0.9%
Decimal Number 11
 
0.6%
Lowercase Letter 8
 
0.5%
Other Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 133
 
8.2%
인 128
 
7.9%
력 109
 
6.8%
개 103
 
6.4%
업 72
 
4.5%
직 62
 
3.8%
발 34
 
2.1%
주 33
 
2.0%
사 26
 
1.6%
파 24
 
1.5%
Other values (222) 890
55.1%
Uppercase Letter
ValueCountFrequency (%)
C 3
18.8%
A 2
12.5%
M 2
12.5%
K 2
12.5%
L 1
 
6.2%
F 1
 
6.2%
I 1
 
6.2%
E 1
 
6.2%
S 1
 
6.2%
O 1
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
f 1
12.5%
k 1
12.5%
o 1
12.5%
r 1
12.5%
a 1
12.5%
h 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 4
36.4%
3 1
 
9.1%
4 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
& 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1614
92.5%
Common 106
 
6.1%
Latin 24
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 133
 
8.2%
인 128
 
7.9%
력 109
 
6.8%
개 103
 
6.4%
업 72
 
4.5%
직 62
 
3.8%
발 34
 
2.1%
주 33
 
2.0%
사 26
 
1.6%
파 24
 
1.5%
Other values (222) 890
55.1%
Latin
ValueCountFrequency (%)
C 3
 
12.5%
A 2
 
8.3%
M 2
 
8.3%
e 2
 
8.3%
K 2
 
8.3%
L 1
 
4.2%
f 1
 
4.2%
k 1
 
4.2%
o 1
 
4.2%
r 1
 
4.2%
Other values (8) 8
33.3%
Common
ValueCountFrequency (%)
) 31
29.2%
( 31
29.2%
27
25.5%
. 5
 
4.7%
2 5
 
4.7%
1 4
 
3.8%
3 1
 
0.9%
4 1
 
0.9%
& 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1614
92.5%
ASCII 130
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 133
 
8.2%
인 128
 
7.9%
력 109
 
6.8%
개 103
 
6.4%
업 72
 
4.5%
직 62
 
3.8%
발 34
 
2.1%
주 33
 
2.0%
사 26
 
1.6%
파 24
 
1.5%
Other values (222) 890
55.1%
ASCII
ValueCountFrequency (%)
) 31
23.8%
( 31
23.8%
27
20.8%
. 5
 
3.8%
2 5
 
3.8%
1 4
 
3.1%
C 3
 
2.3%
A 2
 
1.5%
M 2
 
1.5%
e 2
 
1.5%
Other values (17) 18
13.8%

최종수정일자
Date

UNIQUE 

Distinct250
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2002-11-14 14:33:58
Maximum2024-04-22 19:52:43
2024-05-11T15:58:32.355083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:32.520028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
I
186 
U
64 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 186
74.4%
U 64
 
25.6%

Length

2024-05-11T15:58:32.687181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:32.787341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 186
74.4%
u 64
 
25.6%

데이터갱신일자
Date

Distinct58
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-05-11T15:58:32.896291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T15:58:33.059035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing250
Missing (%)100.0%
Memory size2.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)89.1%
Missing20
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean188868.01
Minimum113095.08
Maximum341150.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:58:33.221703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113095.08
5-th percentile183765.17
Q1186099.24
median187361.09
Q3188621.19
95-th percentile204318.9
Maximum341150.29
Range228055.21
Interquartile range (IQR)2521.9479

Descriptive statistics

Standard deviation13704.471
Coefficient of variation (CV)0.0725611
Kurtosis74.029118
Mean188868.01
Median Absolute Deviation (MAD)1274.3662
Skewness6.1603776
Sum43439643
Variance1.8781252 × 108
MonotonicityNot monotonic
2024-05-11T15:58:33.751190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186861.841550692 4
 
1.6%
188953.066831076 4
 
1.6%
184534.619036954 3
 
1.2%
186963.282678818 3
 
1.2%
184571.315447564 2
 
0.8%
187496.753603391 2
 
0.8%
184867.739383378 2
 
0.8%
185457.654190376 2
 
0.8%
188388.652747683 2
 
0.8%
187330.934717886 2
 
0.8%
Other values (195) 204
81.6%
(Missing) 20
 
8.0%
ValueCountFrequency (%)
113095.075273 1
0.4%
168954.056122259 1
0.4%
172187.444371196 1
0.4%
172887.41749351 1
0.4%
174896.271331121 1
0.4%
174945.237682433 1
0.4%
174971.318696162 1
0.4%
175210.710360048 1
0.4%
177059.741967013 1
0.4%
179060.732353 1
0.4%
ValueCountFrequency (%)
341150.287884 1
0.4%
264739.776172341 1
0.4%
217842.988593725 1
0.4%
212483.769127009 1
0.4%
210018.566847655 1
0.4%
208437.958217401 1
0.4%
206179.384647281 1
0.4%
206128.868093671 1
0.4%
205684.208347808 1
0.4%
205421.214448215 1
0.4%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct205
Distinct (%)89.1%
Missing20
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean444575.46
Minimum89930.455
Maximum484178.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-05-11T15:58:33.903185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum89930.455
5-th percentile440776.61
Q1446446.2
median447078.63
Q3448562.64
95-th percentile455661.36
Maximum484178.72
Range394248.26
Interquartile range (IQR)2116.436

Descriptive statistics

Standard deviation30485.405
Coefficient of variation (CV)0.068571947
Kurtosis95.642015
Mean444575.46
Median Absolute Deviation (MAD)1022.3836
Skewness-9.37201
Sum1.0225235 × 108
Variance9.293599 × 108
MonotonicityNot monotonic
2024-05-11T15:58:34.091396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446885.258091733 4
 
1.6%
447333.569187997 4
 
1.6%
448182.475058135 3
 
1.2%
446428.3165455 3
 
1.2%
448606.448680726 2
 
0.8%
447163.623642728 2
 
0.8%
448186.71968632 2
 
0.8%
460001.971602972 2
 
0.8%
446446.200138375 2
 
0.8%
447028.458459502 2
 
0.8%
Other values (195) 204
81.6%
(Missing) 20
 
8.0%
ValueCountFrequency (%)
89930.4549583 1
0.4%
229655.688109 1
0.4%
264262.988739 1
0.4%
422712.114772036 1
0.4%
429475.863813397 1
0.4%
434166.361701895 1
0.4%
436538.352830994 1
0.4%
439801.517667572 1
0.4%
439853.488919065 1
0.4%
440040.309820942 1
0.4%
ValueCountFrequency (%)
484178.717163437 1
0.4%
470812.461624323 1
0.4%
462933.316362013 1
0.4%
461798.221433785 1
0.4%
461601.416789679 1
0.4%
460544.399483434 1
0.4%
460373.34025965 1
0.4%
460001.971602972 2
0.8%
457912.085738513 1
0.4%
457334.438439462 1
0.4%

법인구분명
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
개인
173 
<NA>
50 
법인
27 

Length

Max length4
Median length2
Mean length2.4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 173
69.2%
<NA> 50
 
20.0%
법인 27
 
10.8%

Length

2024-05-11T15:58:34.284288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:34.422309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 173
69.2%
na 50
 
20.0%
법인 27
 
10.8%

구분명
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
유료
200 
<NA>
50 

Length

Max length4
Median length2
Mean length2.4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 200
80.0%
<NA> 50
 
20.0%

Length

2024-05-11T15:58:34.568239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T15:58:34.701409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 200
80.0%
na 50
 
20.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
0314000019903140070115000011990-02-15<NA>3폐업40폐업2023-02-15<NA><NA><NA>02 26531919<NA><NA>서울특별시 양천구 목4동 795번지 1호 4층서울특별시 양천구 목동중앙서로 12, 4층 (목동)158-819양천사2023-02-15 14:46:33U2022-12-01 23:07:00.0<NA>188005.425844447806.918629<NA><NA>
13140000199031401021150000119900924<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>경기도 고양시덕양구 화정동 870호 은빛마을 563 1301<NA><NA>(주)양천직업소개소2004-11-15 16:00:11I2018-08-31 23:59:59.0<NA>185457.65419460001.971603법인유료
23140000199231400701150000119920110<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 화곡동 산70번지 1호 우신아파트 27 502<NA><NA>(주)요한인력개발직업소개소2004-07-26 14:57:37I2018-08-31 23:59:59.0<NA><NA><NA>법인유료
33140000199331401021150000119930809<NA>4취소/말소/만료/정지/중지70등록취소<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 654번지 43호 동선연립 가서울특별시 강서구 공항대로45나길 28, 가동 (등촌동,동선연립)<NA>코리아인력개발(주)2006-07-21 12:08:21I2018-08-31 23:59:59.0<NA>187191.934901450356.863102법인유료
43140000199631400701150000119961007<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>경기도 부천시원미구 심곡동 336번지 12호 10통 3반경기도 부천시 원미구 심중로68번길 27-7 (심곡동)<NA>(주)아름인력2004-06-22 11:47:35I2018-08-31 23:59:59.0<NA><NA><NA>법인유료
53140000199731400701150000119970113<NA>3폐업40폐업20090703<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 943번지 28호 1통 1반 4층서울특별시 양천구 중앙로 308 (신정동,4층)<NA>(주)신월직업소개소2009-07-03 16:26:43I2018-08-31 23:59:59.0<NA>186798.845446825.965법인유료
63140000199831400701150000119980730<NA>4취소/말소/만료/정지/중지70등록취소20150310<NA><NA><NA>26477370<NA>158724서울특별시 양천구 목1동 916번지 하이페리온 102동 5105호서울특별시 양천구 목동동로 257, 102동 5105호 (목동)158724서울의료부2015-03-23 11:29:53I2018-08-31 23:59:59.0<NA>188884.075622447186.888604개인유료
73140000199931400701150000119991126<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 173번지 25호 9통 9반서울특별시 양천구 남부순환로52길 34 (신월동)<NA>효성직업소개소2005-02-16 16:50:46I2018-08-31 23:59:59.0<NA>184704.734534447827.03791개인유료
83140000199931400701150000219991018<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 목동 526번지 38호 6통 8반서울특별시 양천구 목동중앙북로16길 27 (목동)<NA>유일파출부2005-07-26 17:27:37I2018-08-31 23:59:59.0<NA>188793.650519449195.999918개인유료
93140000199931400701150000319990122<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>경기도 부천시오정구 고강동 389번지 1호 17통 3반 삼우아파트 102 302경기도 부천시 오정구 고리울로52번길 6, 102동 302호 (고강동,삼우아파트)<NA>대우직업소개소2002-12-16 15:42:16I2018-08-31 23:59:59.0<NA><NA><NA>개인유료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
240314000020233140167145000022023-01-31<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 903-25서울특별시 양천구 오목로 211, 4층 403호 (신정동)07945산모피아 강서양천지사2023-04-17 15:08:19U2022-12-03 23:09:00.0<NA>187629.555755447076.283977<NA><NA>
241314000020233140167145000032023-02-12<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 1014-3 법정빌딩8층 801호, R3,R4호실서울특별시 양천구 신월로 376, 법정빌딩 8층 801호 (신정동)08087그랩인코리아2023-12-28 09:01:07U2022-11-01 21:00:00.0<NA>187791.46182446647.027913<NA><NA>
242314000020233140167145000042023-03-30<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 971-20 명성빌딩서울특별시 양천구 중앙로 294, 명성빌딩 6층 6-60호 (신정동)08026리드에이치알2023-05-03 19:57:13U2022-12-05 00:07:00.0<NA>186852.153852446714.974104<NA><NA>
243314000020233140167145000052023-04-17<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 48-9서울특별시 양천구 가로공원로 89, 2층 202,206호 (신월동)07909용한직업소개소2023-04-22 14:35:30U2022-12-03 22:04:00.0<NA>184534.619037448182.475058<NA><NA>
244314000020233140167145000062023-07-04<NA>3폐업40폐업2023-08-14<NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 1078 목동 센트럴 아이파크 위브 4단지서울특별시 양천구 남부순환로83길 47, 상가동 2층 4-30호 (신월동, 목동 센트럴 아이파크 위브 4단지)08067해냄직업소개소2023-08-14 10:02:11U2022-12-07 23:07:00.0<NA>186158.771734446193.976097<NA><NA>
245314000020233140167145222232002-11-13<NA>1영업/정상20영업중<NA><NA><NA><NA>0226000015<NA><NA>서울특별시 양천구 목동 792-1서울특별시 양천구 목동중앙서로7가길 39, 3층 301호 (목동)07965삼성인력개발원2023-11-27 09:14:50U2022-10-31 22:09:00.0<NA>187908.613115447909.376501<NA><NA>
246314000020233140167145222242023-12-07<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 905-2 해풍빌딩서울특별시 양천구 신정중앙로 68, 4층 403호 (신정동, 해풍빌딩)07945현대인력센터2023-12-08 10:06:21I2022-11-01 23:00:00.0<NA>187496.753603447163.623643<NA><NA>
247314000020233140167145222252023-12-12<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 991-7서울특별시 양천구 오목로48길 2, 2층 201호 (신정동)08022든든한파출부 양천구점2023-12-12 15:30:43I2022-11-01 23:04:00.0<NA>187800.01694447035.342184<NA><NA>
248314000020243140167145000012024-01-02<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신정동 319-18서울특별시 양천구 목동서로 301-15, 101호 (신정동)08013대신직업소개소2024-01-02 18:17:14I2023-12-01 00:04:00.0<NA>188374.060947446369.138672<NA><NA>
249314000020243140167145000022024-02-14<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 117-34서울특별시 양천구 곰달래로 43, 2층 (신월동)07923개미인력양천점2024-04-17 16:19:20U2023-12-03 23:09:00.0<NA>185553.50711447554.569961<NA><NA>