Overview

Dataset statistics

Number of variables27
Number of observations200
Missing cells1717
Missing cells (%)31.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.9 KiB
Average record size in memory229.7 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
Author용산구
URLhttps://data.seoul.go.kr/dataList/OA-20204/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 200 (100.0%) missing valuesMissing
폐업일자 has 98 (49.0%) missing valuesMissing
휴업시작일자 has 200 (100.0%) missing valuesMissing
휴업종료일자 has 200 (100.0%) missing valuesMissing
재개업일자 has 200 (100.0%) missing valuesMissing
전화번호 has 132 (66.0%) missing valuesMissing
소재지면적 has 200 (100.0%) missing valuesMissing
소재지우편번호 has 157 (78.5%) missing valuesMissing
지번주소 has 5 (2.5%) missing valuesMissing
도로명주소 has 23 (11.5%) missing valuesMissing
도로명우편번호 has 80 (40.0%) missing valuesMissing
업태구분명 has 200 (100.0%) missing valuesMissing
좌표정보(X) has 11 (5.5%) missing valuesMissing
좌표정보(Y) has 11 (5.5%) 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 6 (3.0%) zerosZeros

Reproduction

Analysis started2024-04-06 11:35:29.095930
Analysis finished2024-04-06 11:35:29.965421
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3020000
200 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000
2nd row3020000
3rd row3020000
4th row3020000
5th row3020000

Common Values

ValueCountFrequency (%)
3020000 200
100.0%

Length

2024-04-06T20:35:30.129572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:30.277580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000 200
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.009912 × 1018
Minimum1.996302 × 1018
Maximum2.024302 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T20:35:30.506490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.996302 × 1018
5-th percentile1.999302 × 1018
Q12.004302 × 1018
median2.008302 × 1018
Q32.015302 × 1018
95-th percentile2.022352 × 1018
Maximum2.024302 × 1018
Range2.8000013 × 1016
Interquartile range (IQR)1.1000008 × 1016

Descriptive statistics

Standard deviation7.1282544 × 1015
Coefficient of variation (CV)0.0035465505
Kurtosis-0.92997009
Mean2.009912 × 1018
Median Absolute Deviation (MAD)5.0000021 × 1015
Skewness0.37987005
Sum-3.8459674 × 1018
Variance5.081201 × 1031
MonotonicityStrictly increasing
2024-04-06T20:35:30.784390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1996302007411500001 1
 
0.5%
2013302012414500010 1
 
0.5%
2012302012414500008 1
 
0.5%
2012302012414500009 1
 
0.5%
2012302012414500010 1
 
0.5%
2012302012414500011 1
 
0.5%
2012302012414500012 1
 
0.5%
2012302012414500013 1
 
0.5%
2013302012414500001 1
 
0.5%
2013302012414500007 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1996302007411500001 1
0.5%
1997302007411500001 1
0.5%
1999302007411500001 1
0.5%
1999302007411500002 1
0.5%
1999302007411500003 1
0.5%
1999302007411500004 1
0.5%
1999302007411500005 1
0.5%
1999302007411500006 1
0.5%
1999302007411500007 1
0.5%
1999302007411500008 1
0.5%
ValueCountFrequency (%)
2024302019914500004 1
0.5%
2024302019914500002 1
0.5%
2024302019914500001 1
0.5%
2023302019914500007 1
0.5%
2023302019914500006 1
0.5%
2023302019914500005 1
0.5%
2023302019914500004 1
0.5%
2023302019914500003 1
0.5%
2023302019914500002 1
0.5%
2023302019914500001 1
0.5%

인허가일자
Date

Distinct185
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1996-12-11 00:00:00
Maximum2024-03-28 00:00:00
2024-04-06T20:35:31.065734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:35:31.283373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
3
144 
1
38 
4
 
11
5
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row4
4th row3
5th row1

Common Values

ValueCountFrequency (%)
3 144
72.0%
1 38
 
19.0%
4 11
 
5.5%
5 7
 
3.5%

Length

2024-04-06T20:35:31.469104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:31.634038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 144
72.0%
1 38
 
19.0%
4 11
 
5.5%
5 7
 
3.5%

영업상태명
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
144 
영업/정상
38 
취소/말소/만료/정지/중지
 
11
제외/삭제/전출
 
7

Length

Max length14
Median length2
Mean length3.44
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 144
72.0%
영업/정상 38
 
19.0%
취소/말소/만료/정지/중지 11
 
5.5%
제외/삭제/전출 7
 
3.5%

Length

2024-04-06T20:35:31.823801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:32.000832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 144
72.0%
영업/정상 38
 
19.0%
취소/말소/만료/정지/중지 11
 
5.5%
제외/삭제/전출 7
 
3.5%

상세영업상태코드
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
40
144 
20
38 
70
 
11
50
 
7

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40
2nd row40
3rd row70
4th row40
5th row20

Common Values

ValueCountFrequency (%)
40 144
72.0%
20 38
 
19.0%
70 11
 
5.5%
50 7
 
3.5%

Length

2024-04-06T20:35:32.208696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:32.379508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 144
72.0%
20 38
 
19.0%
70 11
 
5.5%
50 7
 
3.5%

상세영업상태명
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
폐업
144 
영업중
38 
등록취소
 
11
타시군구이관
 
7

Length

Max length6
Median length2
Mean length2.44
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 144
72.0%
영업중 38
 
19.0%
등록취소 11
 
5.5%
타시군구이관 7
 
3.5%

Length

2024-04-06T20:35:32.602851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:32.811737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 144
72.0%
영업중 38
 
19.0%
등록취소 11
 
5.5%
타시군구이관 7
 
3.5%

폐업일자
Date

MISSING 

Distinct99
Distinct (%)97.1%
Missing98
Missing (%)49.0%
Memory size1.7 KiB
Minimum2005-05-10 00:00:00
Maximum2024-03-25 00:00:00
2024-04-06T20:35:33.015928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:35:33.217116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

전화번호
Text

MISSING 

Distinct68
Distinct (%)100.0%
Missing132
Missing (%)66.0%
Memory size1.7 KiB
2024-04-06T20:35:33.588438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.970588
Min length7

Characters and Unicode

Total characters746
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

Unique68 ?
Unique (%)100.0%

Sample

1st row02 7138025
2nd row000207971289
3rd row02 7975363
4th row02 7778241
5th row02 7975070
ValueCountFrequency (%)
02 23
 
20.5%
0002 4
 
3.6%
070 2
 
1.8%
000207935827 1
 
0.9%
0263393534 1
 
0.9%
7138025 1
 
0.9%
7155580 1
 
0.9%
07040063341 1
 
0.9%
9006 1
 
0.9%
312 1
 
0.9%
Other values (76) 76
67.9%
2024-04-06T20:35:34.139368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 177
23.7%
2 106
14.2%
7 84
11.3%
72
9.7%
9 58
 
7.8%
4 47
 
6.3%
3 46
 
6.2%
1 43
 
5.8%
5 42
 
5.6%
8 36
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 674
90.3%
Space Separator 72
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 177
26.3%
2 106
15.7%
7 84
12.5%
9 58
 
8.6%
4 47
 
7.0%
3 46
 
6.8%
1 43
 
6.4%
5 42
 
6.2%
8 36
 
5.3%
6 35
 
5.2%
Space Separator
ValueCountFrequency (%)
72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 746
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 177
23.7%
2 106
14.2%
7 84
11.3%
72
9.7%
9 58
 
7.8%
4 47
 
6.3%
3 46
 
6.2%
1 43
 
5.8%
5 42
 
5.6%
8 36
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 746
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 177
23.7%
2 106
14.2%
7 84
11.3%
72
9.7%
9 58
 
7.8%
4 47
 
6.3%
3 46
 
6.2%
1 43
 
5.8%
5 42
 
5.6%
8 36
 
4.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

소재지우편번호
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)53.5%
Missing157
Missing (%)78.5%
Infinite0
Infinite (%)0.0%
Mean121128.16
Minimum0
Maximum150070
Zeros6
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T20:35:34.315396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1140012
median140170
Q3140830.5
95-th percentile140872
Maximum150070
Range150070
Interquartile range (IQR)818.5

Descriptive statistics

Standard deviation49378.833
Coefficient of variation (CV)0.40765774
Kurtosis2.767567
Mean121128.16
Median Absolute Deviation (MAD)583
Skewness-2.1520222
Sum5208511
Variance2.4382692 × 109
MonotonicityNot monotonic
2024-04-06T20:35:34.468508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
140012 6
 
3.0%
0 6
 
3.0%
140871 4
 
2.0%
140750 3
 
1.5%
140011 2
 
1.0%
140872 2
 
1.0%
140133 2
 
1.0%
140170 2
 
1.0%
140150 2
 
1.0%
140753 1
 
0.5%
Other values (13) 13
 
6.5%
(Missing) 157
78.5%
ValueCountFrequency (%)
0 6
3.0%
140011 2
 
1.0%
140012 6
3.0%
140013 1
 
0.5%
140111 1
 
0.5%
140133 2
 
1.0%
140150 2
 
1.0%
140160 1
 
0.5%
140170 2
 
1.0%
140210 1
 
0.5%
ValueCountFrequency (%)
150070 1
 
0.5%
142879 1
 
0.5%
140872 2
1.0%
140871 4
2.0%
140863 1
 
0.5%
140858 1
 
0.5%
140832 1
 
0.5%
140829 1
 
0.5%
140827 1
 
0.5%
140821 1
 
0.5%

지번주소
Text

MISSING 

Distinct185
Distinct (%)94.9%
Missing5
Missing (%)2.5%
Memory size1.7 KiB
2024-04-06T20:35:34.878283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length28.882051
Min length17

Characters and Unicode

Total characters5632
Distinct characters214
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

Unique176 ?
Unique (%)90.3%

Sample

1st row경기도 고양시덕양구 행신동 796호 소만마을아파트 102 1207
2nd row서울특별시 양천구 신월동 46번지 12호 21통 2반 삼성주택 4 402
3rd row서울특별시 용산구 갈월동 93번지 60호
4th row서울특별시 용산구 청파동1가 93번지 31호 17통 4반
5th row서울특별시 용산구 동자동 43번지 22호 엠에스
ValueCountFrequency (%)
서울특별시 179
 
14.8%
용산구 146
 
12.1%
한강로2가 28
 
2.3%
동자동 19
 
1.6%
1호 14
 
1.2%
갈월동 13
 
1.1%
43번지 12
 
1.0%
2반 11
 
0.9%
경기도 10
 
0.8%
3호 9
 
0.7%
Other values (462) 766
63.5%
2024-04-06T20:35:35.494639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1134
20.1%
1 249
 
4.4%
2 201
 
3.6%
시 197
 
3.5%
서 192
 
3.4%
구 191
 
3.4%
호 184
 
3.3%
3 183
 
3.2%
울 181
 
3.2%
별 180
 
3.2%
Other values (204) 2740
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3222
57.2%
Decimal Number 1231
 
21.9%
Space Separator 1134
 
20.1%
Dash Punctuation 28
 
0.5%
Lowercase Letter 8
 
0.1%
Uppercase Letter 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 197
 
6.1%
서 192
 
6.0%
구 191
 
5.9%
호 184
 
5.7%
울 181
 
5.6%
별 180
 
5.6%
특 179
 
5.6%
동 174
 
5.4%
산 156
 
4.8%
용 155
 
4.8%
Other values (179) 1433
44.5%
Decimal Number
ValueCountFrequency (%)
1 249
20.2%
2 201
16.3%
3 183
14.9%
4 133
10.8%
0 125
10.2%
5 90
 
7.3%
6 70
 
5.7%
7 69
 
5.6%
8 66
 
5.4%
9 45
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
d 1
 
12.5%
i 1
 
12.5%
s 1
 
12.5%
n 1
 
12.5%
c 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
A 2
28.6%
G 1
14.3%
V 1
14.3%
R 1
14.3%
Space Separator
ValueCountFrequency (%)
1134
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3222
57.2%
Common 2395
42.5%
Latin 15
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 197
 
6.1%
서 192
 
6.0%
구 191
 
5.9%
호 184
 
5.7%
울 181
 
5.6%
별 180
 
5.6%
특 179
 
5.6%
동 174
 
5.4%
산 156
 
4.8%
용 155
 
4.8%
Other values (179) 1433
44.5%
Common
ValueCountFrequency (%)
1134
47.3%
1 249
 
10.4%
2 201
 
8.4%
3 183
 
7.6%
4 133
 
5.6%
0 125
 
5.2%
5 90
 
3.8%
6 70
 
2.9%
7 69
 
2.9%
8 66
 
2.8%
Other values (4) 75
 
3.1%
Latin
ValueCountFrequency (%)
e 3
20.0%
B 2
13.3%
A 2
13.3%
d 1
 
6.7%
i 1
 
6.7%
s 1
 
6.7%
G 1
 
6.7%
V 1
 
6.7%
R 1
 
6.7%
n 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3222
57.2%
ASCII 2410
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1134
47.1%
1 249
 
10.3%
2 201
 
8.3%
3 183
 
7.6%
4 133
 
5.5%
0 125
 
5.2%
5 90
 
3.7%
6 70
 
2.9%
7 69
 
2.9%
8 66
 
2.7%
Other values (15) 90
 
3.7%
Hangul
ValueCountFrequency (%)
시 197
 
6.1%
서 192
 
6.0%
구 191
 
5.9%
호 184
 
5.7%
울 181
 
5.6%
별 180
 
5.6%
특 179
 
5.6%
동 174
 
5.4%
산 156
 
4.8%
용 155
 
4.8%
Other values (179) 1433
44.5%

도로명주소
Text

MISSING 

Distinct171
Distinct (%)96.6%
Missing23
Missing (%)11.5%
Memory size1.7 KiB
2024-04-06T20:35:35.873302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length32.293785
Min length23

Characters and Unicode

Total characters5716
Distinct characters215
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)93.2%

Sample

1st row서울특별시 용산구 한강대로 385 (동자동)
2nd row서울특별시 양천구 가로공원로55길 30-1, 4동 402호 (신월동,삼성주택)
3rd row서울특별시 용산구 한강대로77길 18 (갈월동)
4th row서울특별시 용산구 한강대로77길 20 (갈월동)
5th row서울특별시 용산구 한강대로 363-2, 엠에스 4층 402호 (동자동)
ValueCountFrequency (%)
서울특별시 170
 
15.9%
용산구 151
 
14.1%
한강대로 55
 
5.1%
한강로2가 26
 
2.4%
동자동 20
 
1.9%
갈월동 16
 
1.5%
2층 13
 
1.2%
남영동 10
 
0.9%
4층 9
 
0.8%
한강로1가 9
 
0.8%
Other values (382) 590
55.2%
2024-04-06T20:35:36.354239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
892
 
15.6%
1 239
 
4.2%
로 235
 
4.1%
서 184
 
3.2%
시 180
 
3.1%
) 178
 
3.1%
( 178
 
3.1%
구 175
 
3.1%
울 173
 
3.0%
별 171
 
3.0%
Other values (205) 3111
54.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3222
56.4%
Decimal Number 1018
 
17.8%
Space Separator 892
 
15.6%
Close Punctuation 178
 
3.1%
Open Punctuation 178
 
3.1%
Other Punctuation 146
 
2.6%
Dash Punctuation 64
 
1.1%
Uppercase Letter 10
 
0.2%
Lowercase Letter 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 235
 
7.3%
서 184
 
5.7%
시 180
 
5.6%
구 175
 
5.4%
울 173
 
5.4%
별 171
 
5.3%
특 170
 
5.3%
동 161
 
5.0%
용 161
 
5.0%
산 160
 
5.0%
Other values (177) 1452
45.1%
Decimal Number
ValueCountFrequency (%)
1 239
23.5%
2 162
15.9%
3 122
12.0%
0 117
11.5%
4 107
10.5%
5 82
 
8.1%
8 55
 
5.4%
6 54
 
5.3%
7 47
 
4.6%
9 33
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
A 2
20.0%
K 1
 
10.0%
D 1
 
10.0%
R 1
 
10.0%
V 1
 
10.0%
G 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
c 1
 
12.5%
n 1
 
12.5%
d 1
 
12.5%
i 1
 
12.5%
s 1
 
12.5%
Space Separator
ValueCountFrequency (%)
892
100.0%
Close Punctuation
ValueCountFrequency (%)
) 178
100.0%
Open Punctuation
ValueCountFrequency (%)
( 178
100.0%
Other Punctuation
ValueCountFrequency (%)
, 146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3222
56.4%
Common 2476
43.3%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 235
 
7.3%
서 184
 
5.7%
시 180
 
5.6%
구 175
 
5.4%
울 173
 
5.4%
별 171
 
5.3%
특 170
 
5.3%
동 161
 
5.0%
용 161
 
5.0%
산 160
 
5.0%
Other values (177) 1452
45.1%
Common
ValueCountFrequency (%)
892
36.0%
1 239
 
9.7%
) 178
 
7.2%
( 178
 
7.2%
2 162
 
6.5%
, 146
 
5.9%
3 122
 
4.9%
0 117
 
4.7%
4 107
 
4.3%
5 82
 
3.3%
Other values (5) 253
 
10.2%
Latin
ValueCountFrequency (%)
B 3
16.7%
e 3
16.7%
A 2
11.1%
K 1
 
5.6%
D 1
 
5.6%
c 1
 
5.6%
n 1
 
5.6%
d 1
 
5.6%
i 1
 
5.6%
s 1
 
5.6%
Other values (3) 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3222
56.4%
ASCII 2494
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
892
35.8%
1 239
 
9.6%
) 178
 
7.1%
( 178
 
7.1%
2 162
 
6.5%
, 146
 
5.9%
3 122
 
4.9%
0 117
 
4.7%
4 107
 
4.3%
5 82
 
3.3%
Other values (18) 271
 
10.9%
Hangul
ValueCountFrequency (%)
로 235
 
7.3%
서 184
 
5.7%
시 180
 
5.6%
구 175
 
5.4%
울 173
 
5.4%
별 171
 
5.3%
특 170
 
5.3%
동 161
 
5.0%
용 161
 
5.0%
산 160
 
5.0%
Other values (177) 1452
45.1%

도로명우편번호
Text

MISSING 

Distinct58
Distinct (%)48.3%
Missing80
Missing (%)40.0%
Memory size1.7 KiB
2024-04-06T20:35:36.650121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.45
Min length5

Characters and Unicode

Total characters654
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

Unique33 ?
Unique (%)27.5%

Sample

1st row140821
2nd row140807
3rd row140807
4th row04320
5th row140011
ValueCountFrequency (%)
04320 13
 
10.8%
140871 6
 
5.0%
04382 6
 
5.0%
04352 5
 
4.2%
140806 5
 
4.2%
140807 4
 
3.3%
140750 4
 
3.3%
04376 3
 
2.5%
04321 3
 
2.5%
140872 3
 
2.5%
Other values (48) 68
56.7%
2024-04-06T20:35:37.247111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 162
24.8%
4 130
19.9%
1 93
14.2%
3 81
12.4%
2 47
 
7.2%
8 41
 
6.3%
7 40
 
6.1%
6 20
 
3.1%
9 20
 
3.1%
5 18
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 652
99.7%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 162
24.8%
4 130
19.9%
1 93
14.3%
3 81
12.4%
2 47
 
7.2%
8 41
 
6.3%
7 40
 
6.1%
6 20
 
3.1%
9 20
 
3.1%
5 18
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 654
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 162
24.8%
4 130
19.9%
1 93
14.2%
3 81
12.4%
2 47
 
7.2%
8 41
 
6.3%
7 40
 
6.1%
6 20
 
3.1%
9 20
 
3.1%
5 18
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 654
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 162
24.8%
4 130
19.9%
1 93
14.2%
3 81
12.4%
2 47
 
7.2%
8 41
 
6.3%
7 40
 
6.1%
6 20
 
3.1%
9 20
 
3.1%
5 18
 
2.8%

사업장명
Text

Distinct187
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T20:35:37.715644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.81
Min length2

Characters and Unicode

Total characters1562
Distinct characters247
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique176 ?
Unique (%)88.0%

Sample

1st row서울항우종합정보
2nd row유흥종직업소개소
3rd row최태호직업소개소
4th row천광직업소개소
5th row에스코트 컨설팅
ValueCountFrequency (%)
주식회사 11
 
4.4%
직업소개소 8
 
3.2%
인력 4
 
1.6%
삼성취업정보 3
 
1.2%
대길취업정보 3
 
1.2%
대신 2
 
0.8%
취업정보 2
 
0.8%
강산인력 2
 
0.8%
용산종합씨씨아이(주 2
 
0.8%
은진직업소개소 2
 
0.8%
Other values (199) 209
84.3%
2024-04-06T20:35:38.398174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 107
 
6.9%
업 82
 
5.2%
인 66
 
4.2%
개 61
 
3.9%
직 53
 
3.4%
48
 
3.1%
력 48
 
3.1%
주 46
 
2.9%
이 32
 
2.0%
) 32
 
2.0%
Other values (237) 987
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1409
90.2%
Space Separator 48
 
3.1%
Close Punctuation 32
 
2.0%
Open Punctuation 31
 
2.0%
Uppercase Letter 27
 
1.7%
Lowercase Letter 11
 
0.7%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 107
 
7.6%
업 82
 
5.8%
인 66
 
4.7%
개 61
 
4.3%
직 53
 
3.8%
력 48
 
3.4%
주 46
 
3.3%
이 32
 
2.3%
정 31
 
2.2%
사 29
 
2.1%
Other values (207) 854
60.6%
Uppercase Letter
ValueCountFrequency (%)
I 4
14.8%
G 3
11.1%
E 3
11.1%
R 2
 
7.4%
N 2
 
7.4%
U 2
 
7.4%
T 2
 
7.4%
W 1
 
3.7%
O 1
 
3.7%
A 1
 
3.7%
Other values (6) 6
22.2%
Lowercase Letter
ValueCountFrequency (%)
o 3
27.3%
p 2
18.2%
e 2
18.2%
l 1
 
9.1%
b 1
 
9.1%
u 1
 
9.1%
r 1
 
9.1%
Space Separator
ValueCountFrequency (%)
48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1409
90.2%
Common 115
 
7.4%
Latin 38
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 107
 
7.6%
업 82
 
5.8%
인 66
 
4.7%
개 61
 
4.3%
직 53
 
3.8%
력 48
 
3.4%
주 46
 
3.3%
이 32
 
2.3%
정 31
 
2.2%
사 29
 
2.1%
Other values (207) 854
60.6%
Latin
ValueCountFrequency (%)
I 4
 
10.5%
G 3
 
7.9%
o 3
 
7.9%
E 3
 
7.9%
p 2
 
5.3%
R 2
 
5.3%
N 2
 
5.3%
U 2
 
5.3%
T 2
 
5.3%
e 2
 
5.3%
Other values (13) 13
34.2%
Common
ValueCountFrequency (%)
48
41.7%
) 32
27.8%
( 31
27.0%
& 1
 
0.9%
- 1
 
0.9%
+ 1
 
0.9%
2 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1409
90.2%
ASCII 153
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 107
 
7.6%
업 82
 
5.8%
인 66
 
4.7%
개 61
 
4.3%
직 53
 
3.8%
력 48
 
3.4%
주 46
 
3.3%
이 32
 
2.3%
정 31
 
2.2%
사 29
 
2.1%
Other values (207) 854
60.6%
ASCII
ValueCountFrequency (%)
48
31.4%
) 32
20.9%
( 31
20.3%
I 4
 
2.6%
G 3
 
2.0%
o 3
 
2.0%
E 3
 
2.0%
p 2
 
1.3%
R 2
 
1.3%
N 2
 
1.3%
Other values (20) 23
15.0%

최종수정일자
Date

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2004-09-24 14:41:00
Maximum2024-03-29 09:28:12
2024-04-06T20:35:38.656988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:35:39.256604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
I
128 
U
72 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 128
64.0%
U 72
36.0%

Length

2024-04-06T20:35:39.494010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:39.685660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 128
64.0%
u 72
36.0%

데이터갱신일자
Date

Distinct69
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:06:00
2024-04-06T20:35:39.894493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:35:40.148248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)83.6%
Missing11
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean198545.59
Minimum173236.87
Maximum381567.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T20:35:40.403404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173236.87
5-th percentile191559.5
Q1197048.85
median197418.87
Q3197642.67
95-th percentile203782.94
Maximum381567.36
Range208330.49
Interquartile range (IQR)593.82554

Descriptive statistics

Standard deviation14008.648
Coefficient of variation (CV)0.070556327
Kurtosis157.06806
Mean198545.59
Median Absolute Deviation (MAD)330.52863
Skewness11.955737
Sum37525117
Variance1.9624221 × 108
MonotonicityNot monotonic
2024-04-06T20:35:40.651939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
197117.41843467 4
 
2.0%
197409.520466946 3
 
1.5%
197470.453767228 3
 
1.5%
197418.871548856 3
 
1.5%
197360.94645124 3
 
1.5%
197105.426566714 3
 
1.5%
195531.627650393 2
 
1.0%
197257.765183997 2
 
1.0%
197587.470666784 2
 
1.0%
195723.539073553 2
 
1.0%
Other values (148) 162
81.0%
(Missing) 11
 
5.5%
ValueCountFrequency (%)
173236.86955982 1
0.5%
180635.594962 1
0.5%
184516.713251845 1
0.5%
186244.489030269 1
0.5%
188007.505715409 1
0.5%
189851.987951081 1
0.5%
190700.452096017 1
0.5%
191269.69055423 1
0.5%
191300.240218154 1
0.5%
191559.503925745 2
1.0%
ValueCountFrequency (%)
381567.358967436 1
0.5%
213007.115814 1
0.5%
212508.42447866 1
0.5%
212211.348051215 1
0.5%
211990.475987378 1
0.5%
210193.6886262 1
0.5%
207274.300313358 1
0.5%
207257.88389271 1
0.5%
204409.927623755 1
0.5%
203946.973903274 1
0.5%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)83.6%
Missing11
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean445997.7
Minimum204924.58
Maximum461490.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T20:35:40.892414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum204924.58
5-th percentile442848.41
Q1447583.74
median448446.13
Q3449608.42
95-th percentile453564.14
Maximum461490.74
Range256566.15
Interquartile range (IQR)2024.6846

Descriptive statistics

Standard deviation22781.833
Coefficient of variation (CV)0.051080607
Kurtosis89.993109
Mean445997.7
Median Absolute Deviation (MAD)903.01704
Skewness-9.2975391
Sum84293565
Variance5.1901192 × 108
MonotonicityNot monotonic
2024-04-06T20:35:41.173998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447527.338271365 4
 
2.0%
449608.420224521 3
 
1.5%
450020.433308027 3
 
1.5%
449734.477054997 3
 
1.5%
447743.445553705 3
 
1.5%
447582.719757807 3
 
1.5%
445554.779221886 2
 
1.0%
447772.298383734 2
 
1.0%
448760.927509212 2
 
1.0%
454754.899472127 2
 
1.0%
Other values (148) 162
81.0%
(Missing) 11
 
5.5%
ValueCountFrequency (%)
204924.583768539 1
0.5%
260546.053757 1
0.5%
403939.788315386 1
0.5%
429619.308077682 1
0.5%
432026.627632605 1
0.5%
437564.538326363 1
0.5%
440047.98563234 1
0.5%
441266.315595645 1
0.5%
442662.533646366 1
0.5%
442714.184450604 1
0.5%
ValueCountFrequency (%)
461490.73644056 1
0.5%
460691.522876969 1
0.5%
460253.408203871 1
0.5%
457909.125969428 1
0.5%
457794.730237592 1
0.5%
457226.842401009 1
0.5%
457006.036660272 1
0.5%
454754.899472127 2
1.0%
454409.308917288 1
0.5%
452296.391590981 1
0.5%

법인구분명
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
개인
123 
<NA>
52 
법인
25 

Length

Max length4
Median length2
Mean length2.52
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 123
61.5%
<NA> 52
26.0%
법인 25
 
12.5%

Length

2024-04-06T20:35:41.423656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:41.632685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 123
61.5%
na 52
26.0%
법인 25
 
12.5%

구분명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
유료
148 
<NA>
52 

Length

Max length4
Median length2
Mean length2.52
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 148
74.0%
<NA> 52
 
26.0%

Length

2024-04-06T20:35:41.856437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:35:42.047794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 148
74.0%
na 52
 
26.0%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
03020000199630200741150000119961211<NA>3폐업40폐업20200129<NA><NA><NA>02 7138025<NA><NA>경기도 고양시덕양구 행신동 796호 소만마을아파트 102 1207서울특별시 용산구 한강대로 385 (동자동)140821서울항우종합정보2020-01-29 15:58:17U2020-01-31 02:40:00.0<NA>186244.48903457226.842401개인유료
13020000199730200741150000119970808<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 46번지 12호 21통 2반 삼성주택 4 402서울특별시 양천구 가로공원로55길 30-1, 4동 402호 (신월동,삼성주택)<NA>유흥종직업소개소2006-05-11 13:51:17I2018-08-31 23:59:59.0<NA>184516.713252448252.058022개인유료
23020000199930200741150000119991229<NA>4취소/말소/만료/정지/중지70등록취소20211022<NA><NA><NA>000207971289<NA><NA>서울특별시 용산구 갈월동 93번지 60호서울특별시 용산구 한강대로77길 18 (갈월동)140807최태호직업소개소2021-10-22 13:18:20U2021-10-24 02:40:00.0<NA>197426.265768448872.025564개인유료
33020000199930200741150000219990609<NA>3폐업40폐업20211028<NA><NA><NA>02 7975363<NA><NA>서울특별시 용산구 청파동1가 93번지 31호 17통 4반서울특별시 용산구 한강대로77길 20 (갈월동)140807천광직업소개소2021-10-28 14:44:17U2021-10-30 02:40:00.0<NA>196811.006741449630.443649개인유료
4302000019993020074115000031999-01-01<NA>1영업/정상20영업중<NA><NA><NA><NA>02 7778241<NA><NA>서울특별시 용산구 동자동 43번지 22호 엠에스서울특별시 용산구 한강대로 363-2, 엠에스 4층 402호 (동자동)04320에스코트 컨설팅2023-12-27 15:51:48U2022-11-01 22:09:00.0<NA>197440.1544449850.081584<NA><NA>
53020000199930200741150000419990917<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로2가 255번지 4호 10통 5반서울특별시 용산구 한강대로 141 (한강로2가)<NA>황성복 직업소개소2006-01-16 13:37:14I2018-08-31 23:59:59.0<NA>197304.329637447756.642609개인유료
63020000199930200741150000519990123<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 도원동 25호 11통 7반 도원삼성래미안아파트 202 2013서울특별시 용산구 새창로8길 7, 202동 2013호 (도원동,도원삼성래미안아파트)<NA>사랑인력2006-04-24 15:41:31I2018-08-31 23:59:59.0<NA>196051.113641448579.242368개인유료
73020000199930200741150000619991201<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로1가 231번지 24호 8통 3반 삼각아파트 A 307서울특별시 용산구 한강대로62길 32, A동 307호 (한강로1가,삼각아파트)<NA>(주)생수인력2005-06-08 09:22:59I2018-08-31 23:59:59.0<NA>197565.665087447898.182964법인유료
83020000199930200741150000719991117<NA>4취소/말소/만료/정지/중지70등록취소20110110<NA><NA><NA><NA><NA>140210서울특별시 용산구 한남동 76번지 22호 3층서울특별시 용산구 한남대로 55 (한남동,3층)<NA>(주)사랑과평화2011-01-10 14:36:58I2018-08-31 23:59:59.0<NA>200557.868951447928.158148법인유료
93020000199930200741150000819991122<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 효창동 5번지 291호 13통 5반 202서울특별시 용산구 효창원로66길 35-14, 202호 (효창동)<NA>자영인력2005-07-21 17:45:18I2018-08-31 23:59:59.0<NA>196754.851464448832.244484개인유료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
190302000020233020199145000012023-02-22<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 동자동 43-35서울특별시 용산구 한강대로 353-1, 1층 (동자동)04320용산의희망인력 주식회사2023-06-23 09:16:58U2022-12-05 22:05:00.0<NA>197418.871549449734.477055<NA><NA>
191302000020233020199145000022017-07-21<NA>5제외/삭제/전출50타시군구이관2024-02-01<NA><NA><NA>0222443399<NA><NA>서울특별시 용산구 이태원동 130-43서울특별시 용산구 보광로 117, 2층 (이태원동)04391희망인력건설산업(주)2024-02-01 15:59:00U2023-12-02 00:03:00.0<NA>199418.957825447879.088095<NA><NA>
192302000020233020199145000032023-08-01<NA>5제외/삭제/전출50타시군구이관2024-02-05<NA><NA><NA><NA><NA><NA>서울특별시 용산구 동자동 56 트윈시티 남산서울특별시 용산구 한강대로 366, 트윈시티 남산 6층 631호 (동자동)04323리크루트퍼스트코리아 주식회사2024-02-05 09:36:13U2023-12-02 00:07:00.0<NA>197525.40731449844.319842<NA><NA>
193302000020233020199145000042023-10-16<NA>3폐업40폐업2023-12-26<NA><NA><NA><NA><NA><NA>서울특별시 용산구 원효로1가 41 용산더프라임서울특별시 용산구 원효로90길 11, 11층 1126호 (원효로1가, 용산더프라임)04315에이어티2023-12-28 17:30:15U2022-11-01 21:00:00.0<NA>197287.505067448662.153501<NA><NA>
194302000020233020199145000052023-10-25<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 남영동 89-10서울특별시 용산구 한강대로 260-1, 2층 (남영동)04352대신2023-10-25 16:02:27I2022-10-30 22:07:00.0<NA>197562.956276448818.302758<NA><NA>
195302000020233020199145000062023-11-06<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 한강로2가 71서울특별시 용산구 한강대로40길 43, 307호 (한강로2가)04382주식회사 파이팅에이치알2023-11-06 18:27:01I2022-11-01 00:08:00.0<NA>197430.260839447554.444781<NA><NA>
196302000020233020199145000072023-12-26<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 원효로2가 2-10서울특별시 용산구 원효로 214-6, 4층 (원효로2가)04368든든한파출부 용산점2023-12-26 15:43:30I2022-11-01 22:08:00.0<NA>196925.138995448350.568003<NA><NA>
197302000020243020199145000012024-01-17<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 원효로1가 41 용산더프라임서울특별시 용산구 원효로90길 11, 1126호 (원효로1가, 용산더프라임)04315에이어티2024-01-17 13:21:20I2023-11-30 23:09:00.0<NA>197287.505067448662.153501<NA><NA>
198302000020243020199145000022021-11-25<NA>1영업/정상20영업중<NA><NA><NA><NA>02 62670405<NA><NA>서울특별시 마포구 도화동 250-4 근신빌딩서울특별시 마포구 삼개로 16, 근신빌딩 2층 201호 (도화동)04173일감플러스2024-01-24 11:01:53U2023-11-30 22:06:00.0<NA>195258.466477448540.434893<NA><NA>
199302000020243020199145000042024-03-28<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 청파동2가 71-61서울특별시 용산구 청파로49길 37-3, 디테일씨빌딩 103,105호 (청파동2가)04309하이피플22024-03-28 17:04:26I2023-12-02 21:00:00.0<NA>197115.958078449203.316855<NA><NA>