Overview

Dataset statistics

Number of variables27
Number of observations176
Missing cells1578
Missing cells (%)33.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.5 KiB
Average record size in memory229.8 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
Author서대문구
URLhttps://data.seoul.go.kr/dataList/OA-20214/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 176 (100.0%) missing valuesMissing
폐업일자 has 102 (58.0%) missing valuesMissing
휴업시작일자 has 176 (100.0%) missing valuesMissing
휴업종료일자 has 176 (100.0%) missing valuesMissing
재개업일자 has 176 (100.0%) missing valuesMissing
전화번호 has 132 (75.0%) missing valuesMissing
소재지면적 has 176 (100.0%) missing valuesMissing
소재지우편번호 has 141 (80.1%) missing valuesMissing
지번주소 has 6 (3.4%) missing valuesMissing
도로명주소 has 26 (14.8%) missing valuesMissing
도로명우편번호 has 87 (49.4%) missing valuesMissing
업태구분명 has 176 (100.0%) missing valuesMissing
좌표정보(X) has 14 (8.0%) missing valuesMissing
좌표정보(Y) has 14 (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 2 (1.1%) zerosZeros

Reproduction

Analysis started2024-04-06 11:11:56.646803
Analysis finished2024-04-06 11:11:57.568268
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3120000
176 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3120000 176
100.0%

Length

2024-04-06T20:11:57.754221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:57.946576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3120000 176
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0092779 × 1018
Minimum2.002312 × 1018
Maximum2.024312 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T20:11:58.155437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002312 × 1018
5-th percentile2.002312 × 1018
Q12.003312 × 1018
median2.006312 × 1018
Q32.015312 × 1018
95-th percentile2.021562 × 1018
Maximum2.024312 × 1018
Range2.2000014 × 1016
Interquartile range (IQR)1.2000011 × 1016

Descriptive statistics

Standard deviation6.8718088 × 1015
Coefficient of variation (CV)0.003420039
Kurtosis-1.050055
Mean2.0092779 × 1018
Median Absolute Deviation (MAD)3.9999998 × 1015
Skewness0.67926422
Sum3.1447766 × 1018
Variance4.7221756 × 1031
MonotonicityStrictly increasing
2024-04-06T20:11:58.401005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002312007511500001 1
 
0.6%
2006312007311500004 1
 
0.6%
2011312014514500003 1
 
0.6%
2011312014514500005 1
 
0.6%
2011312014514500006 1
 
0.6%
2012312014514500002 1
 
0.6%
2012312014514500003 1
 
0.6%
2013312014514500001 1
 
0.6%
2013312014514500002 1
 
0.6%
2013312014514500003 1
 
0.6%
Other values (166) 166
94.3%
ValueCountFrequency (%)
2002312007511500001 1
0.6%
2002312007511500002 1
0.6%
2002312007511500003 1
0.6%
2002312007511500004 1
0.6%
2002312007511500005 1
0.6%
2002312007511500006 1
0.6%
2002312007511500007 1
0.6%
2002312007511500008 1
0.6%
2002312007511500010 1
0.6%
2002312007511500012 1
0.6%
ValueCountFrequency (%)
2024312021914500001 1
0.6%
2023312021914500001 1
0.6%
2022312019214500007 1
0.6%
2022312019214500006 1
0.6%
2022312019214500005 1
0.6%
2022312019214500004 1
0.6%
2022312019214500003 1
0.6%
2022312019214500002 1
0.6%
2022312019214500001 1
0.6%
2021312019214500007 1
0.6%

인허가일자
Date

Distinct174
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum1990-01-23 00:00:00
Maximum2024-03-26 00:00:00
2024-04-06T20:11:58.741117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:11:58.998263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
3
122 
1
46 
5
 
6
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 122
69.3%
1 46
 
26.1%
5 6
 
3.4%
4 2
 
1.1%

Length

2024-04-06T20:11:59.234829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:59.406393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 122
69.3%
1 46
 
26.1%
5 6
 
3.4%
4 2
 
1.1%

영업상태명
Categorical

Distinct4
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
122 
영업/정상
46 
제외/삭제/전출
 
6
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length2
Mean length3.125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 122
69.3%
영업/정상 46
 
26.1%
제외/삭제/전출 6
 
3.4%
취소/말소/만료/정지/중지 2
 
1.1%

Length

2024-04-06T20:11:59.613875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:11:59.842966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
69.3%
영업/정상 46
 
26.1%
제외/삭제/전출 6
 
3.4%
취소/말소/만료/정지/중지 2
 
1.1%

상세영업상태코드
Categorical

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
40
122 
20
44 
50
 
6
10
 
2
70
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
40 122
69.3%
20 44
 
25.0%
50 6
 
3.4%
10 2
 
1.1%
70 2
 
1.1%

Length

2024-04-06T20:12:00.083551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:12:00.317877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
40 122
69.3%
20 44
 
25.0%
50 6
 
3.4%
10 2
 
1.1%
70 2
 
1.1%

상세영업상태명
Categorical

Distinct5
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
폐업
122 
영업중
44 
타시군구이관
 
6
<NA>
 
2
등록취소
 
2

Length

Max length6
Median length2
Mean length2.4318182
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 122
69.3%
영업중 44
 
25.0%
타시군구이관 6
 
3.4%
<NA> 2
 
1.1%
등록취소 2
 
1.1%

Length

2024-04-06T20:12:00.551195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:12:00.750988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 122
69.3%
영업중 44
 
25.0%
타시군구이관 6
 
3.4%
na 2
 
1.1%
등록취소 2
 
1.1%

폐업일자
Date

MISSING 

Distinct72
Distinct (%)97.3%
Missing102
Missing (%)58.0%
Memory size1.5 KiB
Minimum2003-07-29 00:00:00
Maximum2023-06-15 00:00:00
2024-04-06T20:12:01.029368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:12:01.403136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

전화번호
Text

MISSING 

Distinct44
Distinct (%)100.0%
Missing132
Missing (%)75.0%
Memory size1.5 KiB
2024-04-06T20:12:01.842283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11.5
Mean length10.613636
Min length7

Characters and Unicode

Total characters467
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

Unique44 ?
Unique (%)100.0%

Sample

1st row02 375 7500
2nd row02 303 8822
3rd row02 363 8766
4th row023751017
5th row02 372 1929
ValueCountFrequency (%)
02 24
28.6%
363 2
 
2.4%
3034878 1
 
1.2%
3254434 1
 
1.2%
0260845130 1
 
1.2%
3370005 1
 
1.2%
3648877 1
 
1.2%
023046251 1
 
1.2%
000220685500 1
 
1.2%
02379096 1
 
1.2%
Other values (50) 50
59.5%
2024-04-06T20:12:02.404432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 100
21.4%
2 64
13.7%
61
13.1%
3 53
11.3%
1 35
 
7.5%
5 33
 
7.1%
6 28
 
6.0%
7 26
 
5.6%
8 25
 
5.4%
4 22
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 406
86.9%
Space Separator 61
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100
24.6%
2 64
15.8%
3 53
13.1%
1 35
 
8.6%
5 33
 
8.1%
6 28
 
6.9%
7 26
 
6.4%
8 25
 
6.2%
4 22
 
5.4%
9 20
 
4.9%
Space Separator
ValueCountFrequency (%)
61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 467
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 100
21.4%
2 64
13.7%
61
13.1%
3 53
11.3%
1 35
 
7.5%
5 33
 
7.1%
6 28
 
6.0%
7 26
 
5.6%
8 25
 
5.4%
4 22
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 100
21.4%
2 64
13.7%
61
13.1%
3 53
11.3%
1 35
 
7.5%
5 33
 
7.1%
6 28
 
6.0%
7 26
 
5.6%
8 25
 
5.4%
4 22
 
4.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

소재지우편번호
Real number (ℝ)

MISSING  ZEROS 

Distinct25
Distinct (%)71.4%
Missing141
Missing (%)80.1%
Infinite0
Infinite (%)0.0%
Mean113680.17
Minimum0
Maximum120859
Zeros2
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T20:12:02.660419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile84008.4
Q1120070
median120806
Q3120833.5
95-th percentile120856.9
Maximum120859
Range120859
Interquartile range (IQR)763.5

Descriptive statistics

Standard deviation28396.919
Coefficient of variation (CV)0.24979659
Kurtosis14.746497
Mean113680.17
Median Absolute Deviation (MAD)47
Skewness-3.9878108
Sum3978806
Variance8.0638503 × 108
MonotonicityNot monotonic
2024-04-06T20:12:02.940028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
120030 4
 
2.3%
0 2
 
1.1%
120070 2
 
1.1%
120759 2
 
1.1%
120834 2
 
1.1%
120812 2
 
1.1%
120859 2
 
1.1%
120805 2
 
1.1%
120090 1
 
0.6%
120854 1
 
0.6%
Other values (15) 15
 
8.5%
(Missing) 141
80.1%
ValueCountFrequency (%)
0 2
1.1%
120012 1
 
0.6%
120013 1
 
0.6%
120030 4
2.3%
120070 2
1.1%
120090 1
 
0.6%
120140 1
 
0.6%
120180 1
 
0.6%
120759 2
1.1%
120805 2
1.1%
ValueCountFrequency (%)
120859 2
1.1%
120856 1
0.6%
120854 1
0.6%
120848 1
0.6%
120844 1
0.6%
120836 1
0.6%
120834 2
1.1%
120833 1
0.6%
120831 1
0.6%
120822 1
0.6%

지번주소
Text

MISSING 

Distinct164
Distinct (%)96.5%
Missing6
Missing (%)3.4%
Memory size1.5 KiB
2024-04-06T20:12:03.490207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40.5
Mean length29.235294
Min length12

Characters and Unicode

Total characters4970
Distinct characters189
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

Unique159 ?
Unique (%)93.5%

Sample

1st row서울특별시 강동구 암사동 414번지 2호 15통 4반 강동아파트 25 106
2nd row서울특별시 서대문구 남가좌동 335번지 7호 18통 6반 명지플러스빌(A) 502
3rd row경기도 고양시덕양구 행신동 726번지 1호 2통 3반 201
4th row서울특별시 마포구 용강동 149번지 20호 6통 6반
5th row서울특별시 노원구 상계동 1256호 14통 9반 은빛아파트 208 1012
ValueCountFrequency (%)
서울특별시 155
 
14.8%
서대문구 123
 
11.7%
홍제동 18
 
1.7%
창천동 16
 
1.5%
남가좌동 14
 
1.3%
북아현동 13
 
1.2%
1호 12
 
1.1%
홍은동 11
 
1.0%
연희동 10
 
1.0%
충정로3가 9
 
0.9%
Other values (411) 669
63.7%
2024-04-06T20:12:04.294132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
983
19.8%
서 285
 
5.7%
1 235
 
4.7%
2 168
 
3.4%
시 168
 
3.4%
동 166
 
3.3%
구 165
 
3.3%
3 164
 
3.3%
울 157
 
3.2%
별 155
 
3.1%
Other values (179) 2324
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2858
57.5%
Decimal Number 1092
 
22.0%
Space Separator 983
 
19.8%
Dash Punctuation 23
 
0.5%
Uppercase Letter 11
 
0.2%
Close Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 285
 
10.0%
시 168
 
5.9%
동 166
 
5.8%
구 165
 
5.8%
울 157
 
5.5%
별 155
 
5.4%
특 155
 
5.4%
호 144
 
5.0%
대 136
 
4.8%
지 132
 
4.6%
Other values (160) 1195
41.8%
Decimal Number
ValueCountFrequency (%)
1 235
21.5%
2 168
15.4%
3 164
15.0%
0 117
10.7%
5 92
 
8.4%
4 89
 
8.2%
6 69
 
6.3%
7 69
 
6.3%
8 49
 
4.5%
9 40
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
S 4
36.4%
K 4
36.4%
B 2
18.2%
A 1
 
9.1%
Space Separator
ValueCountFrequency (%)
983
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2858
57.5%
Common 2101
42.3%
Latin 11
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 285
 
10.0%
시 168
 
5.9%
동 166
 
5.8%
구 165
 
5.8%
울 157
 
5.5%
별 155
 
5.4%
특 155
 
5.4%
호 144
 
5.0%
대 136
 
4.8%
지 132
 
4.6%
Other values (160) 1195
41.8%
Common
ValueCountFrequency (%)
983
46.8%
1 235
 
11.2%
2 168
 
8.0%
3 164
 
7.8%
0 117
 
5.6%
5 92
 
4.4%
4 89
 
4.2%
6 69
 
3.3%
7 69
 
3.3%
8 49
 
2.3%
Other values (5) 66
 
3.1%
Latin
ValueCountFrequency (%)
S 4
36.4%
K 4
36.4%
B 2
18.2%
A 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2858
57.5%
ASCII 2112
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
983
46.5%
1 235
 
11.1%
2 168
 
8.0%
3 164
 
7.8%
0 117
 
5.5%
5 92
 
4.4%
4 89
 
4.2%
6 69
 
3.3%
7 69
 
3.3%
8 49
 
2.3%
Other values (9) 77
 
3.6%
Hangul
ValueCountFrequency (%)
서 285
 
10.0%
시 168
 
5.9%
동 166
 
5.8%
구 165
 
5.8%
울 157
 
5.5%
별 155
 
5.4%
특 155
 
5.4%
호 144
 
5.0%
대 136
 
4.8%
지 132
 
4.6%
Other values (160) 1195
41.8%

도로명주소
Text

MISSING 

Distinct144
Distinct (%)96.0%
Missing26
Missing (%)14.8%
Memory size1.5 KiB
2024-04-06T20:12:04.778032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length44
Mean length31.106667
Min length16

Characters and Unicode

Total characters4666
Distinct characters200
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

Unique139 ?
Unique (%)92.7%

Sample

1st row서울특별시 강동구 고덕로 131, 25동 106호 (암사동,강동아파트)
2nd row서울특별시 서대문구 가재울로4길 48, 502호 (남가좌동,명지플러스빌(A))
3rd row경기도 고양시 덕양구 무원로 50-4, 201호 (행신동)
4th row서울특별시 마포구 대흥로6길 18-9 (용강동)
5th row서울특별시 노원구 동일로245가길 41, 208동 1012호 (상계동,은빛아파트)
ValueCountFrequency (%)
서울특별시 144
 
16.1%
서대문구 119
 
13.3%
3층 19
 
2.1%
통일로 18
 
2.0%
홍제동 17
 
1.9%
신촌로 17
 
1.9%
2층 17
 
1.9%
창천동 15
 
1.7%
북아현동 12
 
1.3%
충정로3가 10
 
1.1%
Other values (343) 505
56.6%
2024-04-06T20:12:05.953638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
743
 
15.9%
서 272
 
5.8%
동 164
 
3.5%
로 158
 
3.4%
1 153
 
3.3%
시 149
 
3.2%
( 148
 
3.2%
) 148
 
3.2%
구 146
 
3.1%
울 146
 
3.1%
Other values (190) 2439
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2731
58.5%
Space Separator 743
 
15.9%
Decimal Number 719
 
15.4%
Open Punctuation 148
 
3.2%
Close Punctuation 148
 
3.2%
Other Punctuation 125
 
2.7%
Dash Punctuation 33
 
0.7%
Uppercase Letter 15
 
0.3%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 272
 
10.0%
동 164
 
6.0%
로 158
 
5.8%
시 149
 
5.5%
구 146
 
5.3%
울 146
 
5.3%
특 144
 
5.3%
별 144
 
5.3%
대 138
 
5.1%
문 127
 
4.7%
Other values (164) 1143
41.9%
Decimal Number
ValueCountFrequency (%)
1 153
21.3%
2 124
17.2%
3 114
15.9%
0 67
9.3%
4 65
9.0%
5 61
 
8.5%
7 44
 
6.1%
6 41
 
5.7%
8 27
 
3.8%
9 23
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
20.0%
S 3
20.0%
K 3
20.0%
A 2
13.3%
U 2
13.3%
G 1
 
6.7%
C 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
t 1
25.0%
i 1
25.0%
n 1
25.0%
u 1
25.0%
Space Separator
ValueCountFrequency (%)
743
100.0%
Open Punctuation
ValueCountFrequency (%)
( 148
100.0%
Close Punctuation
ValueCountFrequency (%)
) 148
100.0%
Other Punctuation
ValueCountFrequency (%)
, 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2731
58.5%
Common 1916
41.1%
Latin 19
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 272
 
10.0%
동 164
 
6.0%
로 158
 
5.8%
시 149
 
5.5%
구 146
 
5.3%
울 146
 
5.3%
특 144
 
5.3%
별 144
 
5.3%
대 138
 
5.1%
문 127
 
4.7%
Other values (164) 1143
41.9%
Common
ValueCountFrequency (%)
743
38.8%
1 153
 
8.0%
( 148
 
7.7%
) 148
 
7.7%
, 125
 
6.5%
2 124
 
6.5%
3 114
 
5.9%
0 67
 
3.5%
4 65
 
3.4%
5 61
 
3.2%
Other values (5) 168
 
8.8%
Latin
ValueCountFrequency (%)
B 3
15.8%
S 3
15.8%
K 3
15.8%
A 2
10.5%
U 2
10.5%
G 1
 
5.3%
t 1
 
5.3%
i 1
 
5.3%
n 1
 
5.3%
u 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2731
58.5%
ASCII 1935
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
743
38.4%
1 153
 
7.9%
( 148
 
7.6%
) 148
 
7.6%
, 125
 
6.5%
2 124
 
6.4%
3 114
 
5.9%
0 67
 
3.5%
4 65
 
3.4%
5 61
 
3.2%
Other values (16) 187
 
9.7%
Hangul
ValueCountFrequency (%)
서 272
 
10.0%
동 164
 
6.0%
로 158
 
5.8%
시 149
 
5.5%
구 146
 
5.3%
울 146
 
5.3%
특 144
 
5.3%
별 144
 
5.3%
대 138
 
5.1%
문 127
 
4.7%
Other values (164) 1143
41.9%

도로명우편번호
Text

MISSING 

Distinct57
Distinct (%)64.0%
Missing87
Missing (%)49.4%
Memory size1.5 KiB
2024-04-06T20:12:06.348157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4719101
Min length5

Characters and Unicode

Total characters487
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

Unique38 ?
Unique (%)42.7%

Sample

1st row120100
2nd row03616
3rd row120-828
4th row120805
5th row120070
ValueCountFrequency (%)
03636 5
 
5.6%
03785 4
 
4.5%
03751 4
 
4.5%
120805 4
 
4.5%
120821 3
 
3.4%
03616 3
 
3.4%
120859 3
 
3.4%
03758 3
 
3.4%
03780 2
 
2.2%
03735 2
 
2.2%
Other values (47) 56
62.9%
2024-04-06T20:12:07.016527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 111
22.8%
3 80
16.4%
1 61
12.5%
7 53
10.9%
2 52
10.7%
8 48
9.9%
6 30
 
6.2%
5 29
 
6.0%
4 11
 
2.3%
9 7
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 482
99.0%
Dash Punctuation 5
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 111
23.0%
3 80
16.6%
1 61
12.7%
7 53
11.0%
2 52
10.8%
8 48
10.0%
6 30
 
6.2%
5 29
 
6.0%
4 11
 
2.3%
9 7
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 487
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 111
22.8%
3 80
16.4%
1 61
12.5%
7 53
10.9%
2 52
10.7%
8 48
9.9%
6 30
 
6.2%
5 29
 
6.0%
4 11
 
2.3%
9 7
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 487
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 111
22.8%
3 80
16.4%
1 61
12.5%
7 53
10.9%
2 52
10.7%
8 48
9.9%
6 30
 
6.2%
5 29
 
6.0%
4 11
 
2.3%
9 7
 
1.4%

사업장명
Text

Distinct160
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-06T20:12:07.442857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.5681818
Min length2

Characters and Unicode

Total characters1156
Distinct characters229
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

Unique147 ?
Unique (%)83.5%

Sample

1st row신진인력
2nd row굿모닝직업소개소
3rd row대양인력
4th row삼일인력
5th row이화직업소개소
ValueCountFrequency (%)
현대인력 4
 
2.2%
인창인력개발 3
 
1.6%
주식회사 3
 
1.6%
효림연꽃간병회 2
 
1.1%
국지파출부 2
 
1.1%
세화파출박사 2
 
1.1%
신도직업소개소 2
 
1.1%
대명인력 2
 
1.1%
장안인력직업소개소 2
 
1.1%
매일인력소개소 2
 
1.1%
Other values (157) 161
87.0%
2024-04-06T20:12:08.234051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 78
 
6.7%
인 76
 
6.6%
력 67
 
5.8%
업 53
 
4.6%
개 48
 
4.2%
직 37
 
3.2%
주 28
 
2.4%
) 26
 
2.2%
( 26
 
2.2%
대 23
 
2.0%
Other values (219) 694
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1086
93.9%
Close Punctuation 26
 
2.2%
Open Punctuation 26
 
2.2%
Space Separator 9
 
0.8%
Uppercase Letter 5
 
0.4%
Decimal Number 2
 
0.2%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 78
 
7.2%
인 76
 
7.0%
력 67
 
6.2%
업 53
 
4.9%
개 48
 
4.4%
직 37
 
3.4%
주 28
 
2.6%
대 23
 
2.1%
사 20
 
1.8%
파 19
 
1.7%
Other values (209) 637
58.7%
Uppercase Letter
ValueCountFrequency (%)
D 2
40.0%
C 2
40.0%
B 1
20.0%
Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1086
93.9%
Common 65
 
5.6%
Latin 5
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 78
 
7.2%
인 76
 
7.0%
력 67
 
6.2%
업 53
 
4.9%
개 48
 
4.4%
직 37
 
3.4%
주 28
 
2.6%
대 23
 
2.1%
사 20
 
1.8%
파 19
 
1.7%
Other values (209) 637
58.7%
Common
ValueCountFrequency (%)
) 26
40.0%
( 26
40.0%
9
 
13.8%
4 1
 
1.5%
2 1
 
1.5%
- 1
 
1.5%
. 1
 
1.5%
Latin
ValueCountFrequency (%)
D 2
40.0%
C 2
40.0%
B 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1086
93.9%
ASCII 70
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 78
 
7.2%
인 76
 
7.0%
력 67
 
6.2%
업 53
 
4.9%
개 48
 
4.4%
직 37
 
3.4%
주 28
 
2.6%
대 23
 
2.1%
사 20
 
1.8%
파 19
 
1.7%
Other values (209) 637
58.7%
ASCII
ValueCountFrequency (%)
) 26
37.1%
( 26
37.1%
9
 
12.9%
D 2
 
2.9%
C 2
 
2.9%
4 1
 
1.4%
2 1
 
1.4%
B 1
 
1.4%
- 1
 
1.4%
. 1
 
1.4%

최종수정일자
Date

UNIQUE 

Distinct176
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2002-12-26 10:13:00
Maximum2024-03-26 11:04:20
2024-04-06T20:12:08.475320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:12:08.700470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
I
114 
U
62 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 114
64.8%
U 62
35.2%

Length

2024-04-06T20:12:08.906983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:12:09.072831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 114
64.8%
u 62
35.2%

데이터갱신일자
Date

Distinct58
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 00:01:00
2024-04-06T20:12:09.332002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:12:09.611891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing176
Missing (%)100.0%
Memory size1.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)82.7%
Missing14
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean195704.67
Minimum162211.61
Maximum307181.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T20:12:09.870150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162211.61
5-th percentile191542.54
Q1193224.16
median194806.78
Q3196448.71
95-th percentile204546.19
Maximum307181.05
Range144969.44
Interquartile range (IQR)3224.5515

Descriptive statistics

Standard deviation10919.348
Coefficient of variation (CV)0.055795028
Kurtosis69.653303
Mean195704.67
Median Absolute Deviation (MAD)1641.9378
Skewness6.8604468
Sum31704157
Variance1.1923216 × 108
MonotonicityNot monotonic
2024-04-06T20:12:10.133529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193658.392546336 4
 
2.3%
192344.544098471 4
 
2.3%
196448.713013759 3
 
1.7%
193712.476983727 3
 
1.7%
195800.331325215 3
 
1.7%
196945.454641052 3
 
1.7%
194806.775203536 2
 
1.1%
194801.032701714 2
 
1.1%
196694.508582738 2
 
1.1%
196547.231336512 2
 
1.1%
Other values (124) 134
76.1%
(Missing) 14
 
8.0%
ValueCountFrequency (%)
162211.611232 1
0.6%
173614.769861 1
0.6%
174929.168939872 2
1.1%
185057.502220867 1
0.6%
185156.62 1
0.6%
191183.459824345 1
0.6%
191244.784879947 1
0.6%
191541.062720484 1
0.6%
191570.558061115 1
0.6%
191575.088500465 1
0.6%
ValueCountFrequency (%)
307181.047797103 1
0.6%
239517.510978 1
0.6%
214250.097969559 1
0.6%
212480.463676316 1
0.6%
209988.377116635 1
0.6%
208153.686495999 1
0.6%
207914.471699463 1
0.6%
207329.748468929 1
0.6%
204650.437591318 1
0.6%
202565.446605672 1
0.6%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct134
Distinct (%)82.7%
Missing14
Missing (%)8.0%
Infinite0
Infinite (%)0.0%
Mean447659.86
Minimum188966.87
Maximum464174.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T20:12:10.430082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum188966.87
5-th percentile443926.49
Q1450637.01
median451813.11
Q3453424.89
95-th percentile455578.17
Maximum464174.16
Range275207.29
Interquartile range (IQR)2787.8825

Descriptive statistics

Standard deviation27898.983
Coefficient of variation (CV)0.062321833
Kurtosis56.042415
Mean447659.86
Median Absolute Deviation (MAD)1241.5961
Skewness-7.1872613
Sum72520898
Variance7.7835327 × 108
MonotonicityNot monotonic
2024-04-06T20:12:10.756837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450660.696125699 4
 
2.3%
452002.278744736 4
 
2.3%
451164.668205346 3
 
1.7%
450637.010875398 3
 
1.7%
450589.776484296 3
 
1.7%
451003.162676008 3
 
1.7%
454220.608298587 2
 
1.1%
454232.508849109 2
 
1.1%
451070.359709608 2
 
1.1%
450950.82823808 2
 
1.1%
Other values (124) 134
76.1%
(Missing) 14
 
8.0%
ValueCountFrequency (%)
188966.870724 1
0.6%
288922.558014 1
0.6%
313121.407876 1
0.6%
344761.575260384 1
0.6%
428046.973145893 1
0.6%
439360.432090159 1
0.6%
443195.096196007 1
0.6%
443385.050640776 1
0.6%
443852.392629143 1
0.6%
445334.308692995 1
0.6%
ValueCountFrequency (%)
464174.158420444 1
0.6%
459671.584918172 1
0.6%
457302.441641659 1
0.6%
457269.513398629 1
0.6%
457207.71 1
0.6%
456952.630974375 1
0.6%
456813.585244572 1
0.6%
455694.013712423 1
0.6%
455588.317096857 1
0.6%
455385.324954246 1
0.6%

법인구분명
Categorical

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
개인
105 
<NA>
50 
법인
21 

Length

Max length4
Median length2
Mean length2.5681818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 105
59.7%
<NA> 50
28.4%
법인 21
 
11.9%

Length

2024-04-06T20:12:11.015390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:12:11.218459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 105
59.7%
na 50
28.4%
법인 21
 
11.9%

구분명
Categorical

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
유료
126 
<NA>
50 

Length

Max length4
Median length2
Mean length2.5681818
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 126
71.6%
<NA> 50
 
28.4%

Length

2024-04-06T20:12:11.409251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:12:11.585713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 126
71.6%
na 50
 
28.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
03120000200231200751150000120021010<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 암사동 414번지 2호 15통 4반 강동아파트 25 106서울특별시 강동구 고덕로 131, 25동 106호 (암사동,강동아파트)<NA>신진인력2004-04-14 15:15:53I2018-08-31 23:59:59.0<NA>212480.463676450472.374955개인유료
13120000200231200751150000220021009<NA>3폐업40폐업20071025<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 335번지 7호 18통 6반 명지플러스빌(A) 502서울특별시 서대문구 가재울로4길 48, 502호 (남가좌동,명지플러스빌(A))<NA>굿모닝직업소개소2007-11-05 15:13:41I2018-08-31 23:59:59.0<NA>193241.260234452606.168709개인유료
23120000200231200751150000320021004<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>경기도 고양시덕양구 행신동 726번지 1호 2통 3반 201경기도 고양시 덕양구 무원로 50-4, 201호 (행신동)<NA>대양인력2004-11-01 15:51:27I2018-08-31 23:59:59.0<NA>185156.62457207.71개인유료
33120000200231200751150000420020712<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 용강동 149번지 20호 6통 6반서울특별시 마포구 대흥로6길 18-9 (용강동)<NA>삼일인력2004-07-12 13:40:39I2018-08-31 23:59:59.0<NA>194548.615449448857.659624개인유료
43120000200231200751150000520021216<NA>3폐업40폐업20050215<NA><NA><NA><NA><NA><NA>서울특별시 노원구 상계동 1256호 14통 9반 은빛아파트 208 1012서울특별시 노원구 동일로245가길 41, 208동 1012호 (상계동,은빛아파트)<NA>이화직업소개소2012-08-21 22:22:01I2018-08-31 23:59:59.0<NA>204650.437591464174.15842개인유료
53120000200231200751150000620020403<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 175번지 21호 6통 3반서울특별시 서대문구 거북골로12라길 38-14 (남가좌동)<NA>대흥직업소개소2004-11-06 10:39:35I2018-08-31 23:59:59.0<NA>192660.968887452760.757507개인유료
63120000200231200751150000720020204<NA>3폐업40폐업20030729<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 340번지 7호 28통 1반서울특별시 서대문구 가좌로2길 9 (홍은동)<NA>성민개발2007-10-25 10:37:10I2018-08-31 23:59:59.0<NA>193212.675108453685.555236개인유료
73120000200231200751150000820011219<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 463호 25통 1반 문화촌현대아파트 103 402<NA><NA>행운직업소개소2003-12-05 16:15:02I2018-08-31 23:59:59.0<NA>195469.809626454441.811923개인유료
83120000200231200751150001020021224<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>충청남도 서천군 서천읍 태월리 305호 16통<NA><NA>하마직업소개소2004-10-28 16:32:13I2018-08-31 23:59:59.0<NA>173614.769861288922.558014개인유료
93120000200231200751150001220010606<NA>3폐업40폐업<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 남가좌동 295번지 5호 13통 2반 4 303서울특별시 서대문구 수색로 42, 4동 303호 (남가좌동)<NA>매일인력소개소2004-10-11 11:31:33I2018-08-31 23:59:59.0<NA>192344.544098452002.278745개인유료
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)법인구분명구분명
166312000020213120192145000072021-12-21<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍은동 48-180서울특별시 서대문구 세검정로 9, 3층 (홍은동)03616국지파출부2023-08-31 18:20:49U2022-12-09 00:02:00.0<NA>194839.712386454410.451782<NA><NA>
167312000020223120192145000012022-01-14<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 503-13 동우빌딩서울특별시 서대문구 신촌로 17, 동우빌딩 305호 (창천동)03785건영인력2024-01-03 10:28:54U2023-12-01 00:05:00.0<NA>193658.392546450660.696126<NA><NA>
168312000020223120192145000022022-05-12<NA>1영업/정상20영업중<NA><NA><NA><NA>16666110<NA><NA>서울특별시 서대문구 창천동 62-63서울특별시 서대문구 연세로5다길 8, 3층 (창천동)03789미림취업정보2023-07-25 15:36:46U2022-12-06 22:07:00.0<NA>194197.840844450465.764164<NA><NA>
169312000020223120192145000032010-11-04<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 20-39서울특별시 서대문구 신촌로 123, 2층 201호 (창천동)03780태림인력개발2023-10-25 08:26:26U2022-10-30 22:07:00.0<NA>194594.316088450445.951377<NA><NA>
170312000020223120192145000042022-08-12<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 대현동 90-73서울특별시 서대문구 이화여대1길 33, UCU 2층 unit 20G (대현동)03766피플넷2023-08-04 08:24:20U2022-12-08 00:06:00.0<NA><NA><NA><NA><NA>
171312000020223120192145000052022-10-27<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 503-8서울특별시 서대문구 신촌로 25, 2층 3136호 (창천동)03785탤런트인사이트2023-10-12 18:47:55U2022-10-30 23:04:00.0<NA>193712.476984450637.010875<NA><NA>
172312000020223120192145000062022-11-22<NA>3폐업40폐업2023-06-02<NA><NA><NA><NA><NA><NA>서울특별시 서대문구 홍제동 282-12 은혜교회서울특별시 서대문구 세검정로4길 2, 은혜교회 4층 (홍제동)03622홍제인력2023-06-02 16:32:41U2022-12-06 00:04:00.0<NA>195375.014054454666.748703<NA><NA>
1733120000202231201921450000720221207<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 717-29 한인트윈빌서울특별시 서대문구 홍연길 77, 202호 A4호 (연희동, 한인트윈빌)03695피플파트너스2022-12-07 16:46:35I2021-11-02 00:09:00.0<NA>193803.424182452723.457356<NA><NA>
174312000020233120219145000012023-05-17<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 창천동 5-46서울특별시 서대문구 명물길 46, 5층 (창천동)03777주식회사 비웰코리아2023-05-17 16:45:59I2022-12-04 23:09:00.0<NA>194551.045111450694.239086<NA><NA>
175312000020243120219145000012024-03-26<NA>1영업/정상20영업중<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 연희동 134-38서울특별시 서대문구 연희맛로 42-3, 지층 (연희동)03708커넥트퓨처2024-03-26 11:04:20I2023-12-02 22:08:00.0<NA>193887.007623451798.960316<NA><NA>