Overview

Dataset statistics

Number of variables29
Number of observations137
Missing cells1403
Missing cells (%)35.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.3 KiB
Average record size in memory249.0 B

Variable types

Numeric4
Text6
DateTime4
Categorical7
Unsupported8

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),전문인력총수,자본금,시설장비,타기관이전여부
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16114/S/1/datasetView.do

Alerts

인허가취소일자 has 87 (63.5%) missing valuesMissing
폐업일자 has 137 (100.0%) missing valuesMissing
휴업시작일자 has 137 (100.0%) missing valuesMissing
휴업종료일자 has 137 (100.0%) missing valuesMissing
재개업일자 has 137 (100.0%) missing valuesMissing
전화번호 has 137 (100.0%) missing valuesMissing
소재지면적 has 137 (100.0%) missing valuesMissing
소재지우편번호 has 137 (100.0%) missing valuesMissing
지번주소 has 5 (3.6%) missing valuesMissing
도로명주소 has 21 (15.3%) missing valuesMissing
도로명우편번호 has 98 (71.5%) missing valuesMissing
업태구분명 has 137 (100.0%) missing valuesMissing
좌표정보(X) has 13 (9.5%) missing valuesMissing
좌표정보(Y) has 13 (9.5%) missing valuesMissing
전문인력총수 has 32 (23.4%) missing valuesMissing
시설장비 has 38 (27.7%) missing valuesMissing
최종수정일자 has unique valuesUnique
폐업일자 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
전화번호 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
소재지우편번호 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

Reproduction

Analysis started2024-04-29 18:52:25.147501
Analysis finished2024-04-29 18:52:25.956626
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct23
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3179270.1
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-30T03:52:26.028169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3050000
Q13150000
median3200000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation56667.698
Coefficient of variation (CV)0.017824122
Kurtosis1.1676261
Mean3179270.1
Median Absolute Deviation (MAD)30000
Skewness-1.3768637
Sum4.3556 × 108
Variance3.211228 × 109
MonotonicityNot monotonic
2024-04-30T03:52:26.136184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3220000 26
19.0%
3210000 20
14.6%
3230000 15
10.9%
3170000 11
8.0%
3150000 9
 
6.6%
3200000 9
 
6.6%
3180000 8
 
5.8%
3240000 6
 
4.4%
3130000 5
 
3.6%
3160000 5
 
3.6%
Other values (13) 23
16.8%
ValueCountFrequency (%)
3000000 1
 
0.7%
3020000 1
 
0.7%
3030000 2
1.5%
3040000 2
1.5%
3050000 4
2.9%
3060000 2
1.5%
3070000 2
1.5%
3090000 1
 
0.7%
3100000 1
 
0.7%
3110000 1
 
0.7%
ValueCountFrequency (%)
3240000 6
 
4.4%
3230000 15
10.9%
3220000 26
19.0%
3210000 20
14.6%
3200000 9
 
6.6%
3190000 2
 
1.5%
3180000 8
 
5.8%
3170000 11
8.0%
3160000 5
 
3.6%
3150000 9
 
6.6%

관리번호
Text

Distinct118
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-30T03:52:26.291872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters2603
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)74.5%

Sample

1st rowS001145310000074L00
2nd rowS001311110247782L00
3rd rowS001101710068062L00
4th rowS001101220021831L00
5th rowS001101111262289L00
ValueCountFrequency (%)
s001101111826978l00 3
 
2.2%
s001101113189556l00 3
 
2.2%
s001101115286623l00 3
 
2.2%
s001101112535536l00 2
 
1.5%
s001101112309014l00 2
 
1.5%
s001101112677859l00 2
 
1.5%
s001101112919326l00 2
 
1.5%
s001101112303850l00 2
 
1.5%
s001101112037350l00 2
 
1.5%
s001101111384380l00 2
 
1.5%
Other values (108) 114
83.2%
2024-04-30T03:52:26.581737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 853
32.8%
1 736
28.3%
S 137
 
5.3%
2 133
 
5.1%
L 131
 
5.0%
3 98
 
3.8%
6 97
 
3.7%
4 95
 
3.6%
8 87
 
3.3%
5 84
 
3.2%
Other values (2) 152
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2335
89.7%
Uppercase Letter 268
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 853
36.5%
1 736
31.5%
2 133
 
5.7%
3 98
 
4.2%
6 97
 
4.2%
4 95
 
4.1%
8 87
 
3.7%
5 84
 
3.6%
9 81
 
3.5%
7 71
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 137
51.1%
L 131
48.9%

Most occurring scripts

ValueCountFrequency (%)
Common 2335
89.7%
Latin 268
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 853
36.5%
1 736
31.5%
2 133
 
5.7%
3 98
 
4.2%
6 97
 
4.2%
4 95
 
4.1%
8 87
 
3.7%
5 84
 
3.6%
9 81
 
3.5%
7 71
 
3.0%
Latin
ValueCountFrequency (%)
S 137
51.1%
L 131
48.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 853
32.8%
1 736
28.3%
S 137
 
5.3%
2 133
 
5.1%
L 131
 
5.0%
3 98
 
3.8%
6 97
 
3.7%
4 95
 
3.6%
8 87
 
3.3%
5 84
 
3.2%
Other values (2) 152
 
5.8%

인허가일자
Date

Distinct124
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1997-09-06 00:00:00
Maximum2024-01-22 00:00:00
2024-04-30T03:52:26.694909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:52:26.859257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct48
Distinct (%)96.0%
Missing87
Missing (%)63.5%
Memory size1.2 KiB
Minimum1997-09-06 00:00:00
Maximum2024-03-28 00:00:00
2024-04-30T03:52:26.977362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:52:27.085648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

영업상태코드
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
86 
3
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 86
62.8%
3 51
37.2%

Length

2024-04-30T03:52:27.178999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:27.259780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 86
62.8%
3 51
37.2%

영업상태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업/정상
86 
폐업
51 

Length

Max length5
Median length5
Mean length3.8832117
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 86
62.8%
폐업 51
37.2%

Length

2024-04-30T03:52:27.351635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:27.431780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 86
62.8%
폐업 51
37.2%

상세영업상태코드
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
86 
2
51 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 86
62.8%
2 51
37.2%

Length

2024-04-30T03:52:27.516910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:27.601227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 86
62.8%
2 51
37.2%

상세영업상태명
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업
86 
취소정지업체
51 

Length

Max length6
Median length2
Mean length3.4890511
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소정지업체
2nd row영업
3rd row영업
4th row취소정지업체
5th row영업

Common Values

ValueCountFrequency (%)
영업 86
62.8%
취소정지업체 51
37.2%

Length

2024-04-30T03:52:27.699950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:27.783368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 86
62.8%
취소정지업체 51
37.2%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

지번주소
Text

MISSING 

Distinct131
Distinct (%)99.2%
Missing5
Missing (%)3.6%
Memory size1.2 KiB
2024-04-30T03:52:28.050656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length26.734848
Min length7

Characters and Unicode

Total characters3529
Distinct characters199
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)98.5%

Sample

1st row서울특별시 서대문구 신촌동 134
2nd row서울특별시 송파구 문정동 651-10 파트너스1 1003호
3rd row서울특별시 영등포구 양평동6가 86-3 해남빌딩
4th row서울특별시 강서구 등촌동 934-9
5th row서울특별시 마포구 공덕동 456번지 르네상스1908
ValueCountFrequency (%)
서울특별시 130
 
19.7%
강남구 25
 
3.8%
서초구 19
 
2.9%
송파구 14
 
2.1%
금천구 11
 
1.7%
강서구 9
 
1.4%
양재동 8
 
1.2%
영등포구 8
 
1.2%
가산동 8
 
1.2%
방배동 7
 
1.1%
Other values (324) 422
63.8%
2024-04-30T03:52:28.463610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
614
 
17.4%
서 164
 
4.6%
동 160
 
4.5%
1 154
 
4.4%
구 139
 
3.9%
시 134
 
3.8%
특 130
 
3.7%
별 130
 
3.7%
울 130
 
3.7%
- 111
 
3.1%
Other values (189) 1663
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2036
57.7%
Decimal Number 741
 
21.0%
Space Separator 614
 
17.4%
Dash Punctuation 111
 
3.1%
Uppercase Letter 23
 
0.7%
Other Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 164
 
8.1%
동 160
 
7.9%
구 139
 
6.8%
시 134
 
6.6%
특 130
 
6.4%
별 130
 
6.4%
울 130
 
6.4%
지 90
 
4.4%
번 85
 
4.2%
호 43
 
2.1%
Other values (163) 831
40.8%
Decimal Number
ValueCountFrequency (%)
1 154
20.8%
2 98
13.2%
4 90
12.1%
0 75
10.1%
5 68
9.2%
3 65
8.8%
6 54
 
7.3%
8 53
 
7.2%
9 46
 
6.2%
7 38
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
A 5
21.7%
I 4
17.4%
F 2
 
8.7%
C 2
 
8.7%
N 2
 
8.7%
K 2
 
8.7%
E 2
 
8.7%
S 2
 
8.7%
D 1
 
4.3%
B 1
 
4.3%
Space Separator
ValueCountFrequency (%)
614
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2036
57.7%
Common 1469
41.6%
Latin 24
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 164
 
8.1%
동 160
 
7.9%
구 139
 
6.8%
시 134
 
6.6%
특 130
 
6.4%
별 130
 
6.4%
울 130
 
6.4%
지 90
 
4.4%
번 85
 
4.2%
호 43
 
2.1%
Other values (163) 831
40.8%
Common
ValueCountFrequency (%)
614
41.8%
1 154
 
10.5%
- 111
 
7.6%
2 98
 
6.7%
4 90
 
6.1%
0 75
 
5.1%
5 68
 
4.6%
3 65
 
4.4%
6 54
 
3.7%
8 53
 
3.6%
Other values (5) 87
 
5.9%
Latin
ValueCountFrequency (%)
A 5
20.8%
I 4
16.7%
F 2
 
8.3%
C 2
 
8.3%
N 2
 
8.3%
K 2
 
8.3%
E 2
 
8.3%
S 2
 
8.3%
D 1
 
4.2%
B 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2036
57.7%
ASCII 1492
42.3%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
614
41.2%
1 154
 
10.3%
- 111
 
7.4%
2 98
 
6.6%
4 90
 
6.0%
0 75
 
5.0%
5 68
 
4.6%
3 65
 
4.4%
6 54
 
3.6%
8 53
 
3.6%
Other values (15) 110
 
7.4%
Hangul
ValueCountFrequency (%)
서 164
 
8.1%
동 160
 
7.9%
구 139
 
6.8%
시 134
 
6.6%
특 130
 
6.4%
별 130
 
6.4%
울 130
 
6.4%
지 90
 
4.4%
번 85
 
4.2%
호 43
 
2.1%
Other values (163) 831
40.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

도로명주소
Text

MISSING 

Distinct115
Distinct (%)99.1%
Missing21
Missing (%)15.3%
Memory size1.2 KiB
2024-04-30T03:52:28.752076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39.5
Mean length31.724138
Min length21

Characters and Unicode

Total characters3680
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

Unique114 ?
Unique (%)98.3%

Sample

1st row서울특별시 서대문구 연세로 50 (신촌동)
2nd row서울특별시 송파구 법원로 92, 파트너스1 10층 1003호 (문정동)
3rd row서울특별시 관악구 관악로 1, 서울대학교 (신림동)
4th row서울특별시 영등포구 양평로28사길 29 (양평동6가)
5th row서울특별시 마포구 만리재로 14 (공덕동,르네상스1908)
ValueCountFrequency (%)
서울특별시 114
 
16.2%
강남구 20
 
2.8%
서초구 16
 
2.3%
송파구 14
 
2.0%
금천구 10
 
1.4%
관악구 8
 
1.1%
영등포구 8
 
1.1%
3층 8
 
1.1%
양재동 6
 
0.9%
신림동 6
 
0.9%
Other values (379) 492
70.1%
2024-04-30T03:52:29.172421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
590
 
16.0%
동 157
 
4.3%
서 147
 
4.0%
1 125
 
3.4%
시 121
 
3.3%
구 119
 
3.2%
로 117
 
3.2%
( 117
 
3.2%
) 117
 
3.2%
울 115
 
3.1%
Other values (210) 1955
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2154
58.5%
Space Separator 590
 
16.0%
Decimal Number 581
 
15.8%
Open Punctuation 117
 
3.2%
Close Punctuation 117
 
3.2%
Other Punctuation 97
 
2.6%
Dash Punctuation 16
 
0.4%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 157
 
7.3%
서 147
 
6.8%
시 121
 
5.6%
구 119
 
5.5%
로 117
 
5.4%
울 115
 
5.3%
별 114
 
5.3%
특 114
 
5.3%
길 53
 
2.5%
호 45
 
2.1%
Other values (191) 1052
48.8%
Decimal Number
ValueCountFrequency (%)
1 125
21.5%
2 91
15.7%
0 68
11.7%
3 61
10.5%
6 55
9.5%
4 50
 
8.6%
5 41
 
7.1%
8 40
 
6.9%
7 25
 
4.3%
9 25
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
37.5%
D 3
37.5%
J 1
 
12.5%
A 1
 
12.5%
Space Separator
ValueCountFrequency (%)
590
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Other Punctuation
ValueCountFrequency (%)
, 97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2154
58.5%
Common 1518
41.2%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 157
 
7.3%
서 147
 
6.8%
시 121
 
5.6%
구 119
 
5.5%
로 117
 
5.4%
울 115
 
5.3%
별 114
 
5.3%
특 114
 
5.3%
길 53
 
2.5%
호 45
 
2.1%
Other values (191) 1052
48.8%
Common
ValueCountFrequency (%)
590
38.9%
1 125
 
8.2%
( 117
 
7.7%
) 117
 
7.7%
, 97
 
6.4%
2 91
 
6.0%
0 68
 
4.5%
3 61
 
4.0%
6 55
 
3.6%
4 50
 
3.3%
Other values (5) 147
 
9.7%
Latin
ValueCountFrequency (%)
B 3
37.5%
D 3
37.5%
J 1
 
12.5%
A 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2154
58.5%
ASCII 1526
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
590
38.7%
1 125
 
8.2%
( 117
 
7.7%
) 117
 
7.7%
, 97
 
6.4%
2 91
 
6.0%
0 68
 
4.5%
3 61
 
4.0%
6 55
 
3.6%
4 50
 
3.3%
Other values (9) 155
 
10.2%
Hangul
ValueCountFrequency (%)
동 157
 
7.3%
서 147
 
6.8%
시 121
 
5.6%
구 119
 
5.5%
로 117
 
5.4%
울 115
 
5.3%
별 114
 
5.3%
특 114
 
5.3%
길 53
 
2.5%
호 45
 
2.1%
Other values (191) 1052
48.8%

도로명우편번호
Text

MISSING 

Distinct38
Distinct (%)97.4%
Missing98
Missing (%)71.5%
Memory size1.2 KiB
2024-04-30T03:52:29.341617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0769231
Min length5

Characters and Unicode

Total characters198
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

Unique37 ?
Unique (%)94.9%

Sample

1st row05855
2nd row08826
3rd row07201
4th row05704
5th row05826
ValueCountFrequency (%)
08589 2
 
5.1%
07547 1
 
2.6%
134-868 1
 
2.6%
08390 1
 
2.6%
07276 1
 
2.6%
07223 1
 
2.6%
08863 1
 
2.6%
151742 1
 
2.6%
06705 1
 
2.6%
06675 1
 
2.6%
Other values (28) 28
71.8%
2024-04-30T03:52:29.630427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51
25.8%
8 22
11.1%
6 22
11.1%
5 21
10.6%
7 21
10.6%
2 16
 
8.1%
3 12
 
6.1%
9 11
 
5.6%
1 11
 
5.6%
4 10
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 197
99.5%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
25.9%
8 22
11.2%
6 22
11.2%
5 21
10.7%
7 21
10.7%
2 16
 
8.1%
3 12
 
6.1%
9 11
 
5.6%
1 11
 
5.6%
4 10
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 198
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 51
25.8%
8 22
11.1%
6 22
11.1%
5 21
10.6%
7 21
10.6%
2 16
 
8.1%
3 12
 
6.1%
9 11
 
5.6%
1 11
 
5.6%
4 10
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 51
25.8%
8 22
11.1%
6 22
11.1%
5 21
10.6%
7 21
10.6%
2 16
 
8.1%
3 12
 
6.1%
9 11
 
5.6%
1 11
 
5.6%
4 10
 
5.1%

사업장명
Text

Distinct127
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-30T03:52:29.834275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length8.8248175
Min length5

Characters and Unicode

Total characters1209
Distinct characters176
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)86.9%

Sample

1st row연세대학교
2nd row(주)골든엔지니어링
3rd row서울대학교 농생명과학대학 농생명과학공동기기원
4th row(재)한국환경수도연구원
5th row㈜한국개발엔지니어링
ValueCountFrequency (%)
주식회사 6
 
3.9%
서울대학교 3
 
2.0%
농생명과학공동기기원 3
 
2.0%
상암지오텍(주 3
 
2.0%
농생명과학대학 3
 
2.0%
㈜대명엔지니어링 2
 
1.3%
주)리치이엔씨 2
 
1.3%
주)한국중앙온천연구소 2
 
1.3%
홍우기술산업㈜ 2
 
1.3%
주)동명엔터프라이즈 2
 
1.3%
Other values (121) 124
81.6%
2024-04-30T03:52:30.180510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 89
 
7.4%
주 89
 
7.4%
) 82
 
6.8%
( 80
 
6.6%
엔 40
 
3.3%
이 30
 
2.5%
㈜ 30
 
2.5%
어 29
 
2.4%
니 29
 
2.4%
링 27
 
2.2%
Other values (166) 684
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 999
82.6%
Close Punctuation 82
 
6.8%
Open Punctuation 80
 
6.6%
Other Symbol 30
 
2.5%
Space Separator 15
 
1.2%
Decimal Number 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 89
 
8.9%
주 89
 
8.9%
엔 40
 
4.0%
이 30
 
3.0%
어 29
 
2.9%
니 29
 
2.9%
링 27
 
2.7%
오 23
 
2.3%
기 23
 
2.3%
사 20
 
2.0%
Other values (159) 600
60.1%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 80
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 30
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1029
85.1%
Common 180
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 89
 
8.6%
주 89
 
8.6%
엔 40
 
3.9%
이 30
 
2.9%
㈜ 30
 
2.9%
어 29
 
2.8%
니 29
 
2.8%
링 27
 
2.6%
오 23
 
2.2%
기 23
 
2.2%
Other values (160) 620
60.3%
Common
ValueCountFrequency (%)
) 82
45.6%
( 80
44.4%
15
 
8.3%
- 1
 
0.6%
2 1
 
0.6%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 999
82.6%
ASCII 180
 
14.9%
None 30
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 89
 
8.9%
주 89
 
8.9%
엔 40
 
4.0%
이 30
 
3.0%
어 29
 
2.9%
니 29
 
2.9%
링 27
 
2.7%
오 23
 
2.3%
기 23
 
2.3%
사 20
 
2.0%
Other values (159) 600
60.1%
ASCII
ValueCountFrequency (%)
) 82
45.6%
( 80
44.4%
15
 
8.3%
- 1
 
0.6%
2 1
 
0.6%
1 1
 
0.6%
None
ValueCountFrequency (%)
㈜ 30
100.0%

최종수정일자
Date

UNIQUE 

Distinct137
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2003-05-01 23:00:18
Maximum2024-04-23 13:57:59
2024-04-30T03:52:30.299989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:52:30.403525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
79 
U
58 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 79
57.7%
U 58
42.3%

Length

2024-04-30T03:52:30.510596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:30.588729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 79
57.7%
u 58
42.3%

데이터갱신일자
Date

Distinct52
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:07:00
2024-04-30T03:52:30.669286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:52:30.774539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing137
Missing (%)100.0%
Memory size1.3 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)93.5%
Missing13
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean199802.77
Minimum176607.33
Maximum211671.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-30T03:52:30.896423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176607.33
5-th percentile187882.2
Q1191927.77
median202115.31
Q3205628.64
95-th percentile211231.8
Maximum211671.21
Range35063.88
Interquartile range (IQR)13700.871

Descriptive statistics

Standard deviation7970.3538
Coefficient of variation (CV)0.039891107
Kurtosis-0.82441284
Mean199802.77
Median Absolute Deviation (MAD)6253.5855
Skewness-0.32979419
Sum24775544
Variance63526540
MonotonicityNot monotonic
2024-04-30T03:52:31.023815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
211367.91579687 2
 
1.5%
191226.287379467 2
 
1.5%
202587.580788273 2
 
1.5%
203041.715702509 2
 
1.5%
206758.410389697 2
 
1.5%
205871.48455217 2
 
1.5%
207430.59305912 2
 
1.5%
196139.864969792 2
 
1.5%
211032.312945459 1
 
0.7%
211416.100517011 1
 
0.7%
Other values (106) 106
77.4%
(Missing) 13
 
9.5%
ValueCountFrequency (%)
176607.326609066 1
0.7%
184572.413912003 1
0.7%
185151.671374777 1
0.7%
186501.233192961 1
0.7%
187561.265938558 1
0.7%
187733.160920858 1
0.7%
187869.778713381 1
0.7%
187952.560027898 1
0.7%
187999.32555627 1
0.7%
188953.066831076 1
0.7%
ValueCountFrequency (%)
211671.206749269 1
0.7%
211416.100517011 1
0.7%
211367.91579687 2
1.5%
211310.447242137 1
0.7%
211255.759612505 1
0.7%
211239.753263781 1
0.7%
211186.749700436 1
0.7%
211032.312945459 1
0.7%
211025.233917273 1
0.7%
211012.501708485 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)93.5%
Missing13
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean445467.91
Minimum437914.06
Maximum458081.51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-30T03:52:31.340644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437914.06
5-th percentile440720.34
Q1442257.31
median444602.83
Q3448564.39
95-th percentile452607.3
Maximum458081.51
Range20167.452
Interquartile range (IQR)6307.0788

Descriptive statistics

Standard deviation4200.2412
Coefficient of variation (CV)0.00942883
Kurtosis0.13241724
Mean445467.91
Median Absolute Deviation (MAD)2851.7013
Skewness0.75357332
Sum55238021
Variance17642026
MonotonicityNot monotonic
2024-04-30T03:52:31.463674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
447225.778131525 2
 
1.5%
437914.06299827 2
 
1.5%
447108.55741274 2
 
1.5%
443080.510187766 2
 
1.5%
456472.216329929 2
 
1.5%
452607.300838198 2
 
1.5%
450270.915721606 2
 
1.5%
439023.167125842 2
 
1.5%
443820.166244998 1
 
0.7%
444932.958214657 1
 
0.7%
Other values (106) 106
77.4%
(Missing) 13
 
9.5%
ValueCountFrequency (%)
437914.06299827 2
1.5%
439023.167125842 2
1.5%
440523.497478209 1
0.7%
440591.943398537 1
0.7%
440685.11304384 1
0.7%
440919.941586052 1
0.7%
440963.790624982 1
0.7%
441055.274791714 1
0.7%
441191.418761721 1
0.7%
441316.29 1
0.7%
ValueCountFrequency (%)
458081.514801677 1
0.7%
456668.120617343 1
0.7%
456472.216329929 2
1.5%
454406.655078623 1
0.7%
452901.786745273 1
0.7%
452607.300838198 2
1.5%
452050.921389104 1
0.7%
451485.251875922 1
0.7%
451381.585492051 1
0.7%
450958.580192166 1
0.7%

전문인력총수
Real number (ℝ)

MISSING 

Distinct11
Distinct (%)10.5%
Missing32
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean4.5809524
Minimum2
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-04-30T03:52:31.582839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median4
Q34
95-th percentile9.6
Maximum21
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.3809377
Coefficient of variation (CV)0.51974732
Kurtosis22.951279
Mean4.5809524
Median Absolute Deviation (MAD)0
Skewness4.2069747
Sum481
Variance5.6688645
MonotonicityNot monotonic
2024-04-30T03:52:31.682410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4 63
46.0%
3 18
 
13.1%
5 10
 
7.3%
6 4
 
2.9%
11 3
 
2.2%
8 2
 
1.5%
21 1
 
0.7%
10 1
 
0.7%
7 1
 
0.7%
12 1
 
0.7%
(Missing) 32
23.4%
ValueCountFrequency (%)
2 1
 
0.7%
3 18
 
13.1%
4 63
46.0%
5 10
 
7.3%
6 4
 
2.9%
7 1
 
0.7%
8 2
 
1.5%
10 1
 
0.7%
11 3
 
2.2%
12 1
 
0.7%
ValueCountFrequency (%)
21 1
 
0.7%
12 1
 
0.7%
11 3
 
2.2%
10 1
 
0.7%
8 2
 
1.5%
7 1
 
0.7%
6 4
 
2.9%
5 10
 
7.3%
4 63
46.0%
3 18
 
13.1%

자본금
Categorical

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
105 
<NA>
32 

Length

Max length4
Median length1
Mean length1.7007299
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 105
76.6%
<NA> 32
 
23.4%

Length

2024-04-30T03:52:31.796443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:31.881100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 105
76.6%
na 32
 
23.4%

시설장비
Text

MISSING 

Distinct81
Distinct (%)81.8%
Missing38
Missing (%)27.7%
Memory size1.2 KiB
2024-04-30T03:52:32.023081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length110
Median length51
Mean length38.161616
Min length9

Characters and Unicode

Total characters3778
Distinct characters153
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

Unique74 ?
Unique (%)74.7%

Sample

1st row지하수위측정기1조, 수소이옹농도1조,수온전기전도도측정장비1조
2nd row지하수수위측정장비, 전기전도도측정기, pH 및 수온측정기
3rd row지하수위 측정장비 수소이온농도(ph), 수온, 전지전도도 측정 장비 지하수질 분석장비(가스크로마토그래피) 지하수 모델링 소프트웨어(MODFLOW) 등.
4th row지하수수위측정기, PH수온측정기, 전기전조도측정기
5th row지구물리탐사장비(2), 수위측정기(2), 수위,수량측정기(1), 간이수질측정기(2)
ValueCountFrequency (%)
1 89
 
13.2%
수위측정기 40
 
5.9%
1대 37
 
5.5%
2 34
 
5.0%
3 31
 
4.6%
ph 29
 
4.3%
4 21
 
3.1%
측정기 14
 
2.1%
meter 14
 
2.1%
14
 
2.1%
Other values (168) 353
52.2%
2024-04-30T03:52:32.312819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
707
18.7%
기 241
 
6.4%
수 224
 
5.9%
측 222
 
5.9%
정 215
 
5.7%
도 191
 
5.1%
1 165
 
4.4%
. 140
 
3.7%
전 136
 
3.6%
, 128
 
3.4%
Other values (143) 1409
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2047
54.2%
Space Separator 707
 
18.7%
Decimal Number 310
 
8.2%
Other Punctuation 275
 
7.3%
Uppercase Letter 274
 
7.3%
Lowercase Letter 85
 
2.2%
Open Punctuation 31
 
0.8%
Close Punctuation 31
 
0.8%
Dash Punctuation 18
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 241
11.8%
수 224
10.9%
측 222
10.8%
정 215
10.5%
도 191
9.3%
전 136
 
6.6%
위 105
 
5.1%
온 103
 
5.0%
대 73
 
3.6%
장 63
 
3.1%
Other values (84) 474
23.2%
Uppercase Letter
ValueCountFrequency (%)
P 52
19.0%
E 46
16.8%
H 46
16.8%
M 23
8.4%
R 23
8.4%
T 22
8.0%
C 9
 
3.3%
S 9
 
3.3%
D 8
 
2.9%
I 7
 
2.6%
Other values (12) 29
10.6%
Lowercase Letter
ValueCountFrequency (%)
h 12
14.1%
p 12
14.1%
e 11
12.9%
t 7
8.2%
c 7
8.2%
r 5
 
5.9%
i 5
 
5.9%
m 5
 
5.9%
n 4
 
4.7%
a 3
 
3.5%
Other values (8) 14
16.5%
Decimal Number
ValueCountFrequency (%)
1 165
53.2%
2 49
 
15.8%
3 36
 
11.6%
4 28
 
9.0%
0 13
 
4.2%
5 12
 
3.9%
7 2
 
0.6%
8 2
 
0.6%
9 2
 
0.6%
6 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 140
50.9%
, 128
46.5%
: 5
 
1.8%
* 1
 
0.4%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
707
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2047
54.2%
Common 1372
36.3%
Latin 359
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 241
11.8%
수 224
10.9%
측 222
10.8%
정 215
10.5%
도 191
9.3%
전 136
 
6.6%
위 105
 
5.1%
온 103
 
5.0%
대 73
 
3.6%
장 63
 
3.1%
Other values (84) 474
23.2%
Latin
ValueCountFrequency (%)
P 52
14.5%
E 46
12.8%
H 46
12.8%
M 23
 
6.4%
R 23
 
6.4%
T 22
 
6.1%
h 12
 
3.3%
p 12
 
3.3%
e 11
 
3.1%
C 9
 
2.5%
Other values (30) 103
28.7%
Common
ValueCountFrequency (%)
707
51.5%
1 165
 
12.0%
. 140
 
10.2%
, 128
 
9.3%
2 49
 
3.6%
3 36
 
2.6%
( 31
 
2.3%
) 31
 
2.3%
4 28
 
2.0%
- 18
 
1.3%
Other values (9) 39
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2047
54.2%
ASCII 1731
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
707
40.8%
1 165
 
9.5%
. 140
 
8.1%
, 128
 
7.4%
P 52
 
3.0%
2 49
 
2.8%
E 46
 
2.7%
H 46
 
2.7%
3 36
 
2.1%
( 31
 
1.8%
Other values (49) 331
19.1%
Hangul
ValueCountFrequency (%)
기 241
11.8%
수 224
10.9%
측 222
10.8%
정 215
10.5%
도 191
9.3%
전 136
 
6.6%
위 105
 
5.1%
온 103
 
5.0%
대 73
 
3.6%
장 63
 
3.1%
Other values (84) 474
23.2%

타기관이전여부
Categorical

Distinct3
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
0
89 
<NA>
32 
1
16 

Length

Max length4
Median length1
Mean length1.7007299
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 89
65.0%
<NA> 32
 
23.4%
1 16
 
11.7%

Length

2024-04-30T03:52:32.427479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:52:32.511174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 89
65.0%
na 32
 
23.4%
1 16
 
11.7%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)전문인력총수자본금시설장비타기관이전여부
03120000S001145310000074L002002-03-082023-04-203폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 서대문구 신촌동 134서울특별시 서대문구 연세로 50 (신촌동)<NA>연세대학교2023-04-20 17:34:38U2022-12-03 22:03:00.0<NA>194584.959249451381.585492<NA><NA><NA><NA>
13230000S001311110247782L002016-09-07<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 문정동 651-10 파트너스1 1003호서울특별시 송파구 법원로 92, 파트너스1 10층 1003호 (문정동)05855(주)골든엔지니어링2023-04-27 08:41:09U2022-12-03 22:09:00.0<NA><NA><NA><NA><NA><NA><NA>
23200000S001101710068062L002014-02-10<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 관악로 1, 서울대학교 (신림동)08826서울대학교 농생명과학대학 농생명과학공동기기원2023-05-08 11:08:40U2022-12-04 23:00:00.0<NA><NA><NA><NA><NA><NA><NA>
33180000S001101220021831L002017-11-022024-03-283폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동6가 86-3 해남빌딩서울특별시 영등포구 양평로28사길 29 (양평동6가)07201(재)한국환경수도연구원2024-04-05 14:36:32U2023-12-04 00:07:00.0<NA>190156.734738449086.219362<NA><NA><NA><NA>
43150000S001101111262289L001997-09-26<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 934-9<NA><NA>㈜한국개발엔지니어링2023-12-04 16:38:09U2022-11-02 00:06:00.0<NA><NA><NA><NA><NA><NA><NA>
53130000S001101112535536L0020041007200607133폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 공덕동 456번지 르네상스1908서울특별시 마포구 만리재로 14 (공덕동,르네상스1908)<NA>(주)삼호2007-11-06 16:52:25I2018-08-31 23:59:59.0<NA>195766.58807449083.30692340지하수위측정기1조, 수소이옹농도1조,수온전기전도도측정장비1조0
63160000S001101112151803L0020120308201512183폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 구로구 구로동 212-13번지 벽산디지털밸리3차 1201호<NA><NA>(주)웹솔루스2017-02-14 11:47:32I2018-08-31 23:59:59.0<NA>190528.450104442352.77036530지하수수위측정장비, 전기전도도측정기, pH 및 수온측정기0
73220000S001101110061666L002010-04-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 역삼동 832-40<NA><NA>주식회사 유신2024-04-23 13:57:59U2023-12-03 22:05:00.0<NA>202741.379034443413.449625<NA><NA><NA><NA>
83230000S001101110337174L001997-10-02<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 가락동 31-3 금아빌딩 3층서울특별시 송파구 양재대로66길 36, 금아빌딩 3층 (가락동)05704㈜한서엔지니어링2023-02-21 12:18:38U2022-12-01 22:03:00.0<NA>210962.2082444224.544921<NA><NA><NA><NA>
93230000S001101116256592L002018-05-08<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 가락동 137-5 한흥빌딩 702호서울특별시 송파구 동남로 159, 한흥빌딩 702호 (가락동)05826(주)지앤아이티글로벌2023-02-21 12:23:48U2022-12-01 22:03:00.0<NA>211239.753264443392.692518<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)전문인력총수자본금시설장비타기관이전여부
1273230000S001101110373912L0020170530<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 오금동 38-16번지서울특별시 송파구 중대로33길 18 (오금동)05660(주)동우티이씨2017-06-04 15:33:06I2018-08-31 23:59:59.0<NA>211416.100517444932.95821540수위측정기, 수질측정기, ORP수질측정기0
1283230000S001101112205494L0020000115200305073폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 가락동 148번지 2층호서울특별시 송파구 중대로16길 3, 2층호 (가락동)<NA>㈜성지지반기술2009-07-10 14:05:34I2018-08-31 23:59:59.0<NA>211032.312945443820.166245401. 수위측정기 1 2. 전기전도도측정기 1 3. 수소이온농도측정기 1 4. 수온측정기0
1293230000S001101112303850L0020120326201312263폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 송파구 오금동 81-15번지 삼보빌딩 4층서울특별시 송파구 중대로 296, 4층 (오금동, 삼보빌딩)<NA>(주)지오웍스2013-12-26 14:47:29I2018-08-31 23:59:59.0<NA>211671.206749444959.23486140<NA>0
1303220000S001101112037350L0020001014<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 중랑구 묵동 239-77 NIKE FASCIA서울특별시 강남구 영동대로106길 41 (삼성동)<NA>홍우기술산업㈜2022-08-12 11:25:42U2021-12-07 23:04:00.0<NA>206758.41039456472.21633<NA><NA><NA><NA>
1313000000S001101112153015L002024-01-22<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 종로구 계동 140-2 현대빌딩서울특별시 종로구 율곡로 75, 현대빌딩 (계동)03058현대엔지니어링(주)2024-01-22 09:31:30U2023-11-30 22:04:00.0<NA>198817.289035452901.786745<NA><NA><NA><NA>
1323240000S001101111802358L002009-07-062022-12-273폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>서울특별시 강동구 천호동 354-6서울특별시 강동구 올림픽로 675 (천호동)134-868(주)동광지오엔지니어링2023-07-19 14:00:16U2022-12-06 22:01:00.0<NA>210913.143235448848.0096<NA><NA><NA><NA>
1333050000S001101110331027L002021-06-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 답십리동 766 백석빌딩서울특별시 동대문구 한천로 103, 백석빌딩 2층 (답십리동)02610삼수개발㈜2023-07-27 13:19:07U2022-12-06 22:09:00.0<NA>205650.039133452050.921389<NA><NA><NA><NA>
1343030000S001101112462218L002022-03-15<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 성동구 성수동2가 280-21 성수동 우림 이비즈센터 502호서울특별시 성동구 광나루로6길 35, 성수동 우림 이비즈센터 502호 (성수동2가)04799(주)동해종합기술공사2023-08-16 09:44:08U2022-12-07 23:08:00.0<NA>205525.616971449394.284127<NA><NA><NA><NA>
1353220000S001101110037740L002011-04-06<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강남구 대치동 942-1<NA><NA>㈜도화엔지니어링2023-10-30 14:13:45U2022-11-01 00:01:00.0<NA>205010.852416444887.348385<NA><NA><NA><NA>
1363170000S001101114944222L002017-12-14<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 345-30 남성프라자서울특별시 금천구 디지털로 130, 남성프라자 10층 1002호 (가산동)08589주식회사 도진엔지니어링2024-02-27 09:46:11U2023-12-01 22:09:00.0<NA>189472.091899441483.675018<NA><NA><NA><NA>