Overview

Dataset statistics

Number of variables48
Number of observations242
Missing cells5000
Missing cells (%)43.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory97.7 KiB
Average record size in memory413.5 B

Variable types

Numeric15
DateTime4
Unsupported8
Categorical11
Text10

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),실험실면적,사업장구분명,영업소면적,위탁업체명,실험실지역코드,실험실우편번호,실험실산,실험실번지,실험실호,실험실통,실험실반,실험실특수주소,실험실특수주소동,실험실특수주소호,실험실도로명주소시군구코드,실험실도로명주소읍면동코드,실험실도로명주소읍면동구분,실험실도로명주소코드,실험실도로명특수주소,실험실도로명주소건물층구분,실험실도로명주소건물본번호,실험실도로명주소건물부번호,실험실도로명주소우편번호
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16129/S/1/datasetView.do

Alerts

소재지우편번호 is highly imbalanced (92.5%)Imbalance
영업소면적 is highly imbalanced (68.1%)Imbalance
인허가취소일자 has 242 (100.0%) missing valuesMissing
폐업일자 has 161 (66.5%) missing valuesMissing
휴업시작일자 has 242 (100.0%) missing valuesMissing
휴업종료일자 has 242 (100.0%) missing valuesMissing
재개업일자 has 242 (100.0%) missing valuesMissing
전화번호 has 21 (8.7%) missing valuesMissing
소재지면적 has 242 (100.0%) missing valuesMissing
지번주소 has 15 (6.2%) missing valuesMissing
도로명주소 has 8 (3.3%) missing valuesMissing
도로명우편번호 has 35 (14.5%) missing valuesMissing
업태구분명 has 224 (92.6%) missing valuesMissing
좌표정보(X) has 12 (5.0%) missing valuesMissing
좌표정보(Y) has 12 (5.0%) missing valuesMissing
실험실면적 has 198 (81.8%) missing valuesMissing
위탁업체명 has 242 (100.0%) missing valuesMissing
실험실지역코드 has 126 (52.1%) missing valuesMissing
실험실우편번호 has 201 (83.1%) missing valuesMissing
실험실번지 has 132 (54.5%) missing valuesMissing
실험실호 has 156 (64.5%) missing valuesMissing
실험실통 has 242 (100.0%) missing valuesMissing
실험실반 has 242 (100.0%) missing valuesMissing
실험실특수주소 has 185 (76.4%) missing valuesMissing
실험실특수주소동 has 240 (99.2%) missing valuesMissing
실험실특수주소호 has 226 (93.4%) missing valuesMissing
실험실도로명주소시군구코드 has 135 (55.8%) missing valuesMissing
실험실도로명주소읍면동코드 has 135 (55.8%) missing valuesMissing
실험실도로명주소코드 has 135 (55.8%) missing valuesMissing
실험실도로명특수주소 has 135 (55.8%) missing valuesMissing
실험실도로명주소건물본번호 has 135 (55.8%) missing valuesMissing
실험실도로명주소건물부번호 has 228 (94.2%) missing valuesMissing
실험실도로명주소우편번호 has 209 (86.4%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
위탁업체명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실통 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실반 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실면적 has 24 (9.9%) zerosZeros

Reproduction

Analysis started2024-04-29 18:53:28.549129
Analysis finished2024-04-29 18:53:29.671488
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct23
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3156900.8
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:29.732999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3030000
Q13132500
median3170000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)77500

Descriptive statistics

Standard deviation66910.965
Coefficient of variation (CV)0.021195143
Kurtosis-0.40566778
Mean3156900.8
Median Absolute Deviation (MAD)40000
Skewness-0.85336808
Sum7.6397 × 108
Variance4.4770773 × 109
MonotonicityNot monotonic
2024-04-30T03:53:29.832953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3170000 31
12.8%
3230000 30
12.4%
3160000 28
11.6%
3220000 24
9.9%
3180000 20
8.3%
3030000 17
 
7.0%
3210000 14
 
5.8%
3150000 13
 
5.4%
3050000 10
 
4.1%
3070000 8
 
3.3%
Other values (13) 47
19.4%
ValueCountFrequency (%)
3000000 4
 
1.7%
3010000 1
 
0.4%
3020000 2
 
0.8%
3030000 17
7.0%
3040000 3
 
1.2%
3050000 10
4.1%
3060000 4
 
1.7%
3070000 8
3.3%
3100000 4
 
1.7%
3110000 1
 
0.4%
ValueCountFrequency (%)
3240000 6
 
2.5%
3230000 30
12.4%
3220000 24
9.9%
3210000 14
5.8%
3200000 8
 
3.3%
3190000 3
 
1.2%
3180000 20
8.3%
3170000 31
12.8%
3160000 28
11.6%
3150000 13
5.4%

관리번호
Real number (ℝ)

UNIQUE 

Distinct242
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1569015 × 1017
Minimum3.0000007 × 1017
Maximum3.2400007 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:29.956075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000007 × 1017
5-th percentile3.0300007 × 1017
Q13.1325007 × 1017
median3.1700007 × 1017
Q33.2100007 × 1017
95-th percentile3.2300007 × 1017
Maximum3.2400007 × 1017
Range2.4 × 1016
Interquartile range (IQR)7.75 × 1015

Descriptive statistics

Standard deviation6.6910965 × 1015
Coefficient of variation (CV)0.021195139
Kurtosis-0.40566778
Mean3.1569015 × 1017
Median Absolute Deviation (MAD)4 × 1015
Skewness-0.85336808
Sum2.6100397 × 1018
Variance4.4770773 × 1031
MonotonicityNot monotonic
2024-04-30T03:53:30.089808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
322000066201800002 1
 
0.4%
303000066201500002 1
 
0.4%
318000066201200001 1
 
0.4%
318000066201200002 1
 
0.4%
318000066201400001 1
 
0.4%
318000066201500001 1
 
0.4%
318000066201600001 1
 
0.4%
318000066201700001 1
 
0.4%
318000066201000008 1
 
0.4%
319000066201400001 1
 
0.4%
Other values (232) 232
95.9%
ValueCountFrequency (%)
300000066201000001 1
0.4%
300000066201100001 1
0.4%
300000066201200001 1
0.4%
300000066202200001 1
0.4%
301000066201300001 1
0.4%
302000066202000001 1
0.4%
302000066202000002 1
0.4%
303000066201000001 1
0.4%
303000066201100001 1
0.4%
303000066201100002 1
0.4%
ValueCountFrequency (%)
324000066202200001 1
0.4%
324000066201500001 1
0.4%
324000066201200001 1
0.4%
324000066201100001 1
0.4%
324000066200900002 1
0.4%
324000066200900001 1
0.4%
323000066202300002 1
0.4%
323000066202300001 1
0.4%
323000066202200003 1
0.4%
323000066202200002 1
0.4%
Distinct223
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1999-08-09 00:00:00
Maximum2024-03-18 00:00:00
2024-04-30T03:53:30.201763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:53:30.317776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
1
132 
3
73 
4
21 
5
16 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 132
54.5%
3 73
30.2%
4 21
 
8.7%
5 16
 
6.6%

Length

2024-04-30T03:53:30.427078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:30.505401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 132
54.5%
3 73
30.2%
4 21
 
8.7%
5 16
 
6.6%

영업상태명
Categorical

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
영업/정상
132 
폐업
73 
취소/말소/만료/정지/중지
21 
제외/삭제/전출
16 

Length

Max length14
Median length5
Mean length5.0743802
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제외/삭제/전출
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 132
54.5%
폐업 73
30.2%
취소/말소/만료/정지/중지 21
 
8.7%
제외/삭제/전출 16
 
6.6%

Length

2024-04-30T03:53:30.610656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:30.695086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 132
54.5%
폐업 73
30.2%
취소/말소/만료/정지/중지 21
 
8.7%
제외/삭제/전출 16
 
6.6%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
BBBB
132 
2
73 
4
21 
5
16 

Length

Max length4
Median length4
Mean length2.6363636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd rowBBBB
3rd rowBBBB
4th rowBBBB
5th rowBBBB

Common Values

ValueCountFrequency (%)
BBBB 132
54.5%
2 73
30.2%
4 21
 
8.7%
5 16
 
6.6%

Length

2024-04-30T03:53:30.787269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:30.883986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 132
54.5%
2 73
30.2%
4 21
 
8.7%
5 16
 
6.6%
Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
영업
132 
폐업
73 
폐쇄
21 
제외사항
16 

Length

Max length4
Median length2
Mean length2.1322314
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 132
54.5%
폐업 73
30.2%
폐쇄 21
 
8.7%
제외사항 16
 
6.6%

Length

2024-04-30T03:53:30.984153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:31.084487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 132
54.5%
폐업 73
30.2%
폐쇄 21
 
8.7%
제외사항 16
 
6.6%

폐업일자
Date

MISSING 

Distinct72
Distinct (%)88.9%
Missing161
Missing (%)66.5%
Memory size2.0 KiB
Minimum2010-05-10 00:00:00
Maximum2023-12-11 00:00:00
2024-04-30T03:53:31.191937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:53:31.323678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

전화번호
Text

MISSING 

Distinct174
Distinct (%)78.7%
Missing21
Missing (%)8.7%
Memory size2.0 KiB
2024-04-30T03:53:31.557097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.9954751
Min length7

Characters and Unicode

Total characters2209
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)65.2%

Sample

1st row027402426
2nd row02-2065-0150
3rd row2679-0361
4th row02-849-5740
5th row21022672
ValueCountFrequency (%)
02-424-2007 5
 
2.3%
02-583-0203 5
 
2.3%
02-6952-7880 5
 
2.3%
025566929 4
 
1.8%
02-719-7452 3
 
1.4%
02-434-3214 3
 
1.4%
02-558-0459 3
 
1.4%
024537315 3
 
1.4%
422-6462 3
 
1.4%
07048701100 3
 
1.4%
Other values (164) 184
83.3%
2024-04-30T03:53:31.907817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 374
16.9%
0 372
16.8%
- 231
10.5%
5 194
8.8%
6 189
8.6%
9 157
7.1%
4 156
7.1%
1 149
 
6.7%
7 129
 
5.8%
8 129
 
5.8%
Other values (3) 129
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1973
89.3%
Dash Punctuation 231
 
10.5%
Close Punctuation 4
 
0.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 374
19.0%
0 372
18.9%
5 194
9.8%
6 189
9.6%
9 157
8.0%
4 156
7.9%
1 149
 
7.6%
7 129
 
6.5%
8 129
 
6.5%
3 124
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 231
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2209
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 374
16.9%
0 372
16.8%
- 231
10.5%
5 194
8.8%
6 189
8.6%
9 157
7.1%
4 156
7.1%
1 149
 
6.7%
7 129
 
5.8%
8 129
 
5.8%
Other values (3) 129
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2209
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 374
16.9%
0 372
16.8%
- 231
10.5%
5 194
8.8%
6 189
8.6%
9 157
7.1%
4 156
7.1%
1 149
 
6.7%
7 129
 
5.8%
8 129
 
5.8%
Other values (3) 129
 
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

소재지우편번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
237 
130878
 
1
130864
 
1
152843
 
1
153787
 
1

Length

Max length6
Median length4
Mean length4.0413223
Min length4

Unique

Unique5 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 237
97.9%
130878 1
 
0.4%
130864 1
 
0.4%
152843 1
 
0.4%
153787 1
 
0.4%
137707 1
 
0.4%

Length

2024-04-30T03:53:32.040030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:32.159244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 237
97.9%
130878 1
 
0.4%
130864 1
 
0.4%
152843 1
 
0.4%
153787 1
 
0.4%
137707 1
 
0.4%

지번주소
Text

MISSING 

Distinct186
Distinct (%)81.9%
Missing15
Missing (%)6.2%
Memory size2.0 KiB
2024-04-30T03:53:32.430167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length37
Mean length26.77533
Min length16

Characters and Unicode

Total characters6078
Distinct characters254
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

Unique155 ?
Unique (%)68.3%

Sample

1st row서울특별시 강남구 역삼동 662-7
2nd row서울특별시 구로구 구로동 611-26 오퍼스1 1025호
3rd row서울특별시 강서구 염창동 240-21 우림블루나인비즈니스센터 에이동 810호
4th row서울특별시 금천구 가산동 554-2
5th row서울특별시 금천구 가산동 459-28 한국생활환경시험연구원
ValueCountFrequency (%)
서울특별시 225
 
19.2%
금천구 31
 
2.7%
가산동 29
 
2.5%
송파구 29
 
2.5%
구로구 26
 
2.2%
구로동 23
 
2.0%
강남구 21
 
1.8%
영등포구 18
 
1.5%
성동구 14
 
1.2%
서초구 14
 
1.2%
Other values (434) 739
63.2%
2024-04-30T03:53:32.819241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1035
 
17.0%
278
 
4.6%
273
 
4.5%
272
 
4.5%
1 258
 
4.2%
240
 
3.9%
229
 
3.8%
226
 
3.7%
225
 
3.7%
2 207
 
3.4%
Other values (244) 2835
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3542
58.3%
Decimal Number 1260
 
20.7%
Space Separator 1035
 
17.0%
Dash Punctuation 177
 
2.9%
Uppercase Letter 33
 
0.5%
Lowercase Letter 12
 
0.2%
Other Punctuation 10
 
0.2%
Math Symbol 7
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
278
 
7.8%
273
 
7.7%
272
 
7.7%
240
 
6.8%
229
 
6.5%
226
 
6.4%
225
 
6.4%
74
 
2.1%
73
 
2.1%
56
 
1.6%
Other values (208) 1596
45.1%
Uppercase Letter
ValueCountFrequency (%)
B 7
21.2%
S 4
12.1%
K 4
12.1%
A 4
12.1%
V 3
9.1%
R 2
 
6.1%
T 2
 
6.1%
I 2
 
6.1%
E 1
 
3.0%
W 1
 
3.0%
Other values (3) 3
9.1%
Decimal Number
ValueCountFrequency (%)
1 258
20.5%
2 207
16.4%
0 127
10.1%
3 126
10.0%
5 106
8.4%
4 103
 
8.2%
6 96
 
7.6%
9 84
 
6.7%
8 77
 
6.1%
7 76
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
33.3%
t 2
16.7%
n 2
16.7%
r 2
16.7%
c 2
16.7%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
/ 1
 
10.0%
& 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1035
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 177
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3542
58.3%
Common 2491
41.0%
Latin 45
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
278
 
7.8%
273
 
7.7%
272
 
7.7%
240
 
6.8%
229
 
6.5%
226
 
6.4%
225
 
6.4%
74
 
2.1%
73
 
2.1%
56
 
1.6%
Other values (208) 1596
45.1%
Common
ValueCountFrequency (%)
1035
41.5%
1 258
 
10.4%
2 207
 
8.3%
- 177
 
7.1%
0 127
 
5.1%
3 126
 
5.1%
5 106
 
4.3%
4 103
 
4.1%
6 96
 
3.9%
9 84
 
3.4%
Other values (8) 172
 
6.9%
Latin
ValueCountFrequency (%)
B 7
15.6%
S 4
 
8.9%
K 4
 
8.9%
e 4
 
8.9%
A 4
 
8.9%
V 3
 
6.7%
t 2
 
4.4%
n 2
 
4.4%
R 2
 
4.4%
T 2
 
4.4%
Other values (8) 11
24.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3542
58.3%
ASCII 2536
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1035
40.8%
1 258
 
10.2%
2 207
 
8.2%
- 177
 
7.0%
0 127
 
5.0%
3 126
 
5.0%
5 106
 
4.2%
4 103
 
4.1%
6 96
 
3.8%
9 84
 
3.3%
Other values (26) 217
 
8.6%
Hangul
ValueCountFrequency (%)
278
 
7.8%
273
 
7.7%
272
 
7.7%
240
 
6.8%
229
 
6.5%
226
 
6.4%
225
 
6.4%
74
 
2.1%
73
 
2.1%
56
 
1.6%
Other values (208) 1596
45.1%

도로명주소
Text

MISSING 

Distinct197
Distinct (%)84.2%
Missing8
Missing (%)3.3%
Memory size2.0 KiB
2024-04-30T03:53:33.098189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length35.636752
Min length22

Characters and Unicode

Total characters8339
Distinct characters293
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

Unique167 ?
Unique (%)71.4%

Sample

1st row서울특별시 강남구 언주로 547, 13층 (역삼동)
2nd row서울특별시 구로구 구로중앙로 207, 오퍼스1 1025호 (구로동)
3rd row서울특별시 강서구 양천로 583, 우림블루나인비즈니스센터 에이동동 810호 (염창동)
4th row서울특별시 금천구 가산디지털2로 43-14, 329호 (가산동)
5th row서울특별시 금천구 가산디지털1로 199, 한국생활환경시험연구원 (가산동)
ValueCountFrequency (%)
서울특별시 232
 
15.2%
금천구 31
 
2.0%
송파구 30
 
2.0%
가산동 29
 
1.9%
구로구 26
 
1.7%
강남구 24
 
1.6%
구로동 23
 
1.5%
영등포구 20
 
1.3%
성동구 17
 
1.1%
가산디지털1로 17
 
1.1%
Other values (583) 1079
70.6%
2024-04-30T03:53:33.531944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1304
 
15.6%
1 337
 
4.0%
307
 
3.7%
289
 
3.5%
287
 
3.4%
282
 
3.4%
, 255
 
3.1%
251
 
3.0%
238
 
2.9%
( 235
 
2.8%
Other values (283) 4554
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4790
57.4%
Decimal Number 1409
 
16.9%
Space Separator 1304
 
15.6%
Other Punctuation 257
 
3.1%
Open Punctuation 235
 
2.8%
Close Punctuation 235
 
2.8%
Uppercase Letter 47
 
0.6%
Dash Punctuation 31
 
0.4%
Lowercase Letter 19
 
0.2%
Math Symbol 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
307
 
6.4%
289
 
6.0%
287
 
6.0%
282
 
5.9%
251
 
5.2%
238
 
5.0%
232
 
4.8%
232
 
4.8%
120
 
2.5%
106
 
2.2%
Other values (241) 2446
51.1%
Uppercase Letter
ValueCountFrequency (%)
A 8
17.0%
B 7
14.9%
K 5
10.6%
S 5
10.6%
V 4
8.5%
T 3
 
6.4%
D 3
 
6.4%
Y 2
 
4.3%
R 2
 
4.3%
I 2
 
4.3%
Other values (6) 6
12.8%
Decimal Number
ValueCountFrequency (%)
1 337
23.9%
2 228
16.2%
0 168
11.9%
3 145
10.3%
6 112
 
7.9%
5 110
 
7.8%
4 93
 
6.6%
7 81
 
5.7%
8 69
 
4.9%
9 66
 
4.7%
Lowercase Letter
ValueCountFrequency (%)
e 5
26.3%
t 3
15.8%
r 3
15.8%
b 2
 
10.5%
c 2
 
10.5%
n 2
 
10.5%
w 1
 
5.3%
o 1
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 255
99.2%
/ 1
 
0.4%
& 1
 
0.4%
Space Separator
ValueCountFrequency (%)
1304
100.0%
Open Punctuation
ValueCountFrequency (%)
( 235
100.0%
Close Punctuation
ValueCountFrequency (%)
) 235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4790
57.4%
Common 3483
41.8%
Latin 66
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
307
 
6.4%
289
 
6.0%
287
 
6.0%
282
 
5.9%
251
 
5.2%
238
 
5.0%
232
 
4.8%
232
 
4.8%
120
 
2.5%
106
 
2.2%
Other values (241) 2446
51.1%
Latin
ValueCountFrequency (%)
A 8
 
12.1%
B 7
 
10.6%
e 5
 
7.6%
K 5
 
7.6%
S 5
 
7.6%
V 4
 
6.1%
t 3
 
4.5%
T 3
 
4.5%
D 3
 
4.5%
r 3
 
4.5%
Other values (14) 20
30.3%
Common
ValueCountFrequency (%)
1304
37.4%
1 337
 
9.7%
, 255
 
7.3%
( 235
 
6.7%
) 235
 
6.7%
2 228
 
6.5%
0 168
 
4.8%
3 145
 
4.2%
6 112
 
3.2%
5 110
 
3.2%
Other values (8) 354
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4790
57.4%
ASCII 3549
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1304
36.7%
1 337
 
9.5%
, 255
 
7.2%
( 235
 
6.6%
) 235
 
6.6%
2 228
 
6.4%
0 168
 
4.7%
3 145
 
4.1%
6 112
 
3.2%
5 110
 
3.1%
Other values (32) 420
 
11.8%
Hangul
ValueCountFrequency (%)
307
 
6.4%
289
 
6.0%
287
 
6.0%
282
 
5.9%
251
 
5.2%
238
 
5.0%
232
 
4.8%
232
 
4.8%
120
 
2.5%
106
 
2.2%
Other values (241) 2446
51.1%

도로명우편번호
Text

MISSING 

Distinct149
Distinct (%)72.0%
Missing35
Missing (%)14.5%
Memory size2.0 KiB
2024-04-30T03:53:33.828809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4202899
Min length5

Characters and Unicode

Total characters1122
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

Unique115 ?
Unique (%)55.6%

Sample

1st row06138
2nd row08216
3rd row07547
4th row08588
5th row08503
ValueCountFrequency (%)
05680 9
 
4.3%
08732 7
 
3.4%
08591 5
 
2.4%
08382 4
 
1.9%
02262 3
 
1.4%
05836 3
 
1.4%
130846 3
 
1.4%
02832 3
 
1.4%
08590 3
 
1.4%
157779 3
 
1.4%
Other values (139) 164
79.2%
2024-04-30T03:53:34.236613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
19.3%
8 143
12.7%
5 132
11.8%
1 132
11.8%
7 112
10.0%
3 104
9.3%
2 95
8.5%
6 68
 
6.1%
4 61
 
5.4%
9 44
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1107
98.7%
Dash Punctuation 15
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
19.5%
8 143
12.9%
5 132
11.9%
1 132
11.9%
7 112
10.1%
3 104
9.4%
2 95
8.6%
6 68
 
6.1%
4 61
 
5.5%
9 44
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1122
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
19.3%
8 143
12.7%
5 132
11.8%
1 132
11.8%
7 112
10.0%
3 104
9.3%
2 95
8.5%
6 68
 
6.1%
4 61
 
5.4%
9 44
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1122
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
19.3%
8 143
12.7%
5 132
11.8%
1 132
11.8%
7 112
10.0%
3 104
9.3%
2 95
8.5%
6 68
 
6.1%
4 61
 
5.4%
9 44
 
3.9%
Distinct161
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-30T03:53:34.446285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length17
Mean length9.7727273
Min length4

Characters and Unicode

Total characters2365
Distinct characters218
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)46.7%

Sample

1st row삼환기업(주)
2nd row(주)대원이씨티
3rd row주식회사 한국쏠텍
4th row(주)한경이테크
5th row(재)한국건설생활환경시험연구원
ValueCountFrequency (%)
주식회사 20
 
7.1%
주)푸른환경산업연구소 7
 
2.5%
상록환경위생(주 5
 
1.8%
주)청명기연환경 5
 
1.8%
주)ehs기술연구소 4
 
1.4%
환경보전협회 4
 
1.4%
노이즈엔지니어링(주 4
 
1.4%
미령환경개발(주 4
 
1.4%
청우환경 4
 
1.4%
주)한국건설환경 4
 
1.4%
Other values (165) 221
78.4%
2024-04-30T03:53:34.777489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
 
7.9%
( 172
 
7.3%
) 171
 
7.2%
100
 
4.2%
94
 
4.0%
71
 
3.0%
58
 
2.5%
54
 
2.3%
48
 
2.0%
46
 
1.9%
Other values (208) 1365
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1952
82.5%
Open Punctuation 172
 
7.3%
Close Punctuation 171
 
7.2%
Space Separator 40
 
1.7%
Uppercase Letter 27
 
1.1%
Other Symbol 1
 
< 0.1%
Connector Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
186
 
9.5%
100
 
5.1%
94
 
4.8%
71
 
3.6%
58
 
3.0%
54
 
2.8%
48
 
2.5%
46
 
2.4%
43
 
2.2%
42
 
2.2%
Other values (188) 1210
62.0%
Uppercase Letter
ValueCountFrequency (%)
E 4
14.8%
H 4
14.8%
S 4
14.8%
A 2
7.4%
J 2
7.4%
O 2
7.4%
I 2
7.4%
T 1
 
3.7%
F 1
 
3.7%
B 1
 
3.7%
Other values (4) 4
14.8%
Open Punctuation
ValueCountFrequency (%)
( 172
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1953
82.6%
Common 385
 
16.3%
Latin 27
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
186
 
9.5%
100
 
5.1%
94
 
4.8%
71
 
3.6%
58
 
3.0%
54
 
2.8%
48
 
2.5%
46
 
2.4%
43
 
2.2%
42
 
2.2%
Other values (189) 1211
62.0%
Latin
ValueCountFrequency (%)
E 4
14.8%
H 4
14.8%
S 4
14.8%
A 2
7.4%
J 2
7.4%
O 2
7.4%
I 2
7.4%
T 1
 
3.7%
F 1
 
3.7%
B 1
 
3.7%
Other values (4) 4
14.8%
Common
ValueCountFrequency (%)
( 172
44.7%
) 171
44.4%
40
 
10.4%
_ 1
 
0.3%
- 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1952
82.5%
ASCII 412
 
17.4%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
186
 
9.5%
100
 
5.1%
94
 
4.8%
71
 
3.6%
58
 
3.0%
54
 
2.8%
48
 
2.5%
46
 
2.4%
43
 
2.2%
42
 
2.2%
Other values (188) 1210
62.0%
ASCII
ValueCountFrequency (%)
( 172
41.7%
) 171
41.5%
40
 
9.7%
E 4
 
1.0%
H 4
 
1.0%
S 4
 
1.0%
A 2
 
0.5%
J 2
 
0.5%
O 2
 
0.5%
I 2
 
0.5%
Other values (9) 9
 
2.2%
None
ValueCountFrequency (%)
1
100.0%

최종수정일자
Date

UNIQUE 

Distinct242
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2010-02-19 08:42:49
Maximum2024-04-23 16:22:22
2024-04-30T03:53:34.898298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:53:35.009310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
U
149 
I
93 

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 (%)
U 149
61.6%
I 93
38.4%

Length

2024-04-30T03:53:35.114016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:35.370335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 149
61.6%
i 93
38.4%
Distinct124
Distinct (%)51.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2019-03-30 02:20:09
Maximum2023-12-04 00:07:00
2024-04-30T03:53:35.469727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T03:53:35.676337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

MISSING 

Distinct12
Distinct (%)66.7%
Missing224
Missing (%)92.6%
Memory size2.0 KiB
2024-04-30T03:53:35.872384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length28
Mean length17.166667
Min length6

Characters and Unicode

Total characters309
Distinct characters56
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)50.0%

Sample

1st row종합 건설업
2nd row건축설계 및 관련 서비스업
3rd row환경컨설팅 및 관련 엔지니어링 서비스업
4th row기타 과학기술 서비스업
5th row전문, 과학 및 기술 서비스업
ValueCountFrequency (%)
13
15.5%
서비스업 11
13.1%
관련 7
 
8.3%
엔지니어링 6
 
7.1%
환경컨설팅 4
 
4.8%
기술 4
 
4.8%
전문 3
 
3.6%
과학 3
 
3.6%
시험 3
 
3.6%
기타 3
 
3.6%
Other values (20) 27
32.1%
2024-04-30T03:53:36.168115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
21.4%
18
 
5.8%
14
 
4.5%
13
 
4.2%
12
 
3.9%
12
 
3.9%
12
 
3.9%
, 10
 
3.2%
8
 
2.6%
7
 
2.3%
Other values (46) 137
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 232
75.1%
Space Separator 66
 
21.4%
Other Punctuation 11
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
7.8%
14
 
6.0%
13
 
5.6%
12
 
5.2%
12
 
5.2%
12
 
5.2%
8
 
3.4%
7
 
3.0%
7
 
3.0%
6
 
2.6%
Other values (43) 123
53.0%
Other Punctuation
ValueCountFrequency (%)
, 10
90.9%
; 1
 
9.1%
Space Separator
ValueCountFrequency (%)
66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 232
75.1%
Common 77
 
24.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
7.8%
14
 
6.0%
13
 
5.6%
12
 
5.2%
12
 
5.2%
12
 
5.2%
8
 
3.4%
7
 
3.0%
7
 
3.0%
6
 
2.6%
Other values (43) 123
53.0%
Common
ValueCountFrequency (%)
66
85.7%
, 10
 
13.0%
; 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 232
75.1%
ASCII 77
 
24.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
85.7%
, 10
 
13.0%
; 1
 
1.3%
Hangul
ValueCountFrequency (%)
18
 
7.8%
14
 
6.0%
13
 
5.6%
12
 
5.2%
12
 
5.2%
12
 
5.2%
8
 
3.4%
7
 
3.0%
7
 
3.0%
6
 
2.6%
Other values (43) 123
53.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct159
Distinct (%)69.1%
Missing12
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean198099.51
Minimum185341.42
Maximum227284.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:36.292898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185341.42
5-th percentile187952.56
Q1190172
median198124.89
Q3204796.98
95-th percentile210640.12
Maximum227284.11
Range41942.683
Interquartile range (IQR)14624.989

Descriptive statistics

Standard deviation8273.6899
Coefficient of variation (CV)0.041765321
Kurtosis-0.89247651
Mean198099.51
Median Absolute Deviation (MAD)7596.4402
Skewness0.33388107
Sum45562888
Variance68453944
MonotonicityNot monotonic
2024-04-30T03:53:36.431222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
208783.783122312 7
 
2.9%
196293.25961572 7
 
2.9%
187952.560027898 5
 
2.1%
212784.616145219 4
 
1.7%
190021.956927088 4
 
1.7%
189841.076534283 4
 
1.7%
203611.969197773 4
 
1.7%
190156.73473829 4
 
1.7%
204835.535359114 3
 
1.2%
208827.801295005 3
 
1.2%
Other values (149) 185
76.4%
(Missing) 12
 
5.0%
ValueCountFrequency (%)
185341.423784971 1
 
0.4%
185588.112351415 1
 
0.4%
185959.79896256 1
 
0.4%
186398.338369074 1
 
0.4%
186501.110937132 1
 
0.4%
187471.842860979 1
 
0.4%
187561.265938558 3
1.2%
187831.720345753 1
 
0.4%
187860.181669909 1
 
0.4%
187952.560027898 5
2.1%
ValueCountFrequency (%)
227284.107082183 1
 
0.4%
215159.121184272 1
 
0.4%
212784.616145219 4
1.7%
212403.643733203 1
 
0.4%
212168.824948649 1
 
0.4%
211970.111597199 1
 
0.4%
211310.447242137 1
 
0.4%
210986.460698452 1
 
0.4%
210970.75707265 1
 
0.4%
210236.0 2
0.8%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct158
Distinct (%)68.7%
Missing12
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean446329.41
Minimum439023.17
Maximum479375.49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:36.547845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile441127.32
Q1442598.14
median444788.35
Q3449476.39
95-th percentile454681.54
Maximum479375.49
Range40352.327
Interquartile range (IQR)6878.2426

Descriptive statistics

Standard deviation4973.6177
Coefficient of variation (CV)0.011143379
Kurtosis7.9071811
Mean446329.41
Median Absolute Deviation (MAD)2720.4478
Skewness1.9192531
Sum1.0265576 × 108
Variance24736873
MonotonicityNot monotonic
2024-04-30T03:53:36.674050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442941.188639656 7
 
2.9%
444488.498088996 7
 
2.9%
450562.020225978 5
 
2.1%
441127.322443807 4
 
1.7%
444002.309741999 4
 
1.7%
440609.209534256 4
 
1.7%
444102.40501477 4
 
1.7%
449086.219361712 4
 
1.7%
449523.964844279 3
 
1.2%
448752.95835214 3
 
1.2%
Other values (148) 185
76.4%
(Missing) 12
 
5.0%
ValueCountFrequency (%)
439023.167125842 1
 
0.4%
440363.954453659 1
 
0.4%
440521.85524888 1
 
0.4%
440523.497478209 1
 
0.4%
440569.770968036 1
 
0.4%
440609.209534256 4
1.7%
440764.426277932 1
 
0.4%
441036.663114495 1
 
0.4%
441127.322443807 4
1.7%
441142.645065053 2
0.8%
ValueCountFrequency (%)
479375.49456073 1
0.4%
461407.049044413 1
0.4%
461040.739754909 1
0.4%
458960.471391303 1
0.4%
458732.958771992 1
0.4%
457943.941481997 1
0.4%
456761.921129526 2
0.8%
456546.901101372 1
0.4%
455417.925754463 2
0.8%
454934.047367752 1
0.4%

실험실면적
Real number (ℝ)

MISSING  ZEROS 

Distinct19
Distinct (%)43.2%
Missing198
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean2714.5455
Minimum0
Maximum90132
Zeros24
Zeros (%)9.9%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:36.780929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q391.75
95-th percentile397.1
Maximum90132
Range90132
Interquartile range (IQR)91.75

Descriptive statistics

Standard deviation14082.182
Coefficient of variation (CV)5.1876758
Kurtosis36.723237
Mean2714.5455
Median Absolute Deviation (MAD)0
Skewness5.9455207
Sum119440
Variance1.9830785 × 108
MonotonicityNot monotonic
2024-04-30T03:53:36.869367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 24
 
9.9%
47 2
 
0.8%
89 2
 
0.8%
5 1
 
0.4%
90132 1
 
0.4%
70 1
 
0.4%
200 1
 
0.4%
118 1
 
0.4%
221 1
 
0.4%
410 1
 
0.4%
Other values (9) 9
 
3.7%
(Missing) 198
81.8%
ValueCountFrequency (%)
0 24
9.9%
1 1
 
0.4%
5 1
 
0.4%
21 1
 
0.4%
47 2
 
0.8%
70 1
 
0.4%
75 1
 
0.4%
89 2
 
0.8%
100 1
 
0.4%
118 1
 
0.4%
ValueCountFrequency (%)
90132 1
0.4%
26966 1
0.4%
410 1
0.4%
324 1
0.4%
261 1
0.4%
221 1
0.4%
200 1
0.4%
134 1
0.4%
130 1
0.4%
118 1
0.4%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
121 
측정대행업
121 

Length

Max length5
Median length4.5
Mean length4.5
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 121
50.0%
측정대행업 121
50.0%

Length

2024-04-30T03:53:36.976133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:37.062060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 121
50.0%
측정대행업 121
50.0%

영업소면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
228 
0
 
14

Length

Max length4
Median length4
Mean length3.8264463
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 (%)
<NA> 228
94.2%
0 14
 
5.8%

Length

2024-04-30T03:53:37.154324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:37.228256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 228
94.2%
0 14
 
5.8%

위탁업체명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

실험실지역코드
Real number (ℝ)

MISSING 

Distinct54
Distinct (%)46.6%
Missing126
Missing (%)52.1%
Infinite0
Infinite (%)0.0%
Mean1.1515496 × 109
Minimum1.1110114 × 109
Maximum1.1740109 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:37.324076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110114 × 109
5-th percentile1.1200115 × 109
Q11.1410114 × 109
median1.1545101 × 109
Q31.1680101 × 109
95-th percentile1.1710114 × 109
Maximum1.1740109 × 109
Range62999500
Interquartile range (IQR)26998750

Descriptive statistics

Standard deviation18138802
Coefficient of variation (CV)0.015751646
Kurtosis-0.61649957
Mean1.1515496 × 109
Median Absolute Deviation (MAD)13500000
Skewness-0.75612347
Sum1.3357976 × 1011
Variance3.2901613 × 1014
MonotonicityNot monotonic
2024-04-30T03:53:37.446196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1153010200 10
 
4.1%
1168010100 9
 
3.7%
1154510100 7
 
2.9%
1171010500 5
 
2.1%
1150010100 4
 
1.7%
1171011400 4
 
1.7%
1129010700 3
 
1.2%
1120011500 3
 
1.2%
1165010100 3
 
1.2%
1165010800 3
 
1.2%
Other values (44) 65
26.9%
(Missing) 126
52.1%
ValueCountFrequency (%)
1111011400 1
 
0.4%
1111013100 2
0.8%
1111013200 1
 
0.4%
1117012000 1
 
0.4%
1120011400 1
 
0.4%
1120011500 3
1.2%
1121510300 1
 
0.4%
1121510500 2
0.8%
1123010300 1
 
0.4%
1123010500 2
0.8%
ValueCountFrequency (%)
1174010900 2
 
0.8%
1174010700 2
 
0.8%
1171011400 4
1.7%
1171011100 1
 
0.4%
1171010900 2
 
0.8%
1171010800 1
 
0.4%
1171010500 5
2.1%
1168011800 2
 
0.8%
1168011400 1
 
0.4%
1168010800 2
 
0.8%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct36
Distinct (%)87.8%
Missing201
Missing (%)83.1%
Infinite0
Infinite (%)0.0%
Mean138822.59
Minimum110053
Maximum158094
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:37.554525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110053
5-th percentile110380
Q1133827
median136791
Q3150101
95-th percentile157040
Maximum158094
Range48041
Interquartile range (IQR)16274

Descriptive statistics

Standard deviation13017.956
Coefficient of variation (CV)0.093774051
Kurtosis-0.18348826
Mean138822.59
Median Absolute Deviation (MAD)7083
Skewness-0.51159197
Sum5691726
Variance1.6946718 × 108
MonotonicityNot monotonic
2024-04-30T03:53:37.662078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
153803 3
 
1.2%
150093 2
 
0.8%
152053 2
 
0.8%
110380 2
 
0.8%
143874 1
 
0.4%
153802 1
 
0.4%
134861 1
 
0.4%
134877 1
 
0.4%
138190 1
 
0.4%
138843 1
 
0.4%
Other values (26) 26
 
10.7%
(Missing) 201
83.1%
ValueCountFrequency (%)
110053 1
0.4%
110380 2
0.8%
120749 1
0.4%
121160 1
0.4%
121828 1
0.4%
130743 1
0.4%
130805 1
0.4%
130862 1
0.4%
130878 1
0.4%
133827 1
0.4%
ValueCountFrequency (%)
158094 1
 
0.4%
157200 1
 
0.4%
157040 1
 
0.4%
153803 3
1.2%
153802 1
 
0.4%
152053 2
0.8%
152051 1
 
0.4%
150101 1
 
0.4%
150093 2
0.8%
150091 1
 
0.4%

실험실산
Categorical

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
126 
1
115 
2
 
1

Length

Max length4
Median length4
Mean length2.5619835
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 126
52.1%
1 115
47.5%
2 1
 
0.4%

Length

2024-04-30T03:53:37.764201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:37.846982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 126
52.1%
1 115
47.5%
2 1
 
0.4%

실험실번지
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)68.2%
Missing132
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean415.23636
Minimum1
Maximum1729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:37.951838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21
Q1134.25
median257
Q3642.75
95-th percentile1487.55
Maximum1729
Range1728
Interquartile range (IQR)508.5

Descriptive statistics

Standard deviation413.2642
Coefficient of variation (CV)0.99525051
Kurtosis2.5370418
Mean415.23636
Median Absolute Deviation (MAD)202
Skewness1.6513395
Sum45676
Variance170787.3
MonotonicityNot monotonic
2024-04-30T03:53:38.069591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
235 4
 
1.7%
222 4
 
1.7%
39 4
 
1.7%
1 3
 
1.2%
33 3
 
1.2%
1729 3
 
1.2%
371 3
 
1.2%
240 3
 
1.2%
212 3
 
1.2%
260 3
 
1.2%
Other values (65) 77
31.8%
(Missing) 132
54.5%
ValueCountFrequency (%)
1 3
1.2%
14 1
 
0.4%
16 1
 
0.4%
21 2
0.8%
23 1
 
0.4%
31 1
 
0.4%
33 3
1.2%
39 4
1.7%
55 2
0.8%
65 1
 
0.4%
ValueCountFrequency (%)
1729 3
1.2%
1598 2
0.8%
1488 1
 
0.4%
1487 1
 
0.4%
1230 1
 
0.4%
942 1
 
0.4%
938 1
 
0.4%
892 1
 
0.4%
873 2
0.8%
790 1
 
0.4%

실험실호
Real number (ℝ)

MISSING 

Distinct31
Distinct (%)36.0%
Missing156
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean22.232558
Minimum1
Maximum208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:38.191233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median9.5
Q320
95-th percentile74.25
Maximum208
Range207
Interquartile range (IQR)17

Descriptive statistics

Standard deviation40.264909
Coefficient of variation (CV)1.8110786
Kurtosis13.185759
Mean22.232558
Median Absolute Deviation (MAD)7.5
Skewness3.5793887
Sum1912
Variance1621.2629
MonotonicityNot monotonic
2024-04-30T03:53:38.297125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 10
 
4.1%
3 7
 
2.9%
13 6
 
2.5%
2 6
 
2.5%
8 6
 
2.5%
20 5
 
2.1%
4 4
 
1.7%
7 4
 
1.7%
21 4
 
1.7%
10 4
 
1.7%
Other values (21) 30
 
12.4%
(Missing) 156
64.5%
ValueCountFrequency (%)
1 10
4.1%
2 6
2.5%
3 7
2.9%
4 4
 
1.7%
5 2
 
0.8%
6 2
 
0.8%
7 4
 
1.7%
8 6
2.5%
9 2
 
0.8%
10 4
 
1.7%
ValueCountFrequency (%)
208 2
0.8%
187 1
0.4%
148 1
0.4%
77 1
0.4%
66 1
0.4%
64 1
0.4%
52 1
0.4%
50 2
0.8%
43 1
0.4%
39 1
0.4%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing242
Missing (%)100.0%
Memory size2.3 KiB

실험실특수주소
Text

MISSING 

Distinct53
Distinct (%)93.0%
Missing185
Missing (%)76.4%
Memory size2.0 KiB
2024-04-30T03:53:38.527137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.5789474
Min length2

Characters and Unicode

Total characters489
Distinct characters141
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

Unique50 ?
Unique (%)87.7%

Sample

1st row서라벌빌딩 302호
2nd row드림트리빌딩
3rd row삼환빌딩 별관601
4th row도원동삼성래미안
5th row협성빌딩 602
ValueCountFrequency (%)
드림트리빌딩 3
 
3.3%
그린빌딩 3
 
3.3%
2층 2
 
2.2%
b-911 2
 
2.2%
우림블루나인 2
 
2.2%
센터플러스 2
 
2.2%
701호 2
 
2.2%
973ab 2
 
2.2%
벤처타운 2
 
2.2%
3층 2
 
2.2%
Other values (67) 69
75.8%
2024-04-30T03:53:38.874393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
7.0%
24
 
4.9%
23
 
4.7%
15
 
3.1%
1 15
 
3.1%
0 14
 
2.9%
3 14
 
2.9%
2 13
 
2.7%
11
 
2.2%
10
 
2.0%
Other values (131) 316
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
71.2%
Decimal Number 85
 
17.4%
Space Separator 34
 
7.0%
Uppercase Letter 15
 
3.1%
Dash Punctuation 3
 
0.6%
Math Symbol 1
 
0.2%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
24
 
6.9%
23
 
6.6%
15
 
4.3%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
6
 
1.7%
Other values (105) 224
64.4%
Decimal Number
ValueCountFrequency (%)
1 15
17.6%
0 14
16.5%
3 14
16.5%
2 13
15.3%
6 6
 
7.1%
9 6
 
7.1%
7 6
 
7.1%
4 6
 
7.1%
5 4
 
4.7%
8 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
26.7%
A 2
13.3%
T 2
13.3%
R 1
 
6.7%
E 1
 
6.7%
W 1
 
6.7%
O 1
 
6.7%
V 1
 
6.7%
K 1
 
6.7%
S 1
 
6.7%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 348
71.2%
Common 125
 
25.6%
Latin 16
 
3.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
24
 
6.9%
23
 
6.6%
15
 
4.3%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
6
 
1.7%
Other values (105) 224
64.4%
Common
ValueCountFrequency (%)
34
27.2%
1 15
12.0%
0 14
11.2%
3 14
11.2%
2 13
 
10.4%
6 6
 
4.8%
9 6
 
4.8%
7 6
 
4.8%
4 6
 
4.8%
5 4
 
3.2%
Other values (5) 7
 
5.6%
Latin
ValueCountFrequency (%)
B 4
25.0%
A 2
12.5%
T 2
12.5%
R 1
 
6.2%
E 1
 
6.2%
W 1
 
6.2%
O 1
 
6.2%
V 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
71.2%
ASCII 141
28.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
24.1%
1 15
10.6%
0 14
9.9%
3 14
9.9%
2 13
 
9.2%
6 6
 
4.3%
9 6
 
4.3%
7 6
 
4.3%
4 6
 
4.3%
B 4
 
2.8%
Other values (16) 23
16.3%
Hangul
ValueCountFrequency (%)
24
 
6.9%
23
 
6.6%
15
 
4.3%
11
 
3.2%
10
 
2.9%
9
 
2.6%
9
 
2.6%
9
 
2.6%
8
 
2.3%
6
 
1.7%
Other values (105) 224
64.4%
Distinct2
Distinct (%)100.0%
Missing240
Missing (%)99.2%
Memory size2.0 KiB
2024-04-30T03:53:39.016068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4.5
Mean length4.5
Min length1

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row제2창업보육센터
2nd rowB
ValueCountFrequency (%)
제2창업보육센터 1
50.0%
b 1
50.0%
2024-04-30T03:53:39.251300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1
11.1%
2 1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
1
11.1%
B 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
77.8%
Decimal Number 1
 
11.1%
Uppercase Letter 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
77.8%
Common 1
 
11.1%
Latin 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Common
ValueCountFrequency (%)
2 1
100.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
77.8%
ASCII 2
 
22.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
ASCII
ValueCountFrequency (%)
2 1
50.0%
B 1
50.0%
Distinct13
Distinct (%)81.2%
Missing226
Missing (%)93.4%
Memory size2.0 KiB
2024-04-30T03:53:39.390798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.5
Min length3

Characters and Unicode

Total characters56
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

Unique10 ?
Unique (%)62.5%

Sample

1st row201
2nd row901
3rd row230
4th row703-2
5th row802
ValueCountFrequency (%)
201 2
12.5%
1105 2
12.5%
216 2
12.5%
901 1
 
6.2%
230 1
 
6.2%
703-2 1
 
6.2%
802 1
 
6.2%
706-2 1
 
6.2%
1003 1
 
6.2%
916 1
 
6.2%
Other values (3) 3
18.8%
2024-04-30T03:53:39.666879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
25.0%
1 11
19.6%
2 9
16.1%
5 5
 
8.9%
6 4
 
7.1%
3 4
 
7.1%
9 2
 
3.6%
7 2
 
3.6%
- 2
 
3.6%
8 2
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
96.4%
Dash Punctuation 2
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
25.9%
1 11
20.4%
2 9
16.7%
5 5
 
9.3%
6 4
 
7.4%
3 4
 
7.4%
9 2
 
3.7%
7 2
 
3.7%
8 2
 
3.7%
4 1
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
25.0%
1 11
19.6%
2 9
16.1%
5 5
 
8.9%
6 4
 
7.1%
3 4
 
7.1%
9 2
 
3.6%
7 2
 
3.6%
- 2
 
3.6%
8 2
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
25.0%
1 11
19.6%
2 9
16.1%
5 5
 
8.9%
6 4
 
7.1%
3 4
 
7.1%
9 2
 
3.6%
7 2
 
3.6%
- 2
 
3.6%
8 2
 
3.6%

실험실도로명주소시군구코드
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)18.7%
Missing135
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean11524.252
Minimum11110
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:39.779950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11200
Q111455
median11560
Q311680
95-th percentile11710
Maximum11740
Range630
Interquartile range (IQR)225

Descriptive statistics

Standard deviation179.71256
Coefficient of variation (CV)0.015594293
Kurtosis-0.48469664
Mean11524.252
Median Absolute Deviation (MAD)120
Skewness-0.85810917
Sum1233095
Variance32296.606
MonotonicityNot monotonic
2024-04-30T03:53:39.871020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
11680 19
 
7.9%
11710 12
 
5.0%
11560 11
 
4.5%
11530 9
 
3.7%
11545 8
 
3.3%
11650 7
 
2.9%
11290 6
 
2.5%
11500 5
 
2.1%
11200 5
 
2.1%
11230 4
 
1.7%
Other values (10) 21
 
8.7%
(Missing) 135
55.8%
ValueCountFrequency (%)
11110 3
1.2%
11170 1
 
0.4%
11200 5
2.1%
11215 3
1.2%
11230 4
1.7%
11290 6
2.5%
11350 3
1.2%
11410 1
 
0.4%
11440 1
 
0.4%
11470 2
 
0.8%
ValueCountFrequency (%)
11740 3
 
1.2%
11710 12
5.0%
11680 19
7.9%
11650 7
 
2.9%
11620 3
 
1.2%
11590 1
 
0.4%
11560 11
4.5%
11545 8
3.3%
11530 9
3.7%
11500 5
 
2.1%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct50
Distinct (%)46.7%
Missing135
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean1.1524361 × 109
Minimum1.1110114 × 109
Maximum1.1740109 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:39.988115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110114 × 109
5-th percentile1.1200115 × 109
Q11.145511 × 109
median1.1560119 × 109
Q31.1680101 × 109
95-th percentile1.1710114 × 109
Maximum1.1740109 × 109
Range62999500
Interquartile range (IQR)22499050

Descriptive statistics

Standard deviation17970996
Coefficient of variation (CV)0.01559392
Kurtosis-0.48475755
Mean1.1524361 × 109
Median Absolute Deviation (MAD)11998200
Skewness-0.85808665
Sum1.2331066 × 1011
Variance3.2295668 × 1014
MonotonicityNot monotonic
2024-04-30T03:53:40.101099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1168010100 11
 
4.5%
1153010200 8
 
3.3%
1154510100 7
 
2.9%
1171010500 5
 
2.1%
1171011400 4
 
1.7%
1120011500 4
 
1.7%
1150010100 3
 
1.2%
1156012900 3
 
1.2%
1162010100 3
 
1.2%
1165010100 3
 
1.2%
Other values (40) 56
23.1%
(Missing) 135
55.8%
ValueCountFrequency (%)
1111011400 1
 
0.4%
1111013100 1
 
0.4%
1111013200 1
 
0.4%
1117012000 1
 
0.4%
1120011400 1
 
0.4%
1120011500 4
1.7%
1121510300 1
 
0.4%
1121510500 2
0.8%
1123010400 1
 
0.4%
1123010500 1
 
0.4%
ValueCountFrequency (%)
1174010900 1
 
0.4%
1174010700 2
 
0.8%
1171011400 4
1.7%
1171011100 1
 
0.4%
1171010800 2
 
0.8%
1171010500 5
2.1%
1168011800 2
 
0.8%
1168011400 1
 
0.4%
1168010800 2
 
0.8%
1168010600 1
 
0.4%
Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
135 
1
107 

Length

Max length4
Median length4
Mean length2.6735537
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 (%)
<NA> 135
55.8%
1 107
44.2%

Length

2024-04-30T03:53:40.412065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:40.496671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 135
55.8%
1 107
44.2%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)65.4%
Missing135
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean3552194.4
Minimum2000003
Maximum4853405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:40.598400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000003
5-th percentile2030605.9
Q13107003
median3124003
Q34154625.5
95-th percentile4169186
Maximum4853405
Range2853402
Interquartile range (IQR)1047622.5

Descriptive statistics

Standard deviation667777.76
Coefficient of variation (CV)0.18799021
Kurtosis-0.51321634
Mean3552194.4
Median Absolute Deviation (MAD)1006165
Skewness-0.54251835
Sum3.800848 × 108
Variance4.4592713 × 1011
MonotonicityNot monotonic
2024-04-30T03:53:40.711899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3117001 5
 
2.1%
3123004 4
 
1.7%
4166644 4
 
1.7%
4160731 3
 
1.2%
3107003 3
 
1.2%
2000003 3
 
1.2%
2000008 3
 
1.2%
4148327 3
 
1.2%
4169186 3
 
1.2%
3115008 3
 
1.2%
Other values (60) 73
30.2%
(Missing) 135
55.8%
ValueCountFrequency (%)
2000003 3
1.2%
2000008 3
1.2%
2102001 1
 
0.4%
3000026 2
0.8%
3000027 1
 
0.4%
3000028 1
 
0.4%
3005018 1
 
0.4%
3005024 1
 
0.4%
3005047 1
 
0.4%
3005050 1
 
0.4%
ValueCountFrequency (%)
4853405 1
 
0.4%
4172024 1
 
0.4%
4169380 1
 
0.4%
4169244 2
0.8%
4169186 3
1.2%
4166761 1
 
0.4%
4166644 4
1.7%
4166618 1
 
0.4%
4166573 1
 
0.4%
4166557 1
 
0.4%
Distinct87
Distinct (%)81.3%
Missing135
Missing (%)55.8%
Memory size2.0 KiB
2024-04-30T03:53:40.942763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length11.794393
Min length5

Characters and Unicode

Total characters1262
Distinct characters177
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

Unique73 ?
Unique (%)68.2%

Sample

1st row(내자동, 서라벌빌딩 302호)
2nd row드림트리빌딩 (동소문동4가)
3rd row(구로동)
4th row(당산동1가)
5th row(운니동)
ValueCountFrequency (%)
역삼동 11
 
5.4%
구로동 8
 
3.9%
2층 6
 
2.9%
석촌동 5
 
2.4%
3층 4
 
2.0%
성수동2가 4
 
2.0%
마천동 4
 
2.0%
염창동 3
 
1.5%
봉천동 3
 
1.5%
5층 3
 
1.5%
Other values (124) 154
75.1%
2024-04-30T03:53:41.281118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
9.4%
109
 
8.6%
( 107
 
8.5%
) 107
 
8.5%
1 42
 
3.3%
35
 
2.8%
, 35
 
2.8%
2 32
 
2.5%
32
 
2.5%
0 29
 
2.3%
Other values (167) 615
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 699
55.4%
Decimal Number 181
 
14.3%
Space Separator 109
 
8.6%
Open Punctuation 107
 
8.5%
Close Punctuation 107
 
8.5%
Other Punctuation 35
 
2.8%
Uppercase Letter 19
 
1.5%
Dash Punctuation 3
 
0.2%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
119
 
17.0%
35
 
5.0%
32
 
4.6%
24
 
3.4%
22
 
3.1%
21
 
3.0%
15
 
2.1%
14
 
2.0%
12
 
1.7%
12
 
1.7%
Other values (139) 393
56.2%
Uppercase Letter
ValueCountFrequency (%)
B 4
21.1%
A 3
15.8%
T 2
10.5%
S 2
10.5%
I 1
 
5.3%
V 1
 
5.3%
O 1
 
5.3%
W 1
 
5.3%
E 1
 
5.3%
R 1
 
5.3%
Other values (2) 2
10.5%
Decimal Number
ValueCountFrequency (%)
1 42
23.2%
2 32
17.7%
0 29
16.0%
3 24
13.3%
5 14
 
7.7%
7 11
 
6.1%
4 10
 
5.5%
6 10
 
5.5%
9 7
 
3.9%
8 2
 
1.1%
Space Separator
ValueCountFrequency (%)
109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 107
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 699
55.4%
Common 544
43.1%
Latin 19
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
119
 
17.0%
35
 
5.0%
32
 
4.6%
24
 
3.4%
22
 
3.1%
21
 
3.0%
15
 
2.1%
14
 
2.0%
12
 
1.7%
12
 
1.7%
Other values (139) 393
56.2%
Common
ValueCountFrequency (%)
109
20.0%
( 107
19.7%
) 107
19.7%
1 42
 
7.7%
, 35
 
6.4%
2 32
 
5.9%
0 29
 
5.3%
3 24
 
4.4%
5 14
 
2.6%
7 11
 
2.0%
Other values (6) 34
 
6.2%
Latin
ValueCountFrequency (%)
B 4
21.1%
A 3
15.8%
T 2
10.5%
S 2
10.5%
I 1
 
5.3%
V 1
 
5.3%
O 1
 
5.3%
W 1
 
5.3%
E 1
 
5.3%
R 1
 
5.3%
Other values (2) 2
10.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 699
55.4%
ASCII 563
44.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
119
 
17.0%
35
 
5.0%
32
 
4.6%
24
 
3.4%
22
 
3.1%
21
 
3.0%
15
 
2.1%
14
 
2.0%
12
 
1.7%
12
 
1.7%
Other values (139) 393
56.2%
ASCII
ValueCountFrequency (%)
109
19.4%
( 107
19.0%
) 107
19.0%
1 42
 
7.5%
, 35
 
6.2%
2 32
 
5.7%
0 29
 
5.2%
3 24
 
4.3%
5 14
 
2.5%
7 11
 
2.0%
Other values (18) 53
9.4%
Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
135 
0
106 
1
 
1

Length

Max length4
Median length4
Mean length2.6735537
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 135
55.8%
0 106
43.8%
1 1
 
0.4%

Length

2024-04-30T03:53:41.397277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T03:53:41.482323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 135
55.8%
0 106
43.8%
1 1
 
0.4%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)58.9%
Missing135
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean200.73832
Minimum2
Maximum2749
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:41.586209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q113
median63
Q3241.5
95-th percentile658.6
Maximum2749
Range2747
Interquartile range (IQR)228.5

Descriptive statistics

Standard deviation410.89328
Coefficient of variation (CV)2.0469101
Kurtosis26.271939
Mean200.73832
Median Absolute Deviation (MAD)54
Skewness4.7027526
Sum21479
Variance168833.29
MonotonicityNot monotonic
2024-04-30T03:53:41.727635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 5
 
2.1%
11 4
 
1.7%
9 4
 
1.7%
12 4
 
1.7%
251 4
 
1.7%
87 3
 
1.2%
3 3
 
1.2%
63 3
 
1.2%
66 3
 
1.2%
5 3
 
1.2%
Other values (53) 71
29.3%
(Missing) 135
55.8%
ValueCountFrequency (%)
2 2
0.8%
3 3
1.2%
5 3
1.2%
6 2
0.8%
8 2
0.8%
9 4
1.7%
10 2
0.8%
11 4
1.7%
12 4
1.7%
13 2
0.8%
ValueCountFrequency (%)
2749 1
 
0.4%
2722 1
 
0.4%
1130 1
 
0.4%
821 1
 
0.4%
775 1
 
0.4%
691 1
 
0.4%
583 3
1.2%
547 1
 
0.4%
527 1
 
0.4%
503 1
 
0.4%

실험실도로명주소건물부번호
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)64.3%
Missing228
Missing (%)94.2%
Infinite0
Infinite (%)0.0%
Mean6.4285714
Minimum0
Maximum26
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:41.840929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.65
Q11.25
median4
Q310
95-th percentile16.9
Maximum26
Range26
Interquartile range (IQR)8.75

Descriptive statistics

Standard deviation6.9582744
Coefficient of variation (CV)1.0823982
Kurtosis4.1703301
Mean6.4285714
Median Absolute Deviation (MAD)3
Skewness1.8538949
Sum90
Variance48.417582
MonotonicityNot monotonic
2024-04-30T03:53:41.946079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 3
 
1.2%
4 2
 
0.8%
7 2
 
0.8%
11 2
 
0.8%
2 1
 
0.4%
26 1
 
0.4%
3 1
 
0.4%
0 1
 
0.4%
12 1
 
0.4%
(Missing) 228
94.2%
ValueCountFrequency (%)
0 1
 
0.4%
1 3
1.2%
2 1
 
0.4%
3 1
 
0.4%
4 2
0.8%
7 2
0.8%
11 2
0.8%
12 1
 
0.4%
26 1
 
0.4%
ValueCountFrequency (%)
26 1
 
0.4%
12 1
 
0.4%
11 2
0.8%
7 2
0.8%
4 2
0.8%
3 1
 
0.4%
2 1
 
0.4%
1 3
1.2%
0 1
 
0.4%

실험실도로명주소우편번호
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)84.8%
Missing209
Missing (%)86.4%
Infinite0
Infinite (%)0.0%
Mean35458.667
Minimum1695
Maximum157779
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-30T03:53:42.042106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1695
5-th percentile1838
Q14779
median6248
Q38732
95-th percentile136083.4
Maximum157779
Range156084
Interquartile range (IQR)3953

Descriptive statistics

Standard deviation54359.774
Coefficient of variation (CV)1.5330462
Kurtosis-0.1383892
Mean35458.667
Median Absolute Deviation (MAD)2484
Skewness1.3234682
Sum1170136
Variance2.9549851 × 109
MonotonicityNot monotonic
2024-04-30T03:53:42.163552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
8732 3
 
1.2%
2832 3
 
1.2%
5680 2
 
0.8%
157779 1
 
0.4%
134877 1
 
0.4%
5838 1
 
0.4%
5641 1
 
0.4%
6225 1
 
0.4%
6138 1
 
0.4%
6248 1
 
0.4%
Other values (18) 18
 
7.4%
(Missing) 209
86.4%
ValueCountFrequency (%)
1695 1
 
0.4%
1811 1
 
0.4%
1856 1
 
0.4%
2832 3
1.2%
4047 1
 
0.4%
4354 1
 
0.4%
4779 1
 
0.4%
4795 1
 
0.4%
5641 1
 
0.4%
5680 2
0.8%
ValueCountFrequency (%)
157779 1
 
0.4%
137893 1
 
0.4%
134877 1
 
0.4%
130805 1
 
0.4%
130743 1
 
0.4%
120749 1
 
0.4%
110380 1
 
0.4%
110053 1
 
0.4%
8732 3
1.2%
8524 1
 
0.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
032200003220000662018000022018-09-04<NA>5제외/삭제/전출5제외사항<NA><NA><NA><NA>027402426<NA><NA>서울특별시 강남구 역삼동 662-7서울특별시 강남구 언주로 547, 13층 (역삼동)06138삼환기업(주)2023-03-03 17:02:03U2022-12-03 00:05:00.0종합 건설업203468.913965444937.661022<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
131600003160000662011000012011-11-29<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2065-0150<NA><NA>서울특별시 구로구 구로동 611-26 오퍼스1 1025호서울특별시 구로구 구로중앙로 207, 오퍼스1 1025호 (구로동)08216(주)대원이씨티2023-06-16 13:20:13U2022-12-05 23:08:00.0<NA>189047.773084444715.218537<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231500003150000662019000022019-10-24<NA>1영업/정상BBBB영업<NA><NA><NA><NA>2679-0361<NA><NA>서울특별시 강서구 염창동 240-21 우림블루나인비즈니스센터 에이동 810호서울특별시 강서구 양천로 583, 우림블루나인비즈니스센터 에이동동 810호 (염창동)07547주식회사 한국쏠텍2023-07-10 18:00:34U2022-12-06 23:03:00.0<NA>187952.560028450562.020226<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
331700003170000662023000012023-03-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-849-5740<NA><NA>서울특별시 금천구 가산동 554-2서울특별시 금천구 가산디지털2로 43-14, 329호 (가산동)08588(주)한경이테크2023-11-03 09:38:10U2022-11-01 00:05:00.0<NA>189450.606005441142.645065<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
431700003170000662015000012015-01-13<NA>1영업/정상BBBB영업<NA><NA><NA><NA>21022672<NA><NA>서울특별시 금천구 가산동 459-28 한국생활환경시험연구원서울특별시 금천구 가산디지털1로 199, 한국생활환경시험연구원 (가산동)08503(재)한국건설생활환경시험연구원2023-07-31 09:55:17U2022-12-08 00:02:00.0<NA>189337.76877442285.30108<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
531700003170000662023000022023-04-21<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-863-9693<NA><NA>서울특별시 금천구 가산동 673서울특별시 금천구 가산디지털1로 16, 403호 (가산동)08591(주)로터스이앤티2024-02-02 15:21:20U2023-12-02 00:04:00.0<NA>190021.956927440609.209534<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
632100003210000662020000012020-10-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-598-0959<NA><NA>서울특별시 서초구 서초동 1355-3 서초월드오피스텔서울특별시 서초구 서운로 19, 서초월드오피스텔 5층 1호 (서초동)06732주식회사 건설분쟁기술원2023-08-14 13:27:09U2022-12-07 23:07:00.0<NA>202508.646066442625.413941<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
732100003210000662019000012019-09-27<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6495-1001<NA><NA>서울특별시 서초구 방배동 895-1 양지빌딩2서울특별시 서초구 서초대로 118, 양지빌딩2 7층 (방배동)06664(주)백아이앤씨2023-08-22 09:57:58U2022-12-07 22:04:00.0<NA>199512.486841442862.203064<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
831600003160000662024000012024-02-01<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2224-0002<NA><NA>서울특별시 구로구 구로동 237 지하이시티서울특별시 구로구 디지털로 243, 지하이시티 701~703호 (구로동)08382(주)여러가지환경문제연구소2024-04-23 16:22:22U2023-12-03 22:05:00.0<NA>190402.032127442203.137447<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
930300003030000662012000022012-07-31<NA>3폐업2폐업2012-12-27<NA><NA><NA>576-6162<NA><NA>서울특별시 성동구 성수동2가 286-67 창미빌딩 401호<NA><NA>에스엔엔지니어링(주)2023-02-21 16:49:59U2022-12-01 22:03:00.0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
232303000030300006620150000120150407<NA>5제외/삭제/전출5제외사항<NA><NA><NA><NA>02-3407-1551<NA><NA>서울특별시 성동구 성수동2가 281-8서울특별시 성동구 광나루로 320-2 (성수동2가, 4층, 6층, 8층(성수동2가, YD빌딩))133832환경보전협회2022-04-11 11:37:39U2021-12-03 23:03:00.0<NA>205673.798754449523.964844<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
233305000030500006620200000120200210<NA>3폐업2폐업20220905<NA><NA><NA>02-2215-9793<NA><NA>서울특별시 동대문구 장안동 464-8서울특별시 동대문구 천호대로 425 (장안동)130846주식회사 성보지오텍2022-09-05 16:00:02U2021-12-09 00:07:00.0<NA>205790.19945451038.454241<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23430300003030000662022000032022-08-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0222107855<NA><NA>서울특별시 성동구 성수동1가 13-209 서울숲에이원센터 1308~호서울특별시 성동구 상원12길 34, 서울숲에이원센터 1308~1310호 (성수동1가)04790㈜로커스솔루션2023-10-12 13:50:02U2022-10-30 23:04:00.0<NA>204399.528008449705.922427<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23532300003230000662009000032009-02-04<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-401-3825<NA><NA>서울특별시 송파구 삼전동 22-1 202호서울특별시 송파구 석촌호수로 138, 202호 (삼전동)05600한국환경설계(주)2023-11-23 17:57:57U2022-10-31 22:05:00.0<NA>208088.55821444991.490733<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23631700003170000662020000012020-01-08<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-867-5999<NA><NA>서울특별시 금천구 가산동 319 호서대벤처타워서울특별시 금천구 가산디지털1로 70, 호서대벤처타워 (가산동)08590(주)가림환경연구소2024-03-17 09:30:40U2023-12-02 23:09:00.0<NA>189841.076534441127.322444<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23731700003170000662019000012019-09-24<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-8675999<NA><NA>서울특별시 금천구 가산동 319 호서대벤처타워서울특별시 금천구 가산디지털1로 70, 호서대벤처타워 1006호 (가산동)08590(주)가림환경연구소2024-03-17 09:30:33U2023-12-02 23:09:00.0<NA>189841.076534441127.322444<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23832300003230000662019000032019-10-28<NA>3폐업2폐업2023-04-30<NA><NA><NA>02-6952-7880<NA><NA>서울특별시 송파구 석촌동 235-20 한양빌딩 4층서울특별시 송파구 백제고분로36길 6, 한양빌딩 4층 (석촌동)05680주식회사 청우환경2023-05-15 10:06:07U2022-12-04 23:07:00.0<NA>208783.783122444488.498089<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23932300003230000662019000012019-01-31<NA>3폐업2폐업2023-04-30<NA><NA><NA>02-6952-7880<NA><NA>서울특별시 송파구 석촌동 235-20 4층서울특별시 송파구 백제고분로36길 6, 4층 (석촌동)05680주식회사 청우환경2023-05-15 10:06:27U2022-12-04 23:07:00.0<NA>208783.783122444488.498089<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24031800003180000662010000042010-04-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0226355100<NA><NA>서울특별시 영등포구 당산동4가 32-47 청암빌딩서울특별시 영등포구 당산로 176 (당산동4가, 청암빌딩)07220한국에너지환경(주)2024-01-24 11:32:17U2023-11-30 22:06:00.0환경 관련 엔지니어링 서비스업191011.486911447515.942072<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
24130300003030000662010000012010-10-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>024537315<NA><NA>서울특별시 성동구 성수동2가 309-148 협성빌딩 602호서울특별시 성동구 성수이로 87, 2층 (성수동2가)133-835(주)한국보건환경연구소2024-03-25 18:55:44U2023-12-02 22:07:00.0<NA>204835.535359448752.958352<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>