Overview

Dataset statistics

Number of variables48
Number of observations61
Missing cells1140
Missing cells (%)38.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.7 KiB
Average record size in memory414.2 B

Variable types

Categorical16
Numeric9
DateTime4
Unsupported9
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
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-19519/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
소재지우편번호 is highly imbalanced (73.5%)Imbalance
업태구분명 is highly imbalanced (64.8%)Imbalance
영업소면적 is highly imbalanced (62.5%)Imbalance
실험실도로명주소시군구코드 is highly imbalanced (55.8%)Imbalance
실험실도로명주소우편번호 is highly imbalanced (84.8%)Imbalance
인허가취소일자 has 61 (100.0%) missing valuesMissing
폐업일자 has 31 (50.8%) missing valuesMissing
휴업시작일자 has 61 (100.0%) missing valuesMissing
휴업종료일자 has 61 (100.0%) missing valuesMissing
재개업일자 has 61 (100.0%) missing valuesMissing
전화번호 has 4 (6.6%) missing valuesMissing
소재지면적 has 61 (100.0%) missing valuesMissing
지번주소 has 1 (1.6%) missing valuesMissing
도로명주소 has 2 (3.3%) missing valuesMissing
도로명우편번호 has 9 (14.8%) missing valuesMissing
위탁업체명 has 54 (88.5%) missing valuesMissing
실험실지역코드 has 47 (77.0%) missing valuesMissing
실험실우편번호 has 61 (100.0%) missing valuesMissing
실험실번지 has 47 (77.0%) missing valuesMissing
실험실호 has 48 (78.7%) missing valuesMissing
실험실통 has 61 (100.0%) missing valuesMissing
실험실반 has 61 (100.0%) missing valuesMissing
실험실특수주소 has 49 (80.3%) missing valuesMissing
실험실특수주소동 has 58 (95.1%) missing valuesMissing
실험실특수주소호 has 53 (86.9%) missing valuesMissing
실험실도로명주소읍면동코드 has 47 (77.0%) missing valuesMissing
실험실도로명주소코드 has 47 (77.0%) missing valuesMissing
실험실도로명특수주소 has 47 (77.0%) missing valuesMissing
실험실도로명주소건물본번호 has 47 (77.0%) missing valuesMissing
실험실도로명주소건물부번호 has 61 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
실험실우편번호 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
실험실도로명주소건물부번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 11:44:57.058582
Analysis finished2024-04-06 11:44:58.537343
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
3170000
61 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3170000
2nd row3170000
3rd row3170000
4th row3170000
5th row3170000

Common Values

ValueCountFrequency (%)
3170000 61
100.0%

Length

2024-04-06T20:44:58.740075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:44:58.917516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3170000 61
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1700007 × 1017
Minimum3.1700007 × 1017
Maximum3.1700007 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:44:59.111641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1700007 × 1017
5-th percentile3.1700007 × 1017
Q13.1700007 × 1017
median3.1700007 × 1017
Q33.1700007 × 1017
95-th percentile3.1700007 × 1017
Maximum3.1700007 × 1017
Range3099999
Interquartile range (IQR)1200000

Descriptive statistics

Standard deviation747243.58
Coefficient of variation (CV)2.3572348 × 10-12
Kurtosis-0.20070906
Mean3.1700007 × 1017
Median Absolute Deviation (MAD)600000
Skewness-0.70552845
Sum8.9026003 × 1017
Variance5.5837297 × 1011
MonotonicityStrictly increasing
2024-04-06T20:44:59.402930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
317000067199300002 1
 
1.6%
317000067202000005 1
 
1.6%
317000067201400012 1
 
1.6%
317000067201400013 1
 
1.6%
317000067201400014 1
 
1.6%
317000067201600001 1
 
1.6%
317000067201600002 1
 
1.6%
317000067201700001 1
 
1.6%
317000067201900001 1
 
1.6%
317000067201900002 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
317000067199300002 1
1.6%
317000067199500003 1
1.6%
317000067200000005 1
1.6%
317000067200100006 1
1.6%
317000067200200001 1
1.6%
317000067200200008 1
1.6%
317000067200200009 1
1.6%
317000067200300002 1
1.6%
317000067200400010 1
1.6%
317000067200500015 1
1.6%
ValueCountFrequency (%)
317000067202400001 1
1.6%
317000067202300002 1
1.6%
317000067202300001 1
1.6%
317000067202200002 1
1.6%
317000067202200001 1
1.6%
317000067202100006 1
1.6%
317000067202100005 1
1.6%
317000067202100004 1
1.6%
317000067202100003 1
1.6%
317000067202100002 1
1.6%
Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
Minimum1993-07-15 00:00:00
Maximum2024-03-18 00:00:00
2024-04-06T20:44:59.637637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:44:59.915912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B
Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
1
31 
3
28 
4
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 31
50.8%
3 28
45.9%
4 2
 
3.3%

Length

2024-04-06T20:45:00.152987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:00.335624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 31
50.8%
3 28
45.9%
4 2
 
3.3%

영업상태명
Categorical

Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
영업/정상
31 
폐업
28 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length3.9180328
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 31
50.8%
폐업 28
45.9%
취소/말소/만료/정지/중지 2
 
3.3%

Length

2024-04-06T20:45:00.525823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:00.734915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 31
50.8%
폐업 28
45.9%
취소/말소/만료/정지/중지 2
 
3.3%
Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
BBBB
31 
2
28 
4
 
2

Length

Max length4
Median length4
Mean length2.5245902
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 31
50.8%
2 28
45.9%
4 2
 
3.3%

Length

2024-04-06T20:45:00.940459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:01.145328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 31
50.8%
2 28
45.9%
4 2
 
3.3%
Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
영업
31 
폐업
28 
폐쇄
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 31
50.8%
폐업 28
45.9%
폐쇄 2
 
3.3%

Length

2024-04-06T20:45:01.348210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:01.594150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 31
50.8%
폐업 28
45.9%
폐쇄 2
 
3.3%

폐업일자
Date

MISSING 

Distinct27
Distinct (%)90.0%
Missing31
Missing (%)50.8%
Memory size620.0 B
Minimum2010-12-31 00:00:00
Maximum2024-01-22 00:00:00
2024-04-06T20:45:01.755616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:45:01.944178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

전화번호
Text

MISSING 

Distinct53
Distinct (%)93.0%
Missing4
Missing (%)6.6%
Memory size620.0 B
2024-04-06T20:45:02.344656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.280702
Min length8

Characters and Unicode

Total characters586
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)86.0%

Sample

1st row0221132300
2nd row0220264780
3rd row028542114
4th row0220260770
5th row028944213
ValueCountFrequency (%)
0263441500 2
 
3.5%
3459-2062 2
 
3.5%
0269004843 2
 
3.5%
028344859 2
 
3.5%
02-6949-0373 1
 
1.8%
02-839-8941 1
 
1.8%
2106-8000 1
 
1.8%
2088-3330 1
 
1.8%
02-6101-0400 1
 
1.8%
02-534-0571 1
 
1.8%
Other values (43) 43
75.4%
2024-04-06T20:45:02.991690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 115
19.6%
2 91
15.5%
- 54
9.2%
6 52
8.9%
3 48
8.2%
4 48
8.2%
1 41
 
7.0%
9 39
 
6.7%
8 36
 
6.1%
7 31
 
5.3%
Other values (2) 31
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 531
90.6%
Dash Punctuation 54
 
9.2%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 115
21.7%
2 91
17.1%
6 52
9.8%
3 48
9.0%
4 48
9.0%
1 41
 
7.7%
9 39
 
7.3%
8 36
 
6.8%
7 31
 
5.8%
5 30
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 586
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 115
19.6%
2 91
15.5%
- 54
9.2%
6 52
8.9%
3 48
8.2%
4 48
8.2%
1 41
 
7.0%
9 39
 
6.7%
8 36
 
6.1%
7 31
 
5.3%
Other values (2) 31
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 586
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 115
19.6%
2 91
15.5%
- 54
9.2%
6 52
8.9%
3 48
8.2%
4 48
8.2%
1 41
 
7.0%
9 39
 
6.7%
8 36
 
6.1%
7 31
 
5.3%
Other values (2) 31
 
5.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

소재지우편번호
Categorical

IMBALANCE 

Distinct6
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
55 
153803
 
2
153789
 
1
153775
 
1
153771
 
1

Length

Max length6
Median length4
Mean length4.1967213
Min length4

Unique

Unique4 ?
Unique (%)6.6%

Sample

1st row<NA>
2nd row<NA>
3rd row153789
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 55
90.2%
153803 2
 
3.3%
153789 1
 
1.6%
153775 1
 
1.6%
153771 1
 
1.6%
153802 1
 
1.6%

Length

2024-04-06T20:45:03.280284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:03.518415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 55
90.2%
153803 2
 
3.3%
153789 1
 
1.6%
153775 1
 
1.6%
153771 1
 
1.6%
153802 1
 
1.6%

지번주소
Text

MISSING 

Distinct52
Distinct (%)86.7%
Missing1
Missing (%)1.6%
Memory size620.0 B
2024-04-06T20:45:03.992090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38
Mean length29.633333
Min length18

Characters and Unicode

Total characters1778
Distinct characters102
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)75.0%

Sample

1st row서울특별시 금천구 가산동 481-10 벽산경인디지털밸리2 918호
2nd row서울특별시 금천구 가산동 371-28 우림라이온스밸리 C동 607호
3rd row서울특별시 금천구 가산동 470-5 에이스테크노타워10차 905호
4th row서울특별시 금천구 가산동 371-28 우림라이온스밸리 B동 709호
5th row서울특별시 금천구 독산동 291-1 현대지식산업센터 제에이동 1101호
ValueCountFrequency (%)
서울특별시 60
18.1%
금천구 60
18.1%
가산동 55
16.6%
371-37 5
 
1.5%
b동 5
 
1.5%
327-32 4
 
1.2%
481-10 4
 
1.2%
470-5 3
 
0.9%
독산동 3
 
0.9%
에이스테크노타워10차 3
 
0.9%
Other values (97) 129
39.0%
2024-04-06T20:45:04.900359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
16.3%
1 89
 
5.0%
69
 
3.9%
66
 
3.7%
62
 
3.5%
61
 
3.4%
61
 
3.4%
60
 
3.4%
60
 
3.4%
60
 
3.4%
Other values (92) 900
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 991
55.7%
Decimal Number 397
22.3%
Space Separator 290
 
16.3%
Dash Punctuation 57
 
3.2%
Uppercase Letter 41
 
2.3%
Lowercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
69
 
7.0%
66
 
6.7%
62
 
6.3%
61
 
6.2%
61
 
6.2%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
Other values (62) 372
37.5%
Uppercase Letter
ValueCountFrequency (%)
T 7
17.1%
B 5
12.2%
I 4
9.8%
C 3
 
7.3%
S 3
 
7.3%
Y 2
 
4.9%
H 2
 
4.9%
O 2
 
4.9%
W 2
 
4.9%
V 2
 
4.9%
Other values (6) 9
22.0%
Decimal Number
ValueCountFrequency (%)
1 89
22.4%
2 52
13.1%
3 47
11.8%
0 46
11.6%
5 36
9.1%
4 36
9.1%
7 35
 
8.8%
8 23
 
5.8%
9 21
 
5.3%
6 12
 
3.0%
Space Separator
ValueCountFrequency (%)
290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 991
55.7%
Common 745
41.9%
Latin 42
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
69
 
7.0%
66
 
6.7%
62
 
6.3%
61
 
6.2%
61
 
6.2%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
Other values (62) 372
37.5%
Latin
ValueCountFrequency (%)
T 7
16.7%
B 5
11.9%
I 4
 
9.5%
C 3
 
7.1%
S 3
 
7.1%
Y 2
 
4.8%
H 2
 
4.8%
O 2
 
4.8%
W 2
 
4.8%
V 2
 
4.8%
Other values (7) 10
23.8%
Common
ValueCountFrequency (%)
290
38.9%
1 89
 
11.9%
- 57
 
7.7%
2 52
 
7.0%
3 47
 
6.3%
0 46
 
6.2%
5 36
 
4.8%
4 36
 
4.8%
7 35
 
4.7%
8 23
 
3.1%
Other values (3) 34
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 991
55.7%
ASCII 787
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
36.8%
1 89
 
11.3%
- 57
 
7.2%
2 52
 
6.6%
3 47
 
6.0%
0 46
 
5.8%
5 36
 
4.6%
4 36
 
4.6%
7 35
 
4.4%
8 23
 
2.9%
Other values (20) 76
 
9.7%
Hangul
ValueCountFrequency (%)
69
 
7.0%
66
 
6.7%
62
 
6.3%
61
 
6.2%
61
 
6.2%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
60
 
6.1%
Other values (62) 372
37.5%

도로명주소
Text

MISSING 

Distinct53
Distinct (%)89.8%
Missing2
Missing (%)3.3%
Memory size620.0 B
2024-04-06T20:45:05.405940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length39.254237
Min length26

Characters and Unicode

Total characters2316
Distinct characters119
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

Unique48 ?
Unique (%)81.4%

Sample

1st row서울특별시 금천구 가산디지털2로 184, 918호 (가산동, 벽산디지털밸리2차)
2nd row서울특별시 금천구 가산디지털1로 168, C동 607호 (가산동,우림라이온스밸리)
3rd row서울특별시 금천구 가산디지털1로 196 (가산동)
4th row서울특별시 금천구 두산로 70, 제에이동 11층 1101호 (독산동, 현대지식산업센터)
5th row서울특별시 금천구 벚꽃로 298, 대륭포스트타워6차 1301-90호 (가산동)
ValueCountFrequency (%)
서울특별시 59
 
14.8%
금천구 59
 
14.8%
가산동 48
 
12.1%
가산디지털1로 28
 
7.0%
가산디지털2로 18
 
4.5%
128 5
 
1.3%
벽산디지털밸리2차 4
 
1.0%
184 4
 
1.0%
53 3
 
0.8%
196 3
 
0.8%
Other values (129) 167
42.0%
2024-04-06T20:45:06.057170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
339
 
14.6%
1 123
 
5.3%
117
 
5.1%
105
 
4.5%
, 73
 
3.2%
2 70
 
3.0%
66
 
2.8%
64
 
2.8%
61
 
2.6%
60
 
2.6%
Other values (109) 1238
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1334
57.6%
Decimal Number 398
 
17.2%
Space Separator 339
 
14.6%
Other Punctuation 73
 
3.2%
Open Punctuation 59
 
2.5%
Close Punctuation 59
 
2.5%
Uppercase Letter 40
 
1.7%
Dash Punctuation 10
 
0.4%
Math Symbol 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
117
 
8.8%
105
 
7.9%
66
 
4.9%
64
 
4.8%
61
 
4.6%
60
 
4.5%
60
 
4.5%
59
 
4.4%
59
 
4.4%
59
 
4.4%
Other values (77) 624
46.8%
Uppercase Letter
ValueCountFrequency (%)
T 7
17.5%
B 4
10.0%
I 4
10.0%
S 3
 
7.5%
C 3
 
7.5%
H 2
 
5.0%
Y 2
 
5.0%
R 2
 
5.0%
E 2
 
5.0%
W 2
 
5.0%
Other values (6) 9
22.5%
Decimal Number
ValueCountFrequency (%)
1 123
30.9%
2 70
17.6%
0 50
12.6%
8 35
 
8.8%
3 25
 
6.3%
6 24
 
6.0%
5 21
 
5.3%
9 21
 
5.3%
4 15
 
3.8%
7 14
 
3.5%
Space Separator
ValueCountFrequency (%)
339
100.0%
Other Punctuation
ValueCountFrequency (%)
, 73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1334
57.6%
Common 942
40.7%
Latin 40
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
117
 
8.8%
105
 
7.9%
66
 
4.9%
64
 
4.8%
61
 
4.6%
60
 
4.5%
60
 
4.5%
59
 
4.4%
59
 
4.4%
59
 
4.4%
Other values (77) 624
46.8%
Common
ValueCountFrequency (%)
339
36.0%
1 123
 
13.1%
, 73
 
7.7%
2 70
 
7.4%
( 59
 
6.3%
) 59
 
6.3%
0 50
 
5.3%
8 35
 
3.7%
3 25
 
2.7%
6 24
 
2.5%
Other values (6) 85
 
9.0%
Latin
ValueCountFrequency (%)
T 7
17.5%
B 4
10.0%
I 4
10.0%
S 3
 
7.5%
C 3
 
7.5%
H 2
 
5.0%
Y 2
 
5.0%
R 2
 
5.0%
E 2
 
5.0%
W 2
 
5.0%
Other values (6) 9
22.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1334
57.6%
ASCII 982
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
339
34.5%
1 123
 
12.5%
, 73
 
7.4%
2 70
 
7.1%
( 59
 
6.0%
) 59
 
6.0%
0 50
 
5.1%
8 35
 
3.6%
3 25
 
2.5%
6 24
 
2.4%
Other values (22) 125
 
12.7%
Hangul
ValueCountFrequency (%)
117
 
8.8%
105
 
7.9%
66
 
4.9%
64
 
4.8%
61
 
4.6%
60
 
4.5%
60
 
4.5%
59
 
4.4%
59
 
4.4%
59
 
4.4%
Other values (77) 624
46.8%

도로명우편번호
Text

MISSING 

Distinct29
Distinct (%)55.8%
Missing9
Missing (%)14.8%
Memory size620.0 B
2024-04-06T20:45:06.349325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.5384615
Min length5

Characters and Unicode

Total characters288
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

Unique18 ?
Unique (%)34.6%

Sample

1st row153-783
2nd row153789
3rd row08584
4th row08510
5th row153775
ValueCountFrequency (%)
153803 7
 
13.5%
08506 4
 
7.7%
08501 4
 
7.7%
08589 3
 
5.8%
08504 3
 
5.8%
153802 3
 
5.8%
153706 2
 
3.8%
08507 2
 
3.8%
08584 2
 
3.8%
08592 2
 
3.8%
Other values (19) 20
38.5%
2024-04-06T20:45:06.879222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59
20.5%
5 52
18.1%
8 48
16.7%
3 38
13.2%
1 34
11.8%
7 18
 
6.2%
9 11
 
3.8%
6 9
 
3.1%
2 9
 
3.1%
4 6
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 284
98.6%
Dash Punctuation 4
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
20.8%
5 52
18.3%
8 48
16.9%
3 38
13.4%
1 34
12.0%
7 18
 
6.3%
9 11
 
3.9%
6 9
 
3.2%
2 9
 
3.2%
4 6
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59
20.5%
5 52
18.1%
8 48
16.7%
3 38
13.2%
1 34
11.8%
7 18
 
6.2%
9 11
 
3.8%
6 9
 
3.1%
2 9
 
3.1%
4 6
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59
20.5%
5 52
18.1%
8 48
16.7%
3 38
13.2%
1 34
11.8%
7 18
 
6.2%
9 11
 
3.8%
6 9
 
3.1%
2 9
 
3.1%
4 6
 
2.1%
Distinct54
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-06T20:45:07.277112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.7377049
Min length4

Characters and Unicode

Total characters533
Distinct characters120
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)77.0%

Sample

1st row(주)가야환경
2nd row새한환경기술(주)
3rd row(주)협진티엔씨
4th row지앤씨엔지니어링(주)
5th row선일기술산업(주)
ValueCountFrequency (%)
주식회사 4
 
6.2%
주)세트이엔지 2
 
3.1%
엘지히타치워터솔루션(주 2
 
3.1%
주)에코이엔티 2
 
3.1%
동림이엔지(주 2
 
3.1%
소리텍엔지니어링(주 2
 
3.1%
엘아이지엔설팅(주 2
 
3.1%
에스지신성건설(주 2
 
3.1%
필즈엔지니어링(주 1
 
1.5%
주)더비씨환경 1
 
1.5%
Other values (45) 45
69.2%
2024-04-06T20:45:07.884588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
11.1%
( 52
 
9.8%
) 52
 
9.8%
24
 
4.5%
24
 
4.5%
18
 
3.4%
13
 
2.4%
9
 
1.7%
9
 
1.7%
9
 
1.7%
Other values (110) 264
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 425
79.7%
Open Punctuation 52
 
9.8%
Close Punctuation 52
 
9.8%
Space Separator 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
59
 
13.9%
24
 
5.6%
24
 
5.6%
18
 
4.2%
13
 
3.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
Other values (107) 243
57.2%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 425
79.7%
Common 108
 
20.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
59
 
13.9%
24
 
5.6%
24
 
5.6%
18
 
4.2%
13
 
3.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
Other values (107) 243
57.2%
Common
ValueCountFrequency (%)
( 52
48.1%
) 52
48.1%
4
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 425
79.7%
ASCII 108
 
20.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
59
 
13.9%
24
 
5.6%
24
 
5.6%
18
 
4.2%
13
 
3.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
9
 
2.1%
8
 
1.9%
Other values (107) 243
57.2%
ASCII
ValueCountFrequency (%)
( 52
48.1%
) 52
48.1%
4
 
3.7%

최종수정일자
Date

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
Minimum2013-02-05 13:33:31
Maximum2024-03-25 16:19:01
2024-04-06T20:45:08.108197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:45:08.339575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
U
34 
I
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 34
55.7%
I 27
44.3%

Length

2024-04-06T20:45:08.542540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:08.701681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 34
55.7%
i 27
44.3%
Distinct36
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
Minimum2019-03-30 02:20:09
Maximum2023-12-02 23:04:00
2024-04-06T20:45:08.856012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:45:09.091707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
52 
환경상담 및 관련 엔지니어링 서비스업
환경 정화 및 복원업
 
1
자동차 제조업
 
1
환경컨설팅 및 관련 엔지니어링 서비스업
 
1

Length

Max length21
Median length4
Mean length6.0163934
Min length4

Unique

Unique3 ?
Unique (%)4.9%

Sample

1st row<NA>
2nd row환경상담 및 관련 엔지니어링 서비스업
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 52
85.2%
환경상담 및 관련 엔지니어링 서비스업 6
 
9.8%
환경 정화 및 복원업 1
 
1.6%
자동차 제조업 1
 
1.6%
환경컨설팅 및 관련 엔지니어링 서비스업 1
 
1.6%

Length

2024-04-06T20:45:09.370954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:09.562501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
55.9%
8
 
8.6%
관련 7
 
7.5%
엔지니어링 7
 
7.5%
서비스업 7
 
7.5%
환경상담 6
 
6.5%
환경 1
 
1.1%
정화 1
 
1.1%
복원업 1
 
1.1%
자동차 1
 
1.1%
Other values (2) 2
 
2.2%

좌표정보(X)
Real number (ℝ)

Distinct36
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189623.32
Minimum189030.11
Maximum191241.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:09.756724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189030.11
5-th percentile189089.93
Q1189369.54
median189538.02
Q3189722.18
95-th percentile190694.88
Maximum191241.43
Range2211.3217
Interquartile range (IQR)352.63891

Descriptive statistics

Standard deviation470.2312
Coefficient of variation (CV)0.0024798173
Kurtosis3.9808845
Mean189623.32
Median Absolute Deviation (MAD)173.92497
Skewness1.8174343
Sum11567023
Variance221117.38
MonotonicityNot monotonic
2024-04-06T20:45:09.972129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
189647.046752134 5
 
8.2%
189127.981104583 4
 
6.6%
189686.475000033 4
 
6.6%
189417.708595762 3
 
4.9%
189538.020935968 3
 
4.9%
189773.53836329 3
 
4.9%
189452.382474246 2
 
3.3%
189202.181652324 2
 
3.3%
189778.774504778 2
 
3.3%
189450.60600488 2
 
3.3%
Other values (26) 31
50.8%
ValueCountFrequency (%)
189030.107416961 1
 
1.6%
189031.670933573 1
 
1.6%
189055.138252216 1
 
1.6%
189089.927764903 1
 
1.6%
189127.981104583 4
6.6%
189174.558570016 1
 
1.6%
189202.181652324 2
3.3%
189228.282678816 1
 
1.6%
189314.711435401 1
 
1.6%
189364.095969911 2
3.3%
ValueCountFrequency (%)
191241.429128495 1
 
1.6%
191226.287379467 1
 
1.6%
190804.00357365 1
 
1.6%
190694.880295092 2
3.3%
190050.903572929 1
 
1.6%
189978.050925581 1
 
1.6%
189930.50790426 1
 
1.6%
189920.528610917 1
 
1.6%
189778.774504778 2
3.3%
189773.53836329 3
4.9%

좌표정보(Y)
Real number (ℝ)

Distinct36
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean441551.59
Minimum437914.06
Maximum442636.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:10.177459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437914.06
5-th percentile440521.86
Q1441142.65
median441677.1
Q3442174.42
95-th percentile442562.72
Maximum442636.32
Range4722.2571
Interquartile range (IQR)1031.779

Descriptive statistics

Standard deviation866.52107
Coefficient of variation (CV)0.0019624458
Kurtosis5.4664703
Mean441551.59
Median Absolute Deviation (MAD)528.77125
Skewness-1.8045455
Sum26934647
Variance750858.77
MonotonicityNot monotonic
2024-04-06T20:45:10.361353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
441677.096205358 5
 
8.2%
442460.505542105 4
 
6.6%
440870.092608694 4
 
6.6%
442309.174987731 3
 
4.9%
441982.427934953 3
 
4.9%
440940.376102266 3
 
4.9%
442205.867457803 2
 
3.3%
442562.722742062 2
 
3.3%
441302.111937219 2
 
3.3%
441142.645065053 2
 
3.3%
Other values (26) 31
50.8%
ValueCountFrequency (%)
437914.06299827 1
 
1.6%
438641.653485665 1
 
1.6%
440363.954453659 1
 
1.6%
440521.85524888 1
 
1.6%
440523.497478209 1
 
1.6%
440764.426277932 2
3.3%
440870.092608694 4
6.6%
440940.376102266 3
4.9%
441018.620015864 1
 
1.6%
441142.645065053 2
3.3%
ValueCountFrequency (%)
442636.320100968 1
 
1.6%
442585.933234852 1
 
1.6%
442569.300676147 1
 
1.6%
442562.722742062 2
3.3%
442460.505542105 4
6.6%
442309.174987731 3
4.9%
442239.943267799 1
 
1.6%
442205.867457803 2
3.3%
442174.424111843 1
 
1.6%
442139.514492212 2
3.3%

실험실면적
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
54 
0

Length

Max length4
Median length4
Mean length3.6557377
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 54
88.5%
0 7
 
11.5%

Length

2024-04-06T20:45:10.945650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:11.120606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 54
88.5%
0 7
 
11.5%
Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
환경전문공사업
36 
<NA>
25 

Length

Max length7
Median length7
Mean length5.7704918
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 36
59.0%
<NA> 25
41.0%

Length

2024-04-06T20:45:11.317299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:11.479881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 36
59.0%
na 25
41.0%

영업소면적
Categorical

IMBALANCE 

Distinct4
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
52 
0
199
 
1
287
 
1

Length

Max length4
Median length4
Mean length3.6229508
Min length1

Unique

Unique2 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 52
85.2%
0 7
 
11.5%
199 1
 
1.6%
287 1
 
1.6%

Length

2024-04-06T20:45:11.669894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:11.872817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 52
85.2%
0 7
 
11.5%
199 1
 
1.6%
287 1
 
1.6%

위탁업체명
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing54
Missing (%)88.5%
Memory size620.0 B
2024-04-06T20:45:12.151689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length10
Mean length9
Min length4

Characters and Unicode

Total characters63
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)71.4%

Sample

1st row성북구 이전
2nd row(주)청룡환경
3rd row(주)산업공해연구소
4th row(주)청룡환경-측정대행계약
5th row서울과학기술대학교 에너지환경연구소
ValueCountFrequency (%)
청룡환경 2
22.2%
성북구 1
11.1%
이전 1
11.1%
주)청룡환경 1
11.1%
주)산업공해연구소 1
11.1%
주)청룡환경-측정대행계약 1
11.1%
서울과학기술대학교 1
11.1%
에너지환경연구소 1
11.1%
2024-04-06T20:45:12.748975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
7.9%
5
 
7.9%
4
 
6.3%
4
 
6.3%
3
 
4.8%
3
 
4.8%
) 3
 
4.8%
( 3
 
4.8%
2
 
3.2%
2
 
3.2%
Other values (26) 29
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
85.7%
Close Punctuation 3
 
4.8%
Open Punctuation 3
 
4.8%
Space Separator 2
 
3.2%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
3
 
5.6%
3
 
5.6%
2
 
3.7%
2
 
3.7%
2
 
3.7%
2
 
3.7%
Other values (22) 22
40.7%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
85.7%
Common 9
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
3
 
5.6%
3
 
5.6%
2
 
3.7%
2
 
3.7%
2
 
3.7%
2
 
3.7%
Other values (22) 22
40.7%
Common
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
2
22.2%
- 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
85.7%
ASCII 9
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
 
9.3%
5
 
9.3%
4
 
7.4%
4
 
7.4%
3
 
5.6%
3
 
5.6%
2
 
3.7%
2
 
3.7%
2
 
3.7%
2
 
3.7%
Other values (22) 22
40.7%
ASCII
ValueCountFrequency (%)
) 3
33.3%
( 3
33.3%
2
22.2%
- 1
 
11.1%

실험실지역코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)42.9%
Missing47
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean1.3679245 × 109
Minimum1.1530102 × 109
Maximum4.1273107 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:12.931399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1530102 × 109
5-th percentile1.1539851 × 109
Q11.1545101 × 109
median1.1545101 × 109
Q31.1545102 × 109
95-th percentile2.2057156 × 109
Maximum4.1273107 × 109
Range2.9743005 × 109
Interquartile range (IQR)75

Descriptive statistics

Standard deviation7.9421844 × 108
Coefficient of variation (CV)0.58060109
Kurtosis13.998901
Mean1.3679245 × 109
Median Absolute Deviation (MAD)0
Skewness3.7414527
Sum1.9150943 × 1010
Variance6.3078293 × 1017
MonotonicityNot monotonic
2024-04-06T20:45:13.109315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1154510100 9
 
14.8%
1154510200 1
 
1.6%
1154510300 1
 
1.6%
1171010500 1
 
1.6%
1153010200 1
 
1.6%
4127310700 1
 
1.6%
(Missing) 47
77.0%
ValueCountFrequency (%)
1153010200 1
 
1.6%
1154510100 9
14.8%
1154510200 1
 
1.6%
1154510300 1
 
1.6%
1171010500 1
 
1.6%
4127310700 1
 
1.6%
ValueCountFrequency (%)
4127310700 1
 
1.6%
1171010500 1
 
1.6%
1154510300 1
 
1.6%
1154510200 1
 
1.6%
1154510100 9
14.8%
1153010200 1
 
1.6%

실험실우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

실험실산
Categorical

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
47 
1
14 

Length

Max length4
Median length4
Mean length3.3114754
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 47
77.0%
1 14
 
23.0%

Length

2024-04-06T20:45:13.346821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:13.552130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
77.0%
1 14
 
23.0%

실험실번지
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)85.7%
Missing47
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean416.5
Minimum50
Maximum984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:13.723086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile145.55
Q1300
median415
Q3478.25
95-th percentile747.4
Maximum984
Range934
Interquartile range (IQR)178.25

Descriptive statistics

Standard deviation219.49899
Coefficient of variation (CV)0.52700839
Kurtosis2.8704668
Mean416.5
Median Absolute Deviation (MAD)89
Skewness1.0511946
Sum5831
Variance48179.808
MonotonicityNot monotonic
2024-04-06T20:45:13.895208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
470 2
 
3.3%
371 2
 
3.3%
291 1
 
1.6%
50 1
 
1.6%
481 1
 
1.6%
327 1
 
1.6%
984 1
 
1.6%
235 1
 
1.6%
459 1
 
1.6%
505 1
 
1.6%
Other values (2) 2
 
3.3%
(Missing) 47
77.0%
ValueCountFrequency (%)
50 1
1.6%
197 1
1.6%
235 1
1.6%
291 1
1.6%
327 1
1.6%
371 2
3.3%
459 1
1.6%
470 2
3.3%
481 1
1.6%
505 1
1.6%
ValueCountFrequency (%)
984 1
1.6%
620 1
1.6%
505 1
1.6%
481 1
1.6%
470 2
3.3%
459 1
1.6%
371 2
3.3%
327 1
1.6%
291 1
1.6%
235 1
1.6%

실험실호
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)69.2%
Missing48
Missing (%)78.7%
Infinite0
Infinite (%)0.0%
Mean15.538462
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:14.056553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q15
median11
Q322
95-th percentile34
Maximum37
Range36
Interquartile range (IQR)17

Descriptive statistics

Standard deviation11.522553
Coefficient of variation (CV)0.74155045
Kurtosis-0.74503424
Mean15.538462
Median Absolute Deviation (MAD)7
Skewness0.57392975
Sum202
Variance132.76923
MonotonicityNot monotonic
2024-04-06T20:45:14.272000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
11 3
 
4.9%
5 2
 
3.3%
18 2
 
3.3%
28 1
 
1.6%
1 1
 
1.6%
3 1
 
1.6%
32 1
 
1.6%
37 1
 
1.6%
22 1
 
1.6%
(Missing) 48
78.7%
ValueCountFrequency (%)
1 1
 
1.6%
3 1
 
1.6%
5 2
3.3%
11 3
4.9%
18 2
3.3%
22 1
 
1.6%
28 1
 
1.6%
32 1
 
1.6%
37 1
 
1.6%
ValueCountFrequency (%)
37 1
 
1.6%
32 1
 
1.6%
28 1
 
1.6%
22 1
 
1.6%
18 2
3.3%
11 3
4.9%
5 2
3.3%
3 1
 
1.6%
1 1
 
1.6%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B

실험실특수주소
Text

MISSING 

Distinct11
Distinct (%)91.7%
Missing49
Missing (%)80.3%
Memory size620.0 B
2024-04-06T20:45:14.599793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9.5
Mean length8.5
Min length5

Characters and Unicode

Total characters102
Distinct characters55
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)83.3%

Sample

1st row에이스테크노타워10차
2nd row우림라이온스밸리
3rd row현대지식산업센터
4th row대륭포스트타워6차
5th row대륭테크노타운8차
ValueCountFrequency (%)
에이스테크노타워10차 2
16.7%
우림라이온스밸리 1
8.3%
현대지식산업센터 1
8.3%
대륭포스트타워6차 1
8.3%
대륭테크노타운8차 1
8.3%
대륭테크노타운12차 1
8.3%
에스티엑스브이타워 1
8.3%
시흥유통상가 1
8.3%
주)청명기연환경 1
8.3%
주)청룡환경 1
8.3%
2024-04-06T20:45:15.178412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
5.9%
6
 
5.9%
5
 
4.9%
4
 
3.9%
4
 
3.9%
4
 
3.9%
4
 
3.9%
4
 
3.9%
4
 
3.9%
3
 
2.9%
Other values (45) 58
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 89
87.3%
Decimal Number 8
 
7.8%
Close Punctuation 2
 
2.0%
Open Punctuation 2
 
2.0%
Other Symbol 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
6.7%
6
 
6.7%
5
 
5.6%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
3
 
3.4%
Other values (37) 45
50.6%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
0 2
25.0%
6 1
 
12.5%
8 1
 
12.5%
2 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
88.2%
Common 12
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6
 
6.7%
6
 
6.7%
5
 
5.6%
4
 
4.4%
4
 
4.4%
4
 
4.4%
4
 
4.4%
4
 
4.4%
4
 
4.4%
3
 
3.3%
Other values (38) 46
51.1%
Common
ValueCountFrequency (%)
1 3
25.0%
0 2
16.7%
) 2
16.7%
( 2
16.7%
6 1
 
8.3%
8 1
 
8.3%
2 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 89
87.3%
ASCII 12
 
11.8%
None 1
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6
 
6.7%
6
 
6.7%
5
 
5.6%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
4
 
4.5%
3
 
3.4%
Other values (37) 45
50.6%
ASCII
ValueCountFrequency (%)
1 3
25.0%
0 2
16.7%
) 2
16.7%
( 2
16.7%
6 1
 
8.3%
8 1
 
8.3%
2 1
 
8.3%
None
ValueCountFrequency (%)
1
100.0%
Distinct3
Distinct (%)100.0%
Missing58
Missing (%)95.1%
Memory size620.0 B
2024-04-06T20:45:15.425162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters6
Distinct characters6
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowB
2nd row제에이
3rd row21
ValueCountFrequency (%)
b 1
33.3%
제에이 1
33.3%
21 1
33.3%
2024-04-06T20:45:15.907462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 1
16.7%
1
16.7%
1
16.7%
1
16.7%
2 1
16.7%
1 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
50.0%
Decimal Number 2
33.3%
Uppercase Letter 1
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
50.0%
Common 2
33.3%
Latin 1
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Common
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
50.0%
Hangul 3
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 1
33.3%
2 1
33.3%
1 1
33.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct8
Distinct (%)100.0%
Missing53
Missing (%)86.9%
Memory size620.0 B
2024-04-06T20:45:16.193965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length4
Min length3

Characters and Unicode

Total characters32
Distinct characters10
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

Unique8 ?
Unique (%)100.0%

Sample

1st row905
2nd row709
3rd row1101
4th row1408
5th row301
ValueCountFrequency (%)
905 1
12.5%
709 1
12.5%
1101 1
12.5%
1408 1
12.5%
301 1
12.5%
515 1
12.5%
1306~1310 1
12.5%
109 1
12.5%
2024-04-06T20:45:16.726562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
31.2%
0 8
25.0%
9 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
7 1
 
3.1%
4 1
 
3.1%
8 1
 
3.1%
6 1
 
3.1%
~ 1
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31
96.9%
Math Symbol 1
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
32.3%
0 8
25.8%
9 3
 
9.7%
5 3
 
9.7%
3 3
 
9.7%
7 1
 
3.2%
4 1
 
3.2%
8 1
 
3.2%
6 1
 
3.2%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
31.2%
0 8
25.0%
9 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
7 1
 
3.1%
4 1
 
3.1%
8 1
 
3.1%
6 1
 
3.1%
~ 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
31.2%
0 8
25.0%
9 3
 
9.4%
5 3
 
9.4%
3 3
 
9.4%
7 1
 
3.1%
4 1
 
3.1%
8 1
 
3.1%
6 1
 
3.1%
~ 1
 
3.1%
Distinct5
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
47 
11545
11 
11710
 
1
11530
 
1
41273
 
1

Length

Max length5
Median length4
Mean length4.2295082
Min length4

Unique

Unique3 ?
Unique (%)4.9%

Sample

1st row<NA>
2nd row<NA>
3rd row11545
4th row11545
5th row11545

Common Values

ValueCountFrequency (%)
<NA> 47
77.0%
11545 11
 
18.0%
11710 1
 
1.6%
11530 1
 
1.6%
41273 1
 
1.6%

Length

2024-04-06T20:45:16.950261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:17.143779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
77.0%
11545 11
 
18.0%
11710 1
 
1.6%
11530 1
 
1.6%
41273 1
 
1.6%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)42.9%
Missing47
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean1.3679245 × 109
Minimum1.1530102 × 109
Maximum4.1273107 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:17.343400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1530102 × 109
5-th percentile1.1539851 × 109
Q11.1545101 × 109
median1.1545101 × 109
Q31.1545102 × 109
95-th percentile2.2057156 × 109
Maximum4.1273107 × 109
Range2.9743005 × 109
Interquartile range (IQR)75

Descriptive statistics

Standard deviation7.9421844 × 108
Coefficient of variation (CV)0.58060109
Kurtosis13.998901
Mean1.3679245 × 109
Median Absolute Deviation (MAD)0
Skewness3.7414527
Sum1.9150943 × 1010
Variance6.3078293 × 1017
MonotonicityNot monotonic
2024-04-06T20:45:17.521190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1154510100 9
 
14.8%
1154510200 1
 
1.6%
1154510300 1
 
1.6%
1171010500 1
 
1.6%
1153010200 1
 
1.6%
4127310700 1
 
1.6%
(Missing) 47
77.0%
ValueCountFrequency (%)
1153010200 1
 
1.6%
1154510100 9
14.8%
1154510200 1
 
1.6%
1154510300 1
 
1.6%
1171010500 1
 
1.6%
4127310700 1
 
1.6%
ValueCountFrequency (%)
4127310700 1
 
1.6%
1171010500 1
 
1.6%
1154510300 1
 
1.6%
1154510200 1
 
1.6%
1154510100 9
14.8%
1153010200 1
 
1.6%
Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
47 
1
14 

Length

Max length4
Median length4
Mean length3.3114754
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 47
77.0%
1 14
 
23.0%

Length

2024-04-06T20:45:17.755074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:17.943277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
77.0%
1 14
 
23.0%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)64.3%
Missing47
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean3183257.6
Minimum2005010
Maximum4169186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:18.123109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005010
5-th percentile2651768.5
Q13117001
median3117001
Q33117004.2
95-th percentile4155632.9
Maximum4169186
Range2164176
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation508767.18
Coefficient of variation (CV)0.15982595
Kurtosis2.9920066
Mean3183257.6
Median Absolute Deviation (MAD)2.5
Skewness0.14496151
Sum44565607
Variance2.5884404 × 1011
MonotonicityNot monotonic
2024-04-06T20:45:18.322495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3117001 6
 
9.8%
3117005 1
 
1.6%
3116013 1
 
1.6%
3000023 1
 
1.6%
3117002 1
 
1.6%
2005010 1
 
1.6%
4169186 1
 
1.6%
4148335 1
 
1.6%
3191027 1
 
1.6%
(Missing) 47
77.0%
ValueCountFrequency (%)
2005010 1
 
1.6%
3000023 1
 
1.6%
3116013 1
 
1.6%
3117001 6
9.8%
3117002 1
 
1.6%
3117005 1
 
1.6%
3191027 1
 
1.6%
4148335 1
 
1.6%
4169186 1
 
1.6%
ValueCountFrequency (%)
4169186 1
 
1.6%
4148335 1
 
1.6%
3191027 1
 
1.6%
3117005 1
 
1.6%
3117002 1
 
1.6%
3117001 6
9.8%
3116013 1
 
1.6%
3000023 1
 
1.6%
2005010 1
 
1.6%
Distinct13
Distinct (%)92.9%
Missing47
Missing (%)77.0%
Memory size620.0 B
2024-04-06T20:45:18.608925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length19.285714
Min length5

Characters and Unicode

Total characters270
Distinct characters74
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)85.7%

Sample

1st row905호 (가산동, 에이스테크노타워10차)
2nd rowB동 709호 (가산동, 우림라이온스밸리)
3rd row제에이동 11층 1101호 (독산동, 현대지식산업센터)
4th row대륭포스트타워6차 1301-90호 (가산동)
5th row1408호 (가산동, 대륭테크노타운8차)
ValueCountFrequency (%)
가산동 9
22.5%
에이스테크노타워10차 2
 
5.0%
515호 1
 
2.5%
3층 1
 
2.5%
㈜동암기계 1
 
2.5%
주)청룡환경 1
 
2.5%
구로동 1
 
2.5%
주)청명기연환경 1
 
2.5%
석촌동 1
 
2.5%
시흥유통상가 1
 
2.5%
Other values (21) 21
52.5%
2024-04-06T20:45:19.118815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26
 
9.6%
18
 
6.7%
1 18
 
6.7%
( 16
 
5.9%
) 16
 
5.9%
0 12
 
4.4%
11
 
4.1%
10
 
3.7%
, 10
 
3.7%
9
 
3.3%
Other values (64) 124
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148
54.8%
Decimal Number 50
 
18.5%
Space Separator 26
 
9.6%
Open Punctuation 16
 
5.9%
Close Punctuation 16
 
5.9%
Other Punctuation 10
 
3.7%
Other Symbol 1
 
0.4%
Uppercase Letter 1
 
0.4%
Dash Punctuation 1
 
0.4%
Math Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
12.2%
11
 
7.4%
10
 
6.8%
9
 
6.1%
6
 
4.1%
6
 
4.1%
5
 
3.4%
5
 
3.4%
4
 
2.7%
4
 
2.7%
Other values (46) 70
47.3%
Decimal Number
ValueCountFrequency (%)
1 18
36.0%
0 12
24.0%
3 5
 
10.0%
9 4
 
8.0%
5 3
 
6.0%
2 2
 
4.0%
8 2
 
4.0%
6 2
 
4.0%
7 1
 
2.0%
4 1
 
2.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149
55.2%
Common 120
44.4%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
12.1%
11
 
7.4%
10
 
6.7%
9
 
6.0%
6
 
4.0%
6
 
4.0%
5
 
3.4%
5
 
3.4%
4
 
2.7%
4
 
2.7%
Other values (47) 71
47.7%
Common
ValueCountFrequency (%)
26
21.7%
1 18
15.0%
( 16
13.3%
) 16
13.3%
0 12
10.0%
, 10
 
8.3%
3 5
 
4.2%
9 4
 
3.3%
5 3
 
2.5%
2 2
 
1.7%
Other values (6) 8
 
6.7%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148
54.8%
ASCII 121
44.8%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26
21.5%
1 18
14.9%
( 16
13.2%
) 16
13.2%
0 12
9.9%
, 10
 
8.3%
3 5
 
4.1%
9 4
 
3.3%
5 3
 
2.5%
2 2
 
1.7%
Other values (7) 9
 
7.4%
Hangul
ValueCountFrequency (%)
18
 
12.2%
11
 
7.4%
10
 
6.8%
9
 
6.1%
6
 
4.1%
6
 
4.1%
5
 
3.4%
5
 
3.4%
4
 
2.7%
4
 
2.7%
Other values (46) 70
47.3%
None
ValueCountFrequency (%)
1
100.0%
Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
47 
0
14 

Length

Max length4
Median length4
Mean length3.3114754
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 47
77.0%
0 14
 
23.0%

Length

2024-04-06T20:45:19.349606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:19.522250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 47
77.0%
0 14
 
23.0%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)92.9%
Missing47
Missing (%)77.0%
Infinite0
Infinite (%)0.0%
Mean137.85714
Minimum12
Maximum298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-06T20:45:19.674532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13.3
Q176.5
median148
Q3196
95-th percentile251.2
Maximum298
Range286
Interquartile range (IQR)119.5

Descriptive statistics

Standard deviation89.37635
Coefficient of variation (CV)0.64832585
Kurtosis-0.95280327
Mean137.85714
Median Absolute Deviation (MAD)63.5
Skewness-0.005600524
Sum1930
Variance7988.1319
MonotonicityNot monotonic
2024-04-06T20:45:19.846698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
196 2
 
3.3%
168 1
 
1.6%
70 1
 
1.6%
298 1
 
1.6%
96 1
 
1.6%
14 1
 
1.6%
128 1
 
1.6%
97 1
 
1.6%
12 1
 
1.6%
186 1
 
1.6%
Other values (3) 3
 
4.9%
(Missing) 47
77.0%
ValueCountFrequency (%)
12 1
1.6%
14 1
1.6%
20 1
1.6%
70 1
1.6%
96 1
1.6%
97 1
1.6%
128 1
1.6%
168 1
1.6%
186 1
1.6%
196 2
3.3%
ValueCountFrequency (%)
298 1
1.6%
226 1
1.6%
223 1
1.6%
196 2
3.3%
186 1
1.6%
168 1
1.6%
128 1
1.6%
97 1
1.6%
96 1
1.6%
70 1
1.6%

실험실도로명주소건물부번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing61
Missing (%)100.0%
Memory size681.0 B
Distinct3
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
<NA>
59 
8510
 
1
15436
 
1

Length

Max length5
Median length4
Mean length4.0163934
Min length4

Unique

Unique2 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
96.7%
8510 1
 
1.6%
15436 1
 
1.6%

Length

2024-04-06T20:45:20.094123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:45:20.273484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
96.7%
8510 1
 
1.6%
15436 1
 
1.6%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
031700003170000671993000021993-07-15<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0221132300<NA><NA>서울특별시 금천구 가산동 481-10 벽산경인디지털밸리2 918호서울특별시 금천구 가산디지털2로 184, 918호 (가산동, 벽산디지털밸리2차)153-783(주)가야환경2023-04-06 16:26:34U2022-12-04 00:08:00.0<NA>189127.981105442460.505542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1317000031700006719950000319950515<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0220264780<NA><NA>서울특별시 금천구 가산동 371-28 우림라이온스밸리 C동 607호서울특별시 금천구 가산디지털1로 168, C동 607호 (가산동,우림라이온스밸리)<NA>새한환경기술(주)2023-01-30 17:54:21U2022-12-02 00:01:00.0환경상담 및 관련 엔지니어링 서비스업189538.020936441982.427935<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2317000031700006720000000520001021<NA>3폐업2폐업20110131<NA><NA><NA>028542114<NA>153789서울특별시 금천구 가산동 470-5 에이스테크노타워10차 905호서울특별시 금천구 가산디지털1로 196 (가산동)153789(주)협진티엔씨2017-12-18 12:18:15I2019-03-30 02:20:09.0<NA>189417.708596442309.174988<NA>환경전문공사업<NA><NA>1154510100<NA>14705<NA><NA>에이스테크노타워10차<NA>90511545115451010013117001905호 (가산동, 에이스테크노타워10차)0196<NA><NA>
3317000031700006720010000620010220<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0220260770<NA><NA>서울특별시 금천구 가산동 371-28 우림라이온스밸리 B동 709호<NA><NA>지앤씨엔지니어링(주)2022-03-14 15:14:38U2022-03-16 02:40:00.0<NA>189538.020936441982.4279350환경전문공사업0<NA>1154510100<NA>137128<NA><NA>우림라이온스밸리B70911545115451010013117001B동 709호 (가산동, 우림라이온스밸리)0168<NA><NA>
4317000031700006720020000120020629<NA>1영업/정상BBBB영업<NA><NA><NA><NA>028944213<NA><NA>서울특별시 금천구 독산동 291-1 현대지식산업센터 제에이동 1101호서울특별시 금천구 두산로 70, 제에이동 11층 1101호 (독산동, 현대지식산업센터)08584선일기술산업(주)2022-03-14 14:48:13U2022-03-16 02:40:00.0<NA>190694.880295440764.4262780환경전문공사업0<NA>1154510200<NA>12911<NA><NA>현대지식산업센터제에이110111545115451020013117005제에이동 11층 1101호 (독산동, 현대지식산업센터)070<NA><NA>
5317000031700006720020000820021021<NA>1영업/정상BBBB영업<NA><NA><NA><NA>025792545<NA><NA><NA>서울특별시 금천구 벚꽃로 298, 대륭포스트타워6차 1301-90호 (가산동)08510(주)호담엔지니어링2021-06-30 14:40:05U2021-07-02 02:40:00.0<NA>189662.959176442139.514492<NA>환경전문공사업<NA><NA>1154510100<NA>1503<NA><NA>대륭포스트타워6차<NA><NA>11545115451010013116013대륭포스트타워6차 1301-90호 (가산동)0298<NA>8510
631700003170000672002000092002-10-22<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0233973431<NA><NA>서울특별시 금천구 가산동 60-19 SJ테크노빌 1212호서울특별시 금천구 벚꽃로 278, 1212호 (가산동,SJ테크노빌)<NA>(주)루선트엔지니어링2024-03-25 16:19:01U2023-12-02 22:07:00.0<NA>189722.178532441920.97277<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
7317000031700006720030000220031230<NA>3폐업2폐업20101231<NA><NA><NA>025877381<NA>153775서울특별시 금천구 가산동 481-11 대륭테크노타운8차 1408호서울특별시 금천구 가마산로 96, 1408호 (가산동, 대륭테크노타운8차)153775소리텍엔지니어링(주)2017-12-18 11:30:10I2019-03-30 02:20:09.0<NA>189089.927765442569.300676<NA>환경전문공사업<NA><NA>1154510100<NA>148111<NA><NA>대륭테크노타운8차<NA>1408115451154510100130000231408호 (가산동, 대륭테크노타운8차)096<NA><NA>
831700003170000672004000102004-12-20<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0226269966<NA><NA>서울특별시 금천구 가산동 429-1 뉴티캐슬 1108호서울특별시 금천구 가산디지털2로 108 (가산동)153-779가람환경기술(주)2023-12-13 17:53:13U2022-11-01 23:05:00.0<NA>189364.09597441746.98153<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9317000031700006720050001520051110<NA>3폐업2폐업20120316<NA><NA><NA>0231402000<NA><NA>서울특별시 금천구 가산동 470-5 에이스테크노타워10차 301호서울특별시 금천구 가산디지털1로 196, 301호 (가산동,에이스테크노타워10차)<NA>삼양정수(주)2017-12-18 12:25:12I2019-03-30 02:20:09.0<NA>189417.708596442309.174988<NA>환경전문공사업<NA><NA>1154510100<NA>14705<NA><NA>에이스테크노타워10차<NA>30111545115451010013117001301호 (가산동, 에이스테크노타워10차)0196<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
51317000031700006720210000220210319<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-3667-7773<NA><NA>서울특별시 금천구 가산동 517-4 에이스 가산 포휴서울특별시 금천구 가산디지털1로 225, 에이스 가산 포휴 (가산동)08501(주)에스에이치모빌리티2022-08-26 17:52:23U2021-12-07 22:08:00.0<NA>189202.181652442562.722742<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
52317000031700006720210000320210326<NA>4취소/말소/만료/정지/중지4폐쇄20220531<NA><NA><NA>02-2102-2900<NA><NA>서울특별시 금천구 가산동 481-10 벽산디지털밸리2차서울특별시 금천구 가산디지털2로 184, 벽산디지털밸리2차 922호 (가산동)08501세안에너텍(주)2022-05-31 09:47:43U2021-12-06 00:04:00.0<NA>189127.981105442460.505542<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
53317000031700006720210000420210405<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-850-3100<NA><NA>서울특별시 금천구 가산동 517-4 에이스 가산 포휴서울특별시 금천구 가산디지털1로 225, 에이스 가산 포휴 (가산동)08501(주)에코센스2021-07-13 17:12:32U2021-07-15 02:40:00.0<NA>189202.181652442562.7227420환경전문공사업0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
54317000031700006720210000520210420<NA>3폐업2폐업20210906<NA><NA><NA>031-494-9928<NA><NA>서울특별시 금천구 가산동 371-37 에스티엑스브이타워서울특별시 금천구 가산디지털1로 128, 에스티엑스브이타워 1105호호 (가산동)08507(주)에코이엔티2021-09-06 13:32:43U2021-09-08 02:40:00.0<NA>189647.046752441677.0962050환경전문공사업0<NA>4127310700<NA>162011<NA><NA>㈜동암기계<NA><NA>41273412731070013191027㈜동암기계 3층 (초지동)0223<NA>15436
55317000031700006720210000620210617<NA>3폐업2폐업20220523<NA><NA><NA>02-863-9694<NA><NA>서울특별시 금천구 가산동 680 우림라이온스밸리2차서울특별시 금천구 가산디지털1로 2, 우림라이온스밸리2차 206호 (가산동)08591(주)더비씨환경2022-05-23 14:20:01U2021-12-04 22:05:00.0<NA>190050.903573440523.497478<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5631700003170000672022000012022-01-04<NA>3폐업2폐업2024-01-22<NA><NA><NA>02-2156-3100<NA><NA>서울특별시 금천구 가산동 371-47 이노플렉스1차서울특별시 금천구 가산디지털1로 151, 이노플렉스1차 1202~1207호호 (가산동)08506(주)진우엔지니어링코리아2024-01-23 12:53:33U2023-11-30 22:05:00.0<NA>189434.721898441862.707623<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5731700003170000672022000022022-06-07<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 가산동 327-32 대륭테크노타운12차서울특별시 금천구 가산디지털2로 14, 대륭테크노타운12차 (가산동)08592(주)기련이엔씨2023-07-19 16:21:02U2022-12-06 22:01:00.0<NA>189686.475440870.092609<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5831700003170000672023000012023-02-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-839-8941<NA><NA>서울특별시 금천구 가산동 371-17 BYC HIGHCITY b동 1304호서울특별시 금천구 가산디지털1로 131, BYC HIGHCITY (가산동)08506(주)페스텍2023-02-23 16:35:11I2022-12-01 22:05:00.0환경상담 및 관련 엔지니어링 서비스업189522.336722441654.010373<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5931700003170000672023000022023-08-20<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2624-1300<NA><NA>서울특별시 금천구 가산동 371-50 에이스하이엔드타워3차서울특별시 금천구 가산디지털1로 145, 에이스하이엔드타워3차 1203, 1206호 (가산동)08506(주)파일란트2023-08-21 08:12:21I2022-12-07 22:03:00.0환경상담 및 관련 엔지니어링 서비스업189467.124187441780.005399<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
6031700003170000672024000012024-03-18<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-866-3639<NA><NA>서울특별시 금천구 가산동 60-26 B동 723호서울특별시 금천구 디지털로 178, B동 723호 (가산동)08513주식회사 우림환경엔지니어링2024-03-19 15:31:26I2023-12-02 22:01:00.0<NA>189930.507904441616.46071<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>