Overview

Dataset statistics

Number of variables48
Number of observations54
Missing cells958
Missing cells (%)37.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory416.4 B

Variable types

Categorical17
Numeric11
DateTime3
Unsupported8
Text9

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
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-19520/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
소재지우편번호 has constant value ""Constant
실험실면적 is highly imbalanced (69.0%)Imbalance
영업소면적 is highly imbalanced (75.4%)Imbalance
실험실특수주소호 is highly imbalanced (80.1%)Imbalance
실험실도로명주소건물부번호 is highly imbalanced (61.9%)Imbalance
실험실도로명주소우편번호 is highly imbalanced (77.3%)Imbalance
인허가취소일자 has 54 (100.0%) missing valuesMissing
폐업일자 has 33 (61.1%) missing valuesMissing
휴업시작일자 has 54 (100.0%) missing valuesMissing
휴업종료일자 has 54 (100.0%) missing valuesMissing
재개업일자 has 54 (100.0%) missing valuesMissing
전화번호 has 5 (9.3%) missing valuesMissing
소재지면적 has 54 (100.0%) missing valuesMissing
소재지우편번호 has 52 (96.3%) missing valuesMissing
지번주소 has 4 (7.4%) missing valuesMissing
도로명주소 has 9 (16.7%) missing valuesMissing
도로명우편번호 has 33 (61.1%) missing valuesMissing
업태구분명 has 50 (92.6%) missing valuesMissing
좌표정보(X) has 1 (1.9%) missing valuesMissing
좌표정보(Y) has 1 (1.9%) missing valuesMissing
위탁업체명 has 51 (94.4%) missing valuesMissing
실험실지역코드 has 30 (55.6%) missing valuesMissing
실험실우편번호 has 36 (66.7%) missing valuesMissing
실험실번지 has 30 (55.6%) missing valuesMissing
실험실호 has 38 (70.4%) missing valuesMissing
실험실통 has 54 (100.0%) missing valuesMissing
실험실반 has 54 (100.0%) missing valuesMissing
실험실특수주소 has 33 (61.1%) missing valuesMissing
실험실특수주소동 has 54 (100.0%) missing valuesMissing
실험실도로명주소읍면동코드 has 30 (55.6%) missing valuesMissing
실험실도로명주소코드 has 30 (55.6%) missing valuesMissing
실험실도로명특수주소 has 30 (55.6%) missing valuesMissing
실험실도로명주소건물본번호 has 30 (55.6%) 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
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
실험실특수주소동 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-06 13:39:27.342384
Analysis finished2024-04-06 13:39:27.985150
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size564.0 B
3180000
54 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3180000
2nd row3180000
3rd row3180000
4th row3180000
5th row3180000

Common Values

ValueCountFrequency (%)
3180000 54
100.0%

Length

2024-04-06T22:39:28.046604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:28.138309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3180000 54
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1800007 × 1017
Minimum3.1800007 × 1017
Maximum3.1800007 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:28.240103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1800007 × 1017
5-th percentile3.1800007 × 1017
Q13.1800007 × 1017
median3.1800007 × 1017
Q33.1800007 × 1017
95-th percentile3.1800007 × 1017
Maximum3.1800007 × 1017
Range1200000
Interquartile range (IQR)574976

Descriptive statistics

Standard deviation357050.62
Coefficient of variation (CV)1.1228004 × 10-12
Kurtosis-0.14401238
Mean3.1800007 × 1017
Median Absolute Deviation (MAD)0
Skewness1.0536408
Sum-1.2747404 × 1018
Variance1.2748514 × 1011
MonotonicityStrictly increasing
2024-04-06T22:39:28.379012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
318000067201000001 1
 
1.9%
318000067201600002 1
 
1.9%
318000067201200001 1
 
1.9%
318000067201200002 1
 
1.9%
318000067201200003 1
 
1.9%
318000067201200004 1
 
1.9%
318000067201300001 1
 
1.9%
318000067201300002 1
 
1.9%
318000067201300003 1
 
1.9%
318000067201500001 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
318000067201000001 1
1.9%
318000067201000002 1
1.9%
318000067201000003 1
1.9%
318000067201000004 1
1.9%
318000067201000005 1
1.9%
318000067201000006 1
1.9%
318000067201000007 1
1.9%
318000067201000008 1
1.9%
318000067201000009 1
1.9%
318000067201000010 1
1.9%
ValueCountFrequency (%)
318000067202200001 1
1.9%
318000067202100001 1
1.9%
318000067202000002 1
1.9%
318000067202000001 1
1.9%
318000067201800002 1
1.9%
318000067201800001 1
1.9%
318000067201700005 1
1.9%
318000067201700004 1
1.9%
318000067201700003 1
1.9%
318000067201700002 1
1.9%

인허가일자
Date

Distinct34
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2010-02-09 00:00:00
Maximum2022-10-28 00:00:00
2024-04-06T22:39:28.503603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:39:28.628902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

영업상태코드
Categorical

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
1
28 
3
23 
4
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 28
51.9%
3 23
42.6%
4 3
 
5.6%

Length

2024-04-06T22:39:28.772191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:28.922751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 28
51.9%
3 23
42.6%
4 3
 
5.6%

영업상태명
Categorical

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
영업/정상
28 
폐업
23 
취소/말소/만료/정지/중지
3 

Length

Max length14
Median length5
Mean length4.2222222
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 28
51.9%
폐업 23
42.6%
취소/말소/만료/정지/중지 3
 
5.6%

Length

2024-04-06T22:39:29.044434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:29.138124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 28
51.9%
폐업 23
42.6%
취소/말소/만료/정지/중지 3
 
5.6%

상세영업상태코드
Categorical

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
BBBB
28 
2
23 
4
3 

Length

Max length4
Median length4
Mean length2.5555556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 28
51.9%
2 23
42.6%
4 3
 
5.6%

Length

2024-04-06T22:39:29.247887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:29.342896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 28
51.9%
2 23
42.6%
4 3
 
5.6%

상세영업상태명
Categorical

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
영업
28 
폐업
23 
폐쇄
3 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 28
51.9%
폐업 23
42.6%
폐쇄 3
 
5.6%

Length

2024-04-06T22:39:29.429762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:29.514222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 28
51.9%
폐업 23
42.6%
폐쇄 3
 
5.6%

폐업일자
Date

MISSING 

Distinct20
Distinct (%)95.2%
Missing33
Missing (%)61.1%
Memory size564.0 B
Minimum2010-05-27 00:00:00
Maximum2024-02-20 00:00:00
2024-04-06T22:39:29.599710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:39:29.695926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

전화번호
Text

MISSING 

Distinct47
Distinct (%)95.9%
Missing5
Missing (%)9.3%
Memory size564.0 B
2024-04-06T22:39:29.883028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.061224
Min length7

Characters and Unicode

Total characters493
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

Unique45 ?
Unique (%)91.8%

Sample

1st row027675670
2nd row0226362662
3rd row0226752166
4th row0226725565
5th row0226328611
ValueCountFrequency (%)
02-2672-9900 2
 
4.1%
02-2068-1435 2
 
4.1%
02-6150-7433 1
 
2.0%
02-302-4077 1
 
2.0%
7821463 1
 
2.0%
0236677773 1
 
2.0%
027675670 1
 
2.0%
02-761-2202 1
 
2.0%
26712960 1
 
2.0%
02-817-0867 1
 
2.0%
Other values (37) 37
75.5%
2024-04-06T22:39:30.217153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 97
19.7%
0 84
17.0%
6 62
12.6%
3 46
9.3%
7 45
9.1%
- 33
 
6.7%
8 32
 
6.5%
1 28
 
5.7%
5 23
 
4.7%
9 22
 
4.5%
Other values (2) 21
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 459
93.1%
Dash Punctuation 33
 
6.7%
Math Symbol 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 97
21.1%
0 84
18.3%
6 62
13.5%
3 46
10.0%
7 45
9.8%
8 32
 
7.0%
1 28
 
6.1%
5 23
 
5.0%
9 22
 
4.8%
4 20
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 493
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 97
19.7%
0 84
17.0%
6 62
12.6%
3 46
9.3%
7 45
9.1%
- 33
 
6.7%
8 32
 
6.5%
1 28
 
5.7%
5 23
 
4.7%
9 22
 
4.5%
Other values (2) 21
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 97
19.7%
0 84
17.0%
6 62
12.6%
3 46
9.3%
7 45
9.1%
- 33
 
6.7%
8 32
 
6.5%
1 28
 
5.7%
5 23
 
4.7%
9 22
 
4.5%
Other values (2) 21
 
4.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

소재지우편번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing52
Missing (%)96.3%
Memory size564.0 B
2024-04-06T22:39:30.311544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownull
2nd rownull
ValueCountFrequency (%)
null 2
100.0%
2024-04-06T22:39:30.490407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 4
33.3%
4
33.3%
n 2
16.7%
u 2
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
66.7%
Space Separator 4
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 4
50.0%
n 2
25.0%
u 2
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
66.7%
Common 4
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 4
50.0%
n 2
25.0%
u 2
25.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 4
33.3%
4
33.3%
n 2
16.7%
u 2
16.7%

지번주소
Text

MISSING 

Distinct48
Distinct (%)96.0%
Missing4
Missing (%)7.4%
Memory size564.0 B
2024-04-06T22:39:30.720515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34.5
Mean length29.3
Min length20

Characters and Unicode

Total characters1465
Distinct characters132
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)92.0%

Sample

1st row서울특별시 영등포구 여의도동 44-5 조흥증권빌딩
2nd row서울특별시 영등포구 여의도동 13-6 기계산업진흥회 11층
3rd row서울특별시 영등포구 영등포동8가 92 케이앤케이디지털타워 810호
4th row서울특별시 영등포구 당산동1가 256-58
5th row서울특별시 영등포구 당산동2가 11 혜천빌딩 6층
ValueCountFrequency (%)
서울특별시 50
18.9%
영등포구 50
18.9%
여의도동 13
 
4.9%
양평동3가 8
 
3.0%
46 7
 
2.7%
문래동3가 7
 
2.7%
이앤씨드림타워 6
 
2.3%
에이스하이테크시티 4
 
1.5%
55-20 4
 
1.5%
양평동1가 3
 
1.1%
Other values (100) 112
42.4%
2024-04-06T22:39:31.065653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245
 
16.7%
1 63
 
4.3%
시 55
 
3.8%
영 53
 
3.6%
동 53
 
3.6%
등 51
 
3.5%
포 51
 
3.5%
서 50
 
3.4%
특 50
 
3.4%
별 50
 
3.4%
Other values (122) 744
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 908
62.0%
Decimal Number 265
 
18.1%
Space Separator 245
 
16.7%
Dash Punctuation 37
 
2.5%
Uppercase Letter 7
 
0.5%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 55
 
6.1%
영 53
 
5.8%
동 53
 
5.8%
등 51
 
5.6%
포 51
 
5.6%
서 50
 
5.5%
특 50
 
5.5%
별 50
 
5.5%
구 50
 
5.5%
울 50
 
5.5%
Other values (102) 395
43.5%
Decimal Number
ValueCountFrequency (%)
1 63
23.8%
3 37
14.0%
2 31
11.7%
5 27
10.2%
4 26
9.8%
0 25
 
9.4%
6 22
 
8.3%
8 16
 
6.0%
9 9
 
3.4%
7 9
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
G 2
28.6%
L 2
28.6%
B 1
14.3%
I 1
14.3%
Z 1
14.3%
Space Separator
ValueCountFrequency (%)
245
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 908
62.0%
Common 549
37.5%
Latin 8
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 55
 
6.1%
영 53
 
5.8%
동 53
 
5.8%
등 51
 
5.6%
포 51
 
5.6%
서 50
 
5.5%
특 50
 
5.5%
별 50
 
5.5%
구 50
 
5.5%
울 50
 
5.5%
Other values (102) 395
43.5%
Common
ValueCountFrequency (%)
245
44.6%
1 63
 
11.5%
3 37
 
6.7%
- 37
 
6.7%
2 31
 
5.6%
5 27
 
4.9%
4 26
 
4.7%
0 25
 
4.6%
6 22
 
4.0%
8 16
 
2.9%
Other values (4) 20
 
3.6%
Latin
ValueCountFrequency (%)
G 2
25.0%
L 2
25.0%
e 1
12.5%
B 1
12.5%
I 1
12.5%
Z 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 908
62.0%
ASCII 557
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
44.0%
1 63
 
11.3%
3 37
 
6.6%
- 37
 
6.6%
2 31
 
5.6%
5 27
 
4.8%
4 26
 
4.7%
0 25
 
4.5%
6 22
 
3.9%
8 16
 
2.9%
Other values (10) 28
 
5.0%
Hangul
ValueCountFrequency (%)
시 55
 
6.1%
영 53
 
5.8%
동 53
 
5.8%
등 51
 
5.6%
포 51
 
5.6%
서 50
 
5.5%
특 50
 
5.5%
별 50
 
5.5%
구 50
 
5.5%
울 50
 
5.5%
Other values (102) 395
43.5%

도로명주소
Text

MISSING 

Distinct44
Distinct (%)97.8%
Missing9
Missing (%)16.7%
Memory size564.0 B
2024-04-06T22:39:31.347022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length37.533333
Min length25

Characters and Unicode

Total characters1689
Distinct characters134
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)95.6%

Sample

1st row서울특별시 영등포구 여의대방로69길 17 (여의도동)
2nd row서울특별시 영등포구 국회대로76길 22 (여의도동,기계산업진흥회 11층)
3rd row서울특별시 영등포구 당산로 82 (당산동1가)
4th row서울특별시 영등포구 문래북로 114 (문래동3가)
5th row서울특별시 영등포구 여의대방로 93-1 (신길동)
ValueCountFrequency (%)
서울특별시 45
 
15.8%
영등포구 45
 
15.8%
여의도동 7
 
2.5%
선유로 6
 
2.1%
146 5
 
1.8%
양평동3가 5
 
1.8%
14 4
 
1.4%
775 4
 
1.4%
경인로 4
 
1.4%
양평동1가 3
 
1.1%
Other values (134) 157
55.1%
2024-04-06T22:39:31.734246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
 
14.9%
1 71
 
4.2%
영 52
 
3.1%
시 50
 
3.0%
동 49
 
2.9%
등 48
 
2.8%
포 48
 
2.8%
) 46
 
2.7%
( 46
 
2.7%
, 46
 
2.7%
Other values (124) 981
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1018
60.3%
Decimal Number 268
 
15.9%
Space Separator 252
 
14.9%
Other Punctuation 47
 
2.8%
Close Punctuation 46
 
2.7%
Open Punctuation 46
 
2.7%
Dash Punctuation 7
 
0.4%
Uppercase Letter 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 52
 
5.1%
시 50
 
4.9%
동 49
 
4.8%
등 48
 
4.7%
포 48
 
4.7%
로 45
 
4.4%
울 45
 
4.4%
서 45
 
4.4%
구 45
 
4.4%
별 45
 
4.4%
Other values (105) 546
53.6%
Decimal Number
ValueCountFrequency (%)
1 71
26.5%
2 37
13.8%
3 32
11.9%
4 26
 
9.7%
0 23
 
8.6%
6 20
 
7.5%
5 20
 
7.5%
7 20
 
7.5%
9 10
 
3.7%
8 9
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
L 2
40.0%
G 2
40.0%
A 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 46
97.9%
. 1
 
2.1%
Space Separator
ValueCountFrequency (%)
252
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1018
60.3%
Common 666
39.4%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 52
 
5.1%
시 50
 
4.9%
동 49
 
4.8%
등 48
 
4.7%
포 48
 
4.7%
로 45
 
4.4%
울 45
 
4.4%
서 45
 
4.4%
구 45
 
4.4%
별 45
 
4.4%
Other values (105) 546
53.6%
Common
ValueCountFrequency (%)
252
37.8%
1 71
 
10.7%
) 46
 
6.9%
( 46
 
6.9%
, 46
 
6.9%
2 37
 
5.6%
3 32
 
4.8%
4 26
 
3.9%
0 23
 
3.5%
6 20
 
3.0%
Other values (6) 67
 
10.1%
Latin
ValueCountFrequency (%)
L 2
40.0%
G 2
40.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1018
60.3%
ASCII 671
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
37.6%
1 71
 
10.6%
) 46
 
6.9%
( 46
 
6.9%
, 46
 
6.9%
2 37
 
5.5%
3 32
 
4.8%
4 26
 
3.9%
0 23
 
3.4%
6 20
 
3.0%
Other values (9) 72
 
10.7%
Hangul
ValueCountFrequency (%)
영 52
 
5.1%
시 50
 
4.9%
동 49
 
4.8%
등 48
 
4.7%
포 48
 
4.7%
로 45
 
4.4%
울 45
 
4.4%
서 45
 
4.4%
구 45
 
4.4%
별 45
 
4.4%
Other values (105) 546
53.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)76.2%
Missing33
Missing (%)61.1%
Infinite0
Infinite (%)0.0%
Mean34532.333
Minimum7218
Maximum150800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:31.848132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7218
5-th percentile7255
Q17272
median7325
Q37371
95-th percentile150103
Maximum150800
Range143582
Interquartile range (IQR)99

Descriptive statistics

Standard deviation57519.533
Coefficient of variation (CV)1.6656718
Kurtosis0.97537463
Mean34532.333
Median Absolute Deviation (MAD)50
Skewness1.7004579
Sum725179
Variance3.3084967 × 109
MonotonicityNot monotonic
2024-04-06T22:39:31.944477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
7272 3
 
5.6%
7299 2
 
3.7%
7255 2
 
3.7%
7325 2
 
3.7%
7358 1
 
1.9%
150103 1
 
1.9%
7371 1
 
1.9%
7328 1
 
1.9%
150800 1
 
1.9%
7338 1
 
1.9%
Other values (6) 6
 
11.1%
(Missing) 33
61.1%
ValueCountFrequency (%)
7218 1
 
1.9%
7255 2
3.7%
7272 3
5.6%
7282 1
 
1.9%
7299 2
3.7%
7320 1
 
1.9%
7325 2
3.7%
7328 1
 
1.9%
7338 1
 
1.9%
7358 1
 
1.9%
ValueCountFrequency (%)
150800 1
1.9%
150103 1
1.9%
150102 1
1.9%
150010 1
1.9%
7375 1
1.9%
7371 1
1.9%
7358 1
1.9%
7338 1
1.9%
7328 1
1.9%
7325 2
3.7%

사업장명
Text

Distinct52
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size564.0 B
2024-04-06T22:39:32.125956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length8.4074074
Min length4

Characters and Unicode

Total characters454
Distinct characters115
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

Unique50 ?
Unique (%)92.6%

Sample

1st row벽산엔지니어링(주)
2nd row(주)립코
3rd row아태수기엔지니어링(주)
4th row(주)대일휀스
5th row(주)혜천산업
ValueCountFrequency (%)
주식회사 4
 
6.8%
주)에코엔서비스 2
 
3.4%
주)한성이엠아이 2
 
3.4%
주)동양 1
 
1.7%
공우이엔씨(주 1
 
1.7%
주)씨에프텍 1
 
1.7%
주)나산플랜트 1
 
1.7%
벽산엔지니어링(주 1
 
1.7%
주)동성진흥 1
 
1.7%
주)네오퍼플 1
 
1.7%
Other values (44) 44
74.6%
2024-04-06T22:39:32.445784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 51
 
11.2%
( 45
 
9.9%
) 45
 
9.9%
이 21
 
4.6%
엔 16
 
3.5%
에 13
 
2.9%
스 11
 
2.4%
한 10
 
2.2%
코 9
 
2.0%
사 8
 
1.8%
Other values (105) 225
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 359
79.1%
Open Punctuation 45
 
9.9%
Close Punctuation 45
 
9.9%
Space Separator 5
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 51
 
14.2%
이 21
 
5.8%
엔 16
 
4.5%
에 13
 
3.6%
스 11
 
3.1%
한 10
 
2.8%
코 9
 
2.5%
사 8
 
2.2%
지 8
 
2.2%
회 6
 
1.7%
Other values (102) 206
57.4%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 359
79.1%
Common 95
 
20.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 51
 
14.2%
이 21
 
5.8%
엔 16
 
4.5%
에 13
 
3.6%
스 11
 
3.1%
한 10
 
2.8%
코 9
 
2.5%
사 8
 
2.2%
지 8
 
2.2%
회 6
 
1.7%
Other values (102) 206
57.4%
Common
ValueCountFrequency (%)
( 45
47.4%
) 45
47.4%
5
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 359
79.1%
ASCII 95
 
20.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 51
 
14.2%
이 21
 
5.8%
엔 16
 
4.5%
에 13
 
3.6%
스 11
 
3.1%
한 10
 
2.8%
코 9
 
2.5%
사 8
 
2.2%
지 8
 
2.2%
회 6
 
1.7%
Other values (102) 206
57.4%
ASCII
ValueCountFrequency (%)
( 45
47.4%
) 45
47.4%
5
 
5.3%

최종수정일자
Date

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
Minimum2011-11-29 11:22:13
Maximum2024-02-22 13:10:12
2024-04-06T22:39:32.582281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T22:39:32.713729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
I
32 
U
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 32
59.3%
U 22
40.7%

Length

2024-04-06T22:39:32.835613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:32.943596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 32
59.3%
u 22
40.7%

데이터갱신일자
Categorical

Distinct22
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
2019-03-30 02:20:09.0
31 
2022-11-02 00:07:00.0
 
3
2019-11-14 02:40:00.0
 
1
2021-05-16 02:40:00.0
 
1
2021-12-02 22:09:00.0
 
1
Other values (17)
17 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique20 ?
Unique (%)37.0%

Sample

1st row2019-03-30 02:20:09.0
2nd row2019-03-30 02:20:09.0
3rd row2022-12-03 00:03:00.0
4th row2019-03-30 02:20:09.0
5th row2019-11-14 02:40:00.0

Common Values

ValueCountFrequency (%)
2019-03-30 02:20:09.0 31
57.4%
2022-11-02 00:07:00.0 3
 
5.6%
2019-11-14 02:40:00.0 1
 
1.9%
2021-05-16 02:40:00.0 1
 
1.9%
2021-12-02 22:09:00.0 1
 
1.9%
2021-10-17 02:40:00.0 1
 
1.9%
2020-05-21 02:40:00.0 1
 
1.9%
2023-11-30 23:08:00.0 1
 
1.9%
2022-12-09 00:06:00.0 1
 
1.9%
2020-07-31 02:40:00.0 1
 
1.9%
Other values (12) 12
 
22.2%

Length

2024-04-06T22:39:33.047406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-03-30 31
28.7%
02:20:09.0 31
28.7%
02:40:00.0 10
 
9.3%
2022-11-02 3
 
2.8%
00:07:00.0 3
 
2.8%
2022-12-01 2
 
1.9%
2023-12-01 2
 
1.9%
23:08:00.0 2
 
1.9%
2021-07-18 1
 
0.9%
2020-08-14 1
 
0.9%
Other values (22) 22
20.4%

업태구분명
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing50
Missing (%)92.6%
Memory size564.0 B
2024-04-06T22:39:33.193729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length18.75
Min length16

Characters and Unicode

Total characters75
Distinct characters30
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row폐기물처리 및 오염방지시설 건설업
2nd row환경 관련 엔지니어링 서비스업
3rd row환경컨설팅 및 관련 엔지니어링 서비스업
4th row환경상담 및 관련 엔지니어링 서비스업
ValueCountFrequency (%)
및 3
16.7%
관련 3
16.7%
엔지니어링 3
16.7%
서비스업 3
16.7%
폐기물처리 1
 
5.6%
오염방지시설 1
 
5.6%
건설업 1
 
5.6%
환경 1
 
5.6%
환경컨설팅 1
 
5.6%
환경상담 1
 
5.6%
2024-04-06T22:39:33.453505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
18.7%
지 4
 
5.3%
업 4
 
5.3%
환 3
 
4.0%
관 3
 
4.0%
경 3
 
4.0%
니 3
 
4.0%
어 3
 
4.0%
설 3
 
4.0%
링 3
 
4.0%
Other values (20) 32
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61
81.3%
Space Separator 14
 
18.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4
 
6.6%
업 4
 
6.6%
환 3
 
4.9%
관 3
 
4.9%
경 3
 
4.9%
니 3
 
4.9%
어 3
 
4.9%
설 3
 
4.9%
링 3
 
4.9%
서 3
 
4.9%
Other values (19) 29
47.5%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61
81.3%
Common 14
 
18.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4
 
6.6%
업 4
 
6.6%
환 3
 
4.9%
관 3
 
4.9%
경 3
 
4.9%
니 3
 
4.9%
어 3
 
4.9%
설 3
 
4.9%
링 3
 
4.9%
서 3
 
4.9%
Other values (19) 29
47.5%
Common
ValueCountFrequency (%)
14
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61
81.3%
ASCII 14
 
18.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
100.0%
Hangul
ValueCountFrequency (%)
지 4
 
6.6%
업 4
 
6.6%
환 3
 
4.9%
관 3
 
4.9%
경 3
 
4.9%
니 3
 
4.9%
어 3
 
4.9%
설 3
 
4.9%
링 3
 
4.9%
서 3
 
4.9%
Other values (19) 29
47.5%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)81.1%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean191378.23
Minimum189604.96
Maximum194632.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:33.574388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189604.96
5-th percentile189955.52
Q1190364.65
median190923.55
Q3192591.24
95-th percentile193551.63
Maximum194632.53
Range5027.562
Interquartile range (IQR)2226.5907

Descriptive statistics

Standard deviation1291.6691
Coefficient of variation (CV)0.0067493001
Kurtosis-0.65829821
Mean191378.23
Median Absolute Deviation (MAD)558.89931
Skewness0.78410428
Sum10143046
Variance1668409
MonotonicityNot monotonic
2024-04-06T22:39:33.683098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
190364.652010662 6
 
11.1%
190996.357288859 4
 
7.4%
190162.670939357 2
 
3.7%
192880.946054063 2
 
3.7%
193469.554731741 1
 
1.9%
192585.693382087 1
 
1.9%
190161.737344082 1
 
1.9%
189700.355755718 1
 
1.9%
190923.551317757 1
 
1.9%
193345.22196413 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
189604.964351874 1
 
1.9%
189700.355755718 1
 
1.9%
189849.410292461 1
 
1.9%
190026.251961332 1
 
1.9%
190144.229279951 1
 
1.9%
190161.737344082 1
 
1.9%
190162.670939357 2
 
3.7%
190359.568822627 1
 
1.9%
190364.652010662 6
11.1%
190372.127120283 1
 
1.9%
ValueCountFrequency (%)
194632.526367463 1
1.9%
193781.852246267 1
1.9%
193674.743726431 1
1.9%
193469.554731741 1
1.9%
193359.669097585 1
1.9%
193345.22196413 1
1.9%
193289.927062166 1
1.9%
193119.936048189 1
1.9%
193065.323272281 1
1.9%
192880.946054063 2
3.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct43
Distinct (%)81.1%
Missing1
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean446682.78
Minimum443783.74
Maximum448642.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:33.794443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum443783.74
5-th percentile444978.11
Q1446361.89
median446888.9
Q3447167.25
95-th percentile448058.49
Maximum448642.11
Range4858.3725
Interquartile range (IQR)805.36316

Descriptive statistics

Standard deviation952.99304
Coefficient of variation (CV)0.0021334896
Kurtosis1.7785481
Mean446682.78
Median Absolute Deviation (MAD)406.29066
Skewness-0.98171466
Sum23674187
Variance908195.74
MonotonicityNot monotonic
2024-04-06T22:39:33.906117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
447158.946262059 6
 
11.1%
445841.377603245 4
 
7.4%
446925.941984211 2
 
3.7%
446664.78738442 2
 
3.7%
446508.068667777 1
 
1.9%
447295.194165729 1
 
1.9%
446125.33590618 1
 
1.9%
446888.903509382 1
 
1.9%
446575.396546634 1
 
1.9%
446531.983116649 1
 
1.9%
Other values (33) 33
61.1%
ValueCountFrequency (%)
443783.73995296 1
 
1.9%
443928.909668748 1
 
1.9%
444826.274708509 1
 
1.9%
445079.327011963 1
 
1.9%
445114.03290833 1
 
1.9%
445548.79737092 1
 
1.9%
445841.377603245 4
7.4%
445883.474973877 1
 
1.9%
446125.33590618 1
 
1.9%
446314.681885687 1
 
1.9%
ValueCountFrequency (%)
448642.112414847 1
1.9%
448289.617887109 1
1.9%
448218.446478138 1
1.9%
447951.84799243 1
1.9%
447523.1165117 1
1.9%
447519.44510272 1
1.9%
447499.48254247 1
1.9%
447494.221918799 1
1.9%
447406.799650264 1
1.9%
447334.294244614 1
1.9%

실험실면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
51 
0
 
3

Length

Max length4
Median length4
Mean length3.8333333
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> 51
94.4%
0 3
 
5.6%

Length

2024-04-06T22:39:34.018488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:34.107217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
94.4%
0 3
 
5.6%

사업장구분명
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
환경전문공사업
42 
<NA>
12 

Length

Max length7
Median length7
Mean length6.3333333
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 42
77.8%
<NA> 12
 
22.2%

Length

2024-04-06T22:39:34.199209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:34.285583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 42
77.8%
na 12
 
22.2%

영업소면적
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
50 
0
 
2
28
 
1
1590
 
1

Length

Max length4
Median length4
Mean length3.8518519
Min length1

Unique

Unique2 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
92.6%
0 2
 
3.7%
28 1
 
1.9%
1590 1
 
1.9%

Length

2024-04-06T22:39:34.387088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:34.482884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
92.6%
0 2
 
3.7%
28 1
 
1.9%
1590 1
 
1.9%

위탁업체명
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing51
Missing (%)94.4%
Memory size564.0 B
2024-04-06T22:39:34.628650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.6666667
Min length8

Characters and Unicode

Total characters26
Distinct characters16
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

Unique3 ?
Unique (%)100.0%

Sample

1st row보성환경이엔텍(주)
2nd row(주)한경이테크
3rd row(주)청담이엠텍
ValueCountFrequency (%)
보성환경이엔텍(주 1
33.3%
주)한경이테크 1
33.3%
주)청담이엠텍 1
33.3%
2024-04-06T22:39:34.884725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 3
11.5%
( 3
11.5%
주 3
11.5%
) 3
11.5%
경 2
 
7.7%
텍 2
 
7.7%
보 1
 
3.8%
성 1
 
3.8%
환 1
 
3.8%
엔 1
 
3.8%
Other values (6) 6
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20
76.9%
Open Punctuation 3
 
11.5%
Close Punctuation 3
 
11.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3
15.0%
주 3
15.0%
경 2
10.0%
텍 2
10.0%
보 1
 
5.0%
성 1
 
5.0%
환 1
 
5.0%
엔 1
 
5.0%
한 1
 
5.0%
테 1
 
5.0%
Other values (4) 4
20.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20
76.9%
Common 6
 
23.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3
15.0%
주 3
15.0%
경 2
10.0%
텍 2
10.0%
보 1
 
5.0%
성 1
 
5.0%
환 1
 
5.0%
엔 1
 
5.0%
한 1
 
5.0%
테 1
 
5.0%
Other values (4) 4
20.0%
Common
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20
76.9%
ASCII 6
 
23.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 3
15.0%
주 3
15.0%
경 2
10.0%
텍 2
10.0%
보 1
 
5.0%
성 1
 
5.0%
환 1
 
5.0%
엔 1
 
5.0%
한 1
 
5.0%
테 1
 
5.0%
Other values (4) 4
20.0%
ASCII
ValueCountFrequency (%)
( 3
50.0%
) 3
50.0%

실험실지역코드
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)54.2%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean1.1560119 × 109
Minimum1.156011 × 109
Maximum1.1560133 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:35.280895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.156011 × 109
5-th percentile1.156011 × 109
Q11.1560111 × 109
median1.1560118 × 109
Q31.1560127 × 109
95-th percentile1.1560132 × 109
Maximum1.1560133 × 109
Range2300
Interquartile range (IQR)1625

Descriptive statistics

Standard deviation827.41741
Coefficient of variation (CV)7.1575163 × 10-7
Kurtosis-1.5805916
Mean1.1560119 × 109
Median Absolute Deviation (MAD)800
Skewness0.23515616
Sum2.7744286 × 1010
Variance684619.57
MonotonicityNot monotonic
2024-04-06T22:39:35.378248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1156011000 6
 
11.1%
1156012700 3
 
5.6%
1156011100 2
 
3.7%
1156012100 2
 
3.7%
1156011800 2
 
3.7%
1156012800 2
 
3.7%
1156011200 1
 
1.9%
1156013200 1
 
1.9%
1156013300 1
 
1.9%
1156012600 1
 
1.9%
Other values (3) 3
 
5.6%
(Missing) 30
55.6%
ValueCountFrequency (%)
1156011000 6
11.1%
1156011100 2
 
3.7%
1156011200 1
 
1.9%
1156011400 1
 
1.9%
1156011600 1
 
1.9%
1156011800 2
 
3.7%
1156012100 2
 
3.7%
1156012600 1
 
1.9%
1156012700 3
5.6%
1156012800 2
 
3.7%
ValueCountFrequency (%)
1156013300 1
 
1.9%
1156013200 1
 
1.9%
1156012900 1
 
1.9%
1156012800 2
3.7%
1156012700 3
5.6%
1156012600 1
 
1.9%
1156012100 2
3.7%
1156011800 2
3.7%
1156011600 1
 
1.9%
1156011400 1
 
1.9%

실험실우편번호
Real number (ℝ)

MISSING 

Distinct13
Distinct (%)72.2%
Missing36
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean150270.06
Minimum150010
Maximum150890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:35.477614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum150010
5-th percentile150010
Q1150044.5
median150102.5
Q3150572.75
95-th percentile150842.4
Maximum150890
Range880
Interquartile range (IQR)528.25

Descriptive statistics

Standard deviation349.52211
Coefficient of variation (CV)0.0023259598
Kurtosis-0.86390391
Mean150270.06
Median Absolute Deviation (MAD)75.5
Skewness1.0715931
Sum2704861
Variance122165.7
MonotonicityNot monotonic
2024-04-06T22:39:35.569000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
150010 4
 
7.4%
150103 2
 
3.7%
150104 2
 
3.7%
150890 1
 
1.9%
150729 1
 
1.9%
150800 1
 
1.9%
150834 1
 
1.9%
150056 1
 
1.9%
150813 1
 
1.9%
150102 1
 
1.9%
Other values (3) 3
 
5.6%
(Missing) 36
66.7%
ValueCountFrequency (%)
150010 4
7.4%
150044 1
 
1.9%
150046 1
 
1.9%
150056 1
 
1.9%
150093 1
 
1.9%
150102 1
 
1.9%
150103 2
3.7%
150104 2
3.7%
150729 1
 
1.9%
150800 1
 
1.9%
ValueCountFrequency (%)
150890 1
1.9%
150834 1
1.9%
150813 1
1.9%
150800 1
1.9%
150729 1
1.9%
150104 2
3.7%
150103 2
3.7%
150102 1
1.9%
150093 1
1.9%
150056 1
1.9%

실험실산
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
30 
1
24 

Length

Max length4
Median length4
Mean length2.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
55.6%
1 24
44.4%

Length

2024-04-06T22:39:35.676581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:35.763221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
55.6%
1 24
44.4%

실험실번지
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)83.3%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean288.5
Minimum1
Maximum4403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:35.844423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q113.75
median45
Q3254
95-th percentile632.05
Maximum4403
Range4402
Interquartile range (IQR)240.25

Descriptive statistics

Standard deviation890.65257
Coefficient of variation (CV)3.087184
Kurtosis22.291383
Mean288.5
Median Absolute Deviation (MAD)36
Skewness4.6602441
Sum6924
Variance793262
MonotonicityNot monotonic
2024-04-06T22:39:35.940241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 3
 
5.6%
46 2
 
3.7%
254 2
 
3.7%
55 1
 
1.9%
60 1
 
1.9%
20 1
 
1.9%
18 1
 
1.9%
121 1
 
1.9%
281 1
 
1.9%
16 1
 
1.9%
Other values (10) 10
 
18.5%
(Missing) 30
55.6%
ValueCountFrequency (%)
1 3
5.6%
7 1
 
1.9%
11 1
 
1.9%
13 1
 
1.9%
14 1
 
1.9%
16 1
 
1.9%
18 1
 
1.9%
20 1
 
1.9%
43 1
 
1.9%
44 1
 
1.9%
ValueCountFrequency (%)
4403 1
1.9%
694 1
1.9%
281 1
1.9%
265 1
1.9%
256 1
1.9%
254 2
3.7%
121 1
1.9%
60 1
1.9%
55 1
1.9%
46 2
3.7%

실험실호
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)75.0%
Missing38
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:36.027130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5.5
Q320.25
95-th percentile102.75
Maximum168
Range167
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation44.435721
Coefficient of variation (CV)1.8137029
Kurtosis7.4734166
Mean24.5
Median Absolute Deviation (MAD)3
Skewness2.6699174
Sum392
Variance1974.5333
MonotonicityNot monotonic
2024-04-06T22:39:36.133325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
3 3
 
5.6%
5 2
 
3.7%
1 2
 
3.7%
6 1
 
1.9%
58 1
 
1.9%
7 1
 
1.9%
2 1
 
1.9%
168 1
 
1.9%
21 1
 
1.9%
20 1
 
1.9%
Other values (2) 2
 
3.7%
(Missing) 38
70.4%
ValueCountFrequency (%)
1 2
3.7%
2 1
 
1.9%
3 3
5.6%
5 2
3.7%
6 1
 
1.9%
7 1
 
1.9%
8 1
 
1.9%
20 1
 
1.9%
21 1
 
1.9%
58 1
 
1.9%
ValueCountFrequency (%)
168 1
 
1.9%
81 1
 
1.9%
58 1
 
1.9%
21 1
 
1.9%
20 1
 
1.9%
8 1
 
1.9%
7 1
 
1.9%
6 1
 
1.9%
5 2
3.7%
3 3
5.6%

실험실통
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

실험실반
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

실험실특수주소
Text

MISSING 

Distinct18
Distinct (%)85.7%
Missing33
Missing (%)61.1%
Memory size564.0 B
2024-04-06T22:39:36.309674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length8
Min length2

Characters and Unicode

Total characters168
Distinct characters80
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row조흥증권빌딩
2nd row기계산업진흥회 11층
3rd row대일빌딩 7층
4th row혜천빌딩 4층
5th row국원빌딩 4층
ValueCountFrequency (%)
2층 4
 
12.1%
4층 2
 
6.1%
11층 2
 
6.1%
1-819 1
 
3.0%
조흥증권빌딩 1
 
3.0%
430호 1
 
3.0%
lg에클라트빌딩 1
 
3.0%
63빌딩 1
 
3.0%
lg트윈타워 1
 
3.0%
205호 1
 
3.0%
Other values (18) 18
54.5%
2024-04-06T22:39:36.602776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
 
7.1%
12
 
7.1%
층 9
 
5.4%
빌 8
 
4.8%
딩 8
 
4.8%
2 6
 
3.6%
스 5
 
3.0%
호 5
 
3.0%
4 4
 
2.4%
0 4
 
2.4%
Other values (70) 95
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
66.1%
Decimal Number 35
 
20.8%
Space Separator 12
 
7.1%
Uppercase Letter 7
 
4.2%
Dash Punctuation 2
 
1.2%
Lowercase Letter 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 9
 
8.1%
빌 8
 
7.2%
딩 8
 
7.2%
스 5
 
4.5%
호 5
 
4.5%
이 4
 
3.6%
트 3
 
2.7%
에 3
 
2.7%
워 3
 
2.7%
타 3
 
2.7%
Other values (52) 60
54.1%
Decimal Number
ValueCountFrequency (%)
1 12
34.3%
2 6
17.1%
4 4
 
11.4%
0 4
 
11.4%
3 3
 
8.6%
5 2
 
5.7%
6 1
 
2.9%
9 1
 
2.9%
8 1
 
2.9%
7 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
G 2
28.6%
Z 1
14.3%
I 1
14.3%
B 1
14.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
66.1%
Common 49
29.2%
Latin 8
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 9
 
8.1%
빌 8
 
7.2%
딩 8
 
7.2%
스 5
 
4.5%
호 5
 
4.5%
이 4
 
3.6%
트 3
 
2.7%
에 3
 
2.7%
워 3
 
2.7%
타 3
 
2.7%
Other values (52) 60
54.1%
Common
ValueCountFrequency (%)
1 12
24.5%
12
24.5%
2 6
12.2%
4 4
 
8.2%
0 4
 
8.2%
3 3
 
6.1%
5 2
 
4.1%
- 2
 
4.1%
6 1
 
2.0%
9 1
 
2.0%
Other values (2) 2
 
4.1%
Latin
ValueCountFrequency (%)
L 2
25.0%
G 2
25.0%
Z 1
12.5%
I 1
12.5%
B 1
12.5%
e 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
66.1%
ASCII 57
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
21.1%
12
21.1%
2 6
10.5%
4 4
 
7.0%
0 4
 
7.0%
3 3
 
5.3%
5 2
 
3.5%
- 2
 
3.5%
L 2
 
3.5%
G 2
 
3.5%
Other values (8) 8
14.0%
Hangul
ValueCountFrequency (%)
층 9
 
8.1%
빌 8
 
7.2%
딩 8
 
7.2%
스 5
 
4.5%
호 5
 
4.5%
이 4
 
3.6%
트 3
 
2.7%
에 3
 
2.7%
워 3
 
2.7%
타 3
 
2.7%
Other values (52) 60
54.1%

실험실특수주소동
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing54
Missing (%)100.0%
Memory size618.0 B

실험실특수주소호
Categorical

IMBALANCE 

Distinct4
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
51 
2408
 
1
314
 
1
904
 
1

Length

Max length4
Median length4
Mean length3.962963
Min length3

Unique

Unique3 ?
Unique (%)5.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 51
94.4%
2408 1
 
1.9%
314 1
 
1.9%
904 1
 
1.9%

Length

2024-04-06T22:39:36.728460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:36.819466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
94.4%
2408 1
 
1.9%
314 1
 
1.9%
904 1
 
1.9%

실험실도로명주소시군구코드
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
30 
11560
24 

Length

Max length5
Median length4
Mean length4.4444444
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11560
2nd row11560
3rd row<NA>
4th row11560
5th row11560

Common Values

ValueCountFrequency (%)
<NA> 30
55.6%
11560 24
44.4%

Length

2024-04-06T22:39:36.924685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:37.026362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
55.6%
11560 24
44.4%

실험실도로명주소읍면동코드
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)50.0%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean1.1560119 × 109
Minimum1.156011 × 109
Maximum1.1560133 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:37.127060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.156011 × 109
5-th percentile1.156011 × 109
Q11.156011 × 109
median1.1560118 × 109
Q31.1560127 × 109
95-th percentile1.1560132 × 109
Maximum1.1560133 × 109
Range2300
Interquartile range (IQR)1700

Descriptive statistics

Standard deviation846.12287
Coefficient of variation (CV)7.3193267 × 10-7
Kurtosis-1.6341821
Mean1.1560119 × 109
Median Absolute Deviation (MAD)800
Skewness0.259527
Sum2.7744285 × 1010
Variance715923.91
MonotonicityNot monotonic
2024-04-06T22:39:37.246979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1156011000 7
 
13.0%
1156012700 3
 
5.6%
1156011100 2
 
3.7%
1156012100 2
 
3.7%
1156011800 2
 
3.7%
1156012800 2
 
3.7%
1156011200 1
 
1.9%
1156013200 1
 
1.9%
1156013300 1
 
1.9%
1156012600 1
 
1.9%
Other values (2) 2
 
3.7%
(Missing) 30
55.6%
ValueCountFrequency (%)
1156011000 7
13.0%
1156011100 2
 
3.7%
1156011200 1
 
1.9%
1156011400 1
 
1.9%
1156011800 2
 
3.7%
1156012100 2
 
3.7%
1156012600 1
 
1.9%
1156012700 3
5.6%
1156012800 2
 
3.7%
1156012900 1
 
1.9%
ValueCountFrequency (%)
1156013300 1
 
1.9%
1156013200 1
 
1.9%
1156012900 1
 
1.9%
1156012800 2
3.7%
1156012700 3
5.6%
1156012600 1
 
1.9%
1156012100 2
3.7%
1156011800 2
3.7%
1156011400 1
 
1.9%
1156011200 1
 
1.9%

실험실도로명주소읍면동구분
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
30 
1
24 

Length

Max length4
Median length4
Mean length2.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
55.6%
1 24
44.4%

Length

2024-04-06T22:39:37.382277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:37.484887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
55.6%
1 24
44.4%

실험실도로명주소코드
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)91.7%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean3447460.3
Minimum2005008
Maximum4154719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:37.594326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005008
5-th percentile2250305.1
Q13118003.2
median3118021.5
Q34154095.2
95-th percentile4154701.6
Maximum4154719
Range2149711
Interquartile range (IQR)1036092

Descriptive statistics

Standard deviation672886.15
Coefficient of variation (CV)0.19518314
Kurtosis-0.63306598
Mean3447460.3
Median Absolute Deviation (MAD)559007
Skewness-0.37408959
Sum82739048
Variance4.5277577 × 1011
MonotonicityNot monotonic
2024-04-06T22:39:37.715311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3118016 2
 
3.7%
3005074 2
 
3.7%
2005008 1
 
1.9%
3118006 1
 
1.9%
4154066 1
 
1.9%
3118001 1
 
1.9%
2118001 1
 
1.9%
4154087 1
 
1.9%
4154099 1
 
1.9%
4154605 1
 
1.9%
Other values (12) 12
 
22.2%
(Missing) 30
55.6%
ValueCountFrequency (%)
2005008 1
1.9%
2118001 1
1.9%
3000028 1
1.9%
3005074 2
3.7%
3118001 1
1.9%
3118004 1
1.9%
3118006 1
1.9%
3118007 1
1.9%
3118009 1
1.9%
3118016 2
3.7%
ValueCountFrequency (%)
4154719 1
1.9%
4154704 1
1.9%
4154688 1
1.9%
4154613 1
1.9%
4154605 1
1.9%
4154099 1
1.9%
4154094 1
1.9%
4154087 1
1.9%
4154074 1
1.9%
4154066 1
1.9%

실험실도로명특수주소
Text

MISSING 

Distinct23
Distinct (%)95.8%
Missing30
Missing (%)55.6%
Memory size564.0 B
2024-04-06T22:39:37.906371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length15.166667
Min length5

Characters and Unicode

Total characters364
Distinct characters84
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

Unique22 ?
Unique (%)91.7%

Sample

1st row(여의도동)
2nd row(여의도동)
3rd row (당산동1가,대일빌딩 7층)
4th row4층 (당산동2가, 혜천빌딩)
5th row(문래동3가)
ValueCountFrequency (%)
여의도동 3
 
6.4%
4층 2
 
4.3%
도림동 2
 
4.3%
한강오피스텔 1
 
2.1%
1-819 1
 
2.1%
9층 1
 
2.1%
904호 1
 
2.1%
양평동3가 1
 
2.1%
우림e-biz센터 1
 
2.1%
1
 
2.1%
Other values (33) 33
70.2%
2024-04-06T22:39:38.231262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31
 
8.5%
( 24
 
6.6%
) 24
 
6.6%
동 24
 
6.6%
, 18
 
4.9%
1 14
 
3.8%
가 13
 
3.6%
3 11
 
3.0%
4 11
 
3.0%
2 10
 
2.7%
Other values (74) 184
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
52.5%
Decimal Number 66
 
18.1%
Space Separator 31
 
8.5%
Open Punctuation 24
 
6.6%
Close Punctuation 24
 
6.6%
Other Punctuation 18
 
4.9%
Uppercase Letter 7
 
1.9%
Dash Punctuation 2
 
0.5%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
 
12.6%
가 13
 
6.8%
층 10
 
5.2%
도 9
 
4.7%
호 9
 
4.7%
평 7
 
3.7%
의 7
 
3.7%
여 7
 
3.7%
양 7
 
3.7%
딩 6
 
3.1%
Other values (53) 92
48.2%
Decimal Number
ValueCountFrequency (%)
1 14
21.2%
3 11
16.7%
4 11
16.7%
2 10
15.2%
0 9
13.6%
9 4
 
6.1%
5 3
 
4.5%
8 2
 
3.0%
7 1
 
1.5%
6 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
G 2
28.6%
B 1
14.3%
I 1
14.3%
Z 1
14.3%
Space Separator
ValueCountFrequency (%)
31
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
52.5%
Common 165
45.3%
Latin 8
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
 
12.6%
가 13
 
6.8%
층 10
 
5.2%
도 9
 
4.7%
호 9
 
4.7%
평 7
 
3.7%
의 7
 
3.7%
여 7
 
3.7%
양 7
 
3.7%
딩 6
 
3.1%
Other values (53) 92
48.2%
Common
ValueCountFrequency (%)
31
18.8%
( 24
14.5%
) 24
14.5%
, 18
10.9%
1 14
8.5%
3 11
 
6.7%
4 11
 
6.7%
2 10
 
6.1%
0 9
 
5.5%
9 4
 
2.4%
Other values (5) 9
 
5.5%
Latin
ValueCountFrequency (%)
L 2
25.0%
G 2
25.0%
B 1
12.5%
e 1
12.5%
I 1
12.5%
Z 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
52.5%
ASCII 173
47.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31
17.9%
( 24
13.9%
) 24
13.9%
, 18
10.4%
1 14
8.1%
3 11
 
6.4%
4 11
 
6.4%
2 10
 
5.8%
0 9
 
5.2%
9 4
 
2.3%
Other values (11) 17
9.8%
Hangul
ValueCountFrequency (%)
동 24
 
12.6%
가 13
 
6.8%
층 10
 
5.2%
도 9
 
4.7%
호 9
 
4.7%
평 7
 
3.7%
의 7
 
3.7%
여 7
 
3.7%
양 7
 
3.7%
딩 6
 
3.1%
Other values (53) 92
48.2%

실험실도로명주소건물층구분
Categorical

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
30 
0
24 

Length

Max length4
Median length4
Mean length2.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 30
55.6%
0 24
44.4%

Length

2024-04-06T22:39:38.383129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:38.517056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
55.6%
0 24
44.4%

실험실도로명주소건물본번호
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)91.7%
Missing30
Missing (%)55.6%
Infinite0
Infinite (%)0.0%
Mean120.91667
Minimum2
Maximum780
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2024-04-06T22:39:38.638724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.65
Q115.75
median46.5
Q3117.5
95-th percentile693.4
Maximum780
Range778
Interquartile range (IQR)101.75

Descriptive statistics

Standard deviation210.81888
Coefficient of variation (CV)1.7435056
Kurtosis7.2389623
Mean120.91667
Median Absolute Deviation (MAD)32.5
Skewness2.7989947
Sum2902
Variance44444.601
MonotonicityNot monotonic
2024-04-06T22:39:38.780124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
14 3
 
5.6%
16 1
 
1.9%
51 1
 
1.9%
15 1
 
1.9%
50 1
 
1.9%
128 1
 
1.9%
2 1
 
1.9%
43 1
 
1.9%
775 1
 
1.9%
780 1
 
1.9%
Other values (12) 12
 
22.2%
(Missing) 30
55.6%
ValueCountFrequency (%)
2 1
 
1.9%
3 1
 
1.9%
14 3
5.6%
15 1
 
1.9%
16 1
 
1.9%
17 1
 
1.9%
19 1
 
1.9%
22 1
 
1.9%
26 1
 
1.9%
43 1
 
1.9%
ValueCountFrequency (%)
780 1
1.9%
775 1
1.9%
231 1
1.9%
170 1
1.9%
146 1
1.9%
128 1
1.9%
114 1
1.9%
93 1
1.9%
82 1
1.9%
77 1
1.9%

실험실도로명주소건물부번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
50 
1
 
4

Length

Max length4
Median length4
Mean length3.7777778
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 50
92.6%
1 4
 
7.4%

Length

2024-04-06T22:39:38.925820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:39.039470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
92.6%
1 4
 
7.4%

실험실도로명주소우편번호
Categorical

IMBALANCE 

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
<NA>
51 
150010
 
2
7375
 
1

Length

Max length6
Median length4
Mean length4.0740741
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

1st row150010
2nd row150010
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 51
94.4%
150010 2
 
3.7%
7375 1
 
1.9%

Length

2024-04-06T22:39:39.171402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T22:39:39.290036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 51
94.4%
150010 2
 
3.7%
7375 1
 
1.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
0318000031800006720100000120100209<NA>3폐업2폐업20101021<NA><NA><NA>027675670<NA>null서울특별시 영등포구 여의도동 44-5 조흥증권빌딩서울특별시 영등포구 여의대방로69길 17 (여의도동)150010벽산엔지니어링(주)2014-12-04 13:09:22I2019-03-30 02:20:09.0<NA>193781.852246446488.190918<NA>환경전문공사업<NA><NA>11560110001508901445<NA><NA>조흥증권빌딩<NA><NA>11560115601100014154688(여의도동)017<NA>150010
1318000031800006720100000220100219<NA>3폐업2폐업20120221<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 여의도동 13-6 기계산업진흥회 11층서울특별시 영등포구 국회대로76길 22 (여의도동,기계산업진흥회 11층)<NA>(주)립코2012-02-23 10:22:29I2019-03-30 02:20:09.0<NA>193065.323272447494.221919<NA>환경전문공사업<NA><NA>11560110001507291136<NA><NA>기계산업진흥회 11층<NA><NA>11560115601100014154094(여의도동)022<NA>150010
231800003180000672010000032010-03-23<NA>3폐업2폐업2023-02-28<NA><NA><NA>0226362662<NA><NA>서울특별시 영등포구 영등포동8가 92 케이앤케이디지털타워 810호<NA><NA>아태수기엔지니어링(주)2023-02-28 17:28:57U2022-12-03 00:03:00.0<NA>191457.663413447179.850507<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
3318000031800006720100000420100323<NA>3폐업2폐업20101019<NA><NA><NA>0226752166<NA><NA>서울특별시 영등포구 당산동1가 256-58서울특별시 영등포구 당산로 82 (당산동1가)<NA>(주)대일휀스2011-11-29 11:39:05I2019-03-30 02:20:09.0<NA>190739.971123446640.996015<NA>환경전문공사업<NA><NA>1156011100150800125658<NA><NA>대일빌딩 7층<NA><NA>11560115601110013118004(당산동1가,대일빌딩 7층)082<NA><NA>
4318000031800006720100000520100323<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0226725565<NA><NA>서울특별시 영등포구 당산동2가 11 혜천빌딩 6층<NA><NA>(주)혜천산업2019-11-12 21:30:56U2019-11-14 02:40:00.0<NA>190578.837077446565.442677<NA>환경전문공사업<NA><NA>1156011200<NA>111<NA><NA><NA>혜천빌딩 4층<NA><NA>115601156011200141547044층 (당산동2가, 혜천빌딩)031<NA>
5318000031800006720100000620100323<NA>3폐업2폐업20140507<NA><NA><NA>0226328611<NA><NA>서울특별시 영등포구 문래동3가 46서울특별시 영등포구 문래북로 114 (문래동3가)<NA>씨제이대한통운 주식회사2014-06-17 09:17:21I2019-03-30 02:20:09.0<NA>190918.714723446361.891182<NA>환경전문공사업<NA><NA>1156012100150834146<NA><NA><NA><NA><NA><NA>11560115601210013118009(문래동3가)0114<NA><NA>
6318000031800006720100000720100323<NA>3폐업2폐업20130123<NA><NA><NA><NA><NA><NA>서울특별시 영등포구 신길동 4403서울특별시 영등포구 여의대방로 93-1 (신길동)<NA>(주)청우이엔이2013-07-29 14:33:48I2019-03-30 02:20:09.0<NA>192591.242714443928.909669<NA>환경전문공사업<NA><NA>115601320015005614403<NA><NA><NA>국원빌딩 4층<NA><NA>11560115601320013118028(신길동,국원빌딩 4층)0931<NA>
7318000031800006720100000820100323<NA>1영업/정상BBBB영업<NA><NA><NA><NA>8435076<NA><NA>서울특별시 영등포구 대림동 694-7서울특별시 영등포구 대림로 170-1 (대림동)<NA>일신엠텍(주)2015-07-21 13:32:42I2019-03-30 02:20:09.0<NA>191079.049803443783.739953<NA>환경전문공사업<NA><NA>115601330015081316947<NA><NA>2층<NA><NA>11560115601330013118027(대림동,2층)01701<NA>
831800003180000672010000092010-03-23<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0221643663<NA><NA>서울특별시 영등포구 문래동3가 55-7서울특별시 영등포구 당산로2길 12, 408호 (문래동3가, 에이스테크노타워)7299한국방진방음2023-12-05 21:41:58U2022-11-02 00:07:00.0<NA>190684.216398445883.474974<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9318000031800006720100001020100323<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0263333045<NA><NA>서울특별시 영등포구 양평동2가 43-3<NA><NA>(주)선진엔지니어링종합건축사사무소2015-04-15 10:48:44I2019-03-30 02:20:09.0<NA>189604.964352447003.012895<NA>환경전문공사업<NA><NA>11560126001501021433<NA><NA><NA><NA><NA>11560115601260014154719(양평동2가)019<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)실험실면적사업장구분명영업소면적위탁업체명실험실지역코드실험실우편번호실험실산실험실번지실험실호실험실통실험실반실험실특수주소실험실특수주소동실험실특수주소호실험실도로명주소시군구코드실험실도로명주소읍면동코드실험실도로명주소읍면동구분실험실도로명주소코드실험실도로명특수주소실험실도로명주소건물층구분실험실도로명주소건물본번호실험실도로명주소건물부번호실험실도로명주소우편번호
44318000031800006720170000220170321<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-788-8382<NA><NA><NA>서울특별시 영등포구 여의공원로 111, 9.10층 (여의도동, 여의도 태영빌딩)<NA>한국발전기술 주식회사2020-08-12 15:26:57U2020-08-14 02:40:00.0<NA>193359.669098447499.482542<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
45318000031800006720170000320170530<NA>3폐업2폐업<NA><NA><NA><NA>02-2679-3611<NA><NA><NA>서울특별시 영등포구 국회대로 529, 2층 (양평동3가, 대한제분빌딩)7218샤론이엠에스(주)2019-08-28 10:26:35U2019-08-30 02:40:00.0<NA>190544.933599447519.445103<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4631800003180000672017000042017-06-22<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2069-1972~3<NA><NA>서울특별시 영등포구 양평동1가 148-8서울특별시 영등포구 영등포로13길 14, 4층 (양평동1가)7272(주)서울프랜트2023-02-16 16:26:53U2022-12-01 23:08:00.0<NA>190144.22928446831.638554<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
47318000031800006720170000520171114<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-302-4077<NA><NA>서울특별시 영등포구 도림동 254-5 송덕빌딩서울특별시 영등포구 도신로 51, 302-1호 (도림동)7375(주)헵스2018-07-30 11:10:20I2019-03-30 02:20:09.0<NA>190938.730735444826.274709<NA>환경전문공사업<NA>(주)청담이엠텍1156011800<NA>12545<NA><NA>송덕빌딩<NA><NA>11560115601180013118006(도림동)051<NA>7375
48318000031800006720180000120180423<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6150-7433<NA><NA>서울특별시 영등포구 여의도동 23-10 삼성생명(주)여의도빌딩서울특별시 영등포구 국제금융로2길 24, 삼성생명(주)여의도빌딩 (여의도동)7325(주)동양2018-04-23 16:30:37I2019-03-30 02:20:09.0<NA>193289.927062446893.487525<NA>환경전문공사업1590<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
4931800003180000672018000022018-05-10<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2672-9900<NA><NA>서울특별시 영등포구 문래동6가 24-1 에이스하이테크시티2서울특별시 영등포구 선유로13길 25, 에이스하이테크시티2 516호 (문래동6가)7282(주)에코엔서비스2023-12-05 21:41:51U2022-11-02 00:07:00.0<NA>189849.410292446314.681886<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5031800003180000672020000012020-09-07<NA>4취소/말소/만료/정지/중지4폐쇄2024-02-20<NA><NA><NA>02-2068-1435<NA><NA>서울특별시 영등포구 양평동1가 120-1 영화빌딩서울특별시 영등포구 선유로27길 9, 영화빌딩 지층 2호 (양평동1가)7272(주)한성이엠아이2024-02-20 16:39:58U2023-12-01 22:02:00.0<NA>190162.670939446925.941984<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
51318000031800006720200000220201013<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0236677773<NA><NA>서울특별시 영등포구 양평동3가 46 이앤씨드림타워서울특별시 영등포구 선유로 146, 이앤씨드림타워 220호 (양평동3가)7255(주)에스에이치모빌리티2020-10-14 09:36:34I2020-10-16 00:23:10.0환경상담 및 관련 엔지니어링 서비스업190364.652011447158.946262<NA>환경전문공사업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5231800003180000672021000012021-09-09<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 영등포구 양평동3가 46 이앤씨드림타워 1108호서울특별시 영등포구 선유로 146, 이앤씨드림타워 1108호 (양평동3가)7255(주)보람이엔지2023-05-17 13:49:26U2022-12-04 23:09:00.0<NA>190364.652011447158.946262<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
5331800003180000672022000012022-10-28<NA>1영업/정상BBBB영업<NA><NA><NA><NA>027888223<NA><NA>서울특별시 영등포구 여의도동 28-1 전경련회관서울특별시 영등포구 여의대로 24, 전경련회관 34층 (여의도동)7320한국발전기술(주)2023-02-10 16:18:28U2022-12-01 23:02:00.0<NA>192880.946054446664.787384<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>