Overview

Dataset statistics

Number of variables8
Number of observations47
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory66.8 B

Variable types

Categorical2
Text6

Dataset

Description대한건설기계안전관리원의 건설기계 출장검사소에 대한 데이터이고, 출장소명, 소재지, 전화번호, FAX번호, 출장요일, 시설업체명, 대표자명에 대한 정보를 제공합니다.
Author(재)대한건설기계안전관리원
URLhttps://www.data.go.kr/data/15121896/fileData.do

Alerts

소재지 has unique valuesUnique
전화번호 has unique valuesUnique
FAX번호 has unique valuesUnique
시설업체명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2024-03-16 04:20:34.292557
Analysis finished2024-03-16 04:20:35.070923
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct16
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
대구
6 
경기
6 
경북
6 
서울
4 
북부
4 
Other values (11)
21 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique5 ?
Unique (%)10.6%

Sample

1st row서울
2nd row서울
3rd row서울
4th row서울
5th row부산

Common Values

ValueCountFrequency (%)
대구 6
12.8%
경기 6
12.8%
경북 6
12.8%
서울 4
8.5%
북부 4
8.5%
영서 4
8.5%
대전 3
6.4%
충남 3
6.4%
광주 2
 
4.3%
영동 2
 
4.3%
Other values (6) 7
14.9%

Length

2024-03-16T13:20:35.131848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구 6
12.8%
경기 6
12.8%
경북 6
12.8%
서울 4
8.5%
북부 4
8.5%
영서 4
8.5%
대전 3
6.4%
충남 3
6.4%
광주 2
 
4.3%
영동 2
 
4.3%
Other values (6) 7
14.9%

출장소명
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:35.335279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3191489
Min length2

Characters and Unicode

Total characters109
Distinct characters53
Distinct categories1 ?
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 (%)95.7%

Sample

1st row문산
2nd row파주
3rd row고양
4th row김포
5th row김해
ValueCountFrequency (%)
여주 2
 
4.3%
충주 1
 
2.1%
사천 1
 
2.1%
서산 1
 
2.1%
가평 1
 
2.1%
가평상면 1
 
2.1%
홍천 1
 
2.1%
제천 1
 
2.1%
양평 1
 
2.1%
동해 1
 
2.1%
Other values (36) 36
76.6%
2024-03-16T13:20:35.791411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 8
 
7.3%
양 7
 
6.4%
천 6
 
5.5%
산 5
 
4.6%
인 4
 
3.7%
부 4
 
3.7%
여 3
 
2.8%
포 3
 
2.8%
서 3
 
2.8%
성 3
 
2.8%
Other values (43) 63
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 8
 
7.3%
양 7
 
6.4%
천 6
 
5.5%
산 5
 
4.6%
인 4
 
3.7%
부 4
 
3.7%
여 3
 
2.8%
포 3
 
2.8%
서 3
 
2.8%
성 3
 
2.8%
Other values (43) 63
57.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 8
 
7.3%
양 7
 
6.4%
천 6
 
5.5%
산 5
 
4.6%
인 4
 
3.7%
부 4
 
3.7%
여 3
 
2.8%
포 3
 
2.8%
서 3
 
2.8%
성 3
 
2.8%
Other values (43) 63
57.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 8
 
7.3%
양 7
 
6.4%
천 6
 
5.5%
산 5
 
4.6%
인 4
 
3.7%
부 4
 
3.7%
여 3
 
2.8%
포 3
 
2.8%
서 3
 
2.8%
성 3
 
2.8%
Other values (43) 63
57.8%

소재지
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:36.041663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length17.574468
Min length12

Characters and Unicode

Total characters826
Distinct characters132
Distinct categories6 ?
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 (%)100.0%

Sample

1st row경기 파주시 문산읍 우계로430-13
2nd row경기 파주시 월롱면 도감로164
3rd row경기 고양시 일산동구 장진천길14-7
4th row경기 김포시 통진읍 옹정로17번길80
5th row경남 김해시 생림면 나전로189
ValueCountFrequency (%)
경기 16
 
9.3%
경북 10
 
5.8%
충남 5
 
2.9%
강원 3
 
1.7%
충북 3
 
1.7%
용인시 3
 
1.7%
경남 2
 
1.2%
양주시 2
 
1.2%
파주시 2
 
1.2%
가평군 2
 
1.2%
Other values (119) 124
72.1%
2024-03-16T13:20:36.421790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
15.1%
로 37
 
4.5%
경 31
 
3.8%
시 31
 
3.8%
1 27
 
3.3%
2 27
 
3.3%
3 22
 
2.7%
4 20
 
2.4%
7 20
 
2.4%
면 19
 
2.3%
Other values (122) 467
56.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 513
62.1%
Decimal Number 168
 
20.3%
Space Separator 125
 
15.1%
Dash Punctuation 14
 
1.7%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 37
 
7.2%
경 31
 
6.0%
시 31
 
6.0%
면 19
 
3.7%
기 18
 
3.5%
북 18
 
3.5%
천 16
 
3.1%
군 14
 
2.7%
산 14
 
2.7%
길 14
 
2.7%
Other values (108) 301
58.7%
Decimal Number
ValueCountFrequency (%)
1 27
16.1%
2 27
16.1%
3 22
13.1%
4 20
11.9%
7 20
11.9%
9 13
7.7%
5 12
7.1%
8 11
6.5%
6 8
 
4.8%
0 8
 
4.8%
Space Separator
ValueCountFrequency (%)
125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 513
62.1%
Common 313
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 37
 
7.2%
경 31
 
6.0%
시 31
 
6.0%
면 19
 
3.7%
기 18
 
3.5%
북 18
 
3.5%
천 16
 
3.1%
군 14
 
2.7%
산 14
 
2.7%
길 14
 
2.7%
Other values (108) 301
58.7%
Common
ValueCountFrequency (%)
125
39.9%
1 27
 
8.6%
2 27
 
8.6%
3 22
 
7.0%
4 20
 
6.4%
7 20
 
6.4%
- 14
 
4.5%
9 13
 
4.2%
5 12
 
3.8%
8 11
 
3.5%
Other values (4) 22
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 513
62.1%
ASCII 313
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
39.9%
1 27
 
8.6%
2 27
 
8.6%
3 22
 
7.0%
4 20
 
6.4%
7 20
 
6.4%
- 14
 
4.5%
9 13
 
4.2%
5 12
 
3.8%
8 11
 
3.5%
Other values (4) 22
 
7.0%
Hangul
ValueCountFrequency (%)
로 37
 
7.2%
경 31
 
6.0%
시 31
 
6.0%
면 19
 
3.7%
기 18
 
3.5%
북 18
 
3.5%
천 16
 
3.1%
군 14
 
2.7%
산 14
 
2.7%
길 14
 
2.7%
Other values (108) 301
58.7%

전화번호
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:36.647063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021277
Min length12

Characters and Unicode

Total characters565
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

Unique47 ?
Unique (%)100.0%

Sample

1st row031)952-2373
2nd row031)949-8075
3rd row031)905-5100
4th row031)983-6626
5th row055)332-9142
ValueCountFrequency (%)
031)952-2373 1
 
2.1%
031)871-8491 1
 
2.1%
031)585-6360 1
 
2.1%
033)434-7701 1
 
2.1%
043)646-2311 1
 
2.1%
031)881-1079 1
 
2.1%
031)771-6665 1
 
2.1%
033)534-7799 1
 
2.1%
033)462-2241 1
 
2.1%
043)853-3045 1
 
2.1%
Other values (37) 37
78.7%
2024-03-16T13:20:37.026201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 79
14.0%
3 74
13.1%
5 63
11.2%
1 54
9.6%
4 48
8.5%
) 47
8.3%
- 47
8.3%
2 36
6.4%
8 34
6.0%
6 31
 
5.5%
Other values (2) 52
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 471
83.4%
Close Punctuation 47
 
8.3%
Dash Punctuation 47
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
16.8%
3 74
15.7%
5 63
13.4%
1 54
11.5%
4 48
10.2%
2 36
7.6%
8 34
7.2%
6 31
 
6.6%
7 27
 
5.7%
9 25
 
5.3%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 565
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 79
14.0%
3 74
13.1%
5 63
11.2%
1 54
9.6%
4 48
8.5%
) 47
8.3%
- 47
8.3%
2 36
6.4%
8 34
6.0%
6 31
 
5.5%
Other values (2) 52
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 79
14.0%
3 74
13.1%
5 63
11.2%
1 54
9.6%
4 48
8.5%
) 47
8.3%
- 47
8.3%
2 36
6.4%
8 34
6.0%
6 31
 
5.5%
Other values (2) 52
9.2%

FAX번호
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:37.332659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021277
Min length12

Characters and Unicode

Total characters565
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

Unique47 ?
Unique (%)100.0%

Sample

1st row031)952-3399
2nd row031)949-2177
3rd row031)905-4296
4th row031)983-6624
5th row055)333-4392
ValueCountFrequency (%)
031)952-3399 1
 
2.1%
031)871-8490 1
 
2.1%
031)585-6362 1
 
2.1%
033)435-7701 1
 
2.1%
043)645-1338 1
 
2.1%
031)881-1078 1
 
2.1%
031)772-4443 1
 
2.1%
033)534-7773 1
 
2.1%
033)462-2243 1
 
2.1%
043)853-5849 1
 
2.1%
Other values (37) 37
78.7%
2024-03-16T13:20:37.752551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71
12.6%
3 71
12.6%
1 57
10.1%
5 55
9.7%
4 52
9.2%
) 47
8.3%
- 47
8.3%
8 40
7.1%
7 35
6.2%
2 31
5.5%
Other values (2) 59
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 471
83.4%
Close Punctuation 47
 
8.3%
Dash Punctuation 47
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 71
15.1%
3 71
15.1%
1 57
12.1%
5 55
11.7%
4 52
11.0%
8 40
8.5%
7 35
7.4%
2 31
6.6%
9 30
6.4%
6 29
6.2%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 565
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 71
12.6%
3 71
12.6%
1 57
10.1%
5 55
9.7%
4 52
9.2%
) 47
8.3%
- 47
8.3%
8 40
7.1%
7 35
6.2%
2 31
5.5%
Other values (2) 59
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 71
12.6%
3 71
12.6%
1 57
10.1%
5 55
9.7%
4 52
9.2%
) 47
8.3%
- 47
8.3%
8 40
7.1%
7 35
6.2%
2 31
5.5%
Other values (2) 59
10.4%

출장요일
Categorical

Distinct21
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size508.0 B
화
8 
목
5 
화, 금
3 
수
3 
금(2주1회)
3 
Other values (16)
25 

Length

Max length10
Median length9
Mean length3.893617
Min length1

Unique

Unique9 ?
Unique (%)19.1%

Sample

1st row화
2nd row목
3rd row수
4th row월(2주1회)
5th row화

Common Values

ValueCountFrequency (%)
화 8
17.0%
목 5
 
10.6%
화, 금 3
 
6.4%
수 3
 
6.4%
금(2주1회) 3
 
6.4%
수(2주1회) 3
 
6.4%
금 3
 
6.4%
화, 목 2
 
4.3%
월 2
 
4.3%
월, 목 2
 
4.3%
Other values (11) 13
27.7%

Length

2024-03-16T13:20:37.944537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화 17
23.9%
목 12
16.9%
금 11
15.5%
수 9
12.7%
월 9
12.7%
금(2주1회 3
 
4.2%
수(2주1회 3
 
4.2%
월(2주1회 2
 
2.8%
4주 2
 
2.8%
월(2주 1
 
1.4%
Other values (2) 2
 
2.8%

시설업체명
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:38.265307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.4468085
Min length4

Characters and Unicode

Total characters397
Distinct characters92
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

Unique47 ?
Unique (%)100.0%

Sample

1st row(주)진흥공업사
2nd row(주)파주현대상용서비스
3rd row원일현대서비스
4th row(주)루돌프앤특장
5th row유진종합자동차정비공장
ValueCountFrequency (%)
주)진흥공업사 1
 
2.1%
주)광진자동차종합센타 1
 
2.1%
가평상용현대서비스 1
 
2.1%
주)홍천중공업 1
 
2.1%
첨단공업(주 1
 
2.1%
대광현대서비스 1
 
2.1%
㈜양평1급종합자동차정비서비스 1
 
2.1%
주)디에치에스 1
 
2.1%
대일공업사 1
 
2.1%
충주자동차공업사 1
 
2.1%
Other values (37) 37
78.7%
2024-03-16T13:20:38.736667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 26
 
6.5%
비 24
 
6.0%
( 23
 
5.8%
) 23
 
5.8%
공 19
 
4.8%
정 16
 
4.0%
대 15
 
3.8%
업 14
 
3.5%
동 14
 
3.5%
사 13
 
3.3%
Other values (82) 210
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 348
87.7%
Open Punctuation 23
 
5.8%
Close Punctuation 23
 
5.8%
Other Symbol 2
 
0.5%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 26
 
7.5%
비 24
 
6.9%
공 19
 
5.5%
정 16
 
4.6%
대 15
 
4.3%
업 14
 
4.0%
동 14
 
4.0%
사 13
 
3.7%
스 12
 
3.4%
자 12
 
3.4%
Other values (78) 183
52.6%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 350
88.2%
Common 47
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 26
 
7.4%
비 24
 
6.9%
공 19
 
5.4%
정 16
 
4.6%
대 15
 
4.3%
업 14
 
4.0%
동 14
 
4.0%
사 13
 
3.7%
스 12
 
3.4%
자 12
 
3.4%
Other values (79) 185
52.9%
Common
ValueCountFrequency (%)
( 23
48.9%
) 23
48.9%
1 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 348
87.7%
ASCII 47
 
11.8%
None 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 26
 
7.5%
비 24
 
6.9%
공 19
 
5.5%
정 16
 
4.6%
대 15
 
4.3%
업 14
 
4.0%
동 14
 
4.0%
사 13
 
3.7%
스 12
 
3.4%
자 12
 
3.4%
Other values (78) 183
52.6%
ASCII
ValueCountFrequency (%)
( 23
48.9%
) 23
48.9%
1 1
 
2.1%
None
ValueCountFrequency (%)
㈜ 2
100.0%

대표자
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2024-03-16T13:20:38.988824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.106383
Min length3

Characters and Unicode

Total characters146
Distinct characters76
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

Unique47 ?
Unique (%)100.0%

Sample

1st row강인석
2nd row정종필
3rd row강경석
4th row민복순
5th row노경준
ValueCountFrequency (%)
강인석 1
 
2.1%
손상수 1
 
2.1%
허기석 1
 
2.1%
이규성 1
 
2.1%
우광호 1
 
2.1%
임철수 1
 
2.1%
송한섭 1
 
2.1%
정상원 1
 
2.1%
문명근 1
 
2.1%
김서철 1
 
2.1%
Other values (38) 38
79.2%
2024-03-16T13:20:39.388121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 9
 
6.2%
상 8
 
5.5%
이 6
 
4.1%
정 5
 
3.4%
철 4
 
2.7%
석 4
 
2.7%
성 4
 
2.7%
영 4
 
2.7%
주 3
 
2.1%
규 3
 
2.1%
Other values (66) 96
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 144
98.6%
Space Separator 1
 
0.7%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
6.2%
상 8
 
5.6%
이 6
 
4.2%
정 5
 
3.5%
철 4
 
2.8%
석 4
 
2.8%
성 4
 
2.8%
영 4
 
2.8%
주 3
 
2.1%
규 3
 
2.1%
Other values (64) 94
65.3%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 144
98.6%
Common 2
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
6.2%
상 8
 
5.6%
이 6
 
4.2%
정 5
 
3.5%
철 4
 
2.8%
석 4
 
2.8%
성 4
 
2.8%
영 4
 
2.8%
주 3
 
2.1%
규 3
 
2.1%
Other values (64) 94
65.3%
Common
ValueCountFrequency (%)
1
50.0%
, 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 144
98.6%
ASCII 2
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 9
 
6.2%
상 8
 
5.6%
이 6
 
4.2%
정 5
 
3.5%
철 4
 
2.8%
석 4
 
2.8%
성 4
 
2.8%
영 4
 
2.8%
주 3
 
2.1%
규 3
 
2.1%
Other values (64) 94
65.3%
ASCII
ValueCountFrequency (%)
1
50.0%
, 1
50.0%

Correlations

2024-03-16T13:20:39.506322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역출장소명소재지전화번호FAX번호출장요일시설업체명대표자
지역1.0000.9841.0001.0001.0000.4911.0001.000
출장소명0.9841.0001.0001.0001.0000.9061.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
FAX번호1.0001.0001.0001.0001.0001.0001.0001.000
출장요일0.4910.9061.0001.0001.0001.0001.0001.000
시설업체명1.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.000
2024-03-16T13:20:39.665066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
출장요일지역
출장요일1.0000.108
지역0.1081.000
2024-03-16T13:20:39.772171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역출장요일
지역1.0000.108
출장요일0.1081.000

Missing values

2024-03-16T13:20:34.806197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T13:20:35.011104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

지역출장소명소재지전화번호FAX번호출장요일시설업체명대표자
0서울문산경기 파주시 문산읍 우계로430-13031)952-2373031)952-3399화(주)진흥공업사강인석
1서울파주경기 파주시 월롱면 도감로164031)949-8075031)949-2177목(주)파주현대상용서비스정종필
2서울고양경기 고양시 일산동구 장진천길14-7031)905-5100031)905-4296수원일현대서비스강경석
3서울김포경기 김포시 통진읍 옹정로17번길80031)983-6626031)983-6624월(2주1회)(주)루돌프앤특장민복순
4부산김해경남 김해시 생림면 나전로189055)332-9142055)333-4392화유진종합자동차정비공장노경준
5대구동부대구 동구 안심로59길33053)964-0055053)964-1458수, 금(주)보성정비박상하
6대구북부대구 북구 신천동로980053)382-5900053)382-2128금(2주1회)(주)창신종합중기정비이영출
7대구달성경북 고령군 성산면 동고령산단1길55054)954-7900054)954-7901화(주)유일정비김재목
8대구구미경북 구미시 비산로71-2054)464-0061054)464-0063화(주)성은종합정비공장김춘용
9대구김천경북 김천시 농공단지2길12054)430-2477054)432-2477목삼영중기정비장정익
지역출장소명소재지전화번호FAX번호출장요일시설업체명대표자
37전북군산전북 군산시 해망로528(소룡동)063)467-0303063)467-0307화, 목(유)세명자동차공업사박효순
38전북부안전북 부안군 동진면 봉황리493-2063)584-9535063)581-1256수강산자동차공업사황상식
39경북여주경북 영주시 구성로88번길172054)634-2122054)634-2093금영주종합정비공장김성득
40경북안동경북 안동시 공단로42054)858-5555054)858-1301월, 수안동종합정비공장민경수
41경북영천경북 영천시 오수5길102054)337-9900054)337-9907화그린종합정비공장김상훈
42경북울진경북 울진군 평해읍 동해대로723054)787-5555054)787-7755월(주)동경자동차종합정비황성기
43경북문경경북 문경시 신기공단2길5054)554-1422054)554-1522목(주)세일정지학
44경북상주경북 상주시 식산로195(화개동232)054)534-3333054)535-9808월(2주, 4주)대신자동차종합정비이주영
45경남사천경남 사천시 사천읍 구암두문로154-32055)852-4901055)855-1182월, 화, 수, 금현대종합정비배효자
46제주서귀포제주 서귀포 토평공단로127번 길47064)733-5059064)733-4925수(2주, 4주)상용건설기계이상용