Overview

Dataset statistics

Number of variables4
Number of observations56
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory34.4 B

Variable types

Text4

Dataset

Description전기안전관리대행업체현황
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202025

Alerts

업체명 has unique valuesUnique
대표자 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:31:46.450139
Analysis finished2024-03-14 01:31:46.794675
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-03-14T10:31:46.969118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.9107143
Min length4

Characters and Unicode

Total characters499
Distinct characters85
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row(주)케시
2nd row전북전기관리공사
3rd row한국전기관리소
4th row대한전기안전관리
5th row(유)호남전기안전관리
ValueCountFrequency (%)
주식회사 2
 
3.3%
주)케시 1
 
1.7%
동부전기안전관리 1
 
1.7%
주)셉코 1
 
1.7%
한일전기관리단 1
 
1.7%
유)고인돌전기안전관리 1
 
1.7%
대한전기안전관리소 1
 
1.7%
kens 1
 
1.7%
삼성전기관리공사 1
 
1.7%
신대한전기컨설팅 1
 
1.7%
Other values (49) 49
81.7%
2024-03-14T10:31:47.291691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 78
15.6%
기 44
 
8.8%
리 40
 
8.0%
관 39
 
7.8%
안 27
 
5.4%
( 24
 
4.8%
) 24
 
4.8%
유 21
 
4.2%
한 19
 
3.8%
사 16
 
3.2%
Other values (75) 167
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 435
87.2%
Open Punctuation 24
 
4.8%
Close Punctuation 24
 
4.8%
Uppercase Letter 10
 
2.0%
Space Separator 4
 
0.8%
Other Symbol 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 78
17.9%
기 44
 
10.1%
리 40
 
9.2%
관 39
 
9.0%
안 27
 
6.2%
유 21
 
4.8%
한 19
 
4.4%
사 16
 
3.7%
공 11
 
2.5%
소 10
 
2.3%
Other values (63) 130
29.9%
Uppercase Letter
ValueCountFrequency (%)
K 3
30.0%
E 2
20.0%
T 1
 
10.0%
O 1
 
10.0%
P 1
 
10.0%
S 1
 
10.0%
N 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
87.4%
Common 53
 
10.6%
Latin 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 78
17.9%
기 44
 
10.1%
리 40
 
9.2%
관 39
 
8.9%
안 27
 
6.2%
유 21
 
4.8%
한 19
 
4.4%
사 16
 
3.7%
공 11
 
2.5%
소 10
 
2.3%
Other values (64) 131
30.0%
Latin
ValueCountFrequency (%)
K 3
30.0%
E 2
20.0%
T 1
 
10.0%
O 1
 
10.0%
P 1
 
10.0%
S 1
 
10.0%
N 1
 
10.0%
Common
ValueCountFrequency (%)
( 24
45.3%
) 24
45.3%
4
 
7.5%
- 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 435
87.2%
ASCII 63
 
12.6%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 78
17.9%
기 44
 
10.1%
리 40
 
9.2%
관 39
 
9.0%
안 27
 
6.2%
유 21
 
4.8%
한 19
 
4.4%
사 16
 
3.7%
공 11
 
2.5%
소 10
 
2.3%
Other values (63) 130
29.9%
ASCII
ValueCountFrequency (%)
( 24
38.1%
) 24
38.1%
4
 
6.3%
K 3
 
4.8%
E 2
 
3.2%
T 1
 
1.6%
O 1
 
1.6%
P 1
 
1.6%
- 1
 
1.6%
S 1
 
1.6%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-03-14T10:31:47.501616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.2678571
Min length3

Characters and Unicode

Total characters239
Distinct characters88
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

Unique56 ?
Unique (%)100.0%

Sample

1st row이성실
2nd row한영규
3rd row서득석외6명
4th row김학열외3명
5th row최재열
ValueCountFrequency (%)
5명 2
 
3.2%
6명 2
 
3.2%
이성실 1
 
1.6%
김홍남 1
 
1.6%
신동호 1
 
1.6%
이태영외 1
 
1.6%
3명 1
 
1.6%
김혜순 1
 
1.6%
박진성외 1
 
1.6%
이승재 1
 
1.6%
Other values (51) 51
81.0%
2024-03-14T10:31:47.822517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
외 20
 
8.4%
명 18
 
7.5%
이 10
 
4.2%
김 10
 
4.2%
성 8
 
3.3%
7
 
2.9%
박 7
 
2.9%
정 6
 
2.5%
3 6
 
2.5%
장 5
 
2.1%
Other values (78) 142
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 211
88.3%
Decimal Number 19
 
7.9%
Space Separator 7
 
2.9%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 20
 
9.5%
명 18
 
8.5%
이 10
 
4.7%
김 10
 
4.7%
성 8
 
3.8%
박 7
 
3.3%
정 6
 
2.8%
장 5
 
2.4%
임 5
 
2.4%
대 4
 
1.9%
Other values (70) 118
55.9%
Decimal Number
ValueCountFrequency (%)
3 6
31.6%
6 4
21.1%
5 4
21.1%
2 3
15.8%
4 1
 
5.3%
7 1
 
5.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 211
88.3%
Common 28
 
11.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
외 20
 
9.5%
명 18
 
8.5%
이 10
 
4.7%
김 10
 
4.7%
성 8
 
3.8%
박 7
 
3.3%
정 6
 
2.8%
장 5
 
2.4%
임 5
 
2.4%
대 4
 
1.9%
Other values (70) 118
55.9%
Common
ValueCountFrequency (%)
7
25.0%
3 6
21.4%
6 4
14.3%
5 4
14.3%
2 3
10.7%
, 2
 
7.1%
4 1
 
3.6%
7 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 211
88.3%
ASCII 28
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
외 20
 
9.5%
명 18
 
8.5%
이 10
 
4.7%
김 10
 
4.7%
성 8
 
3.8%
박 7
 
3.3%
정 6
 
2.8%
장 5
 
2.4%
임 5
 
2.4%
대 4
 
1.9%
Other values (70) 118
55.9%
ASCII
ValueCountFrequency (%)
7
25.0%
3 6
21.4%
6 4
14.3%
5 4
14.3%
2 3
10.7%
, 2
 
7.1%
4 1
 
3.6%
7 1
 
3.6%

전화번호
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-03-14T10:31:48.038217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.053571
Min length12

Characters and Unicode

Total characters675
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

Unique54 ?
Unique (%)96.4%

Sample

1st row063-253-0300
2nd row063-858-1625
3rd row063-854-2221
4th row063-278-8771
5th row063-252-1341
ValueCountFrequency (%)
063-237-2100 2
 
3.6%
063-253-0300 1
 
1.8%
063-537-1921 1
 
1.8%
063-277-5678 1
 
1.8%
063-838-8600 1
 
1.8%
063-564-8885 1
 
1.8%
063-228-8771 1
 
1.8%
063-535-0401 1
 
1.8%
063-212-0996 1
 
1.8%
063-836-2297 1
 
1.8%
Other values (45) 45
80.4%
2024-03-14T10:31:48.335111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 112
16.6%
6 95
14.1%
0 94
13.9%
3 93
13.8%
2 77
11.4%
8 45
6.7%
1 43
 
6.4%
7 32
 
4.7%
5 31
 
4.6%
4 28
 
4.1%
Other values (2) 25
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 555
82.2%
Dash Punctuation 112
 
16.6%
Other Punctuation 8
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 95
17.1%
0 94
16.9%
3 93
16.8%
2 77
13.9%
8 45
8.1%
1 43
7.7%
7 32
 
5.8%
5 31
 
5.6%
4 28
 
5.0%
9 17
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Other Punctuation
ValueCountFrequency (%)
* 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 675
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 112
16.6%
6 95
14.1%
0 94
13.9%
3 93
13.8%
2 77
11.4%
8 45
6.7%
1 43
 
6.4%
7 32
 
4.7%
5 31
 
4.6%
4 28
 
4.1%
Other values (2) 25
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 112
16.6%
6 95
14.1%
0 94
13.9%
3 93
13.8%
2 77
11.4%
8 45
6.7%
1 43
 
6.4%
7 32
 
4.7%
5 31
 
4.6%
4 28
 
4.1%
Other values (2) 25
 
3.7%

주소
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-03-14T10:31:48.524883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length32
Mean length27.892857
Min length15

Characters and Unicode

Total characters1562
Distinct characters150
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 팔달로 322-7 (진북동 363-5)
2nd row익산시 서동로5길 13 (주현동 245-8)
3rd row익산시 서동로 147 (마동 364-6)
4th row전주시 완산구 솟대1길 49(삼천동1가 700-2)
5th row전주시 덕진구 금암2동 1585-4
ValueCountFrequency (%)
전주시 25
 
8.3%
완산구 18
 
6.0%
익산시 12
 
4.0%
덕진구 7
 
2.3%
군산시 7
 
2.3%
정읍시 6
 
2.0%
효자동3가 5
 
1.7%
영등동 4
 
1.3%
남원시 3
 
1.0%
중화산동2가 3
 
1.0%
Other values (205) 212
70.2%
2024-03-14T10:31:48.837243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
280
 
17.9%
1 84
 
5.4%
동 59
 
3.8%
2 59
 
3.8%
3 56
 
3.6%
- 56
 
3.6%
) 55
 
3.5%
( 55
 
3.5%
시 54
 
3.5%
산 51
 
3.3%
Other values (140) 753
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 688
44.0%
Decimal Number 422
27.0%
Space Separator 280
17.9%
Dash Punctuation 56
 
3.6%
Close Punctuation 55
 
3.5%
Open Punctuation 55
 
3.5%
Other Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
 
8.6%
시 54
 
7.8%
산 51
 
7.4%
로 35
 
5.1%
주 31
 
4.5%
전 30
 
4.4%
길 27
 
3.9%
구 26
 
3.8%
가 24
 
3.5%
완 18
 
2.6%
Other values (123) 333
48.4%
Decimal Number
ValueCountFrequency (%)
1 84
19.9%
2 59
14.0%
3 56
13.3%
5 51
12.1%
4 40
9.5%
6 37
8.8%
7 25
 
5.9%
0 25
 
5.9%
9 23
 
5.5%
8 22
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
/ 1
 
16.7%
@ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 874
56.0%
Hangul 688
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
 
8.6%
시 54
 
7.8%
산 51
 
7.4%
로 35
 
5.1%
주 31
 
4.5%
전 30
 
4.4%
길 27
 
3.9%
구 26
 
3.8%
가 24
 
3.5%
완 18
 
2.6%
Other values (123) 333
48.4%
Common
ValueCountFrequency (%)
280
32.0%
1 84
 
9.6%
2 59
 
6.8%
3 56
 
6.4%
- 56
 
6.4%
) 55
 
6.3%
( 55
 
6.3%
5 51
 
5.8%
4 40
 
4.6%
6 37
 
4.2%
Other values (7) 101
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 874
56.0%
Hangul 688
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
32.0%
1 84
 
9.6%
2 59
 
6.8%
3 56
 
6.4%
- 56
 
6.4%
) 55
 
6.3%
( 55
 
6.3%
5 51
 
5.8%
4 40
 
4.6%
6 37
 
4.2%
Other values (7) 101
 
11.6%
Hangul
ValueCountFrequency (%)
동 59
 
8.6%
시 54
 
7.8%
산 51
 
7.4%
로 35
 
5.1%
주 31
 
4.5%
전 30
 
4.4%
길 27
 
3.9%
구 26
 
3.8%
가 24
 
3.5%
완 18
 
2.6%
Other values (123) 333
48.4%

Correlations

2024-03-14T10:31:48.911116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명대표자전화번호주소
업체명1.0001.0001.0001.000
대표자1.0001.0001.0001.000
전화번호1.0001.0001.0001.000
주소1.0001.0001.0001.000

Missing values

2024-03-14T10:31:46.689208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:31:46.761600image/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

업체명대표자전화번호주소
0(주)케시이성실063-253-0300전주시 덕진구 팔달로 322-7 (진북동 363-5)
1전북전기관리공사한영규063-858-1625익산시 서동로5길 13 (주현동 245-8)
2한국전기관리소서득석외6명063-854-2221익산시 서동로 147 (마동 364-6)
3대한전기안전관리김학열외3명063-278-8771전주시 완산구 솟대1길 49(삼천동1가 700-2)
4(유)호남전기안전관리최재열063-252-1341전주시 덕진구 금암2동 1585-4
5나라전기관리공사최임관063-232-6330전주시 완산구 전주객사5길 47 (고사동 203-6) 603호
6(유)한국관리공사정인택063-226-6417전주시 완산구 따박골로 44 (중화산동2가 548-10)
7(유)군장전기안전관리소전덕배063-442-2666군산시 월명로 416-1 (미원동 37)
8(유)한국전력보안공사임계훈063-222-6627전주시 완산구 신촌3길 27-18 (중화산동2가 485-125)
9전북전기사업소김구태063-242-6321전주시 덕진구 견훤로 302 (인후동1가 765-24)
업체명대표자전화번호주소
46전북전기기술공사이상열외3명063-853-1520익산시 군익로 511 (송학동 16-4)
47(주)비엔지솔루션조계명063-237-0070전주시 완산구 덕적골2길 35-36 (평화동1가 459-1)
48㈜전기안전관리컨설팅조무중063-451-9050군산시 검다메안길 6-8, 202(조촌동)
49(유)대한전기안전관리공사채수진,문성대063-286-9800전주시 완산구 물왕멀로 9(중노송동575-8)
50(유)장안전기안전관리장안섭063-226-0189전주시 완산구 우전로 104(효자동2가)
51그린전기안전관리김현주063-538-8966정읍시 벚꽃로 539-11(상동)
52반디이엔에스김성순010-8648-****무주군 무주읍 당산길29-12(당산리 803)
53주식회사 희성박은석070-8252-1911전주시 완산구 천잠로 235, 9107호(효자동2가, 전주비전대학교 미래관)
54주식회사 서브원이규홍02-6924-4102전주시 완산구 백제대로 323(중화산동2가)
55유한회사 삼인전기안전관리김영대010-5531-****부안군 줄포면 줄포6길 11