Overview

Dataset statistics

Number of variables4
Number of observations56
Missing cells2
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory34.4 B

Variable types

Text4

Dataset

Description전기안전관리대행업체현황2
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201454

Alerts

전화번호 has 2 (3.6%) missing valuesMissing
업체명 has unique valuesUnique
대표자 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:48:14.344931
Analysis finished2024-03-14 02:48:14.687969
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
2024-03-14T11:48:14.842597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.9642857
Min length4

Characters and Unicode

Total characters502
Distinct characters80
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%
유한회사 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%
Other values (49) 49
81.7%
2024-03-14T11:48:15.145920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
전 79
15.7%
기 45
 
9.0%
리 41
 
8.2%
관 40
 
8.0%
안 27
 
5.4%
( 23
 
4.6%
) 23
 
4.6%
유 22
 
4.4%
한 20
 
4.0%
사 18
 
3.6%
Other values (70) 164
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
87.6%
Open Punctuation 23
 
4.6%
Close Punctuation 23
 
4.6%
Uppercase Letter 10
 
2.0%
Space Separator 4
 
0.8%
Dash Punctuation 1
 
0.2%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 79
18.0%
기 45
 
10.2%
리 41
 
9.3%
관 40
 
9.1%
안 27
 
6.1%
유 22
 
5.0%
한 20
 
4.5%
사 18
 
4.1%
공 12
 
2.7%
소 10
 
2.3%
Other values (58) 126
28.6%
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 (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 441
87.8%
Common 51
 
10.2%
Latin 10
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 79
17.9%
기 45
 
10.2%
리 41
 
9.3%
관 40
 
9.1%
안 27
 
6.1%
유 22
 
5.0%
한 20
 
4.5%
사 18
 
4.1%
공 12
 
2.7%
소 10
 
2.3%
Other values (59) 127
28.8%
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 (%)
( 23
45.1%
) 23
45.1%
4
 
7.8%
- 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
87.6%
ASCII 61
 
12.2%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
전 79
18.0%
기 45
 
10.2%
리 41
 
9.3%
관 40
 
9.1%
안 27
 
6.1%
유 22
 
5.0%
한 20
 
4.5%
사 18
 
4.1%
공 12
 
2.7%
소 10
 
2.3%
Other values (58) 126
28.6%
ASCII
ValueCountFrequency (%)
( 23
37.7%
) 23
37.7%
4
 
6.6%
K 3
 
4.9%
E 2
 
3.3%
T 1
 
1.6%
- 1
 
1.6%
O 1
 
1.6%
P 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
2024-03-14T11:48:15.343205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length4.4821429
Min length3

Characters and Unicode

Total characters251
Distinct characters92
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 row한영규외 1명
3rd row서득석외6명
4th row김학열외4명
5th row최재열
ValueCountFrequency (%)
6명 3
 
4.7%
5명 2
 
3.1%
김홍남 1
 
1.6%
정진론외6명 1
 
1.6%
신동호 1
 
1.6%
이태영외 1
 
1.6%
김혜순 1
 
1.6%
박진성외 1
 
1.6%
이승재 1
 
1.6%
양성현외5명 1
 
1.6%
Other values (51) 51
79.7%
2024-03-14T11:48:15.777232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
외 21
 
8.4%
명 18
 
7.2%
이 10
 
4.0%
성 9
 
3.6%
김 9
 
3.6%
8
 
3.2%
박 7
 
2.8%
6 6
 
2.4%
정 6
 
2.4%
임 5
 
2.0%
Other values (82) 152
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
87.3%
Decimal Number 20
 
8.0%
Space Separator 8
 
3.2%
Other Punctuation 4
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
외 21
 
9.6%
명 18
 
8.2%
이 10
 
4.6%
성 9
 
4.1%
김 9
 
4.1%
박 7
 
3.2%
정 6
 
2.7%
임 5
 
2.3%
최 5
 
2.3%
장 5
 
2.3%
Other values (73) 124
56.6%
Decimal Number
ValueCountFrequency (%)
6 6
30.0%
3 3
15.0%
5 3
15.0%
2 3
15.0%
4 3
15.0%
7 1
 
5.0%
1 1
 
5.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
87.3%
Common 32
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
외 21
 
9.6%
명 18
 
8.2%
이 10
 
4.6%
성 9
 
4.1%
김 9
 
4.1%
박 7
 
3.2%
정 6
 
2.7%
임 5
 
2.3%
최 5
 
2.3%
장 5
 
2.3%
Other values (73) 124
56.6%
Common
ValueCountFrequency (%)
8
25.0%
6 6
18.8%
, 4
12.5%
3 3
 
9.4%
5 3
 
9.4%
2 3
 
9.4%
4 3
 
9.4%
7 1
 
3.1%
1 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
87.3%
ASCII 32
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
외 21
 
9.6%
명 18
 
8.2%
이 10
 
4.6%
성 9
 
4.1%
김 9
 
4.1%
박 7
 
3.2%
정 6
 
2.7%
임 5
 
2.3%
최 5
 
2.3%
장 5
 
2.3%
Other values (73) 124
56.6%
ASCII
ValueCountFrequency (%)
8
25.0%
6 6
18.8%
, 4
12.5%
3 3
 
9.4%
5 3
 
9.4%
2 3
 
9.4%
4 3
 
9.4%
7 1
 
3.1%
1 1
 
3.1%

전화번호
Text

MISSING 

Distinct52
Distinct (%)96.3%
Missing2
Missing (%)3.6%
Memory size580.0 B
2024-03-14T11:48:15.981355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.018519
Min length12

Characters and Unicode

Total characters649
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)92.6%

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
 
3.7%
063-535-0401 2
 
3.7%
063-626-8382 1
 
1.9%
063-253-0300 1
 
1.9%
063-835-1520 1
 
1.9%
063-537-1921 1
 
1.9%
063-277-5678 1
 
1.9%
063-838-8600 1
 
1.9%
063-564-8885 1
 
1.9%
063-228-8771 1
 
1.9%
Other values (42) 42
77.8%
2024-03-14T11:48:16.301841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 108
16.6%
6 94
14.5%
3 92
14.2%
0 89
13.7%
2 76
11.7%
8 43
 
6.6%
1 41
 
6.3%
5 31
 
4.8%
7 30
 
4.6%
4 28
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 541
83.4%
Dash Punctuation 108
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 94
17.4%
3 92
17.0%
0 89
16.5%
2 76
14.0%
8 43
7.9%
1 41
7.6%
5 31
 
5.7%
7 30
 
5.5%
4 28
 
5.2%
9 17
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 649
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 108
16.6%
6 94
14.5%
3 92
14.2%
0 89
13.7%
2 76
11.7%
8 43
 
6.6%
1 41
 
6.3%
5 31
 
4.8%
7 30
 
4.6%
4 28
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 649
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 108
16.6%
6 94
14.5%
3 92
14.2%
0 89
13.7%
2 76
11.7%
8 43
 
6.6%
1 41
 
6.3%
5 31
 
4.8%
7 30
 
4.6%
4 28
 
4.3%

주소
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-03-14T11:48:16.501617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length31
Mean length27.285714
Min length15

Characters and Unicode

Total characters1528
Distinct characters144
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 157 (마동)
4th row전주시 완산구 솟대1길 49(삼천동1가 700-2)
5th row전주시 덕진구 금암2동 1585-4
ValueCountFrequency (%)
전주시 24
 
8.2%
완산구 16
 
5.5%
익산시 12
 
4.1%
덕진구 8
 
2.7%
군산시 7
 
2.4%
정읍시 7
 
2.4%
효자동3가 5
 
1.7%
영등동 4
 
1.4%
남원시 3
 
1.0%
중화산동2가 2
 
0.7%
Other values (196) 205
70.0%
2024-03-14T11:48:16.820989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
268
 
17.5%
1 80
 
5.2%
2 64
 
4.2%
동 59
 
3.9%
) 55
 
3.6%
3 55
 
3.6%
( 55
 
3.6%
시 54
 
3.5%
- 51
 
3.3%
산 51
 
3.3%
Other values (134) 736
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
44.6%
Decimal Number 410
26.8%
Space Separator 268
 
17.5%
Close Punctuation 55
 
3.6%
Open Punctuation 55
 
3.6%
Dash Punctuation 51
 
3.3%
Other Punctuation 7
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 59
 
8.7%
시 54
 
7.9%
산 51
 
7.5%
로 35
 
5.1%
주 29
 
4.3%
전 27
 
4.0%
길 27
 
4.0%
구 25
 
3.7%
가 24
 
3.5%
완 16
 
2.3%
Other values (117) 335
49.1%
Decimal Number
ValueCountFrequency (%)
1 80
19.5%
2 64
15.6%
3 55
13.4%
5 48
11.7%
4 36
8.8%
6 34
8.3%
7 26
 
6.3%
0 25
 
6.1%
8 22
 
5.4%
9 20
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 5
71.4%
/ 1
 
14.3%
@ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
268
100.0%
Close Punctuation
ValueCountFrequency (%)
) 55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 55
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 846
55.4%
Hangul 682
44.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 59
 
8.7%
시 54
 
7.9%
산 51
 
7.5%
로 35
 
5.1%
주 29
 
4.3%
전 27
 
4.0%
길 27
 
4.0%
구 25
 
3.7%
가 24
 
3.5%
완 16
 
2.3%
Other values (117) 335
49.1%
Common
ValueCountFrequency (%)
268
31.7%
1 80
 
9.5%
2 64
 
7.6%
) 55
 
6.5%
3 55
 
6.5%
( 55
 
6.5%
- 51
 
6.0%
5 48
 
5.7%
4 36
 
4.3%
6 34
 
4.0%
Other values (7) 100
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 846
55.4%
Hangul 682
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
268
31.7%
1 80
 
9.5%
2 64
 
7.6%
) 55
 
6.5%
3 55
 
6.5%
( 55
 
6.5%
- 51
 
6.0%
5 48
 
5.7%
4 36
 
4.3%
6 34
 
4.0%
Other values (7) 100
 
11.8%
Hangul
ValueCountFrequency (%)
동 59
 
8.7%
시 54
 
7.9%
산 51
 
7.5%
로 35
 
5.1%
주 29
 
4.3%
전 27
 
4.0%
길 27
 
4.0%
구 25
 
3.7%
가 24
 
3.5%
완 16
 
2.3%
Other values (117) 335
49.1%

Correlations

2024-03-14T11:48:16.898899image/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

2024-03-14T11:48:14.597996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:48:14.661823image/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)
1전북전기관리공사한영규외 1명063-858-1625익산시 서동로5길 13 (주현동 245-8)
2한국전기관리소서득석외6명063-854-2221익산시 서동로 157 (마동)
3대한전기안전관리김학열외4명063-278-8771전주시 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 메너머3길 24, 2층(중화산동2가)
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
46전북전기기술공사이상열외4명063-853-1520익산시 군익로 511 (송학동 16-4)
47㈜전기안전관리컨설팅조무중063-451-9050군산시 검다메안길 6-8, 202(조촌동)
48(유)대한전기안전관리공사채수진,문성대063-286-9800전주시 완산구 물왕멀로 9(중노송동575-8)
49(유)장안전기안전관리장안섭063-226-0189전주시 완산구 우전로 104(효자동2가)
50그린전기안전관리김현주063-538-8966정읍시 벚꽃로 539-11(상동)
51반디이엔에스김성순<NA>무주군 무주읍 당산길29-12(당산리 803)
52주식회사 희성박은석070-8252-1911전주시 덕진구 가련산로 23,5층 502호(덕진동2가)
53주식회사 서브원이규홍02-6924-4102전주시 완산구 백제대로 323(중화산동2가)
54유한회사 삼인전기안전관리최숙경<NA>고창군 고창읍 월곡공원2길 43
55유한회사삼성전기관리공사박종완063-535-0401정읍시 서부산업도로 476,202호(수성동)