Overview

Dataset statistics

Number of variables7
Number of observations67
Missing cells72
Missing cells (%)15.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory59.0 B

Variable types

Unsupported4
Text2
Categorical1

Dataset

Description안전진단전문기관등록현황201810월말
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201474

Alerts

Unnamed: 0 has 67 (100.0%) missing valuesMissing
안전진단 전문기관 등록현황 has 1 (1.5%) missing valuesMissing
Unnamed: 2 has 1 (1.5%) missing valuesMissing
Unnamed: 3 has 1 (1.5%) missing valuesMissing
Unnamed: 5 has 1 (1.5%) missing valuesMissing
Unnamed: 6 has 1 (1.5%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
안전진단 전문기관 등록현황 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:09:28.197308
Analysis finished2024-03-14 00:09:28.889147
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing67
Missing (%)100.0%
Memory size735.0 B

안전진단 전문기관 등록현황
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)1.5%
Memory size668.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)1.5%
Memory size668.0 B

Unnamed: 3
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:28.995956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length8.4242424
Min length3

Characters and Unicode

Total characters556
Distinct characters111
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

Unique66 ?
Unique (%)100.0%

Sample

1st row업 체 명
2nd row㈜건설품질시험원
3rd row(유)센이엔지건축안전진단
4th row㈜대한건설연구원
5th row㈜대들보구조안전기술단
ValueCountFrequency (%)
주식회사 11
 
13.1%
유)가온기술 1
 
1.2%
㈜혜원이엔지 1
 
1.2%
㈜대승엔지니어링 1
 
1.2%
창운 1
 
1.2%
누리종합건축사사무소 1
 
1.2%
유)대현건설기술 1
 
1.2%
시티이엔지 1
 
1.2%
유)당찬건설진단 1
 
1.2%
㈜고원 1
 
1.2%
Other values (64) 64
76.2%
2024-03-14T09:09:29.343178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 39
 
7.0%
사 27
 
4.9%
건 26
 
4.7%
술 20
 
3.6%
기 20
 
3.6%
설 18
 
3.2%
18
 
3.2%
엔 18
 
3.2%
이 17
 
3.1%
지 16
 
2.9%
Other values (101) 337
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 473
85.1%
Other Symbol 39
 
7.0%
Space Separator 18
 
3.2%
Open Punctuation 13
 
2.3%
Close Punctuation 13
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 27
 
5.7%
건 26
 
5.5%
술 20
 
4.2%
기 20
 
4.2%
설 18
 
3.8%
엔 18
 
3.8%
이 17
 
3.6%
지 16
 
3.4%
유 14
 
3.0%
단 12
 
2.5%
Other values (97) 285
60.3%
Other Symbol
ValueCountFrequency (%)
㈜ 39
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 512
92.1%
Common 44
 
7.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 39
 
7.6%
사 27
 
5.3%
건 26
 
5.1%
술 20
 
3.9%
기 20
 
3.9%
설 18
 
3.5%
엔 18
 
3.5%
이 17
 
3.3%
지 16
 
3.1%
유 14
 
2.7%
Other values (98) 297
58.0%
Common
ValueCountFrequency (%)
18
40.9%
( 13
29.5%
) 13
29.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 473
85.1%
ASCII 44
 
7.9%
None 39
 
7.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 39
100.0%
Hangul
ValueCountFrequency (%)
사 27
 
5.7%
건 26
 
5.5%
술 20
 
4.2%
기 20
 
4.2%
설 18
 
3.8%
엔 18
 
3.8%
이 17
 
3.6%
지 16
 
3.4%
유 14
 
3.0%
단 12
 
2.5%
Other values (97) 285
60.3%
ASCII
ValueCountFrequency (%)
18
40.9%
( 13
29.5%
) 13
29.5%

Unnamed: 4
Categorical

Distinct11
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size668.0 B
교량/터널,수리
22 
교량/터널
20 
건축
11 
교량/터널,건축
4 
교량/터널,수리,건축
4 
Other values (6)
6 

Length

Max length11
Median length9
Mean length6.1940299
Min length2

Unique

Unique6 ?
Unique (%)9.0%

Sample

1st row<NA>
2nd row등록분야
3rd row교량/터널,수리
4th row건축
5th row교량/터널,수리

Common Values

ValueCountFrequency (%)
교량/터널,수리 22
32.8%
교량/터널 20
29.9%
건축 11
16.4%
교량/터널,건축 4
 
6.0%
교량/터널,수리,건축 4
 
6.0%
<NA> 1
 
1.5%
등록분야 1
 
1.5%
교량/터널,항만 1
 
1.5%
수리,건축 1
 
1.5%
교량/터널, 수리 1
 
1.5%

Length

2024-03-14T09:09:29.466760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
교량/터널,수리 22
32.4%
교량/터널 21
30.9%
건축 11
16.2%
교량/터널,건축 4
 
5.9%
교량/터널,수리,건축 4
 
5.9%
na 1
 
1.5%
등록분야 1
 
1.5%
교량/터널,항만 1
 
1.5%
수리,건축 1
 
1.5%
수리 1
 
1.5%

Unnamed: 5
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:29.680081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0606061
Min length2

Characters and Unicode

Total characters202
Distinct characters97
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

Unique66 ?
Unique (%)100.0%

Sample

1st row대표자
2nd row이재열
3rd row박은심
4th row조은아
5th row박형권
ValueCountFrequency (%)
빙인섭 1
 
1.5%
김영호 1
 
1.5%
이혜림 1
 
1.5%
채윤석 1
 
1.5%
최연희 1
 
1.5%
이영운 1
 
1.5%
임진하 1
 
1.5%
허영훈 1
 
1.5%
강명자 1
 
1.5%
이재열 1
 
1.5%
Other values (58) 58
85.3%
2024-03-14T09:09:30.018283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 14
 
6.9%
김 13
 
6.4%
영 8
 
4.0%
박 6
 
3.0%
성 6
 
3.0%
최 5
 
2.5%
호 5
 
2.5%
정 4
 
2.0%
희 4
 
2.0%
형 4
 
2.0%
Other values (87) 133
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 199
98.5%
Space Separator 2
 
1.0%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 14
 
7.0%
김 13
 
6.5%
영 8
 
4.0%
박 6
 
3.0%
성 6
 
3.0%
최 5
 
2.5%
호 5
 
2.5%
정 4
 
2.0%
희 4
 
2.0%
형 4
 
2.0%
Other values (85) 130
65.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
98.5%
Common 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 14
 
7.0%
김 13
 
6.5%
영 8
 
4.0%
박 6
 
3.0%
성 6
 
3.0%
최 5
 
2.5%
호 5
 
2.5%
정 4
 
2.0%
희 4
 
2.0%
형 4
 
2.0%
Other values (85) 130
65.3%
Common
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
98.5%
ASCII 3
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 14
 
7.0%
김 13
 
6.5%
영 8
 
4.0%
박 6
 
3.0%
성 6
 
3.0%
최 5
 
2.5%
호 5
 
2.5%
정 4
 
2.0%
희 4
 
2.0%
형 4
 
2.0%
Other values (85) 130
65.3%
ASCII
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)1.5%
Memory size668.0 B

Correlations

2024-03-14T09:09:30.092429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 3Unnamed: 4Unnamed: 5
Unnamed: 31.0001.0001.000
Unnamed: 41.0001.0001.000
Unnamed: 51.0001.0001.000

Missing values

2024-03-14T09:09:28.392113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:09:28.489439image/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.
2024-03-14T09:09:28.828511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0안전진단 전문기관 등록현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA>NaNNaN<NA><NA><NA>NaN
1<NA>연번등록번호업 체 명등록분야대표자등록일자
2<NA>11, 2㈜건설품질시험원교량/터널,수리이재열2003-04-03 00:00:00
3<NA>24(유)센이엔지건축안전진단건축박은심2005-02-23 00:00:00
4<NA>36㈜대한건설연구원교량/터널,수리조은아2005-06-22 00:00:00
5<NA>47㈜대들보구조안전기술단교량/터널,건축박형권2006-08-09 00:00:00
6<NA>58㈜한국건설기술공사교량/터널,수리장승환2007-03-09 00:00:00
7<NA>611㈜세종건설기술교량/터널,수리유영일2009-05-11 00:00:00
8<NA>712(유)쎈구조엔지니어링건축김용진2009-05-28 00:00:00
9<NA>813(유)용성엔지니어링교량/터널원복주2010-04-12 00:00:00
Unnamed: 0안전진단 전문기관 등록현황Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
57<NA>5676㈜대한구조안전기술원건축소형석2018-06-15 00:00:00
58<NA>5777㈜성진건설기술단건축정지혜2017-11-06 00:00:00
59<NA>5878㈜국성건설엔지니어링교량/터널,수리박동우2018-07-06 00:00:00
60<NA>5979유한회사 지반과건설교량/터널이병기2018-07-18 00:00:00
61<NA>6080주식회사 인우교량/터널송일섭2018-07-26 00:00:00
62<NA>6181일원건축사사무소건축이상규2018-09-14 00:00:00
63<NA>6282(유)서흥이엔지교량/터널이상순2018-09-20 00:00:00
64<NA>6383주식회사 한국진단이엔씨교량/터널장성호2018-10-08 00:00:00
65<NA>64191㈜건설방재기술연구원교량/터널,수리,건축백승복1998-11-09 00:00:00
66<NA>65242기술사건축사사무소 미문건설기술연구원㈜건축전옥영2000-04-08 00:00:00