Overview

Dataset statistics

Number of variables6
Number of observations67
Missing cells5
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory50.0 B

Variable types

Text5
Categorical1

Dataset

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

Alerts

안전진단 전문기관 등록현황 has 1 (1.5%) missing valuesMissing
Unnamed: 1 has 1 (1.5%) missing valuesMissing
Unnamed: 2 has 1 (1.5%) missing valuesMissing
Unnamed: 4 has 1 (1.5%) missing valuesMissing
Unnamed: 5 has 1 (1.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 00:09:23.768113
Analysis finished2024-03-14 00:09:24.342297
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전진단 전문기관 등록현황
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:24.515500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8636364
Min length1

Characters and Unicode

Total characters123
Distinct characters12
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

Unique66 ?
Unique (%)100.0%

Sample

1st row연번
2nd row1
3rd row2
4th row3
5th row4
ValueCountFrequency (%)
16 1
 
1.5%
33 1
 
1.5%
35 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
Other values (56) 56
84.8%
2024-03-14T09:09:24.863740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
13.8%
2 17
13.8%
3 17
13.8%
4 17
13.8%
5 17
13.8%
6 12
9.8%
7 6
 
4.9%
8 6
 
4.9%
9 6
 
4.9%
0 6
 
4.9%
Other values (2) 2
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 121
98.4%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Other Letter
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
14.0%
2 17
14.0%
3 17
14.0%
4 17
14.0%
5 17
14.0%
6 12
9.9%
7 6
 
5.0%
8 6
 
5.0%
9 6
 
5.0%
0 6
 
5.0%
Hangul
ValueCountFrequency (%)
연 1
50.0%
번 1
50.0%

Unnamed: 1
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:25.081634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.030303
Min length1

Characters and Unicode

Total characters134
Distinct characters16
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

Unique66 ?
Unique (%)100.0%

Sample

1st row등록번호
2nd row1, 2
3rd row4
4th row6
5th row7
ValueCountFrequency (%)
25 1
 
1.5%
48 1
 
1.5%
50 1
 
1.5%
52 1
 
1.5%
54 1
 
1.5%
55 1
 
1.5%
56 1
 
1.5%
57 1
 
1.5%
58 1
 
1.5%
59 1
 
1.5%
Other values (57) 57
85.1%
2024-03-14T09:09:25.391806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 17
12.7%
6 16
11.9%
2 15
11.2%
5 15
11.2%
1 15
11.2%
3 15
11.2%
7 14
10.4%
8 10
7.5%
9 7
5.2%
0 4
 
3.0%
Other values (6) 6
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128
95.5%
Other Letter 4
 
3.0%
Other Punctuation 1
 
0.7%
Space Separator 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 17
13.3%
6 16
12.5%
2 15
11.7%
5 15
11.7%
1 15
11.7%
3 15
11.7%
7 14
10.9%
8 10
7.8%
9 7
5.5%
0 4
 
3.1%
Other Letter
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
번 1
25.0%
호 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
97.0%
Hangul 4
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 17
13.1%
6 16
12.3%
2 15
11.5%
5 15
11.5%
1 15
11.5%
3 15
11.5%
7 14
10.8%
8 10
7.7%
9 7
5.4%
0 4
 
3.1%
Other values (2) 2
 
1.5%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
97.0%
Hangul 4
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 17
13.1%
6 16
12.3%
2 15
11.5%
5 15
11.5%
1 15
11.5%
3 15
11.5%
7 14
10.8%
8 10
7.7%
9 7
5.4%
0 4
 
3.1%
Other values (2) 2
 
1.5%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 2
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:25.554875image/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%
2024-03-14T09:09:25.888828image/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: 3
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

2024-03-14T09:09:26.028633image/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: 4
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:26.223193image/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%
2024-03-14T09:09:26.552157image/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: 5
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing1
Missing (%)1.5%
Memory size668.0 B
2024-03-14T09:09:26.776926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9090909
Min length4

Characters and Unicode

Total characters654
Distinct characters15
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 row등록일자
2nd row2003-04-03
3rd row2005-02-23
4th row2005-06-22
5th row2006-08-09
ValueCountFrequency (%)
2013-07-22 1
 
1.5%
2016-04-04 1
 
1.5%
2016-04-22 1
 
1.5%
2016-06-29 1
 
1.5%
2016-09-06 1
 
1.5%
2016-10-21 1
 
1.5%
2016-12-28 1
 
1.5%
2017-01-18 1
 
1.5%
2017-01-19 1
 
1.5%
2017-02-08 1
 
1.5%
Other values (56) 56
84.8%
2024-03-14T09:09:27.171739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 161
24.6%
- 130
19.9%
2 114
17.4%
1 102
15.6%
7 24
 
3.7%
8 24
 
3.7%
4 23
 
3.5%
6 23
 
3.5%
5 18
 
2.8%
9 16
 
2.4%
Other values (5) 19
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
79.5%
Dash Punctuation 130
 
19.9%
Other Letter 4
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 161
31.0%
2 114
21.9%
1 102
19.6%
7 24
 
4.6%
8 24
 
4.6%
4 23
 
4.4%
6 23
 
4.4%
5 18
 
3.5%
9 16
 
3.1%
3 15
 
2.9%
Other Letter
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 650
99.4%
Hangul 4
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 161
24.8%
- 130
20.0%
2 114
17.5%
1 102
15.7%
7 24
 
3.7%
8 24
 
3.7%
4 23
 
3.5%
6 23
 
3.5%
5 18
 
2.8%
9 16
 
2.5%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 650
99.4%
Hangul 4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 161
24.8%
- 130
20.0%
2 114
17.5%
1 102
15.7%
7 24
 
3.7%
8 24
 
3.7%
4 23
 
3.5%
6 23
 
3.5%
5 18
 
2.8%
9 16
 
2.5%
Hangul
ValueCountFrequency (%)
등 1
25.0%
록 1
25.0%
일 1
25.0%
자 1
25.0%

Correlations

2024-03-14T09:09:27.251731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전진단 전문기관 등록현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
안전진단 전문기관 등록현황1.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.0001.000

Missing values

2024-03-14T09:09:24.072966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:09:24.165159image/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.
2024-03-14T09:09:24.269973image/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

안전진단 전문기관 등록현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0<NA><NA><NA><NA><NA><NA>
1연번등록번호업 체 명등록분야대표자등록일자
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안전진단 전문기관 등록현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
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