Overview

Dataset statistics

Number of variables6
Number of observations176
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory48.8 B

Variable types

Categorical3
Text3

Dataset

Description한국건강증진발원 조직구성 및 팀별 인력정보- 실명, 부서명, 직책/직급, 이름, 연락처, 담당업무 등 정보를 제공합니다.
Author한국건강증진개발원
URLhttps://www.data.go.kr/data/15042448/fileData.do

Alerts

부서명 is highly overall correlated with 실명High correlation
실명 is highly overall correlated with 부서명High correlation
연락처 has 3 (1.7%) missing valuesMissing
담당업무 has 3 (1.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:57:39.964066
Analysis finished2023-12-12 13:57:40.557174
Duration0.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

실명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
건강증진사업센터
47 
혁신사업센터
33 
국가금연지원센터
30 
경영지원실
28 
정책연구평가실
19 
Other values (3)
19 

Length

Max length18
Median length8
Mean length6.7386364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row원장실
2nd row원장실
3rd row원장실
4th row원장실
5th row원장실

Common Values

ValueCountFrequency (%)
건강증진사업센터 47
26.7%
혁신사업센터 33
18.8%
국가금연지원센터 30
17.0%
경영지원실 28
15.9%
정책연구평가실 19
10.8%
원장실 11
 
6.2%
전략기획실 6
 
3.4%
국민건강 스마트관리 연구개발사업단 2
 
1.1%

Length

2023-12-12T22:57:40.621523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:57:40.734908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강증진사업센터 47
26.1%
혁신사업센터 33
18.3%
국가금연지원센터 30
16.7%
경영지원실 28
15.6%
정책연구평가실 19
10.6%
원장실 11
 
6.1%
전략기획실 6
 
3.3%
국민건강 2
 
1.1%
스마트관리 2
 
1.1%
연구개발사업단 2
 
1.1%

부서명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
디지털헬스케어팀
 
11
정보화혁신팀
 
10
음주폐해예방팀
 
9
지역정책팀
 
9
금연정책팀
 
9
Other values (27)
128 

Length

Max length18
Median length5
Mean length5.8181818
Min length3

Unique

Unique6 ?
Unique (%)3.4%

Sample

1st row감사실
2nd row감사실
3rd row감사실
4th row전략기획실
5th row정책연구평가실

Common Values

ValueCountFrequency (%)
디지털헬스케어팀 11
 
6.2%
정보화혁신팀 10
 
5.7%
음주폐해예방팀 9
 
5.1%
지역정책팀 9
 
5.1%
금연정책팀 9
 
5.1%
보건인력팀 9
 
5.1%
생활건강팀 8
 
4.5%
안전경영지원팀 8
 
4.5%
인재개발팀 8
 
4.5%
인증평가팀 7
 
4.0%
Other values (22) 88
50.0%

Length

2023-12-12T22:57:40.873366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
디지털헬스케어팀 11
 
6.1%
정보화혁신팀 10
 
5.6%
음주폐해예방팀 9
 
5.0%
지역정책팀 9
 
5.0%
금연정책팀 9
 
5.0%
보건인력팀 9
 
5.0%
생활건강팀 8
 
4.4%
안전경영지원팀 8
 
4.4%
인재개발팀 8
 
4.4%
인증평가팀 7
 
3.9%
Other values (24) 92
51.1%

직책_직급
Categorical

Distinct13
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
주임전문원
66 
선임전문원
40 
팀장
23 
위촉전문원
19 
책임전문원
8 
Other values (8)
20 

Length

Max length6
Median length5
Mean length4.4602273
Min length2

Unique

Unique4 ?
Unique (%)2.3%

Sample

1st row주임전문원
2nd row실장
3rd row선임전문원
4th row센터장
5th row실장

Common Values

ValueCountFrequency (%)
주임전문원 66
37.5%
선임전문원 40
22.7%
팀장 23
 
13.1%
위촉전문원 19
 
10.8%
책임전문원 8
 
4.5%
공중보건의 6
 
3.4%
전문원 4
 
2.3%
실장 3
 
1.7%
센터장 3
 
1.7%
실장(겸임) 1
 
0.6%
Other values (3) 3
 
1.7%

Length

2023-12-12T22:57:41.001721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주임전문원 66
37.5%
선임전문원 40
22.7%
팀장 23
 
13.1%
위촉전문원 19
 
10.8%
책임전문원 8
 
4.5%
공중보건의 6
 
3.4%
전문원 4
 
2.3%
실장 3
 
1.7%
센터장 3
 
1.7%
실장(겸임 1
 
0.6%
Other values (3) 3
 
1.7%

이름
Text

Distinct172
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-12T22:57:41.315636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9886364
Min length2

Characters and Unicode

Total characters526
Distinct characters126
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

Unique168 ?
Unique (%)95.5%

Sample

1st row김장미
2nd row홍경수
3rd row박상일
4th row김수영
5th row오유미
ValueCountFrequency (%)
김지연 2
 
1.1%
이윤수 2
 
1.1%
이지은 2
 
1.1%
김수영 2
 
1.1%
이준영 1
 
0.6%
김지은 1
 
0.6%
노인애 1
 
0.6%
이명화 1
 
0.6%
김정민 1
 
0.6%
김현정 1
 
0.6%
Other values (162) 162
92.0%
2023-12-12T22:57:41.819283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 40
 
7.6%
이 38
 
7.2%
영 20
 
3.8%
정 20
 
3.8%
은 18
 
3.4%
희 16
 
3.0%
수 16
 
3.0%
박 16
 
3.0%
진 15
 
2.9%
현 13
 
2.5%
Other values (116) 314
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 526
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 40
 
7.6%
이 38
 
7.2%
영 20
 
3.8%
정 20
 
3.8%
은 18
 
3.4%
희 16
 
3.0%
수 16
 
3.0%
박 16
 
3.0%
진 15
 
2.9%
현 13
 
2.5%
Other values (116) 314
59.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 526
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 40
 
7.6%
이 38
 
7.2%
영 20
 
3.8%
정 20
 
3.8%
은 18
 
3.4%
희 16
 
3.0%
수 16
 
3.0%
박 16
 
3.0%
진 15
 
2.9%
현 13
 
2.5%
Other values (116) 314
59.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 526
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 40
 
7.6%
이 38
 
7.2%
영 20
 
3.8%
정 20
 
3.8%
은 18
 
3.4%
희 16
 
3.0%
수 16
 
3.0%
박 16
 
3.0%
진 15
 
2.9%
현 13
 
2.5%
Other values (116) 314
59.7%

연락처
Text

MISSING 

Distinct170
Distinct (%)98.3%
Missing3
Missing (%)1.7%
Memory size1.5 KiB
2023-12-12T22:57:42.179608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.00578
Min length12

Characters and Unicode

Total characters2077
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

Unique167 ?
Unique (%)96.5%

Sample

1st row02-3781-2240
2nd row02-3781-2238
3rd row02-3782-7693
4th row02-3781-2201
5th row02-3781-3530
ValueCountFrequency (%)
02-3781-3594 2
 
1.2%
02-3781-2258 2
 
1.2%
02-3781-3572 2
 
1.2%
02-3782-7676 1
 
0.6%
02-3781-3510 1
 
0.6%
02-3782-3569 1
 
0.6%
02-3781-2231 1
 
0.6%
02-3781-2240 1
 
0.6%
02-3781-2226 1
 
0.6%
02-3781-2223 1
 
0.6%
Other values (160) 160
92.5%
2023-12-12T22:57:42.646188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 372
17.9%
- 346
16.7%
3 281
13.5%
7 245
11.8%
0 212
10.2%
8 199
9.6%
1 173
8.3%
5 105
 
5.1%
6 81
 
3.9%
4 37
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1731
83.3%
Dash Punctuation 346
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 372
21.5%
3 281
16.2%
7 245
14.2%
0 212
12.2%
8 199
11.5%
1 173
10.0%
5 105
 
6.1%
6 81
 
4.7%
4 37
 
2.1%
9 26
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 346
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 372
17.9%
- 346
16.7%
3 281
13.5%
7 245
11.8%
0 212
10.2%
8 199
9.6%
1 173
8.3%
5 105
 
5.1%
6 81
 
3.9%
4 37
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 372
17.9%
- 346
16.7%
3 281
13.5%
7 245
11.8%
0 212
10.2%
8 199
9.6%
1 173
8.3%
5 105
 
5.1%
6 81
 
3.9%
4 37
 
1.8%

담당업무
Text

MISSING 

Distinct134
Distinct (%)77.5%
Missing3
Missing (%)1.7%
Memory size1.5 KiB
2023-12-12T22:57:43.010980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length31
Mean length16.433526
Min length4

Characters and Unicode

Total characters2843
Distinct characters259
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique119 ?
Unique (%)68.8%

Sample

1st row청렴제도개선청렴제도개선 / 부패방지시책 / 부패·공익 신고
2nd row감사실 업무총괄
3rd row내외부감사실시 및 결과조치 / 부패취약분야 발굴 및 제도개선
4th row전략기획실 총괄(겸직)
5th row정책연구평가실 총괄
ValueCountFrequency (%)
80
 
11.7%
및 42
 
6.2%
운영 28
 
4.1%
팀업무총괄 22
 
3.2%
지원 20
 
2.9%
사업 12
 
1.8%
운영지원 11
 
1.6%
모니터링 9
 
1.3%
시범사업 8
 
1.2%
기획 8
 
1.2%
Other values (277) 442
64.8%
2023-12-12T22:57:43.513599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
515
 
18.1%
업 87
 
3.1%
/ 82
 
2.9%
지 77
 
2.7%
사 77
 
2.7%
건 61
 
2.1%
원 59
 
2.1%
관 56
 
2.0%
영 54
 
1.9%
보 53
 
1.9%
Other values (249) 1722
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2179
76.6%
Space Separator 515
 
18.1%
Other Punctuation 89
 
3.1%
Uppercase Letter 42
 
1.5%
Open Punctuation 6
 
0.2%
Close Punctuation 6
 
0.2%
Lowercase Letter 5
 
0.2%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 87
 
4.0%
지 77
 
3.5%
사 77
 
3.5%
건 61
 
2.8%
원 59
 
2.7%
관 56
 
2.6%
영 54
 
2.5%
보 53
 
2.4%
운 46
 
2.1%
리 45
 
2.1%
Other values (229) 1564
71.8%
Uppercase Letter
ValueCountFrequency (%)
I 12
28.6%
T 7
16.7%
A 6
14.3%
C 4
 
9.5%
S 4
 
9.5%
P 2
 
4.8%
N 1
 
2.4%
O 1
 
2.4%
F 1
 
2.4%
E 1
 
2.4%
Other values (3) 3
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/ 82
92.1%
· 7
 
7.9%
Space Separator
ValueCountFrequency (%)
515
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 5
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2179
76.6%
Common 617
 
21.7%
Latin 47
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 87
 
4.0%
지 77
 
3.5%
사 77
 
3.5%
건 61
 
2.8%
원 59
 
2.7%
관 56
 
2.6%
영 54
 
2.5%
보 53
 
2.4%
운 46
 
2.1%
리 45
 
2.1%
Other values (229) 1564
71.8%
Latin
ValueCountFrequency (%)
I 12
25.5%
T 7
14.9%
A 6
12.8%
o 5
10.6%
C 4
 
8.5%
S 4
 
8.5%
P 2
 
4.3%
N 1
 
2.1%
O 1
 
2.1%
F 1
 
2.1%
Other values (4) 4
 
8.5%
Common
ValueCountFrequency (%)
515
83.5%
/ 82
 
13.3%
· 7
 
1.1%
( 6
 
1.0%
) 6
 
1.0%
1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2179
76.6%
ASCII 657
 
23.1%
None 7
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
515
78.4%
/ 82
 
12.5%
I 12
 
1.8%
T 7
 
1.1%
( 6
 
0.9%
) 6
 
0.9%
A 6
 
0.9%
o 5
 
0.8%
C 4
 
0.6%
S 4
 
0.6%
Other values (9) 10
 
1.5%
Hangul
ValueCountFrequency (%)
업 87
 
4.0%
지 77
 
3.5%
사 77
 
3.5%
건 61
 
2.8%
원 59
 
2.7%
관 56
 
2.6%
영 54
 
2.5%
보 53
 
2.4%
운 46
 
2.1%
리 45
 
2.1%
Other values (229) 1564
71.8%
None
ValueCountFrequency (%)
· 7
100.0%

Correlations

2023-12-12T22:57:43.642582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실명부서명직책_직급
실명1.0001.0000.614
부서명1.0001.0000.883
직책_직급0.6140.8831.000
2023-12-12T22:57:43.749673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명실명직책_직급
부서명1.0000.9260.487
실명0.9261.0000.329
직책_직급0.4870.3291.000
2023-12-12T22:57:43.849977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실명부서명직책_직급
실명1.0000.9260.329
부서명0.9261.0000.487
직책_직급0.3290.4871.000

Missing values

2023-12-12T22:57:40.308537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:57:40.409951image/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.
2023-12-12T22:57:40.504562image/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

실명부서명직책_직급이름연락처담당업무
0원장실감사실주임전문원김장미02-3781-2240청렴제도개선청렴제도개선 / 부패방지시책 / 부패·공익 신고
1원장실감사실실장홍경수02-3781-2238감사실 업무총괄
2원장실감사실선임전문원박상일02-3782-7693내외부감사실시 및 결과조치 / 부패취약분야 발굴 및 제도개선
3원장실전략기획실센터장김수영02-3781-2201전략기획실 총괄(겸직)
4원장실정책연구평가실실장오유미02-3781-3530정책연구평가실 총괄
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9원장실국민건강 스마트관리 연구개발사업단단장홍윤철<NA>사업단 총괄
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166국가금연지원센터금연상담운영팀선임전문원강혜리02-3782-7653금연상담전화 상담 서비스 운영지원
167건강증진사업센터음주폐해예방팀주임전문원한우섭02-3781-2258절주교육 / 학교금주교육
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170건강증진사업센터음주폐해예방팀위촉전문원김유빈02-3782-7673절주 서포터즈 운영 / 음주폐해예방 홍보
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175건강증진사업센터음주폐해예방팀선임전문원박여진02-3782-7671국가 음주폐해예방정책 및 지원