Overview

Dataset statistics

Number of variables4
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory36.6 B

Variable types

Text3
Categorical1

Dataset

Description국립낙동강생물자원관의 부서정보입니다. 해당 데이터에는 부서명, 부서영문명, 팩스번호 데이터 추출일 정보가 포함되어 있습니다.
Author국립낙동강생물자원관
URLhttps://www.data.go.kr/data/15039048/fileData.do

Alerts

데이터 기준일 has constant value ""Constant
부서명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:48:22.374279
Analysis finished2023-12-12 22:48:22.694207
Duration0.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부서명
Text

UNIQUE 

Distinct29
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-13T07:48:22.845658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.4827586
Min length3

Characters and Unicode

Total characters159
Distinct characters63
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

Unique29 ?
Unique (%)100.0%

Sample

1st row경영관리본부
2nd row담수생물연구본부
3rd row전략기획실
4th row기획부
5th row혁신성과부
ValueCountFrequency (%)
경영관리본부 1
 
3.4%
식물연구팀 1
 
3.4%
소재상용화연구팀 1
 
3.4%
산업화지원팀 1
 
3.4%
산업화지원센터 1
 
3.4%
생물정보팀 1
 
3.4%
자원은행팀 1
 
3.4%
자원은행정보실 1
 
3.4%
균류연구팀 1
 
3.4%
원생생물연구팀 1
 
3.4%
Other values (19) 19
65.5%
2023-12-13T07:48:23.483132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
연 11
 
6.9%
팀 11
 
6.9%
구 11
 
6.9%
부 10
 
6.3%
물 9
 
5.7%
실 7
 
4.4%
생 7
 
4.4%
원 6
 
3.8%
전 4
 
2.5%
시 3
 
1.9%
Other values (53) 80
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
연 11
 
6.9%
팀 11
 
6.9%
구 11
 
6.9%
부 10
 
6.3%
물 9
 
5.7%
실 7
 
4.4%
생 7
 
4.4%
원 6
 
3.8%
전 4
 
2.5%
시 3
 
1.9%
Other values (53) 80
50.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
연 11
 
6.9%
팀 11
 
6.9%
구 11
 
6.9%
부 10
 
6.3%
물 9
 
5.7%
실 7
 
4.4%
생 7
 
4.4%
원 6
 
3.8%
전 4
 
2.5%
시 3
 
1.9%
Other values (53) 80
50.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
연 11
 
6.9%
팀 11
 
6.9%
구 11
 
6.9%
부 10
 
6.3%
물 9
 
5.7%
실 7
 
4.4%
생 7
 
4.4%
원 6
 
3.8%
전 4
 
2.5%
시 3
 
1.9%
Other values (53) 80
50.3%

부서영문명
Text

Distinct28
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-13T07:48:23.663524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length36
Mean length31.241379
Min length17

Characters and Unicode

Total characters906
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)93.1%

Sample

1st rowAdministrative Management Office
2nd rowFreshwater Bioresources Research Office
3rd rowStrategic Planning Department
4th rowPlanning Division
5th rowPerformance Management Division
ValueCountFrequency (%)
division 12
 
12.1%
research 12
 
12.1%
team 9
 
9.1%
department 6
 
6.1%
6
 
6.1%
bioresources 5
 
5.1%
management 5
 
5.1%
animal 2
 
2.0%
support 2
 
2.0%
industrialization 2
 
2.0%
Other values (28) 38
38.4%
2023-12-13T07:48:24.056020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 97
 
10.7%
e 90
 
9.9%
74
 
8.2%
n 72
 
7.9%
a 69
 
7.6%
o 62
 
6.8%
t 53
 
5.8%
r 52
 
5.7%
s 43
 
4.7%
c 37
 
4.1%
Other values (28) 257
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 734
81.0%
Uppercase Letter 92
 
10.2%
Space Separator 74
 
8.2%
Other Punctuation 6
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 97
13.2%
e 90
12.3%
n 72
9.8%
a 69
9.4%
o 62
8.4%
t 53
7.2%
r 52
7.1%
s 43
 
5.9%
c 37
 
5.0%
m 32
 
4.4%
Other values (13) 127
17.3%
Uppercase Letter
ValueCountFrequency (%)
D 18
19.6%
R 13
14.1%
T 10
10.9%
B 9
9.8%
M 7
 
7.6%
P 7
 
7.6%
A 6
 
6.5%
E 6
 
6.5%
I 4
 
4.3%
F 4
 
4.3%
Other values (3) 8
8.7%
Space Separator
ValueCountFrequency (%)
74
100.0%
Other Punctuation
ValueCountFrequency (%)
& 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 826
91.2%
Common 80
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 97
11.7%
e 90
10.9%
n 72
 
8.7%
a 69
 
8.4%
o 62
 
7.5%
t 53
 
6.4%
r 52
 
6.3%
s 43
 
5.2%
c 37
 
4.5%
m 32
 
3.9%
Other values (26) 219
26.5%
Common
ValueCountFrequency (%)
74
92.5%
& 6
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 906
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 97
 
10.7%
e 90
 
9.9%
74
 
8.2%
n 72
 
7.9%
a 69
 
7.6%
o 62
 
6.8%
t 53
 
5.8%
r 52
 
5.7%
s 43
 
4.7%
c 37
 
4.1%
Other values (28) 257
28.4%

팩스번호
Text

Distinct19
Distinct (%)65.5%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-13T07:48:24.218827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique11 ?
Unique (%)37.9%

Sample

1st row054-530-0709
2nd row054-530-0709
3rd row054-530-0719
4th row054-530-0719
5th row054-530-0729
ValueCountFrequency (%)
054-530-0829 3
 
10.3%
054-530-0889 3
 
10.3%
054-530-0779 2
 
6.9%
054-530-0899 2
 
6.9%
054-530-0869 2
 
6.9%
054-530-0719 2
 
6.9%
054-530-0709 2
 
6.9%
054-530-0739 2
 
6.9%
054-530-0799 1
 
3.4%
054-530-0769 1
 
3.4%
Other values (9) 9
31.0%
2023-12-13T07:48:24.490273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 90
25.9%
5 60
17.2%
- 58
16.7%
9 34
 
9.8%
3 32
 
9.2%
4 31
 
8.9%
8 17
 
4.9%
7 16
 
4.6%
2 4
 
1.1%
6 3
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 90
31.0%
5 60
20.7%
9 34
 
11.7%
3 32
 
11.0%
4 31
 
10.7%
8 17
 
5.9%
7 16
 
5.5%
2 4
 
1.4%
6 3
 
1.0%
1 3
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 90
25.9%
5 60
17.2%
- 58
16.7%
9 34
 
9.8%
3 32
 
9.2%
4 31
 
8.9%
8 17
 
4.9%
7 16
 
4.6%
2 4
 
1.1%
6 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 90
25.9%
5 60
17.2%
- 58
16.7%
9 34
 
9.8%
3 32
 
9.2%
4 31
 
8.9%
8 17
 
4.9%
7 16
 
4.6%
2 4
 
1.1%
6 3
 
0.9%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2022-10-28
29 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-28
2nd row2022-10-28
3rd row2022-10-28
4th row2022-10-28
5th row2022-10-28

Common Values

ValueCountFrequency (%)
2022-10-28 29
100.0%

Length

2023-12-13T07:48:24.631027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:48:24.725870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-28 29
100.0%

Correlations

2023-12-13T07:48:24.783934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
부서명부서영문명팩스번호
부서명1.0001.0001.000
부서영문명1.0001.0000.948
팩스번호1.0000.9481.000

Missing values

2023-12-13T07:48:22.563403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:48:22.658630image/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

부서명부서영문명팩스번호데이터 기준일
0경영관리본부Administrative Management Office054-530-07092022-10-28
1담수생물연구본부Freshwater Bioresources Research Office054-530-07092022-10-28
2전략기획실Strategic Planning Department054-530-07192022-10-28
3기획부Planning Division054-530-07192022-10-28
4혁신성과부Performance Management Division054-530-07292022-10-28
5경영관리실Administrative Management Department054-530-07392022-10-28
6인사총무부Performance Management Division054-530-07392022-10-28
7재무회계부Finance & Accounting Division054-530-07492022-10-28
8시설안전부Facilities Management Division054-530-07592022-10-28
9전시교육실Exhibition & Education Department054-530-07792022-10-28
부서명부서영문명팩스번호데이터 기준일
19환경미생물연구팀Environmental Microbiology Research Team054-530-08792022-10-28
20원생생물연구팀Protozoan Research Team054-530-08492022-10-28
21균류연구팀Fungi Research Team054-530-08592022-10-28
22자원은행정보실Bioresources Collection & Information Technology Division054-530-08992022-10-28
23자원은행팀Bioresources Collection & Research Division054-530-08992022-10-28
24생물정보팀Bioinformation technology Team054-530-09092022-10-28
25산업화지원센터Bioresources Industrialization Support Department054-530-08892022-10-28
26산업화지원팀Bioresources Industrialization Support Division054-530-08892022-10-28
27소재상용화연구팀Biomaterial Commercialization Research Team054-530-08892022-10-28
28감사실Audit & Inspection Division054-530-09192022-10-28