Overview

Dataset statistics

Number of variables5
Number of observations395
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.9 KiB
Average record size in memory41.3 B

Variable types

Numeric1
Text2
Categorical2

Dataset

Description한국산업기술진흥원 홈페이지 관련 직원 정보 입니다. 한국산업기술진흥원의 직원 목록 데이터로서 부서, 직책, 직급, 성명 등의 데이터를 제공합니다.
Author한국산업기술진흥원
URLhttps://www.data.go.kr/data/15070092/fileData.do

Alerts

직책명 is highly overall correlated with 직급High correlation
직급 is highly overall correlated with 직책명High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:58:27.726339
Analysis finished2023-12-12 15:58:28.232956
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct395
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198
Minimum1
Maximum395
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2023-12-13T00:58:28.340484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.7
Q199.5
median198
Q3296.5
95-th percentile375.3
Maximum395
Range394
Interquartile range (IQR)197

Descriptive statistics

Standard deviation114.17092
Coefficient of variation (CV)0.57662083
Kurtosis-1.2
Mean198
Median Absolute Deviation (MAD)99
Skewness0
Sum78210
Variance13035
MonotonicityStrictly increasing
2023-12-13T00:58:28.561148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
273 1
 
0.3%
271 1
 
0.3%
270 1
 
0.3%
269 1
 
0.3%
268 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
Other values (385) 385
97.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
395 1
0.3%
394 1
0.3%
393 1
0.3%
392 1
0.3%
391 1
0.3%
390 1
0.3%
389 1
0.3%
388 1
0.3%
387 1
0.3%
386 1
0.3%

부서명
Text

Distinct53
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-13T00:58:28.824617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length7
Mean length6.5822785
Min length3

Characters and Unicode

Total characters2600
Distinct characters101
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)4.3%

Sample

1st row원장실
2nd row감사실
3rd row감사실
4th row감사실
5th row감사실
ValueCountFrequency (%)
지역산업육성실 15
 
3.8%
산업인재전략실 15
 
3.8%
기업성장지원실 15
 
3.8%
지역산업전략실 14
 
3.5%
혁신인재양성실 14
 
3.5%
사업화지원실 14
 
3.5%
중견기업혁신실 14
 
3.5%
산업공급망진흥실 14
 
3.5%
기술동향조사실 13
 
3.2%
산업기술oda실 13
 
3.2%
Other values (45) 259
64.8%
2023-12-13T00:58:29.247256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
실 350
 
13.5%
업 202
 
7.8%
기 136
 
5.2%
산 127
 
4.9%
지 79
 
3.0%
사 68
 
2.6%
혁 67
 
2.6%
신 67
 
2.6%
제 57
 
2.2%
성 56
 
2.2%
Other values (91) 1391
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2512
96.6%
Uppercase Letter 83
 
3.2%
Space Separator 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 350
 
13.9%
업 202
 
8.0%
기 136
 
5.4%
산 127
 
5.1%
지 79
 
3.1%
사 68
 
2.7%
혁 67
 
2.7%
신 67
 
2.7%
제 57
 
2.3%
성 56
 
2.2%
Other values (80) 1303
51.9%
Uppercase Letter
ValueCountFrequency (%)
A 16
19.3%
D 14
16.9%
O 13
15.7%
G 10
12.0%
S 10
12.0%
E 10
12.0%
I 3
 
3.6%
K 3
 
3.6%
T 3
 
3.6%
P 1
 
1.2%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2512
96.6%
Latin 83
 
3.2%
Common 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 350
 
13.9%
업 202
 
8.0%
기 136
 
5.4%
산 127
 
5.1%
지 79
 
3.1%
사 68
 
2.7%
혁 67
 
2.7%
신 67
 
2.7%
제 57
 
2.3%
성 56
 
2.2%
Other values (80) 1303
51.9%
Latin
ValueCountFrequency (%)
A 16
19.3%
D 14
16.9%
O 13
15.7%
G 10
12.0%
S 10
12.0%
E 10
12.0%
I 3
 
3.6%
K 3
 
3.6%
T 3
 
3.6%
P 1
 
1.2%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2512
96.6%
ASCII 88
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
실 350
 
13.9%
업 202
 
8.0%
기 136
 
5.4%
산 127
 
5.1%
지 79
 
3.1%
사 68
 
2.7%
혁 67
 
2.7%
신 67
 
2.7%
제 57
 
2.3%
성 56
 
2.2%
Other values (80) 1303
51.9%
ASCII
ValueCountFrequency (%)
A 16
18.2%
D 14
15.9%
O 13
14.8%
G 10
11.4%
S 10
11.4%
E 10
11.4%
5
 
5.7%
I 3
 
3.4%
K 3
 
3.4%
T 3
 
3.4%

성명
Text

Distinct387
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2023-12-13T00:58:29.669722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9898734
Min length2

Characters and Unicode

Total characters1181
Distinct characters159
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

Unique379 ?
Unique (%)95.9%

Sample

1st row민병주
2nd row이기녕
3rd row박선우
4th row남경우
5th row이택수
ValueCountFrequency (%)
정지은 2
 
0.5%
김상훈 2
 
0.5%
김보람 2
 
0.5%
정희주 2
 
0.5%
정유진 2
 
0.5%
최재혁 2
 
0.5%
김민경 2
 
0.5%
김동영 2
 
0.5%
박은영 1
 
0.3%
박경호 1
 
0.3%
Other values (377) 377
95.4%
2023-12-13T00:58:30.378496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 67
 
5.7%
이 60
 
5.1%
정 49
 
4.1%
영 45
 
3.8%
민 34
 
2.9%
박 33
 
2.8%
진 33
 
2.8%
주 29
 
2.5%
지 28
 
2.4%
현 28
 
2.4%
Other values (149) 775
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1181
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 67
 
5.7%
이 60
 
5.1%
정 49
 
4.1%
영 45
 
3.8%
민 34
 
2.9%
박 33
 
2.8%
진 33
 
2.8%
주 29
 
2.5%
지 28
 
2.4%
현 28
 
2.4%
Other values (149) 775
65.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1181
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 67
 
5.7%
이 60
 
5.1%
정 49
 
4.1%
영 45
 
3.8%
민 34
 
2.9%
박 33
 
2.8%
진 33
 
2.8%
주 29
 
2.5%
지 28
 
2.4%
현 28
 
2.4%
Other values (149) 775
65.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1181
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 67
 
5.7%
이 60
 
5.1%
정 49
 
4.1%
영 45
 
3.8%
민 34
 
2.9%
박 33
 
2.8%
진 33
 
2.8%
주 29
 
2.5%
지 28
 
2.4%
현 28
 
2.4%
Other values (149) 775
65.6%

직급
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2급
142 
4급
121 
3급
93 
1급
34 
전문계약직
 
3
Other values (2)
 
2

Length

Max length5
Median length2
Mean length2.0253165
Min length2

Unique

Unique2 ?
Unique (%)0.5%

Sample

1st row임원
2nd row1급
3rd row2급
4th row2급
5th row2급

Common Values

ValueCountFrequency (%)
2급 142
35.9%
4급 121
30.6%
3급 93
23.5%
1급 34
 
8.6%
전문계약직 3
 
0.8%
임원 1
 
0.3%
전문관 1
 
0.3%

Length

2023-12-13T00:58:30.564741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:58:30.726541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2급 142
35.9%
4급 121
30.6%
3급 93
23.5%
1급 34
 
8.6%
전문계약직 3
 
0.8%
임원 1
 
0.3%
전문관 1
 
0.3%

직책명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
책임연구원
142 
연구원
121 
선임연구원
93 
수석연구원
34 
<NA>
 
4

Length

Max length5
Median length5
Mean length4.3696203
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row원장
2nd row수석연구원
3rd row책임연구원
4th row책임연구원
5th row책임연구원

Common Values

ValueCountFrequency (%)
책임연구원 142
35.9%
연구원 121
30.6%
선임연구원 93
23.5%
수석연구원 34
 
8.6%
<NA> 4
 
1.0%
원장 1
 
0.3%

Length

2023-12-13T00:58:30.892051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:58:31.049339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
책임연구원 142
35.9%
연구원 121
30.6%
선임연구원 93
23.5%
수석연구원 34
 
8.6%
na 4
 
1.0%
원장 1
 
0.3%

Interactions

2023-12-13T00:58:27.974965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:58:31.160242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번부서명직급직책명
순번1.0000.9940.0800.000
부서명0.9941.0000.7480.815
직급0.0800.7481.0001.000
직책명0.0000.8151.0001.000
2023-12-13T00:58:31.264606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
직책명직급
직책명1.0001.000
직급1.0001.000
2023-12-13T00:58:31.361932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번직급직책명
순번1.0000.0390.000
직급0.0391.0001.000
직책명0.0001.0001.000

Missing values

2023-12-13T00:58:28.090673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:58:28.188614image/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

순번부서명성명직급직책명
01원장실민병주임원원장
12감사실이기녕1급수석연구원
23감사실박선우2급책임연구원
34감사실남경우2급책임연구원
45감사실이택수2급책임연구원
56감사실한승석2급책임연구원
67감사실윤명진2급책임연구원
78감사실김나현2급책임연구원
89대외협력실신희균2급책임연구원
910대외협력실김지연2급책임연구원
순번부서명성명직급직책명
385386산업기술ODA실이재진3급선임연구원
386387산업기술ODA실장민석3급선임연구원
387388산업기술ODA실손호영4급연구원
388389산업기술ODA실최대웅4급연구원
389390산업기술ODA실강메자빈4급연구원
390391산업기술ODA실정유진4급연구원
391392산업기술ODA실허유진4급연구원
392393산업기술ODA실이호준3급선임연구원
393394한국산업기술진흥원 노동조합이상주2급책임연구원
394395한국산업기술진흥원 노동조합정완기3급선임연구원