Overview

Dataset statistics

Number of variables3
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory28.3 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description사립학교교직원연금공단 임직원 자격증 보유 현황(2022.12.31. 기준)의 데이터로 구분, 자격증명, 인원 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15113246/fileData.do

Alerts

자격증명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:05:04.853954
Analysis finished2023-12-12 09:05:05.167473
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
금융
23 
기타
9 
전산
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금융 23
57.5%
기타 9
 
22.5%
전산 8
 
20.0%

Length

2023-12-12T18:05:05.228019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:05:05.313806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금융 23
57.5%
기타 9
 
22.5%
전산 8
 
20.0%

자격증명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:05:05.475928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.35
Min length3

Characters and Unicode

Total characters334
Distinct characters102
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st rowAFPK(재무설계사)
2nd rowAICPA(미국공인회계사)
3rd rowFRM(재무위험관리사)
4th rowCFA(공인재무분석사)
5th rowCAIA(국제대체투자분석사)
ValueCountFrequency (%)
1급 3
 
6.7%
컴퓨터활용능력 2
 
4.4%
외환전문역 1
 
2.2%
공인중개사 1
 
2.2%
사회복지사 1
 
2.2%
사회조사분석사2급 1
 
2.2%
요양보호사 1
 
2.2%
간호사 1
 
2.2%
공인노무사 1
 
2.2%
개인정보관리사 1
 
2.2%
Other values (32) 32
71.1%
2023-12-12T18:05:05.780984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 30
 
9.0%
자 19
 
5.7%
인 12
 
3.6%
투 11
 
3.3%
권 8
 
2.4%
A 7
 
2.1%
무 7
 
2.1%
급 7
 
2.1%
( 7
 
2.1%
) 7
 
2.1%
Other values (92) 219
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 277
82.9%
Uppercase Letter 31
 
9.3%
Open Punctuation 7
 
2.1%
Close Punctuation 7
 
2.1%
Decimal Number 7
 
2.1%
Space Separator 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 30
 
10.8%
자 19
 
6.9%
인 12
 
4.3%
투 11
 
4.0%
권 8
 
2.9%
무 7
 
2.5%
급 7
 
2.5%
리 7
 
2.5%
상 6
 
2.2%
관 6
 
2.2%
Other values (77) 164
59.2%
Uppercase Letter
ValueCountFrequency (%)
A 7
22.6%
C 5
16.1%
M 4
12.9%
P 3
9.7%
F 3
9.7%
S 3
9.7%
I 3
9.7%
O 1
 
3.2%
R 1
 
3.2%
K 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 4
57.1%
2 3
42.9%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 277
82.9%
Latin 31
 
9.3%
Common 26
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 30
 
10.8%
자 19
 
6.9%
인 12
 
4.3%
투 11
 
4.0%
권 8
 
2.9%
무 7
 
2.5%
급 7
 
2.5%
리 7
 
2.5%
상 6
 
2.2%
관 6
 
2.2%
Other values (77) 164
59.2%
Latin
ValueCountFrequency (%)
A 7
22.6%
C 5
16.1%
M 4
12.9%
P 3
9.7%
F 3
9.7%
S 3
9.7%
I 3
9.7%
O 1
 
3.2%
R 1
 
3.2%
K 1
 
3.2%
Common
ValueCountFrequency (%)
( 7
26.9%
) 7
26.9%
5
19.2%
1 4
15.4%
2 3
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 277
82.9%
ASCII 57
 
17.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 30
 
10.8%
자 19
 
6.9%
인 12
 
4.3%
투 11
 
4.0%
권 8
 
2.9%
무 7
 
2.5%
급 7
 
2.5%
리 7
 
2.5%
상 6
 
2.2%
관 6
 
2.2%
Other values (77) 164
59.2%
ASCII
ValueCountFrequency (%)
A 7
12.3%
( 7
12.3%
) 7
12.3%
5
8.8%
C 5
8.8%
1 4
7.0%
M 4
7.0%
2 3
 
5.3%
P 3
 
5.3%
F 3
 
5.3%
Other values (5) 9
15.8%

인원
Real number (ℝ)

Distinct16
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.525
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:05:05.909955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5.5
Q313
95-th percentile33.15
Maximum51
Range50
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.272812
Coefficient of variation (CV)1.1834973
Kurtosis4.4880589
Mean9.525
Median Absolute Deviation (MAD)3.5
Skewness2.1196205
Sum381
Variance127.07628
MonotonicityNot monotonic
2023-12-12T18:05:06.036448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3 7
17.5%
1 6
15.0%
7 4
10.0%
14 3
7.5%
2 3
7.5%
33 2
 
5.0%
6 2
 
5.0%
8 2
 
5.0%
13 2
 
5.0%
5 2
 
5.0%
Other values (6) 7
17.5%
ValueCountFrequency (%)
1 6
15.0%
2 3
7.5%
3 7
17.5%
4 2
 
5.0%
5 2
 
5.0%
6 2
 
5.0%
7 4
10.0%
8 2
 
5.0%
12 1
 
2.5%
13 2
 
5.0%
ValueCountFrequency (%)
51 1
 
2.5%
36 1
 
2.5%
33 2
5.0%
25 1
 
2.5%
16 1
 
2.5%
14 3
7.5%
13 2
5.0%
12 1
 
2.5%
8 2
5.0%
7 4
10.0%

Interactions

2023-12-12T18:05:04.971635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:05:06.474514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분자격증명인원
구분1.0001.0000.269
자격증명1.0001.0001.000
인원0.2691.0001.000
2023-12-12T18:05:06.557411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원구분
인원1.0000.265
구분0.2651.000

Missing values

2023-12-12T18:05:05.070707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:05:05.137545image/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

구분자격증명인원
0금융AFPK(재무설계사)3
1금융AICPA(미국공인회계사)1
2금융FRM(재무위험관리사)4
3금융CFA(공인재무분석사)3
4금융CAIA(국제대체투자분석사)3
5금융금융자산관리사7
6금융금융투자분석사7
7금융선물거래상담사4
8금융일반운용전문인력5
9금융재무위험관리사7
구분자격증명인원
30기타개인정보관리사 1급2
31기타재난안전지도사 1급6
32전산CISA(정보시스템감사사)2
33전산MCP(MS 공인기술자격증)1
34전산MOS6
35전산사무자동화산업기사13
36전산워드프로세서33
37전산정보처리기사14
38전산컴퓨터활용능력 1급51
39전산컴퓨터활용능력 2급33