Overview

Dataset statistics

Number of variables6
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory51.8 B

Variable types

Numeric1
Text2
Categorical3

Dataset

Description한국고용정보원이 취업소개 또는 취업정보 제공 등의 방법으로 구인자 및 구직자에 대한 고용서비스 향상에 기여한 민간고용서비스기관의 신청을 받아 심사하여 고용서비스우수기관으로 인증
Author고용노동부
URLhttps://www.data.go.kr/data/15028034/fileData.do

Alerts

연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 13:57:29.683330
Analysis finished2024-03-14 13:57:31.046905
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 B
2024-03-14T22:57:31.271374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2024-03-14T22:57:31.693717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

기관명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size496.0 B
2024-03-14T22:57:32.587836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length12.652174
Min length7

Characters and Unicode

Total characters582
Distinct characters120
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row대전YWCA 여성인력개발센터
2nd row마산여성인력개발센터
3rd row부산동래여성인력개발센터
4th row부산진여성인력개발센터
5th row(사)경남경영자총협회
ValueCountFrequency (%)
주)지에스씨넷 8
 
10.7%
주)제니엘 3
 
4.0%
주식회사 3
 
4.0%
주)일로이룸 3
 
4.0%
주)한국커리어잡스 2
 
2.7%
잡플랜컨설팅 2
 
2.7%
주)제이엠커리어 2
 
2.7%
사단법인 2
 
2.7%
영주지점 1
 
1.3%
세종지점 1
 
1.3%
Other values (48) 48
64.0%
2024-03-14T22:57:34.111860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 34
 
5.8%
( 31
 
5.3%
) 31
 
5.3%
지 29
 
5.0%
29
 
5.0%
터 18
 
3.1%
센 17
 
2.9%
스 16
 
2.7%
사 15
 
2.6%
인 15
 
2.6%
Other values (110) 347
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 483
83.0%
Open Punctuation 31
 
5.3%
Close Punctuation 31
 
5.3%
Space Separator 29
 
5.0%
Uppercase Letter 8
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 34
 
7.0%
지 29
 
6.0%
터 18
 
3.7%
센 17
 
3.5%
스 16
 
3.3%
사 15
 
3.1%
인 15
 
3.1%
점 13
 
2.7%
성 13
 
2.7%
개 11
 
2.3%
Other values (103) 302
62.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Space Separator
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
83.0%
Common 91
 
15.6%
Latin 8
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 34
 
7.0%
지 29
 
6.0%
터 18
 
3.7%
센 17
 
3.5%
스 16
 
3.3%
사 15
 
3.1%
인 15
 
3.1%
점 13
 
2.7%
성 13
 
2.7%
개 11
 
2.3%
Other values (103) 302
62.5%
Latin
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%
Common
ValueCountFrequency (%)
( 31
34.1%
) 31
34.1%
29
31.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
83.0%
ASCII 99
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 34
 
7.0%
지 29
 
6.0%
터 18
 
3.7%
센 17
 
3.5%
스 16
 
3.3%
사 15
 
3.1%
인 15
 
3.1%
점 13
 
2.7%
성 13
 
2.7%
개 11
 
2.3%
Other values (103) 302
62.5%
ASCII
ValueCountFrequency (%)
( 31
31.3%
) 31
31.3%
29
29.3%
A 2
 
2.0%
C 2
 
2.0%
W 2
 
2.0%
Y 2
 
2.0%

대표자
Text

Distinct29
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size496.0 B
2024-03-14T22:57:34.817801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0217391
Min length3

Characters and Unicode

Total characters139
Distinct characters52
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

Unique21 ?
Unique (%)45.7%

Sample

1st row강은혜
2nd row박주옥
3rd row이숙련
4th row김미숙
5th row이상연
ValueCountFrequency (%)
박용수 8
17.4%
최병철 4
 
8.7%
박춘홍 3
 
6.5%
유인순 2
 
4.3%
이영옥 2
 
4.3%
윤종만 2
 
4.3%
이낙준 2
 
4.3%
이수연 2
 
4.3%
윤영구 1
 
2.2%
이석진 1
 
2.2%
Other values (19) 19
41.3%
2024-03-14T22:57:36.129893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
박 16
 
11.5%
수 11
 
7.9%
이 11
 
7.9%
용 8
 
5.8%
병 5
 
3.6%
영 5
 
3.6%
홍 4
 
2.9%
김 4
 
2.9%
철 4
 
2.9%
최 4
 
2.9%
Other values (42) 67
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
박 16
 
11.5%
수 11
 
7.9%
이 11
 
7.9%
용 8
 
5.8%
병 5
 
3.6%
영 5
 
3.6%
홍 4
 
2.9%
김 4
 
2.9%
철 4
 
2.9%
최 4
 
2.9%
Other values (42) 67
48.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
박 16
 
11.5%
수 11
 
7.9%
이 11
 
7.9%
용 8
 
5.8%
병 5
 
3.6%
영 5
 
3.6%
홍 4
 
2.9%
김 4
 
2.9%
철 4
 
2.9%
최 4
 
2.9%
Other values (42) 67
48.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
박 16
 
11.5%
수 11
 
7.9%
이 11
 
7.9%
용 8
 
5.8%
병 5
 
3.6%
영 5
 
3.6%
홍 4
 
2.9%
김 4
 
2.9%
철 4
 
2.9%
최 4
 
2.9%
Other values (42) 67
48.2%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size496.0 B
재인증
31 
신규
15 

Length

Max length3
Median length3
Mean length2.673913
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재인증 31
67.4%
신규 15
32.6%

Length

2024-03-14T22:57:36.652604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:57:37.017224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재인증 31
67.4%
신규 15
32.6%

지역
Categorical

Distinct21
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size496.0 B
서울
11 
대구
9 
부산
4 
창원
3 
대전
2 
Other values (16)
17 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique15 ?
Unique (%)32.6%

Sample

1st row대전
2nd row창원
3rd row부산
4th row부산
5th row창원

Common Values

ValueCountFrequency (%)
서울 11
23.9%
대구 9
19.6%
부산 4
 
8.7%
창원 3
 
6.5%
대전 2
 
4.3%
청주 2
 
4.3%
울산 1
 
2.2%
성남 1
 
2.2%
안산 1
 
2.2%
인천 1
 
2.2%
Other values (11) 11
23.9%

Length

2024-03-14T22:57:37.391729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 11
23.9%
대구 9
19.6%
부산 4
 
8.7%
창원 3
 
6.5%
대전 2
 
4.3%
청주 2
 
4.3%
영주 1
 
2.2%
구미 1
 
2.2%
통영 1
 
2.2%
천안 1
 
2.2%
Other values (11) 11
23.9%

분야
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size496.0 B
유료
31 
무료
14 
직업정보제공
 
1

Length

Max length6
Median length2
Mean length2.0869565
Min length2

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
유료 31
67.4%
무료 14
30.4%
직업정보제공 1
 
2.2%

Length

2024-03-14T22:57:37.986919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:57:38.179575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 31
67.4%
무료 14
30.4%
직업정보제공 1
 
2.2%

Interactions

2024-03-14T22:57:30.216241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:57:38.296810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기관명대표자구분지역분야
연번1.0001.0000.9410.7800.6260.702
기관명1.0001.0001.0001.0001.0001.000
대표자0.9411.0001.0000.0000.0001.000
구분0.7801.0000.0001.0000.3870.000
지역0.6261.0000.0000.3871.0000.000
분야0.7021.0001.0000.0000.0001.000
2024-03-14T22:57:38.468530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분분야지역
구분1.0000.0000.239
분야0.0001.0000.000
지역0.2390.0001.000
2024-03-14T22:57:38.616475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분지역분야
연번1.0000.5540.2370.475
구분0.5541.0000.2390.000
지역0.2370.2391.0000.000
분야0.4750.0000.0001.000

Missing values

2024-03-14T22:57:30.538991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:57:30.959630image/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

연번기관명대표자구분지역분야
01대전YWCA 여성인력개발센터강은혜재인증대전무료
12마산여성인력개발센터박주옥재인증창원무료
23부산동래여성인력개발센터이숙련재인증부산무료
34부산진여성인력개발센터김미숙재인증부산무료
45(사)경남경영자총협회이상연재인증창원무료
56(사)벤처기업협회성상엽신규서울무료
67(사)중소기업기술혁신협회임병훈재인증성남무료
78사단법인 청주YWCA 충북여성인력개발센터점김경민재인증청주무료
89서대문여성인력개발센터박정숙재인증서울무료
910스탭스주식회사박천웅재인증서울유료
연번기관명대표자구분지역분야
3637주식회사 커리어스타이영옥재인증대구유료
3738(주)커리어스타 달서지점이영옥재인증대구유료
3839(주)한국커리어잡스 대전지사유인순재인증대전유료
3940한국건설기술인협회윤영구재인증서울직업정보제공
4041(주)한국커리어잡스 통영지사유인순신규통영유료
4142(주)제이엠커리어 창원지점윤종만신규창원유료
4243(주)일로이룸강북취업지원센터최병철신규대구유료
4344사단법인 한국고용협회 수원지사조현수신규수원무료
4445(사)여성중앙회 종로여성인력개발센터김영실신규서울무료
4546(주)행복인디제이이종찬신규대구유료