Overview

Dataset statistics

Number of variables6
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory50.6 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description대전광역시 중구 직업소개소 (연번, 유무료 구분, 직업소개소명, 대표자명, 법인개인구분, 사업소도로명주소) 현황정보를 제공합니다.
URLhttps://www.data.go.kr/data/15028095/fileData.do

Alerts

운영방식 is highly overall correlated with 법인개인구분High correlation
법인개인구분 is highly overall correlated with 운영방식High correlation
운영방식 is highly imbalanced (54.6%)Imbalance
연번 has unique valuesUnique
직업소개소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:58:56.335142
Analysis finished2023-12-12 15:58:57.652747
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.5
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-13T00:58:57.808299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.15
Q121.75
median42.5
Q363.25
95-th percentile79.85
Maximum84
Range83
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation24.392622
Coefficient of variation (CV)0.57394404
Kurtosis-1.2
Mean42.5
Median Absolute Deviation (MAD)21
Skewness0
Sum3570
Variance595
MonotonicityStrictly increasing
2023-12-13T00:58:58.041641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%

운영방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
유료
76 
무료
8 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 76
90.5%
무료 8
 
9.5%

Length

2023-12-13T00:58:58.198112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:58:58.339656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 76
90.5%
무료 8
 
9.5%

직업소개소명
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T00:58:58.602911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length24
Mean length6.9166667
Min length3

Characters and Unicode

Total characters581
Distinct characters192
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

Unique84 ?
Unique (%)100.0%

Sample

1st row주식회사 보브시스템
2nd row정인기획
3rd row현대인력
4th row복지여성인력
5th row㈜올제이맨파워
ValueCountFrequency (%)
주식회사 1
 
1.1%
영광인력개발 1
 
1.1%
희망이음터 1
 
1.1%
사회적협동조합 1
 
1.1%
온누리인력센터 1
 
1.1%
조은인력개발 1
 
1.1%
고려인력개발 1
 
1.1%
오성인력건설공사 1
 
1.1%
놀부인력 1
 
1.1%
경영자총협회 1
 
1.1%
Other values (83) 83
89.2%
2023-12-13T00:58:59.137441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 62
 
10.7%
력 54
 
9.3%
사 20
 
3.4%
개 18
 
3.1%
발 15
 
2.6%
대 14
 
2.4%
공 13
 
2.2%
전 11
 
1.9%
성 11
 
1.9%
10
 
1.7%
Other values (182) 353
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 511
88.0%
Lowercase Letter 32
 
5.5%
Space Separator 10
 
1.7%
Open Punctuation 9
 
1.5%
Close Punctuation 9
 
1.5%
Uppercase Letter 8
 
1.4%
Other Punctuation 1
 
0.2%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 62
 
12.1%
력 54
 
10.6%
사 20
 
3.9%
개 18
 
3.5%
발 15
 
2.9%
대 14
 
2.7%
공 13
 
2.5%
전 11
 
2.2%
성 11
 
2.2%
주 8
 
1.6%
Other values (156) 285
55.8%
Lowercase Letter
ValueCountFrequency (%)
n 6
18.8%
e 4
12.5%
i 4
12.5%
a 3
9.4%
t 3
9.4%
c 2
 
6.2%
r 2
 
6.2%
g 2
 
6.2%
y 1
 
3.1%
u 1
 
3.1%
Other values (4) 4
12.5%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
R 1
12.5%
I 1
12.5%
J 1
12.5%
C 1
12.5%
W 1
12.5%
Y 1
12.5%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 512
88.1%
Latin 40
 
6.9%
Common 29
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 62
 
12.1%
력 54
 
10.5%
사 20
 
3.9%
개 18
 
3.5%
발 15
 
2.9%
대 14
 
2.7%
공 13
 
2.5%
전 11
 
2.1%
성 11
 
2.1%
주 8
 
1.6%
Other values (157) 286
55.9%
Latin
ValueCountFrequency (%)
n 6
15.0%
e 4
 
10.0%
i 4
 
10.0%
a 3
 
7.5%
t 3
 
7.5%
c 2
 
5.0%
r 2
 
5.0%
g 2
 
5.0%
A 2
 
5.0%
y 1
 
2.5%
Other values (11) 11
27.5%
Common
ValueCountFrequency (%)
10
34.5%
( 9
31.0%
) 9
31.0%
· 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 511
88.0%
ASCII 68
 
11.7%
None 2
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 62
 
12.1%
력 54
 
10.6%
사 20
 
3.9%
개 18
 
3.5%
발 15
 
2.9%
대 14
 
2.7%
공 13
 
2.5%
전 11
 
2.2%
성 11
 
2.2%
주 8
 
1.6%
Other values (156) 285
55.8%
ASCII
ValueCountFrequency (%)
10
14.7%
( 9
13.2%
) 9
13.2%
n 6
 
8.8%
e 4
 
5.9%
i 4
 
5.9%
a 3
 
4.4%
t 3
 
4.4%
c 2
 
2.9%
r 2
 
2.9%
Other values (14) 16
23.5%
None
ValueCountFrequency (%)
· 1
50.0%
㈜ 1
50.0%

대표자명
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T00:58:59.510549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters252
Distinct characters102
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

Unique82 ?
Unique (%)97.6%

Sample

1st row김미란
2nd row정혜영
3rd row이상은
4th row김영미
5th row신성욱
ValueCountFrequency (%)
김영미 2
 
2.4%
유미정 1
 
1.2%
김인희 1
 
1.2%
김봉식 1
 
1.2%
강선구 1
 
1.2%
박지영 1
 
1.2%
이수광 1
 
1.2%
강도묵 1
 
1.2%
민항기 1
 
1.2%
이정욱 1
 
1.2%
Other values (73) 73
86.9%
2023-12-13T00:59:00.102525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 21
 
8.3%
이 12
 
4.8%
영 11
 
4.4%
정 10
 
4.0%
박 7
 
2.8%
민 7
 
2.8%
미 7
 
2.8%
상 6
 
2.4%
현 6
 
2.4%
한 5
 
2.0%
Other values (92) 160
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 21
 
8.3%
이 12
 
4.8%
영 11
 
4.4%
정 10
 
4.0%
박 7
 
2.8%
민 7
 
2.8%
미 7
 
2.8%
상 6
 
2.4%
현 6
 
2.4%
한 5
 
2.0%
Other values (92) 160
63.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 21
 
8.3%
이 12
 
4.8%
영 11
 
4.4%
정 10
 
4.0%
박 7
 
2.8%
민 7
 
2.8%
미 7
 
2.8%
상 6
 
2.4%
현 6
 
2.4%
한 5
 
2.0%
Other values (92) 160
63.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 252
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 21
 
8.3%
이 12
 
4.8%
영 11
 
4.4%
정 10
 
4.0%
박 7
 
2.8%
민 7
 
2.8%
미 7
 
2.8%
상 6
 
2.4%
현 6
 
2.4%
한 5
 
2.0%
Other values (92) 160
63.5%

법인개인구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
개인
70 
법인
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row법인
2nd row개인
3rd row개인
4th row개인
5th row법인

Common Values

ValueCountFrequency (%)
개인 70
83.3%
법인 14
 
16.7%

Length

2023-12-13T00:59:00.313864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:00.443304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 70
83.3%
법인 14
 
16.7%

사업장주소
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-13T00:59:00.729610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length40.5
Mean length29.797619
Min length21

Characters and Unicode

Total characters2503
Distinct characters90
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)97.6%

Sample

1st row대전광역시 중구 대종로550번길 5. 유원오피스텔 12층 1212호 (선화동)
2nd row대전광역시 중구 태평로93번길 46. 1층 (태평동)
3rd row대전광역시 중구 계백로 1636-1 (유천동)
4th row대전광역시 중구 계백로 1719. 센트리아오피스텔 1607호 (오류동)
5th row대전광역시 중구 충무로 174. 101호 (문창동)
ValueCountFrequency (%)
대전광역시 84
 
16.0%
중구 84
 
16.0%
2층 23
 
4.4%
1층 14
 
2.7%
계백로 14
 
2.7%
유천동 13
 
2.5%
오류동 11
 
2.1%
산성동 10
 
1.9%
대종로 8
 
1.5%
1719 8
 
1.5%
Other values (162) 256
48.8%
2023-12-13T00:59:01.208071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
441
 
17.6%
대 120
 
4.8%
1 106
 
4.2%
동 92
 
3.7%
중 91
 
3.6%
전 85
 
3.4%
) 84
 
3.4%
로 84
 
3.4%
구 84
 
3.4%
시 84
 
3.4%
Other values (80) 1232
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1363
54.5%
Space Separator 441
 
17.6%
Decimal Number 437
 
17.5%
Close Punctuation 84
 
3.4%
Open Punctuation 84
 
3.4%
Other Punctuation 80
 
3.2%
Dash Punctuation 14
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 120
 
8.8%
동 92
 
6.7%
중 91
 
6.7%
전 85
 
6.2%
로 84
 
6.2%
구 84
 
6.2%
시 84
 
6.2%
역 84
 
6.2%
광 84
 
6.2%
층 66
 
4.8%
Other values (65) 489
35.9%
Decimal Number
ValueCountFrequency (%)
1 106
24.3%
2 79
18.1%
3 40
 
9.2%
4 35
 
8.0%
0 32
 
7.3%
5 32
 
7.3%
6 31
 
7.1%
9 30
 
6.9%
8 27
 
6.2%
7 25
 
5.7%
Space Separator
ValueCountFrequency (%)
441
100.0%
Close Punctuation
ValueCountFrequency (%)
) 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 84
100.0%
Other Punctuation
ValueCountFrequency (%)
. 80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1363
54.5%
Common 1140
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 120
 
8.8%
동 92
 
6.7%
중 91
 
6.7%
전 85
 
6.2%
로 84
 
6.2%
구 84
 
6.2%
시 84
 
6.2%
역 84
 
6.2%
광 84
 
6.2%
층 66
 
4.8%
Other values (65) 489
35.9%
Common
ValueCountFrequency (%)
441
38.7%
1 106
 
9.3%
) 84
 
7.4%
( 84
 
7.4%
. 80
 
7.0%
2 79
 
6.9%
3 40
 
3.5%
4 35
 
3.1%
0 32
 
2.8%
5 32
 
2.8%
Other values (5) 127
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1363
54.5%
ASCII 1140
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
441
38.7%
1 106
 
9.3%
) 84
 
7.4%
( 84
 
7.4%
. 80
 
7.0%
2 79
 
6.9%
3 40
 
3.5%
4 35
 
3.1%
0 32
 
2.8%
5 32
 
2.8%
Other values (5) 127
 
11.1%
Hangul
ValueCountFrequency (%)
대 120
 
8.8%
동 92
 
6.7%
중 91
 
6.7%
전 85
 
6.2%
로 84
 
6.2%
구 84
 
6.2%
시 84
 
6.2%
역 84
 
6.2%
광 84
 
6.2%
층 66
 
4.8%
Other values (65) 489
35.9%

Interactions

2023-12-13T00:58:57.283895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:59:01.317492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번운영방식직업소개소명대표자명법인개인구분사업장주소
연번1.0000.0001.0000.9470.0000.931
운영방식0.0001.0001.0001.0000.7651.000
직업소개소명1.0001.0001.0001.0001.0001.000
대표자명0.9471.0001.0001.0001.0000.999
법인개인구분0.0000.7651.0001.0001.0001.000
사업장주소0.9311.0001.0000.9991.0001.000
2023-12-13T00:59:01.425519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영방식법인개인구분
운영방식1.0000.555
법인개인구분0.5551.000
2023-12-13T00:59:01.587821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번운영방식법인개인구분
연번1.0000.0000.000
운영방식0.0001.0000.555
법인개인구분0.0000.5551.000

Missing values

2023-12-13T00:58:57.417703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:58:57.579051image/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

연번운영방식직업소개소명대표자명법인개인구분사업장주소
01유료주식회사 보브시스템김미란법인대전광역시 중구 대종로550번길 5. 유원오피스텔 12층 1212호 (선화동)
12유료정인기획정혜영개인대전광역시 중구 태평로93번길 46. 1층 (태평동)
23유료현대인력이상은개인대전광역시 중구 계백로 1636-1 (유천동)
34유료복지여성인력김영미개인대전광역시 중구 계백로 1719. 센트리아오피스텔 1607호 (오류동)
45유료㈜올제이맨파워신성욱법인대전광역시 중구 충무로 174. 101호 (문창동)
56유료가가전공사김병열개인대전광역시 중구 당디로 81-1. 2층 (산성동)
67유료대성인력센터오삼균개인대전광역시 중구 문창로 116. 1층 (문창동)
78유료엄지인력김민서개인대전광역시 중구 대종로 142-5. 2층 2호 (호동)
89유료인투인송지현개인대전광역시 중구 계백로 1619. 벽산프라자 지하1층 20호 (유천동)
910유료메디앤잡진도연개인대전광역시 중구 보문산로 398-1. 402호 (대사동)
연번운영방식직업소개소명대표자명법인개인구분사업장주소
7475유료복음여성인력장향옥개인대전광역시 중구 산성로 55. 206호 (산성동)
7576유료믿음직업소개소윤석운개인대전광역시 중구 대종로 223. 석정빌딩 6층 601호 (석교동)
7677유료신성인력개발신병래개인대전광역시 중구 보문산로 32. 3층 (산성동)
7778유료그린여성인력문성섭개인대전광역시 중구 계백로 1719. 1924호 (오류동.센트리아오피스텔 19층)
7879유료남부인력공사김영미개인대전광역시 중구 문화로 75. 2층 (유천동)
7980유료은혜여성인력김민옥개인대전광역시 중구 계백로 1619. 벽산프라자 지하층 25호 (유천동)
8081유료한성인력개발공사한태홍개인대전광역시 중구 동서대로 1323-1 (용두동.2층)
8182무료(사)대전광역시장애인단체총연합회무료직업소개소황경아법인대전광역시 중구 보문로 246. 7층 705호 (대흥동. 대림빌딩)
8283유료중부인력개발홍금표개인대전광역시 중구 동서대로 1407. 3층 (목동)
8384유료서부인력공사권만주개인대전광역시 중구 계백로 1540 (유천동.2층)