Overview

Dataset statistics

Number of variables6
Number of observations71
Missing cells11
Missing cells (%)2.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory49.9 B

Variable types

Text3
Categorical3

Dataset

Description연수구 관내 유무료 직업소개소 현황에 대한 데이터입니다.본 데이터에는 직업소개소명, 전화번호, 주소, 유/무료여부가 기재되어 있습니다
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3081073&srcSe=7661IVAWM27C61E190

Alerts

구분 is highly overall correlated with 직종 and 1 other fieldsHigh correlation
기타유의사항 is highly overall correlated with 구분High correlation
직종 is highly overall correlated with 구분High correlation
구분 is highly imbalanced (50.2%)Imbalance
기타유의사항 is highly imbalanced (56.5%)Imbalance
전화번호 has 11 (15.5%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:14:35.207001
Analysis finished2024-03-18 04:14:35.946958
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-03-18T13:14:36.096432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length7.5070423
Min length2

Characters and Unicode

Total characters533
Distinct characters171
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

Unique71 ?
Unique (%)100.0%

Sample

1st row한빛종합개발
2nd row파출박사연수점
3rd row㈜금정개발
4th row스피드인력
5th row동부파출부
ValueCountFrequency (%)
주식회사 6
 
6.7%
휴먼잡트러스트 5
 
5.6%
동부파출부 2
 
2.2%
한빛종합개발 1
 
1.1%
청명 1
 
1.1%
인천간병 1
 
1.1%
산후관리센터 1
 
1.1%
굿맘굿베이비 1
 
1.1%
엠피알컴퍼니 1
 
1.1%
제일서치 1
 
1.1%
Other values (70) 70
77.8%
2024-03-18T13:14:36.424277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 22
 
4.1%
19
 
3.6%
력 16
 
3.0%
사 14
 
2.6%
트 12
 
2.3%
개 12
 
2.3%
파 11
 
2.1%
스 11
 
2.1%
점 9
 
1.7%
회 9
 
1.7%
Other values (161) 398
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
88.4%
Uppercase Letter 21
 
3.9%
Space Separator 19
 
3.6%
Open Punctuation 7
 
1.3%
Close Punctuation 7
 
1.3%
Other Symbol 4
 
0.8%
Decimal Number 3
 
0.6%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 22
 
4.7%
력 16
 
3.4%
사 14
 
3.0%
트 12
 
2.5%
개 12
 
2.5%
파 11
 
2.3%
스 11
 
2.3%
점 9
 
1.9%
회 9
 
1.9%
이 9
 
1.9%
Other values (142) 346
73.5%
Uppercase Letter
ValueCountFrequency (%)
S 3
14.3%
M 2
9.5%
D 2
9.5%
A 2
9.5%
T 2
9.5%
L 2
9.5%
J 2
9.5%
O 2
9.5%
K 1
 
4.8%
H 1
 
4.8%
Other values (2) 2
9.5%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
89.1%
Common 37
 
6.9%
Latin 21
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 22
 
4.6%
력 16
 
3.4%
사 14
 
2.9%
트 12
 
2.5%
개 12
 
2.5%
파 11
 
2.3%
스 11
 
2.3%
점 9
 
1.9%
회 9
 
1.9%
이 9
 
1.9%
Other values (143) 350
73.7%
Latin
ValueCountFrequency (%)
S 3
14.3%
M 2
9.5%
D 2
9.5%
A 2
9.5%
T 2
9.5%
L 2
9.5%
J 2
9.5%
O 2
9.5%
K 1
 
4.8%
H 1
 
4.8%
Other values (2) 2
9.5%
Common
ValueCountFrequency (%)
19
51.4%
( 7
 
18.9%
) 7
 
18.9%
1 2
 
5.4%
9 1
 
2.7%
+ 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
88.4%
ASCII 58
 
10.9%
None 4
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 22
 
4.7%
력 16
 
3.4%
사 14
 
3.0%
트 12
 
2.5%
개 12
 
2.5%
파 11
 
2.3%
스 11
 
2.3%
점 9
 
1.9%
회 9
 
1.9%
이 9
 
1.9%
Other values (142) 346
73.5%
ASCII
ValueCountFrequency (%)
19
32.8%
( 7
 
12.1%
) 7
 
12.1%
S 3
 
5.2%
M 2
 
3.4%
D 2
 
3.4%
1 2
 
3.4%
A 2
 
3.4%
T 2
 
3.4%
L 2
 
3.4%
Other values (8) 10
17.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
유료/개인
57 
유료/법인
13 
무료/법인
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row유료/개인
2nd row유료/개인
3rd row유료/법인
4th row유료/법인
5th row유료/개인

Common Values

ValueCountFrequency (%)
유료/개인 57
80.3%
유료/법인 13
 
18.3%
무료/법인 1
 
1.4%

Length

2024-03-18T13:14:36.551414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:14:36.641858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료/개인 57
80.3%
유료/법인 13
 
18.3%
무료/법인 1
 
1.4%

전화번호
Text

MISSING 

Distinct59
Distinct (%)98.3%
Missing11
Missing (%)15.5%
Memory size700.0 B
2024-03-18T13:14:36.834455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.1
Min length11

Characters and Unicode

Total characters726
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

Unique58 ?
Unique (%)96.7%

Sample

1st row032-819-1666
2nd row032-818-8784
3rd row032-816-4112
4th row032-814-1117
5th row032-816-9797
ValueCountFrequency (%)
032-868-3036 2
 
3.3%
032-243-5757 1
 
1.7%
032-819-1666 1
 
1.7%
032-818-8784 1
 
1.7%
032-224-0303 1
 
1.7%
032-876-1459 1
 
1.7%
032-811-8873 1
 
1.7%
032-886-5858 1
 
1.7%
032-822-2248 1
 
1.7%
032-818-1911 1
 
1.7%
Other values (49) 49
81.7%
2024-03-18T13:14:37.204412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
16.5%
3 98
13.5%
2 97
13.4%
0 91
12.5%
1 75
10.3%
8 70
9.6%
7 46
 
6.3%
5 38
 
5.2%
9 32
 
4.4%
4 31
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 606
83.5%
Dash Punctuation 120
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 98
16.2%
2 97
16.0%
0 91
15.0%
1 75
12.4%
8 70
11.6%
7 46
7.6%
5 38
 
6.3%
9 32
 
5.3%
4 31
 
5.1%
6 28
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 726
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
16.5%
3 98
13.5%
2 97
13.4%
0 91
12.5%
1 75
10.3%
8 70
9.6%
7 46
 
6.3%
5 38
 
5.2%
9 32
 
4.4%
4 31
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
16.5%
3 98
13.5%
2 97
13.4%
0 91
12.5%
1 75
10.3%
8 70
9.6%
7 46
 
6.3%
5 38
 
5.2%
9 32
 
4.4%
4 31
 
4.3%

소재지 주소
Text

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-03-18T13:14:37.441436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length36
Mean length29.591549
Min length19

Characters and Unicode

Total characters2101
Distinct characters155
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)97.2%

Sample

1st row인천광역시 연수구 학나래로6번길 61 (선학동)
2nd row인천광역시 연수구 청명로17번길 10-22 (청학동.2층)
3rd row인천광역시 연수구 원인재로 212 (연수동)
4th row인천광역시 연수구 함박뫼로50번길 93
5th row인천광역시 연수구 용담로 134. 연수2동 2층 (연수동)
ValueCountFrequency (%)
인천광역시 69
 
17.0%
연수구 64
 
15.8%
센트럴로 5
 
1.2%
2층 5
 
1.2%
비류대로 4
 
1.0%
경원대로 4
 
1.0%
467번길 4
 
1.0%
학나래로 4
 
1.0%
313 4
 
1.0%
용담로 4
 
1.0%
Other values (193) 239
58.9%
2024-03-18T13:14:37.810379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
337
 
16.0%
1 97
 
4.6%
인 81
 
3.9%
로 74
 
3.5%
천 73
 
3.5%
시 72
 
3.4%
연 71
 
3.4%
수 71
 
3.4%
광 71
 
3.4%
2 70
 
3.3%
Other values (145) 1084
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1214
57.8%
Decimal Number 426
 
20.3%
Space Separator 337
 
16.0%
Other Punctuation 52
 
2.5%
Close Punctuation 21
 
1.0%
Open Punctuation 21
 
1.0%
Uppercase Letter 15
 
0.7%
Dash Punctuation 9
 
0.4%
Lowercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 81
 
6.7%
로 74
 
6.1%
천 73
 
6.0%
시 72
 
5.9%
연 71
 
5.8%
수 71
 
5.8%
광 71
 
5.8%
구 69
 
5.7%
역 69
 
5.7%
호 47
 
3.9%
Other values (117) 516
42.5%
Decimal Number
ValueCountFrequency (%)
1 97
22.8%
2 70
16.4%
0 56
13.1%
3 49
11.5%
4 37
 
8.7%
6 29
 
6.8%
8 26
 
6.1%
5 23
 
5.4%
7 20
 
4.7%
9 19
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 5
33.3%
A 3
20.0%
T 2
 
13.3%
C 2
 
13.3%
D 1
 
6.7%
S 1
 
6.7%
I 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
t 2
33.3%
w 1
16.7%
e 1
16.7%
s 1
16.7%
k 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 46
88.5%
. 6
 
11.5%
Space Separator
ValueCountFrequency (%)
337
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1214
57.8%
Common 866
41.2%
Latin 21
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 81
 
6.7%
로 74
 
6.1%
천 73
 
6.0%
시 72
 
5.9%
연 71
 
5.8%
수 71
 
5.8%
광 71
 
5.8%
구 69
 
5.7%
역 69
 
5.7%
호 47
 
3.9%
Other values (117) 516
42.5%
Common
ValueCountFrequency (%)
337
38.9%
1 97
 
11.2%
2 70
 
8.1%
0 56
 
6.5%
3 49
 
5.7%
, 46
 
5.3%
4 37
 
4.3%
6 29
 
3.3%
8 26
 
3.0%
5 23
 
2.7%
Other values (6) 96
 
11.1%
Latin
ValueCountFrequency (%)
B 5
23.8%
A 3
14.3%
t 2
 
9.5%
T 2
 
9.5%
C 2
 
9.5%
D 1
 
4.8%
w 1
 
4.8%
e 1
 
4.8%
s 1
 
4.8%
S 1
 
4.8%
Other values (2) 2
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1214
57.8%
ASCII 887
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
337
38.0%
1 97
 
10.9%
2 70
 
7.9%
0 56
 
6.3%
3 49
 
5.5%
, 46
 
5.2%
4 37
 
4.2%
6 29
 
3.3%
8 26
 
2.9%
5 23
 
2.6%
Other values (18) 117
 
13.2%
Hangul
ValueCountFrequency (%)
인 81
 
6.7%
로 74
 
6.1%
천 73
 
6.0%
시 72
 
5.9%
연 71
 
5.8%
수 71
 
5.8%
광 71
 
5.8%
구 69
 
5.7%
역 69
 
5.7%
호 47
 
3.9%
Other values (117) 516
42.5%

직종
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size700.0 B
건설
14 
파출
11 
헤드헌팅
9 
취업성공패키지
5 
생산직
5 
Other values (18)
27 

Length

Max length8
Median length7
Mean length4.1549296
Min length2

Unique

Unique12 ?
Unique (%)16.9%

Sample

1st row건설
2nd row파출
3rd row건설, 파출
4th row건설, 파출
5th row파출

Common Values

ValueCountFrequency (%)
건설 14
19.7%
파출 11
15.5%
헤드헌팅 9
12.7%
취업성공패키지 5
 
7.0%
생산직 5
 
7.0%
산모도우미 4
 
5.6%
건설, 파출 3
 
4.2%
간병 2
 
2.8%
무료일자리센터 2
 
2.8%
건설,파출,생산 2
 
2.8%
Other values (13) 14
19.7%

Length

2024-03-18T13:14:37.939976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건설 17
23.0%
파출 14
18.9%
헤드헌팅 9
12.2%
취업성공패키지 5
 
6.8%
생산직 5
 
6.8%
산모도우미 4
 
5.4%
간병 2
 
2.7%
무료일자리센터 2
 
2.7%
건설,파출,생산 2
 
2.7%
정부지원사업 2
 
2.7%
Other values (12) 12
16.2%

기타유의사항
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
<NA>
60 
개인정보 포함
10 
개인정보포함
 
1

Length

Max length7
Median length4
Mean length4.4507042
Min length4

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 60
84.5%
개인정보 포함 10
 
14.1%
개인정보포함 1
 
1.4%

Length

2024-03-18T13:14:38.085129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:14:38.185612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 60
74.1%
개인정보 10
 
12.3%
포함 10
 
12.3%
개인정보포함 1
 
1.2%

Correlations

2024-03-18T13:14:38.242094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명구분전화번호소재지 주소직종기타유의사항
업소명1.0001.0001.0001.0001.0001.000
구분1.0001.0001.0001.0000.821NaN
전화번호1.0001.0001.0000.9970.997NaN
소재지 주소1.0001.0000.9971.0001.0001.000
직종1.0000.8210.9971.0001.0000.000
기타유의사항1.000NaNNaN1.0000.0001.000
2024-03-18T13:14:38.325952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기타유의사항직종
구분1.0001.0000.533
기타유의사항1.0001.0000.000
직종0.5330.0001.000
2024-03-18T13:14:38.395214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분직종기타유의사항
구분1.0000.5331.000
직종0.5331.0000.000
기타유의사항1.0000.0001.000

Missing values

2024-03-18T13:14:35.749699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:14:35.894883image/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

업소명구분전화번호소재지 주소직종기타유의사항
0한빛종합개발유료/개인032-819-1666인천광역시 연수구 학나래로6번길 61 (선학동)건설<NA>
1파출박사연수점유료/개인032-818-8784인천광역시 연수구 청명로17번길 10-22 (청학동.2층)파출<NA>
2㈜금정개발유료/법인032-816-4112인천광역시 연수구 원인재로 212 (연수동)건설, 파출<NA>
3스피드인력유료/법인032-814-1117인천광역시 연수구 함박뫼로50번길 93건설, 파출<NA>
4동부파출부유료/개인032-816-9797인천광역시 연수구 용담로 134. 연수2동 2층 (연수동)파출<NA>
5동부파출부 논현점유료/개인032-437-9797인천광역시 남동구 청능대로 593번길,(논현동 신성프라자 301호)파출<NA>
6인터파크홈스토리유료/개인032-812-1911인천광역시 연수구 비류대로186번길20, 205호 (옥련동,풍림상가)파출<NA>
7신송도인력유료/개인032-831-0466인천광역시 연수구 비류대로 190. 202호 (옥련동. 청량주택상가2층)건설<NA>
8주식회사 휴먼잡트러스트유료/법인032-822-1825인천광역시 연수구 새말로96번길 26, 범한빌딩 4층취업성공패키지<NA>
9주식회사 휴먼잡트러스트 안산지점유료/법인031-414-5712경기도 안산시 고잔로 51 , 303호취업성공패키지<NA>
업소명구분전화번호소재지 주소직종기타유의사항
61비즈코리아유료/개인070-8825-0248인천광역시 연수구 송도과학로70, 송도AT센터 3204호조선소인력<NA>
62(A+)산모도우미119유료/개인032-818-3579인천광역시 연수구 경원대로 467번길 38 206호산모도우미<NA>
63에이치알컨설팅포유유료/개인<NA>인천광역시 연수구 인천타워태로323, 센트로드 A동 1114호헤드헌팅개인정보 포함
64㈜와우아이앤씨유료/법인032-832-0708인천광역시 연수구 비류대로 208, 비류프라자 401에이호생산,물류,조리<NA>
65아침을 여는 사람들유료/개인<NA>인천광역시 연수구 센트럴로 313 씨워크인테라스한라 B동 1427호건설일용직개인정보 포함
66트리플에이유료/개인<NA>인천광역시 연수구 용담로 97, 3층헤드헌팅개인정보 포함
67DS컨설턴트유료/개인032-830-8110인천광역시 연수구 인권로 2, 307호생산,농/어업<NA>
68연수구노인인력개발센터유료/개인032-818-2111인천광역시 연수구 청능대로 109, 4층(연수동, 탑피온)노인일자리사업<NA>
69(재)인천테크노파크(JST지점)유료/개인032-725-3015인천광역시 미추홀구 석정로 229 제물포스마트타운 2층무료일자리센터<NA>
70(사)한국능력평가협회무료/법인032-442-1499인천광역시 연수구 능허대로 136 kt송도빌딩무료일자리센터<NA>