Overview

Dataset statistics

Number of variables8
Number of observations77
Missing cells38
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory68.7 B

Variable types

Numeric3
Categorical2
Text3

Dataset

Description경상남도 거제시에 현재 운영 중인 유무료 직업소개소 현황입니다.(직업소개소명, 도로명주소, 전화번호, 위도, 경도, 데이터기준일)
Author경상남도 거제시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3079268

Alerts

기준일 has constant value ""Constant
유무료구분 is highly imbalanced (90.0%)Imbalance
전화번호 has 38 (49.4%) missing valuesMissing
순번 has unique valuesUnique
법인명 has unique valuesUnique
사업소도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:58:01.638218
Analysis finished2023-12-10 23:58:03.135224
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T08:58:03.241222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q120
median39
Q358
95-th percentile73.2
Maximum77
Range76
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.371857
Coefficient of variation (CV)0.57363737
Kurtosis-1.2
Mean39
Median Absolute Deviation (MAD)19
Skewness0
Sum3003
Variance500.5
MonotonicityStrictly increasing
2023-12-11T08:58:03.385871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
50 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
51 1
 
1.3%
49 1
 
1.3%
Other values (67) 67
87.0%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%
68 1
1.3%

유무료구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size748.0 B
유료
76 
무료
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
유료 76
98.7%
무료 1
 
1.3%

Length

2023-12-11T08:58:03.546868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:58:03.653372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 76
98.7%
무료 1
 
1.3%

법인명
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T08:58:03.840627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.6883117
Min length2

Characters and Unicode

Total characters515
Distinct characters148
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row새열린 직업소개소
2nd row삼성인력
3rd row가자인력
4th rowFE 인력개발원
5th row행복인력
ValueCountFrequency (%)
직업소개소 11
 
10.8%
인력개발 3
 
2.9%
인력 2
 
2.0%
천하직업소개소 1
 
1.0%
우리인력 1
 
1.0%
우리가사원 1
 
1.0%
길손가사원 1
 
1.0%
인력소 1
 
1.0%
imf 1
 
1.0%
하이디 1
 
1.0%
Other values (79) 79
77.5%
2023-12-11T08:58:04.194949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 54
 
10.5%
인 37
 
7.2%
력 35
 
6.8%
개 32
 
6.2%
업 28
 
5.4%
직 26
 
5.0%
25
 
4.9%
사 13
 
2.5%
가 12
 
2.3%
거 12
 
2.3%
Other values (138) 241
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
91.5%
Space Separator 25
 
4.9%
Uppercase Letter 10
 
1.9%
Decimal Number 4
 
0.8%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 54
 
11.5%
인 37
 
7.9%
력 35
 
7.4%
개 32
 
6.8%
업 28
 
5.9%
직 26
 
5.5%
사 13
 
2.8%
가 12
 
2.5%
거 12
 
2.5%
원 11
 
2.3%
Other values (125) 211
44.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
F 2
20.0%
M 1
 
10.0%
I 1
 
10.0%
E 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
0 3
75.0%
2 1
 
25.0%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
91.5%
Common 34
 
6.6%
Latin 10
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 54
 
11.5%
인 37
 
7.9%
력 35
 
7.4%
개 32
 
6.8%
업 28
 
5.9%
직 26
 
5.5%
사 13
 
2.8%
가 12
 
2.5%
거 12
 
2.5%
원 11
 
2.3%
Other values (125) 211
44.8%
Latin
ValueCountFrequency (%)
B 3
30.0%
F 2
20.0%
M 1
 
10.0%
I 1
 
10.0%
E 1
 
10.0%
C 1
 
10.0%
A 1
 
10.0%
Common
ValueCountFrequency (%)
25
73.5%
0 3
 
8.8%
( 2
 
5.9%
) 2
 
5.9%
2 1
 
2.9%
· 1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
91.5%
ASCII 43
 
8.3%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 54
 
11.5%
인 37
 
7.9%
력 35
 
7.4%
개 32
 
6.8%
업 28
 
5.9%
직 26
 
5.5%
사 13
 
2.8%
가 12
 
2.5%
거 12
 
2.5%
원 11
 
2.3%
Other values (125) 211
44.8%
ASCII
ValueCountFrequency (%)
25
58.1%
0 3
 
7.0%
B 3
 
7.0%
( 2
 
4.7%
) 2
 
4.7%
F 2
 
4.7%
M 1
 
2.3%
I 1
 
2.3%
2 1
 
2.3%
E 1
 
2.3%
Other values (2) 2
 
4.7%
None
ValueCountFrequency (%)
· 1
100.0%

사업소도로명주소
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-11T08:58:04.527328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length36
Mean length28.779221
Min length20

Characters and Unicode

Total characters2216
Distinct characters118
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row경상남도 거제시 고현로 121 한양프라자 120호 (고현동)
2nd row경상남도 거제시 고현로 58 무림자동차정비 2층 (고현동)
3rd row경상남도 거제시 거제중앙로 1868 2층 (고현동)
4th row경상남도 거제시 아주로 12-1 (아주동)
5th row경상남도 거제시 장평로 17 1층 (장평동)
ValueCountFrequency (%)
경상남도 77
 
16.5%
거제시 77
 
16.5%
고현동 37
 
7.9%
옥포동 18
 
3.8%
1층 15
 
3.2%
2층 14
 
3.0%
고현로 7
 
1.5%
17 5
 
1.1%
거제중앙로 5
 
1.1%
3층 4
 
0.9%
Other values (156) 209
44.7%
2023-12-11T08:58:05.067757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
391
 
17.6%
1 113
 
5.1%
거 97
 
4.4%
제 97
 
4.4%
상 84
 
3.8%
동 82
 
3.7%
시 78
 
3.5%
경 78
 
3.5%
도 77
 
3.5%
남 77
 
3.5%
Other values (108) 1042
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1298
58.6%
Space Separator 391
 
17.6%
Decimal Number 359
 
16.2%
Open Punctuation 74
 
3.3%
Close Punctuation 74
 
3.3%
Dash Punctuation 18
 
0.8%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 97
 
7.5%
제 97
 
7.5%
상 84
 
6.5%
동 82
 
6.3%
시 78
 
6.0%
경 78
 
6.0%
도 77
 
5.9%
남 77
 
5.9%
로 75
 
5.8%
고 52
 
4.0%
Other values (93) 501
38.6%
Decimal Number
ValueCountFrequency (%)
1 113
31.5%
2 64
17.8%
3 46
12.8%
0 37
 
10.3%
4 23
 
6.4%
5 21
 
5.8%
7 17
 
4.7%
6 15
 
4.2%
8 14
 
3.9%
9 9
 
2.5%
Space Separator
ValueCountFrequency (%)
391
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
， 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1298
58.6%
Common 918
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 97
 
7.5%
제 97
 
7.5%
상 84
 
6.5%
동 82
 
6.3%
시 78
 
6.0%
경 78
 
6.0%
도 77
 
5.9%
남 77
 
5.9%
로 75
 
5.8%
고 52
 
4.0%
Other values (93) 501
38.6%
Common
ValueCountFrequency (%)
391
42.6%
1 113
 
12.3%
( 74
 
8.1%
) 74
 
8.1%
2 64
 
7.0%
3 46
 
5.0%
0 37
 
4.0%
4 23
 
2.5%
5 21
 
2.3%
- 18
 
2.0%
Other values (5) 57
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1298
58.6%
ASCII 916
41.3%
None 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
391
42.7%
1 113
 
12.3%
( 74
 
8.1%
) 74
 
8.1%
2 64
 
7.0%
3 46
 
5.0%
0 37
 
4.0%
4 23
 
2.5%
5 21
 
2.3%
- 18
 
2.0%
Other values (4) 55
 
6.0%
Hangul
ValueCountFrequency (%)
거 97
 
7.5%
제 97
 
7.5%
상 84
 
6.5%
동 82
 
6.3%
시 78
 
6.0%
경 78
 
6.0%
도 77
 
5.9%
남 77
 
5.9%
로 75
 
5.8%
고 52
 
4.0%
Other values (93) 501
38.6%
None
ValueCountFrequency (%)
， 2
100.0%

위도
Real number (ℝ)

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.886576
Minimum34.830519
Maximum34.913228
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T08:58:05.220699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.830519
5-th percentile34.866644
Q134.885347
median34.888092
Q334.891957
95-th percentile34.896322
Maximum34.913228
Range0.08270875
Interquartile range (IQR)0.00661021

Descriptive statistics

Standard deviation0.011066359
Coefficient of variation (CV)0.00031720965
Kurtosis8.4637805
Mean34.886576
Median Absolute Deviation (MAD)0.00337247
Skewness-1.8557608
Sum2686.2664
Variance0.00012246429
MonotonicityNot monotonic
2023-12-11T08:58:05.358929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.88809177 2
 
2.6%
34.88606885 2
 
2.6%
34.91322816 2
 
2.6%
34.88771275 2
 
2.6%
34.88534707 2
 
2.6%
34.88735167 2
 
2.6%
34.89551993 1
 
1.3%
34.87630022 1
 
1.3%
34.88683308 1
 
1.3%
34.89146424 1
 
1.3%
Other values (61) 61
79.2%
ValueCountFrequency (%)
34.83051941 1
1.3%
34.86344244 1
1.3%
34.86492153 1
1.3%
34.86650309 1
1.3%
34.86667892 1
1.3%
34.86706007 1
1.3%
34.86924846 1
1.3%
34.87114198 1
1.3%
34.87410778 1
1.3%
34.87560239 1
1.3%
ValueCountFrequency (%)
34.91322816 2
2.6%
34.90293043 1
1.3%
34.89695251 1
1.3%
34.89616393 1
1.3%
34.89587592 1
1.3%
34.89569283 1
1.3%
34.89551993 1
1.3%
34.89436104 1
1.3%
34.89414676 1
1.3%
34.8938292 1
1.3%

경도
Real number (ℝ)

Distinct71
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.65281
Minimum128.60468
Maximum128.73118
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-11T08:58:05.806185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.60468
5-th percentile128.61745
Q1128.62233
median128.62689
Q3128.69255
95-th percentile128.70866
Maximum128.73118
Range0.1264939
Interquartile range (IQR)0.0702162

Descriptive statistics

Standard deviation0.037600273
Coefficient of variation (CV)0.00029226156
Kurtosis-1.2997944
Mean128.65281
Median Absolute Deviation (MAD)0.0075904
Skewness0.55570088
Sum9906.2667
Variance0.0014137805
MonotonicityNot monotonic
2023-12-11T08:58:05.998120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6256605 2
 
2.6%
128.621105 2
 
2.6%
128.6540313 2
 
2.6%
128.6222333 2
 
2.6%
128.626482 2
 
2.6%
128.6223291 2
 
2.6%
128.6936072 1
 
1.3%
128.6292135 1
 
1.3%
128.617971 1
 
1.3%
128.6934527 1
 
1.3%
Other values (61) 61
79.2%
ValueCountFrequency (%)
128.6046836 1
1.3%
128.6066205 1
1.3%
128.6093721 1
1.3%
128.6153877 1
1.3%
128.617971 1
1.3%
128.6190561 1
1.3%
128.6192985 1
1.3%
128.6193522 1
1.3%
128.6202551 1
1.3%
128.6204545 1
1.3%
ValueCountFrequency (%)
128.7311775 1
1.3%
128.7308754 1
1.3%
128.7295494 1
1.3%
128.7279492 1
1.3%
128.7038401 1
1.3%
128.6970165 1
1.3%
128.6959845 1
1.3%
128.695383 1
1.3%
128.6949598 1
1.3%
128.6940825 1
1.3%

전화번호
Text

MISSING 

Distinct38
Distinct (%)97.4%
Missing38
Missing (%)49.4%
Memory size748.0 B
2023-12-11T08:58:06.245570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.102564
Min length12

Characters and Unicode

Total characters472
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

Unique37 ?
Unique (%)94.9%

Sample

1st row055-634-0104
2nd row055-637-0454
3rd row0507-1352-8150
4th row055-636-8881
5th row055-636-2049
ValueCountFrequency (%)
055-634-0104 2
 
5.1%
055-633-2188 1
 
2.6%
055-682-1134 1
 
2.6%
055-635-3577 1
 
2.6%
055-632-0333 1
 
2.6%
055-688-0015 1
 
2.6%
055-632-8219 1
 
2.6%
055-681-1804 1
 
2.6%
055-637-4333 1
 
2.6%
055-632-9874 1
 
2.6%
Other values (28) 28
71.8%
2023-12-11T08:58:06.629354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 92
19.5%
- 78
16.5%
0 67
14.2%
6 51
10.8%
3 50
10.6%
8 38
8.1%
2 26
 
5.5%
1 23
 
4.9%
7 18
 
3.8%
4 16
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 394
83.5%
Dash Punctuation 78
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 92
23.4%
0 67
17.0%
6 51
12.9%
3 50
12.7%
8 38
9.6%
2 26
 
6.6%
1 23
 
5.8%
7 18
 
4.6%
4 16
 
4.1%
9 13
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 472
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 92
19.5%
- 78
16.5%
0 67
14.2%
6 51
10.8%
3 50
10.6%
8 38
8.1%
2 26
 
5.5%
1 23
 
4.9%
7 18
 
3.8%
4 16
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 92
19.5%
- 78
16.5%
0 67
14.2%
6 51
10.8%
3 50
10.6%
8 38
8.1%
2 26
 
5.5%
1 23
 
4.9%
7 18
 
3.8%
4 16
 
3.4%

기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size748.0 B
2021-08-19
77 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-08-19
2nd row2021-08-19
3rd row2021-08-19
4th row2021-08-19
5th row2021-08-19

Common Values

ValueCountFrequency (%)
2021-08-19 77
100.0%

Length

2023-12-11T08:58:06.766898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:58:06.854985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-08-19 77
100.0%

Interactions

2023-12-11T08:58:02.584422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.017876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.322765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.688052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.128215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.415130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.788745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.216450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:58:02.491445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:58:06.913358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분법인명사업소도로명주소위도경도전화번호
순번1.0000.0001.0001.0000.3630.2710.956
유무료구분0.0001.0001.0001.0000.0000.0001.000
법인명1.0001.0001.0001.0001.0001.0001.000
사업소도로명주소1.0001.0001.0001.0001.0001.0001.000
위도0.3630.0001.0001.0001.0000.7651.000
경도0.2710.0001.0001.0000.7651.0001.000
전화번호0.9561.0001.0001.0001.0001.0001.000
2023-12-11T08:58:07.017806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도유무료구분
순번1.0000.1310.3350.000
위도0.1311.0000.0720.000
경도0.3350.0721.0000.000
유무료구분0.0000.0000.0001.000

Missing values

2023-12-11T08:58:02.936829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:58:03.067753image/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

순번유무료구분법인명사업소도로명주소위도경도전화번호기준일
01유료새열린 직업소개소경상남도 거제시 고현로 121 한양프라자 120호 (고현동)34.888092128.625661<NA>2021-08-19
12유료삼성인력경상남도 거제시 고현로 58 무림자동차정비 2층 (고현동)34.88588128.619299055-634-01042021-08-19
23유료가자인력경상남도 거제시 거제중앙로 1868 2층 (고현동)34.885067128.624948055-637-04542021-08-19
34유료FE 인력개발원경상남도 거제시 아주로 12-1 (아주동)34.86706128.6921430507-1352-81502021-08-19
45유료행복인력경상남도 거제시 장평로 17 1층 (장평동)34.891029128.615388<NA>2021-08-19
56유료명성인력경상남도 거제시 고현로 73-4 지하1층 (고현동)34.886069128.621105055-636-88812021-08-19
67유료거제인력지원센터경상남도 거제시 옥포대첩로7길 31 신강보람빌라 1동 1층 109호 (옥포동)34.89552128.693607055-636-20492021-08-19
78유료(주)에스엠글로벌경상남도 거제시 장평1로 152 2층 (장평동)34.891957128.604684<NA>2021-08-19
89유료한정개발경상남도 거제시 장평3로2길 1 101호 (장평동)34.889788128.6093720507-1318-79462021-08-19
910유료(주)참성실한 기업경상남도 거제시 고현로14길 23 3층 (고현동)34.886314128.627813055-634-01042021-08-19
순번유무료구분법인명사업소도로명주소위도경도전화번호기준일
6768유료왕아 직업소개소경상남도 거제시 옥포로4길 40 1층 105호 (옥포동， 청송빌라)34.892417128.697016<NA>2021-08-19
6869유료솔로몬 직업상담소경상남도 거제시 장평3로5길 23 신일빌딩 102호 (장평동)34.890532128.60662<NA>2021-08-19
6970유료길 인력개발경상남도 거제시 아주로 13 1층 (아주동)34.866679128.692588<NA>2021-08-19
7071유료진선미 직업소개소경상남도 거제시 옥포대첩로6길 38-1 1층 (옥포동)34.890779128.693458<NA>2021-08-19
7172유료청아 인력경상남도 거제시 중곡1로2길 14 3층 302호 (고현동)34.894361128.626616<NA>2021-08-19
7273유료창신산업개발경상남도 거제시 신부로 42-14 5층 503호 (장승포동)34.871142128.730875<NA>2021-08-19
7374유료국민인력경상남도 거제시 옥포중앙로 35-3 1층 (옥포동)34.896164128.68975<NA>2021-08-19
7475유료세기 직업소개소경상남도 거제시 거제중앙로 1930-10 (고현동 고현동주상복합아파트)34.890233128.62304055-636-60222021-08-19
7576유료장승포인력경상남도 거제시 장승포로 101 101호 (장승포동)34.863442128.729549<NA>2021-08-19
7677유료빈 종합인력경상남도 거제시 거제중앙로20길 9 1층 (고현동 창조아파트)34.886688128.625179<NA>2021-08-19