Overview

Dataset statistics

Number of variables8
Number of observations99
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory66.3 B

Variable types

Numeric1
Categorical3
Text4

Dataset

Description청년일자리올인원지원서비스의 일환으로 워크넷에서 제공하는 대악일자리센터 정보 (청년취업진로지도지원기관 정보)를 제공한다.
URLhttps://www.data.go.kr/data/15118488/fileData.do

Alerts

연번 is highly overall correlated with 지역 and 1 other fieldsHigh correlation
지역 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
센터명 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연락처 has 1 (1.0%) missing valuesMissing
연번 has unique valuesUnique
대학 has unique valuesUnique
학교주소 has unique valuesUnique
담당자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:18:20.373532
Analysis finished2023-12-12 12:18:21.408454
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1023.0 B
2023-12-12T21:18:21.502783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.9
Q125.5
median50
Q374.5
95-th percentile94.1
Maximum99
Range98
Interquartile range (IQR)49

Descriptive statistics

Standard deviation28.722813
Coefficient of variation (CV)0.57445626
Kurtosis-1.2
Mean50
Median Absolute Deviation (MAD)25
Skewness0
Sum4950
Variance825
MonotonicityStrictly increasing
2023-12-12T21:18:21.705220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
64 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
Other values (89) 89
89.9%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%

지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size924.0 B
서울
16 
경기
16 
경북
12 
부산
10 
경남
7 
Other values (12)
38 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울 16
16.2%
경기 16
16.2%
경북 12
12.1%
부산 10
10.1%
경남 7
7.1%
전북 5
 
5.1%
대구 5
 
5.1%
충북 5
 
5.1%
광주 5
 
5.1%
강원 4
 
4.0%
Other values (7) 14
14.1%

Length

2023-12-12T21:18:21.871016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 16
16.2%
경기 16
16.2%
경북 12
12.1%
부산 10
10.1%
경남 7
7.1%
충북 5
 
5.1%
광주 5
 
5.1%
대구 5
 
5.1%
전북 5
 
5.1%
강원 4
 
4.0%
Other values (7) 14
14.1%

센터명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size924.0 B
대구
7 
부산
7 
서울북부
7 
수원
 
6
서울
 
4
Other values (37)
68 

Length

Max length4
Median length2
Mean length2.3535354
Min length2

Unique

Unique14 ?
Unique (%)14.1%

Sample

1st row서울
2nd row서울
3rd row서울
4th row서울
5th row서울동부

Common Values

ValueCountFrequency (%)
대구 7
 
7.1%
부산 7
 
7.1%
서울북부 7
 
7.1%
수원 6
 
6.1%
서울 4
 
4.0%
대전 4
 
4.0%
전주 3
 
3.0%
포항 3
 
3.0%
구미 3
 
3.0%
안양 3
 
3.0%
Other values (32) 52
52.5%

Length

2023-12-12T21:18:22.035466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구 7
 
7.1%
서울북부 7
 
7.1%
부산 7
 
7.1%
수원 6
 
6.1%
서울 4
 
4.0%
대전 4
 
4.0%
전주 3
 
3.0%
포항 3
 
3.0%
구미 3
 
3.0%
성남 3
 
3.0%
Other values (32) 52
52.5%

대학
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T21:18:22.415565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length5
Mean length5.7272727
Min length3

Characters and Unicode

Total characters567
Distinct characters112
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

Unique99 ?
Unique (%)100.0%

Sample

1st row상명대학교
2nd row성균관대학교
3rd row한국외국어대학교
4th row서울시립대
5th row세종대
ValueCountFrequency (%)
상명대학교 1
 
1.0%
계명문화대학교 1
 
1.0%
조선대학교 1
 
1.0%
안동과학대학교 1
 
1.0%
안동대학교 1
 
1.0%
금오공과대학교 1
 
1.0%
경운대학교 1
 
1.0%
구미대학교 1
 
1.0%
위덕대학교 1
 
1.0%
wise캠퍼스 1
 
1.0%
Other values (91) 91
90.1%
2023-12-12T21:18:22.995931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 104
18.3%
학 92
16.2%
교 88
15.5%
한 13
 
2.3%
국 12
 
2.1%
동 11
 
1.9%
산 9
 
1.6%
서 7
 
1.2%
명 7
 
1.2%
원 7
 
1.2%
Other values (102) 217
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 559
98.6%
Uppercase Letter 4
 
0.7%
Space Separator 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 104
18.6%
학 92
16.5%
교 88
15.7%
한 13
 
2.3%
국 12
 
2.1%
동 11
 
2.0%
산 9
 
1.6%
서 7
 
1.3%
명 7
 
1.3%
원 7
 
1.3%
Other values (95) 209
37.4%
Uppercase Letter
ValueCountFrequency (%)
E 1
25.0%
W 1
25.0%
I 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 559
98.6%
Common 4
 
0.7%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 104
18.6%
학 92
16.5%
교 88
15.7%
한 13
 
2.3%
국 12
 
2.1%
동 11
 
2.0%
산 9
 
1.6%
서 7
 
1.3%
명 7
 
1.3%
원 7
 
1.3%
Other values (95) 209
37.4%
Latin
ValueCountFrequency (%)
E 1
25.0%
W 1
25.0%
I 1
25.0%
S 1
25.0%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 559
98.6%
ASCII 8
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 104
18.6%
학 92
16.5%
교 88
15.7%
한 13
 
2.3%
국 12
 
2.1%
동 11
 
2.0%
산 9
 
1.6%
서 7
 
1.3%
명 7
 
1.3%
원 7
 
1.3%
Other values (95) 209
37.4%
ASCII
ValueCountFrequency (%)
2
25.0%
E 1
12.5%
( 1
12.5%
) 1
12.5%
W 1
12.5%
I 1
12.5%
S 1
12.5%

학교주소
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T21:18:23.455610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length37
Mean length20.151515
Min length12

Characters and Unicode

Total characters1995
Distinct characters193
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row서울시 종로구 홍지문 2길 20
2nd row서울 종로구 성균관로 25-2 경영관 1층
3rd row서울시 동대문구 이문로107
4th row서울 동대문구 서울시립대로 163
5th row서울 광진구 능동로 209
ValueCountFrequency (%)
경기도 17
 
3.6%
서울 12
 
2.6%
경북 11
 
2.4%
1층 8
 
1.7%
부산시 6
 
1.3%
경산시 5
 
1.1%
서울시 5
 
1.1%
대학로 4
 
0.9%
충북 4
 
0.9%
남구 4
 
0.9%
Other values (329) 391
83.7%
2023-12-12T21:18:24.127769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
372
 
18.6%
로 90
 
4.5%
시 83
 
4.2%
구 66
 
3.3%
대 64
 
3.2%
1 64
 
3.2%
2 47
 
2.4%
경 46
 
2.3%
산 40
 
2.0%
0 39
 
2.0%
Other values (183) 1084
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1252
62.8%
Space Separator 372
 
18.6%
Decimal Number 335
 
16.8%
Open Punctuation 11
 
0.6%
Close Punctuation 11
 
0.6%
Dash Punctuation 7
 
0.4%
Other Punctuation 6
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 90
 
7.2%
시 83
 
6.6%
구 66
 
5.3%
대 64
 
5.1%
경 46
 
3.7%
산 40
 
3.2%
학 32
 
2.6%
서 30
 
2.4%
도 30
 
2.4%
동 29
 
2.3%
Other values (166) 742
59.3%
Decimal Number
ValueCountFrequency (%)
1 64
19.1%
2 47
14.0%
0 39
11.6%
7 33
9.9%
5 33
9.9%
3 33
9.9%
4 24
 
7.2%
6 23
 
6.9%
8 21
 
6.3%
9 18
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 4
66.7%
: 2
33.3%
Space Separator
ValueCountFrequency (%)
372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1252
62.8%
Common 742
37.2%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 90
 
7.2%
시 83
 
6.6%
구 66
 
5.3%
대 64
 
5.1%
경 46
 
3.7%
산 40
 
3.2%
학 32
 
2.6%
서 30
 
2.4%
도 30
 
2.4%
동 29
 
2.3%
Other values (166) 742
59.3%
Common
ValueCountFrequency (%)
372
50.1%
1 64
 
8.6%
2 47
 
6.3%
0 39
 
5.3%
7 33
 
4.4%
5 33
 
4.4%
3 33
 
4.4%
4 24
 
3.2%
6 23
 
3.1%
8 21
 
2.8%
Other values (6) 53
 
7.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1252
62.8%
ASCII 743
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
372
50.1%
1 64
 
8.6%
2 47
 
6.3%
0 39
 
5.2%
7 33
 
4.4%
5 33
 
4.4%
3 33
 
4.4%
4 24
 
3.2%
6 23
 
3.1%
8 21
 
2.8%
Other values (7) 54
 
7.3%
Hangul
ValueCountFrequency (%)
로 90
 
7.2%
시 83
 
6.6%
구 66
 
5.3%
대 64
 
5.1%
경 46
 
3.7%
산 40
 
3.2%
학 32
 
2.6%
서 30
 
2.4%
도 30
 
2.4%
동 29
 
2.3%
Other values (166) 742
59.3%

담당자
Text

UNIQUE 

Distinct99
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
2023-12-12T21:18:24.553862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.4949495
Min length3

Characters and Unicode

Total characters346
Distinct characters115
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)100.0%

Sample

1st row임황섭
2nd row이다은
3rd row정성주
4th row이소연
5th row이윤경
ValueCountFrequency (%)
팀장 2
 
1.8%
과장 2
 
1.8%
김민정 2
 
1.8%
임황섭 1
 
0.9%
차효성 1
 
0.9%
정재호(재맞고 1
 
0.9%
김희욱 1
 
0.9%
김상규 1
 
0.9%
강병희 1
 
0.9%
이수형 1
 
0.9%
Other values (98) 98
88.3%
2023-12-12T21:18:25.064712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 21
 
6.1%
김 21
 
6.1%
이 18
 
5.2%
13
 
3.8%
현 9
 
2.6%
성 9
 
2.6%
영 8
 
2.3%
경 8
 
2.3%
장 8
 
2.3%
진 7
 
2.0%
Other values (105) 224
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
95.4%
Space Separator 13
 
3.8%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 21
 
6.4%
김 21
 
6.4%
이 18
 
5.5%
현 9
 
2.7%
성 9
 
2.7%
영 8
 
2.4%
경 8
 
2.4%
장 8
 
2.4%
진 7
 
2.1%
희 7
 
2.1%
Other values (101) 214
64.8%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
95.4%
Common 16
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 21
 
6.4%
김 21
 
6.4%
이 18
 
5.5%
현 9
 
2.7%
성 9
 
2.7%
영 8
 
2.4%
경 8
 
2.4%
장 8
 
2.4%
진 7
 
2.1%
희 7
 
2.1%
Other values (101) 214
64.8%
Common
ValueCountFrequency (%)
13
81.2%
( 1
 
6.2%
) 1
 
6.2%
, 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
95.4%
ASCII 16
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 21
 
6.4%
김 21
 
6.4%
이 18
 
5.5%
현 9
 
2.7%
성 9
 
2.7%
영 8
 
2.4%
경 8
 
2.4%
장 8
 
2.4%
진 7
 
2.1%
희 7
 
2.1%
Other values (101) 214
64.8%
ASCII
ValueCountFrequency (%)
13
81.2%
( 1
 
6.2%
) 1
 
6.2%
, 1
 
6.2%

연락처
Text

MISSING 

Distinct98
Distinct (%)100.0%
Missing1
Missing (%)1.0%
Memory size924.0 B
2023-12-12T21:18:25.377357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length12
Mean length12.510204
Min length11

Characters and Unicode

Total characters1226
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)100.0%

Sample

1st row02-2287-7087
2nd row02-760-1088
3rd row02-2173-2145
4th row02-6490-6266
5th row02-3408-3060
ValueCountFrequency (%)
02-2287-7087 1
 
1.0%
053-580-6043 1
 
1.0%
062-230-7575 1
 
1.0%
054-851-3679 1
 
1.0%
054-820-7075 1
 
1.0%
054-478-7981 1
 
1.0%
054-479-1127 1
 
1.0%
054-440-1480 1
 
1.0%
054-760-1025 1
 
1.0%
054-770-2052 1
 
1.0%
Other values (93) 93
90.3%
2023-12-12T21:18:25.879413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 216
17.6%
- 202
16.5%
5 120
9.8%
2 117
9.5%
3 103
8.4%
1 96
7.8%
4 78
 
6.4%
9 77
 
6.3%
6 73
 
6.0%
7 67
 
5.5%
Other values (4) 77
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1013
82.6%
Dash Punctuation 202
 
16.5%
Other Punctuation 5
 
0.4%
Space Separator 5
 
0.4%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 216
21.3%
5 120
11.8%
2 117
11.5%
3 103
10.2%
1 96
9.5%
4 78
 
7.7%
9 77
 
7.6%
6 73
 
7.2%
7 67
 
6.6%
8 66
 
6.5%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1226
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 216
17.6%
- 202
16.5%
5 120
9.8%
2 117
9.5%
3 103
8.4%
1 96
7.8%
4 78
 
6.4%
9 77
 
6.3%
6 73
 
6.0%
7 67
 
5.5%
Other values (4) 77
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 216
17.6%
- 202
16.5%
5 120
9.8%
2 117
9.5%
3 103
8.4%
1 96
7.8%
4 78
 
6.4%
9 77
 
6.3%
6 73
 
6.0%
7 67
 
5.5%
Other values (4) 77
 
6.3%

사업유형
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size924.0 B
대플
50 
대플(거점형)
49 

Length

Max length7
Median length2
Mean length4.4747475
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대플(거점형)
2nd row대플
3rd row대플(거점형)
4th row대플(거점형)
5th row대플(거점형)

Common Values

ValueCountFrequency (%)
대플 50
50.5%
대플(거점형) 49
49.5%

Length

2023-12-12T21:18:26.060763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:18:26.178778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대플 50
50.5%
대플(거점형 49
49.5%

Interactions

2023-12-12T21:18:21.070612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:18:26.265613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역센터명대학학교주소담당자연락처사업유형
연번1.0000.9470.9811.0001.0001.0001.0000.352
지역0.9471.0000.9981.0001.0001.0001.0000.377
센터명0.9810.9981.0001.0001.0001.0001.0000.000
대학1.0001.0001.0001.0001.0001.0001.0001.000
학교주소1.0001.0001.0001.0001.0001.0001.0001.000
담당자1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
사업유형0.3520.3770.0001.0001.0001.0001.0001.000
2023-12-12T21:18:26.397892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역센터명사업유형
지역1.0000.8120.309
센터명0.8121.0000.000
사업유형0.3090.0001.000
2023-12-12T21:18:26.517914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역센터명사업유형
연번1.0000.7280.6830.267
지역0.7281.0000.8120.309
센터명0.6830.8121.0000.000
사업유형0.2670.3090.0001.000

Missing values

2023-12-12T21:18:21.208753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:18:21.353409image/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

연번지역센터명대학학교주소담당자연락처사업유형
01서울서울상명대학교서울시 종로구 홍지문 2길 20임황섭02-2287-7087대플(거점형)
12서울서울성균관대학교서울 종로구 성균관로 25-2 경영관 1층이다은02-760-1088대플
23서울서울한국외국어대학교서울시 동대문구 이문로107정성주02-2173-2145대플(거점형)
34서울서울서울시립대서울 동대문구 서울시립대로 163이소연02-6490-6266대플(거점형)
45서울서울동부세종대서울 광진구 능동로 209이윤경02-3408-3060대플(거점형)
56서울서울동부건국대서울 광진구 능동로 120최흥식 차장02-450-3823대플(거점형)
67서울서울서부숙명여자대학교서울 용산구 청파로47길 100이은실02-2077-7003대플(거점형)
78서울서울서부명지대학교서울 서대문구 거북골로 34서연희02-300-1774대플(거점형)
89서울서울북부서일대학교서울 중랑구 용마산로 90길 28노현우02-490-7253대플
910서울서울북부덕성여자대학교서울 도봉구 삼양로144길 33봉선화 김민정 정유신901-8180, 901-8179, 901-8058대플
연번지역센터명대학학교주소담당자연락처사업유형
8990대전대전목원대학교대전시 서구 도안북로88(도안동, 목원대학교)김영림042-829-7155대플
9091대전대전배재대학교대전광역시 서구 배재로 155-40(도마동)곽현민042-520-5521대플(거점형)
9192세종세종고려대세종세종특별자치시 세종로 2511 고려대학교 세종캠퍼스 세종학술정보원 1층 대학일자리센터김해련044-860-1095대플
9293충북청주서원대학교충북 청주시 무심서로 377-3 미래창조관 1층 취창업지원처최명자043-299-8253대플
9394충북청주청주대학교청주시 청원구 대성로 298 입학취업지원관 1층김용미043-229-8981대플
9495충남천안나사렛대충남 천안시 서북구 월봉로 48박순민 계장041-570-7886대플
9596충남천안순천향대충남 아산시 신창면 순천향로 22정상훈 담당041-530-3070대플(거점형)
9697충북충주한국교통대학교충북 충주시 대학로50최창희043-849-1451대플
9798충북충주건국대학교 글로컬캠퍼스충북 충주시 충원대로 268김경목043-840-3933대플
9899충북제천세명대학교충북 제천시 세명로 65, 세명대학교 학생회관 202호김정배043-649-1671대플