Overview

Dataset statistics

Number of variables7
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory62.3 B

Variable types

Text5
Categorical2

Dataset

Description서울특별시 금천구 취업 박람회 현황으로, 행사명, 일시, 주최, 장소, 참여업체, 대상, 데이터기준일자 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3081184/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
일시 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:07:19.335120
Analysis finished2023-12-12 07:07:19.944745
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행사명
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T16:07:20.123069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length21.47619
Min length15

Characters and Unicode

Total characters451
Distinct characters77
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row3월 G밸리 우수기업 채용 박람회
2nd row2017 서울시 여성일자리 박람회
3rd row2017 금천희망새일 여성취업박람회
4th row7월 G밸리 우수기업 채용박람회
5th row2017 G-Valley 채용박람회
ValueCountFrequency (%)
g밸리 12
 
12.4%
우수기업 11
 
11.3%
채용박람회 11
 
11.3%
온라인 5
 
5.2%
박람회 5
 
5.2%
2017 4
 
4.1%
취업박람회 4
 
4.1%
2021년 3
 
3.1%
서울시 3
 
3.1%
여성일자리 3
 
3.1%
Other values (26) 36
37.1%
2023-12-12T16:07:20.544281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
 
17.1%
2 24
 
5.3%
회 21
 
4.7%
람 21
 
4.7%
박 21
 
4.7%
기 19
 
4.2%
0 18
 
4.0%
업 18
 
4.0%
리 15
 
3.3%
용 13
 
2.9%
Other values (67) 204
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 280
62.1%
Space Separator 77
 
17.1%
Decimal Number 68
 
15.1%
Uppercase Letter 15
 
3.3%
Lowercase Letter 7
 
1.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 21
 
7.5%
람 21
 
7.5%
박 21
 
7.5%
기 19
 
6.8%
업 18
 
6.4%
리 15
 
5.4%
용 13
 
4.6%
채 13
 
4.6%
수 12
 
4.3%
우 12
 
4.3%
Other values (46) 115
41.1%
Decimal Number
ValueCountFrequency (%)
2 24
35.3%
0 18
26.5%
1 12
17.6%
7 5
 
7.4%
9 4
 
5.9%
3 3
 
4.4%
8 2
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
l 2
28.6%
o 1
14.3%
b 1
14.3%
a 1
14.3%
e 1
14.3%
y 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
G 13
86.7%
J 1
 
6.7%
V 1
 
6.7%
Space Separator
ValueCountFrequency (%)
77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 280
62.1%
Common 149
33.0%
Latin 22
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 21
 
7.5%
람 21
 
7.5%
박 21
 
7.5%
기 19
 
6.8%
업 18
 
6.4%
리 15
 
5.4%
용 13
 
4.6%
채 13
 
4.6%
수 12
 
4.3%
우 12
 
4.3%
Other values (46) 115
41.1%
Common
ValueCountFrequency (%)
77
51.7%
2 24
 
16.1%
0 18
 
12.1%
1 12
 
8.1%
7 5
 
3.4%
9 4
 
2.7%
3 3
 
2.0%
8 2
 
1.3%
( 1
 
0.7%
) 1
 
0.7%
Other values (2) 2
 
1.3%
Latin
ValueCountFrequency (%)
G 13
59.1%
l 2
 
9.1%
J 1
 
4.5%
o 1
 
4.5%
b 1
 
4.5%
V 1
 
4.5%
a 1
 
4.5%
e 1
 
4.5%
y 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 280
62.1%
ASCII 170
37.7%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
45.3%
2 24
 
14.1%
0 18
 
10.6%
G 13
 
7.6%
1 12
 
7.1%
7 5
 
2.9%
9 4
 
2.4%
3 3
 
1.8%
l 2
 
1.2%
8 2
 
1.2%
Other values (10) 10
 
5.9%
Hangul
ValueCountFrequency (%)
회 21
 
7.5%
람 21
 
7.5%
박 21
 
7.5%
기 19
 
6.8%
업 18
 
6.4%
리 15
 
5.4%
용 13
 
4.6%
채 13
 
4.6%
수 12
 
4.3%
우 12
 
4.3%
Other values (46) 115
41.1%
None
ValueCountFrequency (%)
· 1
100.0%

일시
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T16:07:20.828901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length25.904762
Min length25

Characters and Unicode

Total characters544
Distinct characters21
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row2017-03-30(목) 13:00~16:00
2nd row2017-05-25(목) 13:00~16:00
3rd row2017-07-06(목) 13:00~16:00
4th row2017-07-19(수) 14:00~17:00
5th row2017-09-05(화) 14:00~17:00
ValueCountFrequency (%)
14:00~17:00 8
 
18.2%
13:00~16:00 5
 
11.4%
4
 
9.1%
2017-03-30(목 1
 
2.3%
2020-09-07(월)~2020-09-25(금 1
 
2.3%
09:00 1
 
2.3%
2023-09-20(수 1
 
2.3%
16:00 1
 
2.3%
13:00 1
 
2.3%
2022-8-25(목 1
 
2.3%
Other values (20) 20
45.5%
2023-12-12T16:07:21.286237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 127
23.3%
2 60
11.0%
1 58
10.7%
- 54
9.9%
: 30
 
5.5%
( 27
 
5.0%
) 27
 
5.0%
23
 
4.2%
~ 21
 
3.9%
7 20
 
3.7%
Other values (11) 97
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 335
61.6%
Dash Punctuation 54
 
9.9%
Other Punctuation 30
 
5.5%
Open Punctuation 27
 
5.0%
Close Punctuation 27
 
5.0%
Other Letter 27
 
5.0%
Space Separator 23
 
4.2%
Math Symbol 21
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 127
37.9%
2 60
17.9%
1 58
17.3%
7 20
 
6.0%
9 16
 
4.8%
6 15
 
4.5%
3 13
 
3.9%
4 10
 
3.0%
5 9
 
2.7%
8 7
 
2.1%
Other Letter
ValueCountFrequency (%)
목 8
29.6%
금 7
25.9%
월 6
22.2%
수 4
14.8%
화 2
 
7.4%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%
Other Punctuation
ValueCountFrequency (%)
: 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 517
95.0%
Hangul 27
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 127
24.6%
2 60
11.6%
1 58
11.2%
- 54
10.4%
: 30
 
5.8%
( 27
 
5.2%
) 27
 
5.2%
23
 
4.4%
~ 21
 
4.1%
7 20
 
3.9%
Other values (6) 70
13.5%
Hangul
ValueCountFrequency (%)
목 8
29.6%
금 7
25.9%
월 6
22.2%
수 4
14.8%
화 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 517
95.0%
Hangul 27
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 127
24.6%
2 60
11.6%
1 58
11.2%
- 54
10.4%
: 30
 
5.8%
( 27
 
5.2%
) 27
 
5.2%
23
 
4.4%
~ 21
 
4.1%
7 20
 
3.9%
Other values (6) 70
13.5%
Hangul
ValueCountFrequency (%)
목 8
29.6%
금 7
25.9%
월 6
22.2%
수 4
14.8%
화 2
 
7.4%

주최
Text

Distinct12
Distinct (%)57.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T16:07:21.525408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length14.47619
Min length3

Characters and Unicode

Total characters304
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)23.8%

Sample

1st row한국산업단지공단
2nd row남부여성발전센터,금천구
3rd row남부여성발전센터,금천구
4th row산업단지공단, 관악고용센터, 금천구, 구로구
5th row관악고용센터, 금천구, 구로구
ValueCountFrequency (%)
한국산업단지공단 11
27.5%
금천구 8
20.0%
중소벤처기업진흥공단 4
 
10.0%
남부여성발전센터,금천구 2
 
5.0%
서울지방중소벤처기업청 2
 
5.0%
남부여성발전센터 2
 
5.0%
서울본부 2
 
5.0%
관악고용센터 2
 
5.0%
구로구 2
 
5.0%
산업단지공단 1
 
2.5%
Other values (4) 4
 
10.0%
2023-12-12T16:07:21.861893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 28
 
9.2%
업 19
 
6.2%
, 19
 
6.2%
19
 
6.2%
공 16
 
5.3%
지 15
 
4.9%
구 15
 
4.9%
산 12
 
3.9%
한 11
 
3.6%
국 11
 
3.6%
Other values (39) 139
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 266
87.5%
Other Punctuation 19
 
6.2%
Space Separator 19
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 28
 
10.5%
업 19
 
7.1%
공 16
 
6.0%
지 15
 
5.6%
구 15
 
5.6%
산 12
 
4.5%
한 11
 
4.1%
국 11
 
4.1%
천 10
 
3.8%
금 10
 
3.8%
Other values (37) 119
44.7%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 266
87.5%
Common 38
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 28
 
10.5%
업 19
 
7.1%
공 16
 
6.0%
지 15
 
5.6%
구 15
 
5.6%
산 12
 
4.5%
한 11
 
4.1%
국 11
 
4.1%
천 10
 
3.8%
금 10
 
3.8%
Other values (37) 119
44.7%
Common
ValueCountFrequency (%)
, 19
50.0%
19
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 266
87.5%
ASCII 38
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 28
 
10.5%
업 19
 
7.1%
공 16
 
6.0%
지 15
 
5.6%
구 15
 
5.6%
산 12
 
4.5%
한 11
 
4.1%
국 11
 
4.1%
천 10
 
3.8%
금 10
 
3.8%
Other values (37) 119
44.7%
ASCII
ValueCountFrequency (%)
, 19
50.0%
19
50.0%

장소
Text

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T16:07:22.063908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.3333333
Min length7

Characters and Unicode

Total characters196
Distinct characters65
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)33.3%

Sample

1st rowG밸리컨벤션센터
2nd row현대지식산업센터 마당
3rd row남부여성발전센터 강당
4th rowG밸리컨벤션센터
5th row신도림 테크노마트
ValueCountFrequency (%)
g밸리컨벤션센터 6
17.6%
강당 4
 
11.8%
온라인(잡코리아 4
 
11.8%
남부여성발전센터 3
 
8.8%
금천구청 2
 
5.9%
온라인(키콕스잡 1
 
2.9%
매그넷고 1
 
2.9%
서울 1
 
2.9%
홈페이지 1
 
2.9%
채용 1
 
2.9%
Other values (10) 10
29.4%
2023-12-12T16:07:22.483658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
6.6%
리 11
 
5.6%
센 10
 
5.1%
터 10
 
5.1%
G 6
 
3.1%
라 6
 
3.1%
밸 6
 
3.1%
잡 6
 
3.1%
인 6
 
3.1%
당 6
 
3.1%
Other values (55) 116
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 165
84.2%
Space Separator 13
 
6.6%
Uppercase Letter 6
 
3.1%
Open Punctuation 5
 
2.6%
Close Punctuation 5
 
2.6%
Other Punctuation 1
 
0.5%
Decimal Number 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 11
 
6.7%
센 10
 
6.1%
터 10
 
6.1%
라 6
 
3.6%
밸 6
 
3.6%
잡 6
 
3.6%
인 6
 
3.6%
당 6
 
3.6%
온 6
 
3.6%
컨 6
 
3.6%
Other values (49) 92
55.8%
Space Separator
ValueCountFrequency (%)
13
100.0%
Uppercase Letter
ValueCountFrequency (%)
G 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
84.2%
Common 25
 
12.8%
Latin 6
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 11
 
6.7%
센 10
 
6.1%
터 10
 
6.1%
라 6
 
3.6%
밸 6
 
3.6%
잡 6
 
3.6%
인 6
 
3.6%
당 6
 
3.6%
온 6
 
3.6%
컨 6
 
3.6%
Other values (49) 92
55.8%
Common
ValueCountFrequency (%)
13
52.0%
( 5
 
20.0%
) 5
 
20.0%
, 1
 
4.0%
1 1
 
4.0%
Latin
ValueCountFrequency (%)
G 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 165
84.2%
ASCII 31
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
41.9%
G 6
19.4%
( 5
 
16.1%
) 5
 
16.1%
, 1
 
3.2%
1 1
 
3.2%
Hangul
ValueCountFrequency (%)
리 11
 
6.7%
센 10
 
6.1%
터 10
 
6.1%
라 6
 
3.6%
밸 6
 
3.6%
잡 6
 
3.6%
인 6
 
3.6%
당 6
 
3.6%
온 6
 
3.6%
컨 6
 
3.6%
Other values (49) 92
55.8%

참여업체
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T16:07:22.695921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.047619
Min length5

Characters and Unicode

Total characters127
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)52.4%

Sample

1st row20개 업체
2nd row20개 업체
3rd row10개 업체
4th row20개 업체
5th row50개 업체
ValueCountFrequency (%)
업체 20
48.8%
50개 7
 
17.1%
20개 3
 
7.3%
10개 1
 
2.4%
30개 1
 
2.4%
47개 1
 
2.4%
33개 1
 
2.4%
24개 1
 
2.4%
58개 1
 
2.4%
34개 1
 
2.4%
Other values (4) 4
 
9.8%
2023-12-12T16:07:23.063656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
개 21
16.5%
업 21
16.5%
체 21
16.5%
20
15.7%
0 16
12.6%
5 8
 
6.3%
3 7
 
5.5%
2 6
 
4.7%
4 3
 
2.4%
1 2
 
1.6%
Other values (2) 2
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
49.6%
Decimal Number 44
34.6%
Space Separator 20
 
15.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
36.4%
5 8
18.2%
3 7
15.9%
2 6
 
13.6%
4 3
 
6.8%
1 2
 
4.5%
7 1
 
2.3%
8 1
 
2.3%
Other Letter
ValueCountFrequency (%)
개 21
33.3%
업 21
33.3%
체 21
33.3%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
50.4%
Hangul 63
49.6%

Most frequent character per script

Common
ValueCountFrequency (%)
20
31.2%
0 16
25.0%
5 8
 
12.5%
3 7
 
10.9%
2 6
 
9.4%
4 3
 
4.7%
1 2
 
3.1%
7 1
 
1.6%
8 1
 
1.6%
Hangul
ValueCountFrequency (%)
개 21
33.3%
업 21
33.3%
체 21
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
50.4%
Hangul 63
49.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
개 21
33.3%
업 21
33.3%
체 21
33.3%
ASCII
ValueCountFrequency (%)
20
31.2%
0 16
25.0%
5 8
 
12.5%
3 7
 
10.9%
2 6
 
9.4%
4 3
 
4.7%
1 2
 
3.1%
7 1
 
1.6%
8 1
 
1.6%

대상
Categorical

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
구직자
9 
경력단절여성구직자
4 
청년구직자
4 
청,장년구직자
3 
매그넷고 학생 구직자
1 

Length

Max length11
Median length9
Mean length5.4761905
Min length3

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row구직자
2nd row경력단절여성구직자
3rd row경력단절여성구직자
4th row청년구직자
5th row구직자

Common Values

ValueCountFrequency (%)
구직자 9
42.9%
경력단절여성구직자 4
19.0%
청년구직자 4
19.0%
청,장년구직자 3
 
14.3%
매그넷고 학생 구직자 1
 
4.8%

Length

2023-12-12T16:07:23.253929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:23.417849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구직자 10
43.5%
경력단절여성구직자 4
 
17.4%
청년구직자 4
 
17.4%
청,장년구직자 3
 
13.0%
매그넷고 1
 
4.3%
학생 1
 
4.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-08-26
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-26
2nd row2023-08-26
3rd row2023-08-26
4th row2023-08-26
5th row2023-08-26

Common Values

ValueCountFrequency (%)
2023-08-26 21
100.0%

Length

2023-12-12T16:07:23.578243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:07:23.705336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-26 21
100.0%

Correlations

2023-12-12T16:07:23.790215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행사명일시주최장소참여업체대상
행사명1.0001.0000.9481.0000.9840.950
일시1.0001.0001.0001.0001.0001.000
주최0.9481.0001.0000.7130.4490.758
장소1.0001.0000.7131.0000.8250.891
참여업체0.9841.0000.4490.8251.0000.744
대상0.9501.0000.7580.8910.7441.000

Missing values

2023-12-12T16:07:19.742566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:07:19.888856image/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

행사명일시주최장소참여업체대상데이터기준일자
03월 G밸리 우수기업 채용 박람회2017-03-30(목) 13:00~16:00한국산업단지공단G밸리컨벤션센터20개 업체구직자2023-08-26
12017 서울시 여성일자리 박람회2017-05-25(목) 13:00~16:00남부여성발전센터,금천구현대지식산업센터 마당20개 업체경력단절여성구직자2023-08-26
22017 금천희망새일 여성취업박람회2017-07-06(목) 13:00~16:00남부여성발전센터,금천구남부여성발전센터 강당10개 업체경력단절여성구직자2023-08-26
37월 G밸리 우수기업 채용박람회2017-07-19(수) 14:00~17:00산업단지공단, 관악고용센터, 금천구, 구로구G밸리컨벤션센터20개 업체청년구직자2023-08-26
42017 G-Valley 채용박람회2017-09-05(화) 14:00~17:00관악고용센터, 금천구, 구로구신도림 테크노마트50개 업체구직자2023-08-26
52017 찾아가는 취업박람회2017-09-15(금) 14:00~17:00서울시, 금천구, 동작구동작구청 대강당30개 업체청,장년구직자2023-08-26
63월 G밸리 우수기업 채용 박람회2018-03-22(목) 14:00~17:00한국산업단지공단, 서울지방중소벤처기업청G밸리컨벤션센터50개 업체청년구직자2023-08-26
72018년 금천구 취업박람회2018-03-29(목) 14:00~17:00금천구, 스마트사업협동조합금천구청 강당47개 업체구직자2023-08-26
82018 서울시 여성일자리 박람회2018-07-10(화) 13:00~16:00남부여성발전센터, 금천구남부여성발전센터 강당33개 업체경력단절여성구직자2023-08-26
99월 G밸리 우수기업 채용박람회2018-10-05(금) 14:00~17:00한국산업단지공단, 서울지방중소벤처기업청G밸리컨벤션센터50개 업체청년구직자2023-08-26
행사명일시주최장소참여업체대상데이터기준일자
112019 서울시 여성일자리 박람회2019-09-23(월) 13:00~16:00남부여성발전센터, 금천구남부여성발전센터 1층24개 업체경력단절여성구직자2023-08-26
122019 하반기 G밸리 우수기업 채용박람회2019-09-26(목) 14:00~17:00한국산업단지공단G밸리컨벤션센터58개 업체청,장년구직자2023-08-26
132020 상반기 G밸리 우수기업 온라인 채용박람회2020-06-01(월)~2020-06-24(수)한국산업단지공단, 중소벤처기업진흥공단온라인(키콕스잡, 잡코리아)34개 업체청년구직자2023-08-26
142020 하반기 G밸리 우수기업 온택트 채용박람회2020-09-07(월)~2020-09-25(금)한국산업단지공단, 중소벤처기업진흥공단온라인 채용 홈페이지50개 업체구직자2023-08-26
152021년 상반기 G밸리 우수기업 온라인 채용박람회2021-04-12(월)~2021-05-07(금)한국산업단지공단, 중소벤처기업진흥공단온라인(잡코리아)100개 업체구직자2023-08-26
162021년 G밸리 우수기업·산업기능요원 온라인 채용박람회2021-06-28(월)~2021-07-23(금)한국산업단지공단, 서울지방병무청온라인(잡코리아)50개 업체구직자2023-08-26
172021년 하반기 G밸리 우수기업 온라인 채용박람회2021-09-29(수) ~ 2021-10-29(금)한국산업단지공단 서울본부온라인(잡코리아)50개 업체구직자2023-08-26
182022년 G밸리 우수기업 온라인 채용박람회2022-06-06(월) ~ 2022-12-16(금)한국산업단지공단 서울본부온라인(잡코리아)330개 업체구직자2023-08-26
19특성화고 학생 대상 소규모 취업박람회2022-8-25(목) 13:00 ~ 16:00금천구서울 매그넷고 체육관23개 업체매그넷고 학생 구직자2023-08-26
20내 일(Job)을 향한 2023 금천구 취업박람회2023-09-20(수) 09:00 ~ 18:00금천구금천구청 강당20개업체구직자2023-08-26