Overview

Dataset statistics

Number of variables8
Number of observations27
Missing cells178
Missing cells (%)82.4%
Duplicate rows1
Duplicate rows (%)3.7%
Total size in memory1.9 KiB
Average record size in memory71.9 B

Variable types

Text5
Unsupported3

Dataset

Description대전여성인력개발센터 운영, 여성 취업창업 박람회 개최, 여성새로일하기센터 운영현황에 대한 경력단절여성의 경제활동촉진 사업 현황에 대한 데이터
URLhttps://www.data.go.kr/data/15083559/fileData.do

Alerts

Dataset has 1 (3.7%) duplicate rowsDuplicates
경력단절여성 경제활동촉진사업 현황 has 13 (48.1%) missing valuesMissing
Unnamed: 1 has 27 (100.0%) missing valuesMissing
Unnamed: 2 has 27 (100.0%) missing valuesMissing
Unnamed: 3 has 19 (70.4%) missing valuesMissing
Unnamed: 4 has 23 (85.2%) missing valuesMissing
Unnamed: 5 has 23 (85.2%) missing valuesMissing
Unnamed: 6 has 27 (100.0%) missing valuesMissing
Unnamed: 7 has 19 (70.4%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 19:37:08.335303
Analysis finished2023-12-12 19:37:09.274688
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct10
Distinct (%)71.4%
Missing13
Missing (%)48.1%
Memory size348.0 B
2023-12-13T04:37:09.606927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length391
Median length137
Mean length76.285714
Min length2

Characters and Unicode

Total characters1068
Distinct characters192
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)42.9%

Sample

1st row▶ 대전여성인력개발센터 운영 1. 사업목적: 여성 직업능력개발과 취업기회 제공을 통하여 여성의 사회적 경제적 지위 향상 2. 위 치: 서구 계룡로 636(용문동) 도산회관 5,6층(☎534-4340) 3. 운영주체: 대전YWCA (관장 강은혜) 4. 이용대상: 대전광역시 거주여성 5. 사업내용 - 여성취업을 위한 직업교육훈련 및 사회문화교육과정 운영 - 여성 취업·창업과 관련된 정보제공 및 상담 - 국민취업지원제도 운영 (고용노동부의 취업지원 사업)
2nd row▶ 여성 취업·창업 박람회 개최 1. 사업목적: 취·창업을 희망하는 여성들에게 직업정보 제공 및 취업기회 마련 2. 일시·장소: 2023. 9. 13 / 대전광역시청 *온라인박람회: 2023. 9. 13.~30. / http://대전여성취업창업박람회.kr 3. 주최·주관: 대전광역시 / 배재대학교 산학협력단(대전광역여성새로일하기센터) 4. 참여대상: 대전광역시 관내 여성 5. 사업참여: 채용기업, 구직자, 일자리 유관기관 등 6. 사업내용 - 현장 부스운영, 온라인 면접 플랫폼 운영 - 맞춤형 취업지원 서비스 제공, AI매칭시스템, 온라인 자소서 컨설팅, 온라인 취업특강 등 다양한 서비스 제공 - 일자리 정책 정보 제공, 창업정보 제공, 현장특강, 이벤트 등
3rd row▶ 여성새로일하기센터 운영현황
4th row1. 사업목적 ㅇ 경력단절 여성의 취업지원을 전담하는 여성 종합취업지원센터 운영 ㅇ 일·가정 양립, 여성친화기업 문화 확산 등 경력단절 예방 활동
5th row2. 사업개요 ㅇ운 영: 여성새로일하기센터 3개소 ㅇ사업내용: 새일 여성인턴십 지원, 직업교육훈련, 취업·창업상담, 경력단절 예방활동 추진, 경력이음 사례관리서비스 추진 등
ValueCountFrequency (%)
9
 
4.2%
여성 7
 
3.3%
운영 6
 
2.8%
5
 
2.3%
5
 
2.3%
제공 5
 
2.3%
4
 
1.9%
2 3
 
1.4%
경력단절 3
 
1.4%
직업교육훈련 3
 
1.4%
Other values (131) 163
76.5%
2023-12-13T04:37:10.213495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
227
 
21.3%
41
 
3.8%
27
 
2.5%
26
 
2.4%
24
 
2.2%
. 21
 
2.0%
19
 
1.8%
, 16
 
1.5%
16
 
1.5%
15
 
1.4%
Other values (182) 636
59.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 656
61.4%
Space Separator 227
 
21.3%
Other Punctuation 66
 
6.2%
Decimal Number 47
 
4.4%
Control 27
 
2.5%
Uppercase Letter 12
 
1.1%
Close Punctuation 7
 
0.7%
Dash Punctuation 7
 
0.7%
Open Punctuation 7
 
0.7%
Lowercase Letter 6
 
0.6%
Other values (2) 6
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
41
 
6.2%
26
 
4.0%
24
 
3.7%
19
 
2.9%
16
 
2.4%
15
 
2.3%
15
 
2.3%
14
 
2.1%
11
 
1.7%
11
 
1.7%
Other values (149) 464
70.7%
Decimal Number
ValueCountFrequency (%)
3 12
25.5%
2 7
14.9%
1 7
14.9%
4 5
10.6%
0 4
 
8.5%
6 4
 
8.5%
5 4
 
8.5%
9 4
 
8.5%
Other Punctuation
ValueCountFrequency (%)
. 21
31.8%
, 16
24.2%
: 13
19.7%
· 10
15.2%
/ 5
 
7.6%
* 1
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
I 3
25.0%
T 2
16.7%
A 2
16.7%
W 1
 
8.3%
Y 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
t 2
33.3%
r 1
16.7%
k 1
16.7%
p 1
16.7%
h 1
16.7%
Other Symbol
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Space Separator
ValueCountFrequency (%)
227
100.0%
Control
ValueCountFrequency (%)
27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 656
61.4%
Common 394
36.9%
Latin 18
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
41
 
6.2%
26
 
4.0%
24
 
3.7%
19
 
2.9%
16
 
2.4%
15
 
2.3%
15
 
2.3%
14
 
2.1%
11
 
1.7%
11
 
1.7%
Other values (149) 464
70.7%
Common
ValueCountFrequency (%)
227
57.6%
27
 
6.9%
. 21
 
5.3%
, 16
 
4.1%
: 13
 
3.3%
3 12
 
3.0%
· 10
 
2.5%
) 7
 
1.8%
2 7
 
1.8%
- 7
 
1.8%
Other values (12) 47
 
11.9%
Latin
ValueCountFrequency (%)
C 3
16.7%
I 3
16.7%
t 2
11.1%
T 2
11.1%
A 2
11.1%
W 1
 
5.6%
Y 1
 
5.6%
r 1
 
5.6%
k 1
 
5.6%
p 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 649
60.8%
ASCII 398
37.3%
None 10
 
0.9%
Compat Jamo 7
 
0.7%
Geometric Shapes 3
 
0.3%
Misc Symbols 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
227
57.0%
27
 
6.8%
. 21
 
5.3%
, 16
 
4.0%
: 13
 
3.3%
3 12
 
3.0%
) 7
 
1.8%
2 7
 
1.8%
- 7
 
1.8%
( 7
 
1.8%
Other values (20) 54
 
13.6%
Hangul
ValueCountFrequency (%)
41
 
6.3%
26
 
4.0%
24
 
3.7%
19
 
2.9%
16
 
2.5%
15
 
2.3%
15
 
2.3%
14
 
2.2%
11
 
1.7%
11
 
1.7%
Other values (148) 457
70.4%
None
ValueCountFrequency (%)
· 10
100.0%
Compat Jamo
ValueCountFrequency (%)
7
100.0%
Geometric Shapes
ValueCountFrequency (%)
3
100.0%
Misc Symbols
ValueCountFrequency (%)
1
100.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)87.5%
Missing19
Missing (%)70.4%
Memory size348.0 B
2023-12-13T04:37:10.451195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6.5
Mean length5.625
Min length2

Characters and Unicode

Total characters45
Distinct characters27
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

Unique6 ?
Unique (%)75.0%

Sample

1st row운영주체
2nd row여성인력개발센터
3rd row배재대학교산학협력단
4th row배재대학교산학협력단
5th row유형
ValueCountFrequency (%)
배재대학교산학협력단 2
25.0%
운영주체 1
12.5%
여성인력개발센터 1
12.5%
유형 1
12.5%
일반형 1
12.5%
광역형 1
12.5%
경력개발형 1
12.5%
2023-12-13T04:37:10.917287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
8.9%
4
 
8.9%
4
 
8.9%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (17) 19
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
 
8.9%
4
 
8.9%
4
 
8.9%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (17) 19
42.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
 
8.9%
4
 
8.9%
4
 
8.9%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (17) 19
42.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
 
8.9%
4
 
8.9%
4
 
8.9%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
2
 
4.4%
Other values (17) 19
42.2%

Unnamed: 4
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing23
Missing (%)85.2%
Memory size348.0 B
2023-12-13T04:37:11.124962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length34.75
Min length7

Characters and Unicode

Total characters139
Distinct characters45
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row주요 프로그램
2nd row‧ 새일인턴십 ‧ 직업교육훈련 ‧ 경력이음 사례관리서비스
3rd row‧ 새일인턴십 ‧ 경력단절예방지원사업 ‧ 직업교육훈련 ‧지역맞춤형 직업교육훈련 과정개발
4th row‧ 새일인턴십 ‧ 직업교육훈련 ‧ 경력이음 사례관리서비스
ValueCountFrequency (%)
9
36.0%
직업교육훈련 4
16.0%
새일인턴십 3
 
12.0%
경력이음 2
 
8.0%
사례관리서비스 2
 
8.0%
주요 1
 
4.0%
프로그램 1
 
4.0%
경력단절예방지원사업 1
 
4.0%
‧지역맞춤형 1
 
4.0%
과정개발 1
 
4.0%
2023-12-13T04:37:11.794632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
28.1%
10
 
7.2%
5
 
3.6%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
4
 
2.9%
3
 
2.2%
Other values (35) 58
41.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86
61.9%
Space Separator 39
28.1%
Other Punctuation 10
 
7.2%
Control 4
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
5.8%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
3
 
3.5%
Other values (32) 49
57.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Other Punctuation
ValueCountFrequency (%)
10
100.0%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86
61.9%
Common 53
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
5.8%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
3
 
3.5%
Other values (32) 49
57.0%
Common
ValueCountFrequency (%)
39
73.6%
10
 
18.9%
4
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86
61.9%
ASCII 43
30.9%
Punctuation 10
 
7.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
90.7%
4
 
9.3%
Punctuation
ValueCountFrequency (%)
10
100.0%
Hangul
ValueCountFrequency (%)
5
 
5.8%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
3
 
3.5%
Other values (32) 49
57.0%

Unnamed: 5
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing23
Missing (%)85.2%
Memory size348.0 B
2023-12-13T04:37:11.992413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length7.5
Min length3

Characters and Unicode

Total characters30
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row연락처
2nd row☎524-4181
3rd row☎520-5303
4th row☎520-5087
ValueCountFrequency (%)
연락처 1
25.0%
☎524-4181 1
25.0%
☎520-5303 1
25.0%
☎520-5087 1
25.0%
2023-12-13T04:37:12.387826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 5
16.7%
0 4
13.3%
3
10.0%
2 3
10.0%
- 3
10.0%
4 2
 
6.7%
1 2
 
6.7%
8 2
 
6.7%
3 2
 
6.7%
1
 
3.3%
Other values (3) 3
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21
70.0%
Other Symbol 3
 
10.0%
Dash Punctuation 3
 
10.0%
Other Letter 3
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 5
23.8%
0 4
19.0%
2 3
14.3%
4 2
 
9.5%
1 2
 
9.5%
8 2
 
9.5%
3 2
 
9.5%
7 1
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27
90.0%
Hangul 3
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 5
18.5%
0 4
14.8%
3
11.1%
2 3
11.1%
- 3
11.1%
4 2
 
7.4%
1 2
 
7.4%
8 2
 
7.4%
3 2
 
7.4%
7 1
 
3.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
80.0%
Misc Symbols 3
 
10.0%
Hangul 3
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 5
20.8%
0 4
16.7%
2 3
12.5%
- 3
12.5%
4 2
 
8.3%
1 2
 
8.3%
8 2
 
8.3%
3 2
 
8.3%
7 1
 
4.2%
Misc Symbols
ValueCountFrequency (%)
3
100.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)100.0%
Memory size375.0 B

Unnamed: 7
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing19
Missing (%)70.4%
Memory size348.0 B
2023-12-13T04:37:12.719328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length28.5
Mean length25
Min length2

Characters and Unicode

Total characters200
Distinct characters97
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)100.0%

Sample

1st row위치
2nd row서구 계룡로 636(용문동) 도산회관 5,6층
3rd row서구 배재로 155-40(도마동)배재대학교
4th row유성구 테크노1로 11-3(관평동)
5th row비고
ValueCountFrequency (%)
2
 
4.3%
서구 2
 
4.3%
취업지원서비스 2
 
4.3%
맞춤형 2
 
4.3%
2
 
4.3%
구축 1
 
2.2%
직업훈련 1
 
2.2%
과정 1
 
2.2%
개발 1
 
2.2%
1
 
2.2%
Other values (31) 31
67.4%
2023-12-13T04:37:13.173769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38
 
19.0%
5
 
2.5%
4
 
2.0%
4
 
2.0%
4
 
2.0%
4
 
2.0%
1 4
 
2.0%
3
 
1.5%
5 3
 
1.5%
3
 
1.5%
Other values (87) 128
64.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
67.0%
Space Separator 38
 
19.0%
Decimal Number 17
 
8.5%
Close Punctuation 3
 
1.5%
Open Punctuation 3
 
1.5%
Dash Punctuation 2
 
1.0%
Other Punctuation 2
 
1.0%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
 
3.7%
4
 
3.0%
4
 
3.0%
4
 
3.0%
4
 
3.0%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
Other values (74) 98
73.1%
Decimal Number
ValueCountFrequency (%)
1 4
23.5%
5 3
17.6%
3 3
17.6%
6 3
17.6%
4 2
11.8%
0 2
11.8%
Other Punctuation
ValueCountFrequency (%)
1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
67.0%
Common 66
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
 
3.7%
4
 
3.0%
4
 
3.0%
4
 
3.0%
4
 
3.0%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
Other values (74) 98
73.1%
Common
ValueCountFrequency (%)
38
57.6%
1 4
 
6.1%
5 3
 
4.5%
) 3
 
4.5%
( 3
 
4.5%
3 3
 
4.5%
6 3
 
4.5%
- 2
 
3.0%
4 2
 
3.0%
0 2
 
3.0%
Other values (3) 3
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
67.0%
ASCII 65
32.5%
Punctuation 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38
58.5%
1 4
 
6.2%
5 3
 
4.6%
) 3
 
4.6%
( 3
 
4.6%
3 3
 
4.6%
6 3
 
4.6%
- 2
 
3.1%
4 2
 
3.1%
0 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
5
 
3.7%
4
 
3.0%
4
 
3.0%
4
 
3.0%
4
 
3.0%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
3
 
2.2%
Other values (74) 98
73.1%
Punctuation
ValueCountFrequency (%)
1
100.0%

Correlations

2023-12-13T04:37:13.302414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경력단절여성 경제활동촉진사업 현황Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 7
경력단절여성 경제활동촉진사업 현황1.0000.7081.0001.0001.000
Unnamed: 30.7081.0001.0001.0001.000
Unnamed: 41.0001.0001.000NaN1.000
Unnamed: 51.0001.000NaN1.0001.000
Unnamed: 71.0001.0001.0001.0001.000

Missing values

2023-12-13T04:37:08.884722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:37:09.022866image/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.
2023-12-13T04:37:09.169984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

경력단절여성 경제활동촉진사업 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
0<NA><NA><NA><NA><NA><NA><NA><NA>
1▶ 대전여성인력개발센터 운영 1. 사업목적: 여성 직업능력개발과 취업기회 제공을 통하여 여성의 사회적 경제적 지위 향상 2. 위 치: 서구 계룡로 636(용문동) 도산회관 5,6층(☎534-4340) 3. 운영주체: 대전YWCA (관장 강은혜) 4. 이용대상: 대전광역시 거주여성 5. 사업내용 - 여성취업을 위한 직업교육훈련 및 사회문화교육과정 운영 - 여성 취업·창업과 관련된 정보제공 및 상담 - 국민취업지원제도 운영 (고용노동부의 취업지원 사업)<NA><NA><NA><NA><NA><NA><NA>
2<NA><NA><NA><NA><NA><NA><NA><NA>
3▶ 여성 취업·창업 박람회 개최 1. 사업목적: 취·창업을 희망하는 여성들에게 직업정보 제공 및 취업기회 마련 2. 일시·장소: 2023. 9. 13 / 대전광역시청 *온라인박람회: 2023. 9. 13.~30. / http://대전여성취업창업박람회.kr 3. 주최·주관: 대전광역시 / 배재대학교 산학협력단(대전광역여성새로일하기센터) 4. 참여대상: 대전광역시 관내 여성 5. 사업참여: 채용기업, 구직자, 일자리 유관기관 등 6. 사업내용 - 현장 부스운영, 온라인 면접 플랫폼 운영 - 맞춤형 취업지원 서비스 제공, AI매칭시스템, 온라인 자소서 컨설팅, 온라인 취업특강 등 다양한 서비스 제공 - 일자리 정책 정보 제공, 창업정보 제공, 현장특강, 이벤트 등<NA><NA><NA><NA><NA><NA><NA>
4<NA><NA><NA><NA><NA><NA><NA><NA>
5▶ 여성새로일하기센터 운영현황<NA><NA><NA><NA><NA><NA><NA>
6<NA><NA><NA><NA><NA><NA><NA><NA>
71. 사업목적 ㅇ 경력단절 여성의 취업지원을 전담하는 여성 종합취업지원센터 운영 ㅇ 일·가정 양립, 여성친화기업 문화 확산 등 경력단절 예방 활동<NA><NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA><NA><NA>
경력단절여성 경제활동촉진사업 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7
17대전여성새일센터<NA><NA>여성인력개발센터<NA>☎524-4181<NA>서구 계룡로 636(용문동) 도산회관 5,6층
18대전광역새일센터<NA><NA>배재대학교산학협력단<NA>☎520-5303<NA>서구 배재로 155-40(도마동)배재대학교
19대전배재대ICT융합새일센터<NA><NA>배재대학교산학협력단<NA>☎520-5087<NA>유성구 테크노1로 11-3(관평동)
20<NA><NA><NA><NA><NA><NA><NA><NA>
21구분<NA><NA>유형주요 프로그램<NA><NA>비고
22대전여성새일센터<NA><NA>일반형‧ 새일인턴십 ‧ 직업교육훈련 ‧ 경력이음 사례관리서비스<NA><NA>지역환경에 맞는 직업교육훈련 등 맞춤형 취업지원서비스 제공
23대전광역새일센터<NA><NA>광역형‧ 새일인턴십 ‧ 경력단절예방지원사업 ‧ 직업교육훈련 ‧지역맞춤형 직업교육훈련 과정개발<NA><NA>지역 내 일자리 네트워크 구축 및 직업훈련 과정 개발 ․ 보급 등 새일센터 거점기능 수행
24대전배재대ICT융합새일센터<NA><NA>경력개발형‧ 새일인턴십 ‧ 직업교육훈련 ‧ 경력이음 사례관리서비스<NA><NA>새로운 분야 및 3~40대 특정 직종의 경력단절여성에게 경력 맞춤형 취업지원서비스 지원
25<NA><NA><NA><NA><NA><NA><NA><NA>
263. 사업계획 ㅇ 지속적인 여성 구인기업 발굴 및 경력단절여성 취·창업 상담 실시 ㅇ 구인·구직자 수요조사를 통한 지역특성에 맞는 직업교육훈련 발굴 운영 ㅇ 여성 취업창업 박람회 개최(9월), 여성친화기업 협약(9~11월중 심사·선정)<NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

경력단절여성 경제활동촉진사업 현황Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 7# duplicates
0<NA><NA><NA><NA><NA>13