Overview

Dataset statistics

Number of variables11
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory95.3 B

Variable types

Numeric1
Text5
DateTime1
Categorical3
Boolean1

Dataset

Description전북특별자치도 시군별 여성직업훈련기관 현황 데이터입니다. (시군명, 기관명, 설립일, 대표자, 도로명주소, 연락처, 주요사업 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055716/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
갱신주기(년) has constant value ""Constant
순번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 09:31:46.341040
Analysis finished2024-03-14 09:31:47.802797
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T18:31:47.910166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-03-14T18:31:48.155399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

시군명
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T18:31:48.735354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters72
Distinct characters22
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 (%)25.0%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row전주시
ValueCountFrequency (%)
전주시 5
20.8%
군산시 3
12.5%
익산시 2
 
8.3%
정읍시 2
 
8.3%
남원시 2
 
8.3%
김제시 2
 
8.3%
완주군 2
 
8.3%
진안군 1
 
4.2%
무주군 1
 
4.2%
장수군 1
 
4.2%
Other values (3) 3
12.5%
2024-03-14T18:31:49.690718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 16
22.2%
군 11
15.3%
주 8
11.1%
전 5
 
6.9%
산 5
 
6.9%
김 2
 
2.8%
창 2
 
2.8%
안 2
 
2.8%
완 2
 
2.8%
제 2
 
2.8%
Other values (12) 17
23.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
22.2%
군 11
15.3%
주 8
11.1%
전 5
 
6.9%
산 5
 
6.9%
김 2
 
2.8%
창 2
 
2.8%
안 2
 
2.8%
완 2
 
2.8%
제 2
 
2.8%
Other values (12) 17
23.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
22.2%
군 11
15.3%
주 8
11.1%
전 5
 
6.9%
산 5
 
6.9%
김 2
 
2.8%
창 2
 
2.8%
안 2
 
2.8%
완 2
 
2.8%
제 2
 
2.8%
Other values (12) 17
23.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 16
22.2%
군 11
15.3%
주 8
11.1%
전 5
 
6.9%
산 5
 
6.9%
김 2
 
2.8%
창 2
 
2.8%
안 2
 
2.8%
완 2
 
2.8%
제 2
 
2.8%
Other values (12) 17
23.6%

기관명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T18:31:50.512182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length11.666667
Min length6

Characters and Unicode

Total characters280
Distinct characters61
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

Unique24 ?
Unique (%)100.0%

Sample

1st row전북여성교육문화센터
2nd row전주여성인력개발센터
3rd row전북새일센터(여성교육문화센터)
4th row전북광역센터(여성교육문화센터)
5th row전주새일센터(전주여성인력개발센터)
ValueCountFrequency (%)
전북여성교육문화센터 1
 
4.2%
전주여성인력개발센터 1
 
4.2%
고창여성회관 1
 
4.2%
순창여성회관 1
 
4.2%
여성청소년문화센터 1
 
4.2%
무주종합복지관일자리센터 1
 
4.2%
진안여성일자리지원센터 1
 
4.2%
완주새일센터(완주근로자종합복지관 1
 
4.2%
완주가족문화교육원 1
 
4.2%
김제새일센터(김제시여성문화센터 1
 
4.2%
Other values (14) 14
58.3%
2024-03-14T18:31:51.760658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 21
 
7.5%
터 21
 
7.5%
여 20
 
7.1%
성 20
 
7.1%
일 11
 
3.9%
관 10
 
3.6%
새 9
 
3.2%
문 9
 
3.2%
화 9
 
3.2%
) 9
 
3.2%
Other values (51) 141
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 262
93.6%
Close Punctuation 9
 
3.2%
Open Punctuation 9
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 21
 
8.0%
터 21
 
8.0%
여 20
 
7.6%
성 20
 
7.6%
일 11
 
4.2%
관 10
 
3.8%
새 9
 
3.4%
문 9
 
3.4%
화 9
 
3.4%
시 7
 
2.7%
Other values (49) 125
47.7%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 262
93.6%
Common 18
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 21
 
8.0%
터 21
 
8.0%
여 20
 
7.6%
성 20
 
7.6%
일 11
 
4.2%
관 10
 
3.8%
새 9
 
3.4%
문 9
 
3.4%
화 9
 
3.4%
시 7
 
2.7%
Other values (49) 125
47.7%
Common
ValueCountFrequency (%)
) 9
50.0%
( 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 262
93.6%
ASCII 18
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 21
 
8.0%
터 21
 
8.0%
여 20
 
7.6%
성 20
 
7.6%
일 11
 
4.2%
관 10
 
3.8%
새 9
 
3.4%
문 9
 
3.4%
화 9
 
3.4%
시 7
 
2.7%
Other values (49) 125
47.7%
ASCII
ValueCountFrequency (%)
) 9
50.0%
( 9
50.0%

설립일
Date

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size320.0 B
Minimum1983-05-18 00:00:00
Maximum2019-07-14 00:00:00
2024-03-14T18:31:52.125417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:31:52.502473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

대표자
Text

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T18:31:53.178700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9166667
Min length2

Characters and Unicode

Total characters70
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)54.2%

Sample

1st row이*애
2nd row박*숙
3rd row이*애
4th row이*애
5th row박*숙
ValueCountFrequency (%)
이*애 3
 
12.5%
박*숙 2
 
8.3%
소*숙 2
 
8.3%
최*옥 2
 
8.3%
유*숙 2
 
8.3%
한*숙 1
 
4.2%
문*기 1
 
4.2%
장*주 1
 
4.2%
김*남 1
 
4.2%
이*재 1
 
4.2%
Other values (8) 8
33.3%
2024-03-14T18:31:54.273402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 24
34.3%
숙 7
 
10.0%
이 5
 
7.1%
애 3
 
4.3%
유 3
 
4.3%
최 3
 
4.3%
옥 2
 
2.9%
김 2
 
2.9%
정 2
 
2.9%
소 2
 
2.9%
Other values (16) 17
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46
65.7%
Other Punctuation 24
34.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
숙 7
15.2%
이 5
 
10.9%
애 3
 
6.5%
유 3
 
6.5%
최 3
 
6.5%
옥 2
 
4.3%
김 2
 
4.3%
정 2
 
4.3%
소 2
 
4.3%
박 2
 
4.3%
Other values (15) 15
32.6%
Other Punctuation
ValueCountFrequency (%)
* 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46
65.7%
Common 24
34.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
숙 7
15.2%
이 5
 
10.9%
애 3
 
6.5%
유 3
 
6.5%
최 3
 
6.5%
옥 2
 
4.3%
김 2
 
4.3%
정 2
 
4.3%
소 2
 
4.3%
박 2
 
4.3%
Other values (15) 15
32.6%
Common
ValueCountFrequency (%)
* 24
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46
65.7%
ASCII 24
34.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 24
100.0%
Hangul
ValueCountFrequency (%)
숙 7
15.2%
이 5
 
10.9%
애 3
 
6.5%
유 3
 
6.5%
최 3
 
6.5%
옥 2
 
4.3%
김 2
 
4.3%
정 2
 
4.3%
소 2
 
4.3%
박 2
 
4.3%
Other values (15) 15
32.6%

도로명주소
Text

Distinct17
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T18:31:55.184708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length14.375
Min length10

Characters and Unicode

Total characters345
Distinct characters74
Distinct categories4 ?
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 (%)45.8%

Sample

1st row전주시 덕진구 들사평로 38
2nd row전주시 완산구 장승배기로 213
3rd row전주시 덕진구 들사평로 38
4th row전주시 덕진구 들사평로 38
5th row전주시 완산구 장승배기로 213
ValueCountFrequency (%)
전주시 5
 
6.0%
군산시 3
 
3.6%
들사평로 3
 
3.6%
38 3
 
3.6%
덕진구 3
 
3.6%
완주군 2
 
2.4%
봉동읍 2
 
2.4%
익산시 2
 
2.4%
조곡천1길 2
 
2.4%
정읍시 2
 
2.4%
Other values (45) 57
67.9%
2024-03-14T18:31:56.237563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
60
 
17.4%
1 21
 
6.1%
로 18
 
5.2%
시 16
 
4.6%
3 15
 
4.3%
군 11
 
3.2%
2 11
 
3.2%
읍 10
 
2.9%
산 9
 
2.6%
주 9
 
2.6%
Other values (64) 165
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
60.0%
Decimal Number 76
 
22.0%
Space Separator 60
 
17.4%
Dash Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 18
 
8.7%
시 16
 
7.7%
군 11
 
5.3%
읍 10
 
4.8%
산 9
 
4.3%
주 9
 
4.3%
길 8
 
3.9%
진 6
 
2.9%
창 5
 
2.4%
천 5
 
2.4%
Other values (52) 110
53.1%
Decimal Number
ValueCountFrequency (%)
1 21
27.6%
3 15
19.7%
2 11
14.5%
8 8
 
10.5%
9 4
 
5.3%
4 4
 
5.3%
7 4
 
5.3%
6 4
 
5.3%
5 3
 
3.9%
0 2
 
2.6%
Space Separator
ValueCountFrequency (%)
60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
60.0%
Common 138
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 18
 
8.7%
시 16
 
7.7%
군 11
 
5.3%
읍 10
 
4.8%
산 9
 
4.3%
주 9
 
4.3%
길 8
 
3.9%
진 6
 
2.9%
창 5
 
2.4%
천 5
 
2.4%
Other values (52) 110
53.1%
Common
ValueCountFrequency (%)
60
43.5%
1 21
 
15.2%
3 15
 
10.9%
2 11
 
8.0%
8 8
 
5.8%
9 4
 
2.9%
4 4
 
2.9%
7 4
 
2.9%
6 4
 
2.9%
5 3
 
2.2%
Other values (2) 4
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
60.0%
ASCII 138
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
60
43.5%
1 21
 
15.2%
3 15
 
10.9%
2 11
 
8.0%
8 8
 
5.8%
9 4
 
2.9%
4 4
 
2.9%
7 4
 
2.9%
6 4
 
2.9%
5 3
 
2.2%
Other values (2) 4
 
2.9%
Hangul
ValueCountFrequency (%)
로 18
 
8.7%
시 16
 
7.7%
군 11
 
5.3%
읍 10
 
4.8%
산 9
 
4.3%
주 9
 
4.3%
길 8
 
3.9%
진 6
 
2.9%
창 5
 
2.4%
천 5
 
2.4%
Other values (52) 110
53.1%

전화번호
Text

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size320.0 B
2024-03-14T18:31:56.859031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique12 ?
Unique (%)50.0%

Sample

1st row063-254-3610
2nd row063-232-2346
3rd row063-254-3610
4th row063-254-3620
5th row063-232-2346
ValueCountFrequency (%)
063-254-3610 2
 
8.3%
063-625-4031 2
 
8.3%
063-540-4111 2
 
8.3%
063-468-0055 2
 
8.3%
063-539-5591 2
 
8.3%
063-232-2346 2
 
8.3%
063-261-9372 1
 
4.2%
063-842-9191 1
 
4.2%
063-853-5625 1
 
4.2%
063-442-1203 1
 
4.2%
Other values (8) 8
33.3%
2024-03-14T18:31:57.756888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
16.7%
0 45
15.6%
3 43
14.9%
6 39
13.5%
5 28
9.7%
2 26
9.0%
1 21
7.3%
4 20
6.9%
8 8
 
2.8%
9 8
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
18.8%
3 43
17.9%
6 39
16.2%
5 28
11.7%
2 26
10.8%
1 21
8.8%
4 20
8.3%
8 8
 
3.3%
9 8
 
3.3%
7 2
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
16.7%
0 45
15.6%
3 43
14.9%
6 39
13.5%
5 28
9.7%
2 26
9.0%
1 21
7.3%
4 20
6.9%
8 8
 
2.8%
9 8
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
16.7%
0 45
15.6%
3 43
14.9%
6 39
13.5%
5 28
9.7%
2 26
9.0%
1 21
7.3%
4 20
6.9%
8 8
 
2.8%
9 8
 
2.8%

주요사업
Categorical

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size320.0 B
-직업교육 및 사회교육
12 
-취미교실 및 사회교육
12 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row -직업교육 및 사회교육
2nd row -직업교육 및 사회교육
3rd row -직업교육 및 사회교육
4th row -직업교육 및 사회교육
5th row -직업교육 및 사회교육

Common Values

ValueCountFrequency (%)
-직업교육 및 사회교육 12
50.0%
-취미교실 및 사회교육 12
50.0%

Length

2024-03-14T18:31:57.978409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:31:58.138464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 24
33.3%
사회교육 24
33.3%
직업교육 12
16.7%
취미교실 12
16.7%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
여성청소년과
24 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여성청소년과 24
100.0%

Length

2024-03-14T18:31:58.314303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:31:58.524712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여성청소년과 24
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size152.0 B
True
24 
ValueCountFrequency (%)
True 24
100.0%
2024-03-14T18:31:58.679231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

갱신주기(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
1
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 24
100.0%

Length

2024-03-14T18:31:58.842013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:31:58.998684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
100.0%

Interactions

2024-03-14T18:31:46.840055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:31:59.103951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명기관명설립일대표자도로명주소전화번호주요사업
순번1.0000.9311.0000.7170.8770.9340.9640.434
시군명0.9311.0001.0000.9370.9821.0001.0000.000
기관명1.0001.0001.0001.0001.0001.0001.0001.000
설립일0.7170.9371.0001.0000.8980.9520.9541.000
대표자0.8770.9821.0000.8981.0000.9870.9910.800
도로명주소0.9341.0001.0000.9520.9871.0001.0000.553
전화번호0.9641.0001.0000.9540.9911.0001.0000.478
주요사업0.4340.0001.0001.0000.8000.5530.4781.000
2024-03-14T18:31:59.289332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번주요사업
순번1.0000.236
주요사업0.2361.000

Missing values

2024-03-14T18:31:47.188898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:31:47.692864image/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

순번시군명기관명설립일대표자도로명주소전화번호주요사업자료출처공개여부갱신주기(년)
01전주시전북여성교육문화센터2005-07-28이*애전주시 덕진구 들사평로 38063-254-3610-직업교육 및 사회교육여성청소년과Y1
12전주시전주여성인력개발센터1998-12-11박*숙전주시 완산구 장승배기로 213063-232-2346-직업교육 및 사회교육여성청소년과Y1
23전주시전북새일센터(여성교육문화센터)2009-07-01이*애전주시 덕진구 들사평로 38063-254-3610-직업교육 및 사회교육여성청소년과Y1
34전주시전북광역센터(여성교육문화센터)2010-02-23이*애전주시 덕진구 들사평로 38063-254-3620-직업교육 및 사회교육여성청소년과Y1
45전주시전주새일센터(전주여성인력개발센터)2009-02-01박*숙전주시 완산구 장승배기로 213063-232-2346-직업교육 및 사회교육여성청소년과Y1
56군산시군산여성인력개발센터1996-07-15최*옥군산시 백토로 119063-468-0055-직업교육 및 사회교육여성청소년과Y1
67군산시군산시여성교육장1987-03-11이*연군산시 신금길 18063-442-1203-취미교실 및 사회교육여성청소년과Y1
78군산시군산새일센터(군산여성인력개발센터)2009-02-01최*옥군산시 백토로 119063-468-0055-직업교육 및 사회교육여성청소년과Y1
89익산시익산여성회관1983-05-18윤*익산시 인북로32길 32063-842-9191-취미교실 및 사회교육여성청소년과Y1
910익산시익산새일센터(익산여성새일지원본부)2008-10-01유*숙익산시 익산대로52길11고용복지플러스센터063-853-5625-직업교육 및 사회교육여성청소년과Y1
순번시군명기관명설립일대표자도로명주소전화번호주요사업자료출처공개여부갱신주기(년)
1415김제시김제시여성회관1995-04-21소*숙김제시 동서16길 23063-540-4111-취미교실 및 사회교육여성청소년과Y1
1516김제시김제새일센터(김제시여성문화센터)2013-10-23소*숙김제시 동서16길 23063-540-4111-직업교육 및 사회교육여성청소년과Y1
1617완주군완주가족문화교육원2001-05-02문*기완주군 봉동읍 봉동로 396063-290-2164-취미교실 및 사회교육여성청소년과Y1
1718완주군완주새일센터(완주근로자종합복지관)2015-05-26최*완주군 봉동읍 둔산3로 94063-261-9372-직업교육 및 사회교육여성청소년과Y1
1819진안군진안여성일자리지원센터2010-12-16한*숙진안군 진안읍 진무로 1054-38063-433-2370-취미교실 및 사회교육여성청소년과Y1
1920무주군무주종합복지관일자리센터2005-12-09이*재무주군 무주읍 한풍루로 425063-322-1252-취미교실 및 사회교육여성청소년과Y1
2021장수군여성청소년문화센터2019-07-14김*남장수군 장수읍 신천로 81063-350-2105-취미교실 및 사회교육여성청소년과Y1
2122순창군순창여성회관1998-05-18장*주순창군 순창읍 장류로 407-11063-650-1645-취미교실 및 사회교육여성청소년과Y1
2223고창군고창여성회관1999-02-01황*규고창군 고창읍 월곡공원1길 36063-560-8085-취미교실 및 사회교육여성청소년과Y1
2324부안군노인여성회관1998-10-22유*숙부안군 부안읍 매창로 127063-580-4180-취미교실 및 사회교육여성청소년과Y1