Overview

Dataset statistics

Number of variables7
Number of observations47
Missing cells166
Missing cells (%)50.5%
Duplicate rows1
Duplicate rows (%)2.1%
Total size in memory2.7 KiB
Average record size in memory58.8 B

Variable types

Text6
DateTime1

Alerts

Dataset has 1 (2.1%) duplicate rowsDuplicates
기 관 명 has 34 (72.3%) missing valuesMissing
Unnamed: 1 has 33 (70.2%) missing valuesMissing
Unnamed: 2 has 7 (14.9%) missing valuesMissing
설립일 has 24 (51.1%) missing valuesMissing
대표자 has 24 (51.1%) missing valuesMissing
주 소 has 22 (46.8%) missing valuesMissing
전 화 has 22 (46.8%) missing valuesMissing

Reproduction

Analysis started2024-03-14 02:23:12.458308
Analysis finished2024-03-14 02:23:13.026041
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기 관 명
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing34
Missing (%)72.3%
Memory size508.0 B
2024-03-14T11:23:13.116516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.3846154
Min length1

Characters and Unicode

Total characters18
Distinct characters15
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

Unique13 ?
Unique (%)100.0%

Sample

1st row고
2nd row유
3rd row기
4th row관
5th row별
ValueCountFrequency (%)
고 1
 
7.7%
유 1
 
7.7%
기 1
 
7.7%
관 1
 
7.7%
별 1
 
7.7%
14 1
 
7.7%
새 1
 
7.7%
일 1
 
7.7%
센 1
 
7.7%
터 1
 
7.7%
Other values (3) 3
23.1%
2024-03-14T11:23:13.365165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 2
 
11.1%
관 2
 
11.1%
- 2
 
11.1%
고 1
 
5.6%
유 1
 
5.6%
별 1
 
5.6%
1 1
 
5.6%
4 1
 
5.6%
새 1
 
5.6%
일 1
 
5.6%
Other values (5) 5
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
72.2%
Decimal Number 3
 
16.7%
Dash Punctuation 2
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2
15.4%
관 2
15.4%
고 1
7.7%
유 1
7.7%
별 1
7.7%
새 1
7.7%
일 1
7.7%
센 1
7.7%
터 1
7.7%
지 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
9 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
72.2%
Common 5
 
27.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2
15.4%
관 2
15.4%
고 1
7.7%
유 1
7.7%
별 1
7.7%
새 1
7.7%
일 1
7.7%
센 1
7.7%
터 1
7.7%
지 1
7.7%
Common
ValueCountFrequency (%)
- 2
40.0%
1 1
20.0%
4 1
20.0%
9 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
72.2%
ASCII 5
 
27.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 2
15.4%
관 2
15.4%
고 1
7.7%
유 1
7.7%
별 1
7.7%
새 1
7.7%
일 1
7.7%
센 1
7.7%
터 1
7.7%
지 1
7.7%
ASCII
ValueCountFrequency (%)
- 2
40.0%
1 1
20.0%
4 1
20.0%
9 1
20.0%

Unnamed: 1
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing33
Missing (%)70.2%
Memory size508.0 B
2024-03-14T11:23:13.505564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4
Min length1

Characters and Unicode

Total characters56
Distinct characters29
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

Unique14 ?
Unique (%)100.0%

Sample

1st row전북여성교육문화센터
2nd row여성인력
3rd row개발
4th row센터
5th row-2
ValueCountFrequency (%)
전북여성교육문화센터 1
 
7.1%
여성인력 1
 
7.1%
개발 1
 
7.1%
센터 1
 
7.1%
2 1
 
7.1%
여 1
 
7.1%
성 1
 
7.1%
회 1
 
7.1%
관 1
 
7.1%
11 1
 
7.1%
Other values (4) 4
28.6%
2024-03-14T11:23:13.758955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 5
 
8.9%
여 5
 
8.9%
성 5
 
8.9%
센 5
 
8.9%
- 3
 
5.4%
일 2
 
3.6%
새 2
 
3.6%
1 2
 
3.6%
북 2
 
3.6%
전 2
 
3.6%
Other values (19) 23
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47
83.9%
Decimal Number 4
 
7.1%
Dash Punctuation 3
 
5.4%
Open Punctuation 1
 
1.8%
Close Punctuation 1
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 5
 
10.6%
여 5
 
10.6%
성 5
 
10.6%
센 5
 
10.6%
일 2
 
4.3%
새 2
 
4.3%
북 2
 
4.3%
전 2
 
4.3%
육 2
 
4.3%
교 2
 
4.3%
Other values (13) 15
31.9%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
8 1
25.0%
2 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47
83.9%
Common 9
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 5
 
10.6%
여 5
 
10.6%
성 5
 
10.6%
센 5
 
10.6%
일 2
 
4.3%
새 2
 
4.3%
북 2
 
4.3%
전 2
 
4.3%
육 2
 
4.3%
교 2
 
4.3%
Other values (13) 15
31.9%
Common
ValueCountFrequency (%)
- 3
33.3%
1 2
22.2%
( 1
 
11.1%
8 1
 
11.1%
2 1
 
11.1%
) 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47
83.9%
ASCII 9
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 5
 
10.6%
여 5
 
10.6%
성 5
 
10.6%
센 5
 
10.6%
일 2
 
4.3%
새 2
 
4.3%
북 2
 
4.3%
전 2
 
4.3%
육 2
 
4.3%
교 2
 
4.3%
Other values (13) 15
31.9%
ASCII
ValueCountFrequency (%)
- 3
33.3%
1 2
22.2%
( 1
 
11.1%
8 1
 
11.1%
2 1
 
11.1%
) 1
 
11.1%

Unnamed: 2
Text

MISSING 

Distinct37
Distinct (%)92.5%
Missing7
Missing (%)14.9%
Memory size508.0 B
2024-03-14T11:23:13.932543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.225
Min length2

Characters and Unicode

Total characters249
Distinct characters51
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

Unique36 ?
Unique (%)90.0%

Sample

1st row전 주
2nd row군 산
3rd row군산
4th row(군산시여성교육장)
5th row익산
ValueCountFrequency (%)
여성회관 4
 
9.5%
군산여성인력개발센터 1
 
2.4%
완주새일센터 1
 
2.4%
익산여성새일지원본부 1
 
2.4%
전북새일센터 1
 
2.4%
여성교육문화센터 1
 
2.4%
전주새일센터 1
 
2.4%
전주여성인력개발센터 1
 
2.4%
군산새일센터 1
 
2.4%
익산새일센터 1
 
2.4%
Other values (29) 29
69.0%
2024-03-14T11:23:14.205332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 19
 
7.6%
) 19
 
7.6%
센 16
 
6.4%
여 16
 
6.4%
터 16
 
6.4%
성 16
 
6.4%
일 10
 
4.0%
관 9
 
3.6%
새 9
 
3.6%
산 8
 
3.2%
Other values (41) 111
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 209
83.9%
Open Punctuation 19
 
7.6%
Close Punctuation 19
 
7.6%
Space Separator 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 16
 
7.7%
여 16
 
7.7%
터 16
 
7.7%
성 16
 
7.7%
일 10
 
4.8%
관 9
 
4.3%
새 9
 
4.3%
산 8
 
3.8%
주 7
 
3.3%
문 6
 
2.9%
Other values (38) 96
45.9%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 209
83.9%
Common 40
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 16
 
7.7%
여 16
 
7.7%
터 16
 
7.7%
성 16
 
7.7%
일 10
 
4.8%
관 9
 
4.3%
새 9
 
4.3%
산 8
 
3.8%
주 7
 
3.3%
문 6
 
2.9%
Other values (38) 96
45.9%
Common
ValueCountFrequency (%)
( 19
47.5%
) 19
47.5%
2
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 209
83.9%
ASCII 40
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 19
47.5%
) 19
47.5%
2
 
5.0%
Hangul
ValueCountFrequency (%)
센 16
 
7.7%
여 16
 
7.7%
터 16
 
7.7%
성 16
 
7.7%
일 10
 
4.8%
관 9
 
4.3%
새 9
 
4.3%
산 8
 
3.8%
주 7
 
3.3%
문 6
 
2.9%
Other values (38) 96
45.9%

설립일
Date

MISSING 

Distinct20
Distinct (%)87.0%
Missing24
Missing (%)51.1%
Memory size508.0 B
Minimum1983-05-18 00:00:00
Maximum2015-05-26 00:00:00
2024-03-14T11:23:14.320931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:23:14.519260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)

대표자
Text

MISSING 

Distinct18
Distinct (%)78.3%
Missing24
Missing (%)51.1%
Memory size508.0 B
2024-03-14T11:23:14.685130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters69
Distinct characters42
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

Unique14 ?
Unique (%)60.9%

Sample

1st row신수미
2nd row임경진
3rd row백지연
4th row차정희
5th row김인숙
ValueCountFrequency (%)
신수미 3
 
13.0%
백지연 2
 
8.7%
양동수 2
 
8.7%
임경진 2
 
8.7%
김은희 1
 
4.3%
이선효 1
 
4.3%
양해완 1
 
4.3%
하두수 1
 
4.3%
최경옥 1
 
4.3%
오영택 1
 
4.3%
Other values (8) 8
34.8%
2024-03-14T11:23:14.944583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 6
 
8.7%
이 4
 
5.8%
신 3
 
4.3%
미 3
 
4.3%
임 3
 
4.3%
경 3
 
4.3%
양 3
 
4.3%
김 2
 
2.9%
희 2
 
2.9%
정 2
 
2.9%
Other values (32) 38
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 6
 
8.7%
이 4
 
5.8%
신 3
 
4.3%
미 3
 
4.3%
임 3
 
4.3%
경 3
 
4.3%
양 3
 
4.3%
김 2
 
2.9%
희 2
 
2.9%
정 2
 
2.9%
Other values (32) 38
55.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 6
 
8.7%
이 4
 
5.8%
신 3
 
4.3%
미 3
 
4.3%
임 3
 
4.3%
경 3
 
4.3%
양 3
 
4.3%
김 2
 
2.9%
희 2
 
2.9%
정 2
 
2.9%
Other values (32) 38
55.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 6
 
8.7%
이 4
 
5.8%
신 3
 
4.3%
미 3
 
4.3%
임 3
 
4.3%
경 3
 
4.3%
양 3
 
4.3%
김 2
 
2.9%
희 2
 
2.9%
정 2
 
2.9%
Other values (32) 38
55.1%

주 소
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing22
Missing (%)46.8%
Memory size508.0 B
2024-03-14T11:23:15.188774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length12.12
Min length7

Characters and Unicode

Total characters303
Distinct characters94
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)92.0%

Sample

1st row전주시 덕진구 들사평로 38
2nd row전주시 완산구 장승배기로 213
3rd row군산시 백토로 119
4th row(대주빌딩 2층)
5th row군산시 신금길 18
ValueCountFrequency (%)
전북여성교육문화센터 2
 
3.0%
전주시 2
 
3.0%
군산시 2
 
3.0%
완주군 2
 
3.0%
순창군 1
 
1.5%
396 1
 
1.5%
순창읍 1
 
1.5%
장류로 1
 
1.5%
매창로 1
 
1.5%
봉동로 1
 
1.5%
Other values (52) 52
78.8%
2024-03-14T11:23:15.490221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
13.5%
1 15
 
5.0%
시 11
 
3.6%
로 11
 
3.6%
군 10
 
3.3%
읍 8
 
2.6%
성 8
 
2.6%
산 8
 
2.6%
주 8
 
2.6%
여 7
 
2.3%
Other values (84) 176
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
69.3%
Decimal Number 48
 
15.8%
Space Separator 41
 
13.5%
Dash Punctuation 2
 
0.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 11
 
5.2%
로 11
 
5.2%
군 10
 
4.8%
읍 8
 
3.8%
성 8
 
3.8%
산 8
 
3.8%
주 8
 
3.8%
여 7
 
3.3%
전 5
 
2.4%
창 5
 
2.4%
Other values (70) 129
61.4%
Decimal Number
ValueCountFrequency (%)
1 15
31.2%
3 7
14.6%
2 6
 
12.5%
4 4
 
8.3%
8 4
 
8.3%
7 3
 
6.2%
5 3
 
6.2%
0 2
 
4.2%
6 2
 
4.2%
9 2
 
4.2%
Space Separator
ValueCountFrequency (%)
41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
69.3%
Common 93
30.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 11
 
5.2%
로 11
 
5.2%
군 10
 
4.8%
읍 8
 
3.8%
성 8
 
3.8%
산 8
 
3.8%
주 8
 
3.8%
여 7
 
3.3%
전 5
 
2.4%
창 5
 
2.4%
Other values (70) 129
61.4%
Common
ValueCountFrequency (%)
41
44.1%
1 15
 
16.1%
3 7
 
7.5%
2 6
 
6.5%
4 4
 
4.3%
8 4
 
4.3%
7 3
 
3.2%
5 3
 
3.2%
0 2
 
2.2%
6 2
 
2.2%
Other values (4) 6
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
69.3%
ASCII 93
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
44.1%
1 15
 
16.1%
3 7
 
7.5%
2 6
 
6.5%
4 4
 
4.3%
8 4
 
4.3%
7 3
 
3.2%
5 3
 
3.2%
0 2
 
2.2%
6 2
 
2.2%
Other values (4) 6
 
6.5%
Hangul
ValueCountFrequency (%)
시 11
 
5.2%
로 11
 
5.2%
군 10
 
4.8%
읍 8
 
3.8%
성 8
 
3.8%
산 8
 
3.8%
주 8
 
3.8%
여 7
 
3.3%
전 5
 
2.4%
창 5
 
2.4%
Other values (70) 129
61.4%

전 화
Text

MISSING 

Distinct20
Distinct (%)80.0%
Missing22
Missing (%)46.8%
Memory size508.0 B
2024-03-14T11:23:15.638346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters200
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

Unique15 ?
Unique (%)60.0%

Sample

1st row254-3610
2nd row254-3620
3rd row232-2346
4th row468-0055
5th row454-7860
ValueCountFrequency (%)
468-0055 2
 
8.0%
625-4031 2
 
8.0%
254-3620 2
 
8.0%
254-3610 2
 
8.0%
840-6568 2
 
8.0%
580-4180 1
 
4.0%
322-1191 1
 
4.0%
540-6901 1
 
4.0%
539-5597 1
 
4.0%
232-2352 1
 
4.0%
Other values (10) 10
40.0%
2024-03-14T11:23:15.895136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 25
12.5%
2 25
12.5%
0 24
12.0%
5 24
12.0%
4 20
10.0%
6 20
10.0%
3 20
10.0%
1 18
9.0%
8 12
6.0%
9 7
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 175
87.5%
Dash Punctuation 25
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25
14.3%
0 24
13.7%
5 24
13.7%
4 20
11.4%
6 20
11.4%
3 20
11.4%
1 18
10.3%
8 12
6.9%
9 7
 
4.0%
7 5
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 200
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 25
12.5%
2 25
12.5%
0 24
12.0%
5 24
12.0%
4 20
10.0%
6 20
10.0%
3 20
10.0%
1 18
9.0%
8 12
6.0%
9 7
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 25
12.5%
2 25
12.5%
0 24
12.0%
5 24
12.0%
4 20
10.0%
6 20
10.0%
3 20
10.0%
1 18
9.0%
8 12
6.0%
9 7
 
3.5%

Correlations

2024-03-14T11:23:15.971869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기 관 명Unnamed: 1Unnamed: 2설립일대표자주 소전 화
기 관 명1.0001.0001.0001.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.0001.0001.000
설립일1.0001.0001.0001.0000.9410.9750.923
대표자1.0001.0001.0000.9411.0001.0000.950
주 소1.0001.0001.0000.9751.0001.0000.964
전 화1.0001.0001.0000.9230.9500.9641.000

Missing values

2024-03-14T11:23:12.757819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:23:12.848962image/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.
2024-03-14T11:23:12.946466image/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

기 관 명Unnamed: 1Unnamed: 2설립일대표자주 소전 화
0고전북여성교육문화센터<NA>2005.07.28신수미전주시 덕진구 들사평로 38254-3610
1유<NA><NA><NA><NA><NA>254-3620
2기여성인력전 주1998.12.11임경진전주시 완산구 장승배기로 213232-2346
3관개발<NA><NA><NA><NA><NA>
4별센터<NA><NA><NA><NA><NA>
5-14-2군 산1996.7.15백지연군산시 백토로 119468-0055
6<NA><NA><NA><NA><NA>(대주빌딩 2층)<NA>
7<NA>여군산1987.03.11차정희군산시 신금길 18454-7860
8<NA>성(군산시여성교육장)<NA><NA><NA><NA>
9<NA>회익산1983.05.18김인숙익산시 익산대로 52길 11840-6568
기 관 명Unnamed: 1Unnamed: 2설립일대표자주 소전 화
37<NA><NA>정읍새일센터2009.07.01양동수정읍시여성회관539-5597
38<NA><NA>(정읍시여성문화관)<NA><NA><NA><NA>
39<NA><NA>남원새일센터2009.07.01하두수남원시여성회관625-4031
40<NA><NA>(남원시여성문화센터)<NA><NA><NA><NA>
41<NA><NA>김제새일센터2013.10.23양해완김제시여성회관540-6901
42<NA><NA>(김제시여성문화센터)<NA><NA><NA><NA>
43<NA><NA>완주새일센터2015.05.26이계임완주군 근로자종합복지관261-9897
44<NA><NA>(완주근로자종합복지관)<NA><NA><NA><NA>
45<NA>전북광역새일센터<NA>2010.02.23신수미전북여성교육문화센터254-3620
46<NA>(여성교육문화센터)<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

기 관 명Unnamed: 1Unnamed: 2설립일대표자주 소전 화# duplicates
0<NA><NA>(여성회관)<NA><NA><NA><NA>3