Overview

Dataset statistics

Number of variables10
Number of observations35
Missing cells190
Missing cells (%)54.3%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory2.9 KiB
Average record size in memory83.8 B

Variable types

Text5
Unsupported5

Dataset

Description한부모시설현황17년11월기준
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201771

Alerts

Dataset has 1 (2.9%) duplicate rowsDuplicates
한부모가족복지시설 현황 has 10 (28.6%) missing valuesMissing
Unnamed: 1 has 18 (51.4%) missing valuesMissing
Unnamed: 2 has 19 (54.3%) missing valuesMissing
Unnamed: 3 has 19 (54.3%) missing valuesMissing
Unnamed: 4 has 18 (51.4%) missing valuesMissing
Unnamed: 5 has 25 (71.4%) missing valuesMissing
Unnamed: 6 has 26 (74.3%) missing valuesMissing
Unnamed: 7 has 22 (62.9%) missing valuesMissing
Unnamed: 8 has 13 (37.1%) missing valuesMissing
Unnamed: 9 has 20 (57.1%) missing valuesMissing
Unnamed: 5 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
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:35:33.455690
Analysis finished2024-03-14 01:35:34.073109
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

한부모가족복지시설 현황
Text

MISSING 

Distinct20
Distinct (%)80.0%
Missing10
Missing (%)28.6%
Memory size412.0 B
2024-03-14T10:35:34.186966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length30
Mean length8.64
Min length3

Characters and Unicode

Total characters216
Distinct characters57
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)64.0%

Sample

1st row 법인시설 7개소
2nd row- 시설별 : 모자가족시설(기본) 4, 모자가족시설(자립) 1, 일시지원시설 1, 미혼모자시설(공동) 1
3rd row- 지역별 : 전주 3, 군산 2, 익산 1, 완주 1
4th row(기준 : ‘17. 11월 말)
5th row구 분
ValueCountFrequency (%)
5
 
9.1%
1 5
 
9.1%
복지시설 3
 
5.5%
모자가족 2
 
3.6%
보호3년 2
 
3.6%
연장2년 2
 
3.6%
계 1
 
1.8%
구 1
 
1.8%
분 1
 
1.8%
시 1
 
1.8%
Other values (32) 32
58.2%
2024-03-14T10:35:34.465919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
13.9%
시 13
 
6.0%
설 11
 
5.1%
( 11
 
5.1%
) 11
 
5.1%
1 9
 
4.2%
자 9
 
4.2%
지 7
 
3.2%
모 7
 
3.2%
, 6
 
2.8%
Other values (47) 102
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 129
59.7%
Space Separator 30
 
13.9%
Decimal Number 21
 
9.7%
Open Punctuation 11
 
5.1%
Close Punctuation 11
 
5.1%
Other Punctuation 10
 
4.6%
Dash Punctuation 2
 
0.9%
Initial Punctuation 1
 
0.5%
Private Use 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 13
 
10.1%
설 11
 
8.5%
자 9
 
7.0%
지 7
 
5.4%
모 7
 
5.4%
년 6
 
4.7%
가 5
 
3.9%
족 5
 
3.9%
보 4
 
3.1%
복 4
 
3.1%
Other values (32) 58
45.0%
Decimal Number
ValueCountFrequency (%)
1 9
42.9%
2 4
19.0%
3 3
 
14.3%
7 2
 
9.5%
6 2
 
9.5%
4 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 6
60.0%
: 3
30.0%
. 1
 
10.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Private Use
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 129
59.7%
Common 86
39.8%
Unknown 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 13
 
10.1%
설 11
 
8.5%
자 9
 
7.0%
지 7
 
5.4%
모 7
 
5.4%
년 6
 
4.7%
가 5
 
3.9%
족 5
 
3.9%
보 4
 
3.1%
복 4
 
3.1%
Other values (32) 58
45.0%
Common
ValueCountFrequency (%)
30
34.9%
( 11
 
12.8%
) 11
 
12.8%
1 9
 
10.5%
, 6
 
7.0%
2 4
 
4.7%
3 3
 
3.5%
: 3
 
3.5%
- 2
 
2.3%
7 2
 
2.3%
Other values (4) 5
 
5.8%
Unknown
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 129
59.7%
ASCII 85
39.4%
Punctuation 1
 
0.5%
PUA 1
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
35.3%
( 11
 
12.9%
) 11
 
12.9%
1 9
 
10.6%
, 6
 
7.1%
2 4
 
4.7%
3 3
 
3.5%
: 3
 
3.5%
- 2
 
2.4%
7 2
 
2.4%
Other values (3) 4
 
4.7%
Hangul
ValueCountFrequency (%)
시 13
 
10.1%
설 11
 
8.5%
자 9
 
7.0%
지 7
 
5.4%
모 7
 
5.4%
년 6
 
4.7%
가 5
 
3.9%
족 5
 
3.9%
보 4
 
3.1%
복 4
 
3.1%
Other values (32) 58
45.0%
Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
PUA
ValueCountFrequency (%)
1
100.0%

Unnamed: 1
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing18
Missing (%)51.4%
Memory size412.0 B
2024-03-14T10:35:34.607935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.7647059
Min length2

Characters and Unicode

Total characters81
Distinct characters34
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

Unique15 ?
Unique (%)88.2%

Sample

1st row원광모자원
2nd row(한 울 안)
3rd row신광모자원
4th row(인성재단)
5th row성애모자원
ValueCountFrequency (%)
인성재단 2
 
10.5%
이산원 1
 
5.3%
신광모자 1
 
5.3%
동방사회 1
 
5.3%
기쁨누리 1
 
5.3%
삼성원 1
 
5.3%
쉼터 1
 
5.3%
삼성여성의 1
 
5.3%
자립원 1
 
5.3%
원광모자원 1
 
5.3%
Other values (8) 8
42.1%
2024-03-14T10:35:34.873307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 9
 
11.1%
( 7
 
8.6%
성 7
 
8.6%
) 7
 
8.6%
자 6
 
7.4%
모 5
 
6.2%
광 3
 
3.7%
신 2
 
2.5%
회 2
 
2.5%
삼 2
 
2.5%
Other values (24) 31
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65
80.2%
Open Punctuation 7
 
8.6%
Close Punctuation 7
 
8.6%
Space Separator 2
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 9
 
13.8%
성 7
 
10.8%
자 6
 
9.2%
모 5
 
7.7%
광 3
 
4.6%
신 2
 
3.1%
회 2
 
3.1%
삼 2
 
3.1%
인 2
 
3.1%
애 2
 
3.1%
Other values (21) 25
38.5%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65
80.2%
Common 16
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 9
 
13.8%
성 7
 
10.8%
자 6
 
9.2%
모 5
 
7.7%
광 3
 
4.6%
신 2
 
3.1%
회 2
 
3.1%
삼 2
 
3.1%
인 2
 
3.1%
애 2
 
3.1%
Other values (21) 25
38.5%
Common
ValueCountFrequency (%)
( 7
43.8%
) 7
43.8%
2
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65
80.2%
ASCII 16
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 9
 
13.8%
성 7
 
10.8%
자 6
 
9.2%
모 5
 
7.7%
광 3
 
4.6%
신 2
 
3.1%
회 2
 
3.1%
삼 2
 
3.1%
인 2
 
3.1%
애 2
 
3.1%
Other values (21) 25
38.5%
ASCII
ValueCountFrequency (%)
( 7
43.8%
) 7
43.8%
2
 
12.5%

Unnamed: 2
Text

MISSING 

Distinct14
Distinct (%)87.5%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-03-14T10:35:35.050973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8.5
Mean length5.4375
Min length3

Characters and Unicode

Total characters87
Distinct characters35
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

Unique12 ?
Unique (%)75.0%

Sample

1st row법 인
2nd row대표자/허가일
3rd row김정한
4th row01.9.4.
5th row김미숙
ValueCountFrequency (%)
김미숙 2
 
11.8%
76.5.20 2
 
11.8%
법 1
 
5.9%
인 1
 
5.9%
대표자/허가일 1
 
5.9%
김정한 1
 
5.9%
01.9.4 1
 
5.9%
최성근 1
 
5.9%
64.10.6 1
 
5.9%
오세현 1
 
5.9%
Other values (5) 5
29.4%
2024-03-14T10:35:35.354329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 21
24.1%
2 6
 
6.9%
김 5
 
5.7%
1 5
 
5.7%
7 5
 
5.7%
6 4
 
4.6%
5 4
 
4.6%
0 4
 
4.6%
4 2
 
2.3%
정 2
 
2.3%
Other values (25) 29
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
40.2%
Other Letter 29
33.3%
Other Punctuation 22
25.3%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 5
17.2%
정 2
 
6.9%
미 2
 
6.9%
숙 2
 
6.9%
옥 1
 
3.4%
현 1
 
3.4%
세 1
 
3.4%
오 1
 
3.4%
근 1
 
3.4%
도 1
 
3.4%
Other values (12) 12
41.4%
Decimal Number
ValueCountFrequency (%)
2 6
17.1%
1 5
14.3%
7 5
14.3%
6 4
11.4%
5 4
11.4%
0 4
11.4%
4 2
 
5.7%
8 2
 
5.7%
9 2
 
5.7%
3 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 21
95.5%
/ 1
 
4.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
66.7%
Hangul 29
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 5
17.2%
정 2
 
6.9%
미 2
 
6.9%
숙 2
 
6.9%
옥 1
 
3.4%
현 1
 
3.4%
세 1
 
3.4%
오 1
 
3.4%
근 1
 
3.4%
도 1
 
3.4%
Other values (12) 12
41.4%
Common
ValueCountFrequency (%)
. 21
36.2%
2 6
 
10.3%
1 5
 
8.6%
7 5
 
8.6%
6 4
 
6.9%
5 4
 
6.9%
0 4
 
6.9%
4 2
 
3.4%
8 2
 
3.4%
9 2
 
3.4%
Other values (3) 3
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
66.7%
Hangul 29
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 21
36.2%
2 6
 
10.3%
1 5
 
8.6%
7 5
 
8.6%
6 4
 
6.9%
5 4
 
6.9%
0 4
 
6.9%
4 2
 
3.4%
8 2
 
3.4%
9 2
 
3.4%
Other values (3) 3
 
5.2%
Hangul
ValueCountFrequency (%)
김 5
17.2%
정 2
 
6.9%
미 2
 
6.9%
숙 2
 
6.9%
옥 1
 
3.4%
현 1
 
3.4%
세 1
 
3.4%
오 1
 
3.4%
근 1
 
3.4%
도 1
 
3.4%
Other values (12) 12
41.4%

Unnamed: 3
Text

MISSING 

Distinct15
Distinct (%)93.8%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-03-14T10:35:35.541858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8.5
Mean length5.4375
Min length3

Characters and Unicode

Total characters87
Distinct characters33
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

Unique14 ?
Unique (%)87.5%

Sample

1st row시 설
2nd row시설장/허가일
3rd row조영례
4th row93.1.30.
5th row정영순
ValueCountFrequency (%)
정영순 2
 
11.8%
시 1
 
5.9%
설 1
 
5.9%
시설장/허가일 1
 
5.9%
조영례 1
 
5.9%
93.1.30 1
 
5.9%
69.2.26 1
 
5.9%
최미화 1
 
5.9%
88.11.25 1
 
5.9%
오세현 1
 
5.9%
Other values (6) 6
35.3%
2024-03-14T10:35:35.919341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 21
24.1%
1 6
 
6.9%
9 6
 
6.9%
2 5
 
5.7%
6 4
 
4.6%
0 4
 
4.6%
순 3
 
3.4%
7 3
 
3.4%
영 3
 
3.4%
3 3
 
3.4%
Other values (23) 29
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
40.2%
Other Letter 29
33.3%
Other Punctuation 22
25.3%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
순 3
 
10.3%
영 3
 
10.3%
미 2
 
6.9%
정 2
 
6.9%
설 2
 
6.9%
시 2
 
6.9%
명 1
 
3.4%
김 1
 
3.4%
송 1
 
3.4%
현 1
 
3.4%
Other values (11) 11
37.9%
Decimal Number
ValueCountFrequency (%)
1 6
17.1%
9 6
17.1%
2 5
14.3%
6 4
11.4%
0 4
11.4%
7 3
8.6%
3 3
8.6%
5 2
 
5.7%
8 2
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 21
95.5%
/ 1
 
4.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
66.7%
Hangul 29
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
순 3
 
10.3%
영 3
 
10.3%
미 2
 
6.9%
정 2
 
6.9%
설 2
 
6.9%
시 2
 
6.9%
명 1
 
3.4%
김 1
 
3.4%
송 1
 
3.4%
현 1
 
3.4%
Other values (11) 11
37.9%
Common
ValueCountFrequency (%)
. 21
36.2%
1 6
 
10.3%
9 6
 
10.3%
2 5
 
8.6%
6 4
 
6.9%
0 4
 
6.9%
7 3
 
5.2%
3 3
 
5.2%
5 2
 
3.4%
8 2
 
3.4%
Other values (2) 2
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
66.7%
Hangul 29
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 21
36.2%
1 6
 
10.3%
9 6
 
10.3%
2 5
 
8.6%
6 4
 
6.9%
0 4
 
6.9%
7 3
 
5.2%
3 3
 
5.2%
5 2
 
3.4%
8 2
 
3.4%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
순 3
 
10.3%
영 3
 
10.3%
미 2
 
6.9%
정 2
 
6.9%
설 2
 
6.9%
시 2
 
6.9%
명 1
 
3.4%
김 1
 
3.4%
송 1
 
3.4%
현 1
 
3.4%
Other values (11) 11
37.9%

Unnamed: 4
Text

MISSING 

Distinct13
Distinct (%)76.5%
Missing18
Missing (%)51.4%
Memory size412.0 B
2024-03-14T10:35:36.075104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.6470588
Min length3

Characters and Unicode

Total characters62
Distinct characters14
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

Unique9 ?
Unique (%)52.9%

Sample

1st row정 원
2nd row130세대
3rd row489명
4th row20세대
5th row80명
ValueCountFrequency (%)
20세대 2
11.1%
80명 2
11.1%
24세대 2
11.1%
100명 2
11.1%
정 1
 
5.6%
원 1
 
5.6%
130세대 1
 
5.6%
489명 1
 
5.6%
22세대 1
 
5.6%
88명 1
 
5.6%
Other values (4) 4
22.2%
2024-03-14T10:35:36.628427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
16.1%
세 8
12.9%
대 8
12.9%
명 8
12.9%
2 6
9.7%
1 6
9.7%
8 5
8.1%
4 3
 
4.8%
3 2
 
3.2%
5 2
 
3.2%
Other values (4) 4
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35
56.5%
Other Letter 26
41.9%
Space Separator 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
28.6%
2 6
17.1%
1 6
17.1%
8 5
14.3%
4 3
 
8.6%
3 2
 
5.7%
5 2
 
5.7%
9 1
 
2.9%
Other Letter
ValueCountFrequency (%)
세 8
30.8%
대 8
30.8%
명 8
30.8%
정 1
 
3.8%
원 1
 
3.8%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36
58.1%
Hangul 26
41.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
27.8%
2 6
16.7%
1 6
16.7%
8 5
13.9%
4 3
 
8.3%
3 2
 
5.6%
5 2
 
5.6%
1
 
2.8%
9 1
 
2.8%
Hangul
ValueCountFrequency (%)
세 8
30.8%
대 8
30.8%
명 8
30.8%
정 1
 
3.8%
원 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
58.1%
Hangul 26
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
27.8%
2 6
16.7%
1 6
16.7%
8 5
13.9%
4 3
 
8.3%
3 2
 
5.6%
5 2
 
5.6%
1
 
2.8%
9 1
 
2.8%
Hangul
ValueCountFrequency (%)
세 8
30.8%
대 8
30.8%
명 8
30.8%
정 1
 
3.8%
원 1
 
3.8%

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25
Missing (%)71.4%
Memory size412.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing26
Missing (%)74.3%
Memory size412.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing22
Missing (%)62.9%
Memory size412.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing13
Missing (%)37.1%
Memory size412.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing20
Missing (%)57.1%
Memory size412.0 B

Correlations

2024-03-14T10:35:36.701077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
한부모가족복지시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4
한부모가족복지시설 현황1.0000.8190.8080.8780.938
Unnamed: 10.8191.0001.0001.0001.000
Unnamed: 20.8081.0001.0001.0000.969
Unnamed: 30.8781.0001.0001.0001.000
Unnamed: 40.9381.0000.9691.0001.000

Missing values

2024-03-14T10:35:33.721483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:35:33.836186image/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.
2024-03-14T10:35:33.962466image/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

한부모가족복지시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
0<NA><NA><NA><NA><NA>NaNNaNNaNNaNNaN
1 법인시설 7개소<NA><NA><NA><NA>NaNNaNNaNNaNNaN
2- 시설별 : 모자가족시설(기본) 4, 모자가족시설(자립) 1, 일시지원시설 1, 미혼모자시설(공동) 1<NA><NA><NA><NA>NaNNaNNaNNaNNaN
3- 지역별 : 전주 3, 군산 2, 익산 1, 완주 1<NA><NA><NA><NA>NaNNaNNaNNaNNaN
4(기준 : ‘17. 11월 말)<NA><NA><NA><NA>NaNNaNNaNNaNNaN
5구 분<NA>법 인시 설정 원현 원NaN종주 소전 화
6<NA><NA><NA><NA><NA>NaNNaN사NaNNaN
7시 설 명<NA>대표자/허가일시설장/허가일<NA>세대인원자NaNNaN
8합 계<NA><NA><NA>130세대8220330명NaNNaN
9<NA><NA><NA><NA>489명NaNNaNNaNNaNNaN
한부모가족복지시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9
25보호3년<NA><NA><NA><NA>NaNNaNNaNNaNNaN
26(연장2년)<NA><NA><NA><NA>NaNNaNNaNNaNNaN
27일시지원삼성여성의김옥정송미순15세대1013654880221-
28복지시설쉼터77.1.28.96.9.10.31명NaNNaNNaN전주시 완산구 만지길 20-177004
29보호6월(삼성원)<NA><NA><NA>NaNNaNNaN(팩스221-7012)NaN
30(연장6월)<NA><NA><NA><NA>NaNNaNNaNNaNNaN
31미혼모자가족복지시설기쁨누리김도종김명희5세대49255028241-
32(미혼모자공동)(동방사회75.8.13.15.6.30.10명NaNNaNNaN전주시 덕진구 인교6길 13-133381
33보호2년복지회)<NA><NA><NA>NaNNaNNaN(팩스284-3341)NaN
34(연장1년)<NA><NA><NA><NA>NaNNaNNaNNaNNaN

Duplicate rows

Most frequently occurring

한부모가족복지시설 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4# duplicates
0<NA><NA><NA><NA><NA>5