Overview

Dataset statistics

Number of variables11
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory96.1 B

Variable types

Numeric1
Text6
Categorical3
Boolean1

Dataset

Description전북특별자치도 시군별 노인돌봄센터 현황(시군명, 시설명, 운영주체, 시설장, 도로명주소, 자료출처, 공개여부, 작성일, 갱신주기 등)
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055609/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기(년) has constant value ""Constant
순번 has unique valuesUnique
시설명 has unique valuesUnique
도로명주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 15:29:32.176946
Analysis finished2024-03-14 15:29:33.636791
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size317.0 B
2024-03-15T00:29:33.738798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-03-15T00:29:33.960620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

시군명
Text

Distinct13
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:34.485206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters63
Distinct characters23
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

Unique8 ?
Unique (%)38.1%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row군산시
ValueCountFrequency (%)
전주시 4
19.0%
익산시 3
14.3%
군산시 2
9.5%
남원시 2
9.5%
김제시 2
9.5%
정읍시 1
 
4.8%
완주군 1
 
4.8%
진안군 1
 
4.8%
장수군 1
 
4.8%
임실군 1
 
4.8%
Other values (3) 3
14.3%
2024-03-15T00:29:35.172683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 14
22.2%
군 9
14.3%
산 5
 
7.9%
주 5
 
7.9%
전 4
 
6.3%
익 3
 
4.8%
남 2
 
3.2%
원 2
 
3.2%
김 2
 
3.2%
제 2
 
3.2%
Other values (13) 15
23.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 14
22.2%
군 9
14.3%
산 5
 
7.9%
주 5
 
7.9%
전 4
 
6.3%
익 3
 
4.8%
남 2
 
3.2%
원 2
 
3.2%
김 2
 
3.2%
제 2
 
3.2%
Other values (13) 15
23.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 14
22.2%
군 9
14.3%
산 5
 
7.9%
주 5
 
7.9%
전 4
 
6.3%
익 3
 
4.8%
남 2
 
3.2%
원 2
 
3.2%
김 2
 
3.2%
제 2
 
3.2%
Other values (13) 15
23.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 14
22.2%
군 9
14.3%
산 5
 
7.9%
주 5
 
7.9%
전 4
 
6.3%
익 3
 
4.8%
남 2
 
3.2%
원 2
 
3.2%
김 2
 
3.2%
제 2
 
3.2%
Other values (13) 15
23.8%

시설명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:35.890853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.1904762
Min length8

Characters and Unicode

Total characters193
Distinct characters62
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

Unique21 ?
Unique (%)100.0%

Sample

1st row샬롬노인복지센터
2nd row안골노인복지센터
3rd row늘푸른집주간보호센터
4th row이양재노인종합센터
5th row군산노인복지센터
ValueCountFrequency (%)
샬롬노인복지센터 1
 
4.8%
살림노인복지센터 1
 
4.8%
고창군노인복지센터 1
 
4.8%
순창은빛노인복지센터 1
 
4.8%
섬김노인복지센터 1
 
4.8%
밀알노인복지센터 1
 
4.8%
밀알재가노인복지센터 1
 
4.8%
용진노인복지센터 1
 
4.8%
김제노인전문요양원주간센터 1
 
4.8%
김제노인복지센터 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T00:29:37.069854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
노 20
 
10.4%
인 20
 
10.4%
센 20
 
10.4%
터 20
 
10.4%
지 18
 
9.3%
복 17
 
8.8%
김 4
 
2.1%
양 3
 
1.6%
산 3
 
1.6%
군 3
 
1.6%
Other values (52) 65
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
노 20
 
10.4%
인 20
 
10.4%
센 20
 
10.4%
터 20
 
10.4%
지 18
 
9.3%
복 17
 
8.8%
김 4
 
2.1%
양 3
 
1.6%
산 3
 
1.6%
군 3
 
1.6%
Other values (52) 65
33.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
노 20
 
10.4%
인 20
 
10.4%
센 20
 
10.4%
터 20
 
10.4%
지 18
 
9.3%
복 17
 
8.8%
김 4
 
2.1%
양 3
 
1.6%
산 3
 
1.6%
군 3
 
1.6%
Other values (52) 65
33.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
노 20
 
10.4%
인 20
 
10.4%
센 20
 
10.4%
터 20
 
10.4%
지 18
 
9.3%
복 17
 
8.8%
김 4
 
2.1%
양 3
 
1.6%
산 3
 
1.6%
군 3
 
1.6%
Other values (52) 65
33.7%

운영주체
Text

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:37.767583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length8.5238095
Min length2

Characters and Unicode

Total characters179
Distinct characters46
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

Unique11 ?
Unique (%)52.4%

Sample

1st row사복)한기장복지재단
2nd row사복)전주중부복지재단
3rd row사복)전주중앙복지원
4th row사복)혜산
5th row사복)삼동회
ValueCountFrequency (%)
개인 5
23.8%
사복)한기장복지재단 3
14.3%
재단)대한성공회유지재단 2
 
9.5%
사복)전주중부복지재단 1
 
4.8%
사복)전주중앙복지원 1
 
4.8%
사복)혜산 1
 
4.8%
사복)삼동회 1
 
4.8%
사복)임마누엘복지재단 1
 
4.8%
사복)전주카돌릭사회복지회 1
 
4.8%
사복)한국장로교복지재단 1
 
4.8%
Other values (4) 4
19.0%
2024-03-15T00:29:38.886281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 22
 
12.3%
) 16
 
8.9%
재 16
 
8.9%
단 16
 
8.9%
사 14
 
7.8%
지 14
 
7.8%
한 8
 
4.5%
회 6
 
3.4%
개 5
 
2.8%
인 5
 
2.8%
Other values (36) 57
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
91.1%
Close Punctuation 16
 
8.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 22
13.5%
재 16
 
9.8%
단 16
 
9.8%
사 14
 
8.6%
지 14
 
8.6%
한 8
 
4.9%
회 6
 
3.7%
개 5
 
3.1%
인 5
 
3.1%
장 5
 
3.1%
Other values (35) 52
31.9%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
91.1%
Common 16
 
8.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 22
13.5%
재 16
 
9.8%
단 16
 
9.8%
사 14
 
8.6%
지 14
 
8.6%
한 8
 
4.9%
회 6
 
3.7%
개 5
 
3.1%
인 5
 
3.1%
장 5
 
3.1%
Other values (35) 52
31.9%
Common
ValueCountFrequency (%)
) 16
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
91.1%
ASCII 16
 
8.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 22
13.5%
재 16
 
9.8%
단 16
 
9.8%
사 14
 
8.6%
지 14
 
8.6%
한 8
 
4.9%
회 6
 
3.7%
개 5
 
3.1%
인 5
 
3.1%
장 5
 
3.1%
Other values (35) 52
31.9%
ASCII
ValueCountFrequency (%)
) 16
100.0%

시설장
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:39.567396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.952381
Min length2

Characters and Unicode

Total characters62
Distinct characters30
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

Unique19 ?
Unique (%)90.5%

Sample

1st row김*희
2nd row이*숙
3rd row나*
4th row장*석
5th row성*규
ValueCountFrequency (%)
이*숙 2
 
9.5%
김*희 1
 
4.8%
손*석 1
 
4.8%
윤*천 1
 
4.8%
김*순 1
 
4.8%
고*영 1
 
4.8%
송*순 1
 
4.8%
김*숙 1
 
4.8%
노*보 1
 
4.8%
박*란 1
 
4.8%
Other values (10) 10
47.6%
2024-03-15T00:29:40.628709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 21
33.9%
김 6
 
9.7%
이 3
 
4.8%
숙 3
 
4.8%
신 2
 
3.2%
석 2
 
3.2%
순 2
 
3.2%
노 1
 
1.6%
보 1
 
1.6%
송 1
 
1.6%
Other values (20) 20
32.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41
66.1%
Other Punctuation 21
33.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
14.6%
이 3
 
7.3%
숙 3
 
7.3%
신 2
 
4.9%
석 2
 
4.9%
순 2
 
4.9%
노 1
 
2.4%
보 1
 
2.4%
송 1
 
2.4%
영 1
 
2.4%
Other values (19) 19
46.3%
Other Punctuation
ValueCountFrequency (%)
* 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41
66.1%
Common 21
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
14.6%
이 3
 
7.3%
숙 3
 
7.3%
신 2
 
4.9%
석 2
 
4.9%
순 2
 
4.9%
노 1
 
2.4%
보 1
 
2.4%
송 1
 
2.4%
영 1
 
2.4%
Other values (19) 19
46.3%
Common
ValueCountFrequency (%)
* 21
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41
66.1%
ASCII 21
33.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 21
100.0%
Hangul
ValueCountFrequency (%)
김 6
 
14.6%
이 3
 
7.3%
숙 3
 
7.3%
신 2
 
4.9%
석 2
 
4.9%
순 2
 
4.9%
노 1
 
2.4%
보 1
 
2.4%
송 1
 
2.4%
영 1
 
2.4%
Other values (19) 19
46.3%

도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:41.647607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length15.857143
Min length10

Characters and Unicode

Total characters333
Distinct characters81
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

Unique21 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 능안자구길 53-54
2nd row전주시 덕진구 안골1길 11
3rd row전주시 덕진구 정여립로 1028-8
4th row전주시 완산구 서학2길 33
5th row군산시 조촌안4길 19
ValueCountFrequency (%)
전주시 4
 
5.0%
익산시 3
 
3.8%
덕진구 2
 
2.5%
군산시 2
 
2.5%
남원시 2
 
2.5%
완산구 2
 
2.5%
김제시 2
 
2.5%
하동1길 1
 
1.2%
79 1
 
1.2%
완주군 1
 
1.2%
Other values (60) 60
75.0%
2024-03-15T00:29:42.986270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
17.7%
1 19
 
5.7%
시 14
 
4.2%
2 13
 
3.9%
산 12
 
3.6%
- 12
 
3.6%
로 11
 
3.3%
길 11
 
3.3%
군 9
 
2.7%
4 9
 
2.7%
Other values (71) 164
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
56.2%
Decimal Number 75
22.5%
Space Separator 59
 
17.7%
Dash Punctuation 12
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 14
 
7.5%
산 12
 
6.4%
로 11
 
5.9%
길 11
 
5.9%
군 9
 
4.8%
면 8
 
4.3%
안 8
 
4.3%
읍 6
 
3.2%
주 5
 
2.7%
구 5
 
2.7%
Other values (60) 98
52.4%
Decimal Number
ValueCountFrequency (%)
1 19
25.3%
2 13
17.3%
4 9
12.0%
3 8
10.7%
7 8
10.7%
8 7
 
9.3%
9 5
 
6.7%
5 3
 
4.0%
0 3
 
4.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
56.2%
Common 146
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 14
 
7.5%
산 12
 
6.4%
로 11
 
5.9%
길 11
 
5.9%
군 9
 
4.8%
면 8
 
4.3%
안 8
 
4.3%
읍 6
 
3.2%
주 5
 
2.7%
구 5
 
2.7%
Other values (60) 98
52.4%
Common
ValueCountFrequency (%)
59
40.4%
1 19
 
13.0%
2 13
 
8.9%
- 12
 
8.2%
4 9
 
6.2%
3 8
 
5.5%
7 8
 
5.5%
8 7
 
4.8%
9 5
 
3.4%
5 3
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
56.2%
ASCII 146
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
40.4%
1 19
 
13.0%
2 13
 
8.9%
- 12
 
8.2%
4 9
 
6.2%
3 8
 
5.5%
7 8
 
5.5%
8 7
 
4.8%
9 5
 
3.4%
5 3
 
2.1%
Hangul
ValueCountFrequency (%)
시 14
 
7.5%
산 12
 
6.4%
로 11
 
5.9%
길 11
 
5.9%
군 9
 
4.8%
면 8
 
4.3%
안 8
 
4.3%
읍 6
 
3.2%
주 5
 
2.7%
구 5
 
2.7%
Other values (60) 98
52.4%

전화번호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size296.0 B
2024-03-15T00:29:43.785403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters252
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

Unique21 ?
Unique (%)100.0%

Sample

1st row063-224-8082
2nd row063-241-6435
3rd row063-214-1332
4th row063-282-2277
5th row063-445-7542
ValueCountFrequency (%)
063-224-8082 1
 
4.8%
063-626-0045 1
 
4.8%
063-564-7711 1
 
4.8%
063-653-9107 1
 
4.8%
063-642-1835 1
 
4.8%
063-351-9797 1
 
4.8%
063-433-2194 1
 
4.8%
063-243-9111 1
 
4.8%
063-546-3118 1
 
4.8%
063-548-7005 1
 
4.8%
Other values (11) 11
52.4%
2024-03-15T00:29:44.904249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.7%
0 35
13.9%
3 32
12.7%
6 31
12.3%
2 21
8.3%
1 21
8.3%
4 17
6.7%
5 17
6.7%
9 15
 
6.0%
7 11
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 210
83.3%
Dash Punctuation 42
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 35
16.7%
3 32
15.2%
6 31
14.8%
2 21
10.0%
1 21
10.0%
4 17
8.1%
5 17
8.1%
9 15
7.1%
7 11
 
5.2%
8 10
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.7%
0 35
13.9%
3 32
12.7%
6 31
12.3%
2 21
8.3%
1 21
8.3%
4 17
6.7%
5 17
6.7%
9 15
 
6.0%
7 11
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.7%
0 35
13.9%
3 32
12.7%
6 31
12.3%
2 21
8.3%
1 21
8.3%
4 17
6.7%
5 17
6.7%
9 15
 
6.0%
7 11
 
4.4%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
노인장애인복지과
21 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인장애인복지과 21
100.0%

Length

2024-03-15T00:29:45.301909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:29:45.611840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인장애인복지과 21
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size149.0 B
True
21 
ValueCountFrequency (%)
True 21
100.0%
2024-03-15T00:29:45.887129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
2015-10-01
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015-10-01
2nd row2015-10-01
3rd row2015-10-01
4th row2015-10-01
5th row2015-10-01

Common Values

ValueCountFrequency (%)
2015-10-01 21
100.0%

Length

2024-03-15T00:29:46.203593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:29:46.511107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015-10-01 21
100.0%

갱신주기(년)
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size296.0 B
1
21 

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 21
100.0%

Length

2024-03-15T00:29:46.838983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:29:47.353662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
100.0%

Interactions

2024-03-15T00:29:32.636559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:29:47.544916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명시설명운영주체시설장도로명주소전화번호
순번1.0000.9321.0000.7240.9481.0001.000
시군명0.9321.0001.0000.8710.9791.0001.000
시설명1.0001.0001.0001.0001.0001.0001.000
운영주체0.7240.8711.0001.0000.9501.0001.000
시설장0.9480.9791.0000.9501.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-03-15T00:29:33.025738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:29:33.529283image/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

순번시군명시설명운영주체시설장도로명주소전화번호자료출처공개여부작성일갱신주기(년)
01전주시샬롬노인복지센터사복)한기장복지재단김*희전주시 완산구 능안자구길 53-54063-224-8082노인장애인복지과Y2015-10-011
12전주시안골노인복지센터사복)전주중부복지재단이*숙전주시 덕진구 안골1길 11063-241-6435노인장애인복지과Y2015-10-011
23전주시늘푸른집주간보호센터사복)전주중앙복지원나*전주시 덕진구 정여립로 1028-8063-214-1332노인장애인복지과Y2015-10-011
34전주시이양재노인종합센터사복)혜산장*석전주시 완산구 서학2길 33063-282-2277노인장애인복지과Y2015-10-011
45군산시군산노인복지센터사복)삼동회성*규군산시 조촌안4길 19063-445-7542노인장애인복지과Y2015-10-011
56군산시군산동부노인요양원사랑마을개인신*래군산시 나포면 서왕길 84-7063-453-9902노인장애인복지과Y2015-10-011
67익산시새소망노인복지센터사복)임마누엘복지재단주*현익산시 춘포로 22063-852-1794노인장애인복지과Y2015-10-011
78익산시삼광노인복지센터개인이*숙익산시 배산로8길 21-3063-851-1129노인장애인복지과Y2015-10-011
89익산시사랑방노인복지센터개인김*신익산시 망성면 화산길 107-22063-862-9900노인장애인복지과Y2015-10-011
910정읍시하늘향노인복지센터사복)전주카돌릭사회복지회김*철정읍시 신태인읍 정신로 1204063-571-9009노인장애인복지과Y2015-10-011
순번시군명시설명운영주체시설장도로명주소전화번호자료출처공개여부작성일갱신주기(년)
1112남원시살림노인복지센터사복)한기장복지재단민*완남원시 이백면 이백로 131-4063-626-0045노인장애인복지과Y2015-10-011
1213김제시김제노인복지센터재단)대한성공회유지재단박*란김제시 백산면 소음방2길 19-29063-548-7005노인장애인복지과Y2015-10-011
1314김제시김제노인전문요양원주간센터재단)대한성공회유지재단노*보김제시 하동1길 79063-546-3118노인장애인복지과Y2015-10-011
1415완주군용진노인복지센터사복)한국장로교복지재단김*숙완주군 용진면 상운길 11-14063-243-9111노인장애인복지과Y2015-10-011
1516진안군밀알재가노인복지센터재단)대한예수교장로총회유지재단송*순진안군 진안읍 원반월안길 39-7063-433-2194노인장애인복지과Y2015-10-011
1617장수군밀알노인복지센터개인고*영장수군 장수읍 교촌로 17063-351-9797노인장애인복지과Y2015-10-011
1718임실군섬김노인복지센터사복)섬김복지재단김*순임실군 오수면 삼일로 22-12063-642-1835노인장애인복지과Y2015-10-011
1819순창군순창은빛노인복지센터재단)대한구세군유지재단윤*천순창군 풍산면 풍산로 487-4063-653-9107노인장애인복지과Y2015-10-011
1920고창군고창군노인복지센터사복)선운사복지재단손*석고창군 고창읍 전봉준로 88-15063-564-7711노인장애인복지과Y2015-10-011
2021부안군섬김과나눔노인복지센터사복)한기장복지재단이*섭부안군 부안읍 용암로 134063-581-9260노인장애인복지과Y2015-10-011