Overview

Dataset statistics

Number of variables9
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory77.8 B

Variable types

Text6
Categorical1
Numeric2

Dataset

Description부산광역시_노인복지관현황_20240101
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15042666

Alerts

경도 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 경도High correlation
운영단체 구분 is highly imbalanced (54.4%)Imbalance
시설명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:16:23.183869
Analysis finished2024-03-13 13:16:24.273027
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:24.412039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.9428571
Min length4

Characters and Unicode

Total characters313
Distinct characters63
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

Unique35 ?
Unique (%)100.0%

Sample

1st row중구노인복지관
2nd row중구노인복지관분관
3rd row부민노인복지관
4th row서구노인복지관
5th row동구노인종합복지관
ValueCountFrequency (%)
부산진구 2
 
4.8%
분관 2
 
4.8%
노인복지관 2
 
4.8%
사하사랑채복지관 1
 
2.4%
사하사랑채노인복지관분관 1
 
2.4%
신장림사랑채노인복지관 1
 
2.4%
금정구노인복지관 1
 
2.4%
강서구노인복지관 1
 
2.4%
가덕도동노인복지관 1
 
2.4%
명지노인종합복지관 1
 
2.4%
Other values (29) 29
69.0%
2024-03-13T22:16:24.886815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
관 43
13.7%
복 34
 
10.9%
지 34
 
10.9%
인 33
 
10.5%
노 32
 
10.2%
구 18
 
5.8%
분 8
 
2.6%
사 8
 
2.6%
7
 
2.2%
장 5
 
1.6%
Other values (53) 91
29.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 306
97.8%
Space Separator 7
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 43
14.1%
복 34
 
11.1%
지 34
 
11.1%
인 33
 
10.8%
노 32
 
10.5%
구 18
 
5.9%
분 8
 
2.6%
사 8
 
2.6%
장 5
 
1.6%
합 5
 
1.6%
Other values (52) 86
28.1%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 306
97.8%
Common 7
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 43
14.1%
복 34
 
11.1%
지 34
 
11.1%
인 33
 
10.8%
노 32
 
10.5%
구 18
 
5.9%
분 8
 
2.6%
사 8
 
2.6%
장 5
 
1.6%
합 5
 
1.6%
Other values (52) 86
28.1%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 306
97.8%
ASCII 7
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
관 43
14.1%
복 34
 
11.1%
지 34
 
11.1%
인 33
 
10.8%
노 32
 
10.5%
구 18
 
5.9%
분 8
 
2.6%
사 8
 
2.6%
장 5
 
1.6%
합 5
 
1.6%
Other values (52) 86
28.1%
ASCII
ValueCountFrequency (%)
7
100.0%

시설장
Text

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:25.156489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters105
Distinct characters47
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

Unique19 ?
Unique (%)54.3%

Sample

1st row이희배
2nd row이희배
3rd row김문희
4th row강동인
5th row김채영
ValueCountFrequency (%)
김익현 4
 
11.4%
윤현주 2
 
5.7%
한정민 2
 
5.7%
정영욱 2
 
5.7%
김채영 2
 
5.7%
이희배 2
 
5.7%
박석원 2
 
5.7%
이운철 1
 
2.9%
이은숙 1
 
2.9%
윤원찬 1
 
2.9%
Other values (16) 16
45.7%
2024-03-13T22:16:25.697617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 8
 
7.6%
정 8
 
7.6%
현 7
 
6.7%
이 6
 
5.7%
박 4
 
3.8%
희 4
 
3.8%
윤 4
 
3.8%
익 4
 
3.8%
영 4
 
3.8%
동 3
 
2.9%
Other values (37) 53
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 8
 
7.6%
정 8
 
7.6%
현 7
 
6.7%
이 6
 
5.7%
박 4
 
3.8%
희 4
 
3.8%
윤 4
 
3.8%
익 4
 
3.8%
영 4
 
3.8%
동 3
 
2.9%
Other values (37) 53
50.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 8
 
7.6%
정 8
 
7.6%
현 7
 
6.7%
이 6
 
5.7%
박 4
 
3.8%
희 4
 
3.8%
윤 4
 
3.8%
익 4
 
3.8%
영 4
 
3.8%
동 3
 
2.9%
Other values (37) 53
50.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 8
 
7.6%
정 8
 
7.6%
현 7
 
6.7%
이 6
 
5.7%
박 4
 
3.8%
희 4
 
3.8%
윤 4
 
3.8%
익 4
 
3.8%
영 4
 
3.8%
동 3
 
2.9%
Other values (37) 53
50.5%

주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:26.055539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length19.142857
Min length15

Characters and Unicode

Total characters670
Distinct characters100
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

Unique35 ?
Unique (%)100.0%

Sample

1st row부산광역시 중구 책방골목길3-1
2nd row부산광역시 중구 영주로 8-1
3rd row부산광역시 서구 부용로 30
4th row부산광역시 서구 장군산로46번길21
5th row부산광역시 동구 홍곡중로5번길24
ValueCountFrequency (%)
부산광역시 35
26.9%
강서구 3
 
2.3%
해운대구 3
 
2.3%
동구 3
 
2.3%
기장군 3
 
2.3%
부산진구 3
 
2.3%
중구 2
 
1.5%
사상구 2
 
1.5%
사하구 2
 
1.5%
영도구 2
 
1.5%
Other values (68) 72
55.4%
2024-03-13T22:16:26.556566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
14.2%
부 39
 
5.8%
산 39
 
5.8%
광 36
 
5.4%
시 36
 
5.4%
역 35
 
5.2%
로 31
 
4.6%
구 31
 
4.6%
1 29
 
4.3%
길 19
 
2.8%
Other values (90) 280
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 439
65.5%
Decimal Number 128
 
19.1%
Space Separator 95
 
14.2%
Dash Punctuation 8
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 39
 
8.9%
산 39
 
8.9%
광 36
 
8.2%
시 36
 
8.2%
역 35
 
8.0%
로 31
 
7.1%
구 31
 
7.1%
길 19
 
4.3%
번 16
 
3.6%
대 11
 
2.5%
Other values (78) 146
33.3%
Decimal Number
ValueCountFrequency (%)
1 29
22.7%
3 19
14.8%
0 15
11.7%
2 14
10.9%
8 12
9.4%
4 9
 
7.0%
5 9
 
7.0%
9 8
 
6.2%
6 7
 
5.5%
7 6
 
4.7%
Space Separator
ValueCountFrequency (%)
95
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 439
65.5%
Common 231
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 39
 
8.9%
산 39
 
8.9%
광 36
 
8.2%
시 36
 
8.2%
역 35
 
8.0%
로 31
 
7.1%
구 31
 
7.1%
길 19
 
4.3%
번 16
 
3.6%
대 11
 
2.5%
Other values (78) 146
33.3%
Common
ValueCountFrequency (%)
95
41.1%
1 29
 
12.6%
3 19
 
8.2%
0 15
 
6.5%
2 14
 
6.1%
8 12
 
5.2%
4 9
 
3.9%
5 9
 
3.9%
- 8
 
3.5%
9 8
 
3.5%
Other values (2) 13
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 439
65.5%
ASCII 231
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
41.1%
1 29
 
12.6%
3 19
 
8.2%
0 15
 
6.5%
2 14
 
6.1%
8 12
 
5.2%
4 9
 
3.9%
5 9
 
3.9%
- 8
 
3.5%
9 8
 
3.5%
Other values (2) 13
 
5.6%
Hangul
ValueCountFrequency (%)
부 39
 
8.9%
산 39
 
8.9%
광 36
 
8.2%
시 36
 
8.2%
역 35
 
8.0%
로 31
 
7.1%
구 31
 
7.1%
길 19
 
4.3%
번 16
 
3.6%
대 11
 
2.5%
Other values (78) 146
33.3%

전화번호
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:26.843238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters420
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

Unique35 ?
Unique (%)100.0%

Sample

1st row051-241-2591
2nd row051-462-0316
3rd row051-240-3531
4th row051-240-3541
5th row051-467-7887
ValueCountFrequency (%)
051-241-2591 1
 
2.9%
051-529-9141 1
 
2.9%
051-207-9544 1
 
2.9%
051-266-8515 1
 
2.9%
051-792-7200 1
 
2.9%
051-972-4851 1
 
2.9%
051-972-0048 1
 
2.9%
051-712-7000 1
 
2.9%
051-293-9544 1
 
2.9%
051-853-1872 1
 
2.9%
Other values (25) 25
71.4%
2024-03-13T22:16:27.287349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 70
16.7%
0 62
14.8%
5 60
14.3%
1 58
13.8%
7 30
7.1%
4 29
6.9%
9 29
6.9%
2 26
 
6.2%
8 23
 
5.5%
3 18
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.3%
Dash Punctuation 70
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62
17.7%
5 60
17.1%
1 58
16.6%
7 30
8.6%
4 29
8.3%
9 29
8.3%
2 26
7.4%
8 23
 
6.6%
3 18
 
5.1%
6 15
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 70
16.7%
0 62
14.8%
5 60
14.3%
1 58
13.8%
7 30
7.1%
4 29
6.9%
9 29
6.9%
2 26
 
6.2%
8 23
 
5.5%
3 18
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 70
16.7%
0 62
14.8%
5 60
14.3%
1 58
13.8%
7 30
7.1%
4 29
6.9%
9 29
6.9%
2 26
 
6.2%
8 23
 
5.5%
3 18
 
4.3%

운영단체
Text

Distinct19
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:27.510158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length6.8857143
Min length2

Characters and Unicode

Total characters241
Distinct characters68
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

Unique10 ?
Unique (%)28.6%

Sample

1st row로사리오 카리타스
2nd row로사리오 카리타스
3rd row불국토
4th row대한불교천태종복지재단
5th row새샘복지재단
ValueCountFrequency (%)
주는사랑복지재단 6
14.3%
기장군 3
 
7.1%
도시관리공단 3
 
7.1%
로사리오 3
 
7.1%
카리타스 3
 
7.1%
불국토 3
 
7.1%
혜원 2
 
4.8%
새샘복지재단 2
 
4.8%
대한불교천태종복지재단 2
 
4.8%
의안복지재단 2
 
4.8%
Other values (12) 13
31.0%
2024-03-13T22:16:27.883541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
단 19
 
7.9%
복 17
 
7.1%
지 17
 
7.1%
재 16
 
6.6%
사 12
 
5.0%
리 9
 
3.7%
7
 
2.9%
주 6
 
2.5%
랑 6
 
2.5%
는 6
 
2.5%
Other values (58) 126
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
97.1%
Space Separator 7
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 19
 
8.1%
복 17
 
7.3%
지 17
 
7.3%
재 16
 
6.8%
사 12
 
5.1%
리 9
 
3.8%
주 6
 
2.6%
랑 6
 
2.6%
는 6
 
2.6%
불 5
 
2.1%
Other values (57) 121
51.7%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 234
97.1%
Common 7
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 19
 
8.1%
복 17
 
7.3%
지 17
 
7.3%
재 16
 
6.8%
사 12
 
5.1%
리 9
 
3.8%
주 6
 
2.6%
랑 6
 
2.6%
는 6
 
2.6%
불 5
 
2.1%
Other values (57) 121
51.7%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
97.1%
ASCII 7
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
단 19
 
8.1%
복 17
 
7.3%
지 17
 
7.3%
재 16
 
6.8%
사 12
 
5.1%
리 9
 
3.8%
주 6
 
2.6%
랑 6
 
2.6%
는 6
 
2.6%
불 5
 
2.1%
Other values (57) 121
51.7%
ASCII
ValueCountFrequency (%)
7
100.0%

운영단체 구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Memory size412.0 B
사회복지법인
29 
공단
3 
학교법인
 
2
사단법인
 
1

Length

Max length6
Median length6
Mean length5.4857143
Min length2

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
사회복지법인 29
82.9%
공단 3
 
8.6%
학교법인 2
 
5.7%
사단법인 1
 
2.9%

Length

2024-03-13T22:16:28.046052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:16:28.167130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사회복지법인 29
82.9%
공단 3
 
8.6%
학교법인 2
 
5.7%
사단법인 1
 
2.9%

홈페이지 주소
Text

Distinct26
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T22:16:28.694820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length19.085714
Min length10

Characters and Unicode

Total characters668
Distinct characters36
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)51.4%

Sample

1st rowwww.junggusilver.or.kr
2nd rowwww.junggusilver.or.kr
3rd rowbmsenior.bulgukto.or.kr
4th rowwww.woorinoin.or.kr
5th rowwww.hyojason.or.kr
ValueCountFrequency (%)
www.nosasa.or.kr 3
 
8.6%
www.mjnoin.ai-sw.net 2
 
5.7%
www.sahasilver.org 2
 
5.7%
www.junggusilver.or.kr 2
 
5.7%
www.youngdosenior.or.kr 2
 
5.7%
www.hyojason.or.kr 2
 
5.7%
www.onbokji.org 2
 
5.7%
www.sasang-senior.kr 2
 
5.7%
www.sjrsilver.or.kr 1
 
2.9%
www.다사랑시니어.org 1
 
2.9%
Other values (16) 16
45.7%
2024-03-13T22:16:29.113069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 96
14.4%
w 95
14.2%
r 72
10.8%
o 66
9.9%
n 42
 
6.3%
s 40
 
6.0%
k 34
 
5.1%
a 29
 
4.3%
g 27
 
4.0%
e 26
 
3.9%
Other values (26) 141
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 551
82.5%
Other Punctuation 96
 
14.4%
Other Letter 9
 
1.3%
Decimal Number 8
 
1.2%
Dash Punctuation 4
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 95
17.2%
r 72
13.1%
o 66
12.0%
n 42
7.6%
s 40
7.3%
k 34
 
6.2%
a 29
 
5.3%
g 27
 
4.9%
e 26
 
4.7%
i 25
 
4.5%
Other values (11) 95
17.2%
Other Letter
ValueCountFrequency (%)
사 1
11.1%
니 1
11.1%
시 1
11.1%
랑 1
11.1%
버 1
11.1%
다 1
11.1%
벨 1
11.1%
실 1
11.1%
어 1
11.1%
Decimal Number
ValueCountFrequency (%)
0 3
37.5%
6 2
25.0%
9 2
25.0%
7 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 96
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 551
82.5%
Common 108
 
16.2%
Hangul 9
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 95
17.2%
r 72
13.1%
o 66
12.0%
n 42
7.6%
s 40
7.3%
k 34
 
6.2%
a 29
 
5.3%
g 27
 
4.9%
e 26
 
4.7%
i 25
 
4.5%
Other values (11) 95
17.2%
Hangul
ValueCountFrequency (%)
사 1
11.1%
니 1
11.1%
시 1
11.1%
랑 1
11.1%
버 1
11.1%
다 1
11.1%
벨 1
11.1%
실 1
11.1%
어 1
11.1%
Common
ValueCountFrequency (%)
. 96
88.9%
- 4
 
3.7%
0 3
 
2.8%
6 2
 
1.9%
9 2
 
1.9%
7 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 659
98.7%
Hangul 9
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 96
14.6%
w 95
14.4%
r 72
10.9%
o 66
10.0%
n 42
 
6.4%
s 40
 
6.1%
k 34
 
5.2%
a 29
 
4.4%
g 27
 
4.1%
e 26
 
3.9%
Other values (17) 132
20.0%
Hangul
ValueCountFrequency (%)
사 1
11.1%
니 1
11.1%
시 1
11.1%
랑 1
11.1%
버 1
11.1%
다 1
11.1%
벨 1
11.1%
실 1
11.1%
어 1
11.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05529
Minimum128.83165
Maximum129.23673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-13T22:16:29.279948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.83165
5-th percentile128.95832
Q1129.01151
median129.04841
Q3129.09803
95-th percentile129.18914
Maximum129.23673
Range0.4050812
Interquartile range (IQR)0.0865131

Descriptive statistics

Standard deviation0.079735949
Coefficient of variation (CV)0.00061784333
Kurtosis1.250045
Mean129.05529
Median Absolute Deviation (MAD)0.0448476
Skewness-0.073139719
Sum4516.9351
Variance0.0063578215
MonotonicityNot monotonic
2024-03-13T22:16:29.451887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
129.026183 1
 
2.9%
129.0325002 1
 
2.9%
128.9772442 1
 
2.9%
128.9761521 1
 
2.9%
129.0847903 1
 
2.9%
128.9734691 1
 
2.9%
128.8316513 1
 
2.9%
128.922964 1
 
2.9%
129.0821016 1
 
2.9%
129.1027986 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
128.8316513 1
2.9%
128.922964 1
2.9%
128.9734691 1
2.9%
128.9761521 1
2.9%
128.9772442 1
2.9%
128.9858423 1
2.9%
128.9948438 1
2.9%
128.9987036 1
2.9%
129.0086824 1
2.9%
129.014347 1
2.9%
ValueCountFrequency (%)
129.2367325 1
2.9%
129.2125973 1
2.9%
129.179083 1
2.9%
129.1787854 1
2.9%
129.1275334 1
2.9%
129.1221252 1
2.9%
129.1111735 1
2.9%
129.1048646 1
2.9%
129.1027986 1
2.9%
129.093257 1
2.9%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.154396
Minimum35.056641
Maximum35.324756
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-03-13T22:16:29.666022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.056641
5-th percentile35.074738
Q135.108799
median35.147255
Q335.188237
95-th percentile35.271029
Maximum35.324756
Range0.26811513
Interquartile range (IQR)0.07943769

Descriptive statistics

Standard deviation0.061161173
Coefficient of variation (CV)0.0017397873
Kurtosis0.66791593
Mean35.154396
Median Absolute Deviation (MAD)0.03981856
Skewness0.84743155
Sum1230.4039
Variance0.0037406891
MonotonicityNot monotonic
2024-03-13T22:16:29.821991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
35.10414052 1
 
2.9%
35.11016227 1
 
2.9%
35.09159221 1
 
2.9%
35.0754297 1
 
2.9%
35.27917441 1
 
2.9%
35.20732663 1
 
2.9%
35.05664095 1
 
2.9%
35.110585 1
 
2.9%
35.19110671 1
 
2.9%
35.18536723 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
35.05664095 1
2.9%
35.07312369 1
2.9%
35.0754297 1
2.9%
35.09111411 1
2.9%
35.09133006 1
2.9%
35.09159221 1
2.9%
35.10300921 1
2.9%
35.10414052 1
2.9%
35.10743629 1
2.9%
35.11016227 1
2.9%
ValueCountFrequency (%)
35.32475608 1
2.9%
35.27917441 1
2.9%
35.26753833 1
2.9%
35.23509949 1
2.9%
35.21238058 1
2.9%
35.21107713 1
2.9%
35.20732663 1
2.9%
35.19427427 1
2.9%
35.19110671 1
2.9%
35.18536723 1
2.9%

Interactions

2024-03-13T22:16:23.832278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:23.578040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:23.940580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:16:23.695917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:16:29.929268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명시설장주소전화번호운영단체운영단체 구분홈페이지 주소경도위도
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.000
시설장1.0001.0001.0001.0001.0001.0000.9980.6800.961
주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
운영단체1.0001.0001.0001.0001.0001.0001.0000.3960.730
운영단체 구분1.0001.0001.0001.0001.0001.0001.0000.8190.699
홈페이지 주소1.0000.9981.0001.0001.0001.0001.0000.9040.499
경도1.0000.6801.0001.0000.3960.8190.9041.0000.643
위도1.0000.9611.0001.0000.7300.6990.4990.6431.000
2024-03-13T22:16:30.093260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도운영단체 구분
경도1.0000.6290.419
위도0.6291.0000.443
운영단체 구분0.4190.4431.000

Missing values

2024-03-13T22:16:24.083756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:16:24.221062image/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

시설명시설장주소전화번호운영단체운영단체 구분홈페이지 주소경도위도
0중구노인복지관이희배부산광역시 중구 책방골목길3-1051-241-2591로사리오 카리타스사회복지법인www.junggusilver.or.kr129.02618335.104141
1중구노인복지관분관이희배부산광역시 중구 영주로 8-1051-462-0316로사리오 카리타스사회복지법인www.junggusilver.or.kr129.032535.110162
2부민노인복지관김문희부산광역시 서구 부용로 30051-240-3531불국토사회복지법인bmsenior.bulgukto.or.kr129.01804135.107436
3서구노인복지관강동인부산광역시 서구 장군산로46번길21051-240-3541대한불교천태종복지재단사회복지법인www.woorinoin.or.kr129.01434735.073124
4동구노인종합복지관김채영부산광역시 동구 홍곡중로5번길24051-467-7887새샘복지재단사회복지법인www.hyojason.or.kr129.04042235.125806
5동구분관김채영부산광역시 동구 초량남로 12051-714-6092새샘복지재단사회복지법인www.hyojason.or.kr129.03484635.119562
6동구자성대노인복지관이은숙부산광역시 동구 자성로140번길32051-632-7597봉생사회복지회사회복지법인silver.bsdonggu.go.kr129.06484135.135644
7영도구노인복지관박석원부산광역시 영도구 절영로29번길14051-417-6344혜원사회복지법인www.youngdosenior.or.kr129.04009335.09133
8영도구노인복지관분관박석원부산광역시 영도구 봉래길 372051-418-6300혜원사회복지법인www.youngdosenior.or.kr129.05670535.091114
9부산진구 노인장애인복지관한정민부산광역시 부산진구 전포대로300번길 6 585-1051-808-8090주는사랑복지재단사회복지법인www.onbokji.org129.06584835.164047
시설명시설장주소전화번호운영단체운영단체 구분홈페이지 주소경도위도
25명지노인종합복지관김익현부산광역시 강서구 명지국제13로 33051-712-7000주는사랑복지재단사회복지법인www.mjnoin.ai-sw.net128.92296435.110585
26부산광역시노인종합복지관임종린부산광역시 연제구 거제천로230번길18051-853-1872대한노인회 부산광역시연합회사단법인www.youngsilver.or.kr129.08210235.191107
27연제구노인복지관이운철부산광역시 연제구 고분로 188051-863-9988나온사회복지법인www.yjsilver.kr129.10279935.185367
28수영구노인복지관이병호부산광역시 수영구 황령대로 489번길83051-759-6070불국토사회복지법인6070.bulgukto.or.kr129.11117435.14005
29광안노인복지관손정환부산광역시 수영구 장대골로 75-8051-715-6099불국토사회복지법인6099.bulgukto.or.kr129.10486535.159569
30사상구 노인복지관김익현부산광역시 사상구 가야대로 196번길51051-325-7555주는사랑복지재단사회복지법인www.sasang-senior.kr128.99484435.147255
31사상구노인복지관 분관김익현부산광역시 사상구 모라로 91-8051-317-7555주는사랑복지재단사회복지법인www.sasang-senior.kr128.98584235.159768
32기장군노인복지관이봉규부산광역시 기장군 기장읍 대청로22번길61051-724-3443기장군 도시관리공단공단www.nosasa.or.kr129.21259735.235099
33기장군 노인복지관 일광 분관손병수부산광역시 기장군 일광면 이천리 930-2051-792-4870기장군 도시관리공단공단www.nosasa.or.kr129.23673235.267538
34정관노인복지관금동숙부산광역시 기장군 정관읍 정관중앙로 83-14051-792-4920기장군 도시관리공단공단www.nosasa.or.kr129.17908335.324756