Overview

Dataset statistics

Number of variables10
Number of observations121
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory86.1 B

Variable types

Numeric5
Categorical2
Text3

Dataset

Description부산광역시_노인요양시설현황_20231231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15071152

Alerts

연번 is highly overall correlated with 구군High correlation
연면적(제곱미터) is highly overall correlated with 급여종류High correlation
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
구군 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
급여종류 is highly overall correlated with 연면적(제곱미터) High correlation
연번 has unique valuesUnique
장기요양기관 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:20:23.958886
Analysis finished2024-03-13 13:20:27.514437
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61
Minimum1
Maximum121
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:27.590554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q131
median61
Q391
95-th percentile115
Maximum121
Range120
Interquartile range (IQR)60

Descriptive statistics

Standard deviation35.073732
Coefficient of variation (CV)0.57497921
Kurtosis-1.2
Mean61
Median Absolute Deviation (MAD)30
Skewness0
Sum7381
Variance1230.1667
MonotonicityStrictly increasing
2024-03-13T22:20:27.759606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
92 1
 
0.8%
90 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
Other values (111) 111
91.7%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
121 1
0.8%
120 1
0.8%
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%

구군
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
기장군
20 
북구
13 
사하구
13 
해운대구
10 
사상구
9 
Other values (11)
56 

Length

Max length4
Median length3
Mean length2.9421488
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row중구
2nd row서구
3rd row서구
4th row서구
5th row서구

Common Values

ValueCountFrequency (%)
기장군 20
16.5%
북구 13
10.7%
사하구 13
10.7%
해운대구 10
8.3%
사상구 9
7.4%
부산진구 8
 
6.6%
동래구 8
 
6.6%
금정구 8
 
6.6%
연제구 7
 
5.8%
수영구 6
 
5.0%
Other values (6) 19
15.7%

Length

2024-03-13T22:20:27.921279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기장군 20
16.5%
북구 13
10.7%
사하구 13
10.7%
해운대구 10
8.3%
사상구 9
7.4%
부산진구 8
 
6.6%
동래구 8
 
6.6%
금정구 8
 
6.6%
연제구 7
 
5.8%
수영구 6
 
5.0%
Other values (6) 19
15.7%

급여종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
노인요양시설
98 
노인요양공동생활가정
23 

Length

Max length10
Median length6
Mean length6.7603306
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인요양시설 98
81.0%
노인요양공동생활가정 23
 
19.0%

Length

2024-03-13T22:20:28.388737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:20:28.503474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인요양시설 98
81.0%
노인요양공동생활가정 23
 
19.0%

장기요양기관
Text

UNIQUE 

Distinct121
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:28.759548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.0991736
Min length3

Characters and Unicode

Total characters980
Distinct characters178
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

Unique121 ?
Unique (%)100.0%

Sample

1st row굿모닝노인요양원
2nd row안나노인건강센터
3rd row인창서구그린빌노인요양원
4th row실버웰요양센터
5th row송도사랑요양원
ValueCountFrequency (%)
집 3
 
2.1%
녹원요양원 3
 
2.1%
정다운 2
 
1.4%
요양원 2
 
1.4%
노인요양원 2
 
1.4%
굿모닝노인요양원 1
 
0.7%
정금나무집 1
 
0.7%
소규모요양시설(가형 1
 
0.7%
큰별요양원 1
 
0.7%
미루나무집 1
 
0.7%
Other values (124) 124
87.9%
2024-03-13T22:20:29.207491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 76
 
7.8%
요 74
 
7.6%
원 70
 
7.1%
인 57
 
5.8%
노 52
 
5.3%
버 27
 
2.8%
실 26
 
2.7%
센 24
 
2.4%
터 24
 
2.4%
20
 
2.0%
Other values (168) 530
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 954
97.3%
Space Separator 20
 
2.0%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.3%
인 57
 
6.0%
노 52
 
5.5%
버 27
 
2.8%
실 26
 
2.7%
센 24
 
2.5%
터 24
 
2.5%
정 16
 
1.7%
Other values (165) 508
53.2%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 954
97.3%
Common 26
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.3%
인 57
 
6.0%
노 52
 
5.5%
버 27
 
2.8%
실 26
 
2.7%
센 24
 
2.5%
터 24
 
2.5%
정 16
 
1.7%
Other values (165) 508
53.2%
Common
ValueCountFrequency (%)
20
76.9%
) 3
 
11.5%
( 3
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 954
97.3%
ASCII 26
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.3%
인 57
 
6.0%
노 52
 
5.5%
버 27
 
2.8%
실 26
 
2.7%
센 24
 
2.5%
터 24
 
2.5%
정 16
 
1.7%
Other values (165) 508
53.2%
ASCII
ValueCountFrequency (%)
20
76.9%
) 3
 
11.5%
( 3
 
11.5%

설립연도
Real number (ℝ)

Distinct28
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.1736
Minimum1940
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:29.376697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1940
5-th percentile1999
Q12008
median2011
Q32018
95-th percentile2023
Maximum2023
Range83
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.5600538
Coefficient of variation (CV)0.0047534703
Kurtosis24.814181
Mean2011.1736
Median Absolute Deviation (MAD)5
Skewness-3.5489136
Sum243352
Variance91.394628
MonotonicityNot monotonic
2024-03-13T22:20:29.549457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2009 13
 
10.7%
2019 10
 
8.3%
2008 10
 
8.3%
2012 9
 
7.4%
2010 8
 
6.6%
2013 7
 
5.8%
2023 7
 
5.8%
2021 5
 
4.1%
2011 5
 
4.1%
2018 4
 
3.3%
Other values (18) 43
35.5%
ValueCountFrequency (%)
1940 1
 
0.8%
1986 1
 
0.8%
1997 1
 
0.8%
1998 3
2.5%
1999 1
 
0.8%
2001 2
1.7%
2002 2
1.7%
2003 4
3.3%
2004 3
2.5%
2005 2
1.7%
ValueCountFrequency (%)
2023 7
5.8%
2022 4
 
3.3%
2021 5
4.1%
2020 3
 
2.5%
2019 10
8.3%
2018 4
 
3.3%
2017 3
 
2.5%
2016 3
 
2.5%
2015 2
 
1.7%
2014 1
 
0.8%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1586.8236
Minimum107
Maximum6259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:29.680121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107
5-th percentile204.48
Q1489.02
median1113
Q32318.96
95-th percentile3969
Maximum6259
Range6152
Interquartile range (IQR)1829.94

Descriptive statistics

Standard deviation1321.9889
Coefficient of variation (CV)0.83310386
Kurtosis1.3769038
Mean1586.8236
Median Absolute Deviation (MAD)808
Skewness1.2108473
Sum192005.66
Variance1747654.6
MonotonicityNot monotonic
2024-03-13T22:20:29.847566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1460.0 2
 
1.7%
2318.96 1
 
0.8%
977.0 1
 
0.8%
2020.0 1
 
0.8%
1492.0 1
 
0.8%
197.0 1
 
0.8%
305.0 1
 
0.8%
186.42 1
 
0.8%
373.0 1
 
0.8%
378.0 1
 
0.8%
Other values (110) 110
90.9%
ValueCountFrequency (%)
107.0 1
0.8%
185.0 1
0.8%
186.42 1
0.8%
194.0 1
0.8%
196.08 1
0.8%
197.0 1
0.8%
204.48 1
0.8%
208.0 1
0.8%
211.6 1
0.8%
215.16 1
0.8%
ValueCountFrequency (%)
6259.0 1
0.8%
6059.0 1
0.8%
5169.0 1
0.8%
4901.0 1
0.8%
4480.0 1
0.8%
4105.0 1
0.8%
3969.0 1
0.8%
3852.0 1
0.8%
3794.0 1
0.8%
3680.0 1
0.8%

전화번호
Text

Distinct118
Distinct (%)98.3%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-03-13T22:20:30.104353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1440
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

Unique117 ?
Unique (%)97.5%

Sample

1st row051-468-5688
2nd row051-245-0035
3rd row051-255-0904
4th row051-242-8050
5th row051-255-3315
ValueCountFrequency (%)
051-862-3200 3
 
2.5%
051-518-6838 1
 
0.8%
051-756-0569 1
 
0.8%
051-751-0561 1
 
0.8%
051-752-8393 1
 
0.8%
051-752-2982 1
 
0.8%
051-865-9988 1
 
0.8%
051-710-0708 1
 
0.8%
051-868-0588 1
 
0.8%
051-502-3979 1
 
0.8%
Other values (108) 108
90.0%
2024-03-13T22:20:30.527705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 258
17.9%
- 240
16.7%
5 210
14.6%
1 208
14.4%
2 108
7.5%
8 94
 
6.5%
3 90
 
6.2%
7 82
 
5.7%
6 58
 
4.0%
9 46
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1200
83.3%
Dash Punctuation 240
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 258
21.5%
5 210
17.5%
1 208
17.3%
2 108
9.0%
8 94
 
7.8%
3 90
 
7.5%
7 82
 
6.8%
6 58
 
4.8%
9 46
 
3.8%
4 46
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1440
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 258
17.9%
- 240
16.7%
5 210
14.6%
1 208
14.4%
2 108
7.5%
8 94
 
6.5%
3 90
 
6.2%
7 82
 
5.7%
6 58
 
4.0%
9 46
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 258
17.9%
- 240
16.7%
5 210
14.6%
1 208
14.4%
2 108
7.5%
8 94
 
6.5%
3 90
 
6.2%
7 82
 
5.7%
6 58
 
4.0%
9 46
 
3.2%

주소
Text

Distinct118
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:30.865163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length29.909091
Min length20

Characters and Unicode

Total characters3619
Distinct characters190
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)95.0%

Sample

1st row부산광역시 중구 대영로 235 (영주동)
2nd row 부산광역시 서구 꽃마을로163번길 94-16 (서대신동3가)
3rd row 부산광역시 서구 대영로73번길 111 (동대신동3가)
4th row 부산광역시 서구 시약로 35 (서대신동3가)
5th row 부산광역시 서구 암남공원로 522 (암남동)
ValueCountFrequency (%)
부산광역시 120
 
18.3%
기장군 20
 
3.0%
사하구 13
 
2.0%
북구 13
 
2.0%
장안읍 11
 
1.7%
해운대구 10
 
1.5%
사상구 9
 
1.4%
기장읍 9
 
1.4%
부산진구 8
 
1.2%
동래구 8
 
1.2%
Other values (305) 435
66.3%
2024-03-13T22:20:31.411783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
750
20.7%
산 142
 
3.9%
부 130
 
3.6%
광 127
 
3.5%
동 127
 
3.5%
시 124
 
3.4%
역 120
 
3.3%
( 116
 
3.2%
) 116
 
3.2%
1 110
 
3.0%
Other values (180) 1757
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2058
56.9%
Space Separator 750
 
20.7%
Decimal Number 519
 
14.3%
Open Punctuation 116
 
3.2%
Close Punctuation 116
 
3.2%
Other Punctuation 31
 
0.9%
Dash Punctuation 29
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 142
 
6.9%
부 130
 
6.3%
광 127
 
6.2%
동 127
 
6.2%
시 124
 
6.0%
역 120
 
5.8%
구 106
 
5.2%
로 102
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (165) 946
46.0%
Decimal Number
ValueCountFrequency (%)
1 110
21.2%
2 66
12.7%
3 59
11.4%
5 48
9.2%
6 45
8.7%
4 44
 
8.5%
7 41
 
7.9%
8 39
 
7.5%
9 35
 
6.7%
0 32
 
6.2%
Space Separator
ValueCountFrequency (%)
750
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
56.9%
Common 1561
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 142
 
6.9%
부 130
 
6.3%
광 127
 
6.2%
동 127
 
6.2%
시 124
 
6.0%
역 120
 
5.8%
구 106
 
5.2%
로 102
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (165) 946
46.0%
Common
ValueCountFrequency (%)
750
48.0%
( 116
 
7.4%
) 116
 
7.4%
1 110
 
7.0%
2 66
 
4.2%
3 59
 
3.8%
5 48
 
3.1%
6 45
 
2.9%
4 44
 
2.8%
7 41
 
2.6%
Other values (5) 166
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
56.9%
ASCII 1561
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
750
48.0%
( 116
 
7.4%
) 116
 
7.4%
1 110
 
7.0%
2 66
 
4.2%
3 59
 
3.8%
5 48
 
3.1%
6 45
 
2.9%
4 44
 
2.8%
7 41
 
2.6%
Other values (5) 166
 
10.6%
Hangul
ValueCountFrequency (%)
산 142
 
6.9%
부 130
 
6.3%
광 127
 
6.2%
동 127
 
6.2%
시 124
 
6.0%
역 120
 
5.8%
구 106
 
5.2%
로 102
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (165) 946
46.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct116
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.189406
Minimum35.05039
Maximum35.379486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:31.604979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.05039
5-th percentile35.085951
Q135.138031
median35.182112
Q335.229008
95-th percentile35.329331
Maximum35.379486
Range0.3290966
Interquartile range (IQR)0.09097742

Descriptive statistics

Standard deviation0.073065186
Coefficient of variation (CV)0.0020763404
Kurtosis-0.094959483
Mean35.189406
Median Absolute Deviation (MAD)0.04689627
Skewness0.53018654
Sum4257.9182
Variance0.0053385214
MonotonicityNot monotonic
2024-03-13T22:20:31.778831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17974113 3
 
2.5%
35.14722597 2
 
1.7%
35.23156397 2
 
1.7%
35.22920006 2
 
1.7%
35.11259417 1
 
0.8%
35.175744 1
 
0.8%
35.16444665 1
 
0.8%
35.17623417 1
 
0.8%
35.17008274 1
 
0.8%
35.17708282 1
 
0.8%
Other values (106) 106
87.6%
ValueCountFrequency (%)
35.0503898 1
0.8%
35.068374 1
0.8%
35.0740233 1
0.8%
35.07660279 1
0.8%
35.07974049 1
0.8%
35.08123157 1
0.8%
35.08595082 1
0.8%
35.08628423 1
0.8%
35.08830952 1
0.8%
35.09284604 1
0.8%
ValueCountFrequency (%)
35.3794864 1
0.8%
35.36665765 1
0.8%
35.35898651 1
0.8%
35.34448035 1
0.8%
35.34389738 1
0.8%
35.33516414 1
0.8%
35.329331 1
0.8%
35.329257 1
0.8%
35.321063 1
0.8%
35.31518227 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct116
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.07584
Minimum128.86853
Maximum129.28363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:31.933842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.86853
5-th percentile128.97264
Q1129.01119
median129.06803
Q3129.111
95-th percentile129.25108
Maximum129.28363
Range0.4151012
Interquartile range (IQR)0.0998047

Descriptive statistics

Standard deviation0.085877109
Coefficient of variation (CV)0.00066532289
Kurtosis-0.016242994
Mean129.07584
Median Absolute Deviation (MAD)0.054956
Skewness0.53994991
Sum15618.176
Variance0.0073748778
MonotonicityNot monotonic
2024-03-13T22:20:32.081484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0900311 3
 
2.5%
129.045315 2
 
1.7%
129.076696 2
 
1.7%
129.074929 2
 
1.7%
129.0364413 1
 
0.8%
129.107203 1
 
0.8%
129.1106165 1
 
0.8%
129.1000513 1
 
0.8%
129.0994963 1
 
0.8%
129.1038613 1
 
0.8%
Other values (106) 106
87.6%
ValueCountFrequency (%)
128.8685299 1
0.8%
128.9088564 1
0.8%
128.9173604 1
0.8%
128.9238884 1
0.8%
128.9658567 1
0.8%
128.9719463 1
0.8%
128.9726353 1
0.8%
128.9767058 1
0.8%
128.9776688 1
0.8%
128.979128 1
0.8%
ValueCountFrequency (%)
129.2836311 1
0.8%
129.2771782 1
0.8%
129.2733574 1
0.8%
129.2614089 1
0.8%
129.2602205 1
0.8%
129.2573159 1
0.8%
129.2510753 1
0.8%
129.2413835 1
0.8%
129.2277195 1
0.8%
129.2262975 1
0.8%

Interactions

2024-03-13T22:20:26.526458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.417139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.997097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.532500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.018400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.634710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.521181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.086639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.627584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.110224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.757301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.631905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.200665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.721315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.218341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.878594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.728205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.320129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.833067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.318420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:27.024275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:24.894578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.432261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:25.937124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:26.418550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:20:32.191144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군급여종류설립연도연면적(제곱미터)위도경도
연번1.0000.9380.0000.3560.2230.8000.821
구군0.9381.0000.2250.3900.1430.8340.880
급여종류0.0000.2251.0000.3070.7000.0860.097
설립연도0.3560.3900.3071.0000.5930.0000.000
연면적(제곱미터)0.2230.1430.7000.5931.0000.0000.000
위도0.8000.8340.0860.0000.0001.0000.776
경도0.8210.8800.0970.0000.0000.7761.000
2024-03-13T22:20:32.347263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군급여종류
구군1.0000.163
급여종류0.1631.000
2024-03-13T22:20:32.446337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설립연도연면적(제곱미터)위도경도구군급여종류
연번1.0000.026-0.0380.4200.3490.7210.000
설립연도0.0261.000-0.342-0.0920.0020.1540.360
연면적(제곱미터)-0.038-0.3421.0000.128-0.0780.0430.527
위도0.420-0.0920.1281.0000.6510.5070.059
경도0.3490.002-0.0780.6511.0000.5870.083
구군0.7210.1540.0430.5070.5871.0000.163
급여종류0.0000.3600.5270.0590.0830.1631.000

Missing values

2024-03-13T22:20:27.242504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:20:27.434742image/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

연번구군급여종류장기요양기관설립연도연면적(제곱미터)전화번호주소위도경도
01중구노인요양시설굿모닝노인요양원20212318.96051-468-5688부산광역시 중구 대영로 235 (영주동)35.112594129.036441
12서구노인요양시설안나노인건강센터20053076.0051-245-0035부산광역시 서구 꽃마을로163번길 94-16 (서대신동3가)35.127712129.004667
23서구노인요양시설인창서구그린빌노인요양원20121329.0051-255-0904부산광역시 서구 대영로73번길 111 (동대신동3가)35.115147129.016536
34서구노인요양시설실버웰요양센터20131086.0051-242-8050부산광역시 서구 시약로 35 (서대신동3가)35.112564129.008485
45서구노인요양시설송도사랑요양원20191654.0051-255-3315부산광역시 서구 암남공원로 522 (암남동)35.07974129.012137
56동구노인요양시설인창동구노인요양원20104480.0051-464-1004부산광역시 동구 고관로 34 (초량동)35.122386129.042979
67동구노인요양시설송원노인전문요양원20083192.0051-637-8260부산광역시 동구 안창로 51 (범일동)35.145624129.043934
78동구노인요양공동생활가정지혜실버홈2013259.0051-751-8388부산광역시 동구 범곡남로 15 (범일동)35.138031129.054788
89영도구노인요양시설파랑새노인건강센터20033325.0051-412-5422부산광역시 영도구 와치로 78 (청학동)35.085951129.059599
910영도구노인요양공동생활가정영도요양원2019185.0051-405-7888부산광역시 영도구 중리로 35 101호, 201호 (동삼동, 영도빌딩)35.074023129.06803
연번구군급여종류장기요양기관설립연도연면적(제곱미터)전화번호주소위도경도
111112기장군노인요양시설백양원2015685.0051-727-3990부산광역시 기장군 일광면 칠암3길 14 (일광면)35.297269129.257316
112113기장군노인요양시설행복한어르신의집 노인요양원2012957.0051-728-9007부산광역시 기장군 장안읍 기장대로 1727 (장안읍, 행복한어르신의집)35.343897129.251075
113114기장군노인요양시설주사랑재활요양원2018919.0051-724-8181부산광역시 기장군 기장읍 연화길 62 (기장읍)35.219097129.226297
114115기장군노인요양공동생활가정해피케어 노인요양공동생활가정2018194.0051-508-2201부산광역시 기장군 철마면 강변길 20 (철마면)35.3075129.11201
115116기장군노인요양시설효산요양원20191460.0051-508-0675부산광역시 기장군 철마면 철마삼동로 103 (철마면)35.313805129.114505
116117기장군노인요양시설온누리요양원20142124.0051-714-0120부산광역시 기장군 장안읍 못안길 47 (장안읍)35.379486129.260221
117118기장군노인요양공동생활가정해강노인요양공동생활가정원2021196.08051-714-7454부산광역시 기장군 정관읍 용수1길 16-10, 1,2층(정관읍)35.329257129.174588
118119기장군노인요양시설해빛실버타운요양원20231898.16051-723-8006부산광역시 기장군 기장읍 내리길 168(기장읍)35.21706129.197861
119120기장군노인요양시설정관스마트요양원20231901.0051-921-0777부산광역시 기장군 정관읍 구연3로 11 3,4,6층 (정관읍, 서울프라자)35.321063129.181196
120121기장군노인요양공동생활가정정관자연노인요양공동생활가정2023476.15<NA>부산광역시 기장군 정관읍 용수1길 16-4 1층 (정관읍)35.329331129.174531