Overview

Dataset statistics

Number of variables10
Number of observations115
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory86.1 B

Variable types

Numeric5
Categorical2
Text3

Dataset

Description부산광역시_노인요양시설현황_20220228
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15071152

Alerts

연번 is highly overall correlated with 구군High 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
연번 has unique valuesUnique
장기요양기관 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:20:14.626657
Analysis finished2024-03-13 13:20:18.187547
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58
Minimum1
Maximum115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:18.285619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q129.5
median58
Q386.5
95-th percentile109.3
Maximum115
Range114
Interquartile range (IQR)57

Descriptive statistics

Standard deviation33.341666
Coefficient of variation (CV)0.5748563
Kurtosis-1.2
Mean58
Median Absolute Deviation (MAD)29
Skewness0
Sum6670
Variance1111.6667
MonotonicityStrictly increasing
2024-03-13T22:20:18.473956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
74 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%

구군
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
기장군
19 
해운대구
11 
사하구
11 
북구
10 
부산진구
8 
Other values (11)
56 

Length

Max length4
Median length3
Mean length2.9652174
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기장군 19
16.5%
해운대구 11
9.6%
사하구 11
9.6%
북구 10
8.7%
부산진구 8
 
7.0%
금정구 8
 
7.0%
연제구 8
 
7.0%
사상구 8
 
7.0%
동래구 7
 
6.1%
수영구 5
 
4.3%
Other values (6) 20
17.4%

Length

2024-03-13T22:20:18.634132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기장군 19
16.5%
해운대구 11
9.6%
사하구 11
9.6%
북구 10
8.7%
부산진구 8
 
7.0%
금정구 8
 
7.0%
연제구 8
 
7.0%
사상구 8
 
7.0%
동래구 7
 
6.1%
수영구 5
 
4.3%
Other values (6) 20
17.4%

급여종류
Categorical

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
노인요양시설
93 
노인요양공동생활가정
22 

Length

Max length10
Median length6
Mean length6.7652174
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인요양시설 93
80.9%
노인요양공동생활가정 22
 
19.1%

Length

2024-03-13T22:20:18.792915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:20:18.924833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인요양시설 93
80.9%
노인요양공동생활가정 22
 
19.1%

장기요양기관
Text

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T22:20:19.184044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.0173913
Min length3

Characters and Unicode

Total characters922
Distinct characters173
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

Unique115 ?
Unique (%)100.0%

Sample

1st row송산노인전문요양원
2nd row굿모닝노인요양원
3rd row안나노인건강센터
4th row인창서구그린빌노인요양원
5th row실버웰요양센터
ValueCountFrequency (%)
집 4
 
2.9%
녹원요양원 3
 
2.2%
요양원 3
 
2.2%
노인요양원 2
 
1.4%
정다운 2
 
1.4%
안심노인건강센터 2
 
1.4%
정금나무집 1
 
0.7%
큰별요양원 1
 
0.7%
미루나무집 1
 
0.7%
보경요양원(실버홈 1
 
0.7%
Other values (118) 118
85.5%
2024-03-13T22:20:19.615313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 68
 
7.4%
요 66
 
7.2%
원 64
 
6.9%
인 56
 
6.1%
노 51
 
5.5%
터 26
 
2.8%
센 26
 
2.8%
버 26
 
2.8%
실 25
 
2.7%
23
 
2.5%
Other values (163) 491
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 891
96.6%
Space Separator 23
 
2.5%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 68
 
7.6%
요 66
 
7.4%
원 64
 
7.2%
인 56
 
6.3%
노 51
 
5.7%
터 26
 
2.9%
센 26
 
2.9%
버 26
 
2.9%
실 25
 
2.8%
홈 14
 
1.6%
Other values (160) 469
52.6%
Space Separator
ValueCountFrequency (%)
23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 891
96.6%
Common 31
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 68
 
7.6%
요 66
 
7.4%
원 64
 
7.2%
인 56
 
6.3%
노 51
 
5.7%
터 26
 
2.9%
센 26
 
2.9%
버 26
 
2.9%
실 25
 
2.8%
홈 14
 
1.6%
Other values (160) 469
52.6%
Common
ValueCountFrequency (%)
23
74.2%
( 4
 
12.9%
) 4
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 891
96.6%
ASCII 31
 
3.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 68
 
7.6%
요 66
 
7.4%
원 64
 
7.2%
인 56
 
6.3%
노 51
 
5.7%
터 26
 
2.9%
센 26
 
2.9%
버 26
 
2.9%
실 25
 
2.8%
홈 14
 
1.6%
Other values (160) 469
52.6%
ASCII
ValueCountFrequency (%)
23
74.2%
( 4
 
12.9%
) 4
 
12.9%

설립연도
Real number (ℝ)

Distinct26
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010
Minimum1940
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:20.057756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1940
5-th percentile1998.7
Q12008
median2010
Q32015
95-th percentile2020
Maximum2021
Range81
Interquartile range (IQR)7

Descriptive statistics

Standard deviation9.0611955
Coefficient of variation (CV)0.0045080574
Kurtosis30.762124
Mean2010
Median Absolute Deviation (MAD)3
Skewness-4.1997517
Sum231150
Variance82.105263
MonotonicityNot monotonic
2024-03-13T22:20:20.202148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2009 14
 
12.2%
2008 12
 
10.4%
2019 10
 
8.7%
2012 9
 
7.8%
2010 8
 
7.0%
2011 7
 
6.1%
2013 6
 
5.2%
2018 6
 
5.2%
2003 4
 
3.5%
2007 4
 
3.5%
Other values (16) 35
30.4%
ValueCountFrequency (%)
1940 1
 
0.9%
1986 1
 
0.9%
1997 1
 
0.9%
1998 3
2.6%
1999 1
 
0.9%
2001 2
1.7%
2002 2
1.7%
2003 4
3.5%
2004 3
2.6%
2005 2
1.7%
ValueCountFrequency (%)
2021 4
 
3.5%
2020 3
 
2.6%
2019 10
8.7%
2018 6
5.2%
2017 2
 
1.7%
2016 3
 
2.6%
2015 3
 
2.6%
2014 1
 
0.9%
2013 6
5.2%
2012 9
7.8%

연면적(제곱미터)
Real number (ℝ)

Distinct114
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1646.0869
Minimum107
Maximum6259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:20.424115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107
5-th percentile204.7
Q1504.5
median1252
Q32527
95-th percentile4009.8
Maximum6259
Range6152
Interquartile range (IQR)2022.5

Descriptive statistics

Standard deviation1350.9146
Coefficient of variation (CV)0.82068242
Kurtosis1.0164628
Mean1646.0869
Median Absolute Deviation (MAD)874
Skewness1.1080983
Sum189299.99
Variance1824970.1
MonotonicityNot monotonic
2024-03-13T22:20:20.656546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1460.0 2
 
1.7%
977.0 1
 
0.9%
197.0 1
 
0.9%
305.0 1
 
0.9%
186.42 1
 
0.9%
179.0 1
 
0.9%
373.0 1
 
0.9%
378.0 1
 
0.9%
386.0 1
 
0.9%
804.0 1
 
0.9%
Other values (104) 104
90.4%
ValueCountFrequency (%)
107.0 1
0.9%
179.0 1
0.9%
185.0 1
0.9%
186.42 1
0.9%
194.0 1
0.9%
197.0 1
0.9%
208.0 1
0.9%
211.6 1
0.9%
244.0 1
0.9%
259.0 1
0.9%
ValueCountFrequency (%)
6259.0 1
0.9%
6059.0 1
0.9%
5169.0 1
0.9%
4901.0 1
0.9%
4480.0 1
0.9%
4105.0 1
0.9%
3969.0 1
0.9%
3852.0 1
0.9%
3794.0 1
0.9%
3680.0 1
0.9%

전화번호
Text

Distinct113
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T22:20:20.901327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1380
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

Unique112 ?
Unique (%)97.4%

Sample

1st row051-466-0007
2nd row051-468-5688
3rd row051-245-0035
4th row051-255-0904
5th row051-242-8050
ValueCountFrequency (%)
051-862-3200 3
 
2.6%
051-466-0007 1
 
0.9%
051-292-3311 1
 
0.9%
051-751-0561 1
 
0.9%
051-752-8393 1
 
0.9%
051-752-2982 1
 
0.9%
051-865-9988 1
 
0.9%
051-868-9845 1
 
0.9%
051-710-0708 1
 
0.9%
051-868-0588 1
 
0.9%
Other values (103) 103
89.6%
2024-03-13T22:20:21.254068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 248
18.0%
- 230
16.7%
5 201
14.6%
1 200
14.5%
2 98
 
7.1%
8 90
 
6.5%
3 82
 
5.9%
7 81
 
5.9%
6 61
 
4.4%
9 46
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1150
83.3%
Dash Punctuation 230
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 248
21.6%
5 201
17.5%
1 200
17.4%
2 98
 
8.5%
8 90
 
7.8%
3 82
 
7.1%
7 81
 
7.0%
6 61
 
5.3%
9 46
 
4.0%
4 43
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1380
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 248
18.0%
- 230
16.7%
5 201
14.6%
1 200
14.5%
2 98
 
7.1%
8 90
 
6.5%
3 82
 
5.9%
7 81
 
5.9%
6 61
 
4.4%
9 46
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 248
18.0%
- 230
16.7%
5 201
14.6%
1 200
14.5%
2 98
 
7.1%
8 90
 
6.5%
3 82
 
5.9%
7 81
 
5.9%
6 61
 
4.4%
9 46
 
3.3%

주소
Text

Distinct111
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-03-13T22:20:21.539008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length39
Mean length30.043478
Min length20

Characters and Unicode

Total characters3455
Distinct characters191
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

Unique107 ?
Unique (%)93.0%

Sample

1st row 부산광역시 중구 충장대로13번길 31 (중앙동4가)
2nd row부산광역시 중구 대영로 235 (영주동)
3rd row 부산광역시 서구 꽃마을로163번길 94-16 (서대신동3가)
4th row 부산광역시 서구 대영로73번길 111 (동대신동3가)
5th row 부산광역시 서구 시약로 35 (서대신동3가)
ValueCountFrequency (%)
부산광역시 114
 
18.1%
기장군 19
 
3.0%
장안읍 13
 
2.1%
해운대구 11
 
1.7%
사하구 11
 
1.7%
북구 10
 
1.6%
기장읍 8
 
1.3%
부산진구 8
 
1.3%
사상구 8
 
1.3%
금정구 8
 
1.3%
Other values (290) 421
66.7%
2024-03-13T22:20:21.960584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
738
21.4%
산 136
 
3.9%
부 124
 
3.6%
광 121
 
3.5%
동 119
 
3.4%
시 118
 
3.4%
역 114
 
3.3%
( 110
 
3.2%
) 110
 
3.2%
구 99
 
2.9%
Other values (181) 1666
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1951
56.5%
Space Separator 738
 
21.4%
Decimal Number 495
 
14.3%
Open Punctuation 110
 
3.2%
Close Punctuation 110
 
3.2%
Dash Punctuation 27
 
0.8%
Other Punctuation 24
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 136
 
7.0%
부 124
 
6.4%
광 121
 
6.2%
동 119
 
6.1%
시 118
 
6.0%
역 114
 
5.8%
구 99
 
5.1%
로 98
 
5.0%
길 70
 
3.6%
번 59
 
3.0%
Other values (166) 893
45.8%
Decimal Number
ValueCountFrequency (%)
1 96
19.4%
2 64
12.9%
3 58
11.7%
5 46
9.3%
4 45
9.1%
7 44
8.9%
6 41
8.3%
8 37
 
7.5%
9 34
 
6.9%
0 30
 
6.1%
Space Separator
ValueCountFrequency (%)
738
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1951
56.5%
Common 1504
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 136
 
7.0%
부 124
 
6.4%
광 121
 
6.2%
동 119
 
6.1%
시 118
 
6.0%
역 114
 
5.8%
구 99
 
5.1%
로 98
 
5.0%
길 70
 
3.6%
번 59
 
3.0%
Other values (166) 893
45.8%
Common
ValueCountFrequency (%)
738
49.1%
( 110
 
7.3%
) 110
 
7.3%
1 96
 
6.4%
2 64
 
4.3%
3 58
 
3.9%
5 46
 
3.1%
4 45
 
3.0%
7 44
 
2.9%
6 41
 
2.7%
Other values (5) 152
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1951
56.5%
ASCII 1504
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
738
49.1%
( 110
 
7.3%
) 110
 
7.3%
1 96
 
6.4%
2 64
 
4.3%
3 58
 
3.9%
5 46
 
3.1%
4 45
 
3.0%
7 44
 
2.9%
6 41
 
2.7%
Other values (5) 152
 
10.1%
Hangul
ValueCountFrequency (%)
산 136
 
7.0%
부 124
 
6.4%
광 121
 
6.2%
동 119
 
6.1%
시 118
 
6.0%
역 114
 
5.8%
구 99
 
5.1%
로 98
 
5.0%
길 70
 
3.6%
번 59
 
3.0%
Other values (166) 893
45.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.18931
Minimum35.05039
Maximum35.379486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:22.097880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.05039
5-th percentile35.086184
Q135.134682
median35.181083
Q335.22838
95-th percentile35.337784
Maximum35.379486
Range0.3290966
Interquartile range (IQR)0.093698935

Descriptive statistics

Standard deviation0.074244916
Coefficient of variation (CV)0.0021098713
Kurtosis0.023884649
Mean35.18931
Median Absolute Deviation (MAD)0.04792484
Skewness0.63301349
Sum4046.7706
Variance0.0055123075
MonotonicityNot monotonic
2024-03-13T22:20:22.229050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17974113 3
 
2.6%
35.23156397 2
 
1.7%
35.22920006 2
 
1.7%
35.3794864 2
 
1.7%
35.14722597 2
 
1.7%
35.10820976 1
 
0.9%
35.09284604 1
 
0.9%
35.17008274 1
 
0.9%
35.17708282 1
 
0.9%
35.15111417 1
 
0.9%
Other values (99) 99
86.1%
ValueCountFrequency (%)
35.0503898 1
0.9%
35.0740233 1
0.9%
35.07660279 1
0.9%
35.07974049 1
0.9%
35.08123157 1
0.9%
35.08595082 1
0.9%
35.08628423 1
0.9%
35.08830952 1
0.9%
35.09039619 1
0.9%
35.09284604 1
0.9%
ValueCountFrequency (%)
35.3794864 2
1.7%
35.36665765 1
0.9%
35.35898651 1
0.9%
35.34448035 1
0.9%
35.34389738 1
0.9%
35.33516414 1
0.9%
35.32082326 1
0.9%
35.31518227 1
0.9%
35.3138049 1
0.9%
35.3122241 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.07884
Minimum128.86853
Maximum129.28363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:22.387629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.86853
5-th percentile128.97243
Q1129.01426
median129.07044
Q3129.11326
95-th percentile129.25819
Maximum129.28363
Range0.4151012
Interquartile range (IQR)0.09900135

Descriptive statistics

Standard deviation0.085982139
Coefficient of variation (CV)0.0006661211
Kurtosis0.11846099
Mean129.07884
Median Absolute Deviation (MAD)0.0510067
Skewness0.5319853
Sum14844.067
Variance0.0073929282
MonotonicityNot monotonic
2024-03-13T22:20:22.594677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0900311 3
 
2.6%
129.076696 2
 
1.7%
129.074929 2
 
1.7%
129.2602205 2
 
1.7%
129.045315 2
 
1.7%
129.0384099 1
 
0.9%
128.9088564 1
 
0.9%
129.0994963 1
 
0.9%
129.1038613 1
 
0.9%
129.1107205 1
 
0.9%
Other values (99) 99
86.1%
ValueCountFrequency (%)
128.8685299 1
0.9%
128.9088564 1
0.9%
128.9173604 1
0.9%
128.9238884 1
0.9%
128.9658567 1
0.9%
128.9719463 1
0.9%
128.9726353 1
0.9%
128.9767058 1
0.9%
128.9776688 1
0.9%
128.983366 1
0.9%
ValueCountFrequency (%)
129.2836311 1
0.9%
129.2771782 1
0.9%
129.2733574 1
0.9%
129.2614089 1
0.9%
129.2602205 2
1.7%
129.2573159 1
0.9%
129.2510753 1
0.9%
129.2413835 1
0.9%
129.2277195 1
0.9%
129.2262975 1
0.9%

Interactions

2024-03-13T22:20:17.322997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.073608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.580800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.255310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.794538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.404518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.160032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.684896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.350398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.896807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.512711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.277136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.865970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.460451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.028689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.605195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.375605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.993614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.576670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.127532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.700774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:15.486929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.128931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:16.694259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:17.231076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:20:22.752474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군급여종류설립연도연면적(제곱미터)위도경도
연번1.0000.9400.0000.2210.0000.7910.806
구군0.9401.0000.4810.3640.0350.8320.878
급여종류0.0000.4811.0000.4870.6610.3270.216
설립연도0.2210.3640.4871.0000.3490.1590.000
연면적(제곱미터)0.0000.0350.6610.3491.0000.2670.000
위도0.7910.8320.3270.1590.2671.0000.764
경도0.8060.8780.2160.0000.0000.7641.000
2024-03-13T22:20:22.867478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군급여종류
구군1.0000.353
급여종류0.3531.000
2024-03-13T22:20:22.945691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설립연도연면적(제곱미터)위도경도구군급여종류
연번1.000-0.037-0.0660.4610.3690.7310.000
설립연도-0.0371.000-0.322-0.1700.0150.1080.316
연면적(제곱미터)-0.066-0.3221.0000.117-0.1330.0000.495
위도0.461-0.1700.1171.0000.6720.5030.240
경도0.3690.015-0.1330.6721.0000.5810.166
구군0.7310.1080.0000.5030.5811.0000.353
급여종류0.0000.3160.4950.2400.1660.3531.000

Missing values

2024-03-13T22:20:17.838345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:20:18.072807image/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
01중구노인요양시설송산노인전문요양원20082862.0051-466-0007부산광역시 중구 충장대로13번길 31 (중앙동4가)35.10821129.03841
12중구노인요양시설굿모닝노인요양원20212318.96051-468-5688부산광역시 중구 대영로 235 (영주동)35.112594129.036441
23서구노인요양시설안나노인건강센터20053076.0051-245-0035부산광역시 서구 꽃마을로163번길 94-16 (서대신동3가)35.127712129.004667
34서구노인요양시설인창서구그린빌노인요양원20121329.0051-255-0904부산광역시 서구 대영로73번길 111 (동대신동3가)35.115147129.016536
45서구노인요양시설실버웰요양센터20131086.0051-242-8050부산광역시 서구 시약로 35 (서대신동3가)35.112564129.008485
56서구노인요양시설송도사랑요양원20191654.0051-255-3315부산광역시 서구 암남공원로 522 (암남동)35.07974129.012137
67동구노인요양시설인창동구노인요양원20104480.0051-464-1004부산광역시 동구 고관로 34 (초량동)35.122386129.042979
78동구노인요양시설송원노인전문요양원20083192.0051-637-8260부산광역시 동구 안창로 51 (범일동)35.145624129.043934
89동구노인요양공동생활가정지혜실버홈2013259.0051-751-8388부산광역시 동구 범곡남로 15 (범일동)35.138031129.054788
910영도구노인요양시설파랑새노인건강센터20033325.0051-412-5422부산광역시 영도구 와치로 78 (청학동)35.085951129.059599
연번구군급여종류장기요양기관설립연도연면적(제곱미터)전화번호주소위도경도
105106기장군노인요양시설기장노인의료센터20092403.0051-722-6500부산광역시 기장군 일광면 화전2길 86-25 (일광면)35.287127129.22772
106107기장군노인요양시설다인요양원20161463.0051-723-6636부산광역시 기장군 장안읍 오리길 376-28 (장안읍)35.34448129.277178
107108기장군노인요양시설반석노인건강센터20093078.0051-711-5000부산광역시 기장군 장안읍 못안길 47 (장안읍)35.379486129.260221
108109기장군노인요양시설백양원2015685.0051-727-3990부산광역시 기장군 일광면 칠암3길 14 (일광면)35.297269129.257316
109110기장군노인요양시설행복한어르신의집 노인요양원2012957.0051-728-9007부산광역시 기장군 장안읍 기장대로 1727 (장안읍, 행복한어르신의집)35.343897129.251075
110111기장군노인요양시설주사랑재활요양원2018919.0051-724-8181부산광역시 기장군 기장읍 연화길 62 (기장읍)35.219097129.226297
111112기장군노인요양시설하서 요양원2018799.0051-921-0777부산광역시 기장군 정관읍 구연3로 11 4,5,6층 (정관읍)35.320823129.181225
112113기장군노인요양공동생활가정해피케어 노인요양공동생활가정2018194.0051-508-2201부산광역시 기장군 철마면 강변길 20 (철마면)35.3075129.11201
113114기장군노인요양시설효산요양원20191460.0051-508-0675부산광역시 기장군 철마면 철마삼동로 103 (철마면)35.313805129.114505
114115기장군노인요양시설온누리요양원20142124.0051-714-0120부산광역시 기장군 장안읍 못안길 47 (장안읍)35.379486129.260221