Overview

Dataset statistics

Number of variables10
Number of observations121
Missing cells0
Missing cells (%)0.0%
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_20230321
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 13:20:04.506521
Analysis finished2024-03-13 13:20:08.465422
Duration3.96 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
2024-03-13T22:20:08.553429image/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
2024-03-13T22:20:08.716082image/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 
사하구
13 
북구
11 
해운대구
10 
사상구
9 
Other values (11)
58 

Length

Max length4
Median length3
Mean length2.9504132
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기장군 20
16.5%
사하구 13
10.7%
북구 11
9.1%
해운대구 10
8.3%
사상구 9
7.4%
부산진구 8
 
6.6%
동래구 8
 
6.6%
금정구 8
 
6.6%
연제구 8
 
6.6%
수영구 6
 
5.0%
Other values (6) 20
16.5%

Length

2024-03-13T22:20:08.891643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기장군 20
16.5%
사하구 13
10.7%
북구 11
9.1%
해운대구 10
8.3%
사상구 9
7.4%
부산진구 8
 
6.6%
동래구 8
 
6.6%
금정구 8
 
6.6%
연제구 8
 
6.6%
수영구 6
 
5.0%
Other values (6) 20
16.5%

급여종류
Categorical

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

2024-03-13T22:20:09.113167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:20:09.289424image/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
2024-03-13T22:20:09.534297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.0743802
Min length3

Characters and Unicode

Total characters977
Distinct characters175
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 row송산노인전문요양원
2nd row굿모닝노인요양원
3rd row안나노인건강센터
4th row인창서구그린빌노인요양원
5th row실버웰요양센터
ValueCountFrequency (%)
요양원 3
 
2.1%
녹원요양원 3
 
2.1%
집 3
 
2.1%
정다운 2
 
1.4%
노인요양원 2
 
1.4%
함박꽃나무집 1
 
0.7%
큰별요양원 1
 
0.7%
미루나무집 1
 
0.7%
정금나무집 1
 
0.7%
보경요양원(실버홈 1
 
0.7%
Other values (124) 124
87.3%
2024-03-13T22:20:10.031514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 76
 
7.8%
요 74
 
7.6%
원 70
 
7.2%
인 58
 
5.9%
노 53
 
5.4%
버 28
 
2.9%
실 27
 
2.8%
터 25
 
2.6%
센 25
 
2.6%
21
 
2.1%
Other values (165) 520
53.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 948
97.0%
Space Separator 21
 
2.1%
Open Punctuation 4
 
0.4%
Close Punctuation 4
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.4%
인 58
 
6.1%
노 53
 
5.6%
버 28
 
3.0%
실 27
 
2.8%
터 25
 
2.6%
센 25
 
2.6%
홈 15
 
1.6%
Other values (162) 497
52.4%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 948
97.0%
Common 29
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.4%
인 58
 
6.1%
노 53
 
5.6%
버 28
 
3.0%
실 27
 
2.8%
터 25
 
2.6%
센 25
 
2.6%
홈 15
 
1.6%
Other values (162) 497
52.4%
Common
ValueCountFrequency (%)
21
72.4%
( 4
 
13.8%
) 4
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 948
97.0%
ASCII 29
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 76
 
8.0%
요 74
 
7.8%
원 70
 
7.4%
인 58
 
6.1%
노 53
 
5.6%
버 28
 
3.0%
실 27
 
2.8%
터 25
 
2.6%
센 25
 
2.6%
홈 15
 
1.6%
Other values (162) 497
52.4%
ASCII
ValueCountFrequency (%)
21
72.4%
( 4
 
13.8%
) 4
 
13.8%

설립연도
Real number (ℝ)

Distinct28
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010.8099
Minimum1940
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:10.172041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1940
5-th percentile1999
Q12008
median2011
Q32017
95-th percentile2021
Maximum2023
Range83
Interquartile range (IQR)9

Descriptive statistics

Standard deviation9.3205097
Coefficient of variation (CV)0.0046352018
Kurtosis27.073959
Mean2010.8099
Median Absolute Deviation (MAD)4
Skewness-3.7837114
Sum243308
Variance86.871901
MonotonicityNot monotonic
2024-03-13T22:20:10.297766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2009 14
 
11.6%
2008 11
 
9.1%
2019 10
 
8.3%
2012 9
 
7.4%
2010 8
 
6.6%
2013 7
 
5.8%
2021 6
 
5.0%
2011 5
 
4.1%
2018 5
 
4.1%
2003 4
 
3.3%
Other values (18) 42
34.7%
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 2
 
1.7%
2022 4
 
3.3%
2021 6
5.0%
2020 3
 
2.5%
2019 10
8.3%
2018 5
4.1%
2017 3
 
2.5%
2016 3
 
2.5%
2015 3
 
2.5%
2014 1
 
0.8%

연면적(제곱미터)
Real number (ℝ)

Distinct120
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1615.1134
Minimum107
Maximum6259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:10.449371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum107
5-th percentile197
Q1491
median1252
Q32392
95-th percentile3969
Maximum6259
Range6152
Interquartile range (IQR)1901

Descriptive statistics

Standard deviation1330.542
Coefficient of variation (CV)0.82380715
Kurtosis1.1786237
Mean1615.1134
Median Absolute Deviation (MAD)872
Skewness1.1453565
Sum195428.72
Variance1770341.9
MonotonicityNot monotonic
2024-03-13T22:20:10.589315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1460.0 2
 
1.7%
2862.0 1
 
0.8%
3322.0 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%
179.0 1
 
0.8%
373.0 1
 
0.8%
Other values (110) 110
90.9%
ValueCountFrequency (%)
107.0 1
0.8%
179.0 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%
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

Distinct119
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:10.843208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1452
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

Unique118 ?
Unique (%)97.5%

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
 
2.5%
051-310-7500 1
 
0.8%
051-973-9201 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%
051-868-9845 1
 
0.8%
051-710-0708 1
 
0.8%
Other values (109) 109
90.1%
2024-03-13T22:20:11.243180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 263
18.1%
- 242
16.7%
5 211
14.5%
1 208
14.3%
2 108
7.4%
8 93
 
6.4%
3 88
 
6.1%
7 83
 
5.7%
6 61
 
4.2%
4 48
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1210
83.3%
Dash Punctuation 242
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 263
21.7%
5 211
17.4%
1 208
17.2%
2 108
8.9%
8 93
 
7.7%
3 88
 
7.3%
7 83
 
6.9%
6 61
 
5.0%
4 48
 
4.0%
9 47
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 263
18.1%
- 242
16.7%
5 211
14.5%
1 208
14.3%
2 108
7.4%
8 93
 
6.4%
3 88
 
6.1%
7 83
 
5.7%
6 61
 
4.2%
4 48
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 263
18.1%
- 242
16.7%
5 211
14.5%
1 208
14.3%
2 108
7.4%
8 93
 
6.4%
3 88
 
6.1%
7 83
 
5.7%
6 61
 
4.2%
4 48
 
3.3%

주소
Text

Distinct117
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-13T22:20:11.654650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length29.85124
Min length20

Characters and Unicode

Total characters3612
Distinct characters192
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

Unique113 ?
Unique (%)93.4%

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 120
 
18.3%
기장군 20
 
3.1%
장안읍 13
 
2.0%
사하구 13
 
2.0%
북구 11
 
1.7%
해운대구 10
 
1.5%
기장읍 9
 
1.4%
사상구 9
 
1.4%
부산진구 8
 
1.2%
연제구 8
 
1.2%
Other values (303) 433
66.2%
2024-03-13T22:20:12.194648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
747
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%
구 106
 
2.9%
Other values (182) 1757
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2057
56.9%
Space Separator 747
 
20.7%
Decimal Number 518
 
14.3%
Open Punctuation 116
 
3.2%
Close Punctuation 116
 
3.2%
Other Punctuation 30
 
0.8%
Dash Punctuation 28
 
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 103
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (167) 944
45.9%
Decimal Number
ValueCountFrequency (%)
1 106
20.5%
2 65
12.5%
3 60
11.6%
5 48
9.3%
4 46
8.9%
6 43
8.3%
7 42
 
8.1%
8 39
 
7.5%
9 36
 
6.9%
0 33
 
6.4%
Space Separator
ValueCountFrequency (%)
747
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2057
56.9%
Common 1555
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 103
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (167) 944
45.9%
Common
ValueCountFrequency (%)
747
48.0%
( 116
 
7.5%
) 116
 
7.5%
1 106
 
6.8%
2 65
 
4.2%
3 60
 
3.9%
5 48
 
3.1%
4 46
 
3.0%
6 43
 
2.8%
7 42
 
2.7%
Other values (5) 166
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2057
56.9%
ASCII 1555
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
747
48.0%
( 116
 
7.5%
) 116
 
7.5%
1 106
 
6.8%
2 65
 
4.2%
3 60
 
3.9%
5 48
 
3.1%
4 46
 
3.0%
6 43
 
2.8%
7 42
 
2.7%
Other values (5) 166
 
10.7%
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 103
 
5.0%
길 73
 
3.5%
번 61
 
3.0%
Other values (167) 944
45.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.188051
Minimum35.05039
Maximum35.379486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:12.686969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.05039
5-th percentile35.085951
Q135.131332
median35.180472
Q335.220501
95-th percentile35.335164
Maximum35.379486
Range0.3290966
Interquartile range (IQR)0.08916847

Descriptive statistics

Standard deviation0.073945422
Coefficient of variation (CV)0.0021014356
Kurtosis0.083469085
Mean35.188051
Median Absolute Deviation (MAD)0.04728067
Skewness0.63177442
Sum4257.7541
Variance0.0054679255
MonotonicityNot monotonic
2024-03-13T22:20:12.842970image/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%
35.3794864 2
 
1.7%
35.10820976 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 (105) 105
86.8%
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 2
1.7%
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%
35.329257 1
0.8%
35.32082326 1
0.8%
35.31518227 1
0.8%
35.3138049 1
0.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct115
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.07695
Minimum128.86853
Maximum129.28363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-03-13T22:20:12.989860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.86853
5-th percentile128.97264
Q1129.01119
median129.06877
Q3129.111
95-th percentile129.25732
Maximum129.28363
Range0.4151012
Interquartile range (IQR)0.0998047

Descriptive statistics

Standard deviation0.086503565
Coefficient of variation (CV)0.00067017049
Kurtosis0.01572245
Mean129.07695
Median Absolute Deviation (MAD)0.0533171
Skewness0.55543558
Sum15618.311
Variance0.0074828667
MonotonicityNot monotonic
2024-03-13T22:20:13.129013image/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%
129.2602205 2
 
1.7%
129.0384099 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 (105) 105
86.8%
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 2
1.7%
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

2024-03-13T22:20:07.347668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:04.961295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.459934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.049823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.590689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:07.547499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.040876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.605007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.143257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.775373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:07.770889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.138484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.701479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.235604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.965699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:07.904489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.234622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.815330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.339883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:07.074304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:08.016585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.338816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:05.944495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:06.442825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:20:07.188441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:20:13.237373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구군급여종류설립연도연면적(제곱미터)위도경도
연번1.0000.9470.0000.3880.2180.8030.824
구군0.9471.0000.3830.3680.1990.8350.882
급여종류0.0000.3831.0000.3270.6510.3180.000
설립연도0.3880.3680.3271.0000.5760.0000.000
연면적(제곱미터)0.2180.1990.6510.5761.0000.1400.000
위도0.8030.8350.3180.0000.1401.0000.771
경도0.8240.8820.0000.0000.0000.7711.000
2024-03-13T22:20:13.385331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구군급여종류
구군1.0000.281
급여종류0.2811.000
2024-03-13T22:20:13.487963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설립연도연면적(제곱미터)위도경도구군급여종류
연번1.0000.023-0.0520.4390.3610.7430.000
설립연도0.0231.000-0.351-0.166-0.0130.1410.385
연면적(제곱미터)-0.052-0.3511.0000.150-0.0710.0690.488
위도0.439-0.1660.1501.0000.6770.5090.234
경도0.361-0.013-0.0710.6771.0000.5910.000
구군0.7430.1410.0690.5090.5911.0000.281
급여종류0.0000.3850.4880.2340.0000.2811.000

Missing values

2024-03-13T22:20:08.181583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:20:08.379200image/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
111112기장군노인요양시설반석노인건강센터20093078.0051-711-5000부산광역시 기장군 장안읍 못안길 47 (장안읍)35.379486129.260221
112113기장군노인요양시설백양원2015685.0051-727-3990부산광역시 기장군 일광면 칠암3길 14 (일광면)35.297269129.257316
113114기장군노인요양시설행복한어르신의집 노인요양원2012957.0051-728-9007부산광역시 기장군 장안읍 기장대로 1727 (장안읍, 행복한어르신의집)35.343897129.251075
114115기장군노인요양시설주사랑재활요양원2018919.0051-724-8181부산광역시 기장군 기장읍 연화길 62 (기장읍)35.219097129.226297
115116기장군노인요양시설하서 요양원2018799.0051-921-0777부산광역시 기장군 정관읍 구연3로 11 4,5,6층 (정관읍)35.320823129.181225
116117기장군노인요양공동생활가정해피케어 노인요양공동생활가정2018194.0051-508-2201부산광역시 기장군 철마면 강변길 20 (철마면)35.3075129.11201
117118기장군노인요양시설효산요양원20191460.0051-508-0675부산광역시 기장군 철마면 철마삼동로 103 (철마면)35.313805129.114505
118119기장군노인요양시설온누리요양원20142124.0051-714-0120부산광역시 기장군 장안읍 못안길 47 (장안읍)35.379486129.260221
119120기장군노인요양공동생활가정해강노인요양공동생활가정원2021196.08051-714-7454부산광역시 기장군 정관읍 용수1길 16-10, 1,2층(정관읍)35.329257129.174588
120121기장군노인요양시설해빛실버타운요양원20231898.16051-723-8006부산광역시 기장군 기장읍 내리길 168(기장읍)35.21706129.197861