Overview

Dataset statistics

Number of variables6
Number of observations67
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description동래구 관내 노인복지시설 현황에 대한 데이터로 구분, 시설명, 소재지, 정원, 전화번호, 비고 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/3079126/fileData.do

Alerts

비고 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 정원 and 1 other fieldsHigh correlation
정원 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly imbalanced (62.7%)Imbalance
비고 is highly imbalanced (62.7%)Imbalance
정원 has 1 (1.5%) missing valuesMissing
소재지 has unique valuesUnique
정원 has 45 (67.2%) zerosZeros

Reproduction

Analysis started2023-12-12 17:57:09.461615
Analysis finished2023-12-12 17:57:10.556169
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
재가노인 복지시설
57 
요양시설
8 
양로시설
 
1
노인복지관
 
1

Length

Max length9
Median length9
Mean length8.2686567
Min length4

Unique

Unique2 ?
Unique (%)3.0%

Sample

1st row양로시설
2nd row요양시설
3rd row요양시설
4th row요양시설
5th row요양시설

Common Values

ValueCountFrequency (%)
재가노인 복지시설 57
85.1%
요양시설 8
 
11.9%
양로시설 1
 
1.5%
노인복지관 1
 
1.5%

Length

2023-12-13T02:57:10.645016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:57:10.795281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인 57
46.0%
복지시설 57
46.0%
요양시설 8
 
6.5%
양로시설 1
 
0.8%
노인복지관 1
 
0.8%

시설명
Text

Distinct66
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-13T02:57:11.048043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length9.8208955
Min length5

Characters and Unicode

Total characters658
Distinct characters135
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)97.0%

Sample

1st row황전양로원
2nd row황전요양원
3rd row무량수노인요양원
4th row성지노인요양원
5th row안심노인종합복지센터
ValueCountFrequency (%)
노인복지센터 3
 
3.6%
안심노인종합복지센터 2
 
2.4%
복지센터 2
 
2.4%
동래구노인복지관 2
 
2.4%
재가노인복지센터 2
 
2.4%
편한재활주간보호센터 1
 
1.2%
부산열린재가복지센터 1
 
1.2%
다사랑재가복지센터 1
 
1.2%
선한이웃재가복지센터 1
 
1.2%
가득행복복지센터 1
 
1.2%
Other values (67) 67
80.7%
2023-12-13T02:57:11.573569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 55
 
8.4%
터 55
 
8.4%
복 47
 
7.1%
지 47
 
7.1%
재 36
 
5.5%
가 34
 
5.2%
노 22
 
3.3%
인 22
 
3.3%
16
 
2.4%
주 11
 
1.7%
Other values (125) 313
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 629
95.6%
Space Separator 16
 
2.4%
Decimal Number 6
 
0.9%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 55
 
8.7%
터 55
 
8.7%
복 47
 
7.5%
지 47
 
7.5%
재 36
 
5.7%
가 34
 
5.4%
노 22
 
3.5%
인 22
 
3.5%
주 11
 
1.7%
양 11
 
1.7%
Other values (116) 289
45.9%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
1 1
16.7%
5 1
16.7%
6 1
16.7%
3 1
16.7%
Space Separator
ValueCountFrequency (%)
16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 629
95.6%
Common 28
 
4.3%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 55
 
8.7%
터 55
 
8.7%
복 47
 
7.5%
지 47
 
7.5%
재 36
 
5.7%
가 34
 
5.4%
노 22
 
3.5%
인 22
 
3.5%
주 11
 
1.7%
양 11
 
1.7%
Other values (116) 289
45.9%
Common
ValueCountFrequency (%)
16
57.1%
( 3
 
10.7%
) 3
 
10.7%
0 2
 
7.1%
1 1
 
3.6%
5 1
 
3.6%
6 1
 
3.6%
3 1
 
3.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 629
95.6%
ASCII 29
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 55
 
8.7%
터 55
 
8.7%
복 47
 
7.5%
지 47
 
7.5%
재 36
 
5.7%
가 34
 
5.4%
노 22
 
3.5%
인 22
 
3.5%
주 11
 
1.7%
양 11
 
1.7%
Other values (116) 289
45.9%
ASCII
ValueCountFrequency (%)
16
55.2%
( 3
 
10.3%
) 3
 
10.3%
0 2
 
6.9%
A 1
 
3.4%
1 1
 
3.4%
5 1
 
3.4%
6 1
 
3.4%
3 1
 
3.4%

소재지
Text

UNIQUE 

Distinct67
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-13T02:57:11.951811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length37
Mean length29.61194
Min length23

Characters and Unicode

Total characters1984
Distinct characters95
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

Unique67 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 구만덕로172 (온천동)
2nd row부산광역시 동래구 구만덕로172 (온천동)
3rd row부산광역시 동래구 금정마을로59-6 (온천동)
4th row부산광역시 동래구 석사북로40-1 (사직동)
5th row부산광역시 동래구 충렬대로86번길5 (온천동)
ValueCountFrequency (%)
부산광역시 67
17.4%
동래구 67
17.4%
안락동 18
 
4.7%
온천동 15
 
3.9%
1층 13
 
3.4%
2층 10
 
2.6%
명장동 8
 
2.1%
사직동 7
 
1.8%
명륜동 7
 
1.8%
수안동 6
 
1.6%
Other values (130) 167
43.4%
2023-12-13T02:57:12.547117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
319
 
16.1%
동 142
 
7.2%
시 73
 
3.7%
래 72
 
3.6%
구 69
 
3.5%
1 68
 
3.4%
부 67
 
3.4%
) 67
 
3.4%
광 67
 
3.4%
역 67
 
3.4%
Other values (85) 973
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1150
58.0%
Decimal Number 322
 
16.2%
Space Separator 319
 
16.1%
Close Punctuation 67
 
3.4%
Open Punctuation 67
 
3.4%
Other Punctuation 50
 
2.5%
Dash Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 142
 
12.3%
시 73
 
6.3%
래 72
 
6.3%
구 69
 
6.0%
부 67
 
5.8%
광 67
 
5.8%
역 67
 
5.8%
산 67
 
5.8%
로 67
 
5.8%
번 39
 
3.4%
Other values (70) 420
36.5%
Decimal Number
ValueCountFrequency (%)
1 68
21.1%
2 56
17.4%
3 35
10.9%
0 30
9.3%
6 29
9.0%
4 26
 
8.1%
5 22
 
6.8%
9 21
 
6.5%
7 19
 
5.9%
8 16
 
5.0%
Space Separator
ValueCountFrequency (%)
319
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1150
58.0%
Common 834
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 142
 
12.3%
시 73
 
6.3%
래 72
 
6.3%
구 69
 
6.0%
부 67
 
5.8%
광 67
 
5.8%
역 67
 
5.8%
산 67
 
5.8%
로 67
 
5.8%
번 39
 
3.4%
Other values (70) 420
36.5%
Common
ValueCountFrequency (%)
319
38.2%
1 68
 
8.2%
) 67
 
8.0%
( 67
 
8.0%
2 56
 
6.7%
, 50
 
6.0%
3 35
 
4.2%
0 30
 
3.6%
6 29
 
3.5%
4 26
 
3.1%
Other values (5) 87
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1150
58.0%
ASCII 834
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
319
38.2%
1 68
 
8.2%
) 67
 
8.0%
( 67
 
8.0%
2 56
 
6.7%
, 50
 
6.0%
3 35
 
4.2%
0 30
 
3.6%
6 29
 
3.5%
4 26
 
3.1%
Other values (5) 87
 
10.4%
Hangul
ValueCountFrequency (%)
동 142
 
12.3%
시 73
 
6.3%
래 72
 
6.3%
구 69
 
6.0%
부 67
 
5.8%
광 67
 
5.8%
역 67
 
5.8%
산 67
 
5.8%
로 67
 
5.8%
번 39
 
3.4%
Other values (70) 420
36.5%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)28.8%
Missing1
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean14.80303
Minimum0
Maximum120
Zeros45
Zeros (%)67.2%
Negative0
Negative (%)0.0%
Memory size735.0 B
2023-12-13T02:57:12.709294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q324.25
95-th percentile79.25
Maximum120
Range120
Interquartile range (IQR)24.25

Descriptive statistics

Standard deviation27.153252
Coefficient of variation (CV)1.8343036
Kurtosis3.75223
Mean14.80303
Median Absolute Deviation (MAD)0
Skewness2.0383912
Sum977
Variance737.29907
MonotonicityNot monotonic
2023-12-13T02:57:12.848780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 45
67.2%
49 2
 
3.0%
22 2
 
3.0%
27 2
 
3.0%
88 1
 
1.5%
77 1
 
1.5%
46 1
 
1.5%
30 1
 
1.5%
28 1
 
1.5%
68 1
 
1.5%
Other values (9) 9
 
13.4%
ValueCountFrequency (%)
0 45
67.2%
9 1
 
1.5%
13 1
 
1.5%
22 2
 
3.0%
25 1
 
1.5%
27 2
 
3.0%
28 1
 
1.5%
30 1
 
1.5%
31 1
 
1.5%
39 1
 
1.5%
ValueCountFrequency (%)
120 1
1.5%
88 1
1.5%
84 1
1.5%
80 1
1.5%
77 1
1.5%
68 1
1.5%
49 2
3.0%
46 1
1.5%
43 1
1.5%
39 1
1.5%

전화번호
Text

Distinct66
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size668.0 B
2023-12-13T02:57:13.113384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters804
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

Unique65 ?
Unique (%)97.0%

Sample

1st row051-556-3373
2nd row051-554-6661
3rd row051-552-7900
4th row051-506-0033
5th row051-503-0002
ValueCountFrequency (%)
051-503-0002 2
 
3.0%
051-751-7988 1
 
1.5%
051-557-4919 1
 
1.5%
051-558-0707 1
 
1.5%
051-507-6753 1
 
1.5%
051-529-3334 1
 
1.5%
051-710-5776 1
 
1.5%
051-522-3356 1
 
1.5%
051-555-9194 1
 
1.5%
051-555-1878 1
 
1.5%
Other values (56) 56
83.6%
2023-12-13T02:57:13.499023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 192
23.9%
- 134
16.7%
0 119
14.8%
1 98
12.2%
7 54
 
6.7%
2 51
 
6.3%
3 46
 
5.7%
8 33
 
4.1%
4 32
 
4.0%
9 24
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 670
83.3%
Dash Punctuation 134
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 192
28.7%
0 119
17.8%
1 98
14.6%
7 54
 
8.1%
2 51
 
7.6%
3 46
 
6.9%
8 33
 
4.9%
4 32
 
4.8%
9 24
 
3.6%
6 21
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 192
23.9%
- 134
16.7%
0 119
14.8%
1 98
12.2%
7 54
 
6.7%
2 51
 
6.3%
3 46
 
5.7%
8 33
 
4.1%
4 32
 
4.0%
9 24
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 192
23.9%
- 134
16.7%
0 119
14.8%
1 98
12.2%
7 54
 
6.7%
2 51
 
6.3%
3 46
 
5.7%
8 33
 
4.1%
4 32
 
4.0%
9 24
 
3.0%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size668.0 B
재가노인복지
57 
노인의료복지
8 
노인주거복지
 
1
노인여가복지
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique2 ?
Unique (%)3.0%

Sample

1st row노인주거복지
2nd row노인의료복지
3rd row노인의료복지
4th row노인의료복지
5th row노인의료복지

Common Values

ValueCountFrequency (%)
재가노인복지 57
85.1%
노인의료복지 8
 
11.9%
노인주거복지 1
 
1.5%
노인여가복지 1
 
1.5%

Length

2023-12-13T02:57:13.669220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:57:13.801460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지 57
85.1%
노인의료복지 8
 
11.9%
노인주거복지 1
 
1.5%
노인여가복지 1
 
1.5%

Interactions

2023-12-13T02:57:09.899128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:57:13.912310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설명소재지정원전화번호비고
구분1.0000.7271.0000.9870.7271.000
시설명0.7271.0001.0000.0001.0000.727
소재지1.0001.0001.0001.0001.0001.000
정원0.9870.0001.0001.0000.0000.987
전화번호0.7271.0001.0000.0001.0000.727
비고1.0000.7271.0000.9870.7271.000
2023-12-13T02:57:14.029387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고구분
비고1.0001.000
구분1.0001.000
2023-12-13T02:57:14.126694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원구분비고
정원1.0000.8210.821
구분0.8211.0001.000
비고0.8211.0001.000

Missing values

2023-12-13T02:57:10.379433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:57:10.502094image/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

구분시설명소재지정원전화번호비고
0양로시설황전양로원부산광역시 동래구 구만덕로172 (온천동)88051-556-3373노인주거복지
1요양시설황전요양원부산광역시 동래구 구만덕로172 (온천동)84051-554-6661노인의료복지
2요양시설무량수노인요양원부산광역시 동래구 금정마을로59-6 (온천동)120051-552-7900노인의료복지
3요양시설성지노인요양원부산광역시 동래구 석사북로40-1 (사직동)9051-506-0033노인의료복지
4요양시설안심노인종합복지센터부산광역시 동래구 충렬대로86번길5 (온천동)13051-503-0002노인의료복지
5요양시설원광효마을요양원부산광역시 동래구 명륜로207번길 6(명륜동)49051-554-4438노인의료복지
6요양시설늘봄실버요양센터부산광역시 동래구 시실로 107번가길 23 (명장동)80051-529-0701노인의료복지
7요양시설대열실버센터부산광역시 동래구 명륜로 147, 7층 (명륜동)25051-557-0070노인의료복지
8요양시설우하요양원부산광역시 동래구 명륜로112번길 60 (수안동)49051-558-2477노인의료복지
9노인복지관동래구노인복지관부산광역시 동래구 명륜로207번길18 (명륜동)<NA>051-554-6252노인여가복지
구분시설명소재지정원전화번호비고
57재가노인 복지시설100세누리 재가복지센터부산광역시 동래구 명서로 169, 1층 (명장동)0051-526-5006재가노인복지
58재가노인 복지시설다함께통합재가복지센터부산광역시 동래구 명륜로94번길 16, 303호 (수안동)0051-715-7572재가노인복지
59재가노인 복지시설보담실버케어센터부산광역시 동래구 충렬대로 502 (안락동)0051-523-0555재가노인복지
60재가노인 복지시설맘편한 재가노인복지센터부산광역시 동래구 중앙대로1333번길 14, 1층 (온천동)0051-558-9447재가노인복지
61재가노인 복지시설주식회사 동부산재활주간보호센터부산광역시 동래구 안연로109번길 24, 3층 (안락동)46051-523-3435재가노인복지
62재가노인 복지시설동래구노인복지관 노인복지센터부산광역시 동래구 명륜로207번길 18 (명륜동)22051-714-2888재가노인복지
63재가노인 복지시설손잡이 복지센터부산광역시 동래구 금강로74번길 2, 2층 (온천동)0051-552-3813재가노인복지
64재가노인 복지시설(주)실로암재가노인복지센터부산광역시 동래구 연안로59번길 83-4, 1층 (안락동)0051-528-1233재가노인복지
65재가노인 복지시설한마음복지용구부산광역시 동래구 금강로8번길 89, 1층 (온천동)0051-557-4919재가노인복지
66재가노인 복지시설착한재가복지센터부산광역시 동래구 충렬대로 334, 2층 (안락동)0051-556-6003재가노인복지