Overview

Dataset statistics

Number of variables16
Number of observations10000
Missing cells7841
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory143.0 B

Variable types

Numeric7
Categorical5
Text3
DateTime1

Dataset

Description1. 2018년 ~ 2021년까지 노인장기요양기관의 평가결과- 급여종류별 3년 주기로 평가 수행 : (’18년) 시설 → (’19년) 재가_짝수 → ("20년) 재가_홀수 → ("21년) 시설** 코로나19로 인해 2021년 시설평가 연장으로 2022년까지 진행2. 평가구분, 장기요양기관기호, 장기요양기관명, 급여종류, 설립주체, 관할시도명, 관할시군구명, 평가일자, 평가등급, 평가총점*, 기관운영, 환경 및 안전, 수급자권리보장, 급여제공과정, 급여제공결과* 평가총점은 2021년도 정기평가부터 공개※ 민원인의 제공 신청에 따른 제공 건으로 2023.9.26. 기준 발췌자료, 기존 제공되던 ‘장기요양기관 평가등급 현황’ 데이터에서 설립주체, 평가총점 항목을 추가하여 ‘장기요양기관 평가 결과’로 목록명 변경
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15104801/fileData.do

Alerts

연번 is highly overall correlated with 평가구분High correlation
평가총점 is highly overall correlated with 기관운영 and 5 other fieldsHigh correlation
기관운영 is highly overall correlated with 평가총점 and 2 other fieldsHigh correlation
환경및안전 is highly overall correlated with 평가총점 and 1 other fieldsHigh correlation
수급자권리보장 is highly overall correlated with 평가총점 and 2 other fieldsHigh correlation
급여제공과정 is highly overall correlated with 평가총점 and 4 other fieldsHigh correlation
평가구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
급여종류 is highly overall correlated with 평가구분High correlation
평가등급 is highly overall correlated with 평가총점 and 1 other fieldsHigh correlation
설립주체 is highly imbalanced (54.7%)Imbalance
평가총점 has 7841 (78.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:59:36.689330
Analysis finished2023-12-12 02:59:47.682847
Duration10.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10247.793
Minimum1
Maximum20575
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:47.802423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile993.95
Q15075.75
median10224.5
Q315468.5
95-th percentile19506.05
Maximum20575
Range20574
Interquartile range (IQR)10392.75

Descriptive statistics

Standard deviation5948.5837
Coefficient of variation (CV)0.5804746
Kurtosis-1.2084665
Mean10247.793
Median Absolute Deviation (MAD)5195.5
Skewness0.0036713284
Sum1.0247793 × 108
Variance35385648
MonotonicityNot monotonic
2023-12-12T11:59:48.008168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8273 1
 
< 0.1%
10002 1
 
< 0.1%
14970 1
 
< 0.1%
1569 1
 
< 0.1%
2726 1
 
< 0.1%
16471 1
 
< 0.1%
16073 1
 
< 0.1%
8126 1
 
< 0.1%
5768 1
 
< 0.1%
12692 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
13 1
< 0.1%
15 1
< 0.1%
ValueCountFrequency (%)
20575 1
< 0.1%
20572 1
< 0.1%
20567 1
< 0.1%
20564 1
< 0.1%
20562 1
< 0.1%
20561 1
< 0.1%
20558 1
< 0.1%
20554 1
< 0.1%
20553 1
< 0.1%
20552 1
< 0.1%

평가구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2019년 정기평가
2927 
2020년 정기평가
2821 
2021년 정기평가
2159 
2018년 정기평가
2093 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019년 정기평가
2nd row2018년 정기평가
3rd row2020년 정기평가
4th row2021년 정기평가
5th row2019년 정기평가

Common Values

ValueCountFrequency (%)
2019년 정기평가 2927
29.3%
2020년 정기평가 2821
28.2%
2021년 정기평가 2159
21.6%
2018년 정기평가 2093
20.9%

Length

2023-12-12T11:59:48.183771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:59:48.327628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정기평가 10000
50.0%
2019년 2927
 
14.6%
2020년 2821
 
14.1%
2021년 2159
 
10.8%
2018년 2093
 
10.5%

장기요양기관기호
Text

Distinct8643
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:59:48.615973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters130000
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

Unique7321 ?
Unique (%)73.2%

Sample

1st row3-43130-00038
2nd row1-31710-00010
3rd row3-48120-00373
4th row1-29140-00009
5th row3-29200-00268
ValueCountFrequency (%)
3-41460-00286 5
 
< 0.1%
3-41590-00226 4
 
< 0.1%
2-44760-00002 3
 
< 0.1%
2-42830-00011 3
 
< 0.1%
3-28245-00138 3
 
< 0.1%
2-46780-00045 3
 
< 0.1%
3-47830-00010 3
 
< 0.1%
3-50130-00057 3
 
< 0.1%
3-42210-00037 3
 
< 0.1%
2-47250-00006 3
 
< 0.1%
Other values (8633) 9967
99.7%
2023-12-12T11:59:49.113116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36713
28.2%
- 20000
15.4%
1 19285
14.8%
3 11015
 
8.5%
4 10779
 
8.3%
2 9924
 
7.6%
7 5574
 
4.3%
5 4889
 
3.8%
8 4631
 
3.6%
6 4158
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 110000
84.6%
Dash Punctuation 20000
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 36713
33.4%
1 19285
17.5%
3 11015
 
10.0%
4 10779
 
9.8%
2 9924
 
9.0%
7 5574
 
5.1%
5 4889
 
4.4%
8 4631
 
4.2%
6 4158
 
3.8%
9 3032
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 36713
28.2%
- 20000
15.4%
1 19285
14.8%
3 11015
 
8.5%
4 10779
 
8.3%
2 9924
 
7.6%
7 5574
 
4.3%
5 4889
 
3.8%
8 4631
 
3.6%
6 4158
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36713
28.2%
- 20000
15.4%
1 19285
14.8%
3 11015
 
8.5%
4 10779
 
8.3%
2 9924
 
7.6%
7 5574
 
4.3%
5 4889
 
3.8%
8 4631
 
3.6%
6 4158
 
3.2%

장기요양기관명
Text

Distinct7539
Distinct (%)75.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:59:49.831902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length8.7529
Min length1

Characters and Unicode

Total characters87529
Distinct characters678
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5857 ?
Unique (%)58.6%

Sample

1st row아가페노인요양센터
2nd row효도의집
3rd row친절한방문요양센터
4th row평강의집
5th row다원 노인지원복지센터
ValueCountFrequency (%)
노인복지센터 107
 
0.9%
요양원 93
 
0.8%
집 86
 
0.7%
재가복지센터 72
 
0.6%
재가노인복지센터 57
 
0.5%
방문요양센터 48
 
0.4%
노인요양공동생활가정 39
 
0.3%
노인요양원 29
 
0.2%
재가장기요양기관 29
 
0.2%
노인요양시설 27
 
0.2%
Other values (7677) 11040
95.0%
2023-12-12T11:59:50.392627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 5257
 
6.0%
터 5229
 
6.0%
양 4403
 
5.0%
요 4211
 
4.8%
복 3865
 
4.4%
지 3803
 
4.3%
인 3602
 
4.1%
노 3457
 
3.9%
원 3182
 
3.6%
가 2680
 
3.1%
Other values (668) 47840
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83853
95.8%
Space Separator 1627
 
1.9%
Decimal Number 499
 
0.6%
Close Punctuation 412
 
0.5%
Open Punctuation 410
 
0.5%
Uppercase Letter 330
 
0.4%
Other Punctuation 182
 
0.2%
Lowercase Letter 104
 
0.1%
Math Symbol 86
 
0.1%
Dash Punctuation 19
 
< 0.1%
Other values (2) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 5257
 
6.3%
터 5229
 
6.2%
양 4403
 
5.3%
요 4211
 
5.0%
복 3865
 
4.6%
지 3803
 
4.5%
인 3602
 
4.3%
노 3457
 
4.1%
원 3182
 
3.8%
가 2680
 
3.2%
Other values (595) 44164
52.7%
Uppercase Letter
ValueCountFrequency (%)
A 150
45.5%
C 31
 
9.4%
I 19
 
5.8%
P 15
 
4.5%
S 14
 
4.2%
W 11
 
3.3%
N 10
 
3.0%
V 10
 
3.0%
O 8
 
2.4%
B 7
 
2.1%
Other values (12) 55
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 34
32.7%
o 10
 
9.6%
r 8
 
7.7%
h 7
 
6.7%
n 6
 
5.8%
i 6
 
5.8%
w 5
 
4.8%
a 5
 
4.8%
c 3
 
2.9%
k 3
 
2.9%
Other values (11) 17
16.3%
Decimal Number
ValueCountFrequency (%)
2 166
33.3%
1 148
29.7%
3 54
 
10.8%
0 51
 
10.2%
5 20
 
4.0%
6 17
 
3.4%
4 16
 
3.2%
8 14
 
2.8%
9 12
 
2.4%
7 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
" 102
56.0%
' 43
23.6%
. 22
 
12.1%
· 9
 
4.9%
& 3
 
1.6%
/ 2
 
1.1%
: 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 408
99.0%
」 2
 
0.5%
］ 1
 
0.2%
] 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 406
99.0%
「 2
 
0.5%
［ 1
 
0.2%
[ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1627
100.0%
Math Symbol
ValueCountFrequency (%)
+ 86
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83842
95.8%
Common 3235
 
3.7%
Latin 439
 
0.5%
Han 12
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 5257
 
6.3%
터 5229
 
6.2%
양 4403
 
5.3%
요 4211
 
5.0%
복 3865
 
4.6%
지 3803
 
4.5%
인 3602
 
4.3%
노 3457
 
4.1%
원 3182
 
3.8%
가 2680
 
3.2%
Other values (591) 44153
52.7%
Latin
ValueCountFrequency (%)
A 150
34.2%
e 34
 
7.7%
C 31
 
7.1%
I 19
 
4.3%
P 15
 
3.4%
S 14
 
3.2%
W 11
 
2.5%
N 10
 
2.3%
o 10
 
2.3%
V 10
 
2.3%
Other values (33) 135
30.8%
Common
ValueCountFrequency (%)
1627
50.3%
) 408
 
12.6%
( 406
 
12.6%
2 166
 
5.1%
1 148
 
4.6%
" 102
 
3.2%
+ 86
 
2.7%
3 54
 
1.7%
0 51
 
1.6%
' 43
 
1.3%
Other values (18) 144
 
4.5%
Han
ValueCountFrequency (%)
孝 6
50.0%
愛 3
25.0%
美 1
 
8.3%
蜂 1
 
8.3%
加 1
 
8.3%
Greek
ValueCountFrequency (%)
α 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83840
95.8%
ASCII 3653
 
4.2%
None 17
 
< 0.1%
CJK 12
 
< 0.1%
Number Forms 6
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 5257
 
6.3%
터 5229
 
6.2%
양 4403
 
5.3%
요 4211
 
5.0%
복 3865
 
4.6%
지 3803
 
4.5%
인 3602
 
4.3%
노 3457
 
4.1%
원 3182
 
3.8%
가 2680
 
3.2%
Other values (589) 44151
52.7%
ASCII
ValueCountFrequency (%)
1627
44.5%
) 408
 
11.2%
( 406
 
11.1%
2 166
 
4.5%
A 150
 
4.1%
1 148
 
4.1%
" 102
 
2.8%
+ 86
 
2.4%
3 54
 
1.5%
0 51
 
1.4%
Other values (55) 455
 
12.5%
None
ValueCountFrequency (%)
· 9
52.9%
」 2
 
11.8%
「 2
 
11.8%
［ 1
 
5.9%
］ 1
 
5.9%
α 1
 
5.9%
㈜ 1
 
5.9%
CJK
ValueCountFrequency (%)
孝 6
50.0%
愛 3
25.0%
美 1
 
8.3%
蜂 1
 
8.3%
加 1
 
8.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

급여종류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
04.방문요양
3328 
01.입소시설30인이상
1614 
03.입소시설10인미만
1353 
02.입소시설10이상30인미만
1285 
07.주야간보호
1149 
Other values (4)
1271 

Length

Max length16
Median length12
Mean length9.7549
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row04.방문요양
2nd row01.입소시설30인이상
3rd row04.방문요양
4th row01.입소시설30인이상
5th row04.방문요양

Common Values

ValueCountFrequency (%)
04.방문요양 3328
33.3%
01.입소시설30인이상 1614
16.1%
03.입소시설10인미만 1353
13.5%
02.입소시설10이상30인미만 1285
 
12.8%
07.주야간보호 1149
 
11.5%
05.방문목욕 654
 
6.5%
09.복지용구 468
 
4.7%
06.방문간호 114
 
1.1%
08.단기보호 35
 
0.4%

Length

2023-12-12T11:59:50.599962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:59:50.828840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
04.방문요양 3328
33.3%
01.입소시설30인이상 1614
16.1%
03.입소시설10인미만 1353
13.5%
02.입소시설10이상30인미만 1285
 
12.8%
07.주야간보호 1149
 
11.5%
05.방문목욕 654
 
6.5%
09.복지용구 468
 
4.7%
06.방문간호 114
 
1.1%
08.단기보호 35
 
0.4%

설립주체
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개인
7593 
법인
2212 
지방자치단체
 
166
기타
 
29

Length

Max length6
Median length2
Mean length2.0664
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row법인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 7593
75.9%
법인 2212
 
22.1%
지방자치단체 166
 
1.7%
기타 29
 
0.3%

Length

2023-12-12T11:59:51.044823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:59:51.206264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 7593
75.9%
법인 2212
 
22.1%
지방자치단체 166
 
1.7%
기타 29
 
0.3%

관할시도명
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
2404 
서울특별시
1329 
경상북도
733 
경상남도
611 
인천광역시
610 
Other values (12)
4313 

Length

Max length7
Median length5
Mean length4.2928
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청북도
2nd row울산광역시
3rd row경상남도
4th row광주광역시
5th row광주광역시

Common Values

ValueCountFrequency (%)
경기도 2404
24.0%
서울특별시 1329
13.3%
경상북도 733
 
7.3%
경상남도 611
 
6.1%
인천광역시 610
 
6.1%
충청남도 579
 
5.8%
전라남도 564
 
5.6%
전라북도 559
 
5.6%
대구광역시 490
 
4.9%
강원특별자치도 449
 
4.5%
Other values (7) 1672
16.7%

Length

2023-12-12T11:59:51.395041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 2404
24.0%
서울특별시 1329
13.3%
경상북도 733
 
7.3%
경상남도 611
 
6.1%
인천광역시 610
 
6.1%
충청남도 579
 
5.8%
전라남도 564
 
5.6%
전라북도 559
 
5.6%
대구광역시 490
 
4.9%
강원특별자치도 449
 
4.5%
Other values (7) 1672
16.7%

관할시군구명
Text

Distinct229
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:59:51.888397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4852
Min length1

Characters and Unicode

Total characters34852
Distinct characters141
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row충주시
2nd row울주군
3rd row창원시 마산합포구
4th row서구
5th row광산구
ValueCountFrequency (%)
서구 292
 
2.6%
북구 245
 
2.2%
고양시 235
 
2.1%
동구 216
 
1.9%
남구 187
 
1.7%
용인시 182
 
1.6%
부천시 176
 
1.6%
청주시 168
 
1.5%
중구 166
 
1.5%
남양주시 158
 
1.4%
Other values (224) 9219
82.0%
2023-12-12T11:59:52.593311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5081
 
14.6%
구 4789
 
13.7%
군 1735
 
5.0%
주 1316
 
3.8%
1290
 
3.7%
산 1115
 
3.2%
양 1085
 
3.1%
천 1014
 
2.9%
동 828
 
2.4%
서 761
 
2.2%
Other values (131) 15838
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33562
96.3%
Space Separator 1290
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5081
 
15.1%
구 4789
 
14.3%
군 1735
 
5.2%
주 1316
 
3.9%
산 1115
 
3.3%
양 1085
 
3.2%
천 1014
 
3.0%
동 828
 
2.5%
서 761
 
2.3%
성 740
 
2.2%
Other values (130) 15098
45.0%
Space Separator
ValueCountFrequency (%)
1290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33562
96.3%
Common 1290
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5081
 
15.1%
구 4789
 
14.3%
군 1735
 
5.2%
주 1316
 
3.9%
산 1115
 
3.3%
양 1085
 
3.2%
천 1014
 
3.0%
동 828
 
2.5%
서 761
 
2.3%
성 740
 
2.2%
Other values (130) 15098
45.0%
Common
ValueCountFrequency (%)
1290
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33562
96.3%
ASCII 1290
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5081
 
15.1%
구 4789
 
14.3%
군 1735
 
5.2%
주 1316
 
3.9%
산 1115
 
3.3%
양 1085
 
3.2%
천 1014
 
3.0%
동 828
 
2.5%
서 761
 
2.3%
성 740
 
2.2%
Other values (130) 15098
45.0%
ASCII
ValueCountFrequency (%)
1290
100.0%

평가일자
Date

Distinct696
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-03-05 00:00:00
Maximum2022-11-24 00:00:00
2023-12-12T11:59:52.812475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:53.017918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

평가등급
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
B
2978 
A
2525 
C
2045 
E
1251 
D
1201 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowB
2nd rowD
3rd rowB
4th rowA
5th rowB

Common Values

ValueCountFrequency (%)
B 2978
29.8%
A 2525
25.2%
C 2045
20.4%
E 1251
12.5%
D 1201
12.0%

Length

2023-12-12T11:59:53.214901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:59:53.372896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
b 2978
29.8%
a 2525
25.2%
c 2045
20.4%
e 1251
12.5%
d 1201
12.0%

평가총점
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1394
Distinct (%)64.6%
Missing7841
Missing (%)78.4%
Infinite0
Infinite (%)0.0%
Mean79.126823
Minimum28.54
Maximum99.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:53.560909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.54
5-th percentile56.687
Q171.81
median80.8
Q388.6
95-th percentile96.3
Maximum99.75
Range71.21
Interquartile range (IQR)16.79

Descriptive statistics

Standard deviation12.304422
Coefficient of variation (CV)0.15550254
Kurtosis0.56013655
Mean79.126823
Median Absolute Deviation (MAD)8.3
Skewness-0.75326685
Sum170834.81
Variance151.3988
MonotonicityNot monotonic
2023-12-12T11:59:53.780706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
94.1 10
 
0.1%
91.35 10
 
0.1%
86.6 10
 
0.1%
83.35 10
 
0.1%
83.85 10
 
0.1%
94.85 10
 
0.1%
91.6 10
 
0.1%
89.6 10
 
0.1%
90.85 9
 
0.1%
97.1 9
 
0.1%
Other values (1384) 2061
 
20.6%
(Missing) 7841
78.4%
ValueCountFrequency (%)
28.54 1
< 0.1%
29.16 1
< 0.1%
30.33 1
< 0.1%
32.28 1
< 0.1%
33.06 1
< 0.1%
33.08 1
< 0.1%
34.07 1
< 0.1%
35.77 1
< 0.1%
36.89 1
< 0.1%
37.38 1
< 0.1%
ValueCountFrequency (%)
99.75 1
 
< 0.1%
99.5 1
 
< 0.1%
99.35 1
 
< 0.1%
99.3 2
< 0.1%
99.1 2
< 0.1%
99.05 1
 
< 0.1%
98.85 4
< 0.1%
98.8 1
 
< 0.1%
98.75 1
 
< 0.1%
98.6 3
< 0.1%

기관운영
Real number (ℝ)

HIGH CORRELATION 

Distinct308
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.010102
Minimum0
Maximum100
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:54.020253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.4
Q167.86
median79.76
Q390
95-th percentile98.33
Maximum100
Range100
Interquartile range (IQR)22.14

Descriptive statistics

Standard deviation16.363708
Coefficient of variation (CV)0.21248781
Kurtosis0.71156704
Mean77.010102
Median Absolute Deviation (MAD)10.72
Skewness-0.8998616
Sum770101.02
Variance267.77093
MonotonicityNot monotonic
2023-12-12T11:59:54.256758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91.67 337
 
3.4%
100.0 301
 
3.0%
83.33 286
 
2.9%
75.0 252
 
2.5%
95.24 239
 
2.4%
66.67 181
 
1.8%
90.48 173
 
1.7%
97.62 136
 
1.4%
92.86 134
 
1.3%
84.52 133
 
1.3%
Other values (298) 7828
78.3%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
3.33 1
 
< 0.1%
5.33 2
 
< 0.1%
7.13 1
 
< 0.1%
8.33 1
 
< 0.1%
10.0 4
< 0.1%
10.73 4
< 0.1%
14.27 5
0.1%
15.0 1
 
< 0.1%
16.67 3
< 0.1%
ValueCountFrequency (%)
100.0 301
3.0%
98.81 104
 
1.0%
98.68 6
 
0.1%
98.67 4
 
< 0.1%
98.61 26
 
0.3%
98.33 94
 
0.9%
98.2 17
 
0.2%
97.62 136
1.4%
97.38 8
 
0.1%
97.37 5
 
0.1%

환경및안전
Real number (ℝ)

HIGH CORRELATION 

Distinct200
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88.730072
Minimum0
Maximum100
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:54.490765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile60
Q183
median91
Q3100
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)17

Descriptive statistics

Standard deviation12.544393
Coefficient of variation (CV)0.14137702
Kurtosis3.88471
Mean88.730072
Median Absolute Deviation (MAD)9
Skewness-1.7172352
Sum887300.72
Variance157.3618
MonotonicityNot monotonic
2023-12-12T11:59:54.757663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 2631
26.3%
90.0 1009
 
10.1%
80.0 548
 
5.5%
97.32 381
 
3.8%
95.0 280
 
2.8%
94.64 224
 
2.2%
60.0 208
 
2.1%
75.0 163
 
1.6%
92.0 152
 
1.5%
98.0 136
 
1.4%
Other values (190) 4268
42.7%
ValueCountFrequency (%)
0.0 3
 
< 0.1%
12.0 1
 
< 0.1%
25.0 25
0.2%
30.0 5
 
0.1%
30.67 1
 
< 0.1%
31.24 1
 
< 0.1%
32.0 2
 
< 0.1%
35.0 2
 
< 0.1%
36.38 1
 
< 0.1%
37.5 2
 
< 0.1%
ValueCountFrequency (%)
100.0 2631
26.3%
98.86 12
 
0.1%
98.21 47
 
0.5%
98.0 136
 
1.4%
97.73 5
 
0.1%
97.71 134
 
1.3%
97.5 26
 
0.3%
97.32 381
 
3.8%
97.0 95
 
0.9%
96.59 1
 
< 0.1%

수급자권리보장
Real number (ℝ)

HIGH CORRELATION 

Distinct154
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.486413
Minimum0
Maximum100
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:55.038865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42.84
Q166.67
median82.61
Q393.48
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)26.81

Descriptive statistics

Standard deviation18.122017
Coefficient of variation (CV)0.23089369
Kurtosis-0.20724769
Mean78.486413
Median Absolute Deviation (MAD)13.04
Skewness-0.71863215
Sum784864.13
Variance328.40751
MonotonicityNot monotonic
2023-12-12T11:59:55.249921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 1559
 
15.6%
66.67 594
 
5.9%
95.65 560
 
5.6%
91.3 421
 
4.2%
83.33 282
 
2.8%
75.0 273
 
2.7%
63.64 263
 
2.6%
91.67 244
 
2.4%
50.0 216
 
2.2%
59.09 209
 
2.1%
Other values (144) 5379
53.8%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
8.33 1
 
< 0.1%
13.64 6
 
0.1%
18.18 1
 
< 0.1%
20.45 21
0.2%
25.0 1
 
< 0.1%
27.08 1
 
< 0.1%
27.27 44
0.4%
28.58 1
 
< 0.1%
30.43 4
 
< 0.1%
ValueCountFrequency (%)
100.0 1559
15.6%
97.92 56
 
0.6%
96.74 115
 
1.1%
96.42 7
 
0.1%
96.15 1
 
< 0.1%
96.04 2
 
< 0.1%
95.83 47
 
0.5%
95.65 560
 
5.6%
95.45 94
 
0.9%
94.74 3
 
< 0.1%

급여제공과정
Real number (ℝ)

HIGH CORRELATION 

Distinct952
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.986742
Minimum0
Maximum100
Zeros21
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:55.498415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile39.72
Q162.89
median77.24
Q388.13
95-th percentile97.97
Maximum100
Range100
Interquartile range (IQR)25.24

Descriptive statistics

Standard deviation18.246762
Coefficient of variation (CV)0.24662204
Kurtosis0.6869432
Mean73.986742
Median Absolute Deviation (MAD)12.15
Skewness-0.88734755
Sum739867.42
Variance332.94431
MonotonicityNot monotonic
2023-12-12T11:59:55.713923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 310
 
3.1%
94.7 191
 
1.9%
75.0 179
 
1.8%
91.67 164
 
1.6%
88.64 111
 
1.1%
79.55 106
 
1.1%
50.0 104
 
1.0%
82.58 98
 
1.0%
85.61 95
 
0.9%
84.09 93
 
0.9%
Other values (942) 8549
85.5%
ValueCountFrequency (%)
0.0 21
0.2%
2.29 1
 
< 0.1%
3.8 1
 
< 0.1%
4.05 1
 
< 0.1%
4.17 2
 
< 0.1%
4.54 1
 
< 0.1%
5.39 2
 
< 0.1%
5.83 1
 
< 0.1%
5.89 2
 
< 0.1%
6.41 1
 
< 0.1%
ValueCountFrequency (%)
100.0 310
3.1%
99.38 1
 
< 0.1%
99.36 7
 
0.1%
99.33 2
 
< 0.1%
99.32 1
 
< 0.1%
99.29 7
 
0.1%
99.23 11
 
0.1%
99.17 4
 
< 0.1%
98.72 13
 
0.1%
98.64 1
 
< 0.1%

급여제공결과
Real number (ℝ)

Distinct176
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.438921
Minimum31.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:59:55.947532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.5
5-th percentile73
Q186
median93.5
Q3100
95-th percentile100
Maximum100
Range68.5
Interquartile range (IQR)14

Descriptive statistics

Standard deviation9.3593756
Coefficient of variation (CV)0.10235658
Kurtosis1.552681
Mean91.438921
Median Absolute Deviation (MAD)6.5
Skewness-1.2309384
Sum914389.21
Variance87.597912
MonotonicityNot monotonic
2023-12-12T11:59:56.171886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 3446
34.5%
92.31 522
 
5.2%
95.0 290
 
2.9%
98.08 268
 
2.7%
90.0 264
 
2.6%
86.0 233
 
2.3%
96.0 198
 
2.0%
83.0 161
 
1.6%
91.0 159
 
1.6%
91.69 154
 
1.5%
Other values (166) 4305
43.0%
ValueCountFrequency (%)
31.5 1
 
< 0.1%
40.0 3
< 0.1%
44.5 1
 
< 0.1%
45.0 2
< 0.1%
45.5 1
 
< 0.1%
46.5 1
 
< 0.1%
48.0 1
 
< 0.1%
49.0 2
< 0.1%
49.5 1
 
< 0.1%
50.0 1
 
< 0.1%
ValueCountFrequency (%)
100.0 3446
34.5%
98.5 14
 
0.1%
98.08 268
 
2.7%
98.0 20
 
0.2%
97.8 1
 
< 0.1%
97.5 151
 
1.5%
97.0 106
 
1.1%
96.7 4
 
< 0.1%
96.15 73
 
0.7%
96.0 198
 
2.0%

Interactions

2023-12-12T11:59:46.039626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:39.690080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:40.873954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.057370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.150815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.188653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.150471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.179635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:39.808897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.007100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.192513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.283512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.313700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.295563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.341599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:39.923895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.133562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.352032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.463991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.480777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.413618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.559899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:40.028829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.257616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.498363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.618149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.622074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.542130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.682094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:40.475055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.400608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.682643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.761926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.757621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.665999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.815231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:40.598224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.565834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.830079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:43.890978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.888842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.804203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:46.967573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:40.730663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:41.895697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:42.968729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.029252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:44.996898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:59:45.906428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:59:56.339155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번평가구분급여종류설립주체관할시도명평가등급평가총점기관운영환경및안전수급자권리보장급여제공과정급여제공결과
연번1.0000.9970.6260.1790.7410.3430.0820.2890.2360.4920.2330.577
평가구분0.9971.0000.7380.2430.1900.214NaN0.2670.2040.4780.2080.568
급여종류0.6260.7381.0000.3320.2520.3290.3930.2810.2830.4020.3280.468
설립주체0.1790.2430.3321.0000.2470.1110.2750.1780.1290.1070.1320.074
관할시도명0.7410.1900.2520.2471.0000.1280.1560.1230.1140.1370.1190.139
평가등급0.3430.2140.3290.1110.1281.0000.9480.8020.5950.7970.8890.361
평가총점0.082NaN0.3930.2750.1560.9481.0000.8010.7720.6490.9330.222
기관운영0.2890.2670.2810.1780.1230.8020.8011.0000.4900.6270.6590.309
환경및안전0.2360.2040.2830.1290.1140.5950.7720.4901.0000.6480.5810.425
수급자권리보장0.4920.4780.4020.1070.1370.7970.6490.6270.6481.0000.6350.444
급여제공과정0.2330.2080.3280.1320.1190.8890.9330.6590.5810.6351.0000.244
급여제공결과0.5770.5680.4680.0740.1390.3610.2220.3090.4250.4440.2441.000
2023-12-12T11:59:56.559825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립주체평가구분관할시도명평가등급급여종류
설립주체1.0000.0980.1390.0910.218
평가구분0.0981.0000.1070.1760.579
관할시도명0.1390.1071.0000.0660.103
평가등급0.0910.1760.0661.0000.197
급여종류0.2180.5790.1030.1971.000
2023-12-12T11:59:56.734141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번평가총점기관운영환경및안전수급자권리보장급여제공과정급여제공결과평가구분급여종류설립주체관할시도명평가등급
연번1.0000.0650.0570.1300.0500.107-0.0120.9710.3450.1080.4020.149
평가총점0.0651.0000.8020.7300.7750.9270.2541.0000.2570.1670.0610.687
기관운영0.0570.8021.0000.4600.5620.6130.2480.1620.1310.1070.0470.458
환경및안전0.1300.7300.4601.0000.4380.5300.1590.1220.1280.0770.0440.288
수급자권리보장0.0500.7750.5620.4381.0000.6110.3000.3050.1950.0640.0540.453
급여제공과정0.1070.9270.6130.5300.6111.0000.1830.1260.1550.0790.0460.570
급여제공결과-0.0120.2540.2480.1590.3000.1831.0000.3770.2340.0440.0540.158
평가구분0.9711.0000.1620.1220.3050.1260.3771.0000.5790.0980.1070.176
급여종류0.3450.2570.1310.1280.1950.1550.2340.5791.0000.2180.1030.197
설립주체0.1080.1670.1070.0770.0640.0790.0440.0980.2181.0000.1390.091
관할시도명0.4020.0610.0470.0440.0540.0460.0540.1070.1030.1391.0000.066
평가등급0.1490.6870.4580.2880.4530.5700.1580.1760.1970.0910.0661.000

Missing values

2023-12-12T11:59:47.179814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:59:47.532498image/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

연번평가구분장기요양기관기호장기요양기관명급여종류설립주체관할시도명관할시군구명평가일자평가등급평가총점기관운영환경및안전수급자권리보장급여제공과정급여제공결과
827282732019년 정기평가3-43130-00038아가페노인요양센터04.방문요양개인충청북도충주시2019-05-29B<NA>92.8670.078.2669.7100.0
119111922018년 정기평가1-31710-00010효도의집01.입소시설30인이상법인울산광역시울주군2018-07-02D<NA>56.6781.045.4555.1367.0
15907159082020년 정기평가3-48120-00373친절한방문요양센터04.방문요양개인경상남도창원시 마산합포구2020-06-24B<NA>86.9100.096.7463.64100.0
17243172442021년 정기평가1-29140-00009평강의집01.입소시설30인이상개인광주광역시서구2022-01-12A99.3598.33100.0100.0100.096.0
623762382019년 정기평가3-29200-00268다원 노인지원복지센터04.방문요양개인광주광역시광산구2019-05-08B<NA>82.1490.089.1372.7398.08
12782127832020년 정기평가3-41570-00255함께하는 재가노인복지센터04.방문요양개인경기도김포시2020-07-06A<NA>91.67100.089.1381.82100.0
12835128362020년 정기평가3-41360-00711아리아케어 방문요양 남양주진접센터04.방문요양개인경기도남양주시2020-06-15A<NA>89.29100.095.6587.88100.0
16356163572021년 정기평가1-11320-00216동그라미요양센터1호점03.입소시설10인미만개인서울특별시도봉구2021-12-22B86.4278.6100.066.6786.6683.0
997199722019년 정기평가3-48720-00008정남실버재가복지센터05.방문목욕개인경상남도의령군2019-07-24A<NA>92.86100.0100.097.97100.0
13514135152020년 정기평가3-41150-00165성장하는재가장기요양기관04.방문요양개인경기도의정부시2020-07-03D<NA>61.960.045.6551.52100.0
연번평가구분장기요양기관기호장기요양기관명급여종류설립주체관할시도명관할시군구명평가일자평가등급평가총점기관운영환경및안전수급자권리보장급여제공과정급여제공결과
889989002019년 정기평가2-45750-00050정드림 노인복지센터05.방문목욕개인전라북도임실군2019-04-29E<NA>78.5755.078.2643.24100.0
16664166652021년 정기평가1-26470-00048녹원요양원 미루나무집03.입소시설10인미만법인부산광역시연제구2022-09-05D64.9448.287.545.8360.665.0
373037312018년 정기평가1-47290-28830데레사노인요양공동생활가정03.입소시설10인미만개인경상북도경산시2018-09-28E<NA>10.7332.020.454.0580.7
540054012019년 정기평가3-26320-00050공덕향재가장기요양기관04.방문요양법인부산광역시북구2019-03-05E<NA>71.4360.050.044.7100.0
10278102792020년 정기평가2-11680-00177국민건강보험공단 서울요양원 재가복지센터04.방문요양법인서울특별시강남구2020-10-07B<NA>100.0100.091.391.6765.38
11323113242020년 정기평가3-26380-00157우리재가복지센터04.방문요양개인부산광역시사하구2020-09-21D<NA>71.0590.043.4873.4898.08
14399144002020년 정기평가3-44130-00361동행 재가복지센터04.방문요양개인충청남도천안시2020-06-02B<NA>75.090.0100.084.85100.0
826182622019년 정기평가3-43110-00548성심노인주간보호센터07.주야간보호개인충청북도청주시 흥덕구2019-05-22C<NA>62.593.1977.0866.26100.0
13749137502020년 정기평가3-42150-00035(I)에이플러스홈 재가복지센터04.방문요양개인강원특별자치도강릉시2020-05-20A<NA>78.57100.086.9689.3992.31
18066180672021년 정기평가1-41270-00855고수련요양원세종점02.입소시설10이상30인미만개인경기도안산시2022-07-15C72.0365.094.6458.3359.0981.0