Overview

Dataset statistics

Number of variables4
Number of observations647
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.0 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description보건복지부에서 노인돌봄기본서비스 수행기관 현황(전국)과 독거노인서비스 수행기관 (전국) 자료를 제공합니다.
Author보건복지부
URLhttps://www.data.go.kr/data/15004317/fileData.do

Alerts

연번 is highly overall correlated with 시도High correlation
시도 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:11:23.702313
Analysis finished2023-12-12 15:11:24.438649
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct647
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean324
Minimum1
Maximum647
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 KiB
2023-12-13T00:11:24.521306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33.3
Q1162.5
median324
Q3485.5
95-th percentile614.7
Maximum647
Range646
Interquartile range (IQR)323

Descriptive statistics

Standard deviation186.91709
Coefficient of variation (CV)0.57690461
Kurtosis-1.2
Mean324
Median Absolute Deviation (MAD)162
Skewness0
Sum209628
Variance34938
MonotonicityStrictly increasing
2023-12-13T00:11:24.715877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
446 1
 
0.2%
428 1
 
0.2%
429 1
 
0.2%
430 1
 
0.2%
431 1
 
0.2%
432 1
 
0.2%
433 1
 
0.2%
434 1
 
0.2%
435 1
 
0.2%
Other values (637) 637
98.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
647 1
0.2%
646 1
0.2%
645 1
0.2%
644 1
0.2%
643 1
0.2%
642 1
0.2%
641 1
0.2%
640 1
0.2%
639 1
0.2%
638 1
0.2%

시도
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
경기도
110 
서울특별시
70 
경상북도
59 
경상남도
54 
전라북도
51 
Other values (12)
303 

Length

Max length7
Median length5
Mean length4.1823802
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 110
17.0%
서울특별시 70
10.8%
경상북도 59
9.1%
경상남도 54
8.3%
전라북도 51
7.9%
전라남도 45
7.0%
부산광역시 43
 
6.6%
대구광역시 39
 
6.0%
강원도 34
 
5.3%
충청남도 33
 
5.1%
Other values (7) 109
16.8%

Length

2023-12-13T00:11:24.909034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 110
17.0%
서울특별시 70
10.8%
경상북도 59
9.1%
경상남도 54
8.3%
전라북도 51
7.9%
전라남도 45
7.0%
부산광역시 43
 
6.6%
대구광역시 39
 
6.0%
강원도 34
 
5.3%
충청남도 33
 
5.1%
Other values (7) 109
16.8%

시군구
Text

Distinct207
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2023-12-13T00:11:25.321537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9366306
Min length2

Characters and Unicode

Total characters1900
Distinct characters137
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)6.2%

Sample

1st row종로구
2nd row중구
3rd row중구
4th row중구
5th row용산구
ValueCountFrequency (%)
서구 18
 
2.8%
동구 18
 
2.8%
중구 16
 
2.5%
북구 16
 
2.5%
남구 13
 
2.0%
고양시 13
 
2.0%
전주시 11
 
1.7%
창원시 10
 
1.5%
수원시 10
 
1.5%
용인시 9
 
1.4%
Other values (197) 513
79.3%
2023-12-13T00:11:25.862832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 286
 
15.1%
구 226
 
11.9%
군 160
 
8.4%
주 81
 
4.3%
성 54
 
2.8%
산 52
 
2.7%
양 52
 
2.7%
천 49
 
2.6%
동 44
 
2.3%
서 41
 
2.2%
Other values (127) 855
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1900
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 286
 
15.1%
구 226
 
11.9%
군 160
 
8.4%
주 81
 
4.3%
성 54
 
2.8%
산 52
 
2.7%
양 52
 
2.7%
천 49
 
2.6%
동 44
 
2.3%
서 41
 
2.2%
Other values (127) 855
45.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1900
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 286
 
15.1%
구 226
 
11.9%
군 160
 
8.4%
주 81
 
4.3%
성 54
 
2.8%
산 52
 
2.7%
양 52
 
2.7%
천 49
 
2.6%
동 44
 
2.3%
서 41
 
2.2%
Other values (127) 855
45.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1900
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 286
 
15.1%
구 226
 
11.9%
군 160
 
8.4%
주 81
 
4.3%
성 54
 
2.8%
산 52
 
2.7%
양 52
 
2.7%
천 49
 
2.6%
동 44
 
2.3%
서 41
 
2.2%
Other values (127) 855
45.0%

기관명
Text

Distinct641
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size5.2 KiB
2023-12-13T00:11:26.089994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length9.9242658
Min length4

Characters and Unicode

Total characters6421
Distinct characters336
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique635 ?
Unique (%)98.1%

Sample

1st row종로노인종합복지관
2nd row약수노인종합복지관
3rd row유락종합사회복지관
4th row중림종합사회복지관
5th row용산노인종합복지관
ValueCountFrequency (%)
사회적협동조합 4
 
0.6%
남구노인복지관 2
 
0.3%
사회복지법인 2
 
0.3%
서구노인복지관 2
 
0.3%
중구노인복지관 2
 
0.3%
샬롬노인복지센터 2
 
0.3%
강서노인종합복지관 2
 
0.3%
동구노인복지관 2
 
0.3%
노인통합지원센터 2
 
0.3%
동부재가노인통합지원센터 1
 
0.1%
Other values (649) 649
96.9%
2023-12-13T00:11:26.454052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 550
 
8.6%
인 449
 
7.0%
복 423
 
6.6%
노 420
 
6.5%
터 305
 
4.8%
센 304
 
4.7%
관 283
 
4.4%
합 223
 
3.5%
종 172
 
2.7%
사 162
 
2.5%
Other values (326) 3130
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6340
98.7%
Space Separator 23
 
0.4%
Uppercase Letter 16
 
0.2%
Close Punctuation 12
 
0.2%
Open Punctuation 11
 
0.2%
Lowercase Letter 8
 
0.1%
Decimal Number 6
 
0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 550
 
8.7%
인 449
 
7.1%
복 423
 
6.7%
노 420
 
6.6%
터 305
 
4.8%
센 304
 
4.8%
관 283
 
4.5%
합 223
 
3.5%
종 172
 
2.7%
사 162
 
2.6%
Other values (303) 3049
48.1%
Uppercase Letter
ValueCountFrequency (%)
C 6
37.5%
U 2
 
12.5%
A 2
 
12.5%
Y 2
 
12.5%
M 1
 
6.2%
K 1
 
6.2%
S 1
 
6.2%
W 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 1
16.7%
4 1
16.7%
2 1
16.7%
3 1
16.7%
9 1
16.7%
7 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
e 3
37.5%
r 2
25.0%
a 2
25.0%
c 1
 
12.5%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6340
98.7%
Common 57
 
0.9%
Latin 24
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 550
 
8.7%
인 449
 
7.1%
복 423
 
6.7%
노 420
 
6.6%
터 305
 
4.8%
센 304
 
4.8%
관 283
 
4.5%
합 223
 
3.5%
종 172
 
2.7%
사 162
 
2.6%
Other values (303) 3049
48.1%
Latin
ValueCountFrequency (%)
C 6
25.0%
e 3
12.5%
r 2
 
8.3%
a 2
 
8.3%
U 2
 
8.3%
A 2
 
8.3%
Y 2
 
8.3%
c 1
 
4.2%
M 1
 
4.2%
K 1
 
4.2%
Other values (2) 2
 
8.3%
Common
ValueCountFrequency (%)
23
40.4%
) 12
21.1%
( 11
19.3%
. 3
 
5.3%
- 2
 
3.5%
1 1
 
1.8%
4 1
 
1.8%
2 1
 
1.8%
3 1
 
1.8%
9 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6340
98.7%
ASCII 81
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 550
 
8.7%
인 449
 
7.1%
복 423
 
6.7%
노 420
 
6.6%
터 305
 
4.8%
센 304
 
4.8%
관 283
 
4.5%
합 223
 
3.5%
종 172
 
2.7%
사 162
 
2.6%
Other values (303) 3049
48.1%
ASCII
ValueCountFrequency (%)
23
28.4%
) 12
14.8%
( 11
13.6%
C 6
 
7.4%
. 3
 
3.7%
e 3
 
3.7%
r 2
 
2.5%
a 2
 
2.5%
- 2
 
2.5%
U 2
 
2.5%
Other values (13) 15
18.5%

Interactions

2023-12-13T00:11:24.034554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:11:26.541902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시도
연번1.0000.972
시도0.9721.000
2023-12-13T00:11:26.633173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시도
연번1.0000.863
시도0.8631.000

Missing values

2023-12-13T00:11:24.252749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:11:24.394980image/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

연번시도시군구기관명
01서울특별시종로구종로노인종합복지관
12서울특별시중구약수노인종합복지관
23서울특별시중구유락종합사회복지관
34서울특별시중구중림종합사회복지관
45서울특별시용산구용산노인종합복지관
56서울특별시용산구갈월종합사회복지관
67서울특별시용산구효창종합사회복지관
78서울특별시용산구청파노인복지센터
89서울특별시용산구용산재가노인지원센터
910서울특별시성동구성동노인종합복지관
연번시도시군구기관명
637638제주특별자치도제주시제주원광재가노인복지센터
638639제주특별자치도제주시은빛마을노인복지센터
639640제주특별자치도제주시제주시홀로사는노인지원센터
640641제주특별자치도제주시제주이어도지역자활센터
641642제주특별자치도제주시성안노인복지센터
642643제주특별자치도제주시제주노인복지센터
643644제주특별자치도서귀포시동광노인복지센터
644645제주특별자치도서귀포시성산원광소규모요양시설
645646제주특별자치도서귀포시서귀포시홀로사는노인지원센터
646647제주특별자치도서귀포시서귀원광노인복지센터