Overview

Dataset statistics

Number of variables10
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory85.5 B

Variable types

Numeric3
Categorical2
Text4
DateTime1

Dataset

Description금산군 관내 노인복지시설에 대한 데이터로 시설유형, 시설명, 소재지, 위도, 경도, 전화번호 등에 대한 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=33&beforeMenuCd=DOM_000000201001001000&publicdatapk=15117910

Alerts

데이터기준일 has constant value ""Constant
시설유형 is highly overall correlated with 시설종류High correlation
시설종류 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 시설종류High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 19:47:35.650032
Analysis finished2024-01-09 19:47:36.927681
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2024-01-10T04:47:36.982931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2024-01-10T04:47:37.085876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

시설유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size548.0 B
재가노인복지시설
26 
노인의료복지시설
24 
노인주거복지시설
 
1
노인일자리지원기관
 
1

Length

Max length9
Median length8
Mean length8.0192308
Min length8

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row노인주거복지시설
2nd row노인의료복지시설
3rd row노인의료복지시설
4th row노인의료복지시설
5th row노인의료복지시설

Common Values

ValueCountFrequency (%)
재가노인복지시설 26
50.0%
노인의료복지시설 24
46.2%
노인주거복지시설 1
 
1.9%
노인일자리지원기관 1
 
1.9%

Length

2024-01-10T04:47:37.181765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:47:37.257107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 26
50.0%
노인의료복지시설 24
46.2%
노인주거복지시설 1
 
1.9%
노인일자리지원기관 1
 
1.9%

시설종류
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
재가노인복지시설
26 
노인요양공동생활가정
16 
노인요양시설
노인공동생활가정
 
1
노인일자리지원기관
 
1

Length

Max length10
Median length8
Mean length8.3269231
Min length6

Unique

Unique2 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 26
50.0%
노인요양공동생활가정 16
30.8%
노인요양시설 8
 
15.4%
노인공동생활가정 1
 
1.9%
노인일자리지원기관 1
 
1.9%

Length

2024-01-10T04:47:37.363064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T04:47:37.448150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 26
50.0%
노인요양공동생활가정 16
30.8%
노인요양시설 8
 
15.4%
노인공동생활가정 1
 
1.9%
노인일자리지원기관 1
 
1.9%
Distinct49
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T04:47:37.621762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.75
Min length4

Characters and Unicode

Total characters403
Distinct characters111
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)88.5%

Sample

1st row축복의동산양로원
2nd row금산실버타운홍익원
3rd row나눔의 집
4th row금산무지개요양원
5th row장기요양기관 사회복지법인 인삼골건강마을
ValueCountFrequency (%)
동행랜드 4
 
6.3%
새금산실버케어 2
 
3.2%
그린동 2
 
3.2%
핑크동 2
 
3.2%
재가복지센터 1
 
1.6%
새금산복지용구 1
 
1.6%
축복의동산양로원 1
 
1.6%
금산군치매주간보호센터 1
 
1.6%
성심주간보호센터 1
 
1.6%
신나는주간보호센터 1
 
1.6%
Other values (47) 47
74.6%
2024-01-10T04:47:38.121007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22
 
5.5%
22
 
5.5%
18
 
4.5%
16
 
4.0%
15
 
3.7%
15
 
3.7%
14
 
3.5%
14
 
3.5%
14
 
3.5%
11
 
2.7%
Other values (101) 242
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
96.3%
Space Separator 11
 
2.7%
Decimal Number 4
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
22
 
5.7%
22
 
5.7%
18
 
4.6%
16
 
4.1%
15
 
3.9%
15
 
3.9%
14
 
3.6%
14
 
3.6%
14
 
3.6%
10
 
2.6%
Other values (97) 228
58.8%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
96.3%
Common 15
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
22
 
5.7%
22
 
5.7%
18
 
4.6%
16
 
4.1%
15
 
3.9%
15
 
3.9%
14
 
3.6%
14
 
3.6%
14
 
3.6%
10
 
2.6%
Other values (97) 228
58.8%
Common
ValueCountFrequency (%)
11
73.3%
0 2
 
13.3%
1 1
 
6.7%
2 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
96.3%
ASCII 15
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
22
 
5.7%
22
 
5.7%
18
 
4.6%
16
 
4.1%
15
 
3.9%
15
 
3.9%
14
 
3.6%
14
 
3.6%
14
 
3.6%
10
 
2.6%
Other values (97) 228
58.8%
ASCII
ValueCountFrequency (%)
11
73.3%
0 2
 
13.3%
1 1
 
6.7%
2 1
 
6.7%
Distinct38
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T04:47:38.303571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length21.423077
Min length19

Characters and Unicode

Total characters1114
Distinct characters58
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

Unique30 ?
Unique (%)57.7%

Sample

1st row충청남도 금산군 제원면 명암리 90-6
2nd row충청남도 금산군 금산읍 상리 34-13
3rd row충청남도 금산군 금성면 화림리 411-2
4th row충청남도 금산군 금산읍 상리 34-13
5th row충청남도 금산군 금산읍 계진리 273
ValueCountFrequency (%)
충청남도 52
20.0%
금산군 52
20.0%
금산읍 30
 
11.5%
상리 17
 
6.5%
아인리 6
 
2.3%
177-10 5
 
1.9%
군북면 5
 
1.9%
복수면 5
 
1.9%
상곡리 4
 
1.5%
948-4 4
 
1.5%
Other values (58) 80
30.8%
2024-01-10T04:47:38.602412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
18.7%
85
 
7.6%
84
 
7.5%
57
 
5.1%
55
 
4.9%
54
 
4.8%
53
 
4.8%
52
 
4.7%
52
 
4.7%
- 44
 
3.9%
Other values (48) 370
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 659
59.2%
Space Separator 208
 
18.7%
Decimal Number 203
 
18.2%
Dash Punctuation 44
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
85
12.9%
84
12.7%
57
8.6%
55
8.3%
54
8.2%
53
8.0%
52
7.9%
52
7.9%
30
 
4.6%
22
 
3.3%
Other values (36) 115
17.5%
Decimal Number
ValueCountFrequency (%)
1 39
19.2%
2 24
11.8%
3 24
11.8%
7 23
11.3%
6 23
11.3%
4 22
10.8%
8 13
 
6.4%
5 13
 
6.4%
0 11
 
5.4%
9 11
 
5.4%
Space Separator
ValueCountFrequency (%)
208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 659
59.2%
Common 455
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
85
12.9%
84
12.7%
57
8.6%
55
8.3%
54
8.2%
53
8.0%
52
7.9%
52
7.9%
30
 
4.6%
22
 
3.3%
Other values (36) 115
17.5%
Common
ValueCountFrequency (%)
208
45.7%
- 44
 
9.7%
1 39
 
8.6%
2 24
 
5.3%
3 24
 
5.3%
7 23
 
5.1%
6 23
 
5.1%
4 22
 
4.8%
8 13
 
2.9%
5 13
 
2.9%
Other values (2) 22
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 659
59.2%
ASCII 455
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
45.7%
- 44
 
9.7%
1 39
 
8.6%
2 24
 
5.3%
3 24
 
5.3%
7 23
 
5.1%
6 23
 
5.1%
4 22
 
4.8%
8 13
 
2.9%
5 13
 
2.9%
Other values (2) 22
 
4.8%
Hangul
ValueCountFrequency (%)
85
12.9%
84
12.7%
57
8.6%
55
8.3%
54
8.2%
53
8.0%
52
7.9%
52
7.9%
30
 
4.6%
22
 
3.3%
Other values (36) 115
17.5%
Distinct44
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size548.0 B
2024-01-10T04:47:38.804745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length22
Min length18

Characters and Unicode

Total characters1144
Distinct characters88
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

Unique38 ?
Unique (%)73.1%

Sample

1st row충청남도 금산군 제원면 흰바우길 171
2nd row충청남도 금산군 금산읍 후곤천길 73 (디엔에스프라자(4층, 5층))
3rd row충청남도 금산군 금성면 화엄로 173-27
4th row충청남도 금산군 금산읍 후곤천길 73, 6층, 7층
5th row충청남도 금산군 금산읍 족실1길 10
ValueCountFrequency (%)
충청남도 52
19.0%
금산군 52
19.0%
금산읍 30
 
11.0%
오리정1길 6
 
2.2%
비단로 5
 
1.8%
41 5
 
1.8%
군북면 5
 
1.8%
복수면 5
 
1.8%
인삼로 4
 
1.5%
2층 4
 
1.5%
Other values (76) 105
38.5%
2024-01-10T04:47:39.119816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/