Overview

Dataset statistics

Number of variables7
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory60.3 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description홍성군내 노인복지 시설 현황으로 시군명, 단체시설명, 소재지도로명주소, 대표자, 전화번호, 데이터 기준일등을 제공합니다.
Author충청남도 홍성군
URLhttps://www.data.go.kr/data/3073580/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
단체시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:35:13.085398
Analysis finished2023-12-12 09:35:13.988900
Duration0.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-12T18:35:14.114707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2023-12-12T18:35:14.679850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
홍성군
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
홍성군 40
100.0%

Length

2023-12-12T18:35:14.915628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:35:15.042522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
홍성군 40
100.0%

단체시설명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:35:15.293349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.675
Min length4

Characters and Unicode

Total characters347
Distinct characters94
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

Unique40 ?
Unique (%)100.0%

Sample

1st row대한노인회 홍성군지회
2nd row홍성군노인종합복지관
3rd row에덴광천요양원
4th row혜경요양원
5th row굿모닝요양원
ValueCountFrequency (%)
대한노인회 1
 
2.3%
사랑재가복지센터 1
 
2.3%
행복의료기 1
 
2.3%
복지용구 1
 
2.3%
은빛주간보호센터 1
 
2.3%
가나안주간보호센터 1
 
2.3%
소망재가노인복지센터 1
 
2.3%
청로노인종합복지센터 1
 
2.3%
브라보광천주간보호센터 1
 
2.3%
주)홍성돌봄요양센터 1
 
2.3%
Other values (33) 33
76.7%
2023-12-12T18:35:15.803745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
6.6%
23
 
6.6%
18
 
5.2%
16
 
4.6%
16
 
4.6%
16
 
4.6%
15
 
4.3%
14
 
4.0%
13
 
3.7%
13
 
3.7%
Other values (84) 180
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
98.6%
Space Separator 3
 
0.9%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
 
6.7%
23
 
6.7%
18
 
5.3%
16
 
4.7%
16
 
4.7%
16
 
4.7%
15
 
4.4%
14
 
4.1%
13
 
3.8%
13
 
3.8%
Other values (81) 175
51.2%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
98.6%
Common 5
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
 
6.7%
23
 
6.7%
18
 
5.3%
16
 
4.7%
16
 
4.7%
16
 
4.7%
15
 
4.4%
14
 
4.1%
13
 
3.8%
13
 
3.8%
Other values (81) 175
51.2%
Common
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
98.6%
ASCII 5
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
23
 
6.7%
23
 
6.7%
18
 
5.3%
16
 
4.7%
16
 
4.7%
16
 
4.7%
15
 
4.4%
14
 
4.1%
13
 
3.8%
13
 
3.8%
Other values (81) 175
51.2%
ASCII
ValueCountFrequency (%)
3
60.0%
) 1
 
20.0%
( 1
 
20.0%
Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:35:16.130851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length28
Mean length25.125
Min length19

Characters and Unicode

Total characters1005
Distinct characters62
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

Unique33 ?
Unique (%)82.5%

Sample

1st row충청남도 홍성군 홍성읍 홍성천길 120-27
2nd row충청남도 홍성군 홍성읍 내포로 146번길 30-11
3rd row충청남도 홍성군 광천읍 홍남동로64번길 176-48
4th row충청남도 홍성군 갈산면 상촌로9번길 18-9
5th row충청남도 홍성군 홍성읍 충서로 1341
ValueCountFrequency (%)
충청남도 41
19.2%
홍성군 41
19.2%
홍성읍 20
 
9.3%
광천읍 7
 
3.3%
갈산면 4
 
1.9%
내포로 4
 
1.9%
은하면 3
 
1.4%
1718-36 3
 
1.4%
2층 3
 
1.4%
구항면 2
 
0.9%
Other values (74) 86
40.2%
2023-12-12T18:35:16.703102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
17.4%
71
 
7.1%
66
 
6.6%
50
 
5.0%
1 47
 
4.7%
45
 
4.5%
44
 
4.4%
44
 
4.4%
41
 
4.1%
36
 
3.6%
Other values (52) 386
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 596
59.3%
Decimal Number 204
 
20.3%
Space Separator 175
 
17.4%
Dash Punctuation 22
 
2.2%
Other Punctuation 6
 
0.6%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
71
11.9%
66
11.1%
50
 
8.4%
45
 
7.6%
44
 
7.4%
44
 
7.4%
41
 
6.9%
36
 
6.0%
29
 
4.9%
25
 
4.2%
Other values (37) 145
24.3%
Decimal Number
ValueCountFrequency (%)
1 47
23.0%
3 26
12.7%
6 24
11.8%
2 21
10.3%
0 17
 
8.3%
4 16
 
7.8%
7 16
 
7.8%
8 14
 
6.9%
5 12
 
5.9%
9 11
 
5.4%
Space Separator
ValueCountFrequency (%)
175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 596
59.3%
Common 409
40.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
71
11.9%
66
11.1%
50
 
8.4%
45
 
7.6%
44
 
7.4%
44
 
7.4%
41
 
6.9%
36
 
6.0%
29
 
4.9%
25
 
4.2%
Other values (37) 145
24.3%
Common
ValueCountFrequency (%)
175
42.8%
1 47
 
11.5%
3 26
 
6.4%
6 24
 
5.9%
- 22
 
5.4%
2 21
 
5.1%
0 17
 
4.2%
4 16
 
3.9%
7 16
 
3.9%
8 14
 
3.4%
Other values (5) 31
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 596
59.3%
ASCII 409
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
42.8%
1 47
 
11.5%
3 26
 
6.4%
6 24
 
5.9%
- 22
 
5.4%
2 21
 
5.1%
0 17
 
4.2%
4 16
 
3.9%
7 16
 
3.9%
8 14
 
3.4%
Other values (5) 31
 
7.6%
Hangul
ValueCountFrequency (%)
71
11.9%
66
11.1%
50
 
8.4%
45
 
7.6%
44
 
7.4%
44
 
7.4%
41
 
6.9%
36
 
6.0%
29
 
4.9%
25
 
4.2%
Other values (37) 145
24.3%
Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:35:16.960103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1
Min length2

Characters and Unicode

Total characters124
Distinct characters65
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

Unique33 ?
Unique (%)82.5%

Sample

1st row조화원
2nd row이동명(한재선)
3rd row한명희
4th row박혜경
5th row송대일
ValueCountFrequency (%)
김세중 3
 
7.5%
박승희 2
 
5.0%
이철이 2
 
5.0%
조화원 1
 
2.5%
이석주 1
 
2.5%
안형숙 1
 
2.5%
박제순 1
 
2.5%
김주형 1
 
2.5%
김기화 1
 
2.5%
유금재 1
 
2.5%
Other values (26) 26
65.0%
2023-12-12T18:35:17.397890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
8.1%
9
 
7.3%
6
 
4.8%
5
 
4.0%
4
 
3.2%
3
 
2.4%
3
 
2.4%
3
 
2.4%
2
 
1.6%
2
 
1.6%
Other values (55) 77
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
98.4%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10
 
8.2%
9
 
7.4%
6
 
4.9%
5
 
4.1%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (53) 75
61.5%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
98.4%
Common 2
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10
 
8.2%
9
 
7.4%
6
 
4.9%
5
 
4.1%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (53) 75
61.5%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
98.4%
ASCII 2
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
10
 
8.2%
9
 
7.4%
6
 
4.9%
5
 
4.1%
4
 
3.3%
3
 
2.5%
3
 
2.5%
3
 
2.5%
2
 
1.6%
2
 
1.6%
Other values (53) 75
61.5%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%
Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-12T18:35:17.680985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/