Overview

Dataset statistics

Number of variables10
Number of observations110
Missing cells110
Missing cells (%)10.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory84.2 B

Variable types

Numeric1
Categorical5
Text3
Unsupported1

Dataset

Description2016제세동기설치내역공공데이터
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201885

Alerts

시도 has constant value ""Constant
자료출처 has constant value ""Constant
연번 is highly overall correlated with 시군구High correlation
시군구 is highly overall correlated with 연번High correlation
시설 유형 (시설법인 1,지원법인 2) is highly imbalanced (69.5%)Imbalance
비고 has 110 (100.0%) missing valuesMissing
연번 has unique valuesUnique
법 인 명 has unique valuesUnique
주소지 has unique valuesUnique
비고 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 23:53:40.399938
Analysis finished2024-03-13 23:53:41.009709
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.5
Minimum1
Maximum110
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-03-14T08:53:41.072293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.45
Q128.25
median55.5
Q382.75
95-th percentile104.55
Maximum110
Range109
Interquartile range (IQR)54.5

Descriptive statistics

Standard deviation31.898276
Coefficient of variation (CV)0.57474371
Kurtosis-1.2
Mean55.5
Median Absolute Deviation (MAD)27.5
Skewness0
Sum6105
Variance1017.5
MonotonicityStrictly increasing
2024-03-14T08:53:41.186889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
71 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
Other values (100) 100
90.9%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
전북
110 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북 110
100.0%

Length

2024-03-14T08:53:41.287822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:53:41.374403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북 110
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size1012.0 B
전주시
28 
익산시
17 
군산시
13 
완주군
13 
남원시
10 
Other values (8)
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 28
25.5%
익산시 17
15.5%
군산시 13
11.8%
완주군 13
11.8%
남원시 10
 
9.1%
정읍시 8
 
7.3%
김제시 6
 
5.5%
고창군 4
 
3.6%
임실군 3
 
2.7%
순창군 3
 
2.7%
Other values (3) 5
 
4.5%

Length

2024-03-14T08:53:41.450912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 28
25.5%
익산시 17
15.5%
군산시 13
11.8%
완주군 13
11.8%
남원시 10
 
9.1%
정읍시 8
 
7.3%
김제시 6
 
5.5%
고창군 4
 
3.6%
임실군 3
 
2.7%
순창군 3
 
2.7%
Other values (3) 5
 
4.5%

법 인 명
Text

UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-03-14T08:53:41.647063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length5.6636364
Min length1

Characters and Unicode

Total characters623
Distinct characters162
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

Unique110 ?
Unique (%)100.0%

Sample

1st row전라북도사회복지협의회
2nd row참사랑복지회
3rd row천주교성가복지회
4th row전주시사회복지협의회
5th row한빛원
ValueCountFrequency (%)
전라북도사회복지협의회 1
 
0.8%
광덕복지재단 1
 
0.8%
성암복지원 1
 
0.8%
김제가나안복지재단 1
 
0.8%
시온회 1
 
0.8%
길보른재단 1
 
0.8%
햇빛 1
 
0.8%
우리원 1
 
0.8%
예닮문화복지재단 1
 
0.8%
서남행복원 1
 
0.8%
Other values (108) 108
91.5%
2024-03-14T08:53:41.996378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
복 62
 
10.0%
지 59
 
9.5%
단 43
 
6.9%
재 43
 
6.9%
원 38
 
6.1%
회 21
 
3.4%
사 15
 
2.4%
14
 
2.2%
성 11
 
1.8%
산 8
 
1.3%
Other values (152) 309
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 605
97.1%
Space Separator 14
 
2.2%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 62
 
10.2%
지 59
 
9.8%
단 43
 
7.1%
재 43
 
7.1%
원 38
 
6.3%
회 21
 
3.5%
사 15
 
2.5%
성 11
 
1.8%
산 8
 
1.3%
전 8
 
1.3%
Other values (149) 297
49.1%
Space Separator
ValueCountFrequency (%)
14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 605
97.1%
Common 18
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 62
 
10.2%
지 59
 
9.8%
단 43
 
7.1%
재 43
 
7.1%
원 38
 
6.3%
회 21
 
3.5%
사 15
 
2.5%
성 11
 
1.8%
산 8
 
1.3%
전 8
 
1.3%
Other values (149) 297
49.1%
Common
ValueCountFrequency (%)
14
77.8%
) 2
 
11.1%
( 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 605
97.1%
ASCII 18
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
복 62
 
10.2%
지 59
 
9.8%
단 43
 
7.1%
재 43
 
7.1%
원 38
 
6.3%
회 21
 
3.5%
사 15
 
2.5%
성 11
 
1.8%
산 8
 
1.3%
전 8
 
1.3%
Other values (149) 297
49.1%
ASCII
ValueCountFrequency (%)
14
77.8%
) 2
 
11.1%
( 2
 
11.1%

대표자명
Text

Distinct108
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-03-14T08:53:42.249189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0090909
Min length2

Characters and Unicode

Total characters331
Distinct characters110
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

Unique107 ?
Unique (%)97.3%

Sample

1st row차종선
2nd row양기승
3rd row이병호
4th row김정석
5th row임석기
ValueCountFrequency (%)
이병호 3
 
2.7%
김재영 1
 
0.9%
유재천 1
 
0.9%
권혁일 1
 
0.9%
한규택 1
 
0.9%
김영식 1
 
0.9%
온주현 1
 
0.9%
최재식 1
 
0.9%
조종남 1
 
0.9%
최규순 1
 
0.9%
Other values (100) 100
89.3%
2024-03-14T08:53:42.605144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 25
 
7.6%
이 15
 
4.5%
박 14
 
4.2%
영 11
 
3.3%
정 10
 
3.0%
병 8
 
2.4%
순 7
 
2.1%
인 7
 
2.1%
최 6
 
1.8%
양 6
 
1.8%
Other values (100) 222
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
98.8%
Space Separator 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 25
 
7.6%
이 15
 
4.6%
박 14
 
4.3%
영 11
 
3.4%
정 10
 
3.1%
병 8
 
2.4%
순 7
 
2.1%
인 7
 
2.1%
최 6
 
1.8%
양 6
 
1.8%
Other values (99) 218
66.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
98.8%
Common 4
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 25
 
7.6%
이 15
 
4.6%
박 14
 
4.3%
영 11
 
3.4%
정 10
 
3.1%
병 8
 
2.4%
순 7
 
2.1%
인 7
 
2.1%
최 6
 
1.8%
양 6
 
1.8%
Other values (99) 218
66.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
98.8%
ASCII 4
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 25
 
7.6%
이 15
 
4.6%
박 14
 
4.3%
영 11
 
3.4%
정 10
 
3.1%
병 8
 
2.4%
순 7
 
2.1%
인 7
 
2.1%
최 6
 
1.8%
양 6
 
1.8%
Other values (99) 218
66.7%
ASCII
ValueCountFrequency (%)
4
100.0%

설립연도
Categorical

Distinct43
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2006
14 
2004
11 
2007
9 
1999
7 
2005
7 
Other values (38)
62 

Length

Max length10
Median length4
Mean length4.0545455
Min length4

Unique

Unique23 ?
Unique (%)20.9%

Sample

1st row1999
2nd row1982
3rd row1999
4th row2007
5th row1997

Common Values

ValueCountFrequency (%)
2006 14
 
12.7%
2004 11
 
10.0%
2007 9
 
8.2%
1999 7
 
6.4%
2005 7
 
6.4%
2003 5
 
4.5%
2000 4
 
3.6%
1997 3
 
2.7%
1982 3
 
2.7%
2002 3
 
2.7%
Other values (33) 44
40.0%

Length

2024-03-14T08:53:42.774421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2006 14
 
12.7%
2004 11
 
10.0%
2007 9
 
8.2%
1999 7
 
6.4%
2005 7
 
6.4%
2003 5
 
4.5%
2000 4
 
3.6%
1997 3
 
2.7%
1982 3
 
2.7%
2002 3
 
2.7%
Other values (33) 44
40.0%

주소지
Text

UNIQUE 

Distinct110
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2024-03-14T08:53:43.055947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length19
Mean length15.081818
Min length10

Characters and Unicode

Total characters1659
Distinct characters170
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique110 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 전주천동로 483
2nd row전주시 완산구 바람쐬는길 152
3rd row전주시 완산구 서노송동 560-6
4th row전주시 완산구 전주객사 2길 12-8
5th row전주시 완산구 선너머로 35-3
ValueCountFrequency (%)
전주시 28
 
6.8%
완산구 19
 
4.6%
익산시 16
 
3.9%
군산시 13
 
3.1%
완주군 13
 
3.1%
남원시 10
 
2.4%
덕진구 9
 
2.2%
정읍시 8
 
1.9%
김제시 6
 
1.5%
고창군 4
 
1.0%
Other values (249) 287
69.5%
2024-03-14T08:53:43.445412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
303
 
18.3%
시 81
 
4.9%
1 61
 
3.7%
산 61
 
3.7%
로 57
 
3.4%
길 54
 
3.3%
2 52
 
3.1%
주 47
 
2.8%
- 45
 
2.7%
4 45
 
2.7%
Other values (160) 853
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 953
57.4%
Decimal Number 354
 
21.3%
Space Separator 303
 
18.3%
Dash Punctuation 45
 
2.7%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 81
 
8.5%
산 61
 
6.4%
로 57
 
6.0%
길 54
 
5.7%
주 47
 
4.9%
군 39
 
4.1%
면 38
 
4.0%
전 33
 
3.5%
완 32
 
3.4%
구 31
 
3.3%
Other values (146) 480
50.4%
Decimal Number
ValueCountFrequency (%)
1 61
17.2%
2 52
14.7%
4 45
12.7%
3 36
10.2%
7 33
9.3%
6 32
9.0%
9 29
8.2%
5 26
7.3%
8 23
 
6.5%
0 17
 
4.8%
Space Separator
ValueCountFrequency (%)
303
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 953
57.4%
Common 706
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 81
 
8.5%
산 61
 
6.4%
로 57
 
6.0%
길 54
 
5.7%
주 47
 
4.9%
군 39
 
4.1%
면 38
 
4.0%
전 33
 
3.5%
완 32
 
3.4%
구 31
 
3.3%
Other values (146) 480
50.4%
Common
ValueCountFrequency (%)
303
42.9%
1 61
 
8.6%
2 52
 
7.4%
- 45
 
6.4%
4 45
 
6.4%
3 36
 
5.1%
7 33
 
4.7%
6 32
 
4.5%
9 29
 
4.1%
5 26
 
3.7%
Other values (4) 44
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 953
57.4%
ASCII 706
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
303
42.9%
1 61
 
8.6%
2 52
 
7.4%
- 45
 
6.4%
4 45
 
6.4%
3 36
 
5.1%
7 33
 
4.7%
6 32
 
4.5%
9 29
 
4.1%
5 26
 
3.7%
Other values (4) 44
 
6.2%
Hangul
ValueCountFrequency (%)
시 81
 
8.5%
산 61
 
6.4%
로 57
 
6.0%
길 54
 
5.7%
주 47
 
4.9%
군 39
 
4.1%
면 38
 
4.0%
전 33
 
3.5%
완 32
 
3.4%
구 31
 
3.3%
Other values (146) 480
50.4%

시설 유형 (시설법인 1,지원법인 2)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1012.0 B
1
104 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 104
94.5%
2 6
 
5.5%

Length

2024-03-14T08:53:43.565324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:53:43.637944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 104
94.5%
2 6
 
5.5%

비고
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing110
Missing (%)100.0%
Memory size1.1 KiB

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
보건의료과
110 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건의료과 110
100.0%

Length

2024-03-14T08:53:43.717689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:53:43.793847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건의료과 110
100.0%

Interactions

2024-03-14T08:53:40.756658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T08:53:43.854731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구설립연도시설 유형 (시설법인 1,지원법인 2)
연번1.0000.9210.3230.000
시군구0.9211.0000.5610.000
설립연도0.3230.5611.0000.000
시설 유형 (시설법인 1,지원법인 2)0.0000.0000.0001.000
2024-03-14T08:53:43.943894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설 유형 (시설법인 1,지원법인 2)설립연도시군구
시설 유형 (시설법인 1,지원법인 2)1.0000.0000.000
설립연도0.0001.0000.159
시군구0.0000.1591.000
2024-03-14T08:53:44.023664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구설립연도시설 유형 (시설법인 1,지원법인 2)
연번1.0000.7110.0740.000
시군구0.7111.0000.1590.000
설립연도0.0740.1591.0000.000
시설 유형 (시설법인 1,지원법인 2)0.0000.0000.0001.000

Missing values

2024-03-14T08:53:40.848649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:53:40.964286image/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

연번시도시군구법 인 명대표자명설립연도주소지시설 유형 (시설법인 1,지원법인 2)비고자료출처
01전북전주시전라북도사회복지협의회차종선1999전주시 덕진구 전주천동로 4832<NA>보건의료과
12전북전주시참사랑복지회양기승1982전주시 완산구 바람쐬는길 1521<NA>보건의료과
23전북전주시천주교성가복지회이병호1999전주시 완산구 서노송동 560-61<NA>보건의료과
34전북전주시전주시사회복지협의회김정석2007전주시 완산구 전주객사 2길 12-82<NA>보건의료과
45전북전주시한빛원임석기1997전주시 완산구 선너머로 35-31<NA>보건의료과
56전북전주시성혜복지재단송독열1997전주시 덕진구 석소로 74-51<NA>보건의료과
67전북전주시삼성원김옥정1956전주시 완산구 만지길 20-151<NA>보건의료과
78전북전주시선덕복지재단김준진1968전주시 완산구 모악로 47041<NA>보건의료과
89전북전주시호성원나종범1957전주시 덕진구 추천로 217-281<NA>보건의료과
910전북전주시한울안김정선2000전주시 완산구 팔달로 192-41<NA>보건의료과
연번시도시군구법 인 명대표자명설립연도주소지시설 유형 (시설법인 1,지원법인 2)비고자료출처
100101전북임실군섬김복지재단김경순2004임실군 오수면 삼일로 22-131<NA>보건의료과
101102전북임실군크리스찬복지재단노 준1998임실군 신평면 석등슬치로 491-71<NA>보건의료과
102103전북임실군미리암복지재단고병훈2006임실군 임실읍 호국로 1716-151<NA>보건의료과
103104전북순창군순창군사회복지협의회민선홍2006순창군 순창읍 옥천로 662<NA>보건의료과
104105전북순창군원산원서양원2009순창읍 남계리 638-51<NA>보건의료과
105106전북순창군도실원김인영1999순창읍 장류로 289-31<NA>보건의료과
106107전북고창군고창행복원전준구1986고창군 고창읍 모양성로 116-131<NA>보건의료과
107108전북고창군아모스김성강1973고창군 무장면 학천로 2211<NA>보건의료과
108109전북고창군아름다운마을김범일2004고창군 상하면 풍촌길 81<NA>보건의료과
109110전북고창군선운사 복지재단(대한불교조계종)황찬연2011고창군 아산면 선운사로 2501<NA>보건의료과