Overview

Dataset statistics

Number of variables5
Number of observations93
Missing cells34
Missing cells (%)7.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory42.4 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description2023년 기준으로 계룡시 관내 종교시설 현황에 관한 데이터로서, 시설명칭, 주소, 종교분류, 전화번호를 공공데이터로 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=309&beforeMenuCd=DOM_000000201001001000&publicdatapk=15093923

Alerts

연번 is highly overall correlated with 종교별High correlation
종교별 is highly overall correlated with 연번High correlation
일반전화 has 34 (36.6%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 23:12:22.159630
Analysis finished2024-01-09 23:12:22.660651
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-01-10T08:12:22.732865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.6
Q124
median47
Q370
95-th percentile88.4
Maximum93
Range92
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.990739
Coefficient of variation (CV)0.57427105
Kurtosis-1.2
Mean47
Median Absolute Deviation (MAD)23
Skewness0
Sum4371
Variance728.5
MonotonicityStrictly increasing
2024-01-10T08:12:22.854599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%

시설명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-01-10T08:12:23.108260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length5.3870968
Min length3

Characters and Unicode

Total characters501
Distinct characters137
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

Unique93 ?
Unique (%)100.0%

Sample

1st row주사랑교회
2nd row행복한교회
3rd row아름다운교회
4th row푸른초장교회
5th row온누리교회
ValueCountFrequency (%)
계룡교회 3
 
3.0%
원불교 2
 
2.0%
주사랑교회 1
 
1.0%
연합장로교회 1
 
1.0%
삼위일체성당 1
 
1.0%
계룡성당 1
 
1.0%
새늘교회 1
 
1.0%
시온교회 1
 
1.0%
신광교회 1
 
1.0%
빛의교회 1
 
1.0%
Other values (87) 87
87.0%
2024-01-10T08:12:23.493156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 77
 
15.4%
회 72
 
14.4%
사 22
 
4.4%
계 16
 
3.2%
룡 14
 
2.8%
도 9
 
1.8%
로 8
 
1.6%
7
 
1.4%
의 7
 
1.4%
원 7
 
1.4%
Other values (127) 262
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 494
98.6%
Space Separator 7
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 77
 
15.6%
회 72
 
14.6%
사 22
 
4.5%
계 16
 
3.2%
룡 14
 
2.8%
도 9
 
1.8%
로 8
 
1.6%
의 7
 
1.4%
원 7
 
1.4%
한 7
 
1.4%
Other values (126) 255
51.6%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 494
98.6%
Common 7
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 77
 
15.6%
회 72
 
14.6%
사 22
 
4.5%
계 16
 
3.2%
룡 14
 
2.8%
도 9
 
1.8%
로 8
 
1.6%
의 7
 
1.4%
원 7
 
1.4%
한 7
 
1.4%
Other values (126) 255
51.6%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 494
98.6%
ASCII 7
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 77
 
15.6%
회 72
 
14.6%
사 22
 
4.5%
계 16
 
3.2%
룡 14
 
2.8%
도 9
 
1.8%
로 8
 
1.6%
의 7
 
1.4%
원 7
 
1.4%
한 7
 
1.4%
Other values (126) 255
51.6%
ASCII
ValueCountFrequency (%)
7
100.0%

주소
Text

Distinct92
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-01-10T08:12:23.805838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length30
Mean length21.354839
Min length15

Characters and Unicode

Total characters1986
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)97.8%

Sample

1st row충청남도 계룡시 금암동 169-12
2nd row충청남도 계룡시 금암동 장안2길 3-2
3rd row충청남도 계룡시 금암동 장안1길 24
4th row충청남도 계룡시 장안로 43 대승프라자 4층
5th row충청남도 계룡시 서금암로 19, 7층
ValueCountFrequency (%)
충청남도 93
20.1%
계룡시 93
20.1%
엄사면 52
 
11.3%
금암동 11
 
2.4%
두마면 10
 
2.2%
번영로 9
 
1.9%
번영3길 7
 
1.5%
계룡대로 5
 
1.1%
신도안면 5
 
1.1%
전원로 5
 
1.1%
Other values (143) 172
37.2%
2024-01-10T08:12:24.268473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
370
18.6%
도 102
 
5.1%
계 101
 
5.1%
룡 99
 
5.0%
남 97
 
4.9%
충 93
 
4.7%
시 93
 
4.7%
청 93
 
4.7%
1 71
 
3.6%
면 67
 
3.4%
Other values (73) 800
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1235
62.2%
Space Separator 370
 
18.6%
Decimal Number 331
 
16.7%
Dash Punctuation 41
 
2.1%
Other Punctuation 9
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 102
 
8.3%
계 101
 
8.2%
룡 99
 
8.0%
남 97
 
7.9%
충 93
 
7.5%
시 93
 
7.5%
청 93
 
7.5%
면 67
 
5.4%
사 58
 
4.7%
엄 55
 
4.5%
Other values (60) 377
30.5%
Decimal Number
ValueCountFrequency (%)
1 71
21.5%
2 56
16.9%
3 49
14.8%
4 30
9.1%
6 28
 
8.5%
0 23
 
6.9%
8 22
 
6.6%
9 20
 
6.0%
5 17
 
5.1%
7 15
 
4.5%
Space Separator
ValueCountFrequency (%)
370
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1235
62.2%
Common 751
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 102
 
8.3%
계 101
 
8.2%
룡 99
 
8.0%
남 97
 
7.9%
충 93
 
7.5%
시 93
 
7.5%
청 93
 
7.5%
면 67
 
5.4%
사 58
 
4.7%
엄 55
 
4.5%
Other values (60) 377
30.5%
Common
ValueCountFrequency (%)
370
49.3%
1 71
 
9.5%
2 56
 
7.5%
3 49
 
6.5%
- 41
 
5.5%
4 30
 
4.0%
6 28
 
3.7%
0 23
 
3.1%
8 22
 
2.9%
9 20
 
2.7%
Other values (3) 41
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1235
62.2%
ASCII 751
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
370
49.3%
1 71
 
9.5%
2 56
 
7.5%
3 49
 
6.5%
- 41
 
5.5%
4 30
 
4.0%
6 28
 
3.7%
0 23
 
3.1%
8 22
 
2.9%
9 20
 
2.7%
Other values (3) 41
 
5.5%
Hangul
ValueCountFrequency (%)
도 102
 
8.3%
계 101
 
8.2%
룡 99
 
8.0%
남 97
 
7.9%
충 93
 
7.5%
시 93
 
7.5%
청 93
 
7.5%
면 67
 
5.4%
사 58
 
4.7%
엄 55
 
4.5%
Other values (60) 377
30.5%

종교별
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size876.0 B
기독교
68 
불교
14 
기타
9 
천주교
 
2

Length

Max length3
Median length3
Mean length2.7526882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기독교 68
73.1%
불교 14
 
15.1%
기타 9
 
9.7%
천주교 2
 
2.2%

Length

2024-01-10T08:12:24.410599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:12:24.513095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기독교 68
73.1%
불교 14
 
15.1%
기타 9
 
9.7%
천주교 2
 
2.2%

일반전화
Text

MISSING 

Distinct59
Distinct (%)100.0%
Missing34
Missing (%)36.6%
Memory size876.0 B
2024-01-10T08:12:24.736451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016949
Min length12

Characters and Unicode

Total characters709
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

Unique59 ?
Unique (%)100.0%

Sample

1st row042-719-9179
2nd row042-840-5200
3rd row042-551-5591
4th row042-841-9091
5th row042-840-9191
ValueCountFrequency (%)
042-719-9179 1
 
1.7%
042-841-8320 1
 
1.7%
042-551-0179 1
 
1.7%
042-841-9697 1
 
1.7%
042-551-5690 1
 
1.7%
042-551-3004 1
 
1.7%
042-841-3636 1
 
1.7%
042-841-4528 1
 
1.7%
042-841-1895 1
 
1.7%
042-841-2681 1
 
1.7%
Other values (49) 49
83.1%
2024-01-10T08:12:25.092978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 118
16.6%
4 117
16.5%
0 98
13.8%
1 88
12.4%
2 77
10.9%
8 71
10.0%
5 45
 
6.3%
9 33
 
4.7%
6 25
 
3.5%
7 20
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 591
83.4%
Dash Punctuation 118
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 117
19.8%
0 98
16.6%
1 88
14.9%
2 77
13.0%
8 71
12.0%
5 45
 
7.6%
9 33
 
5.6%
6 25
 
4.2%
7 20
 
3.4%
3 17
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 709
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 118
16.6%
4 117
16.5%
0 98
13.8%
1 88
12.4%
2 77
10.9%
8 71
10.0%
5 45
 
6.3%
9 33
 
4.7%
6 25
 
3.5%
7 20
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 709
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 118
16.6%
4 117
16.5%
0 98
13.8%
1 88
12.4%
2 77
10.9%
8 71
10.0%
5 45
 
6.3%
9 33
 
4.7%
6 25
 
3.5%
7 20
 
2.8%

Interactions

2024-01-10T08:12:22.453573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T08:12:25.188929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명주소종교별일반전화
연번1.0001.0000.9340.8901.000
시설명1.0001.0001.0001.0001.000
주소0.9341.0001.0001.0001.000
종교별0.8901.0001.0001.0001.000
일반전화1.0001.0001.0001.0001.000
2024-01-10T08:12:25.284037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교별
연번1.0000.737
종교별0.7371.000

Missing values

2024-01-10T08:12:22.548589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T08:12:22.627435image/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

연번시설명주소종교별일반전화
01주사랑교회충청남도 계룡시 금암동 169-12기독교<NA>
12행복한교회충청남도 계룡시 금암동 장안2길 3-2기독교042-719-9179
23아름다운교회충청남도 계룡시 금암동 장안1길 24기독교042-840-5200
34푸른초장교회충청남도 계룡시 장안로 43 대승프라자 4층기독교042-551-5591
45온누리교회충청남도 계룡시 서금암로 19, 7층기독교<NA>
56늘사랑교회충청남도 계룡시 금암동 서금암로 53, 3층기독교042-841-9091
67은혜와사랑의교회충청남도 계룡시 서금암로 73기독교042-840-9191
78새빛교회충청남도 계룡시 금암동 대실남북로 36 신성2차 상가 2층기독교042-551-0611
89새생명복된교회충청남도 계룡시 두마면 입암길 298기독교<NA>
910빌립보교회충청남도 계룡시 두마면 왕대2길 21기독교042-841-0694
연번시설명주소종교별일반전화
8384향국암충청남도 계룡시 도곡리 산 65-1불교<NA>
8485거북암충청남도 계룡시 엄사면 향적산길기타042-841-3526
8586원불교 계룡교당충청남도 계룡시 엄사면 번영4길 3-8기타042-841-1787
8687천지대안도충청남도 계룡시 엄사면 번영3길 61-15기타<NA>
8788계룡산연화사불무암충청남도 계룡시 엄사면 향적산길 99-32기타<NA>
8889대한불교총화종연화사충청남도 계룡시 엄사면 향적산3길 57기타<NA>
8990증산도 계룡도장충청남도 계룡시 금암동 서금암3길 15기타042-841-9155
9091원불교 계룡대교당충청남도 계룡시 신도안면 계룡대로 663기타<NA>
9192시온산수도원충청남도 계룡시 천마로 89기타042-841-7280
9293하나님의교회세계복음선교회 계룡교회충청남도 계룡시 계룡대로 320, 3층기타<NA>