Overview

Dataset statistics

Number of variables5
Number of observations308
Missing cells71
Missing cells (%)4.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.5 KiB
Average record size in memory41.4 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description본 공공데이터는 완주군내 종교시설(단체)현황 정보를 제공하는 공공데이터로 종교(사찰, 절, 교회, 성당), 시설명, 주소, 등의 정보를 포함하고 있습니다.
Author전라북도 완주군
URLhttps://www.data.go.kr/data/15037118/fileData.do

Alerts

종교 is highly imbalanced (61.2%)Imbalance
전화번호 has 71 (23.1%) missing valuesMissing
연번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-14 23:53:22.074277
Analysis finished2024-03-14 23:53:22.997935
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.5
Minimum1
Maximum308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-15T08:53:23.127969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.35
Q177.75
median154.5
Q3231.25
95-th percentile292.65
Maximum308
Range307
Interquartile range (IQR)153.5

Descriptive statistics

Standard deviation89.056162
Coefficient of variation (CV)0.57641529
Kurtosis-1.2
Mean154.5
Median Absolute Deviation (MAD)77
Skewness0
Sum47586
Variance7931
MonotonicityStrictly increasing
2024-03-15T08:53:23.491390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
208 1
 
0.3%
207 1
 
0.3%
206 1
 
0.3%
204 1
 
0.3%
Other values (298) 298
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
308 1
0.3%
307 1
0.3%
306 1
0.3%
305 1
0.3%
304 1
0.3%
303 1
0.3%
302 1
0.3%
301 1
0.3%
300 1
0.3%
299 1
0.3%

종교
Categorical

IMBALANCE 

Distinct10
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
개신교
213 
불교
73 
천주교
 
11
원불교
 
5
개신교(하나님의 교회)
 
1
Other values (5)
 
5

Length

Max length12
Median length3
Mean length2.8344156
Min length2

Unique

Unique6 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
개신교 213
69.2%
불교 73
 
23.7%
천주교 11
 
3.6%
원불교 5
 
1.6%
개신교(하나님의 교회) 1
 
0.3%
개신교(여호와의 증인) 1
 
0.3%
기타(통일교) 1
 
0.3%
기독교 1
 
0.3%
유교 1
 
0.3%
이슬람교 1
 
0.3%

Length

2024-03-15T08:53:23.902046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:53:24.117997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개신교 213
68.7%
불교 73
 
23.5%
천주교 11
 
3.5%
원불교 5
 
1.6%
개신교(하나님의 1
 
0.3%
교회 1
 
0.3%
개신교(여호와의 1
 
0.3%
증인 1
 
0.3%
기타(통일교 1
 
0.3%
기독교 1
 
0.3%
Other values (2) 2
 
0.6%

시설명
Text

Distinct294
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T08:53:25.416295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length5.0324675
Min length3

Characters and Unicode

Total characters1550
Distinct characters231
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

Unique283 ?
Unique (%)91.9%

Sample

1st row늘푸른교회
2nd row평강교회
3rd row동부교회
4th row제일교회
5th row침례교회
ValueCountFrequency (%)
교회 4
 
1.2%
임마누엘교회 3
 
0.9%
샘물교회 3
 
0.9%
동부교회 3
 
0.9%
관음사 3
 
0.9%
새에덴교회 2
 
0.6%
성결교회 2
 
0.6%
사랑의교회 2
 
0.6%
원불교 2
 
0.6%
은혜교회 2
 
0.6%
Other values (297) 304
92.1%
2024-03-15T08:53:26.934424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 239
 
15.4%
회 216
 
13.9%
사 71
 
4.6%
원 28
 
1.8%
23
 
1.5%
암 23
 
1.5%
성 21
 
1.4%
동 20
 
1.3%
주 20
 
1.3%
봉 20
 
1.3%
Other values (221) 869
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1492
96.3%
Space Separator 23
 
1.5%
Close Punctuation 18
 
1.2%
Open Punctuation 17
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 239
 
16.0%
회 216
 
14.5%
사 71
 
4.8%
원 28
 
1.9%
암 23
 
1.5%
성 21
 
1.4%
동 20
 
1.3%
주 20
 
1.3%
봉 20
 
1.3%
수 20
 
1.3%
Other values (218) 814
54.6%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1492
96.3%
Common 58
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 239
 
16.0%
회 216
 
14.5%
사 71
 
4.8%
원 28
 
1.9%
암 23
 
1.5%
성 21
 
1.4%
동 20
 
1.3%
주 20
 
1.3%
봉 20
 
1.3%
수 20
 
1.3%
Other values (218) 814
54.6%
Common
ValueCountFrequency (%)
23
39.7%
) 18
31.0%
( 17
29.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1492
96.3%
ASCII 58
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 239
 
16.0%
회 216
 
14.5%
사 71
 
4.8%
원 28
 
1.9%
암 23
 
1.5%
성 21
 
1.4%
동 20
 
1.3%
주 20
 
1.3%
봉 20
 
1.3%
수 20
 
1.3%
Other values (218) 814
54.6%
ASCII
ValueCountFrequency (%)
23
39.7%
) 18
31.0%
( 17
29.3%

도로명주소
Text

UNIQUE 

Distinct308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-15T08:53:28.893819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length25.412338
Min length19

Characters and Unicode

Total characters7827
Distinct characters185
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 완주군 삼례읍 웃삼례길 18
2nd row전북특별자치도 완주군 삼례읍 삼봉로 67-27
3rd row전북특별자치도 완주군 삼례읍 역참로53
4th row전북특별자치도 완주군 삼례읍 만경하서길 18
5th row전북특별자치도 완주군 삼례읍 마천3길 5
ValueCountFrequency (%)
전북특별자치도 307
19.6%
완주군 305
19.5%
소양면 44
 
2.8%
봉동읍 42
 
2.7%
삼례읍 34
 
2.2%
구이면 33
 
2.1%
용진읍 31
 
2.0%
이서면 23
 
1.5%
고산면 22
 
1.4%
화산면 19
 
1.2%
Other values (495) 703
45.0%
2024-03-15T08:53:31.906229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1430
18.3%
주 333
 
4.3%
전 317
 
4.1%
완 316
 
4.0%
치 313
 
4.0%
도 312
 
4.0%
북 310
 
4.0%
별 309
 
3.9%
자 309
 
3.9%
특 308
 
3.9%
Other values (175) 3570
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5211
66.6%
Space Separator 1430
 
18.3%
Decimal Number 1028
 
13.1%
Dash Punctuation 136
 
1.7%
Other Punctuation 7
 
0.1%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 333
 
6.4%
전 317
 
6.1%
완 316
 
6.1%
치 313
 
6.0%
도 312
 
6.0%
북 310
 
5.9%
별 309
 
5.9%
자 309
 
5.9%
특 308
 
5.9%
군 307
 
5.9%
Other values (157) 2077
39.9%
Decimal Number
ValueCountFrequency (%)
1 216
21.0%
2 133
12.9%
3 113
11.0%
4 102
9.9%
7 89
8.7%
5 86
 
8.4%
6 84
 
8.2%
8 79
 
7.7%
9 72
 
7.0%
0 54
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
1430
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5211
66.6%
Common 2613
33.4%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 333
 
6.4%
전 317
 
6.1%
완 316
 
6.1%
치 313
 
6.0%
도 312
 
6.0%
북 310
 
5.9%
별 309
 
5.9%
자 309
 
5.9%
특 308
 
5.9%
군 307
 
5.9%
Other values (157) 2077
39.9%
Common
ValueCountFrequency (%)
1430
54.7%
1 216
 
8.3%
- 136
 
5.2%
2 133
 
5.1%
3 113
 
4.3%
4 102
 
3.9%
7 89
 
3.4%
5 86
 
3.3%
6 84
 
3.2%
8 79
 
3.0%
Other values (5) 145
 
5.5%
Latin
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5211
66.6%
ASCII 2616
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1430
54.7%
1 216
 
8.3%
- 136
 
5.2%
2 133
 
5.1%
3 113
 
4.3%
4 102
 
3.9%
7 89
 
3.4%
5 86
 
3.3%
6 84
 
3.2%
8 79
 
3.0%
Other values (8) 148
 
5.7%
Hangul
ValueCountFrequency (%)
주 333
 
6.4%
전 317
 
6.1%
완 316
 
6.1%
치 313
 
6.0%
도 312
 
6.0%
북 310
 
5.9%
별 309
 
5.9%
자 309
 
5.9%
특 308
 
5.9%
군 307
 
5.9%
Other values (157) 2077
39.9%

전화번호
Text

MISSING 

Distinct230
Distinct (%)97.0%
Missing71
Missing (%)23.1%
Memory size2.5 KiB
2024-03-15T08:53:32.860152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016878
Min length12

Characters and Unicode

Total characters2848
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

Unique224 ?
Unique (%)94.5%

Sample

1st row063-291-6213
2nd row063-291-8788
3rd row063-291-3364
4th row063-291-9820
5th row063-291-2375
ValueCountFrequency (%)
063-291-3364 3
 
1.3%
063-263-7475 2
 
0.8%
063-261-6914 2
 
0.8%
063-261-9339 2
 
0.8%
063-243-7178 2
 
0.8%
063-282-5526 2
 
0.8%
063-263-5213 1
 
0.4%
063-244-7808 1
 
0.4%
063-243-9026 1
 
0.4%
063-243-9044 1
 
0.4%
Other values (220) 220
92.8%
2024-03-15T08:53:33.964145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 474
16.6%
6 422
14.8%
3 411
14.4%
2 406
14.3%
0 338
11.9%
1 179
 
6.3%
4 176
 
6.2%
8 114
 
4.0%
7 113
 
4.0%
5 108
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2374
83.4%
Dash Punctuation 474
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 422
17.8%
3 411
17.3%
2 406
17.1%
0 338
14.2%
1 179
7.5%
4 176
7.4%
8 114
 
4.8%
7 113
 
4.8%
5 108
 
4.5%
9 107
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2848
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 474
16.6%
6 422
14.8%
3 411
14.4%
2 406
14.3%
0 338
11.9%
1 179
 
6.3%
4 176
 
6.2%
8 114
 
4.0%
7 113
 
4.0%
5 108
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 474
16.6%
6 422
14.8%
3 411
14.4%
2 406
14.3%
0 338
11.9%
1 179
 
6.3%
4 176
 
6.2%
8 114
 
4.0%
7 113
 
4.0%
5 108
 
3.8%

Interactions

2024-03-15T08:53:22.537321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T08:53:34.132399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교
연번1.0000.809
종교0.8091.000
2024-03-15T08:53:34.274699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교
연번1.0000.373
종교0.3731.000

Missing values

2024-03-15T08:53:22.747248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:53:22.929978image/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

연번종교시설명도로명주소전화번호
01개신교늘푸른교회전북특별자치도 완주군 삼례읍 웃삼례길 18063-291-6213
12개신교평강교회전북특별자치도 완주군 삼례읍 삼봉로 67-27063-291-8788
23개신교동부교회전북특별자치도 완주군 삼례읍 역참로53063-291-3364
34개신교제일교회전북특별자치도 완주군 삼례읍 만경하서길 18063-291-9820
45개신교침례교회전북특별자치도 완주군 삼례읍 마천3길 5063-291-2375
56개신교축복의 교회전북특별자치도 완주군 삼례읍 마천3길 21-9063-291-8191
67개신교새에덴교회전북특별자치도 완주군 삼례읍 삼례역로 46<NA>
78개신교해전교회전북특별자치도 완주군 삼례읍 해전길 24063-291-2975
89개신교샘물교회전북특별자치도 완주군 삼례읍 신기길 34-21063-261-9339
910개신교예선교회전북특별자치도 완주군 삼례읍 삼봉로 117<NA>
연번종교시설명도로명주소전화번호
298299천주교용진성당전북특별자치도 완주군 용진읍 신지송광로 399<NA>
299300천주교상관성당전북특별자치도 완주군 상관면 신리 616063-285-6652
300301천주교초남이성지전북특별자치도 완주군 이서면 초남신기길 122-1063-214-5004
301302천주교소양성당전북특별자치도 완주군 소양면 망표길 13063-244-3007
302303천주교천주교유지재단(해월리 피정의집)전북특별자치도 완주군 소양면 다리안길 77-9063-244-4101
303304천주교고산성당전북특별자치도 완주군 고산면 읍내7길 20063-261-6012
304305천주교되재성당전북특별자치도 완주군 화산면 승치로 477<NA>
305306천주교천주교피정의집전북특별자치도 완주군 비봉면 천호성지길 124063-263-1004
306307유교고산향교전북특별자치도 완주군 고산면 고산로 147-23063-263-4066
307308이슬람교이슬람예배소 무쌀라전북특별자치도 완주군 봉동읍 봉동동서로 134-10<NA>