Overview

Dataset statistics

Number of variables4
Number of observations402
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory33.3 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description전라북도 정읍시 소재한 종교단체 현황중(구분(천주교, 원불교, 불교, 개신교), 종교단체명, 소재지도로명주소)등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/3079860/fileData.do

Alerts

연번 is highly overall correlated with 종교High correlation
종교 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:42:59.403196
Analysis finished2023-12-12 15:42:59.976234
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct402
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201.5
Minimum1
Maximum402
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2023-12-13T00:43:00.060461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.05
Q1101.25
median201.5
Q3301.75
95-th percentile381.95
Maximum402
Range401
Interquartile range (IQR)200.5

Descriptive statistics

Standard deviation116.19165
Coefficient of variation (CV)0.57663351
Kurtosis-1.2
Mean201.5
Median Absolute Deviation (MAD)100.5
Skewness0
Sum81003
Variance13500.5
MonotonicityStrictly increasing
2023-12-13T00:43:00.200558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
266 1
 
0.2%
276 1
 
0.2%
275 1
 
0.2%
274 1
 
0.2%
273 1
 
0.2%
272 1
 
0.2%
271 1
 
0.2%
270 1
 
0.2%
269 1
 
0.2%
Other values (392) 392
97.5%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
402 1
0.2%
401 1
0.2%
400 1
0.2%
399 1
0.2%
398 1
0.2%
397 1
0.2%
396 1
0.2%
395 1
0.2%
394 1
0.2%
393 1
0.2%

종교
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
개신교
293 
불교
79 
원불교
 
18
천주교
 
12

Length

Max length3
Median length3
Mean length2.8034826
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개신교 293
72.9%
불교 79
 
19.7%
원불교 18
 
4.5%
천주교 12
 
3.0%

Length

2023-12-13T00:43:00.338742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:43:00.459831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개신교 293
72.9%
불교 79
 
19.7%
원불교 18
 
4.5%
천주교 12
 
3.0%

종교단체명
Text

Distinct382
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T00:43:00.660065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length5.1169154
Min length3

Characters and Unicode

Total characters2057
Distinct characters237
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

Unique364 ?
Unique (%)90.5%

Sample

1st row천주교신태인성당
2nd row연지성당 한교공소
3rd row연지성당 신평공소
4th row등천공소
5th row태인공소
ValueCountFrequency (%)
원불교 18
 
4.0%
벧엘교회 5
 
1.1%
정읍교회 4
 
0.9%
교회 3
 
0.7%
연지성당 3
 
0.7%
보은교회 2
 
0.4%
은혜교회 2
 
0.4%
칠보교회 2
 
0.4%
정읍 2
 
0.4%
온누리교회 2
 
0.4%
Other values (383) 402
90.3%
2023-12-13T00:43:01.052050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 342
 
16.6%
회 299
 
14.5%
사 73
 
3.5%
정 60
 
2.9%
43
 
2.1%
읍 40
 
1.9%
성 37
 
1.8%
일 29
 
1.4%
원 28
 
1.4%
당 25
 
1.2%
Other values (227) 1081
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2012
97.8%
Space Separator 43
 
2.1%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 342
 
17.0%
회 299
 
14.9%
사 73
 
3.6%
정 60
 
3.0%
읍 40
 
2.0%
성 37
 
1.8%
일 29
 
1.4%
원 28
 
1.4%
당 25
 
1.2%
암 23
 
1.1%
Other values (224) 1056
52.5%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2012
97.8%
Common 45
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 342
 
17.0%
회 299
 
14.9%
사 73
 
3.6%
정 60
 
3.0%
읍 40
 
2.0%
성 37
 
1.8%
일 29
 
1.4%
원 28
 
1.4%
당 25
 
1.2%
암 23
 
1.1%
Other values (224) 1056
52.5%
Common
ValueCountFrequency (%)
43
95.6%
2 1
 
2.2%
1 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2012
97.8%
ASCII 45
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 342
 
17.0%
회 299
 
14.9%
사 73
 
3.6%
정 60
 
3.0%
읍 40
 
2.0%
성 37
 
1.8%
일 29
 
1.4%
원 28
 
1.4%
당 25
 
1.2%
암 23
 
1.1%
Other values (224) 1056
52.5%
ASCII
ValueCountFrequency (%)
43
95.6%
2 1
 
2.2%
1 1
 
2.2%

도로명주소
Text

Distinct400
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-12-13T00:43:01.322026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length23
Mean length15.049751
Min length9

Characters and Unicode

Total characters6050
Distinct characters202
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

Unique398 ?
Unique (%)99.0%

Sample

1st row정읍시 신태인읍 정신로 1196
2nd row정읍시 북면 북신촌2길 9-8
3rd row정읍시 북면 서신길 25-34
4th row정읍시 입암면 등천리 117-3
5th row정읍시 태인면 태거길 2924
ValueCountFrequency (%)
정읍시 422
29.2%
북면 22
 
1.5%
신태인읍 21
 
1.5%
감곡면 20
 
1.4%
고부면 19
 
1.3%
태인면 16
 
1.1%
칠보면 16
 
1.1%
산외면 14
 
1.0%
덕천면 14
 
1.0%
입암면 14
 
1.0%
Other values (609) 869
60.1%
2023-12-13T00:43:01.722626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1048
17.3%
정 480
 
7.9%
읍 454
 
7.5%
시 423
 
7.0%
1 330
 
5.5%
길 250
 
4.1%
2 214
 
3.5%
면 200
 
3.3%
- 192
 
3.2%
3 151
 
2.5%
Other values (192) 2308
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3372
55.7%
Decimal Number 1396
23.1%
Space Separator 1048
 
17.3%
Dash Punctuation 192
 
3.2%
Close Punctuation 15
 
0.2%
Open Punctuation 15
 
0.2%
Other Punctuation 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 480
14.2%
읍 454
 
13.5%
시 423
 
12.5%
길 250
 
7.4%
면 200
 
5.9%
로 142
 
4.2%
산 83
 
2.5%
태 65
 
1.9%
신 58
 
1.7%
성 54
 
1.6%
Other values (175) 1163
34.5%
Decimal Number
ValueCountFrequency (%)
1 330
23.6%
2 214
15.3%
3 151
10.8%
4 142
10.2%
5 119
 
8.5%
6 109
 
7.8%
7 99
 
7.1%
9 84
 
6.0%
8 75
 
5.4%
0 73
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 10
83.3%
. 1
 
8.3%
@ 1
 
8.3%
Space Separator
ValueCountFrequency (%)
1048
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3372
55.7%
Common 2678
44.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 480
14.2%
읍 454
 
13.5%
시 423
 
12.5%
길 250
 
7.4%
면 200
 
5.9%
로 142
 
4.2%
산 83
 
2.5%
태 65
 
1.9%
신 58
 
1.7%
성 54
 
1.6%
Other values (175) 1163
34.5%
Common
ValueCountFrequency (%)
1048
39.1%
1 330
 
12.3%
2 214
 
8.0%
- 192
 
7.2%
3 151
 
5.6%
4 142
 
5.3%
5 119
 
4.4%
6 109
 
4.1%
7 99
 
3.7%
9 84
 
3.1%
Other values (7) 190
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3372
55.7%
ASCII 2678
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1048
39.1%
1 330
 
12.3%
2 214
 
8.0%
- 192
 
7.2%
3 151
 
5.6%
4 142
 
5.3%
5 119
 
4.4%
6 109
 
4.1%
7 99
 
3.7%
9 84
 
3.1%
Other values (7) 190
 
7.1%
Hangul
ValueCountFrequency (%)
정 480
14.2%
읍 454
 
13.5%
시 423
 
12.5%
길 250
 
7.4%
면 200
 
5.9%
로 142
 
4.2%
산 83
 
2.5%
태 65
 
1.9%
신 58
 
1.7%
성 54
 
1.6%
Other values (175) 1163
34.5%

Interactions

2023-12-13T00:42:59.685076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:43:01.822438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교
연번1.0000.850
종교0.8501.000
2023-12-13T00:43:01.909268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종교
연번1.0000.692
종교0.6921.000

Missing values

2023-12-13T00:42:59.825466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:42:59.939821image/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

연번종교종교단체명도로명주소
01천주교천주교신태인성당정읍시 신태인읍 정신로 1196
12천주교연지성당 한교공소정읍시 북면 북신촌2길 9-8
23천주교연지성당 신평공소정읍시 북면 서신길 25-34
34천주교등천공소정읍시 입암면 등천리 117-3
45천주교태인공소정읍시 태인면 태거길 2924
56천주교신기공소정읍시 태인면 신기1길 103
67천주교옥단공소정읍시 감곡면 옥신2길 17
78천주교석점공소정읍시 감곡면 석점1길 43-1
89천주교천주교 칠보성당정읍시 칠보면 칠보중앙로 103-27
910천주교천주교 능교공소정읍시 산내면 능교신기길 12-10
연번종교종교단체명도로명주소
392393개신교사랑의교회정읍시 용흥2길 3
393394개신교신일교회정읍시 신정마을길 42-7
394395개신교신정교회정읍시 부귀1길 43
395396개신교신정중앙교회정읍시 정촌1길 60
396397개신교우리교회정읍시 이슬어지길3
397398개신교정읍성광교회정읍시 월천길 44
398399개신교향지교회정읍시 향지길 69
399400개신교임마누엘정읍교회정읍시 용흥2길 7-1(상평동)
400401개신교푸른초장교회정읍시 용흥1길 15-19
401402개신교호남장로교회정읍시 용흥1길 15-48