Overview

Dataset statistics

Number of variables8
Number of observations68
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory67.9 B

Variable types

Numeric2
Categorical2
Text4

Dataset

Description전북특별자치도 장사시설현황에 대한 데이터입니다.연번, 시군, 명칭, 위치, 관리주체, 전화번호, 설치연도를 제공합니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15045443/fileData.do

Alerts

연번 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 연번High correlation
관리주체 has 1 (1.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 18:38:15.130335
Analysis finished2024-03-14 18:38:17.997286
Duration2.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-15T03:38:18.328081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-03-15T03:38:18.775815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size672.0 B
공설묘지
17 
공설봉안시설
9 
사설(법인)봉안시설
9 
공설자연장지
8 
사설(종교단체)봉안시설
8 
Other values (4)
17 

Length

Max length12
Median length9
Mean length7.0735294
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공설묘지 17
25.0%
공설봉안시설 9
13.2%
사설(법인)봉안시설 9
13.2%
공설자연장지 8
11.8%
사설(종교단체)봉안시설 8
11.8%
사설(법인)묘지 7
10.3%
화장장 5
 
7.4%
사설(법인)자연장지 3
 
4.4%
사설(종교단체)자연장지 2
 
2.9%

Length

2024-03-15T03:38:19.362490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:38:19.817568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공설묘지 17
25.0%
공설봉안시설 9
13.2%
사설(법인)봉안시설 9
13.2%
공설자연장지 8
11.8%
사설(종교단체)봉안시설 8
11.8%
사설(법인)묘지 7
10.3%
화장장 5
 
7.4%
사설(법인)자연장지 3
 
4.4%
사설(종교단체)자연장지 2
 
2.9%

시군
Categorical

Distinct15
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Memory size672.0 B
전주시
14 
익산시
8 
완주군
7 
정읍시
6 
군산시
5 
Other values (10)
28 

Length

Max length4
Median length3
Mean length3.0735294
Min length3

Unique

Unique3 ?
Unique (%)4.4%

Sample

1st row전주시
2nd row군산시
3rd row익산시
4th row정읍시
5th row남원시

Common Values

ValueCountFrequency (%)
전주시 14
20.6%
익산시 8
11.8%
완주군 7
10.3%
정읍시 6
8.8%
군산시 5
 
7.4%
김제시 5
 
7.4%
고창군 5
 
7.4%
남원시 4
 
5.9%
진안군 4
 
5.9%
무주군 3
 
4.4%
Other values (5) 7
10.3%

Length

2024-03-15T03:38:20.295849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 14
20.6%
익산시 8
11.8%
완주군 7
10.3%
고창군 7
10.3%
정읍시 6
8.8%
군산시 5
 
7.4%
김제시 5
 
7.4%
남원시 4
 
5.9%
진안군 4
 
5.9%
무주군 3
 
4.4%
Other values (4) 5
 
7.4%

명칭
Text

Distinct63
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-15T03:38:21.283762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length7.5882353
Min length3

Characters and Unicode

Total characters516
Distinct characters112
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

Unique59 ?
Unique (%)86.8%

Sample

1st row전주승화원
2nd row군산시승화원
3rd row익산시정수원
4th row서남권추모공원
5th row남원시승화원
ValueCountFrequency (%)
집 4
 
4.7%
영모묘원 3
 
3.5%
추모의 3
 
3.5%
호정공원 3
 
3.5%
지평선(금선화)공원묘원 2
 
2.3%
전주효자자연장(1차 2
 
2.3%
봉안당 2
 
2.3%
2차 2
 
2.3%
전주효자공원 2
 
2.3%
봉안원(봉안담 1
 
1.2%
Other values (62) 62
72.1%
2024-03-15T03:38:22.454410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 45
 
8.7%
공 40
 
7.8%
모 21
 
4.1%
18
 
3.5%
자 16
 
3.1%
설 16
 
3.1%
추 15
 
2.9%
화 13
 
2.5%
묘 12
 
2.3%
장 12
 
2.3%
Other values (102) 308
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 472
91.5%
Space Separator 18
 
3.5%
Close Punctuation 9
 
1.7%
Open Punctuation 9
 
1.7%
Other Punctuation 4
 
0.8%
Decimal Number 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 45
 
9.5%
공 40
 
8.5%
모 21
 
4.4%
자 16
 
3.4%
설 16
 
3.4%
추 15
 
3.2%
화 13
 
2.8%
묘 12
 
2.5%
장 12
 
2.5%
주 11
 
2.3%
Other values (96) 271
57.4%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
91.5%
Common 44
 
8.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 45
 
9.5%
공 40
 
8.5%
모 21
 
4.4%
자 16
 
3.4%
설 16
 
3.4%
추 15
 
3.2%
화 13
 
2.8%
묘 12
 
2.5%
장 12
 
2.5%
주 11
 
2.3%
Other values (96) 271
57.4%
Common
ValueCountFrequency (%)
18
40.9%
) 9
20.5%
( 9
20.5%
, 4
 
9.1%
2 2
 
4.5%
1 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 472
91.5%
ASCII 44
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 45
 
9.5%
공 40
 
8.5%
모 21
 
4.4%
자 16
 
3.4%
설 16
 
3.4%
추 15
 
3.2%
화 13
 
2.8%
묘 12
 
2.5%
장 12
 
2.5%
주 11
 
2.3%
Other values (96) 271
57.4%
ASCII
ValueCountFrequency (%)
18
40.9%
) 9
20.5%
( 9
20.5%
, 4
 
9.1%
2 2
 
4.5%
1 2
 
4.5%

위치
Text

Distinct51
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-15T03:38:23.921816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length14.088235
Min length9

Characters and Unicode

Total characters958
Distinct characters129
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

Unique43 ?
Unique (%)63.2%

Sample

1st row완산구 콩쥐팥쥐로 1705-138
2nd row임피면 보석리 401-5외 1필지
3rd row무왕로 1471-63
4th row감곡면 정읍북로 1850
5th row솔터길 40-36
ValueCountFrequency (%)
완산구 13
 
6.1%
콩쥐팥쥐로 10
 
4.7%
산 9
 
4.2%
1705-138 6
 
2.8%
1471-63 4
 
1.9%
무왕로 4
 
1.9%
임피면 4
 
1.9%
왕궁면 3
 
1.4%
금구면 3
 
1.4%
보석리 3
 
1.4%
Other values (123) 153
72.2%
2024-03-15T03:38:25.977004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
 
15.0%
1 71
 
7.4%
- 41
 
4.3%
면 38
 
4.0%
산 37
 
3.9%
7 35
 
3.7%
5 35
 
3.7%
로 33
 
3.4%
0 31
 
3.2%
3 29
 
3.0%
Other values (119) 464
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
49.9%
Decimal Number 293
30.6%
Space Separator 144
 
15.0%
Dash Punctuation 41
 
4.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 38
 
7.9%
산 37
 
7.7%
로 33
 
6.9%
리 25
 
5.2%
쥐 20
 
4.2%
구 17
 
3.6%
완 16
 
3.3%
읍 12
 
2.5%
팥 10
 
2.1%
콩 10
 
2.1%
Other values (105) 260
54.4%
Decimal Number
ValueCountFrequency (%)
1 71
24.2%
7 35
11.9%
5 35
11.9%
0 31
10.6%
3 29
9.9%
4 21
 
7.2%
2 20
 
6.8%
8 20
 
6.8%
6 19
 
6.5%
9 12
 
4.1%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
50.1%
Hangul 478
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 38
 
7.9%
산 37
 
7.7%
로 33
 
6.9%
리 25
 
5.2%
쥐 20
 
4.2%
구 17
 
3.6%
완 16
 
3.3%
읍 12
 
2.5%
팥 10
 
2.1%
콩 10
 
2.1%
Other values (105) 260
54.4%
Common
ValueCountFrequency (%)
144
30.0%
1 71
14.8%
- 41
 
8.5%
7 35
 
7.3%
5 35
 
7.3%
0 31
 
6.5%
3 29
 
6.0%
4 21
 
4.4%
2 20
 
4.2%
8 20
 
4.2%
Other values (4) 33
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
50.1%
Hangul 478
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
30.0%
1 71
14.8%
- 41
 
8.5%
7 35
 
7.3%
5 35
 
7.3%
0 31
 
6.5%
3 29
 
6.0%
4 21
 
4.4%
2 20
 
4.2%
8 20
 
4.2%
Other values (4) 33
 
6.9%
Hangul
ValueCountFrequency (%)
면 38
 
7.9%
산 37
 
7.7%
로 33
 
6.9%
리 25
 
5.2%
쥐 20
 
4.2%
구 17
 
3.6%
완 16
 
3.3%
읍 12
 
2.5%
팥 10
 
2.1%
콩 10
 
2.1%
Other values (105) 260
54.4%

관리주체
Text

MISSING 

Distinct44
Distinct (%)65.7%
Missing1
Missing (%)1.5%
Memory size672.0 B
2024-03-15T03:38:26.983245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length6.0895522
Min length3

Characters and Unicode

Total characters408
Distinct characters77
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

Unique32 ?
Unique (%)47.8%

Sample

1st row전주시설관리공단
2nd row군산시
3rd row익산시
4th row정읍시
5th row남원시
ValueCountFrequency (%)
익산시 5
 
6.8%
고창군 5
 
6.8%
정읍시 4
 
5.4%
재)호정공원 3
 
4.1%
재 3
 
4.1%
진안군 3
 
4.1%
전주시시설관리공단 3
 
4.1%
재)영모묘원 2
 
2.7%
군산시 2
 
2.7%
재)천주교전교구유지재단 2
 
2.7%
Other values (37) 42
56.8%
2024-03-15T03:38:28.318015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 27
 
6.6%
원 23
 
5.6%
) 23
 
5.6%
( 23
 
5.6%
재 21
 
5.1%
군 18
 
4.4%
공 17
 
4.2%
주 15
 
3.7%
정 11
 
2.7%
교 10
 
2.5%
Other values (67) 220
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 355
87.0%
Close Punctuation 23
 
5.6%
Open Punctuation 23
 
5.6%
Space Separator 7
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 27
 
7.6%
원 23
 
6.5%
재 21
 
5.9%
군 18
 
5.1%
공 17
 
4.8%
주 15
 
4.2%
정 11
 
3.1%
교 10
 
2.8%
전 10
 
2.8%
산 9
 
2.5%
Other values (64) 194
54.6%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 355
87.0%
Common 53
 
13.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 27
 
7.6%
원 23
 
6.5%
재 21
 
5.9%
군 18
 
5.1%
공 17
 
4.8%
주 15
 
4.2%
정 11
 
3.1%
교 10
 
2.8%
전 10
 
2.8%
산 9
 
2.5%
Other values (64) 194
54.6%
Common
ValueCountFrequency (%)
) 23
43.4%
( 23
43.4%
7
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 355
87.0%
ASCII 53
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 27
 
7.6%
원 23
 
6.5%
재 21
 
5.9%
군 18
 
5.1%
공 17
 
4.8%
주 15
 
4.2%
정 11
 
3.1%
교 10
 
2.8%
전 10
 
2.8%
산 9
 
2.5%
Other values (64) 194
54.6%
ASCII
ValueCountFrequency (%)
) 23
43.4%
( 23
43.4%
7
 
13.2%

전화번호
Text

Distinct49
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Memory size672.0 B
2024-03-15T03:38:29.346159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.014706
Min length12

Characters and Unicode

Total characters817
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

Unique39 ?
Unique (%)57.4%

Sample

1st row063-239-2690
2nd row063-454-7954
3rd row063-859-3840
4th row063-539-6725
5th row063-632-5874
ValueCountFrequency (%)
063-239-2690 5
 
7.4%
063-859-3840 4
 
5.9%
063-290-2208 3
 
4.4%
063-546-5011 3
 
4.4%
063-836-4311 3
 
4.4%
063-214-1009 3
 
4.4%
063-632-5874 2
 
2.9%
063-560-8503 2
 
2.9%
063-539-5518 2
 
2.9%
063-539-6725 2
 
2.9%
Other values (39) 39
57.4%
2024-03-15T03:38:30.409485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 136
16.6%
0 132
16.2%
3 124
15.2%
6 107
13.1%
2 67
8.2%
5 65
8.0%
4 48
 
5.9%
9 42
 
5.1%
1 42
 
5.1%
8 36
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 681
83.4%
Dash Punctuation 136
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 132
19.4%
3 124
18.2%
6 107
15.7%
2 67
9.8%
5 65
9.5%
4 48
 
7.0%
9 42
 
6.2%
1 42
 
6.2%
8 36
 
5.3%
7 18
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 817
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 136
16.6%
0 132
16.2%
3 124
15.2%
6 107
13.1%
2 67
8.2%
5 65
8.0%
4 48
 
5.9%
9 42
 
5.1%
1 42
 
5.1%
8 36
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 136
16.6%
0 132
16.2%
3 124
15.2%
6 107
13.1%
2 67
8.2%
5 65
8.0%
4 48
 
5.9%
9 42
 
5.1%
1 42
 
5.1%
8 36
 
4.4%

설치연도
Real number (ℝ)

Distinct30
Distinct (%)44.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2002.6324
Minimum1977
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size740.0 B
2024-03-15T03:38:30.856794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1977
5-th percentile1980
Q11996.75
median2004
Q32011.5
95-th percentile2020
Maximum2020
Range43
Interquartile range (IQR)14.75

Descriptive statistics

Standard deviation11.989927
Coefficient of variation (CV)0.0059870833
Kurtosis-0.4403906
Mean2002.6324
Median Absolute Deviation (MAD)7.5
Skewness-0.55028426
Sum136179
Variance143.75834
MonotonicityNot monotonic
2024-03-15T03:38:31.234530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2020 6
 
8.8%
2006 6
 
8.8%
2015 5
 
7.4%
2004 4
 
5.9%
2007 4
 
5.9%
2002 3
 
4.4%
1999 3
 
4.4%
1997 3
 
4.4%
2003 2
 
2.9%
1993 2
 
2.9%
Other values (20) 30
44.1%
ValueCountFrequency (%)
1977 2
2.9%
1979 1
1.5%
1980 2
2.9%
1981 2
2.9%
1983 2
2.9%
1988 1
1.5%
1989 2
2.9%
1993 2
2.9%
1995 1
1.5%
1996 2
2.9%
ValueCountFrequency (%)
2020 6
8.8%
2017 2
 
2.9%
2016 1
 
1.5%
2015 5
7.4%
2014 1
 
1.5%
2013 2
 
2.9%
2011 2
 
2.9%
2010 1
 
1.5%
2009 2
 
2.9%
2007 4
5.9%

Interactions

2024-03-15T03:38:16.644761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:38:16.139327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:38:16.954448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:38:16.402554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:38:31.493070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분시군명칭위치관리주체전화번호설치연도
연번1.0000.8970.5050.8770.4360.8000.6680.713
구분0.8971.0000.0000.0000.0000.8980.0000.546
시군0.5050.0001.0001.0001.0000.9991.0000.611
명칭0.8770.0001.0001.0000.9990.9971.0000.932
위치0.4360.0001.0000.9991.0000.9850.9980.898
관리주체0.8000.8980.9990.9970.9851.0000.9860.000
전화번호0.6680.0001.0001.0000.9980.9861.0000.725
설치연도0.7130.5460.6110.9320.8980.0000.7251.000
2024-03-15T03:38:31.680364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군
구분1.0000.000
시군0.0001.000
2024-03-15T03:38:31.819393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치연도구분시군
연번1.0000.0550.6860.195
설치연도0.0551.0000.2890.240
구분0.6860.2891.0000.000
시군0.1950.2400.0001.000

Missing values

2024-03-15T03:38:17.385514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:38:17.828770image/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

연번구분시군명칭위치관리주체전화번호설치연도
01화장장전주시전주승화원완산구 콩쥐팥쥐로 1705-138전주시설관리공단063-239-26901977
12화장장군산시군산시승화원임피면 보석리 401-5외 1필지군산시063-454-79541997
23화장장익산시익산시정수원무왕로 1471-63익산시063-859-38401980
34화장장정읍시서남권추모공원감곡면 정읍북로 1850정읍시063-539-67252015
45화장장남원시남원시승화원솔터길 40-36남원시063-632-58741983
56공설자연장지전주시전주효자자연장(1차, 2차)완산구 콩쥐팥쥐로 1705-138전주시시설관리공 단063-239-26902009
67공설자연장지전주시전주효자자연장(1차, 2차)완산구 콩쥐팥쥐로 1705-138전주시시설관리공 단063-239-26902015
78공설자연장지익산시익산시공설자연장지무왕로 1471-63익산시063-859-38402010
89공설자연장지정읍시서남권추모공원자연장감곡면 정읍북로 1850정읍시063-539-67262015
910공설자연장지남원시남원시추모공원자연장남원시 광치동 산233-2남원시063-620-57312017
연번구분시군명칭위치관리주체전화번호설치연도
5859사설(법인)봉안시설익산시영모묘원 (대원전)납골당왕궁면 호반로173-45(재) 영모묘원063-836-43111999
5960사설(종교단체)봉안시설남원시영각전보절면 관음사길 82김정문(태고종관음사)063-620-92002004
6061사설(종교단체)봉안시설김제시성모암,영락원만경읍 화포리 388<NA>063-544-04162006
6162사설(법인)봉안시설김제시평화원공덕면 공덕리 1167(재)평화원063-853-10232000
6263사설(법인)봉안시설김제시지평선(금선화)공원묘원금구면 선암리 474번지(재)지평선(금선화)공원묘원063-546-50112007
6364사설(법인)봉안시설완주군천호성지 봉안경당비봉면 천호성지길 133(재)천주교전교구유지재단063-262-10142009
6465사설(법인)봉안시설완주군호정공원완주군 화산면 운곡리 720-10(재)호정공원063-214-10092020
6566사설(종교단체)봉안시설순창군대한불교대각조계종금화추모관순창읍 담순로 951-67(사)대한불교대각조계종063-652-60222015
6667사설(종교단체)봉안시설부안군한국불교화업종용화사부안군 행안면 역리 342용화사063-584-49192007
6768사설(종교단체)봉안시설부안군미륵불교 봉안당상서면 저기양산길 16-9미륵불교063-582-55092005