Overview

Dataset statistics

Number of variables12
Number of observations535
Missing cells931
Missing cells (%)14.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.4 KiB
Average record size in memory100.2 B

Variable types

Categorical2
Text6
Numeric4

Dataset

Description보건복지부에서 제공하는 시도별 묘지현황으로 시도, 시군구, 시설명, 주소, 전화번호, 팩스번호, 홈페이지준소, 주차대수, 공/사설구분, 허가면적, 묘역면적, 총매장능력의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15120533/fileData.do

Alerts

허가면적 is highly overall correlated with 묘역면적 and 1 other fieldsHigh correlation
묘역면적 is highly overall correlated with 허가면적 and 1 other fieldsHigh correlation
총매장능력 is highly overall correlated with 허가면적 and 1 other fieldsHigh correlation
전화번호 has 7 (1.3%) missing valuesMissing
팩스번호 has 497 (92.9%) missing valuesMissing
홈페이지 주소 has 427 (79.8%) missing valuesMissing
시설명 has unique valuesUnique
주차대수 has 433 (80.9%) zerosZeros
허가면적 has 125 (23.4%) zerosZeros
묘역면적 has 125 (23.4%) zerosZeros
총매장능력 has 133 (24.9%) zerosZeros

Reproduction

Analysis started2023-12-12 00:32:25.122168
Analysis finished2023-12-12 00:32:27.825618
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct20
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
경기도
186 
인천광역시
88 
전라남도
45 
제주특별자치도
33 
경상남도
30 
Other values (15)
153 

Length

Max length8
Median length7
Mean length5.2056075
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 186
34.8%
인천광역시 88
16.4%
전라남도 45
 
8.4%
제주특별자치도 33
 
6.2%
경상남도 30
 
5.6%
경상북도 27
 
5.0%
전라북도 26
 
4.9%
강원특별자치도 26
 
4.9%
충청남도 22
 
4.1%
충청북도 14
 
2.6%
Other values (10) 38
 
7.1%

Length

2023-12-12T09:32:27.952052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 186
34.8%
인천광역시 88
16.4%
전라남도 45
 
8.4%
제주특별자치도 33
 
6.2%
경상남도 30
 
5.6%
경상북도 27
 
5.0%
전라북도 26
 
4.9%
강원특별자치도 26
 
4.9%
충청남도 22
 
4.1%
대구광역시 15
 
2.8%
Other values (7) 37
 
6.9%

시군구
Text

Distinct143
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T09:32:28.200662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.2149533
Min length2

Characters and Unicode

Total characters1720
Distinct characters126
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

Unique70 ?
Unique (%)13.1%

Sample

1st row도봉구
2nd row도봉구
3rd row서울특별시
4th row서울특별시
5th row서울특별시
ValueCountFrequency (%)
강화군 60
 
10.8%
포천시 38
 
6.9%
양주시 34
 
6.1%
파주시 22
 
4.0%
나주시 21
 
3.8%
서귀포시 18
 
3.2%
제주시 15
 
2.7%
서구 11
 
2.0%
옹진군 11
 
2.0%
광주시 8
 
1.4%
Other values (136) 316
57.0%
2023-12-12T09:32:28.605349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 315
18.3%
군 194
 
11.3%
주 140
 
8.1%
양 67
 
3.9%
포 66
 
3.8%
천 65
 
3.8%
강 64
 
3.7%
화 63
 
3.7%
구 62
 
3.6%
서 34
 
2.0%
Other values (116) 650
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1700
98.8%
Space Separator 19
 
1.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 315
18.5%
군 194
 
11.4%
주 140
 
8.2%
양 67
 
3.9%
포 66
 
3.9%
천 65
 
3.8%
강 64
 
3.8%
화 63
 
3.7%
구 62
 
3.6%
서 34
 
2.0%
Other values (114) 630
37.1%
Space Separator
ValueCountFrequency (%)
19
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1700
98.8%
Common 20
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 315
18.5%
군 194
 
11.4%
주 140
 
8.2%
양 67
 
3.9%
포 66
 
3.9%
천 65
 
3.8%
강 64
 
3.8%
화 63
 
3.7%
구 62
 
3.6%
서 34
 
2.0%
Other values (114) 630
37.1%
Common
ValueCountFrequency (%)
19
95.0%
4 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1700
98.8%
ASCII 20
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 315
18.5%
군 194
 
11.4%
주 140
 
8.2%
양 67
 
3.9%
포 66
 
3.9%
천 65
 
3.8%
강 64
 
3.8%
화 63
 
3.7%
구 62
 
3.6%
서 34
 
2.0%
Other values (114) 630
37.1%
ASCII
ValueCountFrequency (%)
19
95.0%
4 1
 
5.0%

시설명
Text

UNIQUE 

Distinct535
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T09:32:28.840276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.5308411
Min length3

Characters and Unicode

Total characters4564
Distinct characters277
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique535 ?
Unique (%)100.0%

Sample

1st row혜화동성당 도봉동묘원
2nd row혜화동성당 방학동묘원
3rd row내곡리묘지
4th row벽제리묘지
5th row용미리제1묘지
ValueCountFrequency (%)
제2공설묘지 9
 
1.4%
제1공설묘지 8
 
1.2%
공설묘지 7
 
1.1%
신북면 6
 
0.9%
청송리 6
 
0.9%
묘지 5
 
0.8%
묘원 4
 
0.6%
제3공설묘지 4
 
0.6%
가산면 4
 
0.6%
천주교 4
 
0.6%
Other values (558) 586
91.1%
2023-12-12T09:32:29.255312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
묘 507
 
11.1%
공 496
 
10.9%
지 400
 
8.8%
원 317
 
6.9%
설 284
 
6.2%
( 129
 
2.8%
) 129
 
2.8%
리 113
 
2.5%
동 112
 
2.5%
108
 
2.4%
Other values (267) 1969
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4144
90.8%
Open Punctuation 129
 
2.8%
Close Punctuation 129
 
2.8%
Space Separator 108
 
2.4%
Decimal Number 46
 
1.0%
Uppercase Letter 7
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
묘 507
 
12.2%
공 496
 
12.0%
지 400
 
9.7%
원 317
 
7.6%
설 284
 
6.9%
리 113
 
2.7%
동 112
 
2.7%
재 64
 
1.5%
산 62
 
1.5%
교 57
 
1.4%
Other values (252) 1732
41.8%
Decimal Number
ValueCountFrequency (%)
2 17
37.0%
1 15
32.6%
3 6
 
13.0%
4 4
 
8.7%
6 2
 
4.3%
5 2
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
H 2
28.6%
L 2
28.6%
I 1
14.3%
E 1
14.3%
T 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 129
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Space Separator
ValueCountFrequency (%)
108
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4144
90.8%
Common 413
 
9.0%
Latin 7
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
묘 507
 
12.2%
공 496
 
12.0%
지 400
 
9.7%
원 317
 
7.6%
설 284
 
6.9%
리 113
 
2.7%
동 112
 
2.7%
재 64
 
1.5%
산 62
 
1.5%
교 57
 
1.4%
Other values (252) 1732
41.8%
Common
ValueCountFrequency (%)
( 129
31.2%
) 129
31.2%
108
26.2%
2 17
 
4.1%
1 15
 
3.6%
3 6
 
1.5%
4 4
 
1.0%
6 2
 
0.5%
5 2
 
0.5%
. 1
 
0.2%
Latin
ValueCountFrequency (%)
H 2
28.6%
L 2
28.6%
I 1
14.3%
E 1
14.3%
T 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4144
90.8%
ASCII 420
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
묘 507
 
12.2%
공 496
 
12.0%
지 400
 
9.7%
원 317
 
7.6%
설 284
 
6.9%
리 113
 
2.7%
동 112
 
2.7%
재 64
 
1.5%
산 62
 
1.5%
교 57
 
1.4%
Other values (252) 1732
41.8%
ASCII
ValueCountFrequency (%)
( 129
30.7%
) 129
30.7%
108
25.7%
2 17
 
4.0%
1 15
 
3.6%
3 6
 
1.4%
4 4
 
1.0%
H 2
 
0.5%
L 2
 
0.5%
6 2
 
0.5%
Other values (5) 6
 
1.4%

주소
Text

Distinct533
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T09:32:29.646083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length42
Mean length24.106542
Min length1

Characters and Unicode

Total characters12897
Distinct characters305
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

Unique531 ?
Unique (%)99.3%

Sample

1st row서울특별시 도봉구 도봉동 산66-9
2nd row서울특별시 도봉구 방학동 산65-1
3rd row경기 남양주시 진접읍 내곡리 558-3
4th row경기도 고양시 덕양구 보광로 193-2 (벽제동)
5th row경기도 파주시 광탄면 용미리 산107
ValueCountFrequency (%)
경기도 187
 
6.6%
인천광역시 88
 
3.1%
강화군 60
 
2.1%
전라남도 44
 
1.6%
포천시 37
 
1.3%
양주시 35
 
1.2%
경상남도 29
 
1.0%
제주특별자치도 29
 
1.0%
경상북도 28
 
1.0%
강원특별자치도 26
 
0.9%
Other values (1529) 2257
80.0%
2023-12-12T09:32:30.188985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2299
 
17.8%
도 460
 
3.6%
시 434
 
3.4%
리 429
 
3.3%
1 423
 
3.3%
산 420
 
3.3%
면 328
 
2.5%
경 264
 
2.0%
- 220
 
1.7%
동 219
 
1.7%
Other values (295) 7401
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8163
63.3%
Space Separator 2299
 
17.8%
Decimal Number 1787
 
13.9%
Dash Punctuation 220
 
1.7%
Open Punctuation 181
 
1.4%
Close Punctuation 181
 
1.4%
Other Punctuation 66
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 460
 
5.6%
시 434
 
5.3%
리 429
 
5.3%
산 420
 
5.1%
면 328
 
4.0%
경 264
 
3.2%
동 219
 
2.7%
군 215
 
2.6%
주 203
 
2.5%
기 203
 
2.5%
Other values (280) 4988
61.1%
Decimal Number
ValueCountFrequency (%)
1 423
23.7%
2 216
12.1%
3 188
10.5%
5 168
 
9.4%
4 157
 
8.8%
8 139
 
7.8%
6 136
 
7.6%
7 130
 
7.3%
0 116
 
6.5%
9 114
 
6.4%
Space Separator
ValueCountFrequency (%)
2299
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 220
100.0%
Open Punctuation
ValueCountFrequency (%)
( 181
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Other Punctuation
ValueCountFrequency (%)
, 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8163
63.3%
Common 4734
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 460
 
5.6%
시 434
 
5.3%
리 429
 
5.3%
산 420
 
5.1%
면 328
 
4.0%
경 264
 
3.2%
동 219
 
2.7%
군 215
 
2.6%
주 203
 
2.5%
기 203
 
2.5%
Other values (280) 4988
61.1%
Common
ValueCountFrequency (%)
2299
48.6%
1 423
 
8.9%
- 220
 
4.6%
2 216
 
4.6%
3 188
 
4.0%
( 181
 
3.8%
) 181
 
3.8%
5 168
 
3.5%
4 157
 
3.3%
8 139
 
2.9%
Other values (5) 562
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8163
63.3%
ASCII 4734
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2299
48.6%
1 423
 
8.9%
- 220
 
4.6%
2 216
 
4.6%
3 188
 
4.0%
( 181
 
3.8%
) 181
 
3.8%
5 168
 
3.5%
4 157
 
3.3%
8 139
 
2.9%
Other values (5) 562
 
11.9%
Hangul
ValueCountFrequency (%)
도 460
 
5.6%
시 434
 
5.3%
리 429
 
5.3%
산 420
 
5.1%
면 328
 
4.0%
경 264
 
3.2%
동 219
 
2.7%
군 215
 
2.6%
주 203
 
2.5%
기 203
 
2.5%
Other values (280) 4988
61.1%

전화번호
Text

MISSING 

Distinct395
Distinct (%)74.8%
Missing7
Missing (%)1.3%
Memory size4.3 KiB
2023-12-12T09:32:30.439605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030303
Min length9

Characters and Unicode

Total characters6352
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

Unique341 ?
Unique (%)64.6%

Sample

1st row02-742-1007
2nd row031-434-3337
3rd row031-964-3443
4th row031-943-1930
5th row031-943-3937
ValueCountFrequency (%)
032-899-2333 11
 
2.1%
032-934-2183 10
 
1.9%
031-8082-7580 8
 
1.5%
032-937-5301 7
 
1.3%
032-930-3604 7
 
1.3%
055-940-3892 7
 
1.3%
041-830-6748 6
 
1.1%
031-538-4361 6
 
1.1%
032-930-3612 6
 
1.1%
031-8082-7610 6
 
1.1%
Other values (385) 454
86.0%
2023-12-12T09:32:30.888793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1055
16.6%
0 961
15.1%
3 937
14.8%
1 538
8.5%
4 535
8.4%
2 493
7.8%
5 438
6.9%
8 408
 
6.4%
6 404
 
6.4%
7 325
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5297
83.4%
Dash Punctuation 1055
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 961
18.1%
3 937
17.7%
1 538
10.2%
4 535
10.1%
2 493
9.3%
5 438
8.3%
8 408
7.7%
6 404
7.6%
7 325
 
6.1%
9 258
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 1055
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6352
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1055
16.6%
0 961
15.1%
3 937
14.8%
1 538
8.5%
4 535
8.4%
2 493
7.8%
5 438
6.9%
8 408
 
6.4%
6 404
 
6.4%
7 325
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1055
16.6%
0 961
15.1%
3 937
14.8%
1 538
8.5%
4 535
8.4%
2 493
7.8%
5 438
6.9%
8 408
 
6.4%
6 404
 
6.4%
7 325
 
5.1%

팩스번호
Text

MISSING 

Distinct37
Distinct (%)97.4%
Missing497
Missing (%)92.9%
Memory size4.3 KiB
2023-12-12T09:32:31.107988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters456
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

Unique36 ?
Unique (%)94.7%

Sample

1st row02-3672-1197
2nd row02-3672-1197
3rd row051-508-6024
4th row051-722-1268
5th row054-383-9623
ValueCountFrequency (%)
02-3672-1197 2
 
5.3%
033-530-2735 1
 
2.6%
061-749-4520 1
 
2.6%
033-550-2961 1
 
2.6%
042-256-5159 1
 
2.6%
041-339-8259 1
 
2.6%
041-554-4197 1
 
2.6%
041-567-0535 1
 
2.6%
063-836-4313 1
 
2.6%
063-859-5072 1
 
2.6%
Other values (27) 27
71.1%
2023-12-12T09:32:31.455710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.7%
3 61
13.4%
0 56
12.3%
5 47
10.3%
1 43
9.4%
7 35
7.7%
2 33
7.2%
6 32
7.0%
4 31
6.8%
9 24
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 380
83.3%
Dash Punctuation 76
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 61
16.1%
0 56
14.7%
5 47
12.4%
1 43
11.3%
7 35
9.2%
2 33
8.7%
6 32
8.4%
4 31
8.2%
9 24
 
6.3%
8 18
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.7%
3 61
13.4%
0 56
12.3%
5 47
10.3%
1 43
9.4%
7 35
7.7%
2 33
7.2%
6 32
7.0%
4 31
6.8%
9 24
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.7%
3 61
13.4%
0 56
12.3%
5 47
10.3%
1 43
9.4%
7 35
7.7%
2 33
7.2%
6 32
7.0%
4 31
6.8%
9 24
 
5.3%

홈페이지 주소
Text

MISSING 

Distinct91
Distinct (%)84.3%
Missing427
Missing (%)79.8%
Memory size4.3 KiB
2023-12-12T09:32:31.671099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length50
Mean length27.083333
Min length6

Characters and Unicode

Total characters2925
Distinct characters73
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)78.7%

Sample

1st rowwww.hyehwa.org/cemetery/cemetery.asp?goCemetery=3
2nd rowwww.hyehwa.org/cemetery/cemetery.asp?goCemetery=2
3rd rowwww.memorial-zone.or.kr
4th rowwww.memorial-zone.or.kr
5th rowwww.memorial-zone.or.kr
ValueCountFrequency (%)
www.geochang.go.kr/welfare/index.do?c=wl0306040200 8
 
7.4%
www.jahayeon.com 4
 
3.7%
www.memorial-zone.or.kr 3
 
2.8%
https://www.15774129.go.kr/portal/fnlfac/faclist.do 3
 
2.8%
www.dangjin.go.kr/html/welf/old/old_07_04.html 3
 
2.8%
www.hdpark.co.kr 2
 
1.9%
www.pungsanpark.co.kr 1
 
0.9%
www.jjss.or.kr/content02/02_02.asp 1
 
0.9%
ymw.kr 1
 
0.9%
http://www.wanju.go.kr/index.wanju?menucd=dom_000000104002005005 1
 
0.9%
Other values (81) 81
75.0%
2023-12-12T09:32:31.990314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 303
 
10.4%
. 303
 
10.4%
o 193
 
6.6%
r 187
 
6.4%
a 151
 
5.2%
e 133
 
4.5%
k 126
 
4.3%
n 121
 
4.1%
/ 117
 
4.0%
0 111
 
3.8%
Other values (63) 1180
40.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2123
72.6%
Other Punctuation 451
 
15.4%
Decimal Number 236
 
8.1%
Uppercase Letter 44
 
1.5%
Connector Punctuation 24
 
0.8%
Other Letter 21
 
0.7%
Math Symbol 20
 
0.7%
Dash Punctuation 4
 
0.1%
Space Separator 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 303
14.3%
o 193
 
9.1%
r 187
 
8.8%
a 151
 
7.1%
e 133
 
6.3%
k 126
 
5.9%
n 121
 
5.7%
c 109
 
5.1%
g 87
 
4.1%
m 78
 
3.7%
Other values (15) 635
29.9%
Other Letter
ValueCountFrequency (%)
원 4
19.0%
공 3
14.3%
라 1
 
4.8%
나 1
 
4.8%
늘 1
 
4.8%
하 1
 
4.8%
현 1
 
4.8%
경 1
 
4.8%
운 1
 
4.8%
회 1
 
4.8%
Other values (6) 6
28.6%
Uppercase Letter
ValueCountFrequency (%)
L 12
27.3%
W 9
20.5%
I 9
20.5%
C 4
 
9.1%
R 2
 
4.5%
O 2
 
4.5%
D 2
 
4.5%
K 1
 
2.3%
B 1
 
2.3%
M 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
0 111
47.0%
2 31
 
13.1%
4 23
 
9.7%
1 17
 
7.2%
7 16
 
6.8%
3 14
 
5.9%
6 11
 
4.7%
9 6
 
2.5%
5 6
 
2.5%
8 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 303
67.2%
/ 117
 
25.9%
? 19
 
4.2%
: 9
 
2.0%
, 1
 
0.2%
@ 1
 
0.2%
& 1
 
0.2%
Connector Punctuation
ValueCountFrequency (%)
_ 24
100.0%
Math Symbol
ValueCountFrequency (%)
= 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2167
74.1%
Common 737
 
25.2%
Hangul 21
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 303
14.0%
o 193
 
8.9%
r 187
 
8.6%
a 151
 
7.0%
e 133
 
6.1%
k 126
 
5.8%
n 121
 
5.6%
c 109
 
5.0%
g 87
 
4.0%
m 78
 
3.6%
Other values (26) 679
31.3%
Common
ValueCountFrequency (%)
. 303
41.1%
/ 117
 
15.9%
0 111
 
15.1%
2 31
 
4.2%
_ 24
 
3.3%
4 23
 
3.1%
= 20
 
2.7%
? 19
 
2.6%
1 17
 
2.3%
7 16
 
2.2%
Other values (11) 56
 
7.6%
Hangul
ValueCountFrequency (%)
원 4
19.0%
공 3
14.3%
라 1
 
4.8%
나 1
 
4.8%
늘 1
 
4.8%
하 1
 
4.8%
현 1
 
4.8%
경 1
 
4.8%
운 1
 
4.8%
회 1
 
4.8%
Other values (6) 6
28.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2904
99.3%
Hangul 21
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 303
 
10.4%
. 303
 
10.4%
o 193
 
6.6%
r 187
 
6.4%
a 151
 
5.2%
e 133
 
4.6%
k 126
 
4.3%
n 121
 
4.2%
/ 117
 
4.0%
0 111
 
3.8%
Other values (47) 1159
39.9%
Hangul
ValueCountFrequency (%)
원 4
19.0%
공 3
14.3%
라 1
 
4.8%
나 1
 
4.8%
늘 1
 
4.8%
하 1
 
4.8%
현 1
 
4.8%
경 1
 
4.8%
운 1
 
4.8%
회 1
 
4.8%
Other values (6) 6
28.6%

주차대수
Real number (ℝ)

ZEROS 

Distinct36
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.908411
Minimum0
Maximum15000
Zeros433
Zeros (%)80.9%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T09:32:32.105955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile365
Maximum15000
Range15000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation692.42009
Coefficient of variation (CV)7.8766079
Kurtosis406.10094
Mean87.908411
Median Absolute Deviation (MAD)0
Skewness19.158351
Sum47031
Variance479445.58
MonotonicityNot monotonic
2023-12-12T09:32:32.233884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 433
80.9%
100 13
 
2.4%
200 9
 
1.7%
50 9
 
1.7%
500 9
 
1.7%
150 6
 
1.1%
30 6
 
1.1%
1000 6
 
1.1%
300 5
 
0.9%
10 5
 
0.9%
Other values (26) 34
 
6.4%
ValueCountFrequency (%)
0 433
80.9%
4 2
 
0.4%
5 2
 
0.4%
10 5
 
0.9%
15 1
 
0.2%
20 1
 
0.2%
25 1
 
0.2%
28 1
 
0.2%
30 6
 
1.1%
40 3
 
0.6%
ValueCountFrequency (%)
15000 1
 
0.2%
3800 1
 
0.2%
1500 3
 
0.6%
1300 1
 
0.2%
1000 6
1.1%
900 1
 
0.2%
800 1
 
0.2%
700 1
 
0.2%
500 9
1.7%
480 1
 
0.2%

공_사설 구분
Categorical

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
공설
351 
사설
183 
0
 
1

Length

Max length2
Median length2
Mean length1.9981308
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row사설
2nd row사설
3rd row공설
4th row공설
5th row공설

Common Values

ValueCountFrequency (%)
공설 351
65.6%
사설 183
34.2%
0 1
 
0.2%

Length

2023-12-12T09:32:32.349382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:32:32.437690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공설 351
65.6%
사설 183
34.2%
0 1
 
0.2%

허가면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct375
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean125611.28
Minimum0
Maximum2836118
Zeros125
Zeros (%)23.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T09:32:32.537387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11255
median18645
Q3155153.5
95-th percentile562925
Maximum2836118
Range2836118
Interquartile range (IQR)153898.5

Descriptive statistics

Standard deviation248900.35
Coefficient of variation (CV)1.9815127
Kurtosis32.940844
Mean125611.28
Median Absolute Deviation (MAD)18645
Skewness4.5606885
Sum67202037
Variance6.1951385 × 1010
MonotonicityNot monotonic
2023-12-12T09:32:32.666738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 125
 
23.4%
9620 3
 
0.6%
4959 3
 
0.6%
142111 2
 
0.4%
6248 2
 
0.4%
320727 2
 
0.4%
177559 2
 
0.4%
446204 2
 
0.4%
165000 2
 
0.4%
969620 2
 
0.4%
Other values (365) 390
72.9%
ValueCountFrequency (%)
0 125
23.4%
15 1
 
0.2%
397 1
 
0.2%
476 1
 
0.2%
694 1
 
0.2%
881 1
 
0.2%
893 1
 
0.2%
995 1
 
0.2%
1114 1
 
0.2%
1190 1
 
0.2%
ValueCountFrequency (%)
2836118 1
0.2%
1668729 1
0.2%
1526387 1
0.2%
1307080 1
0.2%
1083527 2
0.4%
1072743 1
0.2%
989761 1
0.2%
969620 2
0.4%
931627 1
0.2%
891000 1
0.2%

묘역면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct392
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96590.692
Minimum0
Maximum2826118
Zeros125
Zeros (%)23.4%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T09:32:32.785675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1944
median16165
Q3104118.5
95-th percentile405496.4
Maximum2826118
Range2826118
Interquartile range (IQR)103174.5

Descriptive statistics

Standard deviation224293.63
Coefficient of variation (CV)2.322104
Kurtosis49.889804
Mean96590.692
Median Absolute Deviation (MAD)16165
Skewness5.7727295
Sum51676020
Variance5.0307633 × 1010
MonotonicityNot monotonic
2023-12-12T09:32:32.897237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 125
 
23.4%
9620 3
 
0.6%
4959 3
 
0.6%
1005969 2
 
0.4%
28628 2
 
0.4%
11900 2
 
0.4%
17596 2
 
0.4%
10413 2
 
0.4%
4860 2
 
0.4%
6248 2
 
0.4%
Other values (382) 390
72.9%
ValueCountFrequency (%)
0 125
23.4%
15 1
 
0.2%
109 1
 
0.2%
300 1
 
0.2%
397 1
 
0.2%
476 1
 
0.2%
690 1
 
0.2%
694 1
 
0.2%
881 1
 
0.2%
893 1
 
0.2%
ValueCountFrequency (%)
2826118 1
0.2%
1668729 1
0.2%
1195479 1
0.2%
1143353 1
0.2%
1072743 1
0.2%
1005969 2
0.4%
989761 1
0.2%
949710 1
0.2%
931627 1
0.2%
913936 1
0.2%

총매장능력
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct331
Distinct (%)61.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4682.7626
Minimum0
Maximum60380
Zeros133
Zeros (%)24.9%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T09:32:33.034272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.5
median698
Q35773
95-th percentile22892.2
Maximum60380
Range60380
Interquartile range (IQR)5769.5

Descriptive statistics

Standard deviation8666.391
Coefficient of variation (CV)1.8507005
Kurtosis11.83076
Mean4682.7626
Median Absolute Deviation (MAD)698
Skewness3.0996885
Sum2505278
Variance75106333
MonotonicityNot monotonic
2023-12-12T09:32:33.392240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 133
 
24.9%
1000 5
 
0.9%
300 5
 
0.9%
30000 4
 
0.7%
220 4
 
0.7%
500 4
 
0.7%
5000 4
 
0.7%
110 3
 
0.6%
15000 3
 
0.6%
1500 3
 
0.6%
Other values (321) 367
68.6%
ValueCountFrequency (%)
0 133
24.9%
3 1
 
0.2%
4 1
 
0.2%
5 1
 
0.2%
14 1
 
0.2%
18 1
 
0.2%
19 1
 
0.2%
25 1
 
0.2%
37 1
 
0.2%
41 1
 
0.2%
ValueCountFrequency (%)
60380 1
0.2%
60000 1
0.2%
50000 1
0.2%
49120 1
0.2%
47631 1
0.2%
43866 1
0.2%
41542 2
0.4%
35000 1
0.2%
34217 1
0.2%
30950 1
0.2%

Interactions

2023-12-12T09:32:27.040868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.043253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.373103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.694495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:27.134484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.124240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.457266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.783610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:27.223239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.201611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.530884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.861037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:27.317873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.285223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.604327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:32:26.948668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:32:33.474141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도팩스번호홈페이지 주소주차대수공_사설 구분허가면적묘역면적총매장능력
시도1.0001.0001.0000.0000.4760.2510.1610.439
팩스번호1.0001.0000.9881.0001.0001.0001.0000.967
홈페이지 주소1.0000.9881.0001.0001.0000.9980.9960.991
주차대수0.0001.0001.0001.0000.0000.6070.4360.546
공_사설 구분0.4761.0001.0000.0001.0000.2050.1910.333
허가면적0.2511.0000.9980.6070.2051.0000.9550.764
묘역면적0.1611.0000.9960.4360.1910.9551.0000.681
총매장능력0.4390.9670.9910.5460.3330.7640.6811.000
2023-12-12T09:32:33.580629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공_사설 구분시도
공_사설 구분1.0000.282
시도0.2821.000
2023-12-12T09:32:33.670271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차대수허가면적묘역면적총매장능력시도공_사설 구분
주차대수1.0000.4250.4090.3720.0000.000
허가면적0.4251.0000.9690.8820.1090.139
묘역면적0.4090.9691.0000.8760.0690.130
총매장능력0.3720.8820.8761.0000.1520.211
시도0.0000.1090.0690.1521.0000.282
공_사설 구분0.0000.1390.1300.2110.2821.000

Missing values

2023-12-12T09:32:27.457386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:32:27.629176image/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.
2023-12-12T09:32:27.761820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시도시군구시설명주소전화번호팩스번호홈페이지 주소주차대수공_사설 구분허가면적묘역면적총매장능력
0서울특별시도봉구혜화동성당 도봉동묘원서울특별시 도봉구 도봉동 산66-9<NA>02-3672-1197www.hyehwa.org/cemetery/cemetery.asp?goCemetery=30사설1500010678600
1서울특별시도봉구혜화동성당 방학동묘원서울특별시 도봉구 방학동 산65-102-742-100702-3672-1197www.hyehwa.org/cemetery/cemetery.asp?goCemetery=20사설159232717846682
2서울특별시서울특별시내곡리묘지경기 남양주시 진접읍 내곡리 558-3031-434-3337<NA><NA>0공설2187452187456900
3서울특별시서울특별시벽제리묘지경기도 고양시 덕양구 보광로 193-2 (벽제동)031-964-3443<NA>www.memorial-zone.or.kr4공설1954791169195846
4서울특별시서울특별시용미리제1묘지경기도 파주시 광탄면 용미리 산107031-943-1930<NA>www.memorial-zone.or.kr100공설2128862128861200
5서울특별시서울특별시용미리제2묘지경기도 파주시 광탄면 진지로 151 (용미리, 추모의집)031-943-3937<NA>www.memorial-zone.or.kr100공설19998019834712000
6서울특별시중랑구망우역사문화공원서울특별시 중랑구 망우동 산57-102-496-8976<NA>manguripark.or.kr28공설78555478555447631
7부산광역시금정구부산영락공원묘지부산광역시 금정구 금정도서관로 108 (두구동, 영락공원)051-790-5000051-508-6024yeongnakpark.bisco.or.kr/burial/burial01/index.asp0공설75093275093229021
8부산광역시기장군(재)실로암공원묘원부산광역시 기장군 철마면 사등길 181 (고촌리, 실로암공원묘원관리사무소)051-721-5115051-722-1268www.siloami.com0사설4792771968270
9부산광역시기장군대정공원묘원부산광역시 기장군 정관읍 양수길 76 (용수리, 대정공원묘원관리소)051-728-4949<NA><NA>0사설20335420335411274
시도시군구시설명주소전화번호팩스번호홈페이지 주소주차대수공_사설 구분허가면적묘역면적총매장능력
525제주특별자치도제주시애향묘지제주특별자치도 제주시 노형동 산18-1064-728-2563<NA><NA>0공설22810228102074
526제주특별자치도제주시어승생공설묘지제주특별자치도 제주시 연동 2488-1064-728-2563<NA><NA>0공설1842651013455067
527제주특별자치도제주시예수장로회 제주교회묘지제주특별자치도 제주시 구좌읍 세화리 2453-2064-722-3091<NA><NA>0사설158687920810
528제주특별자치도제주시우도면공설묘지제주특별자치도 제주시 우도면 연평리 394064-728-4331<NA><NA>0공설15258015420939
529제주특별자치도제주시제주향교묘지제주특별자치도 제주시 동샘길 44-14 (영평동)064-757-2249<NA><NA>0사설1909319093424
530제주특별자치도제주시조수천주교묘지제주특별자치도 제주시 한경면 조수리 4041064-773-2217<NA><NA>0사설14479412645817127
531제주특별자치도제주시조천읍공설묘지제주특별자치도 제주시 조천읍 선흘리 4116064-728-7831<NA><NA>0공설96962029238619690
532제주특별자치도제주시조천장로교회묘지제주특별자치도 제주시 조천읍 와산리 462064-783-6078<NA><NA>0사설165000990006689
533제주특별자치도제주시천아오름공원묘지제주특별자치도 제주시 한림읍 광산로 11-50 (상대리)064-796-4044<NA><NA>0사설2408024080450
534제주특별자치도제주시천주교제주교구묘지제주특별자치도 제주시 기와5길 117-22 (화북이동)064-756-5531<NA><NA>0사설58192581921939