Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells26300
Missing cells (%)20.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory114.0 B

Variable types

Text2
Categorical7
DateTime3
Boolean1

Dataset

Description부산 영락공원 묘지정보, 순번, 사망일자, 매장일자, 만료일자, 개장여부, 개장일자, 시도구분, 매장종류, 감면구분, 묘지수납구분, 사용료 등에 관한 정보
Author부산시설공단
URLhttps://www.data.go.kr/data/15067559/fileData.do

Alerts

개장여부 has constant value ""Constant
순번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
매장종류 is highly overall correlated with 묘지수납구분High correlation
감면구분 is highly overall correlated with 묘지수납구분High correlation
묘지수납구분 is highly overall correlated with 순번 and 3 other fieldsHigh correlation
순번 is highly imbalanced (79.5%)Imbalance
시도구분 is highly imbalanced (76.1%)Imbalance
매장종류 is highly imbalanced (81.6%)Imbalance
감면구분 is highly imbalanced (86.8%)Imbalance
묘지수납구분 is highly imbalanced (67.2%)Imbalance
사용료 is highly imbalanced (97.7%)Imbalance
만료일자 has 9359 (93.6%) missing valuesMissing
개장여부 has 8442 (84.4%) missing valuesMissing
개장일자 has 8442 (84.4%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:57:58.876235
Analysis finished2024-04-06 08:58:01.823824
Duration2.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

묘지정보
Text

Distinct9807
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:58:02.241815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters150000
Distinct characters16
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

Unique9614 ?
Unique (%)96.1%

Sample

1st row05묘원 31블럭 0356호
2nd row01묘원 12블럭 0023호
3rd row04묘원 28블럭 0269호
4th row01묘원 06블럭 0246호
5th row02묘원 14블럭 0336호
ValueCountFrequency (%)
01묘원 1381
 
4.6%
11묘원 1027
 
3.4%
14묘원 989
 
3.3%
08묘원 918
 
3.1%
07묘원 874
 
2.9%
02묘원 703
 
2.3%
03묘원 642
 
2.1%
13묘원 609
 
2.0%
09묘원 599
 
2.0%
04묘원 555
 
1.8%
Other values (953) 21703
72.3%
2024-04-06T17:58:03.117144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 23512
15.7%
20000
13.3%
1 12234
8.2%
묘 10000
 
6.7%
원 10000
 
6.7%
블 10000
 
6.7%
럭 10000
 
6.7%
호 10000
 
6.7%
3 7633
 
5.1%
2 7350
 
4.9%
Other values (6) 29271
19.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80000
53.3%
Other Letter 50000
33.3%
Space Separator 20000
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 23512
29.4%
1 12234
15.3%
3 7633
 
9.5%
2 7350
 
9.2%
4 7129
 
8.9%
5 6167
 
7.7%
6 4897
 
6.1%
7 3869
 
4.8%
8 3822
 
4.8%
9 3387
 
4.2%
Other Letter
ValueCountFrequency (%)
묘 10000
20.0%
원 10000
20.0%
블 10000
20.0%
럭 10000
20.0%
호 10000
20.0%
Space Separator
ValueCountFrequency (%)
20000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100000
66.7%
Hangul 50000
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 23512
23.5%
20000
20.0%
1 12234
12.2%
3 7633
 
7.6%
2 7350
 
7.3%
4 7129
 
7.1%
5 6167
 
6.2%
6 4897
 
4.9%
7 3869
 
3.9%
8 3822
 
3.8%
Hangul
ValueCountFrequency (%)
묘 10000
20.0%
원 10000
20.0%
블 10000
20.0%
럭 10000
20.0%
호 10000
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
66.7%
Hangul 50000
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 23512
23.5%
20000
20.0%
1 12234
12.2%
3 7633
 
7.6%
2 7350
 
7.3%
4 7129
 
7.1%
5 6167
 
6.2%
6 4897
 
4.9%
7 3869
 
3.9%
8 3822
 
3.8%
Hangul
ValueCountFrequency (%)
묘 10000
20.0%
원 10000
20.0%
블 10000
20.0%
럭 10000
20.0%
호 10000
20.0%

순번
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
9424 
2
 
566
3
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 9424
94.2%
2 566
 
5.7%
3 10
 
0.1%

Length

2024-04-06T17:58:03.408695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:03.595709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 9424
94.2%
2 566
 
5.7%
3 10
 
0.1%

사망일자
Text

Distinct5355
Distinct (%)53.9%
Missing57
Missing (%)0.6%
Memory size156.2 KiB
2024-04-06T17:58:04.058620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters99430
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

Unique2931 ?
Unique (%)29.5%

Sample

1st row1974-01-15
2nd row2015-03-29
3rd row1974-09-05
4th row1970-06-15
5th row1987-07-25
ValueCountFrequency (%)
1901-01-01 44
 
0.4%
1927-08-27 17
 
0.2%
1980-02-22 10
 
0.1%
1980-12-22 9
 
0.1%
1979-06-15 9
 
0.1%
1978-02-20 8
 
0.1%
1980-04-20 8
 
0.1%
1979-06-03 8
 
0.1%
1977-12-29 8
 
0.1%
1981-02-13 8
 
0.1%
Other values (5345) 9814
98.7%
2024-04-06T17:58:04.780875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 19886
20.0%
1 19855
20.0%
0 14603
14.7%
9 12580
12.7%
7 8847
8.9%
2 7287
 
7.3%
8 4550
 
4.6%
6 3210
 
3.2%
3 3124
 
3.1%
5 2838
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79544
80.0%
Dash Punctuation 19886
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19855
25.0%
0 14603
18.4%
9 12580
15.8%
7 8847
11.1%
2 7287
 
9.2%
8 4550
 
5.7%
6 3210
 
4.0%
3 3124
 
3.9%
5 2838
 
3.6%
4 2650
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 19886
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99430
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 19886
20.0%
1 19855
20.0%
0 14603
14.7%
9 12580
12.7%
7 8847
8.9%
2 7287
 
7.3%
8 4550
 
4.6%
6 3210
 
3.2%
3 3124
 
3.1%
5 2838
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 19886
20.0%
1 19855
20.0%
0 14603
14.7%
9 12580
12.7%
7 8847
8.9%
2 7287
 
7.3%
8 4550
 
4.6%
6 3210
 
3.2%
3 3124
 
3.1%
5 2838
 
2.9%

매장일자
Date

Distinct5100
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1955-01-14 00:00:00
Maximum2020-09-14 00:00:00
2024-04-06T17:58:05.064353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:58:05.283975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

만료일자
Date

MISSING 

Distinct617
Distinct (%)96.3%
Missing9359
Missing (%)93.6%
Memory size156.2 KiB
Minimum2019-10-02 00:00:00
Maximum2050-09-13 00:00:00
2024-04-06T17:58:05.547268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:58:05.800106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신규
7884 
개장
1558 
재사용
 
558

Length

Max length3
Median length2
Mean length2.0558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신규
2nd row재사용
3rd row신규
4th row신규
5th row재사용

Common Values

ValueCountFrequency (%)
신규 7884
78.8%
개장 1558
 
15.6%
재사용 558
 
5.6%

Length

2024-04-06T17:58:06.027687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:06.229251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신규 7884
78.8%
개장 1558
 
15.6%
재사용 558
 
5.6%

개장여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing8442
Missing (%)84.4%
Memory size97.7 KiB
True
1558 
(Missing)
8442 
ValueCountFrequency (%)
True 1558
 
15.6%
(Missing) 8442
84.4%
2024-04-06T17:58:06.389917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

개장일자
Date

MISSING 

Distinct1222
Distinct (%)78.4%
Missing8442
Missing (%)84.4%
Memory size156.2 KiB
Minimum1969-05-01 00:00:00
Maximum2020-10-25 00:00:00
2024-04-06T17:58:06.593143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:58:06.875543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시도구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
자시
9416 
인접
 
333
타시
 
251

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자시 9416
94.2%
인접 333
 
3.3%
타시 251
 
2.5%

Length

2024-04-06T17:58:07.191616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:07.505128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자시 9416
94.2%
인접 333
 
3.3%
타시 251
 
2.5%

매장종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
시체
9384 
개장유골
 
363
부부합장
 
135
화장유골
 
96
유골합장
 
22

Length

Max length4
Median length2
Mean length2.1232
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
시체 9384
93.8%
개장유골 363
 
3.6%
부부합장 135
 
1.4%
화장유골 96
 
1.0%
유골합장 22
 
0.2%

Length

2024-04-06T17:58:07.804965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:08.295607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시체 9384
93.8%
개장유골 363
 
3.6%
부부합장 135
 
1.4%
화장유골 96
 
1.0%
유골합장 22
 
0.2%

감면구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9458 
기타면제
 
399
사전예매
 
95
생활수급
 
24
지역주민
 
16
Other values (2)
 
8

Length

Max length4
Median length2
Mean length2.1084
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row사전예매
3rd row일반
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 9458
94.6%
기타면제 399
 
4.0%
사전예매 95
 
0.9%
생활수급 24
 
0.2%
지역주민 16
 
0.2%
국가유공 4
 
< 0.1%
참전유공 4
 
< 0.1%

Length

2024-04-06T17:58:08.524624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:08.743141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 9458
94.6%
기타면제 399
 
4.0%
사전예매 95
 
0.9%
생활수급 24
 
0.2%
지역주민 16
 
0.2%
국가유공 4
 
< 0.1%
참전유공 4
 
< 0.1%

묘지수납구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영구(신규불가)
9398 
최초(15년)
 
602

Length

Max length8
Median length8
Mean length7.9398
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영구(신규불가)
2nd row최초(15년)
3rd row영구(신규불가)
4th row영구(신규불가)
5th row영구(신규불가)

Common Values

ValueCountFrequency (%)
영구(신규불가) 9398
94.0%
최초(15년) 602
 
6.0%

Length

2024-04-06T17:58:08.955964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:09.127465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영구(신규불가 9398
94.0%
최초(15년 602
 
6.0%

사용료
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
300000
9963 
600000
 
33
0
 
4

Length

Max length6
Median length6
Mean length5.998
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row300000
2nd row300000
3rd row300000
4th row300000
5th row300000

Common Values

ValueCountFrequency (%)
300000 9963
99.6%
600000 33
 
0.3%
0 4
 
< 0.1%

Length

2024-04-06T17:58:09.323280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:58:09.550918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
300000 9963
99.6%
600000 33
 
0.3%
0 4
 
< 0.1%

Correlations

2024-04-06T17:58:09.700129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분시도구분매장종류감면구분묘지수납구분사용료
순번1.0000.9380.0000.4570.4520.5370.314
구분0.9381.0000.0000.4480.4380.5300.327
시도구분0.0000.0001.0000.0600.1050.0180.368
매장종류0.4570.4480.0601.0000.2820.4460.191
감면구분0.4520.4380.1050.2821.0000.5490.369
묘지수납구분0.5370.5300.0180.4460.5491.0000.097
사용료0.3140.3270.3680.1910.3690.0971.000
2024-04-06T17:58:09.933827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사용료감면구분매장종류시도구분순번묘지수납구분구분
사용료1.0000.2680.1460.1310.1070.1610.112
감면구분0.2681.0000.1850.0700.3410.5900.328
매장종류0.1460.1851.0000.0450.3890.5430.379
시도구분0.1310.0700.0451.0000.0000.0300.000
순번0.1070.3410.3890.0001.0000.8040.695
묘지수납구분0.1610.5900.5430.0300.8041.0000.796
구분0.1120.3280.3790.0000.6950.7961.000
2024-04-06T17:58:10.233233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분시도구분매장종류감면구분묘지수납구분사용료
순번1.0000.6950.0000.3890.3410.8040.107
구분0.6951.0000.0000.3790.3280.7960.112
시도구분0.0000.0001.0000.0450.0700.0300.131
매장종류0.3890.3790.0451.0000.1850.5430.146
감면구분0.3410.3280.0700.1851.0000.5900.268
묘지수납구분0.8040.7960.0300.5430.5901.0000.161
사용료0.1070.1120.1310.1460.2680.1611.000

Missing values

2024-04-06T17:58:01.090179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:58:01.447832image/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.
2024-04-06T17:58:01.695331image/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

묘지정보순번사망일자매장일자만료일자구분개장여부개장일자시도구분매장종류감면구분묘지수납구분사용료
1117605묘원 31블럭 0356호11974-01-151974-01-17<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
398801묘원 12블럭 0023호22015-03-292015-03-312045-03-30재사용<NA><NA>자시시체사전예매최초(15년)300000
975404묘원 28블럭 0269호11974-09-051974-09-07<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
223701묘원 06블럭 0246호11970-06-151970-06-17<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
493402묘원 14블럭 0336호21987-07-251987-07-27<NA>재사용<NA><NA>자시시체일반영구(신규불가)300000
32301묘원 02블럭 0019호11968-10-011968-10-02<NA>신규<NA><NA>자시시체기타면제영구(신규불가)300000
2241911묘원 54블럭 0457호11978-11-241978-11-25<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2322311묘원 55블럭 0605호11979-06-181979-06-19<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
883504묘원 26블럭 0131호11972-11-231972-11-24<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
1196406묘원 32블럭 0591호12011-11-032011-11-052026-11-04신규<NA><NA>자시시체기타면제영구(신규불가)300000
묘지정보순번사망일자매장일자만료일자구분개장여부개장일자시도구분매장종류감면구분묘지수납구분사용료
2221311묘원 54블럭 0253호11978-12-041978-12-06<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2246811묘원 54블럭 0505호11978-12-071979-01-09<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
704203묘원 20블럭 0164호12010-01-112010-01-132040-01-12신규<NA><NA>자시화장유골기타면제최초(15년)300000
441102묘원 13블럭 0325호11992-11-041992-11-05<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
9101묘원 01블럭 0091호11969-04-101969-04-12<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2558413묘원 59블럭 0016호11980-07-131980-07-16<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2567913묘원 59블럭 0106호11980-04-201980-04-21<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2951614묘원 64블럭 0614호11981-03-241981-03-26<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
1542708묘원 40블럭 0163호11976-05-051976-05-07<NA>신규<NA><NA>자시시체일반영구(신규불가)300000
2298511묘원 55블럭 0374호11979-04-101979-04-12<NA>개장Y2014-05-15자시시체일반영구(신규불가)300000