Overview

Dataset statistics

Number of variables10
Number of observations44
Missing cells31
Missing cells (%)7.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory86.9 B

Variable types

Numeric4
Categorical3
Text3

Dataset

Description남양주시 장사시설 정보에 대한 데이터로 구분(공설공동묘지, 사설묘지, 사설봉안시설, 장례식장), 묘지명, 주소, 면적 등의 항목을 제공합니다.
Author경기도 남양주시
URLhttps://www.data.go.kr/data/3033819/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
구분 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
비고 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
순번 is highly overall correlated with 개설년도 and 2 other fieldsHigh correlation
면적 is highly overall correlated with 기수_빈소수 and 2 other fieldsHigh correlation
기수_빈소수 is highly overall correlated with 면적 and 2 other fieldsHigh correlation
개설년도 is highly overall correlated with 순번 and 2 other fieldsHigh correlation
면적 has 6 (13.6%) missing valuesMissing
전화번호 has 25 (56.8%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-15 01:41:00.956213
Analysis finished2024-03-15 01:41:07.182872
Duration6.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T10:41:07.415868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2024-03-15T10:41:07.817831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size480.0 B
공설공동묘지
25 
장례식장
6 
사설묘지(재단법인)
4 
사설봉안시설(종교단체봉안당)
3 
사설봉안시설(법인봉안묘)
 
2
Other values (4)
4 

Length

Max length15
Median length6
Mean length7.5
Min length4

Unique

Unique4 ?
Unique (%)9.1%

Sample

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

Common Values

ValueCountFrequency (%)
공설공동묘지 25
56.8%
장례식장 6
 
13.6%
사설묘지(재단법인) 4
 
9.1%
사설봉안시설(종교단체봉안당) 3
 
6.8%
사설봉안시설(법인봉안묘) 2
 
4.5%
사설묘지 1
 
2.3%
사설봉안시설(사설봉안당) 1
 
2.3%
사설봉안시설(재단봉안당) 1
 
2.3%
사설봉안시설(종교단체봉안탑) 1
 
2.3%

Length

2024-03-15T10:41:08.112567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:41:08.405529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공설공동묘지 25
56.8%
장례식장 6
 
13.6%
사설묘지(재단법인 4
 
9.1%
사설봉안시설(종교단체봉안당 3
 
6.8%
사설봉안시설(법인봉안묘 2
 
4.5%
사설묘지 1
 
2.3%
사설봉안시설(사설봉안당 1
 
2.3%
사설봉안시설(재단봉안당 1
 
2.3%
사설봉안시설(종교단체봉안탑 1
 
2.3%

묘지명
Text

Distinct30
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T10:41:09.181964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length6
Mean length6.25
Min length3

Characters and Unicode

Total characters275
Distinct characters65
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)50.0%

Sample

1st row와부공동묘지
2nd row와부공동묘지
3rd row진접공동묘지
4th row진접공동묘지
5th row진접공동묘지
ValueCountFrequency (%)
화도공동묘지 4
 
9.1%
진접공동묘지 4
 
9.1%
진건공동묘지 4
 
9.1%
와부공동묘지 2
 
4.5%
재)천주교소화묘원 2
 
4.5%
수동공동묘지 2
 
4.5%
모란공원(한국공원개발㈜ 2
 
4.5%
봉인사 2
 
4.5%
재)천주교평내묘원 1
 
2.3%
한양병원 1
 
2.3%
Other values (20) 20
45.5%
2024-03-15T10:41:10.299533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 31
 
11.3%
묘 30
 
10.9%
지 26
 
9.5%
동 25
 
9.1%
원 17
 
6.2%
( 9
 
3.3%
) 9
 
3.3%
진 8
 
2.9%
화 7
 
2.5%
재 7
 
2.5%
Other values (55) 106
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
92.7%
Open Punctuation 9
 
3.3%
Close Punctuation 9
 
3.3%
Other Symbol 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 31
 
12.2%
묘 30
 
11.8%
지 26
 
10.2%
동 25
 
9.8%
원 17
 
6.7%
진 8
 
3.1%
화 7
 
2.7%
재 7
 
2.7%
주 5
 
2.0%
교 5
 
2.0%
Other values (52) 94
36.9%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 257
93.5%
Common 18
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 31
 
12.1%
묘 30
 
11.7%
지 26
 
10.1%
동 25
 
9.7%
원 17
 
6.6%
진 8
 
3.1%
화 7
 
2.7%
재 7
 
2.7%
주 5
 
1.9%
교 5
 
1.9%
Other values (53) 96
37.4%
Common
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
92.7%
ASCII 18
 
6.5%
None 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 31
 
12.2%
묘 30
 
11.8%
지 26
 
10.2%
동 25
 
9.8%
원 17
 
6.7%
진 8
 
3.1%
화 7
 
2.7%
재 7
 
2.7%
주 5
 
2.0%
교 5
 
2.0%
Other values (52) 94
36.9%
ASCII
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

주소
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T10:41:11.383833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length22.25
Min length18

Characters and Unicode

Total characters979
Distinct characters86
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

Unique42 ?
Unique (%)95.5%

Sample

1st row경기도 남양주시 와부읍 월문리 산339
2nd row경기도 남양주시 와부읍 팔당리 산90
3rd row경기도 남양주시 진접읍 팔야리 산119
4th row경기도 남양주시 진접읍 내곡리 산77
5th row경기도 남양주시 진접읍 장현리 산11
ValueCountFrequency (%)
경기도 44
19.8%
남양주시 44
19.8%
화도읍 11
 
5.0%
진건읍 8
 
3.6%
진접읍 5
 
2.3%
오남읍 3
 
1.4%
평내동 3
 
1.4%
조안면 3
 
1.4%
수동면 3
 
1.4%
산10 2
 
0.9%
Other values (89) 96
43.2%
2024-03-15T10:41:13.003034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
18.3%
도 55
 
5.6%
남 51
 
5.2%
양 49
 
5.0%
경 47
 
4.8%
주 45
 
4.6%
시 44
 
4.5%
기 44
 
4.5%
1 43
 
4.4%
산 33
 
3.4%
Other values (76) 389
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 611
62.4%
Space Separator 179
 
18.3%
Decimal Number 157
 
16.0%
Dash Punctuation 20
 
2.0%
Other Punctuation 7
 
0.7%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 55
 
9.0%
남 51
 
8.3%
양 49
 
8.0%
경 47
 
7.7%
주 45
 
7.4%
시 44
 
7.2%
기 44
 
7.2%
산 33
 
5.4%
읍 29
 
4.7%
리 29
 
4.7%
Other values (60) 185
30.3%
Decimal Number
ValueCountFrequency (%)
1 43
27.4%
0 18
11.5%
5 16
 
10.2%
9 14
 
8.9%
3 14
 
8.9%
4 13
 
8.3%
2 12
 
7.6%
7 11
 
7.0%
6 9
 
5.7%
8 7
 
4.5%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 611
62.4%
Common 367
37.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 55
 
9.0%
남 51
 
8.3%
양 49
 
8.0%
경 47
 
7.7%
주 45
 
7.4%
시 44
 
7.2%
기 44
 
7.2%
산 33
 
5.4%
읍 29
 
4.7%
리 29
 
4.7%
Other values (60) 185
30.3%
Common
ValueCountFrequency (%)
179
48.8%
1 43
 
11.7%
- 20
 
5.4%
0 18
 
4.9%
5 16
 
4.4%
9 14
 
3.8%
3 14
 
3.8%
4 13
 
3.5%
2 12
 
3.3%
7 11
 
3.0%
Other values (5) 27
 
7.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 611
62.4%
ASCII 368
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
48.6%
1 43
 
11.7%
- 20
 
5.4%
0 18
 
4.9%
5 16
 
4.3%
9 14
 
3.8%
3 14
 
3.8%
4 13
 
3.5%
2 12
 
3.3%
7 11
 
3.0%
Other values (6) 28
 
7.6%
Hangul
ValueCountFrequency (%)
도 55
 
9.0%
남 51
 
8.3%
양 49
 
8.0%
경 47
 
7.7%
주 45
 
7.4%
시 44
 
7.2%
기 44
 
7.2%
산 33
 
5.4%
읍 29
 
4.7%
리 29
 
4.7%
Other values (60) 185
30.3%

면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct36
Distinct (%)94.7%
Missing6
Missing (%)13.6%
Infinite0
Infinite (%)0.0%
Mean55519.395
Minimum166
Maximum832425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T10:41:13.407732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum166
5-th percentile2741.6
Q15851
median10437
Q329082.5
95-th percentile227024.9
Maximum832425
Range832259
Interquartile range (IQR)23231.5

Descriptive statistics

Standard deviation143237.32
Coefficient of variation (CV)2.5799511
Kurtosis24.504668
Mean55519.395
Median Absolute Deviation (MAD)6470.5
Skewness4.685088
Sum2109737
Variance2.051693 × 1010
MonotonicityNot monotonic
2024-03-15T10:41:14.018088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
6872 2
 
4.5%
5851 2
 
4.5%
156761 1
 
2.3%
11254 1
 
2.3%
8220 1
 
2.3%
3306 1
 
2.3%
832425 1
 
2.3%
274885 1
 
2.3%
218579 1
 
2.3%
145768 1
 
2.3%
Other values (26) 26
59.1%
(Missing) 6
 
13.6%
ValueCountFrequency (%)
166 1
2.3%
1980 1
2.3%
2876 1
2.3%
2985 1
2.3%
3306 1
2.3%
3966 1
2.3%
3967 1
2.3%
4396 1
2.3%
5620 1
2.3%
5851 2
4.5%
ValueCountFrequency (%)
832425 1
2.3%
274885 1
2.3%
218579 1
2.3%
156761 1
2.3%
145768 1
2.3%
59823 1
2.3%
50294 1
2.3%
46477 1
2.3%
37686 1
2.3%
29256 1
2.3%

기수_빈소수
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4146.75
Minimum3
Maximum77675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T10:41:14.440101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q176.25
median262
Q3823.75
95-th percentile13350.75
Maximum77675
Range77672
Interquartile range (IQR)747.5

Descriptive statistics

Standard deviation14023.253
Coefficient of variation (CV)3.3817456
Kurtosis20.801356
Mean4146.75
Median Absolute Deviation (MAD)255
Skewness4.5082937
Sum182457
Variance1.9665164 × 108
MonotonicityNot monotonic
2024-03-15T10:41:14.707111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
4 2
 
4.5%
3 2
 
4.5%
6 2
 
4.5%
1114 1
 
2.3%
1677 1
 
2.3%
11 1
 
2.3%
13500 1
 
2.3%
12505 1
 
2.3%
6900 1
 
2.3%
2200 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
3 2
4.5%
4 2
4.5%
5 1
2.3%
6 2
4.5%
8 1
2.3%
11 1
2.3%
49 1
2.3%
62 1
2.3%
81 1
2.3%
108 1
2.3%
ValueCountFrequency (%)
77675 1
2.3%
52556 1
2.3%
13500 1
2.3%
12505 1
2.3%
6900 1
2.3%
3456 1
2.3%
2385 1
2.3%
2200 1
2.3%
1677 1
2.3%
1114 1
2.3%

개설년도
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1979.4318
Minimum1959
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T10:41:14.964832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1959
5-th percentile1962.15
Q11968
median1968
Q32000.5
95-th percentile2011.85
Maximum2022
Range63
Interquartile range (IQR)32.5

Descriptive statistics

Standard deviation19.252783
Coefficient of variation (CV)0.009726419
Kurtosis-0.77697861
Mean1979.4318
Median Absolute Deviation (MAD)1.5
Skewness0.98800947
Sum87095
Variance370.66966
MonotonicityNot monotonic
2024-03-15T10:41:15.269946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1968 21
47.7%
1963 2
 
4.5%
1962 2
 
4.5%
1973 2
 
4.5%
2002 2
 
4.5%
2009 2
 
4.5%
2000 1
 
2.3%
2012 1
 
2.3%
2011 1
 
2.3%
2007 1
 
2.3%
Other values (9) 9
20.5%
ValueCountFrequency (%)
1959 1
 
2.3%
1962 2
 
4.5%
1963 2
 
4.5%
1966 1
 
2.3%
1968 21
47.7%
1969 1
 
2.3%
1972 1
 
2.3%
1973 2
 
4.5%
1999 1
 
2.3%
2000 1
 
2.3%
ValueCountFrequency (%)
2022 1
2.3%
2017 1
2.3%
2012 1
2.3%
2011 1
2.3%
2010 1
2.3%
2009 2
4.5%
2007 1
2.3%
2005 1
2.3%
2002 2
4.5%
2000 1
2.3%

전화번호
Text

MISSING 

Distinct17
Distinct (%)89.5%
Missing25
Missing (%)56.8%
Memory size480.0 B
2024-03-15T10:41:15.861927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters228
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

Unique15 ?
Unique (%)78.9%

Sample

1st row031-594-6363
2nd row031-573-8123
3rd row031-576-1461
4th row031-571-8800
5th row031-511-8550
ValueCountFrequency (%)
031-594-6363 2
 
10.5%
031-527-5678 2
 
10.5%
031-592-0081 1
 
5.3%
02-2238-3004 1
 
5.3%
031-529-4440 1
 
5.3%
031-574-4442 1
 
5.3%
031-594-4444 1
 
5.3%
031-511-9943 1
 
5.3%
031-528-4444 1
 
5.3%
031-527-1951 1
 
5.3%
Other values (7) 7
36.8%
2024-03-15T10:41:16.745615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 38
16.7%
0 31
13.6%
1 30
13.2%
3 27
11.8%
4 25
11.0%
5 24
10.5%
2 13
 
5.7%
7 12
 
5.3%
9 11
 
4.8%
8 9
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
16.3%
1 30
15.8%
3 27
14.2%
4 25
13.2%
5 24
12.6%
2 13
6.8%
7 12
 
6.3%
9 11
 
5.8%
8 9
 
4.7%
6 8
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 38
16.7%
0 31
13.6%
1 30
13.2%
3 27
11.8%
4 25
11.0%
5 24
10.5%
2 13
 
5.7%
7 12
 
5.3%
9 11
 
4.8%
8 9
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 38
16.7%
0 31
13.6%
1 30
13.2%
3 27
11.8%
4 25
11.0%
5 24
10.5%
2 13
 
5.7%
7 12
 
5.3%
9 11
 
4.8%
8 9
 
3.9%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size480.0 B
만장
25 
<NA>
19 

Length

Max length4
Median length2
Mean length2.8636364
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
만장 25
56.8%
<NA> 19
43.2%

Length

2024-03-15T10:41:16.990638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:41:17.216241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
만장 25
56.8%
na 19
43.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-01-23
44 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-23
2nd row2024-01-23
3rd row2024-01-23
4th row2024-01-23
5th row2024-01-23

Common Values

ValueCountFrequency (%)
2024-01-23 44
100.0%

Length

2024-03-15T10:41:17.497410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:41:17.821749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-23 44
100.0%

Interactions

2024-03-15T10:41:04.980580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:01.530310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:02.684655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:03.800554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:05.255834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:01.800023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:02.940142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:04.079401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:05.512650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:02.045190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:03.190016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:04.375746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:05.795484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:02.426399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:03.521382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:41:04.704985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:41:18.018498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구분묘지명주소면적기수_빈소수개설년도전화번호
순번1.0000.8400.9460.9330.3470.2010.6380.000
구분0.8401.0000.8370.0000.7720.8840.7340.000
묘지명0.9460.8371.0001.0000.9480.9650.9571.000
주소0.9330.0001.0001.0001.0001.0000.4000.934
면적0.3470.7720.9481.0001.0000.5780.0000.934
기수_빈소수0.2010.8840.9651.0000.5781.0000.2760.830
개설년도0.6380.7340.9570.4000.0000.2761.0000.415
전화번호0.0000.0001.0000.9340.9340.8300.4151.000
2024-03-15T10:41:18.299602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분비고
구분1.0001.000
비고1.0001.000
2024-03-15T10:41:18.543929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번면적기수_빈소수개설년도구분비고
순번1.000-0.031-0.0650.7340.5771.000
면적-0.0311.0000.561-0.4080.5901.000
기수_빈소수-0.0650.5611.000-0.2420.7421.000
개설년도0.734-0.408-0.2421.0000.5091.000
구분0.5770.5900.7420.5091.0001.000
비고1.0001.0001.0001.0001.0001.000

Missing values

2024-03-15T10:41:06.161047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:41:06.649107image/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.
2024-03-15T10:41:07.029948image/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

순번구분묘지명주소면적기수_빈소수개설년도전화번호비고데이터기준일자
01공설공동묘지와부공동묘지경기도 남양주시 와부읍 월문리 산3395982311141963<NA>만장2024-01-23
12공설공동묘지와부공동묘지경기도 남양주시 와부읍 팔당리 산9076362421963<NA>만장2024-01-23
23공설공동묘지진접공동묘지경기도 남양주시 진접읍 팔야리 산1193967491968<NA>만장2024-01-23
34공설공동묘지진접공동묘지경기도 남양주시 진접읍 내곡리 산77155702141968<NA>만장2024-01-23
45공설공동묘지진접공동묘지경기도 남양주시 진접읍 장현리 산11376866391968<NA>만장2024-01-23
56공설공동묘지진접공동묘지경기도 남양주시 진접읍 부평리 산6966451181968<NA>만장2024-01-23
67공설공동묘지화도공동묘지경기도 남양주시 화도읍 금남리 40556203151968<NA>만장2024-01-23
78공설공동묘지화도공동묘지경기도 남양주시 화도읍 답내리 산57285624671968<NA>만장2024-01-23
89공설공동묘지화도공동묘지경기도 남양주시 화도읍 차산리 산97292562511968<NA>만장2024-01-23
910공설공동묘지화도공동묘지경기도 남양주시 화도읍 묵현리 산151-1,2138272731968<NA>만장2024-01-23
순번구분묘지명주소면적기수_빈소수개설년도전화번호비고데이터기준일자
3435사설봉안시설(종교단체봉안당)화광사경기도 남양주시 화도읍 월산리 96-1129854962022031-595-0977<NA>2024-01-23
3536사설봉안시설(법인봉안묘)(재)천주교소화묘원경기도 남양주시 조안면 능내리 산10166108201702-2238-3004<NA>2024-01-23
3637사설봉안시설(법인봉안묘)(재)북한강공원경기도 남양주시 화도읍 구암리 285-1,285-246477776752000031-592-0081<NA>2024-01-23
3738사설봉안시설(종교단체봉안탑)봉인사경기도 남양주시 진건읍 송능리 304-1468729762010031-527-5678<NA>2024-01-23
3839장례식장남양주경기도 남양주시 진건읍 진건오남로 485<NA>32002031-528-4444<NA>2024-01-23
3940장례식장원병원경기도 남양주시 화도읍 경춘로 1943-16<NA>62002031-511-9943<NA>2024-01-23
4041장례식장백련장경기도 남양주시 마치로 90 (호평동)<NA>42005031-594-4444<NA>2024-01-23
4142장례식장나눔병원경기도 남양주시 오남읍 진건오남로797번길 9<NA>32007031-574-4442<NA>2024-01-23
4243장례식장한양병원경기도 남양주시 오남읍 양지로 47-55 남양주한양병원 내<NA>52011031-529-4440<NA>2024-01-23
4344장례식장국민병원경기도 남양주시 경춘로1308번길 4 (평내동) B1<NA>42012031-594-4442<NA>2024-01-23