Overview

Dataset statistics

Number of variables13
Number of observations39
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory113.4 B

Variable types

Categorical3
Text3
DateTime1
Numeric6

Dataset

Description강원도 납골당추모공원 정보(시설명, 공사설 구분, 종류, 설치년도, 안치능력, 연락처 소재지도로명주소, 위치 위도/경도 등) 데이터를 제공합니다.
Author강원도
URLhttps://www.data.go.kr/data/15033696/fileData.do

Alerts

허가면적 is highly overall correlated with 시설면적High correlation
시설면적 is highly overall correlated with 허가면적High correlation
안치능력 is highly overall correlated with 기안치수High correlation
기안치수 is highly overall correlated with 안치능력High correlation
경도 is highly overall correlated with 시군구명High correlation
위도 is highly overall correlated with 시군구명High correlation
시군구명 is highly overall correlated with 경도 and 2 other fieldsHigh correlation
공사설구분 is highly overall correlated with 시군구명High correlation
설치년도 has 1 (2.6%) missing valuesMissing
기안치수 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:55:35.474519
Analysis finished2023-12-12 21:55:40.111816
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
춘천시
5 
강릉시
4 
인제군
4 
정선군
4 
양구군
3 
Other values (11)
19 

Length

Max length4
Median length3
Mean length3.1282051
Min length3

Unique

Unique5 ?
Unique (%)12.8%

Sample

1st row강릉시
2nd row강릉시
3rd row강릉시
4th row강릉시
5th row고성군

Common Values

ValueCountFrequency (%)
춘천시 5
12.8%
강릉시 4
10.3%
인제군 4
10.3%
정선군 4
10.3%
양구군 3
7.7%
태백시 3
7.7%
평창군 3
7.7%
고성군 2
 
5.1%
속초시 2
 
5.1%
양양군 2
 
5.1%
Other values (6) 7
17.9%

Length

2023-12-13T06:55:40.197708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
춘천시 5
12.8%
강릉시 4
10.3%
인제군 4
10.3%
정선군 4
10.3%
양구군 3
7.7%
태백시 3
7.7%
평창군 3
7.7%
고성군 2
 
5.1%
속초시 2
 
5.1%
양양군 2
 
5.1%
Other values (6) 7
17.9%

시설명
Text

Distinct33
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T06:55:40.423900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.6666667
Min length3

Characters and Unicode

Total characters299
Distinct characters74
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

Unique30 ?
Unique (%)76.9%

Sample

1st row청솔공원묘원
2nd row강릉공원묘원
3rd row영동공원묘원
4th row청솔공원 영생의 집
5th row고성군 공설묘원
ValueCountFrequency (%)
공설봉안시설 4
 
7.4%
평창군 3
 
5.6%
태백공원묘원 3
 
5.6%
공설묘지 3
 
5.6%
봉안시설 2
 
3.7%
집 2
 
3.7%
고성군 2
 
3.7%
양양군 2
 
3.7%
속초시 2
 
3.7%
경춘공원묘원 1
 
1.9%
Other values (30) 30
55.6%
2023-12-13T06:55:40.886616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 27
 
9.0%
원 25
 
8.4%
설 22
 
7.4%
묘 19
 
6.4%
15
 
5.0%
안 14
 
4.7%
군 12
 
4.0%
봉 12
 
4.0%
시 9
 
3.0%
지 8
 
2.7%
Other values (64) 136
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 278
93.0%
Space Separator 15
 
5.0%
Close Punctuation 3
 
1.0%
Open Punctuation 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 27
 
9.7%
원 25
 
9.0%
설 22
 
7.9%
묘 19
 
6.8%
안 14
 
5.0%
군 12
 
4.3%
봉 12
 
4.3%
시 9
 
3.2%
지 8
 
2.9%
천 6
 
2.2%
Other values (61) 124
44.6%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 278
93.0%
Common 21
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 27
 
9.7%
원 25
 
9.0%
설 22
 
7.9%
묘 19
 
6.8%
안 14
 
5.0%
군 12
 
4.3%
봉 12
 
4.3%
시 9
 
3.2%
지 8
 
2.9%
천 6
 
2.2%
Other values (61) 124
44.6%
Common
ValueCountFrequency (%)
15
71.4%
) 3
 
14.3%
( 3
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 278
93.0%
ASCII 21
 
7.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 27
 
9.7%
원 25
 
9.0%
설 22
 
7.9%
묘 19
 
6.8%
안 14
 
5.0%
군 12
 
4.3%
봉 12
 
4.3%
시 9
 
3.2%
지 8
 
2.9%
천 6
 
2.2%
Other values (61) 124
44.6%
ASCII
ValueCountFrequency (%)
15
71.4%
) 3
 
14.3%
( 3
 
14.3%

공사설구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
공설
30 
사설
9 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공설 30
76.9%
사설 9
 
23.1%

Length

2023-12-13T06:55:41.063224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:55:41.164429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공설 30
76.9%
사설 9
 
23.1%

종류
Categorical

Distinct14
Distinct (%)35.9%
Missing0
Missing (%)0.0%
Memory size444.0 B
묘지
11 
봉안시설
11 
봉안당
5 
자연장지
2 
납골
 
1
Other values (9)
9 

Length

Max length15
Median length12
Mean length3.8205128
Min length2

Unique

Unique10 ?
Unique (%)25.6%

Sample

1st row묘지
2nd row묘지
3rd row묘지
4th row봉안시설
5th row묘지

Common Values

ValueCountFrequency (%)
묘지 11
28.2%
봉안시설 11
28.2%
봉안당 5
12.8%
자연장지 2
 
5.1%
납골 1
 
2.6%
묘지/봉안시설 1
 
2.6%
봉안묘 1
 
2.6%
하늘공원(묘지) 1
 
2.6%
휴공원(개인단,부부단) 1
 
2.6%
무연단 1
 
2.6%
Other values (4) 4
 
10.3%

Length

2023-12-13T06:55:41.272008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
묘지 11
28.2%
봉안시설 11
28.2%
봉안당 5
12.8%
자연장지 2
 
5.1%
납골 1
 
2.6%
묘지/봉안시설 1
 
2.6%
봉안묘 1
 
2.6%
하늘공원(묘지 1
 
2.6%
휴공원(개인단,부부단 1
 
2.6%
무연단 1
 
2.6%
Other values (4) 4
 
10.3%

설치년도
Date

MISSING 

Distinct28
Distinct (%)73.7%
Missing1
Missing (%)2.6%
Memory size444.0 B
Minimum1905-06-19 00:00:00
Maximum2015-07-01 00:00:00
2023-12-13T06:55:41.378170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:41.533652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

허가면적
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49396.291
Minimum70
Maximum248000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:41.686443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile301.6
Q11849.5
median4461
Q396169
95-th percentile196998
Maximum248000
Range247930
Interquartile range (IQR)94319.5

Descriptive statistics

Standard deviation72992.019
Coefficient of variation (CV)1.4776822
Kurtosis0.5574622
Mean49396.291
Median Absolute Deviation (MAD)4361
Skewness1.3537508
Sum1926455.4
Variance5.3278349 × 109
MonotonicityNot monotonic
2023-12-13T06:55:41.808069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
129500.0 3
 
7.7%
178400.0 2
 
5.1%
8970.0 2
 
5.1%
248000.0 1
 
2.6%
6480.0 1
 
2.6%
2003.0 1
 
2.6%
9930.0 1
 
2.6%
100.0 1
 
2.6%
9950.0 1
 
2.6%
70.0 1
 
2.6%
Other values (25) 25
64.1%
ValueCountFrequency (%)
70.0 1
2.6%
100.0 1
2.6%
324.0 1
2.6%
348.0 1
2.6%
541.0 1
2.6%
826.06 1
2.6%
883.0 1
2.6%
1234.0 1
2.6%
1243.7 1
2.6%
1805.0 1
2.6%
ValueCountFrequency (%)
248000.0 1
 
2.6%
210669.0 1
 
2.6%
195479.0 1
 
2.6%
178400.0 2
5.1%
129500.0 3
7.7%
114513.0 1
 
2.6%
98611.0 1
 
2.6%
93727.0 1
 
2.6%
70702.0 1
 
2.6%
44534.0 1
 
2.6%

시설면적
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18293.771
Minimum13
Maximum157000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:41.940569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile68.4
Q1859
median1807
Q39940
95-th percentile114753.6
Maximum157000
Range156987
Interquartile range (IQR)9081

Descriptive statistics

Standard deviation36584.953
Coefficient of variation (CV)1.9998585
Kurtosis6.4839929
Mean18293.771
Median Absolute Deviation (MAD)1753
Skewness2.6318181
Sum713457.06
Variance1.3384588 × 109
MonotonicityNot monotonic
2023-12-13T06:55:42.066942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
8970.0 2
 
5.1%
77603.0 1
 
2.6%
11337.0 1
 
2.6%
54.0 1
 
2.6%
1181.0 1
 
2.6%
9930.0 1
 
2.6%
100.0 1
 
2.6%
9950.0 1
 
2.6%
13.0 1
 
2.6%
6480.0 1
 
2.6%
Other values (28) 28
71.8%
ValueCountFrequency (%)
13.0 1
2.6%
54.0 1
2.6%
70.0 1
2.6%
100.0 1
2.6%
160.0 1
2.6%
324.0 1
2.6%
663.0 1
2.6%
705.0 1
2.6%
826.06 1
2.6%
835.0 1
2.6%
ValueCountFrequency (%)
157000.0 1
2.6%
116919.0 1
2.6%
114513.0 1
2.6%
77603.0 1
2.6%
44534.0 1
2.6%
43371.0 1
2.6%
37687.0 1
2.6%
20720.0 1
2.6%
11337.0 1
2.6%
9950.0 1
2.6%

안치능력
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3652.6154
Minimum3
Maximum15000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:42.198142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile92
Q1868
median2000
Q35400
95-th percentile11099.2
Maximum15000
Range14997
Interquartile range (IQR)4532

Descriptive statistics

Standard deviation3810.8516
Coefficient of variation (CV)1.0433214
Kurtosis1.0138426
Mean3652.6154
Median Absolute Deviation (MAD)1600
Skewness1.310973
Sum142452
Variance14522590
MonotonicityNot monotonic
2023-12-13T06:55:42.324216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
5000 2
 
5.1%
455 1
 
2.6%
481 1
 
2.6%
11200 1
 
2.6%
610 1
 
2.6%
2353 1
 
2.6%
941 1
 
2.6%
1617 1
 
2.6%
3763 1
 
2.6%
97 1
 
2.6%
Other values (28) 28
71.8%
ValueCountFrequency (%)
3 1
2.6%
47 1
2.6%
97 1
2.6%
220 1
2.6%
285 1
2.6%
455 1
2.6%
481 1
2.6%
528 1
2.6%
610 1
2.6%
810 1
2.6%
ValueCountFrequency (%)
15000 1
2.6%
11200 1
2.6%
11088 1
2.6%
10480 1
2.6%
10066 1
2.6%
8676 1
2.6%
7344 1
2.6%
6324 1
2.6%
5846 1
2.6%
5800 1
2.6%

기안치수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1582.2821
Minimum6
Maximum8855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:42.446052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile19.8
Q1181.5
median795
Q31863
95-th percentile5024.7
Maximum8855
Range8849
Interquartile range (IQR)1681.5

Descriptive statistics

Standard deviation2097.8316
Coefficient of variation (CV)1.3258266
Kurtosis4.4524479
Mean1582.2821
Median Absolute Deviation (MAD)698
Skewness2.0876429
Sum61709
Variance4400897.6
MonotonicityNot monotonic
2023-12-13T06:55:42.573941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
4691 1
 
2.6%
3275 1
 
2.6%
1211 1
 
2.6%
334 1
 
2.6%
8855 1
 
2.6%
2043 1
 
2.6%
143 1
 
2.6%
997 1
 
2.6%
98 1
 
2.6%
79 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
6 1
2.6%
18 1
2.6%
20 1
2.6%
47 1
2.6%
61 1
2.6%
79 1
2.6%
82 1
2.6%
97 1
2.6%
98 1
2.6%
143 1
2.6%
ValueCountFrequency (%)
8855 1
2.6%
8028 1
2.6%
4691 1
2.6%
4461 1
2.6%
4163 1
2.6%
3896 1
2.6%
3275 1
2.6%
2817 1
2.6%
2800 1
2.6%
2043 1
2.6%

연락처
Text

Distinct24
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T06:55:42.764944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters468
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 (%)38.5%

Sample

1st row033-660-2361
2nd row033-644-0533
3rd row033-645-7444
4th row033-660-2364
5th row033-682-4448
ValueCountFrequency (%)
033-462-6989 4
 
10.3%
033-550-2844 3
 
7.7%
033-480-2576 3
 
7.7%
033-563-2333 3
 
7.7%
033-330-2309 3
 
7.7%
033-430-2106 2
 
5.1%
033-682-4448 2
 
5.1%
033-635-7023 2
 
5.1%
033-670-2342 2
 
5.1%
033-251-7073 1
 
2.6%
Other values (14) 14
35.9%
2023-12-13T06:55:43.108184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 119
25.4%
- 78
16.7%
0 70
15.0%
4 45
 
9.6%
2 40
 
8.5%
6 38
 
8.1%
5 22
 
4.7%
9 17
 
3.6%
7 17
 
3.6%
8 16
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
83.3%
Dash Punctuation 78
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 119
30.5%
0 70
17.9%
4 45
 
11.5%
2 40
 
10.3%
6 38
 
9.7%
5 22
 
5.6%
9 17
 
4.4%
7 17
 
4.4%
8 16
 
4.1%
1 6
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 119
25.4%
- 78
16.7%
0 70
15.0%
4 45
 
9.6%
2 40
 
8.5%
6 38
 
8.1%
5 22
 
4.7%
9 17
 
3.6%
7 17
 
3.6%
8 16
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 119
25.4%
- 78
16.7%
0 70
15.0%
4 45
 
9.6%
2 40
 
8.5%
6 38
 
8.1%
5 22
 
4.7%
9 17
 
3.6%
7 17
 
3.6%
8 16
 
3.4%

소재지도로명주소
Text

Distinct26
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
2023-12-13T06:55:43.357423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.923077
Min length15

Characters and Unicode

Total characters816
Distinct characters90
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

Unique19 ?
Unique (%)48.7%

Sample

1st row강원도 강릉시 청솔공원길 292-55
2nd row강원도 강릉시 사천면 청솔공원길 400
3rd row강원도 강릉시 강동면 율곡로2118-45
4th row강원도 강릉시 청솔공원길 292-55
5th row강원도 고성군 죽왕면 공설묘원길 32
ValueCountFrequency (%)
강원도 39
 
21.2%
서동로 6
 
3.3%
춘천시 5
 
2.7%
남면 4
 
2.2%
원남로 4
 
2.2%
444-62 4
 
2.2%
인제군 4
 
2.2%
강릉시 4
 
2.2%
정선군 4
 
2.2%
518-40 3
 
1.6%
Other values (69) 107
58.2%
2023-12-13T06:55:43.706225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
145
 
17.8%
강 51
 
6.2%
원 51
 
6.2%
도 39
 
4.8%
4 34
 
4.2%
로 30
 
3.7%
1 29
 
3.6%
- 25
 
3.1%
2 24
 
2.9%
군 22
 
2.7%
Other values (80) 366
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
57.2%
Decimal Number 179
 
21.9%
Space Separator 145
 
17.8%
Dash Punctuation 25
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
강 51
 
10.9%
원 51
 
10.9%
도 39
 
8.4%
로 30
 
6.4%
군 22
 
4.7%
면 21
 
4.5%
시 17
 
3.6%
남 14
 
3.0%
양 14
 
3.0%
천 14
 
3.0%
Other values (68) 194
41.5%
Decimal Number
ValueCountFrequency (%)
4 34
19.0%
1 29
16.2%
2 24
13.4%
3 17
9.5%
6 17
9.5%
5 16
8.9%
8 14
7.8%
7 11
 
6.1%
9 9
 
5.0%
0 8
 
4.5%
Space Separator
ValueCountFrequency (%)
145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 467
57.2%
Common 349
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
강 51
 
10.9%
원 51
 
10.9%
도 39
 
8.4%
로 30
 
6.4%
군 22
 
4.7%
면 21
 
4.5%
시 17
 
3.6%
남 14
 
3.0%
양 14
 
3.0%
천 14
 
3.0%
Other values (68) 194
41.5%
Common
ValueCountFrequency (%)
145
41.5%
4 34
 
9.7%
1 29
 
8.3%
- 25
 
7.2%
2 24
 
6.9%
3 17
 
4.9%
6 17
 
4.9%
5 16
 
4.6%
8 14
 
4.0%
7 11
 
3.2%
Other values (2) 17
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 467
57.2%
ASCII 349
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
145
41.5%
4 34
 
9.7%
1 29
 
8.3%
- 25
 
7.2%
2 24
 
6.9%
3 17
 
4.9%
6 17
 
4.9%
5 16
 
4.6%
8 14
 
4.0%
7 11
 
3.2%
Other values (2) 17
 
4.9%
Hangul
ValueCountFrequency (%)
강 51
 
10.9%
원 51
 
10.9%
도 39
 
8.4%
로 30
 
6.4%
군 22
 
4.7%
면 21
 
4.5%
시 17
 
3.6%
남 14
 
3.0%
양 14
 
3.0%
천 14
 
3.0%
Other values (68) 194
41.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.3798
Minimum127.58996
Maximum129.11506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:43.811407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.58996
5-th percentile127.67439
Q1127.99863
median128.42233
Q3128.80542
95-th percentile129.00195
Maximum129.11506
Range1.525105
Interquartile range (IQR)0.80678915

Descriptive statistics

Standard deviation0.47385254
Coefficient of variation (CV)0.0036910209
Kurtosis-1.3149315
Mean128.3798
Median Absolute Deviation (MAD)0.40181
Skewness-0.12600867
Sum5006.8123
Variance0.22453623
MonotonicityNot monotonic
2023-12-13T06:55:43.908871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
128.162539 4
 
10.3%
128.422327 3
 
7.7%
127.998629 3
 
7.7%
128.9895916 3
 
7.7%
128.7943933 3
 
7.7%
128.816443 2
 
5.1%
128.547915 2
 
5.1%
128.615158 2
 
5.1%
127.630353 1
 
2.6%
128.0807076 1
 
2.6%
Other values (15) 15
38.5%
ValueCountFrequency (%)
127.58996 1
 
2.6%
127.630353 1
 
2.6%
127.6792806 1
 
2.6%
127.699129 1
 
2.6%
127.729239 1
 
2.6%
127.743979 1
 
2.6%
127.845206 1
 
2.6%
127.845228 1
 
2.6%
127.8929789 1
 
2.6%
127.998629 3
7.7%
ValueCountFrequency (%)
129.115065 1
 
2.6%
129.1131467 1
 
2.6%
128.9895916 3
7.7%
128.965063 1
 
2.6%
128.8393382 1
 
2.6%
128.824137 1
 
2.6%
128.816443 2
5.1%
128.7943933 3
7.7%
128.615158 2
5.1%
128.547915 2
5.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.765715
Minimum37.230272
Maximum38.367899
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2023-12-13T06:55:44.027436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.230272
5-th percentile37.235838
Q137.48249
median37.827348
Q338.026316
95-th percentile38.219448
Maximum38.367899
Range1.1376272
Interquartile range (IQR)0.54382558

Descriptive statistics

Standard deviation0.32995028
Coefficient of variation (CV)0.0087367676
Kurtosis-1.0453796
Mean37.765715
Median Absolute Deviation (MAD)0.294315
Skewness-0.047018283
Sum1472.8629
Variance0.10886719
MonotonicityNot monotonic
2023-12-13T06:55:44.139082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
38.00234 4
 
10.3%
37.420673 3
 
7.7%
38.121663 3
 
7.7%
37.23583833 3
 
7.7%
37.50364764 3
 
7.7%
37.8287759 2
 
5.1%
38.203041 2
 
5.1%
38.050292 2
 
5.1%
37.81294 1
 
2.6%
37.52912261 1
 
2.6%
Other values (15) 15
38.5%
ValueCountFrequency (%)
37.23027176 1
 
2.6%
37.23583833 3
7.7%
37.3354754 1
 
2.6%
37.420673 3
7.7%
37.456509 1
 
2.6%
37.4613332 1
 
2.6%
37.50364764 3
7.7%
37.52912261 1
 
2.6%
37.678671 1
 
2.6%
37.678738 1
 
2.6%
ValueCountFrequency (%)
38.367899 1
 
2.6%
38.36710911 1
 
2.6%
38.203041 2
5.1%
38.121663 3
7.7%
38.0703023 1
 
2.6%
38.050292 2
5.1%
38.00234 4
10.3%
37.849209 1
 
2.6%
37.84669 1
 
2.6%
37.841653 1
 
2.6%

Interactions

2023-12-13T06:55:38.820112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:35.986749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.503019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.089004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.736285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.280005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.925323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.061085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.592368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.183769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.824924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.377395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:39.020959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.152210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.680676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.346320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.915037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.471675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:39.112671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.229791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.782838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.443086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.004129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.554175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:39.210778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.300007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.875430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.525116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.082811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.635391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:39.327414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.424477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:36.979291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:37.631058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.187211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:55:38.722401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:55:44.220414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명시설명공사설구분종류설치년도허가면적시설면적안치능력기안치수연락처소재지도로명주소경도위도
시군구명1.0000.9930.7960.7760.9960.6980.0000.7850.0001.0001.0000.9710.973
시설명0.9931.0000.7240.0000.9630.9920.7860.9290.9400.9970.9980.9760.986
공사설구분0.7960.7241.0000.0001.0000.0000.1930.0000.2940.9730.9610.5530.628
종류0.7760.0000.0001.0000.0000.0000.0000.5820.0000.0000.0000.0000.000
설치년도0.9960.9631.0000.0001.0000.9810.8750.9170.7080.9880.9810.9920.986
허가면적0.6980.9920.0000.0000.9811.0000.9200.0690.3190.8790.9560.8040.608
시설면적0.0000.7860.1930.0000.8750.9201.0000.4170.5240.8790.7340.1680.043
안치능력0.7850.9290.0000.5820.9170.0690.4171.0000.7080.8520.7890.0000.000
기안치수0.0000.9400.2940.0000.7080.3190.5240.7081.0000.9340.8640.0000.315
연락처1.0000.9970.9730.0000.9880.8790.8790.8520.9341.0000.9961.0001.000
소재지도로명주소1.0000.9980.9610.0000.9810.9560.7340.7890.8640.9961.0001.0001.000
경도0.9710.9760.5530.0000.9920.8040.1680.0000.0001.0001.0001.0000.876
위도0.9730.9860.6280.0000.9860.6080.0430.0000.3151.0001.0000.8761.000
2023-12-13T06:55:44.333992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공사설구분종류시군구명
공사설구분1.0000.0000.506
종류0.0001.0000.365
시군구명0.5060.3651.000
2023-12-13T06:55:44.408743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가면적시설면적안치능력기안치수경도위도시군구명공사설구분종류
허가면적1.0000.7290.0130.1710.358-0.1400.3130.0000.000
시설면적0.7291.0000.1470.1720.3300.0890.0000.1170.000
안치능력0.0130.1471.0000.7300.414-0.2410.4020.0000.246
기안치수0.1710.1720.7301.0000.268-0.1680.0000.2860.000
경도0.3580.3300.4140.2681.000-0.3830.7690.4970.000
위도-0.1400.089-0.241-0.168-0.3831.0000.7770.4260.000
시군구명0.3130.0000.4020.0000.7690.7771.0000.5060.365
공사설구분0.0000.1170.0000.2860.4970.4260.5061.0000.000
종류0.0000.0000.2460.0000.0000.0000.3650.0001.000

Missing values

2023-12-13T06:55:39.513204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:55:40.032272image/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

시군구명시설명공사설구분종류설치년도허가면적시설면적안치능력기안치수연락처소재지도로명주소경도위도
0강릉시청솔공원묘원공설묘지08/01/2000248000.077603.073444691033-660-2361강원도 강릉시 청솔공원길 292-55128.81644337.828776
1강릉시강릉공원묘원사설묘지08/24/1982210669.0157000.050003275033-644-0533강원도 강릉시 사천면 청솔공원길 400128.82413737.827348
2강릉시영동공원묘원사설묘지03/01/1979195479.0116919.058463896033-645-7444강원도 강릉시 강동면 율곡로2118-45128.96506337.728834
3강릉시청솔공원 영생의 집공설봉안시설10/08/20013500.0901.0100668028033-660-2364강원도 강릉시 청솔공원길 292-55128.81644337.828776
4고성군고성군 공설묘원공설묘지06/19/190544534.044534.01504801033-682-4448강원도 고성군 죽왕면 공설묘원길 32128.49862838.367109
5고성군고성군 추모의집공설봉안시설07/01/19054461.0835.01616626033-682-4448강원도 고성군 죽왕면 공설묘원길 47128.49684738.367899
6동해시하늘정원봉안당공설납골01/01/20081894.01575.6150001291033-530-2796강원도 동해시 강원남부로 4589129.11314737.461333
7삼척시삼척시 공설묘지공설묘지/봉안시설02/01/199893727.043371.063244163033-570-7912강원도 삼척시 강원남부로 4541129.11506537.456509
8속초시속초시 추모의 집공설봉안당02/02/2004826.06826.0686764461033-635-7023강원도 속초시 이목로 196128.54791538.203041
9속초시속초시 공설봉안묘공설봉안묘07/01/20154055.04055.052847033-635-7023강원도 속초시 이목로 196128.54791538.203041
시군구명시설명공사설구분종류설치년도허가면적시설면적안치능력기안치수연락처소재지도로명주소경도위도
29태백시태백공원묘원공설자연장지07/01/20136480.06480.0200079033-550-2844강원도 태백시 백두대간로 844128.98959237.235838
30태백시태백공원묘원공설묘지01/01/200320720.020720.01972795033-550-2844강원도 태백시 백두대간로 844128.98959237.235838
31태백시태백공원묘원공설추모관01/01/2003883.0883.0104802817033-550-2844강원도 태백시 백두대간로 844128.98959237.235838
32평창군평창군 공설묘지공설묘지05/03/2002178400.037687.01140754033-330-2309강원도 평창군 방림면 서동로 1741-36128.42232737.420673
33평창군평창군 봉안시설공설봉안담05/03/2002178400.070.0926926033-330-2309강원도 평창군 방림면 서동로 1741-36128.42232737.420673
34평창군평창군 봉안시설공설봉안당10/29/20141234.0663.0500097033-330-2309강원도 평창군 방림면 서동로 1741-36128.42232737.420673
35홍천군홍천군공설묘지공설묘지08/01/200970702.09700.0970275033-430-2106강원도 홍천군 홍천읍 느리울길 141-22127.84522837.678671
36홍천군홍천군공설묘지봉안당공설봉안당08/01/20093377.01086.0110881253033-430-2106강원도 홍천군 홍천읍 느리울길 141-23127.84520637.678738
37화천군화천공설장례식장공설장례식장<NA>1805.01285.036033-442-0452강원도 화천군 하남면 영서로 5697-69127.67928138.070302
38횡성군횡성군공설묘원 추모관공설봉안시설04/01/20043610.01108.035001683033-340-2904강원도 횡성군 갑천면 태기로구방8길 132128.08070837.529123