Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells44
Missing cells (%)11.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory67.6 B

Variable types

Categorical2
Text4
Numeric1
DateTime1

Dataset

Description함안군의 공동주택(아파트, 연립주택, 다세대)현황 제공, 공동주택의 단지명, 공동주택의 도로명주소, 공동주택의 세대수, 공동주택의 연면적합계, 공동주택의 사용승인일, 공동주택의 동수,공동주택의 지하층수 ,지상층수 및 세부용도 등의 정보 포함
Author경상남도 함안군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3080708

Alerts

데이터기준일자 has constant value ""Constant
비고 has 44 (88.0%) missing valuesMissing

Reproduction

Analysis started2024-04-17 18:37:27.501100
Analysis finished2024-04-17 18:37:28.050882
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면
Categorical

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
가야읍
28 
칠원읍
13 
칠서면
4 
군북면
3 
법수면
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
가야읍 28
56.0%
칠원읍 13
26.0%
칠서면 4
 
8.0%
군북면 3
 
6.0%
법수면 1
 
2.0%
대산면 1
 
2.0%

Length

2024-04-18T03:37:28.104457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:37:28.181795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가야읍 28
56.0%
칠원읍 13
26.0%
칠서면 4
 
8.0%
군북면 3
 
6.0%
법수면 1
 
2.0%
대산면 1
 
2.0%

아파트 단지명
Text

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-04-18T03:37:28.340386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8.5
Mean length4.64
Min length2

Characters and Unicode

Total characters232
Distinct characters103
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)96.0%

Sample

1st row대송(1차)
2nd row대송(2차)
3rd row대한
4th row동명
5th row무학
ValueCountFrequency (%)
무학 2
 
3.9%
금안주택 1
 
2.0%
메트로자이 1
 
2.0%
고려제강 1
 
2.0%
함안사옥 1
 
2.0%
청호 1
 
2.0%
뉴선두 1
 
2.0%
대륭아트빌 1
 
2.0%
수정그린 1
 
2.0%
신영장미 1
 
2.0%
Other values (40) 40
78.4%
2024-04-18T03:37:28.607915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 11
 
4.7%
( 11
 
4.7%
대 9
 
3.9%
동 8
 
3.4%
빌 7
 
3.0%
차 7
 
3.0%
2 6
 
2.6%
트 5
 
2.2%
1 5
 
2.2%
스 5
 
2.2%
Other values (93) 158
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
85.3%
Close Punctuation 11
 
4.7%
Open Punctuation 11
 
4.7%
Decimal Number 11
 
4.7%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 9
 
4.5%
동 8
 
4.0%
빌 7
 
3.5%
차 7
 
3.5%
트 5
 
2.5%
스 5
 
2.5%
단 4
 
2.0%
지 4
 
2.0%
아 4
 
2.0%
라 4
 
2.0%
Other values (88) 141
71.2%
Decimal Number
ValueCountFrequency (%)
2 6
54.5%
1 5
45.5%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
85.3%
Common 34
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 9
 
4.5%
동 8
 
4.0%
빌 7
 
3.5%
차 7
 
3.5%
트 5
 
2.5%
스 5
 
2.5%
단 4
 
2.0%
지 4
 
2.0%
아 4
 
2.0%
라 4
 
2.0%
Other values (88) 141
71.2%
Common
ValueCountFrequency (%)
) 11
32.4%
( 11
32.4%
2 6
17.6%
1 5
14.7%
1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
85.3%
ASCII 34
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 11
32.4%
( 11
32.4%
2 6
17.6%
1 5
14.7%
1
 
2.9%
Hangul
ValueCountFrequency (%)
대 9
 
4.5%
동 8
 
4.0%
빌 7
 
3.5%
차 7
 
3.5%
트 5
 
2.5%
스 5
 
2.5%
단 4
 
2.0%
지 4
 
2.0%
아 4
 
2.0%
라 4
 
2.0%
Other values (88) 141
71.2%

도로명 주소
Text

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-04-18T03:37:28.809729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length20.46
Min length17

Characters and Unicode

Total characters1023
Distinct characters67
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

Unique48 ?
Unique (%)96.0%

Sample

1st row경상남도 함안군 가야읍 중앙남 3길 6
2nd row경상남도 함안군 가야읍 중앙남 3길 6
3rd row경상남도 함안군 가야읍 고분2길 6
4th row경상남도 함안군 가야읍 중앙남길 50
5th row경상남도 함안군 가야읍 말산1길 20
ValueCountFrequency (%)
경상남도 50
19.8%
함안군 50
19.8%
가야읍 27
 
10.7%
칠원읍 13
 
5.2%
칠서면 4
 
1.6%
6 4
 
1.6%
함마대로 4
 
1.6%
남경길 4
 
1.6%
가야로 3
 
1.2%
군북면 3
 
1.2%
Other values (79) 90
35.7%
2024-04-18T03:37:29.122631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
19.7%
남 60
 
5.9%
경 55
 
5.4%
함 55
 
5.4%
도 53
 
5.2%
군 53
 
5.2%
안 52
 
5.1%
상 50
 
4.9%
읍 40
 
3.9%
길 36
 
3.5%
Other values (57) 367
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 668
65.3%
Space Separator 202
 
19.7%
Decimal Number 145
 
14.2%
Dash Punctuation 8
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 60
 
9.0%
경 55
 
8.2%
함 55
 
8.2%
도 53
 
7.9%
군 53
 
7.9%
안 52
 
7.8%
상 50
 
7.5%
읍 40
 
6.0%
길 36
 
5.4%
가 35
 
5.2%
Other values (45) 179
26.8%
Decimal Number
ValueCountFrequency (%)
1 32
22.1%
2 27
18.6%
5 18
12.4%
6 14
9.7%
8 12
 
8.3%
4 12
 
8.3%
0 11
 
7.6%
3 9
 
6.2%
7 8
 
5.5%
9 2
 
1.4%
Space Separator
ValueCountFrequency (%)
202
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 668
65.3%
Common 355
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 60
 
9.0%
경 55
 
8.2%
함 55
 
8.2%
도 53
 
7.9%
군 53
 
7.9%
안 52
 
7.8%
상 50
 
7.5%
읍 40
 
6.0%
길 36
 
5.4%
가 35
 
5.2%
Other values (45) 179
26.8%
Common
ValueCountFrequency (%)
202
56.9%
1 32
 
9.0%
2 27
 
7.6%
5 18
 
5.1%
6 14
 
3.9%
8 12
 
3.4%
4 12
 
3.4%
0 11
 
3.1%
3 9
 
2.5%
7 8
 
2.3%
Other values (2) 10
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 668
65.3%
ASCII 355
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
56.9%
1 32
 
9.0%
2 27
 
7.6%
5 18
 
5.1%
6 14
 
3.9%
8 12
 
3.4%
4 12
 
3.4%
0 11
 
3.1%
3 9
 
2.5%
7 8
 
2.3%
Other values (2) 10
 
2.8%
Hangul
ValueCountFrequency (%)
남 60
 
9.0%
경 55
 
8.2%
함 55
 
8.2%
도 53
 
7.9%
군 53
 
7.9%
안 52
 
7.8%
상 50
 
7.5%
읍 40
 
6.0%
길 36
 
5.4%
가 35
 
5.2%
Other values (45) 179
26.8%

세대수
Real number (ℝ)

Distinct39
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.78
Minimum16
Maximum1794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-04-18T03:37:29.228956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile18.45
Q142.5
median67.5
Q3173.75
95-th percentile694.5
Maximum1794
Range1778
Interquartile range (IQR)131.25

Descriptive statistics

Standard deviation303.0911
Coefficient of variation (CV)1.5886943
Kurtosis15.793725
Mean190.78
Median Absolute Deviation (MAD)46
Skewness3.5329336
Sum9539
Variance91864.216
MonotonicityNot monotonic
2024-04-18T03:37:29.352438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
50 5
 
10.0%
19 4
 
8.0%
40 2
 
4.0%
60 2
 
4.0%
18 2
 
4.0%
150 2
 
4.0%
726 1
 
2.0%
78 1
 
2.0%
498 1
 
2.0%
55 1
 
2.0%
Other values (29) 29
58.0%
ValueCountFrequency (%)
16 1
 
2.0%
18 2
4.0%
19 4
8.0%
20 1
 
2.0%
30 1
 
2.0%
34 1
 
2.0%
40 2
4.0%
42 1
 
2.0%
44 1
 
2.0%
48 1
 
2.0%
ValueCountFrequency (%)
1794 1
2.0%
837 1
2.0%
726 1
2.0%
656 1
2.0%
498 1
2.0%
450 1
2.0%
431 1
2.0%
415 1
2.0%
364 1
2.0%
355 1
2.0%

사용승인일
Date

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
Minimum1989-06-08 00:00:00
Maximum2014-01-03 00:00:00
2024-04-18T03:37:29.461692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:37:29.570655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

동수(층수)
Text

Distinct32
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-04-18T03:37:29.936634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.94
Min length6

Characters and Unicode

Total characters447
Distinct characters19
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

Unique27 ?
Unique (%)54.0%

Sample

1st row1동(5층)
2nd row1동(5층)
3rd row1동(5층)
4th row1동(5층)
5th row1동(5층)
ValueCountFrequency (%)
1동(지1 13
16.7%
15층 12
15.4%
1동(5층 9
 
11.5%
2동(5층 3
 
3.8%
1동(9층 3
 
3.8%
2동(지1 3
 
3.8%
5층 2
 
2.6%
10 2
 
2.6%
18층 2
 
2.6%
14층 2
 
2.6%
Other values (26) 27
34.6%
2024-04-18T03:37:30.176891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 88
19.7%
동 50
11.2%
( 50
11.2%
층 50
11.2%
) 50
11.2%
5 32
 
7.2%
28
 
6.3%
, 26
 
5.8%
지 25
 
5.6%
2 16
 
3.6%
Other values (9) 32
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 164
36.7%
Other Letter 125
28.0%
Open Punctuation 50
 
11.2%
Close Punctuation 50
 
11.2%
Space Separator 28
 
6.3%
Other Punctuation 28
 
6.3%
Dash Punctuation 2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 88
53.7%
5 32
 
19.5%
2 16
 
9.8%
9 5
 
3.0%
7 5
 
3.0%
0 5
 
3.0%
6 4
 
2.4%
3 4
 
2.4%
8 3
 
1.8%
4 2
 
1.2%
Other Letter
ValueCountFrequency (%)
동 50
40.0%
층 50
40.0%
지 25
20.0%
Other Punctuation
ValueCountFrequency (%)
, 26
92.9%
. 2
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 322
72.0%
Hangul 125
 
28.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 88
27.3%
( 50
15.5%
) 50
15.5%
5 32
 
9.9%
28
 
8.7%
, 26
 
8.1%
2 16
 
5.0%
9 5
 
1.6%
7 5
 
1.6%
0 5
 
1.6%
Other values (6) 17
 
5.3%
Hangul
ValueCountFrequency (%)
동 50
40.0%
층 50
40.0%
지 25
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 322
72.0%
Hangul 125
 
28.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 88
27.3%
( 50
15.5%
) 50
15.5%
5 32
 
9.9%
28
 
8.7%
, 26
 
8.1%
2 16
 
5.0%
9 5
 
1.6%
7 5
 
1.6%
0 5
 
1.6%
Other values (6) 17
 
5.3%
Hangul
ValueCountFrequency (%)
동 50
40.0%
층 50
40.0%
지 25
20.0%

비고
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing44
Missing (%)88.0%
Memory size532.0 B
2024-04-18T03:37:30.300477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.5
Min length4

Characters and Unicode

Total characters27
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row주상복합
2nd row국민임대
3rd row도시형생활주택
4th row공공임대
5th row국민임대
ValueCountFrequency (%)
국민임대 2
33.3%
공공임대 2
33.3%
주상복합 1
16.7%
도시형생활주택 1
16.7%
2024-04-18T03:37:30.545522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
임 4
14.8%
대 4
14.8%
공 4
14.8%
국 2
 
7.4%
민 2
 
7.4%
주 2
 
7.4%
상 1
 
3.7%
복 1
 
3.7%
합 1
 
3.7%
도 1
 
3.7%
Other values (5) 5
18.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 4
14.8%
대 4
14.8%
공 4
14.8%
국 2
 
7.4%
민 2
 
7.4%
주 2
 
7.4%
상 1
 
3.7%
복 1
 
3.7%
합 1
 
3.7%
도 1
 
3.7%
Other values (5) 5
18.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 4
14.8%
대 4
14.8%
공 4
14.8%
국 2
 
7.4%
민 2
 
7.4%
주 2
 
7.4%
상 1
 
3.7%
복 1
 
3.7%
합 1
 
3.7%
도 1
 
3.7%
Other values (5) 5
18.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
임 4
14.8%
대 4
14.8%
공 4
14.8%
국 2
 
7.4%
민 2
 
7.4%
주 2
 
7.4%
상 1
 
3.7%
복 1
 
3.7%
합 1
 
3.7%
도 1
 
3.7%
Other values (5) 5
18.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2018-10-17
50 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018-10-17
2nd row2018-10-17
3rd row2018-10-17
4th row2018-10-17
5th row2018-10-17

Common Values

ValueCountFrequency (%)
2018-10-17 50
100.0%

Length

2024-04-18T03:37:30.639001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:37:30.707531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-10-17 50
100.0%

Interactions

2024-04-18T03:37:27.828049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-18T03:37:30.751730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면아파트 단지명도로명 주소세대수사용승인일동수(층수)비고
읍면1.0000.5631.0000.2991.0000.0000.000
아파트 단지명0.5631.0000.9961.0000.9960.9981.000
도로명 주소1.0000.9961.0001.0000.9961.0001.000
세대수0.2991.0001.0001.0000.0001.0000.000
사용승인일1.0000.9960.9960.0001.0000.9271.000
동수(층수)0.0000.9981.0001.0000.9271.0001.000
비고0.0001.0001.0000.0001.0001.0001.000
2024-04-18T03:37:30.830249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수읍면
세대수1.0000.102
읍면0.1021.000

Missing values

2024-04-18T03:37:27.918403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T03:37:28.014798image/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

읍면아파트 단지명도로명 주소세대수사용승인일동수(층수)비고데이터기준일자
0가야읍대송(1차)경상남도 함안군 가야읍 중앙남 3길 6501990-01-121동(5층)<NA>2018-10-17
1가야읍대송(2차)경상남도 함안군 가야읍 중앙남 3길 6501990-11-301동(5층)<NA>2018-10-17
2가야읍대한경상남도 함안군 가야읍 고분2길 6341989-06-081동(5층)<NA>2018-10-17
3가야읍동명경상남도 함안군 가야읍 중앙남길 50401990-01-201동(5층)<NA>2018-10-17
4가야읍무학경상남도 함안군 가야읍 말산1길 20501990-07-251동(5층)<NA>2018-10-17
5가야읍금강그린경상남도 함안군 가야읍 중앙본길 18601990-08-132동(5층)<NA>2018-10-17
6가야읍천일아라(1차)경상남도 함안군 가야읍 가야20길 24601990-12-312동(5층)<NA>2018-10-17
7가야읍천일아라(2차)경상남도 함안군 가야20길 24401991-10-211동(5층)<NA>2018-10-17
8가야읍동신(1차)경상남도 함안군 가야읍 도항2길 651731991-12-301동(지1, 15층)<NA>2018-10-17
9가야읍동신(2차)경상남도 함안군 가야읍 가도항 2길 552851992-04-182동(지1, 10, 15층)<NA>2018-10-17
읍면아파트 단지명도로명 주소세대수사용승인일동수(층수)비고데이터기준일자
40칠원읍호암아트빌경상남도 함안군 칠원읍 호암길 22192014-01-031동(지2, 7층)<NA>2018-10-17
41군북면문화스타경상남도 함안군 군북면 함마대로 755-1421991-07-221동(지1, 5층)<NA>2018-10-17
42군북면무학경상남도 함안군 군북면 중앙4길 47-1531997-03-291동(지1, 15층)<NA>2018-10-17
43군북면봉국한마음경상남도 함안군 군북면 함마대로 885502013-11-292동(5층)공공임대2018-10-17
44법수면서정에이스경상남도 함안군 법수면 윤외리 168482011-02-111동(9층)<NA>2018-10-17
45대산면삼진경상남도 함안군 대산면 대산중앙3길 88512001-10-161동(6층)<NA>2018-10-17
46칠서면기공경상남도 함안군 칠서면 함의로 71071997-08-021동(15층)<NA>2018-10-17
47칠서면에이스(1단지)경상남도 함안군 칠서면 칠평로 648372001-04-167동(지2, 15층)<NA>2018-10-17
48칠서면에이스(2단지)경상남도 함안군 칠서면 칠평로 624152001-04-165동(지1, 15층)<NA>2018-10-17
49칠서면진명리브빌경상남도 함안군 칠서면 계내리2길 26182011-02-171동(5층)<NA>2018-10-17