Overview

Dataset statistics

Number of variables6
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory50.7 B

Variable types

Text1
Categorical4
Numeric1

Dataset

Description의무관리공동주택의 주택명, 소재지, 담당부서 등 정보 제공
Author제주특별자치도
URLhttps://www.data.go.kr/data/15056453/fileData.do

Alerts

담당부서 has constant value ""Constant
연락처 has constant value ""Constant
데이터기준일자 has constant value ""Constant
아파트명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:12:19.900683
Analysis finished2023-12-12 15:12:20.550270
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-13T00:12:20.793470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length6.7051282
Min length2

Characters and Unicode

Total characters523
Distinct characters131
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

Unique78 ?
Unique (%)100.0%

Sample

1st row신천지1
2nd row대유대림
3rd row일도우성1단지
4th row혜성대유
5th row삼주
ValueCountFrequency (%)
신천지1 1
 
1.2%
부영2차 1
 
1.2%
연동한일시티파크 1
 
1.2%
제원 1
 
1.2%
연동대림1차 1
 
1.2%
제주삼화lh3단지 1
 
1.2%
삼화1차부영 1
 
1.2%
제주삼화6차부영 1
 
1.2%
미듬하나로 1
 
1.2%
함덕광명샤인빌 1
 
1.2%
Other values (71) 71
87.7%
2023-12-13T00:12:21.319565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 29
 
5.5%
아 26
 
5.0%
제 19
 
3.6%
차 18
 
3.4%
1 15
 
2.9%
지 15
 
2.9%
파 15
 
2.9%
동 14
 
2.7%
화 14
 
2.7%
단 13
 
2.5%
Other values (121) 345
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 460
88.0%
Decimal Number 42
 
8.0%
Uppercase Letter 8
 
1.5%
Lowercase Letter 7
 
1.3%
Space Separator 3
 
0.6%
Dash Punctuation 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 29
 
6.3%
아 26
 
5.7%
제 19
 
4.1%
차 18
 
3.9%
지 15
 
3.3%
파 15
 
3.3%
동 14
 
3.0%
화 14
 
3.0%
단 13
 
2.8%
삼 12
 
2.6%
Other values (103) 285
62.0%
Decimal Number
ValueCountFrequency (%)
1 15
35.7%
2 12
28.6%
3 7
16.7%
5 3
 
7.1%
6 2
 
4.8%
4 2
 
4.8%
7 1
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
57.1%
d 1
 
14.3%
s 1
 
14.3%
u 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 3
37.5%
H 3
37.5%
G 1
 
12.5%
S 1
 
12.5%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 460
88.0%
Common 48
 
9.2%
Latin 15
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 29
 
6.3%
아 26
 
5.7%
제 19
 
4.1%
차 18
 
3.9%
지 15
 
3.3%
파 15
 
3.3%
동 14
 
3.0%
화 14
 
3.0%
단 13
 
2.8%
삼 12
 
2.6%
Other values (103) 285
62.0%
Common
ValueCountFrequency (%)
1 15
31.2%
2 12
25.0%
3 7
14.6%
5 3
 
6.2%
3
 
6.2%
6 2
 
4.2%
- 2
 
4.2%
4 2
 
4.2%
. 1
 
2.1%
7 1
 
2.1%
Latin
ValueCountFrequency (%)
e 4
26.7%
L 3
20.0%
H 3
20.0%
d 1
 
6.7%
G 1
 
6.7%
s 1
 
6.7%
S 1
 
6.7%
u 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 460
88.0%
ASCII 63
 
12.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 29
 
6.3%
아 26
 
5.7%
제 19
 
4.1%
차 18
 
3.9%
지 15
 
3.3%
파 15
 
3.3%
동 14
 
3.0%
화 14
 
3.0%
단 13
 
2.8%
삼 12
 
2.6%
Other values (103) 285
62.0%
ASCII
ValueCountFrequency (%)
1 15
23.8%
2 12
19.0%
3 7
11.1%
e 4
 
6.3%
L 3
 
4.8%
H 3
 
4.8%
5 3
 
4.8%
3
 
4.8%
6 2
 
3.2%
- 2
 
3.2%
Other values (8) 9
14.3%

읍면동
Categorical

Distinct24
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
노형동
16 
동홍동
10 
일도이동
6 
아라일동
5 
화북일동
5 
Other values (19)
36 

Length

Max length8
Median length7
Mean length3.7820513
Min length2

Unique

Unique9 ?
Unique (%)11.5%

Sample

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

Common Values

ValueCountFrequency (%)
노형동 16
20.5%
동홍동 10
12.8%
일도이동 6
 
7.7%
아라일동 5
 
6.4%
화북일동 5
 
6.4%
연동 4
 
5.1%
도련일동 4
 
5.1%
이도이동 4
 
5.1%
외도일동 3
 
3.8%
도남동 2
 
2.6%
Other values (14) 19
24.4%

Length

2023-12-13T00:12:21.773128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
노형동 16
18.8%
동홍동 10
 
11.8%
일도이동 6
 
7.1%
아라일동 5
 
5.9%
화북일동 5
 
5.9%
연동 4
 
4.7%
도련일동 4
 
4.7%
이도이동 4
 
4.7%
외도일동 3
 
3.5%
대정읍 3
 
3.5%
Other values (18) 25
29.4%

세대수
Real number (ℝ)

Distinct73
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean441.79487
Minimum155
Maximum1364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-13T00:12:21.900441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum155
5-th percentile173.4
Q1254.75
median396
Q3571.5
95-th percentile856.3
Maximum1364
Range1209
Interquartile range (IQR)316.75

Descriptive statistics

Standard deviation233.86067
Coefficient of variation (CV)0.52934221
Kurtosis2.5174301
Mean441.79487
Median Absolute Deviation (MAD)149.5
Skewness1.3654945
Sum34460
Variance54690.815
MonotonicityNot monotonic
2023-12-13T00:12:22.054849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400 2
 
2.6%
360 2
 
2.6%
350 2
 
2.6%
420 2
 
2.6%
448 2
 
2.6%
468 1
 
1.3%
160 1
 
1.3%
630 1
 
1.3%
440 1
 
1.3%
850 1
 
1.3%
Other values (63) 63
80.8%
ValueCountFrequency (%)
155 1
1.3%
160 1
1.3%
168 1
1.3%
170 1
1.3%
174 1
1.3%
180 1
1.3%
181 1
1.3%
185 1
1.3%
192 1
1.3%
193 1
1.3%
ValueCountFrequency (%)
1364 1
1.3%
1068 1
1.3%
1012 1
1.3%
892 1
1.3%
850 1
1.3%
830 1
1.3%
810 1
1.3%
760 1
1.3%
711 1
1.3%
710 1
1.3%

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
디자인건축지적과
78 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
디자인건축지적과 78
100.0%

Length

2023-12-13T00:12:22.203695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:22.304312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
디자인건축지적과 78
100.0%

연락처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
064-710-2691
78 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row064-710-2691
2nd row064-710-2691
3rd row064-710-2691
4th row064-710-2691
5th row064-710-2691

Common Values

ValueCountFrequency (%)
064-710-2691 78
100.0%

Length

2023-12-13T00:12:22.405328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:22.493033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
064-710-2691 78
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2016-05-30
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2016-05-30
2nd row2016-05-30
3rd row2016-05-30
4th row2016-05-30
5th row2016-05-30

Common Values

ValueCountFrequency (%)
2016-05-30 78
100.0%

Length

2023-12-13T00:12:22.595522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:22.701959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016-05-30 78
100.0%

Interactions

2023-12-13T00:12:20.118186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:12:22.767903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아파트명읍면동세대수
아파트명1.0001.0001.000
읍면동1.0001.0000.000
세대수1.0000.0001.000
2023-12-13T00:12:22.862375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수읍면동
세대수1.0000.000
읍면동0.0001.000

Missing values

2023-12-13T00:12:20.358245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:12:20.503983image/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

아파트명읍면동세대수담당부서연락처데이터기준일자
0신천지1일도이동468디자인건축지적과064-710-26912016-05-30
1대유대림일도이동600디자인건축지적과064-710-26912016-05-30
2일도우성1단지일도이동360디자인건축지적과064-710-26912016-05-30
3혜성대유일도이동204디자인건축지적과064-710-26912016-05-30
4삼주일도이동180디자인건축지적과064-710-26912016-05-30
5신천지2차일도이동228디자인건축지적과064-710-26912016-05-30
6장원월드컵아파트이도일동181디자인건축지적과064-710-26912016-05-30
7이도주공2단지3단지이도이동760디자인건축지적과064-710-26912016-05-30
8이도주공1이도이동490디자인건축지적과064-710-26912016-05-30
9영산홍주택이도이동312디자인건축지적과064-710-26912016-05-30
아파트명읍면동세대수담당부서연락처데이터기준일자
68서귀포동홍6동홍동602디자인건축지적과064-710-26912016-05-30
69서귀포 동홍2아파트동홍동300디자인건축지적과064-710-26912016-05-30
70동홍주공1단지동홍동310디자인건축지적과064-710-26912016-05-30
71동홍동대림동홍동192디자인건축지적과064-710-26912016-05-30
72동홍주공4단지동홍동320디자인건축지적과064-710-26912016-05-30
73중문푸른마을중문동460디자인건축지적과064-710-26912016-05-30
74강정상록아파트강정동400디자인건축지적과064-710-26912016-05-30
75서귀포대정휴먼시아대정읍 하모리327디자인건축지적과064-710-26912016-05-30
76제주라온프라이빗에듀대정읍 보성리420디자인건축지적과064-710-26912016-05-30
77삼정G.edu대정읍 보성리701디자인건축지적과064-710-26912016-05-30