Overview

Dataset statistics

Number of variables4
Number of observations205
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory33.6 B

Variable types

Categorical1
Text2
Numeric1

Dataset

Description경상남도 양산시 읍면동별 공동주택 아파트 현황을 확인할 수 있스니다. 행정동, 아파트 단지명, 도로명 주소, 세대수를 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3065860

Alerts

도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-04-19 07:02:26.203569
Analysis finished2024-04-19 07:02:26.646595
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct12
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
물금읍
53 
서창동
21 
평산동
21 
동면
17 
중앙동
16 
Other values (7)
77 

Length

Max length3
Median length3
Mean length2.9170732
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물금읍 53
25.9%
서창동 21
 
10.2%
평산동 21
 
10.2%
동면 17
 
8.3%
중앙동 16
 
7.8%
상북면 15
 
7.3%
삼성동 12
 
5.9%
소주동 11
 
5.4%
양주동 11
 
5.4%
하북면 10
 
4.9%
Other values (2) 18
 
8.8%

Length

2024-04-19T16:02:26.722397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
물금읍 53
25.9%
서창동 21
 
10.2%
평산동 21
 
10.2%
동면 17
 
8.3%
중앙동 16
 
7.8%
상북면 15
 
7.3%
삼성동 12
 
5.9%
소주동 11
 
5.4%
양주동 11
 
5.4%
하북면 10
 
4.9%
Other values (2) 18
 
8.8%

단지명
Text

Distinct203
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T16:02:26.994634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length5.9707317
Min length2

Characters and Unicode

Total characters1224
Distinct characters225
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

Unique201 ?
Unique (%)98.0%

Sample

1st row덕성연립
2nd row창조
3rd row협성강변
4th row성신
5th row삼성파크빌(임대)
ValueCountFrequency (%)
동원 3
 
1.3%
일동미라주 2
 
0.8%
반도유보라 2
 
0.8%
삼한 2
 
0.8%
부영임대 2
 
0.8%
로얄듀크비스타 2
 
0.8%
휴먼시아 2
 
0.8%
남양산 2
 
0.8%
e편한세상 2
 
0.8%
우성스마트시티뷰 2
 
0.8%
Other values (217) 218
91.2%
2024-04-19T16:02:27.431337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
차 72
 
5.9%
대 35
 
2.9%
34
 
2.8%
산 33
 
2.7%
양 31
 
2.5%
동 30
 
2.5%
2 27
 
2.2%
1 23
 
1.9%
우 23
 
1.9%
신 23
 
1.9%
Other values (215) 893
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1065
87.0%
Decimal Number 85
 
6.9%
Space Separator 34
 
2.8%
Close Punctuation 11
 
0.9%
Open Punctuation 11
 
0.9%
Uppercase Letter 11
 
0.9%
Lowercase Letter 6
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 72
 
6.8%
대 35
 
3.3%
산 33
 
3.1%
양 31
 
2.9%
동 30
 
2.8%
우 23
 
2.2%
신 23
 
2.2%
스 21
 
2.0%
시 20
 
1.9%
지 20
 
1.9%
Other values (194) 757
71.1%
Decimal Number
ValueCountFrequency (%)
2 27
31.8%
1 23
27.1%
3 13
15.3%
5 7
 
8.2%
4 5
 
5.9%
6 4
 
4.7%
7 3
 
3.5%
8 3
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
H 3
27.3%
L 3
27.3%
C 2
18.2%
K 1
 
9.1%
G 1
 
9.1%
E 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
e 4
66.7%
h 1
 
16.7%
t 1
 
16.7%
Space Separator
ValueCountFrequency (%)
34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1065
87.0%
Common 142
 
11.6%
Latin 17
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 72
 
6.8%
대 35
 
3.3%
산 33
 
3.1%
양 31
 
2.9%
동 30
 
2.8%
우 23
 
2.2%
신 23
 
2.2%
스 21
 
2.0%
시 20
 
1.9%
지 20
 
1.9%
Other values (194) 757
71.1%
Common
ValueCountFrequency (%)
34
23.9%
2 27
19.0%
1 23
16.2%
3 13
 
9.2%
) 11
 
7.7%
( 11
 
7.7%
5 7
 
4.9%
4 5
 
3.5%
6 4
 
2.8%
7 3
 
2.1%
Other values (2) 4
 
2.8%
Latin
ValueCountFrequency (%)
e 4
23.5%
H 3
17.6%
L 3
17.6%
C 2
11.8%
K 1
 
5.9%
h 1
 
5.9%
t 1
 
5.9%
G 1
 
5.9%
E 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1065
87.0%
ASCII 159
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
차 72
 
6.8%
대 35
 
3.3%
산 33
 
3.1%
양 31
 
2.9%
동 30
 
2.8%
우 23
 
2.2%
신 23
 
2.2%
스 21
 
2.0%
시 20
 
1.9%
지 20
 
1.9%
Other values (194) 757
71.1%
ASCII
ValueCountFrequency (%)
34
21.4%
2 27
17.0%
1 23
14.5%
3 13
 
8.2%
) 11
 
6.9%
( 11
 
6.9%
5 7
 
4.4%
4 5
 
3.1%
6 4
 
2.5%
e 4
 
2.5%
Other values (11) 20
12.6%

도로명주소
Text

UNIQUE 

Distinct205
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T16:02:27.777114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.039024
Min length15

Characters and Unicode

Total characters3698
Distinct characters110
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

Unique205 ?
Unique (%)100.0%

Sample

1st row경상남도 양산시 회현1길 15-3
2nd row경상남도 양산시 회현1길 6
3rd row경상남도 양산시 회현1길 3
4th row경상남도 양산시 두전길 42-3
5th row경상남도 양산시 두전길 42
ValueCountFrequency (%)
경상남도 205
22.6%
양산시 205
22.6%
물금읍 53
 
5.8%
동면 17
 
1.9%
상북면 15
 
1.7%
양주로 11
 
1.2%
하북면 10
 
1.1%
오봉로 7
 
0.8%
14 7
 
0.8%
야리로 6
 
0.7%
Other values (235) 371
40.9%
2024-04-19T16:02:28.209840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
735
19.9%
산 231
 
6.2%
상 224
 
6.1%
양 218
 
5.9%
남 213
 
5.8%
도 207
 
5.6%
경 205
 
5.5%
시 205
 
5.5%
1 146
 
3.9%
로 115
 
3.1%
Other values (100) 1199
32.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2401
64.9%
Space Separator 735
 
19.9%
Decimal Number 547
 
14.8%
Dash Punctuation 13
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 231
 
9.6%
상 224
 
9.3%
양 218
 
9.1%
남 213
 
8.9%
도 207
 
8.6%
경 205
 
8.5%
시 205
 
8.5%
로 115
 
4.8%
길 90
 
3.7%
금 71
 
3.0%
Other values (87) 622
25.9%
Decimal Number
ValueCountFrequency (%)
1 146
26.7%
3 63
11.5%
5 58
 
10.6%
2 55
 
10.1%
4 47
 
8.6%
7 45
 
8.2%
6 42
 
7.7%
9 32
 
5.9%
0 31
 
5.7%
8 28
 
5.1%
Space Separator
ValueCountFrequency (%)
735
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2401
64.9%
Common 1297
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 231
 
9.6%
상 224
 
9.3%
양 218
 
9.1%
남 213
 
8.9%
도 207
 
8.6%
경 205
 
8.5%
시 205
 
8.5%
로 115
 
4.8%
길 90
 
3.7%
금 71
 
3.0%
Other values (87) 622
25.9%
Common
ValueCountFrequency (%)
735
56.7%
1 146
 
11.3%
3 63
 
4.9%
5 58
 
4.5%
2 55
 
4.2%
4 47
 
3.6%
7 45
 
3.5%
6 42
 
3.2%
9 32
 
2.5%
0 31
 
2.4%
Other values (3) 43
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2401
64.9%
ASCII 1297
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
735
56.7%
1 146
 
11.3%
3 63
 
4.9%
5 58
 
4.5%
2 55
 
4.2%
4 47
 
3.6%
7 45
 
3.5%
6 42
 
3.2%
9 32
 
2.5%
0 31
 
2.4%
Other values (3) 43
 
3.3%
Hangul
ValueCountFrequency (%)
산 231
 
9.6%
상 224
 
9.3%
양 218
 
9.1%
남 213
 
8.9%
도 207
 
8.6%
경 205
 
8.5%
시 205
 
8.5%
로 115
 
4.8%
길 90
 
3.7%
금 71
 
3.0%
Other values (87) 622
25.9%

세대
Real number (ℝ)

Distinct170
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean539.77073
Minimum20
Maximum3000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T16:02:28.346111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile42.4
Q1148
median483
Q3796
95-th percentile1285.6
Maximum3000
Range2980
Interquartile range (IQR)648

Descriptive statistics

Standard deviation462.68761
Coefficient of variation (CV)0.85719285
Kurtosis4.2201962
Mean539.77073
Median Absolute Deviation (MAD)333
Skewness1.5395275
Sum110653
Variance214079.82
MonotonicityNot monotonic
2024-04-19T16:02:28.474625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 4
 
2.0%
72 3
 
1.5%
499 3
 
1.5%
160 3
 
1.5%
84 3
 
1.5%
420 3
 
1.5%
998 3
 
1.5%
700 2
 
1.0%
80 2
 
1.0%
30 2
 
1.0%
Other values (160) 177
86.3%
ValueCountFrequency (%)
20 1
 
0.5%
21 1
 
0.5%
29 1
 
0.5%
30 2
1.0%
34 1
 
0.5%
40 4
2.0%
42 1
 
0.5%
44 1
 
0.5%
48 2
1.0%
49 2
1.0%
ValueCountFrequency (%)
3000 1
0.5%
2280 1
0.5%
2130 1
0.5%
1768 1
0.5%
1724 1
0.5%
1663 1
0.5%
1414 1
0.5%
1385 1
0.5%
1337 1
0.5%
1300 1
0.5%

Interactions

2024-04-19T16:02:26.411969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T16:02:28.555053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동세대
행정동1.0000.479
세대0.4791.000
2024-04-19T16:02:28.640096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대행정동
세대1.0000.222
행정동0.2221.000

Missing values

2024-04-19T16:02:26.520998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T16:02:26.604908image/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

행정동단지명도로명주소세대
0강서동덕성연립경상남도 양산시 회현1길 15-372
1강서동창조경상남도 양산시 회현1길 6150
2강서동협성강변경상남도 양산시 회현1길 3390
3강서동성신경상남도 양산시 두전길 42-3473
4강서동삼성파크빌(임대)경상남도 양산시 두전길 42625
5강서동로얄파크빌경상남도 양산시 두전길 18445
6강서동일동미라주경상남도 양산시 회현1길 48925
7강서동월드메르디앙1단지경상남도 양산시 교동1길 65164
8강서동월드메르디앙2단지경상남도 양산시 교동1길 74124
9덕계동경보1차경상남도 양산시 덕계회야길 7227
행정동단지명도로명주소세대
195하북면옥수경상남도 양산시 하북면 진목1길 3040
196하북면삼보1차경상남도 양산시 하북면 신평3길 1130
197하북면대영1차경상남도 양산시 하북면 지곡1길 895
198하북면삼보2차경상남도 양산시 하북면 신평로 11-142
199하북면초원1차경상남도 양산시 하북면 지산로 1750
200하북면초원2차경상남도 양산시 하북면 신평5길 680
201하북면대영파크2차경상남도 양산시 하북면 지산로 27-7105
202하북면초원3차경상남도 양산시 하북면 지산로 2960
203하북면진흥목화경상남도 양산시 하북면 용연로 59165
204하북면협진경상남도 양산시 하북면 통도사로 5197