Overview

Dataset statistics

Number of variables4
Number of observations216
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 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 07:02:29.406218
Analysis finished2024-04-19 07:02:29.819784
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct12
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
물금읍
57 
동면
21 
서창동
21 
평산동
21 
중앙동
16 
Other values (7)
80 

Length

Max length3
Median length3
Mean length2.9027778
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
물금읍 57
26.4%
동면 21
 
9.7%
서창동 21
 
9.7%
평산동 21
 
9.7%
중앙동 16
 
7.4%
상북면 15
 
6.9%
삼성동 12
 
5.6%
소주동 12
 
5.6%
덕계동 11
 
5.1%
양주동 11
 
5.1%
Other values (2) 19
 
8.8%

Length

2024-04-19T16:02:29.880938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
물금읍 57
26.4%
동면 21
 
9.7%
서창동 21
 
9.7%
평산동 21
 
9.7%
중앙동 16
 
7.4%
상북면 15
 
6.9%
삼성동 12
 
5.6%
소주동 12
 
5.6%
덕계동 11
 
5.1%
양주동 11
 
5.1%
Other values (2) 19
 
8.8%

단지명
Text

Distinct214
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-19T16:02:30.110411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.1481481
Min length2

Characters and Unicode

Total characters1328
Distinct characters230
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

Unique212 ?
Unique (%)98.1%

Sample

1st row덕성연립
2nd row창조
3rd row협성강변
4th row성신
5th row삼성파크빌(임대)
ValueCountFrequency (%)
동원 3
 
1.2%
일동미라주 2
 
0.8%
사랑채 2
 
0.8%
로얄듀크비스타 2
 
0.8%
남양산 2
 
0.8%
e편한세상 2
 
0.8%
2단지 2
 
0.8%
1단지 2
 
0.8%
두산위브2차 2
 
0.8%
휴먼시아 2
 
0.8%
Other values (227) 231
91.7%
2024-04-19T16:02:30.497006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
차 77
 
5.8%
36
 
2.7%
대 35
 
2.6%
산 35
 
2.6%
양 32
 
2.4%
동 30
 
2.3%
2 30
 
2.3%
1 29
 
2.2%
지 26
 
2.0%
우 24
 
1.8%
Other values (220) 974
73.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1144
86.1%
Decimal Number 96
 
7.2%
Space Separator 36
 
2.7%
Open Punctuation 16
 
1.2%
Close Punctuation 16
 
1.2%
Uppercase Letter 13
 
1.0%
Lowercase Letter 6
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 77
 
6.7%
대 35
 
3.1%
산 35
 
3.1%
양 32
 
2.8%
동 30
 
2.6%
지 26
 
2.3%
우 24
 
2.1%
신 24
 
2.1%
스 23
 
2.0%
시 23
 
2.0%
Other values (199) 815
71.2%
Decimal Number
ValueCountFrequency (%)
2 30
31.2%
1 29
30.2%
3 14
14.6%
5 7
 
7.3%
4 6
 
6.2%
6 4
 
4.2%
8 3
 
3.1%
7 3
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
H 4
30.8%
L 4
30.8%
C 2
15.4%
K 1
 
7.7%
G 1
 
7.7%
E 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
66.7%
h 1
 
16.7%
t 1
 
16.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1144
86.1%
Common 165
 
12.4%
Latin 19
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 77
 
6.7%
대 35
 
3.1%
산 35
 
3.1%
양 32
 
2.8%
동 30
 
2.6%
지 26
 
2.3%
우 24
 
2.1%
신 24
 
2.1%
스 23
 
2.0%
시 23
 
2.0%
Other values (199) 815
71.2%
Common
ValueCountFrequency (%)
36
21.8%
2 30
18.2%
1 29
17.6%
( 16
9.7%
) 16
9.7%
3 14
 
8.5%
5 7
 
4.2%
4 6
 
3.6%
6 4
 
2.4%
8 3
 
1.8%
Other values (2) 4
 
2.4%
Latin
ValueCountFrequency (%)
H 4
21.1%
L 4
21.1%
e 4
21.1%
C 2
10.5%
K 1
 
5.3%
h 1
 
5.3%
t 1
 
5.3%
G 1
 
5.3%
E 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1144
86.1%
ASCII 184
 
13.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
차 77
 
6.7%
대 35
 
3.1%
산 35
 
3.1%
양 32
 
2.8%
동 30
 
2.6%
지 26
 
2.3%
우 24
 
2.1%
신 24
 
2.1%
스 23
 
2.0%
시 23
 
2.0%
Other values (199) 815
71.2%
ASCII
ValueCountFrequency (%)
36
19.6%
2 30
16.3%
1 29
15.8%
( 16
8.7%
) 16
8.7%
3 14
 
7.6%
5 7
 
3.8%
4 6
 
3.3%
H 4
 
2.2%
L 4
 
2.2%
Other values (11) 22
12.0%

도로명주소
Text

UNIQUE 

Distinct216
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-04-19T16:02:30.818459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length18.060185
Min length15

Characters and Unicode

Total characters3901
Distinct characters114
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

Unique216 ?
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 216
22.6%
양산시 216
22.6%
물금읍 55
 
5.7%
동면 21
 
2.2%
상북면 15
 
1.6%
양주로 11
 
1.1%
하북면 10
 
1.0%
오봉로 7
 
0.7%
14 7
 
0.7%
야리로 6
 
0.6%
Other values (243) 393
41.1%
2024-04-19T16:02:31.256427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
774
19.8%
산 244
 
6.3%
상 235
 
6.0%
양 229
 
5.9%
남 224
 
5.7%
도 218
 
5.6%
경 216
 
5.5%
시 216
 
5.5%
1 153
 
3.9%
로 123
 
3.2%
Other values (104) 1269
32.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2536
65.0%
Space Separator 774
 
19.8%
Decimal Number 576
 
14.8%
Dash Punctuation 13
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 244
 
9.6%
상 235
 
9.3%
양 229
 
9.0%
남 224
 
8.8%
도 218
 
8.6%
경 216
 
8.5%
시 216
 
8.5%
로 123
 
4.9%
길 93
 
3.7%
금 73
 
2.9%
Other values (91) 665
26.2%
Decimal Number
ValueCountFrequency (%)
1 153
26.6%
3 66
11.5%
5 60
 
10.4%
2 55
 
9.5%
4 50
 
8.7%
7 49
 
8.5%
6 43
 
7.5%
9 37
 
6.4%
0 33
 
5.7%
8 30
 
5.2%
Space Separator
ValueCountFrequency (%)
774
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2536
65.0%
Common 1365
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 244
 
9.6%
상 235
 
9.3%
양 229
 
9.0%
남 224
 
8.8%
도 218
 
8.6%
경 216
 
8.5%
시 216
 
8.5%
로 123
 
4.9%
길 93
 
3.7%
금 73
 
2.9%
Other values (91) 665
26.2%
Common
ValueCountFrequency (%)
774
56.7%
1 153
 
11.2%
3 66
 
4.8%
5 60
 
4.4%
2 55
 
4.0%
4 50
 
3.7%
7 49
 
3.6%
6 43
 
3.2%
9 37
 
2.7%
0 33
 
2.4%
Other values (3) 45
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2536
65.0%
ASCII 1365
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
774
56.7%
1 153
 
11.2%
3 66
 
4.8%
5 60
 
4.4%
2 55
 
4.0%
4 50
 
3.7%
7 49
 
3.6%
6 43
 
3.2%
9 37
 
2.7%
0 33
 
2.4%
Other values (3) 45
 
3.3%
Hangul
ValueCountFrequency (%)
산 244
 
9.6%
상 235
 
9.3%
양 229
 
9.0%
남 224
 
8.8%
도 218
 
8.6%
경 216
 
8.5%
시 216
 
8.5%
로 123
 
4.9%
길 93
 
3.7%
금 73
 
2.9%
Other values (91) 665
26.2%

세대
Real number (ℝ)

Distinct179
Distinct (%)82.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538.02315
Minimum20
Maximum3000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-04-19T16:02:31.399251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile43.5
Q1150
median479.5
Q3791.5
95-th percentile1268
Maximum3000
Range2980
Interquartile range (IQR)641.5

Descriptive statistics

Standard deviation455.18565
Coefficient of variation (CV)0.84603358
Kurtosis4.3449795
Mean538.02315
Median Absolute Deviation (MAD)320.5
Skewness1.5448273
Sum116213
Variance207193.98
MonotonicityNot monotonic
2024-04-19T16:02:31.526073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40 4
 
1.9%
72 3
 
1.4%
420 3
 
1.4%
998 3
 
1.4%
160 3
 
1.4%
499 3
 
1.4%
84 3
 
1.4%
483 2
 
0.9%
324 2
 
0.9%
648 2
 
0.9%
Other values (169) 188
87.0%
ValueCountFrequency (%)
20 1
 
0.5%
21 1
 
0.5%
29 1
 
0.5%
30 2
0.9%
34 1
 
0.5%
40 4
1.9%
42 1
 
0.5%
44 1
 
0.5%
48 2
0.9%
49 2
0.9%
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

2024-04-19T16:02:29.608903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T16:02:31.618931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동세대
행정동1.0000.469
세대0.4691.000
2024-04-19T16:02:31.705797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대행정동
세대1.0000.216
행정동0.2161.000

Missing values

2024-04-19T16:02:29.715391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T16:02:29.789751image/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
206하북면옥수경상남도 양산시 하북면 진목1길 3040
207하북면삼보1차경상남도 양산시 하북면 신평3길 1130
208하북면대영1차경상남도 양산시 하북면 지곡1길 895
209하북면삼보2차경상남도 양산시 하북면 신평로 11-142
210하북면초원1차경상남도 양산시 하북면 지산로 1750
211하북면초원2차경상남도 양산시 하북면 신평5길 680
212하북면대영파크2차경상남도 양산시 하북면 지산로 27-7105
213하북면초원3차경상남도 양산시 하북면 지산로 2960
214하북면진흥목화경상남도 양산시 하북면 용연로 59165
215하북면협진경상남도 양산시 하북면 통도사로 5197