Overview

Dataset statistics

Number of variables16
Number of observations45
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory135.9 B

Variable types

Categorical4
Text6
Numeric4
DateTime2

Dataset

Description부산광역시_동래구_공개공지현황_20221017
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15039195

Alerts

구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
공개공지면적 is highly overall correlated with 연면적High correlation
연면적 is highly overall correlated with 공개공지면적High correlation
공개공지편의시설 has 1 (2.2%) missing valuesMissing
건축물명 has unique valuesUnique
공개공지면적 has unique valuesUnique
연면적 has unique valuesUnique
허가일자 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:50:49.214846
Analysis finished2023-12-10 16:50:53.377699
Duration4.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
동래구
45 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동래구 45
100.0%

Length

2023-12-11T01:50:53.461947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:50:53.611377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동래구 45
100.0%

건축물명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-11T01:50:53.874872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.3777778
Min length4

Characters and Unicode

Total characters332
Distinct characters146
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row허브센티움3
2nd row온천동 퀸즈w
3rd row케이에이치 마이우스
4th row대신증권
5th row사직 유로빌
ValueCountFrequency (%)
온천동 5
 
7.4%
더 2
 
2.9%
온천삼정그린코아 1
 
1.5%
더베스트 1
 
1.5%
동래에코하임 1
 
1.5%
용진스타티스7차 1
 
1.5%
반도보라 1
 
1.5%
스카이뷰 1
 
1.5%
호텔농심 1
 
1.5%
불이빌딩 1
 
1.5%
Other values (53) 53
77.9%
2023-12-11T01:50:54.370281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
6.9%
동 12
 
3.6%
이 11
 
3.3%
스 10
 
3.0%
온 9
 
2.7%
천 9
 
2.7%
브 6
 
1.8%
래 6
 
1.8%
라 5
 
1.5%
명 5
 
1.5%
Other values (136) 236
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
87.0%
Space Separator 23
 
6.9%
Uppercase Letter 10
 
3.0%
Decimal Number 4
 
1.2%
Lowercase Letter 3
 
0.9%
Letter Number 1
 
0.3%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 12
 
4.2%
이 11
 
3.8%
스 10
 
3.5%
온 9
 
3.1%
천 9
 
3.1%
브 6
 
2.1%
래 6
 
2.1%
라 5
 
1.7%
명 5
 
1.7%
허 5
 
1.7%
Other values (122) 211
73.0%
Uppercase Letter
ValueCountFrequency (%)
K 4
40.0%
S 3
30.0%
P 1
 
10.0%
R 1
 
10.0%
H 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
33.3%
s 1
33.3%
w 1
33.3%
Decimal Number
ValueCountFrequency (%)
3 3
75.0%
7 1
 
25.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
87.0%
Common 29
 
8.7%
Latin 14
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 12
 
4.2%
이 11
 
3.8%
스 10
 
3.5%
온 9
 
3.1%
천 9
 
3.1%
브 6
 
2.1%
래 6
 
2.1%
라 5
 
1.7%
명 5
 
1.7%
허 5
 
1.7%
Other values (122) 211
73.0%
Latin
ValueCountFrequency (%)
K 4
28.6%
S 3
21.4%
k 1
 
7.1%
s 1
 
7.1%
P 1
 
7.1%
Ⅱ 1
 
7.1%
w 1
 
7.1%
R 1
 
7.1%
H 1
 
7.1%
Common
ValueCountFrequency (%)
23
79.3%
3 3
 
10.3%
7 1
 
3.4%
) 1
 
3.4%
( 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
87.0%
ASCII 42
 
12.7%
Number Forms 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
54.8%
K 4
 
9.5%
S 3
 
7.1%
3 3
 
7.1%
k 1
 
2.4%
s 1
 
2.4%
7 1
 
2.4%
P 1
 
2.4%
) 1
 
2.4%
( 1
 
2.4%
Other values (3) 3
 
7.1%
Hangul
ValueCountFrequency (%)
동 12
 
4.2%
이 11
 
3.8%
스 10
 
3.5%
온 9
 
3.1%
천 9
 
3.1%
브 6
 
2.1%
래 6
 
2.1%
라 5
 
1.7%
명 5
 
1.7%
허 5
 
1.7%
Other values (122) 211
73.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

층수
Text

Distinct38
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-11T01:50:54.658068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.1111111
Min length7

Characters and Unicode

Total characters410
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)75.6%

Sample

1st row지하1층/지상15층
2nd row지하1층/지상15층
3rd row지하1층/지상15층
4th row지하5/지상13
5th row지하1/지상15
ValueCountFrequency (%)
지하1층/지상15층 5
 
11.1%
지하3/지상12 2
 
4.4%
지하1층/지상20층 2
 
4.4%
지하1/지상15 2
 
4.4%
지하4/지상29 1
 
2.2%
지하4/지상25 1
 
2.2%
지하1층/지상14층 1
 
2.2%
지하4/지상40 1
 
2.2%
지하2/지상9층 1
 
2.2%
지하2/지상7 1
 
2.2%
Other values (28) 28
62.2%
2023-12-11T01:50:55.053962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 90
22.0%
층 58
14.1%
하 45
11.0%
/ 45
11.0%
상 45
11.0%
1 42
10.2%
5 20
 
4.9%
2 19
 
4.6%
4 15
 
3.7%
3 13
 
3.2%
Other values (5) 18
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
58.0%
Decimal Number 127
31.0%
Other Punctuation 45
 
11.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 42
33.1%
5 20
15.7%
2 19
15.0%
4 15
 
11.8%
3 13
 
10.2%
0 7
 
5.5%
9 5
 
3.9%
6 2
 
1.6%
7 2
 
1.6%
8 2
 
1.6%
Other Letter
ValueCountFrequency (%)
지 90
37.8%
층 58
24.4%
하 45
18.9%
상 45
18.9%
Other Punctuation
ValueCountFrequency (%)
/ 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
58.0%
Common 172
42.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 45
26.2%
1 42
24.4%
5 20
11.6%
2 19
11.0%
4 15
 
8.7%
3 13
 
7.6%
0 7
 
4.1%
9 5
 
2.9%
6 2
 
1.2%
7 2
 
1.2%
Hangul
ValueCountFrequency (%)
지 90
37.8%
층 58
24.4%
하 45
18.9%
상 45
18.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
58.0%
ASCII 172
42.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 90
37.8%
층 58
24.4%
하 45
18.9%
상 45
18.9%
ASCII
ValueCountFrequency (%)
/ 45
26.2%
1 42
24.4%
5 20
11.6%
2 19
11.0%
4 15
 
8.7%
3 13
 
7.6%
0 7
 
4.1%
9 5
 
2.9%
6 2
 
1.2%
7 2
 
1.2%

용도
Text

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-11T01:50:55.267911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length9.8222222
Min length4

Characters and Unicode

Total characters442
Distinct characters41
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

Unique22 ?
Unique (%)48.9%

Sample

1st row공동주택
2nd row공동주택, 업무시설
3rd row업무시설
4th row업무시설, 근생
5th row업무시설
ValueCountFrequency (%)
공동주택 23
27.4%
업무시설 22
26.2%
근생 8
 
9.5%
근린생활시설 4
 
4.8%
등 4
 
4.8%
판매시설 4
 
4.8%
제1,2종근린생활시설 4
 
4.8%
의료시설 3
 
3.6%
문화및집회 3
 
3.6%
종교시설 2
 
2.4%
Other values (7) 7
 
8.3%
2023-12-11T01:50:55.840780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
설 44
 
10.0%
시 44
 
10.0%
, 41
 
9.3%
40
 
9.0%
동 24
 
5.4%
공 24
 
5.4%
택 24
 
5.4%
주 24
 
5.4%
업 23
 
5.2%
무 22
 
5.0%
Other values (31) 132
29.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 352
79.6%
Other Punctuation 41
 
9.3%
Space Separator 40
 
9.0%
Decimal Number 9
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 44
12.5%
시 44
12.5%
동 24
 
6.8%
공 24
 
6.8%
택 24
 
6.8%
주 24
 
6.8%
업 23
 
6.5%
무 22
 
6.2%
근 18
 
5.1%
생 18
 
5.1%
Other values (27) 87
24.7%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
2 4
44.4%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
79.6%
Common 90
 
20.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 44
12.5%
시 44
12.5%
동 24
 
6.8%
공 24
 
6.8%
택 24
 
6.8%
주 24
 
6.8%
업 23
 
6.5%
무 22
 
6.2%
근 18
 
5.1%
생 18
 
5.1%
Other values (27) 87
24.7%
Common
ValueCountFrequency (%)
, 41
45.6%
40
44.4%
1 5
 
5.6%
2 4
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 352
79.6%
ASCII 90
 
20.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
설 44
12.5%
시 44
12.5%
동 24
 
6.8%
공 24
 
6.8%
택 24
 
6.8%
주 24
 
6.8%
업 23
 
6.5%
무 22
 
6.2%
근 18
 
5.1%
생 18
 
5.1%
Other values (27) 87
24.7%
ASCII
ValueCountFrequency (%)
, 41
45.6%
40
44.4%
1 5
 
5.6%
2 4
 
4.4%

공개공지위치
Categorical

Distinct13
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
건물 전면
18 
건물 우측면
6 
건물전면
6 
건물 좌측면
3 
건물 후면
3 
Other values (8)
9 

Length

Max length15
Median length14
Mean length5.9555556
Min length4

Unique

Unique7 ?
Unique (%)15.6%

Sample

1st row건물 전면
2nd row건물 우측면
3rd row건물 좌측면
4th row건물 우측면
5th row건물 전면

Common Values

ValueCountFrequency (%)
건물 전면 18
40.0%
건물 우측면 6
 
13.3%
건물전면 6
 
13.3%
건물 좌측면 3
 
6.7%
건물 후면 3
 
6.7%
건물 전면, 후면 2
 
4.4%
건물 전면, 우측면, 좌측면 1
 
2.2%
건물 전면, 측면 1
 
2.2%
아파트 주위 도로 쪽 1
 
2.2%
건물 정면 1
 
2.2%
Other values (3) 3
 
6.7%

Length

2023-12-11T01:50:56.006049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건물 35
38.5%
전면 22
24.2%
우측면 8
 
8.8%
건물전면 8
 
8.8%
좌측면 6
 
6.6%
후면 5
 
5.5%
측면 1
 
1.1%
아파트 1
 
1.1%
주위 1
 
1.1%
도로 1
 
1.1%
Other values (3) 3
 
3.3%

공개공지편의시설
Text

MISSING 

Distinct28
Distinct (%)63.6%
Missing1
Missing (%)2.2%
Memory size492.0 B
2023-12-11T01:50:56.285934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length23
Mean length10.954545
Min length2

Characters and Unicode

Total characters482
Distinct characters62
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)56.8%

Sample

1st row의자,표지판
2nd row의자,조명, 표지판
3rd row의자,표지판
4th row파고라, 의자, 표지판 1
5th row의자, 표지판 1
ValueCountFrequency (%)
표지판 23
19.3%
의자 18
15.1%
1 15
12.6%
조경 8
 
6.7%
벤치 5
 
4.2%
파고라1 3
 
2.5%
파고라 3
 
2.5%
의자,표지판 3
 
2.5%
조명 2
 
1.7%
미술장식품 2
 
1.7%
Other values (35) 37
31.1%
2023-12-11T01:50:56.791338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
15.6%
, 63
13.1%
의 32
 
6.6%
자 32
 
6.6%
1 28
 
5.8%
표 27
 
5.6%
판 27
 
5.6%
지 27
 
5.6%
조 14
 
2.9%
벤 12
 
2.5%
Other values (52) 145
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
60.4%
Space Separator 75
 
15.6%
Other Punctuation 64
 
13.3%
Decimal Number 51
 
10.6%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 32
 
11.0%
자 32
 
11.0%
표 27
 
9.3%
판 27
 
9.3%
지 27
 
9.3%
조 14
 
4.8%
벤 12
 
4.1%
치 12
 
4.1%
경 10
 
3.4%
라 8
 
2.7%
Other values (39) 90
30.9%
Decimal Number
ValueCountFrequency (%)
1 28
54.9%
2 7
 
13.7%
3 5
 
9.8%
6 3
 
5.9%
5 3
 
5.9%
8 2
 
3.9%
7 1
 
2.0%
9 1
 
2.0%
4 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 63
98.4%
. 1
 
1.6%
Space Separator
ValueCountFrequency (%)
75
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
60.4%
Common 190
39.4%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 32
 
11.0%
자 32
 
11.0%
표 27
 
9.3%
판 27
 
9.3%
지 27
 
9.3%
조 14
 
4.8%
벤 12
 
4.1%
치 12
 
4.1%
경 10
 
3.4%
라 8
 
2.7%
Other values (39) 90
30.9%
Common
ValueCountFrequency (%)
75
39.5%
, 63
33.2%
1 28
 
14.7%
2 7
 
3.7%
3 5
 
2.6%
6 3
 
1.6%
5 3
 
1.6%
8 2
 
1.1%
7 1
 
0.5%
. 1
 
0.5%
Other values (2) 2
 
1.1%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
60.4%
ASCII 191
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
39.3%
, 63
33.0%
1 28
 
14.7%
2 7
 
3.7%
3 5
 
2.6%
6 3
 
1.6%
5 3
 
1.6%
8 2
 
1.0%
7 1
 
0.5%
m 1
 
0.5%
Other values (3) 3
 
1.6%
Hangul
ValueCountFrequency (%)
의 32
 
11.0%
자 32
 
11.0%
표 27
 
9.3%
판 27
 
9.3%
지 27
 
9.3%
조 14
 
4.8%
벤 12
 
4.1%
치 12
 
4.1%
경 10
 
3.4%
라 8
 
2.7%
Other values (39) 90
30.9%

공개공지개소
Categorical

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
1
36 
2
8 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

1st row1
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 36
80.0%
2 8
 
17.8%
4 1
 
2.2%

Length

2023-12-11T01:50:56.984960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:50:57.142550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 36
80.0%
2 8
 
17.8%
4 1
 
2.2%

공개공지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean622.26956
Minimum28.56
Maximum5781.53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T01:50:57.319773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28.56
5-th percentile40.6
Q186.17
median214.52
Q3448.96
95-th percentile2660.77
Maximum5781.53
Range5752.97
Interquartile range (IQR)362.79

Descriptive statistics

Standard deviation1107.6224
Coefficient of variation (CV)1.779972
Kurtosis11.166696
Mean622.26956
Median Absolute Deviation (MAD)141.74
Skewness3.1540155
Sum28002.13
Variance1226827.4
MonotonicityNot monotonic
2023-12-11T01:50:57.528718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
102.75 1
 
2.2%
150.6 1
 
2.2%
63.0 1
 
2.2%
72.78 1
 
2.2%
5781.53 1
 
2.2%
929.92 1
 
2.2%
107.4 1
 
2.2%
66.3 1
 
2.2%
2438.81 1
 
2.2%
302.96 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
28.56 1
2.2%
38.14 1
2.2%
39.11 1
2.2%
46.56 1
2.2%
55.7 1
2.2%
60.93 1
2.2%
63.0 1
2.2%
66.3 1
2.2%
70.2 1
2.2%
72.78 1
2.2%
ValueCountFrequency (%)
5781.53 1
2.2%
3678.46 1
2.2%
2716.26 1
2.2%
2438.81 1
2.2%
1862.55 1
2.2%
1501.55 1
2.2%
1291.08 1
2.2%
929.92 1
2.2%
758.12 1
2.2%
694.77 1
2.2%

연면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38484.138
Minimum1904.99
Maximum228198.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T01:50:57.746567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1904.99
5-th percentile2756.0164
Q17093.035
median12172.11
Q335071.21
95-th percentile193005.15
Maximum228198.18
Range226293.19
Interquartile range (IQR)27978.175

Descriptive statistics

Standard deviation60937.633
Coefficient of variation (CV)1.5834481
Kurtosis3.7898437
Mean38484.138
Median Absolute Deviation (MAD)7413.2
Skewness2.2224003
Sum1731786.2
Variance3.7133951 × 109
MonotonicityNot monotonic
2023-12-11T01:50:57.957765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
5590.64 1
 
2.2%
9609.21 1
 
2.2%
2330.873 1
 
2.2%
7093.035 1
 
2.2%
228198.18 1
 
2.2%
19585.31 1
 
2.2%
7594.0 1
 
2.2%
7957.0 1
 
2.2%
28885.81 1
 
2.2%
36091.73 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1904.99 1
2.2%
2300.66 1
2.2%
2330.873 1
2.2%
4456.59 1
2.2%
4635.12 1
2.2%
4938.22 1
2.2%
5590.64 1
2.2%
5612.68 1
2.2%
5788.53 1
2.2%
6053.31 1
2.2%
ValueCountFrequency (%)
228198.18 1
2.2%
223428.0 1
2.2%
201609.414 1
2.2%
158588.11 1
2.2%
151490.411 1
2.2%
146758.77 1
2.2%
67748.662 1
2.2%
44346.48 1
2.2%
37069.85 1
2.2%
36091.73 1
2.2%

허가일자
Date

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum1978-04-27 00:00:00
Maximum2020-12-21 00:00:00
2023-12-11T01:50:58.292614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:58.529234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)

사용승인일자
Date

Distinct44
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
Minimum1978-11-25 00:00:00
Maximum2022-05-26 00:00:00
2023-12-11T01:50:58.750835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:58.918614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
2022-10-17
45 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-10-17
2nd row2022-10-17
3rd row2022-10-17
4th row2022-10-17
5th row2022-10-17

Common Values

ValueCountFrequency (%)
2022-10-17 45
100.0%

Length

2023-12-11T01:50:59.107749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:50:59.257092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-10-17 45
100.0%

도로명주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-11T01:50:59.601809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.977778
Min length15

Characters and Unicode

Total characters854
Distinct characters47
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 아시아드대로246번길 7
2nd row부산광역시 동래구 동래로 9
3rd row부산광역시 동래구 금강공원로 27
4th row부산광역시 동래구 충렬대로 212
5th row부산광역시 동래구 석사로 43
ValueCountFrequency (%)
부산광역시 45
24.9%
동래구 45
24.9%
충렬대로 8
 
4.4%
중앙대로 5
 
2.8%
온천장로 3
 
1.7%
7 3
 
1.7%
금강공원로 3
 
1.7%
아시아드대로 2
 
1.1%
미남로 2
 
1.1%
23 2
 
1.1%
Other values (60) 63
34.8%
2023-12-11T01:51:00.199524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
16.0%
시 48
 
5.6%
동 48
 
5.6%
래 48
 
5.6%
부 45
 
5.3%
광 45
 
5.3%
역 45
 
5.3%
구 45
 
5.3%
산 45
 
5.3%
로 45
 
5.3%
Other values (37) 303
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 573
67.1%
Decimal Number 144
 
16.9%
Space Separator 137
 
16.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 48
 
8.4%
동 48
 
8.4%
래 48
 
8.4%
부 45
 
7.9%
광 45
 
7.9%
역 45
 
7.9%
구 45
 
7.9%
산 45
 
7.9%
로 45
 
7.9%
번 18
 
3.1%
Other values (26) 141
24.6%
Decimal Number
ValueCountFrequency (%)
1 26
18.1%
2 24
16.7%
4 17
11.8%
3 17
11.8%
7 14
9.7%
5 12
8.3%
9 11
7.6%
6 8
 
5.6%
0 8
 
5.6%
8 7
 
4.9%
Space Separator
ValueCountFrequency (%)
137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 573
67.1%
Common 281
32.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 48
 
8.4%
동 48
 
8.4%
래 48
 
8.4%
부 45
 
7.9%
광 45
 
7.9%
역 45
 
7.9%
구 45
 
7.9%
산 45
 
7.9%
로 45
 
7.9%
번 18
 
3.1%
Other values (26) 141
24.6%
Common
ValueCountFrequency (%)
137
48.8%
1 26
 
9.3%
2 24
 
8.5%
4 17
 
6.0%
3 17
 
6.0%
7 14
 
5.0%
5 12
 
4.3%
9 11
 
3.9%
6 8
 
2.8%
0 8
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 573
67.1%
ASCII 281
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
48.8%
1 26
 
9.3%
2 24
 
8.5%
4 17
 
6.0%
3 17
 
6.0%
7 14
 
5.0%
5 12
 
4.3%
9 11
 
3.9%
6 8
 
2.8%
0 8
 
2.8%
Hangul
ValueCountFrequency (%)
시 48
 
8.4%
동 48
 
8.4%
래 48
 
8.4%
부 45
 
7.9%
광 45
 
7.9%
역 45
 
7.9%
구 45
 
7.9%
산 45
 
7.9%
로 45
 
7.9%
번 18
 
3.1%
Other values (26) 141
24.6%

지번주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-11T01:51:00.587670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length20.133333
Min length17

Characters and Unicode

Total characters906
Distinct characters37
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

Unique45 ?
Unique (%)100.0%

Sample

1st row부산광역시 동래구 온천동 1421-35
2nd row부산광역시 동래구 온천동 477-5
3rd row부산광역시 동래구 온천동 210-16
4th row부산광역시 동래구 수안동 1-11
5th row부산광역시 동래구 사직동 53-5
ValueCountFrequency (%)
부산광역시 45
23.3%
동래구 45
23.3%
온천동 23
11.9%
외 6
 
3.1%
사직동 5
 
2.6%
안락동 4
 
2.1%
명륜동 4
 
2.1%
명장동 3
 
1.6%
낙민동 3
 
1.6%
수안동 3
 
1.6%
Other values (50) 52
26.9%
2023-12-11T01:51:01.172189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
149
16.4%
동 91
 
10.0%
1 50
 
5.5%
부 45
 
5.0%
산 45
 
5.0%
래 45
 
5.0%
구 45
 
5.0%
시 45
 
5.0%
역 45
 
5.0%
광 45
 
5.0%
Other values (27) 301
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 520
57.4%
Decimal Number 198
 
21.9%
Space Separator 149
 
16.4%
Dash Punctuation 39
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 91
17.5%
부 45
8.7%
산 45
8.7%
래 45
8.7%
구 45
8.7%
시 45
8.7%
역 45
8.7%
광 45
8.7%
온 23
 
4.4%
천 23
 
4.4%
Other values (15) 68
13.1%
Decimal Number
ValueCountFrequency (%)
1 50
25.3%
3 27
13.6%
8 23
11.6%
2 20
 
10.1%
4 18
 
9.1%
0 16
 
8.1%
6 15
 
7.6%
5 14
 
7.1%
7 9
 
4.5%
9 6
 
3.0%
Space Separator
ValueCountFrequency (%)
149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 520
57.4%
Common 386
42.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 91
17.5%
부 45
8.7%
산 45
8.7%
래 45
8.7%
구 45
8.7%
시 45
8.7%
역 45
8.7%
광 45
8.7%
온 23
 
4.4%
천 23
 
4.4%
Other values (15) 68
13.1%
Common
ValueCountFrequency (%)
149
38.6%
1 50
 
13.0%
- 39
 
10.1%
3 27
 
7.0%
8 23
 
6.0%
2 20
 
5.2%
4 18
 
4.7%
0 16
 
4.1%
6 15
 
3.9%
5 14
 
3.6%
Other values (2) 15
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 520
57.4%
ASCII 386
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
149
38.6%
1 50
 
13.0%
- 39
 
10.1%
3 27
 
7.0%
8 23
 
6.0%
2 20
 
5.2%
4 18
 
4.7%
0 16
 
4.1%
6 15
 
3.9%
5 14
 
3.6%
Other values (2) 15
 
3.9%
Hangul
ValueCountFrequency (%)
동 91
17.5%
부 45
8.7%
산 45
8.7%
래 45
8.7%
구 45
8.7%
시 45
8.7%
역 45
8.7%
광 45
8.7%
온 23
 
4.4%
천 23
 
4.4%
Other values (15) 68
13.1%

위도
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.207668
Minimum35.194633
Maximum35.221265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T01:51:01.479367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.194633
5-th percentile35.196255
Q135.2008
median35.204938
Q335.216455
95-th percentile35.219742
Maximum35.221265
Range0.026632
Interquartile range (IQR)0.015655

Descriptive statistics

Standard deviation0.0084423796
Coefficient of variation (CV)0.00023978809
Kurtosis-1.3923632
Mean35.207668
Median Absolute Deviation (MAD)0.007623
Skewness0.21375108
Sum1584.3451
Variance7.1273773 × 10-5
MonotonicityNot monotonic
2023-12-11T01:51:01.767681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
35.205694 1
 
2.2%
35.20073211 1
 
2.2%
35.197 1
 
2.2%
35.220987 1
 
2.2%
35.204527 1
 
2.2%
35.219818 1
 
2.2%
35.202686 1
 
2.2%
35.196292 1
 
2.2%
35.204322 1
 
2.2%
35.2186 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
35.194633 1
2.2%
35.195283 1
2.2%
35.196246 1
2.2%
35.196292 1
2.2%
35.197 1
2.2%
35.197315 1
2.2%
35.198006 1
2.2%
35.198641 1
2.2%
35.200393 1
2.2%
35.200457 1
2.2%
ValueCountFrequency (%)
35.221265 1
2.2%
35.220987 1
2.2%
35.219818 1
2.2%
35.219437 1
2.2%
35.219109 1
2.2%
35.218917 1
2.2%
35.2186 1
2.2%
35.218572 1
2.2%
35.21848 1
2.2%
35.21821 1
2.2%

경도
Real number (ℝ)

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.08231
Minimum129.06127
Maximum129.10625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-11T01:51:02.398391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.06127
5-th percentile129.06438
Q1129.07771
median129.08145
Q3129.08556
95-th percentile129.1057
Maximum129.10625
Range0.044984
Interquartile range (IQR)0.007846

Descriptive statistics

Standard deviation0.011863348
Coefficient of variation (CV)9.1905295 × 10-5
Kurtosis-0.1066485
Mean129.08231
Median Absolute Deviation (MAD)0.003851
Skewness0.50225448
Sum5808.7041
Variance0.00014073903
MonotonicityNot monotonic
2023-12-11T01:51:02.756850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
129.068654 1
 
2.2%
129.087281 1
 
2.2%
129.106109 1
 
2.2%
129.082103 1
 
2.2%
129.068663 1
 
2.2%
129.082072 1
 
2.2%
129.081426 1
 
2.2%
129.103319 1
 
2.2%
129.081184 1
 
2.2%
129.084151 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
129.06127 1
2.2%
129.06247 1
2.2%
129.063739 1
2.2%
129.066921 1
2.2%
129.0678187 1
2.2%
129.068654 1
2.2%
129.068663 1
2.2%
129.069279 1
2.2%
129.070859 1
2.2%
129.070891 1
2.2%
ValueCountFrequency (%)
129.106254 1
2.2%
129.106109 1
2.2%
129.105863 1
2.2%
129.10506 1
2.2%
129.103319 1
2.2%
129.100923 1
2.2%
129.098291 1
2.2%
129.095359 1
2.2%
129.094915 1
2.2%
129.087281 1
2.2%

Interactions

2023-12-11T01:50:52.403244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:50.717501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.384366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.883477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.512882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:50.881871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.507341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.017583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.621675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.056457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.633539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.136385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.818027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.227223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:51.767234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:50:52.272807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:51:02.964319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물명층수용도공개공지위치공개공지편의시설공개공지개소공개공지면적연면적허가일자사용승인일자도로명주소지번주소위도경도
건축물명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
층수1.0001.0000.9370.8230.8230.8570.9770.9821.0000.9781.0001.0000.0000.862
용도1.0000.9371.0000.8730.9530.8740.7770.1861.0001.0001.0001.0000.7390.820
공개공지위치1.0000.8230.8731.0000.0000.3600.7690.3451.0001.0001.0001.0000.0000.000
공개공지편의시설1.0000.8230.9530.0001.0000.0000.7840.9161.0000.9101.0001.0000.8240.000
공개공지개소1.0000.8570.8740.3600.0001.0000.5530.6931.0001.0001.0001.0000.3600.000
공개공지면적1.0000.9770.7770.7690.7840.5531.0000.7731.0001.0001.0001.0000.4460.000
연면적1.0000.9820.1860.3450.9160.6930.7731.0001.0000.0001.0001.0000.3860.000
허가일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사용승인일자1.0000.9781.0001.0000.9101.0001.0000.0001.0001.0001.0001.0000.9480.965
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0000.0000.7390.0000.8240.3600.4460.3861.0000.9481.0001.0001.0000.830
경도1.0000.8620.8200.0000.0000.0000.0000.0001.0000.9651.0001.0000.8301.000
2023-12-11T01:51:03.209871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공개공지위치공개공지개소
공개공지위치1.0000.174
공개공지개소0.1741.000
2023-12-11T01:51:03.435647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공개공지면적연면적위도경도공개공지위치공개공지개소
공개공지면적1.0000.8740.160-0.0950.4500.417
연면적0.8741.0000.372-0.1260.1610.364
위도0.1600.3721.000-0.0870.0000.144
경도-0.095-0.126-0.0871.0000.0000.000
공개공지위치0.4500.1610.0000.0001.0000.174
공개공지개소0.4170.3640.1440.0000.1741.000

Missing values

2023-12-11T01:50:53.052819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:50:53.288773image/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

구군명건축물명층수용도공개공지위치공개공지편의시설공개공지개소공개공지면적연면적허가일자사용승인일자데이터기준일자도로명주소지번주소위도경도
0동래구허브센티움3지하1층/지상15층공동주택건물 전면의자,표지판1102.755590.642014-03-252015-04-152022-10-17부산광역시 동래구 아시아드대로246번길 7부산광역시 동래구 온천동 1421-3535.205694129.068654
1동래구온천동 퀸즈w지하1층/지상15층공동주택, 업무시설건물 우측면의자,조명, 표지판2319.2815565.572014-06-182015-12-032022-10-17부산광역시 동래구 동래로 9부산광역시 동래구 온천동 477-535.213976129.077714
2동래구케이에이치 마이우스지하1층/지상15층업무시설건물 좌측면의자,표지판155.79853.582009-05-282016-08-052022-10-17부산광역시 동래구 금강공원로 27부산광역시 동래구 온천동 210-1635.218917129.081455
3동래구대신증권지하5/지상13업무시설, 근생건물 우측면파고라, 의자, 표지판 1186.9614561.01996-10-021999-05-242022-10-17부산광역시 동래구 충렬대로 212부산광역시 동래구 수안동 1-1135.202088129.082452
4동래구사직 유로빌지하1/지상15업무시설건물 전면의자, 표지판 1184.267151.02000-02-142002-03-142022-10-17부산광역시 동래구 석사로 43부산광역시 동래구 사직동 53-535.200393129.063739
5동래구명선하이츠지하2/지상15공동주택, 근생건물 전면의자, 표지판 12176.277281.792002-08-262004-04-282022-10-17부산광역시 동래구 반송로273번길 7부산광역시 동래구 명장동 29-235.204388129.100923
6동래구프리존 오피스텔지하3/지상15업무시설건물 후면의자, 표지판 1186.611481.02000-12-042004-03-232022-10-17부산광역시 동래구 온천장로 14부산광역시 동래구 온천동 1750-3335.21347129.079289
7동래구롯데백화점(동래점)지하3/지상12판매시설, 문화및집회건물 전면의자, 조명, 조형물, 표지판 222716.26158588.112005-11-142012-05-292022-10-17부산광역시 동래구 중앙대로 1393부산광역시 동래구 온천동 502-335.211506129.077601
8동래구허브센티움Ⅱ지하1/지상15공동주택, 업무시설건물 좌측면의자, 표지판 11103.424938.222012-12-282013-12-052022-10-17부산광역시 동래구 아사아드대로 231부산광역시 동래구 온천동 1248-1235.204938129.066921
9동래구삼정자이언츠파크지하4층/지상11제1,2종근린생활시설 등건물 전면조명, 조경, 의자, 미술장식품, 표지판11346.8923195.362013-07-232015-06-302022-10-17부산광역시 동래구 사직북로 4부산광역시 동래구 사직동 93-635.196246129.06127
구군명건축물명층수용도공개공지위치공개공지편의시설공개공지개소공개공지면적연면적허가일자사용승인일자데이터기준일자도로명주소지번주소위도경도
35동래구동래효성해링턴지하4층/지상49층공동주택, 업무시설건물전면연식파고라1, 의자9, 연식플랜터72.5m11862.55146758.772008-04-082019-05-302022-10-17부산광역시 동래구 아시아드대로 255번길 14부산광역시 동래구 온천동 183835.207215129.067819
36동래구프라임온천동지하1층/지상15층업무시설, 제1,2종근린생활시설건물후면벤치6138.145612.682018-02-122020-12-182022-10-17부산광역시 동래구 동래로19번길 4부산광역시 동래구 온천동 474-1435.21331129.07824
37동래구동래롯데캐슬퀸지하3층/지상34층공동주택, 근린생활시설건물전면파고라1, 평의자2, 등의자3, 목재데크1441.7935684.43352016-12-212020-12-242022-10-17부산광역시 동래구 온천천로 165부산광역시 동래구 명륜동 533-229 외 6필지35.20509129.07892
38동래구온천장역 삼정그린코아 더시티지하5층/지상24층업무시설, 근린생활시설건물전면, 좌측면파고라, 등의자5, 평의자21268.9434730.94282018-03-092021-01-292022-10-17부산광역시 동래구 중앙대로 1473번길 24부산광역시 동래구 온천동 180-14 외 2필지35.21848129.08253
39동래구성완 세띠앙지하2층/지상20층공동주택, 제1,2종근린생활시설건물전면, 우측면, 좌측면조경, 벤치1448.9622278.932002-12-032005-06-072022-10-17부산광역시 동래구 충렬대로 238번길 7부산광역시 동래구 수안동 18235.20127129.08556
40동래구에코하임 명당지하1층/지상11층업무시설, 공동주택, 제1종근린생활시설건물 우측면파고라, 벤치2139.111904.992019-09-082021-07-072022-10-17부산광역시 동래구 명안로86번길 12부산광역시 동래구 명장동 136-4 외 1필지35.20413129.10506
41동래구동래sk뷰3차지하5층/지상38층공동주택건물전면평의자6, 등의자3, 독립의자16, 파고라1, 앉음벽1, 장식플랜터121501.55201609.4142018-01-162021-12-062022-10-17부산광역시 동래구 온천장로65번길 9부산광역시 동래구 온천동 185035.2168129.0806
42동래구아이뷰파크지하1층/지상15층공동주택, 업무시설, 근린생활시설건물전면벤치3146.564456.592019-01-182021-12-202022-10-17부산광역시 동래구 명안로78번길 25부산광역시 동래구 명장동 136-935.203673129.105863
43동래구여고플래티넘지하1층/지상6층오피스텔, 공동주택, 제1,2종근린생활시설건물전면벤치1128.562300.662020-12-212022-01-212022-10-17부산광역시 동래구 미남로 52부산광역시 동래구 사직동 151-8번지 외 4필지35.198641129.070859
44동래구힐스테이트명륜 트라디움지하2층/지상42층공동주택, 근린생활시설건물전면<NA>2758.12151490.4112017-01-262022-05-262022-10-17부산광역시 동래구 동래로57번길 94부산광역시 동래구 명륜동 700-10135.2136129.0815