Overview

Dataset statistics

Number of variables6
Number of observations747
Missing cells186
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.1 KiB
Average record size in memory48.2 B

Variable types

Text5
Categorical1

Dataset

Description부산광역시_동래구_부동산중개업소정보_20221013
Author부산광역시 동래구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3039790

Alerts

사무소전화번호 has 186 (24.9%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:53:43.469215
Analysis finished2023-12-10 16:53:44.946106
Duration1.48 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct747
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T01:53:45.183068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.267738
Min length8

Characters and Unicode

Total characters10658
Distinct characters13
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

Unique747 ?
Unique (%)100.0%

Sample

1st row나-06-652
2nd row나-06-343
3rd row나-06-292
4th row가-06-4180
5th row가-06-1892
ValueCountFrequency (%)
나-06-652 1
 
0.1%
26260-2020-00220 1
 
0.1%
26260-2020-00209 1
 
0.1%
26260-2020-00239 1
 
0.1%
26260-2020-00210 1
 
0.1%
26260-2020-00211 1
 
0.1%
26260-2020-00212 1
 
0.1%
26260-2020-00213 1
 
0.1%
26260-2020-00216 1
 
0.1%
26260-2020-00217 1
 
0.1%
Other values (737) 737
98.7%
2023-12-11T01:53:45.794220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3053
28.6%
2 2346
22.0%
6 1511
14.2%
- 1494
14.0%
1 735
 
6.9%
4 286
 
2.7%
3 263
 
2.5%
9 215
 
2.0%
5 209
 
2.0%
7 193
 
1.8%
Other values (3) 353
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8980
84.3%
Dash Punctuation 1494
 
14.0%
Other Letter 184
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3053
34.0%
2 2346
26.1%
6 1511
16.8%
1 735
 
8.2%
4 286
 
3.2%
3 263
 
2.9%
9 215
 
2.4%
5 209
 
2.3%
7 193
 
2.1%
8 169
 
1.9%
Other Letter
ValueCountFrequency (%)
가 181
98.4%
나 3
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 1494
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10474
98.3%
Hangul 184
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3053
29.1%
2 2346
22.4%
6 1511
14.4%
- 1494
14.3%
1 735
 
7.0%
4 286
 
2.7%
3 263
 
2.5%
9 215
 
2.1%
5 209
 
2.0%
7 193
 
1.8%
Hangul
ValueCountFrequency (%)
가 181
98.4%
나 3
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10474
98.3%
Hangul 184
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3053
29.1%
2 2346
22.4%
6 1511
14.4%
- 1494
14.3%
1 735
 
7.0%
4 286
 
2.7%
3 263
 
2.5%
9 215
 
2.1%
5 209
 
2.0%
7 193
 
1.8%
Hangul
ValueCountFrequency (%)
가 181
98.4%
나 3
 
1.6%

사무소명
Text

Distinct659
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T01:53:46.155661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length11.610442
Min length7

Characters and Unicode

Total characters8673
Distinct characters331
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique602 ?
Unique (%)80.6%

Sample

1st row제일부동산중개사무소
2nd row제일부동산중개사무소
3rd row한라부동산중개사무소
4th row의령부동산중개사무소
5th row럭키3.1부동산중개사무소
ValueCountFrequency (%)
미래공인중개사사무소 7
 
0.9%
태양공인중개사사무소 6
 
0.8%
중앙공인중개사사무소 5
 
0.7%
삼성공인중개사사무소 5
 
0.7%
합동 5
 
0.7%
우리공인중개사사무소 4
 
0.5%
행운부동산공인중개사사무소 4
 
0.5%
행운공인중개사사무소 4
 
0.5%
강남공인중개사사무소 4
 
0.5%
제일공인중개사사무소 4
 
0.5%
Other values (650) 710
93.7%
2023-12-11T01:53:46.819899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1365
15.7%
중 753
 
8.7%
개 751
 
8.7%
소 728
 
8.4%
무 721
 
8.3%
인 626
 
7.2%
공 617
 
7.1%
동 366
 
4.2%
부 317
 
3.7%
산 314
 
3.6%
Other values (321) 2115
24.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8491
97.9%
Uppercase Letter 104
 
1.2%
Decimal Number 27
 
0.3%
Lowercase Letter 17
 
0.2%
Space Separator 12
 
0.1%
Close Punctuation 9
 
0.1%
Open Punctuation 9
 
0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1365
16.1%
중 753
 
8.9%
개 751
 
8.8%
소 728
 
8.6%
무 721
 
8.5%
인 626
 
7.4%
공 617
 
7.3%
동 366
 
4.3%
부 317
 
3.7%
산 314
 
3.7%
Other values (281) 1933
22.8%
Uppercase Letter
ValueCountFrequency (%)
K 27
26.0%
S 15
14.4%
C 12
11.5%
E 7
 
6.7%
I 5
 
4.8%
W 5
 
4.8%
N 5
 
4.8%
H 4
 
3.8%
T 4
 
3.8%
P 4
 
3.8%
Other values (10) 16
15.4%
Lowercase Letter
ValueCountFrequency (%)
e 8
47.1%
w 2
 
11.8%
u 1
 
5.9%
n 1
 
5.9%
k 1
 
5.9%
o 1
 
5.9%
h 1
 
5.9%
c 1
 
5.9%
i 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 22
81.5%
4 3
 
11.1%
3 1
 
3.7%
0 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
# 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8489
97.9%
Latin 121
 
1.4%
Common 61
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1365
16.1%
중 753
 
8.9%
개 751
 
8.8%
소 728
 
8.6%
무 721
 
8.5%
인 626
 
7.4%
공 617
 
7.3%
동 366
 
4.3%
부 317
 
3.7%
산 314
 
3.7%
Other values (279) 1931
22.7%
Latin
ValueCountFrequency (%)
K 27
22.3%
S 15
12.4%
C 12
9.9%
e 8
 
6.6%
E 7
 
5.8%
I 5
 
4.1%
W 5
 
4.1%
N 5
 
4.1%
H 4
 
3.3%
T 4
 
3.3%
Other values (19) 29
24.0%
Common
ValueCountFrequency (%)
1 22
36.1%
12
19.7%
) 9
14.8%
( 9
14.8%
4 3
 
4.9%
- 1
 
1.6%
. 1
 
1.6%
3 1
 
1.6%
` 1
 
1.6%
# 1
 
1.6%
Han
ValueCountFrequency (%)
本 1
50.0%
炫 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8489
97.9%
ASCII 182
 
2.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1365
16.1%
중 753
 
8.9%
개 751
 
8.8%
소 728
 
8.6%
무 721
 
8.5%
인 626
 
7.4%
공 617
 
7.3%
동 366
 
4.3%
부 317
 
3.7%
산 314
 
3.7%
Other values (279) 1931
22.7%
ASCII
ValueCountFrequency (%)
K 27
14.8%
1 22
 
12.1%
S 15
 
8.2%
C 12
 
6.6%
12
 
6.6%
) 9
 
4.9%
( 9
 
4.9%
e 8
 
4.4%
E 7
 
3.8%
I 5
 
2.7%
Other values (30) 56
30.8%
CJK
ValueCountFrequency (%)
本 1
50.0%
炫 1
50.0%

중개업자명
Text

Distinct716
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T01:53:47.353437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.0080321
Min length2

Characters and Unicode

Total characters2247
Distinct characters198
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique689 ?
Unique (%)92.2%

Sample

1st row손덕수
2nd row송욱명
3rd row장이수
4th row김정애
5th row정정숙
ValueCountFrequency (%)
김영미 3
 
0.4%
이정미 3
 
0.4%
이영주 3
 
0.4%
박지영 3
 
0.4%
박선우 2
 
0.3%
김순희 2
 
0.3%
배수진 2
 
0.3%
이정희 2
 
0.3%
이명숙 2
 
0.3%
이영옥 2
 
0.3%
Other values (707) 725
96.8%
2023-12-11T01:53:48.134500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 155
 
6.9%
이 129
 
5.7%
정 107
 
4.8%
영 100
 
4.5%
박 70
 
3.1%
경 65
 
2.9%
희 50
 
2.2%
수 50
 
2.2%
숙 47
 
2.1%
미 47
 
2.1%
Other values (188) 1427
63.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2243
99.8%
Space Separator 2
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 155
 
6.9%
이 129
 
5.8%
정 107
 
4.8%
영 100
 
4.5%
박 70
 
3.1%
경 65
 
2.9%
희 50
 
2.2%
수 50
 
2.2%
숙 47
 
2.1%
미 47
 
2.1%
Other values (185) 1423
63.4%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2240
99.7%
Common 4
 
0.2%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 155
 
6.9%
이 129
 
5.8%
정 107
 
4.8%
영 100
 
4.5%
박 70
 
3.1%
경 65
 
2.9%
희 50
 
2.2%
수 50
 
2.2%
숙 47
 
2.1%
미 47
 
2.1%
Other values (182) 1420
63.4%
Common
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%
Han
ValueCountFrequency (%)
金 1
33.3%
順 1
33.3%
熙 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2240
99.7%
ASCII 4
 
0.2%
CJK 3
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 155
 
6.9%
이 129
 
5.8%
정 107
 
4.8%
영 100
 
4.5%
박 70
 
3.1%
경 65
 
2.9%
희 50
 
2.2%
수 50
 
2.2%
숙 47
 
2.1%
미 47
 
2.1%
Other values (182) 1420
63.4%
ASCII
ValueCountFrequency (%)
2
50.0%
( 1
25.0%
) 1
25.0%
CJK
ValueCountFrequency (%)
金 1
33.3%
順 1
33.3%
熙 1
33.3%

사무소전화번호
Text

MISSING 

Distinct542
Distinct (%)96.6%
Missing186
Missing (%)24.9%
Memory size6.0 KiB
2023-12-11T01:53:48.552959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.003565
Min length12

Characters and Unicode

Total characters6734
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique523 ?
Unique (%)93.2%

Sample

1st row051-552-9001
2nd row051-525-6812
3rd row051-521-0005
4th row051-502-4444
5th row051-552-3131
ValueCountFrequency (%)
051-521-8848 2
 
0.4%
051-501-5111 2
 
0.4%
051-552-9001 2
 
0.4%
051-554-2200 2
 
0.4%
051-521-0001 2
 
0.4%
051-502-3377 2
 
0.4%
051-553-8887 2
 
0.4%
051-553-8888 2
 
0.4%
051-502-0888 2
 
0.4%
051-554-1009 2
 
0.4%
Other values (532) 541
96.4%
2023-12-11T01:53:49.120113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1587
23.6%
0 1247
18.5%
- 1122
16.7%
1 827
12.3%
8 380
 
5.6%
2 316
 
4.7%
3 288
 
4.3%
9 266
 
4.0%
7 250
 
3.7%
4 249
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5612
83.3%
Dash Punctuation 1122
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1587
28.3%
0 1247
22.2%
1 827
14.7%
8 380
 
6.8%
2 316
 
5.6%
3 288
 
5.1%
9 266
 
4.7%
7 250
 
4.5%
4 249
 
4.4%
6 202
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 1122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6734
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1587
23.6%
0 1247
18.5%
- 1122
16.7%
1 827
12.3%
8 380
 
5.6%
2 316
 
4.7%
3 288
 
4.3%
9 266
 
4.0%
7 250
 
3.7%
4 249
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6734
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1587
23.6%
0 1247
18.5%
- 1122
16.7%
1 827
12.3%
8 380
 
5.6%
2 316
 
4.7%
3 288
 
4.3%
9 266
 
4.0%
7 250
 
3.7%
4 249
 
3.7%

사무소주소
Text

Distinct673
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-11T01:53:49.541001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length52
Mean length34.874163
Min length21

Characters and Unicode

Total characters26051
Distinct characters232
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique613 ?
Unique (%)82.1%

Sample

1st row부산광역시 동래구 차밭골로 9, 102호 (온천동)
2nd row부산광역시 동래구 반송로 287-8 (명장동)
3rd row부산광역시 동래구 명안로 4 (안락동)
4th row부산광역시 동래구 사직북로48번길 12 (사직동)
5th row부산광역시 동래구 충렬대로107번길 54, 상가동 1-1호 (온천동,럭키아파트)
ValueCountFrequency (%)
부산광역시 747
 
15.7%
동래구 747
 
15.7%
온천동 242
 
5.1%
사직동 123
 
2.6%
1층 112
 
2.4%
명륜동 81
 
1.7%
안락동 80
 
1.7%
명장동 50
 
1.1%
충렬대로107번길 48
 
1.0%
수안동 46
 
1.0%
Other values (786) 2468
52.0%
2023-12-11T01:53:50.202780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4072
 
15.6%
동 1851
 
7.1%
1 1208
 
4.6%
래 901
 
3.5%
시 857
 
3.3%
산 776
 
3.0%
, 776
 
3.0%
역 753
 
2.9%
부 752
 
2.9%
광 750
 
2.9%
Other values (222) 13355
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15010
57.6%
Decimal Number 4350
 
16.7%
Space Separator 4072
 
15.6%
Other Punctuation 779
 
3.0%
Open Punctuation 750
 
2.9%
Close Punctuation 750
 
2.9%
Uppercase Letter 209
 
0.8%
Dash Punctuation 122
 
0.5%
Lowercase Letter 8
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1851
 
12.3%
래 901
 
6.0%
시 857
 
5.7%
산 776
 
5.2%
역 753
 
5.0%
부 752
 
5.0%
광 750
 
5.0%
로 748
 
5.0%
구 747
 
5.0%
번 391
 
2.6%
Other values (191) 6484
43.2%
Uppercase Letter
ValueCountFrequency (%)
K 37
17.7%
B 36
17.2%
S 29
13.9%
A 21
10.0%
E 16
7.7%
W 15
7.2%
I 15
7.2%
V 15
7.2%
C 14
 
6.7%
H 4
 
1.9%
Other values (3) 7
 
3.3%
Decimal Number
ValueCountFrequency (%)
1 1208
27.8%
2 548
12.6%
0 530
12.2%
3 457
 
10.5%
5 320
 
7.4%
7 314
 
7.2%
4 312
 
7.2%
6 252
 
5.8%
8 209
 
4.8%
9 200
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 776
99.6%
· 3
 
0.4%
Space Separator
ValueCountFrequency (%)
4072
100.0%
Open Punctuation
ValueCountFrequency (%)
( 750
100.0%
Close Punctuation
ValueCountFrequency (%)
) 750
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15010
57.6%
Common 10824
41.5%
Latin 217
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1851
 
12.3%
래 901
 
6.0%
시 857
 
5.7%
산 776
 
5.2%
역 753
 
5.0%
부 752
 
5.0%
광 750
 
5.0%
로 748
 
5.0%
구 747
 
5.0%
번 391
 
2.6%
Other values (191) 6484
43.2%
Common
ValueCountFrequency (%)
4072
37.6%
1 1208
 
11.2%
, 776
 
7.2%
( 750
 
6.9%
) 750
 
6.9%
2 548
 
5.1%
0 530
 
4.9%
3 457
 
4.2%
5 320
 
3.0%
7 314
 
2.9%
Other values (7) 1099
 
10.2%
Latin
ValueCountFrequency (%)
K 37
17.1%
B 36
16.6%
S 29
13.4%
A 21
9.7%
E 16
7.4%
W 15
6.9%
I 15
6.9%
V 15
6.9%
C 14
 
6.5%
e 8
 
3.7%
Other values (4) 11
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15010
57.6%
ASCII 11038
42.4%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4072
36.9%
1 1208
 
10.9%
, 776
 
7.0%
( 750
 
6.8%
) 750
 
6.8%
2 548
 
5.0%
0 530
 
4.8%
3 457
 
4.1%
5 320
 
2.9%
7 314
 
2.8%
Other values (20) 1313
 
11.9%
Hangul
ValueCountFrequency (%)
동 1851
 
12.3%
래 901
 
6.0%
시 857
 
5.7%
산 776
 
5.2%
역 753
 
5.0%
부 752
 
5.0%
광 750
 
5.0%
로 748
 
5.0%
구 747
 
5.0%
번 391
 
2.6%
Other values (191) 6484
43.2%
None
ValueCountFrequency (%)
· 3
100.0%

행정동
Categorical

Distinct14
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
온천제1동
110 
명륜동
85 
온천제2동
83 
수민동
80 
온천제3동
67 
Other values (9)
322 

Length

Max length5
Median length5
Mean length4.4605087
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row온천제1동
2nd row명장제2동
3rd row안락제2동
4th row사직제1동
5th row온천제2동

Common Values

ValueCountFrequency (%)
온천제1동 110
14.7%
명륜동 85
11.4%
온천제2동 83
11.1%
수민동 80
10.7%
온천제3동 67
9.0%
사직제3동 54
7.2%
안락제2동 50
6.7%
사직제2동 50
6.7%
안락제1동 39
 
5.2%
사직제1동 33
 
4.4%
Other values (4) 96
12.9%

Length

2023-12-11T01:53:50.406021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
온천제1동 110
14.7%
명륜동 85
11.4%
온천제2동 83
11.1%
수민동 80
10.7%
온천제3동 67
9.0%
사직제3동 54
7.2%
안락제2동 50
6.7%
사직제2동 50
6.7%
안락제1동 39
 
5.2%
사직제1동 33
 
4.4%
Other values (4) 96
12.9%

Missing values

2023-12-11T01:53:44.684921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:53:44.870135image/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

등록번호사무소명중개업자명사무소전화번호사무소주소행정동
0나-06-652제일부동산중개사무소손덕수051-552-9001부산광역시 동래구 차밭골로 9, 102호 (온천동)온천제1동
1나-06-343제일부동산중개사무소송욱명051-525-6812부산광역시 동래구 반송로 287-8 (명장동)명장제2동
2나-06-292한라부동산중개사무소장이수051-521-0005부산광역시 동래구 명안로 4 (안락동)안락제2동
3가-06-4180의령부동산중개사무소김정애051-502-4444부산광역시 동래구 사직북로48번길 12 (사직동)사직제1동
4가-06-1892럭키3.1부동산중개사무소정정숙051-552-3131부산광역시 동래구 충렬대로107번길 54, 상가동 1-1호 (온천동,럭키아파트)온천제2동
5가-06-1601삼성부동산중개사무소김희도051-504-7757부산광역시 동래구 여고로113번길 26 (사직동)사직제3동
6가-06-1780동래부동산중개사무소안영기051-555-8849부산광역시 동래구 동래로148번길 23 (복천동)복산동
7가-06-1875한주부동산중개사무소김평남051-529-3232부산광역시 동래구 안락로 9 (안락동)안락제1동
8가-06-1315한성부동산중개사무소이향화051-553-3300부산광역시 동래구 충렬대로 318, A상가 102호 (낙민동)수민동
9가-14-374으뜸공인중개사사무소주양숙051-524-0108부산광역시 동래구 충렬대로459번길 38 (안락동)안락제2동
등록번호사무소명중개업자명사무소전화번호사무소주소행정동
737가-06-4552주식회사 뉴미래부동산중개공영호051-557-0661부산광역시 동래구 충렬대로 343 (안락동)안락제1동
73826260-2016-00186주식회사우주부동산중개이영준<NA>부산광역시 동래구 충렬대로 236 (수안동)수민동
73926260-2016-00203(주)바다부동산중개김권051-557-5200부산광역시 동래구 명륜로98번길 34, 2층 (수안동)수민동
74026260-2020-00235반도부동산중개법인주식회사이정란051-506-4006부산광역시 동래구 아시아드대로231번길 17 (온천동)온천제3동
74126260-2022-00099주식회사랜드멘토부동산중개법인이종화<NA>부산광역시 동래구 온천장로 109, 9층 (온천동, 불이빌딩)온천제1동
74226260-2021-00150도울부동산중개법인박수빈051-507-7774부산광역시 동래구 사직북로 42, 1층 (사직동)사직제1동
74326260-2022-00043주식회사 이화부동산중개법인유윤상<NA>부산광역시 동래구 연안로59번길 30, 101호 (안락동, 모스트빌)안락제2동
74426260-2022-00079오스카부동산중개법인 (주)우연정<NA>부산광역시 동래구 온천장로 108-6, 102호 (온천동, 오스카빌딩)온천제1동
74526260-2022-00092주식회사 거성부동산중개법인정유진051-927-8000부산광역시 동래구 명륜로207번길 41, 2층 (명륜동)<NA>
74626260-2021-00070성광디앤씨부동산중개법인이영한051-556-2227부산광역시 동래구 명륜로217번길 1, 1층 (명륜동)명륜동