Overview

Dataset statistics

Number of variables7
Number of observations780
Missing cells85
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.8 KiB
Average record size in memory56.2 B

Variable types

Text5
Categorical2

Dataset

Description경상남도 양산시 부동산 등록번호 중개업소명 , 중개업소종별, 중개업자명, 사무실연락처, 소재주소를 확인할 수 있습니다.
Author경상남도 양산시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3065863

Alerts

직위 has constant value ""Constant
중개업소종별 is highly imbalanced (94.1%)Imbalance
사무소전화번호 has 85 (10.9%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 07:06:56.854758
Analysis finished2024-04-21 07:06:58.200821
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct780
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-21T16:06:58.808213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length12.178205
Min length9

Characters and Unicode

Total characters9499
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

Unique780 ?
Unique (%)100.0%

Sample

1st row48330-2015-00026
2nd row48330-2015-00210
3rd row48330-2015-00223
4th row48330-2015-00173
5th row48330-2015-00031
ValueCountFrequency (%)
48330-2015-00026 1
 
0.1%
가4330-2459 1
 
0.1%
가4330-2214 1
 
0.1%
48330-2016-00091 1
 
0.1%
48330-2016-00057 1
 
0.1%
48330-2016-00035 1
 
0.1%
가4330-1737 1
 
0.1%
가4330-467 1
 
0.1%
48330-2015-00136 1
 
0.1%
48330-2015-00208 1
 
0.1%
Other values (770) 770
98.7%
2024-04-21T16:06:59.828186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2026
21.3%
3 1784
18.8%
- 1070
11.3%
4 1032
10.9%
1 802
 
8.4%
2 791
 
8.3%
가 490
 
5.2%
8 470
 
4.9%
5 374
 
3.9%
6 279
 
2.9%
Other values (3) 381
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7938
83.6%
Dash Punctuation 1070
 
11.3%
Other Letter 491
 
5.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2026
25.5%
3 1784
22.5%
4 1032
13.0%
1 802
 
10.1%
2 791
 
10.0%
8 470
 
5.9%
5 374
 
4.7%
6 279
 
3.5%
7 202
 
2.5%
9 178
 
2.2%
Other Letter
ValueCountFrequency (%)
가 490
99.8%
호 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 1070
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9008
94.8%
Hangul 491
 
5.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2026
22.5%
3 1784
19.8%
- 1070
11.9%
4 1032
11.5%
1 802
 
8.9%
2 791
 
8.8%
8 470
 
5.2%
5 374
 
4.2%
6 279
 
3.1%
7 202
 
2.2%
Hangul
ValueCountFrequency (%)
가 490
99.8%
호 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9008
94.8%
Hangul 491
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2026
22.5%
3 1784
19.8%
- 1070
11.9%
4 1032
11.5%
1 802
 
8.9%
2 791
 
8.8%
8 470
 
5.2%
5 374
 
4.2%
6 279
 
3.1%
7 202
 
2.2%
Hangul
ValueCountFrequency (%)
가 490
99.8%
호 1
 
0.2%

사무소명
Text

Distinct773
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-21T16:07:00.551661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length11.321795
Min length6

Characters and Unicode

Total characters8831
Distinct characters345
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique766 ?
Unique (%)98.2%

Sample

1st row(새)온누리공인중개사사무소
2nd row(신)온누리공인중개사사무소
3rd row(주)LBA양산부동산중개법인
4th row(주)타워부동산중개법인
5th row114공인중개사사무소
ValueCountFrequency (%)
신대동합동공인중개사사무소 2
 
0.3%
에이원합동공인중개사사무소 2
 
0.3%
sk합동공인중개사사무소 2
 
0.3%
큰길합동공인중개사사무소 2
 
0.3%
금성합동공인중개사사무소 2
 
0.3%
좋은사람합동공인중개사사무소 2
 
0.3%
114합동공인중개사사무소 2
 
0.3%
양산한결공인중개사사무소 1
 
0.1%
양산키움공인중개사사무소 1
 
0.1%
양산탑공인중개사사무소 1
 
0.1%
Other values (764) 764
97.8%
2024-04-21T16:07:01.494314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1503
17.0%
개 784
 
8.9%
중 781
 
8.8%
소 769
 
8.7%
무 763
 
8.6%
인 741
 
8.4%
공 730
 
8.3%
동 252
 
2.9%
산 245
 
2.8%
부 189
 
2.1%
Other values (335) 2074
23.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8700
98.5%
Uppercase Letter 49
 
0.6%
Decimal Number 41
 
0.5%
Lowercase Letter 23
 
0.3%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Other Punctuation 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1503
17.3%
개 784
9.0%
중 781
9.0%
소 769
 
8.8%
무 763
 
8.8%
인 741
 
8.5%
공 730
 
8.4%
동 252
 
2.9%
산 245
 
2.8%
부 189
 
2.2%
Other values (302) 1943
22.3%
Uppercase Letter
ValueCountFrequency (%)
K 9
18.4%
N 8
16.3%
O 7
14.3%
W 5
10.2%
E 5
10.2%
S 3
 
6.1%
L 2
 
4.1%
J 2
 
4.1%
T 2
 
4.1%
G 1
 
2.0%
Other values (5) 5
10.2%
Decimal Number
ValueCountFrequency (%)
1 12
29.3%
4 10
24.4%
2 8
19.5%
3 4
 
9.8%
8 4
 
9.8%
5 3
 
7.3%
Lowercase Letter
ValueCountFrequency (%)
e 12
52.2%
w 5
21.7%
c 2
 
8.7%
h 2
 
8.7%
k 1
 
4.3%
n 1
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
· 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8698
98.5%
Latin 72
 
0.8%
Common 59
 
0.7%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1503
17.3%
개 784
9.0%
중 781
9.0%
소 769
 
8.8%
무 763
 
8.8%
인 741
 
8.5%
공 730
 
8.4%
동 252
 
2.9%
산 245
 
2.8%
부 189
 
2.2%
Other values (300) 1941
22.3%
Latin
ValueCountFrequency (%)
e 12
16.7%
K 9
12.5%
N 8
11.1%
O 7
9.7%
W 5
 
6.9%
E 5
 
6.9%
w 5
 
6.9%
S 3
 
4.2%
L 2
 
2.8%
J 2
 
2.8%
Other values (11) 14
19.4%
Common
ValueCountFrequency (%)
1 12
20.3%
4 10
16.9%
2 8
13.6%
) 6
10.2%
( 6
10.2%
3 4
 
6.8%
8 4
 
6.8%
5 3
 
5.1%
- 2
 
3.4%
, 2
 
3.4%
Other values (2) 2
 
3.4%
Han
ValueCountFrequency (%)
眞 1
50.0%
安 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8698
98.5%
ASCII 130
 
1.5%
CJK 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1503
17.3%
개 784
9.0%
중 781
9.0%
소 769
 
8.8%
무 763
 
8.8%
인 741
 
8.5%
공 730
 
8.4%
동 252
 
2.9%
산 245
 
2.8%
부 189
 
2.2%
Other values (300) 1941
22.3%
ASCII
ValueCountFrequency (%)
1 12
 
9.2%
e 12
 
9.2%
4 10
 
7.7%
K 9
 
6.9%
N 8
 
6.2%
2 8
 
6.2%
O 7
 
5.4%
) 6
 
4.6%
( 6
 
4.6%
W 5
 
3.8%
Other values (22) 47
36.2%
CJK
ValueCountFrequency (%)
眞 1
50.0%
安 1
50.0%
None
ValueCountFrequency (%)
· 1
100.0%

중개업소종별
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
공인중개사
772 
법인
 
4
중개인
 
4

Length

Max length5
Median length5
Mean length4.974359
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공인중개사
2nd row공인중개사
3rd row법인
4th row법인
5th row공인중개사

Common Values

ValueCountFrequency (%)
공인중개사 772
99.0%
법인 4
 
0.5%
중개인 4
 
0.5%

Length

2024-04-21T16:07:01.759150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:07:01.968171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 772
99.0%
법인 4
 
0.5%
중개인 4
 
0.5%

중개업자명
Text

Distinct755
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-21T16:07:03.184170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9987179
Min length2

Characters and Unicode

Total characters2339
Distinct characters190
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique736 ?
Unique (%)94.4%

Sample

1st row박인만
2nd row김경표
3rd row문상호
4th row김정호
5th row김문정
ValueCountFrequency (%)
김지영 4
 
0.5%
김경희 4
 
0.5%
김경화 3
 
0.4%
김정미 3
 
0.4%
이숙희 2
 
0.3%
박미정 2
 
0.3%
김현주 2
 
0.3%
김도은 2
 
0.3%
이정자 2
 
0.3%
김정태 2
 
0.3%
Other values (745) 754
96.7%
2024-04-21T16:07:04.690661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 187
 
8.0%
이 119
 
5.1%
정 117
 
5.0%
영 81
 
3.5%
희 70
 
3.0%
숙 66
 
2.8%
경 62
 
2.7%
박 59
 
2.5%
미 54
 
2.3%
수 40
 
1.7%
Other values (180) 1484
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2339
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 187
 
8.0%
이 119
 
5.1%
정 117
 
5.0%
영 81
 
3.5%
희 70
 
3.0%
숙 66
 
2.8%
경 62
 
2.7%
박 59
 
2.5%
미 54
 
2.3%
수 40
 
1.7%
Other values (180) 1484
63.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2339
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 187
 
8.0%
이 119
 
5.1%
정 117
 
5.0%
영 81
 
3.5%
희 70
 
3.0%
숙 66
 
2.8%
경 62
 
2.7%
박 59
 
2.5%
미 54
 
2.3%
수 40
 
1.7%
Other values (180) 1484
63.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2339
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 187
 
8.0%
이 119
 
5.1%
정 117
 
5.0%
영 81
 
3.5%
희 70
 
3.0%
숙 66
 
2.8%
경 62
 
2.7%
박 59
 
2.5%
미 54
 
2.3%
수 40
 
1.7%
Other values (180) 1484
63.4%

직위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
대표
780 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대표 780
100.0%

Length

2024-04-21T16:07:05.093878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:07:05.397832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대표 780
100.0%

사무소전화번호
Text

MISSING 

Distinct654
Distinct (%)94.1%
Missing85
Missing (%)10.9%
Memory size6.2 KiB
2024-04-21T16:07:06.189999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length12
Mean length12.027338
Min length9

Characters and Unicode

Total characters8359
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique616 ?
Unique (%)88.6%

Sample

1st row055-374-8953
2nd row055-362-6622
3rd row055-379-8800
4th row055-366-1114
5th row055-388-9114
ValueCountFrequency (%)
055-383-3001 4
 
0.6%
055-388-5511 3
 
0.4%
055-388-0369 2
 
0.3%
055-367-0002 2
 
0.3%
055-367-0016 2
 
0.3%
055-382-3800 2
 
0.3%
055-387-7007 2
 
0.3%
055-362-7744 2
 
0.3%
055-381-1962 2
 
0.3%
055-366-3600 2
 
0.3%
Other values (644) 672
96.7%
2024-04-21T16:07:07.441001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1710
20.5%
- 1391
16.6%
0 1360
16.3%
3 1018
12.2%
8 697
8.3%
6 591
 
7.1%
7 375
 
4.5%
2 316
 
3.8%
4 316
 
3.8%
9 303
 
3.6%
Other values (2) 282
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6964
83.3%
Dash Punctuation 1391
 
16.6%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1710
24.6%
0 1360
19.5%
3 1018
14.6%
8 697
10.0%
6 591
 
8.5%
7 375
 
5.4%
2 316
 
4.5%
4 316
 
4.5%
9 303
 
4.4%
1 278
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 1391
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1710
20.5%
- 1391
16.6%
0 1360
16.3%
3 1018
12.2%
8 697
8.3%
6 591
 
7.1%
7 375
 
4.5%
2 316
 
3.8%
4 316
 
3.8%
9 303
 
3.6%
Other values (2) 282
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1710
20.5%
- 1391
16.6%
0 1360
16.3%
3 1018
12.2%
8 697
8.3%
6 591
 
7.1%
7 375
 
4.5%
2 316
 
3.8%
4 316
 
3.8%
9 303
 
3.6%
Other values (2) 282
 
3.4%

소재지주소
Text

Distinct688
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-04-21T16:07:08.478219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length42
Mean length28.962821
Min length14

Characters and Unicode

Total characters22591
Distinct characters249
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

Unique608 ?
Unique (%)77.9%

Sample

1st row경상남도 양산시 상북면 양산대로 1228
2nd row경상남도 양산시 상북면 양산대로 1228
3rd row경상남도 양산시 동면 금오7길 2
4th row경상남도 양산시 물금읍 야리로 90, 313동 106호(대방노블랜드연리지3차)
5th row경상남도 양산시 북안남3길 39-1
ValueCountFrequency (%)
경상남도 780
 
18.2%
양산시 780
 
18.2%
물금읍 330
 
7.7%
상가 83
 
1.9%
동면 75
 
1.7%
상가동 66
 
1.5%
양주로 37
 
0.9%
야리로 32
 
0.7%
물금로 31
 
0.7%
범어로 31
 
0.7%
Other values (953) 2043
47.6%
2024-04-21T16:07:10.047325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3508
 
15.5%
1 1139
 
5.0%
상 1074
 
4.8%
산 969
 
4.3%
양 907
 
4.0%
남 860
 
3.8%
도 835
 
3.7%
시 824
 
3.6%
경 786
 
3.5%
동 668
 
3.0%
Other values (239) 11021
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13663
60.5%
Decimal Number 3580
 
15.8%
Space Separator 3508
 
15.5%
Open Punctuation 575
 
2.5%
Close Punctuation 572
 
2.5%
Other Punctuation 519
 
2.3%
Dash Punctuation 101
 
0.4%
Uppercase Letter 48
 
0.2%
Lowercase Letter 24
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1074
 
7.9%
산 969
 
7.1%
양 907
 
6.6%
남 860
 
6.3%
도 835
 
6.1%
시 824
 
6.0%
경 786
 
5.8%
동 668
 
4.9%
로 541
 
4.0%
호 514
 
3.8%
Other values (209) 5685
41.6%
Decimal Number
ValueCountFrequency (%)
1 1139
31.8%
0 463
12.9%
3 381
 
10.6%
2 357
 
10.0%
5 260
 
7.3%
4 254
 
7.1%
6 198
 
5.5%
7 192
 
5.4%
9 173
 
4.8%
8 163
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 19
39.6%
A 12
25.0%
N 4
 
8.3%
G 4
 
8.3%
C 3
 
6.2%
E 3
 
6.2%
I 2
 
4.2%
D 1
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 20
83.3%
y 1
 
4.2%
i 1
 
4.2%
t 1
 
4.2%
c 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 518
99.8%
@ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3508
100.0%
Open Punctuation
ValueCountFrequency (%)
( 575
100.0%
Close Punctuation
ValueCountFrequency (%)
) 572
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13663
60.5%
Common 8855
39.2%
Latin 73
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1074
 
7.9%
산 969
 
7.1%
양 907
 
6.6%
남 860
 
6.3%
도 835
 
6.1%
시 824
 
6.0%
경 786
 
5.8%
동 668
 
4.9%
로 541
 
4.0%
호 514
 
3.8%
Other values (209) 5685
41.6%
Common
ValueCountFrequency (%)
3508
39.6%
1 1139
 
12.9%
( 575
 
6.5%
) 572
 
6.5%
, 518
 
5.8%
0 463
 
5.2%
3 381
 
4.3%
2 357
 
4.0%
5 260
 
2.9%
4 254
 
2.9%
Other values (6) 828
 
9.4%
Latin
ValueCountFrequency (%)
e 20
27.4%
B 19
26.0%
A 12
16.4%
N 4
 
5.5%
G 4
 
5.5%
C 3
 
4.1%
E 3
 
4.1%
I 2
 
2.7%
y 1
 
1.4%
Ⅱ 1
 
1.4%
Other values (4) 4
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13663
60.5%
ASCII 8927
39.5%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3508
39.3%
1 1139
 
12.8%
( 575
 
6.4%
) 572
 
6.4%
, 518
 
5.8%
0 463
 
5.2%
3 381
 
4.3%
2 357
 
4.0%
5 260
 
2.9%
4 254
 
2.8%
Other values (19) 900
 
10.1%
Hangul
ValueCountFrequency (%)
상 1074
 
7.9%
산 969
 
7.1%
양 907
 
6.6%
남 860
 
6.3%
도 835
 
6.1%
시 824
 
6.0%
경 786
 
5.8%
동 668
 
4.9%
로 541
 
4.0%
호 514
 
3.8%
Other values (209) 5685
41.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

Missing values

2024-04-21T16:06:57.667525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T16:06:58.052742image/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

등록번호사무소명중개업소종별중개업자명직위사무소전화번호소재지주소
048330-2015-00026(새)온누리공인중개사사무소공인중개사박인만대표055-374-8953경상남도 양산시 상북면 양산대로 1228
148330-2015-00210(신)온누리공인중개사사무소공인중개사김경표대표<NA>경상남도 양산시 상북면 양산대로 1228
248330-2015-00223(주)LBA양산부동산중개법인법인문상호대표055-362-6622경상남도 양산시 동면 금오7길 2
348330-2015-00173(주)타워부동산중개법인법인김정호대표055-379-8800경상남도 양산시 물금읍 야리로 90, 313동 106호(대방노블랜드연리지3차)
448330-2015-00031114공인중개사사무소공인중개사김문정대표055-366-1114경상남도 양산시 북안남3길 39-1
5가4330-1936114합동공인중개사사무소공인중개사송경희대표055-388-9114경상남도 양산시 북정로 58(북정동)
6가4330-1972114합동공인중개사사무소공인중개사나혜영대표055-367-3337경상남도 양산시 북정로 58(북정동)
7가4330-229725시공인중개사사무소공인중개사고정희대표055-387-2526경상남도 양산시 신명동로 9(명동)
848330-2016-000584단지부동산공인중개사사무소공인중개사조삼미대표<NA>경상남도 양산시 양주로 115, 상가동 102호(중부동, 양산신도시주공아파트)
9가4330-23888단지공인중개사사무소공인중개사김미선대표055-366-8898경상남도 양산시 양주로 39, 상가105호(남부동, 주공8단지아파트)
등록번호사무소명중개업소종별중개업자명직위사무소전화번호소재지주소
770가4330-1485황산공인중개사사무소공인중개사윤한섭대표055-387-9114경상남도 양산시 물금읍 범어로 30-1(물금읍)
771가4330-2173황소공인중개사사무소공인중개사전정환대표055-365-0400경상남도 양산시 양주로 110, 상가 107호(중부동, 현대아파트)
772가4330-1883황토공인중개사사무소공인중개사김경학대표055-382-7701경상남도 양산시 북정1길 46(북정동)
773가4330-2242황하수공인중개사사무소공인중개사황하수대표055-366-0031경상남도 양산시 서창동1길 5(삼호동)
77448330-2015-00144효성부동산공인중개사사무소공인중개사김도희대표055-365-5454경상남도 양산시 물금읍 범어로 29, 상가동 103호(효성백년가약아파트)
77548330-2015-00202효성부동산합동공인중개사사무소공인중개사주정화대표055-365-5454경상남도 양산시 물금읍 범어로 29, 상가동 103호(효성백년가약아파트)
776가4330-1832효원공인중개사사무소공인중개사신상철대표055-374-9434경상남도 양산시 상북면 공암길 24, 202호(일양종합상가)
777가4330-1980효자부동산공인중개사사무소공인중개사김혜정대표055-384-4949경상남도 양산시 중앙로 117
77848330-2015-00069효정공인중개사사무소공인중개사안미숙대표055-366-0067경상남도 양산시 양주로 99, 상가동 102호(남부동, 쌍용아파트)
779가4330-2347희망공인중개사사무소공인중개사김부기대표055-367-8040경상남도 양산시 물금읍 물금로 165