Overview

Dataset statistics

Number of variables7
Number of observations901
Missing cells227
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.4 KiB
Average record size in memory56.1 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 (96.5%)Imbalance
사무소전화번호 has 227 (25.2%) missing valuesMissing

Reproduction

Analysis started2024-04-21 07:06:24.948859
Analysis finished2024-04-21 07:06:26.404337
Duration1.46 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

Distinct900
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-21T16:06:27.095786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length14.157603
Min length9

Characters and Unicode

Total characters12756
Distinct characters13
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

Unique899 ?
Unique (%)99.8%

Sample

1st row48330-2015-00003
2nd row48330-2015-00004
3rd row48330-2015-00005
4th row48330-2015-00017
5th row48330-2015-00031
ValueCountFrequency (%)
가 5
 
0.6%
48330-2022-00061 2
 
0.2%
48330-2022-00043 1
 
0.1%
48330-2022-00088 1
 
0.1%
48330-2022-00064 1
 
0.1%
48330-2022-00065 1
 
0.1%
48330-2022-00066 1
 
0.1%
48330-2022-00067 1
 
0.1%
48330-2022-00068 1
 
0.1%
48330-2022-00069 1
 
0.1%
Other values (891) 891
98.3%
2024-04-21T16:06:28.179326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3454
27.1%
3 2044
16.0%
- 1530
12.0%
2 1378
 
10.8%
4 1139
 
8.9%
1 1004
 
7.9%
8 873
 
6.8%
7 275
 
2.2%
가 272
 
2.1%
6 268
 
2.1%
Other values (3) 519
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10949
85.8%
Dash Punctuation 1530
 
12.0%
Other Letter 272
 
2.1%
Space Separator 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3454
31.5%
3 2044
18.7%
2 1378
 
12.6%
4 1139
 
10.4%
1 1004
 
9.2%
8 873
 
8.0%
7 275
 
2.5%
6 268
 
2.4%
5 268
 
2.4%
9 246
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 1530
100.0%
Other Letter
ValueCountFrequency (%)
가 272
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12484
97.9%
Hangul 272
 
2.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3454
27.7%
3 2044
16.4%
- 1530
12.3%
2 1378
 
11.0%
4 1139
 
9.1%
1 1004
 
8.0%
8 873
 
7.0%
7 275
 
2.2%
6 268
 
2.1%
5 268
 
2.1%
Other values (2) 251
 
2.0%
Hangul
ValueCountFrequency (%)
가 272
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12484
97.9%
Hangul 272
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3454
27.7%
3 2044
16.4%
- 1530
12.3%
2 1378
 
11.0%
4 1139
 
9.1%
1 1004
 
8.0%
8 873
 
7.0%
7 275
 
2.2%
6 268
 
2.1%
5 268
 
2.1%
Other values (2) 251
 
2.0%
Hangul
ValueCountFrequency (%)
가 272
100.0%

사무소명
Text

Distinct896
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-21T16:06:28.981718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length11.607103
Min length7

Characters and Unicode

Total characters10458
Distinct characters392
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

Unique891 ?
Unique (%)98.9%

Sample

1st row통도공인중개사사무소
2nd row보라부동산공인중개사사무소
3rd row소주대동공인중개사사무소
4th row복받는공인중개사사무소
5th row114공인중개사사무소
ValueCountFrequency (%)
114합동공인중개사사무소 2
 
0.2%
상지부동산중개법인 2
 
0.2%
신대동합동공인중개사사무소 2
 
0.2%
좋은사람합동공인중개사사무소 2
 
0.2%
sk합동공인중개사사무소 2
 
0.2%
주식회사 2
 
0.2%
사송더샵공감부동산공인중개사사무소 1
 
0.1%
the골드공인중개사사무소 1
 
0.1%
한국부동산공인중개사사무소 1
 
0.1%
가금공인중개사사무소 1
 
0.1%
Other values (890) 890
98.2%
2024-04-21T16:06:30.137769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 1723
16.5%
개 905
 
8.7%
중 903
 
8.6%
소 873
 
8.3%
무 871
 
8.3%
인 834
 
8.0%
공 819
 
7.8%
산 348
 
3.3%
동 314
 
3.0%
부 266
 
2.5%
Other values (382) 2602
24.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10265
98.2%
Uppercase Letter 67
 
0.6%
Decimal Number 66
 
0.6%
Lowercase Letter 37
 
0.4%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%
Space Separator 5
 
< 0.1%
Other Punctuation 3
 
< 0.1%
Math Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 1723
16.8%
개 905
 
8.8%
중 903
 
8.8%
소 873
 
8.5%
무 871
 
8.5%
인 834
 
8.1%
공 819
 
8.0%
산 348
 
3.4%
동 314
 
3.1%
부 266
 
2.6%
Other values (345) 2409
23.5%
Uppercase Letter
ValueCountFrequency (%)
K 13
19.4%
T 8
11.9%
N 7
10.4%
O 6
9.0%
C 6
9.0%
E 6
9.0%
W 4
 
6.0%
G 4
 
6.0%
S 3
 
4.5%
M 2
 
3.0%
Other values (5) 8
11.9%
Decimal Number
ValueCountFrequency (%)
1 17
25.8%
2 11
16.7%
4 9
13.6%
8 9
13.6%
5 8
12.1%
3 7
10.6%
6 4
 
6.1%
7 1
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
e 17
45.9%
h 7
18.9%
c 4
 
10.8%
w 4
 
10.8%
n 2
 
5.4%
k 2
 
5.4%
t 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
& 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10257
98.1%
Latin 104
 
1.0%
Common 89
 
0.9%
Han 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 1723
16.8%
개 905
 
8.8%
중 903
 
8.8%
소 873
 
8.5%
무 871
 
8.5%
인 834
 
8.1%
공 819
 
8.0%
산 348
 
3.4%
동 314
 
3.1%
부 266
 
2.6%
Other values (339) 2401
23.4%
Latin
ValueCountFrequency (%)
e 17
16.3%
K 13
12.5%
T 8
 
7.7%
h 7
 
6.7%
N 7
 
6.7%
O 6
 
5.8%
C 6
 
5.8%
E 6
 
5.8%
W 4
 
3.8%
G 4
 
3.8%
Other values (12) 26
25.0%
Common
ValueCountFrequency (%)
1 17
19.1%
2 11
12.4%
4 9
10.1%
8 9
10.1%
5 8
9.0%
3 7
7.9%
( 6
 
6.7%
) 6
 
6.7%
5
 
5.6%
6 4
 
4.5%
Other values (5) 7
7.9%
Han
ValueCountFrequency (%)
世 2
25.0%
上 2
25.0%
玉 1
12.5%
眞 1
12.5%
新 1
12.5%
多 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10257
98.1%
ASCII 193
 
1.8%
CJK 8
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 1723
16.8%
개 905
 
8.8%
중 903
 
8.8%
소 873
 
8.5%
무 871
 
8.5%
인 834
 
8.1%
공 819
 
8.0%
산 348
 
3.4%
동 314
 
3.1%
부 266
 
2.6%
Other values (339) 2401
23.4%
ASCII
ValueCountFrequency (%)
1 17
 
8.8%
e 17
 
8.8%
K 13
 
6.7%
2 11
 
5.7%
4 9
 
4.7%
8 9
 
4.7%
T 8
 
4.1%
5 8
 
4.1%
h 7
 
3.6%
N 7
 
3.6%
Other values (27) 87
45.1%
CJK
ValueCountFrequency (%)
世 2
25.0%
上 2
25.0%
玉 1
12.5%
眞 1
12.5%
新 1
12.5%
多 1
12.5%

중개업소종별
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
공인중개사
896 
법인
 
3
중개인
 
2

Length

Max length5
Median length5
Mean length4.9855716
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 896
99.4%
법인 3
 
0.3%
중개인 2
 
0.2%

Length

2024-04-21T16:06:30.394378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:06:30.584338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 896
99.4%
법인 3
 
0.3%
중개인 2
 
0.2%

중개업자명
Text

Distinct871
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-21T16:06:31.787888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9988901
Min length2

Characters and Unicode

Total characters2702
Distinct characters189
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

Unique844 ?
Unique (%)93.7%

Sample

1st row김경창
2nd row박종성
3rd row김정숙
4th row안명관
5th row김문정
ValueCountFrequency (%)
김정미 3
 
0.3%
박정희 3
 
0.3%
김경희 3
 
0.3%
김현주 2
 
0.2%
이미영 2
 
0.2%
김혜정 2
 
0.2%
김미정 2
 
0.2%
김정화 2
 
0.2%
김수현 2
 
0.2%
이영희 2
 
0.2%
Other values (861) 878
97.4%
2024-04-21T16:06:33.426764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 197
 
7.3%
정 133
 
4.9%
이 127
 
4.7%
영 81
 
3.0%
희 77
 
2.8%
박 70
 
2.6%
미 68
 
2.5%
숙 67
 
2.5%
경 63
 
2.3%
최 54
 
2.0%
Other values (179) 1765
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2702
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 197
 
7.3%
정 133
 
4.9%
이 127
 
4.7%
영 81
 
3.0%
희 77
 
2.8%
박 70
 
2.6%
미 68
 
2.5%
숙 67
 
2.5%
경 63
 
2.3%
최 54
 
2.0%
Other values (179) 1765
65.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2702
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 197
 
7.3%
정 133
 
4.9%
이 127
 
4.7%
영 81
 
3.0%
희 77
 
2.8%
박 70
 
2.6%
미 68
 
2.5%
숙 67
 
2.5%
경 63
 
2.3%
최 54
 
2.0%
Other values (179) 1765
65.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2702
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 197
 
7.3%
정 133
 
4.9%
이 127
 
4.7%
영 81
 
3.0%
희 77
 
2.8%
박 70
 
2.6%
미 68
 
2.5%
숙 67
 
2.5%
경 63
 
2.3%
최 54
 
2.0%
Other values (179) 1765
65.3%

직위
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
대표
901 

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 901
100.0%

Length

2024-04-21T16:06:33.669951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T16:06:33.950243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대표 901
100.0%

사무소전화번호
Text

MISSING 

Distinct648
Distinct (%)96.1%
Missing227
Missing (%)25.2%
Memory size7.2 KiB
2024-04-21T16:06:34.818793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.022255
Min length12

Characters and Unicode

Total characters8103
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

Unique622 ?
Unique (%)92.3%

Sample

1st row055-382-7266
2nd row055-363-1000
3rd row055-362-7088
4th row055-384-4090
5th row055-366-1114
ValueCountFrequency (%)
055-367-0011 2
 
0.3%
055-366-7722 2
 
0.3%
055-364-8844 2
 
0.3%
055 2
 
0.3%
055-366-0888 2
 
0.3%
055-372-7007 2
 
0.3%
055-388-9114 2
 
0.3%
055-912-4545 2
 
0.3%
055-384-0055 2
 
0.3%
055-362-0550 2
 
0.3%
Other values (639) 656
97.0%
2024-04-21T16:06:36.160794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1682
20.8%
- 1348
16.6%
0 1327
16.4%
3 976
12.0%
8 616
 
7.6%
6 585
 
7.2%
7 343
 
4.2%
1 328
 
4.0%
2 327
 
4.0%
9 280
 
3.5%
Other values (2) 291
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6740
83.2%
Dash Punctuation 1348
 
16.6%
Control 15
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1682
25.0%
0 1327
19.7%
3 976
14.5%
8 616
 
9.1%
6 585
 
8.7%
7 343
 
5.1%
1 328
 
4.9%
2 327
 
4.9%
9 280
 
4.2%
4 276
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1348
100.0%
Control
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8103
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1682
20.8%
- 1348
16.6%
0 1327
16.4%
3 976
12.0%
8 616
 
7.6%
6 585
 
7.2%
7 343
 
4.2%
1 328
 
4.0%
2 327
 
4.0%
9 280
 
3.5%
Other values (2) 291
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8103
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1682
20.8%
- 1348
16.6%
0 1327
16.4%
3 976
12.0%
8 616
 
7.6%
6 585
 
7.2%
7 343
 
4.2%
1 328
 
4.0%
2 327
 
4.0%
9 280
 
3.5%
Other values (2) 291
 
3.6%

소재지주소
Text

Distinct841
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size7.2 KiB
2024-04-21T16:06:37.430158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length45
Mean length29.900111
Min length14

Characters and Unicode

Total characters26940
Distinct characters272
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique786 ?
Unique (%)87.2%

Sample

1st row경상남도 양산시 하북면 통도사로 51
2nd row경상남도 양산시 물금읍 범구로 48
3rd row경상남도 양산시 소주로 180
4th row경상남도 양산시 물금읍 백호로 91 , 상가B동 116호(반도유보라4차아파트)
5th row경상남도 양산시 북안남3길 39-1
ValueCountFrequency (%)
경상남도 901
 
15.4%
양산시 901
 
15.4%
물금읍 378
 
6.5%
233
 
4.0%
1층 228
 
3.9%
일부 189
 
3.2%
상가동 135
 
2.3%
동면 120
 
2.0%
백호로 43
 
0.7%
상북면 41
 
0.7%
Other values (959) 2691
45.9%
2024-04-21T16:06:39.191774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4959
18.4%
1 1629
 
6.0%
상 1199
 
4.5%
산 1186
 
4.4%
양 1109
 
4.1%
도 958
 
3.6%
시 958
 
3.6%
남 957
 
3.6%
경 906
 
3.4%
동 747
 
2.8%
Other values (262) 12332
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16032
59.5%
Space Separator 4959
 
18.4%
Decimal Number 4541
 
16.9%
Open Punctuation 440
 
1.6%
Close Punctuation 439
 
1.6%
Other Punctuation 364
 
1.4%
Dash Punctuation 105
 
0.4%
Uppercase Letter 32
 
0.1%
Lowercase Letter 28
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1199
 
7.5%
산 1186
 
7.4%
양 1109
 
6.9%
도 958
 
6.0%
시 958
 
6.0%
남 957
 
6.0%
경 906
 
5.7%
동 747
 
4.7%
로 607
 
3.8%
호 589
 
3.7%
Other values (230) 6816
42.5%
Lowercase Letter
ValueCountFrequency (%)
e 13
46.4%
c 5
 
17.9%
t 2
 
7.1%
l 1
 
3.6%
p 1
 
3.6%
h 1
 
3.6%
y 1
 
3.6%
i 1
 
3.6%
u 1
 
3.6%
k 1
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 1629
35.9%
0 571
 
12.6%
2 459
 
10.1%
3 408
 
9.0%
5 339
 
7.5%
4 312
 
6.9%
6 262
 
5.8%
7 221
 
4.9%
8 174
 
3.8%
9 166
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 19
59.4%
A 9
28.1%
D 2
 
6.2%
J 1
 
3.1%
K 1
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 363
99.7%
& 1
 
0.3%
Space Separator
ValueCountFrequency (%)
4959
100.0%
Open Punctuation
ValueCountFrequency (%)
( 440
100.0%
Close Punctuation
ValueCountFrequency (%)
) 439
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16032
59.5%
Common 10848
40.3%
Latin 60
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1199
 
7.5%
산 1186
 
7.4%
양 1109
 
6.9%
도 958
 
6.0%
시 958
 
6.0%
남 957
 
6.0%
경 906
 
5.7%
동 747
 
4.7%
로 607
 
3.8%
호 589
 
3.7%
Other values (230) 6816
42.5%
Common
ValueCountFrequency (%)
4959
45.7%
1 1629
 
15.0%
0 571
 
5.3%
2 459
 
4.2%
( 440
 
4.1%
) 439
 
4.0%
3 408
 
3.8%
, 363
 
3.3%
5 339
 
3.1%
4 312
 
2.9%
Other values (6) 929
 
8.6%
Latin
ValueCountFrequency (%)
B 19
31.7%
e 13
21.7%
A 9
15.0%
c 5
 
8.3%
D 2
 
3.3%
t 2
 
3.3%
l 1
 
1.7%
p 1
 
1.7%
h 1
 
1.7%
y 1
 
1.7%
Other values (6) 6
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16032
59.5%
ASCII 10908
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4959
45.5%
1 1629
 
14.9%
0 571
 
5.2%
2 459
 
4.2%
( 440
 
4.0%
) 439
 
4.0%
3 408
 
3.7%
, 363
 
3.3%
5 339
 
3.1%
4 312
 
2.9%
Other values (22) 989
 
9.1%
Hangul
ValueCountFrequency (%)
상 1199
 
7.5%
산 1186
 
7.4%
양 1109
 
6.9%
도 958
 
6.0%
시 958
 
6.0%
남 957
 
6.0%
경 906
 
5.7%
동 747
 
4.7%
로 607
 
3.8%
호 589
 
3.7%
Other values (230) 6816
42.5%

Missing values

2024-04-21T16:06:25.833738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T16:06:26.248311image/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
048330-2015-00003통도공인중개사사무소공인중개사김경창대표055-382-7266경상남도 양산시 하북면 통도사로 51
148330-2015-00004보라부동산공인중개사사무소공인중개사박종성대표055-363-1000경상남도 양산시 물금읍 범구로 48
248330-2015-00005소주대동공인중개사사무소공인중개사김정숙대표055-362-7088경상남도 양산시 소주로 180
348330-2015-00017복받는공인중개사사무소공인중개사안명관대표055-384-4090경상남도 양산시 물금읍 백호로 91 , 상가B동 116호(반도유보라4차아파트)
448330-2015-00031114공인중개사사무소공인중개사김문정대표055-366-1114경상남도 양산시 북안남3길 39-1
548330-2015-00032샤인공인중개사사무소공인중개사김상숙대표055-364-0049경상남도 양산시 물금읍 물금로 165 , 102호
648330-2015-00034삼성명가공인중개사사무소공인중개사장정숙대표055-364-9200경상남도 양산시 평산중앙로 74 (평산동)
748330-2015-00040정부동산공인중개사사무소공인중개사박정희대표055-383-8055경상남도 양산시 물금읍 부산대학로 144 102호(신양산코아루캠퍼스시티)
848330-2015-00043신대림공인중개사사무소공인중개사김춘애대표055-387-8887경상남도 양산시 물금읍 신주로 73 ,상가 101호(신창비바패밀리)
948330-2015-00044캐슬공인중개사사무소공인중개사손용화대표055-364-0070경상남도 양산시 진등길 26 상가동 B105호(주진동, 양산롯데캐슬)
등록번호사무소명중개업소종별중개업자명직위사무소전화번호소재지주소
891가4330-853덕계그린부동산중개사무소공인중개사이미화대표055-366-4489경상남도 양산시 신명로 88 상가105호(평산동,동일스위트1차)
892가4330-857명성공인중개사사무소공인중개사강태석대표055-367-1600경상남도 양산시 동면 금오7길 2 , 1층
893가4330-872벽산공인중개사사무소공인중개사김장호대표055-374-8000경상남도 양산시 상북면 상북중앙로 300
894가4330-878비젼21부동산컨설팅공인중개사사무소공인중개사강정식대표055-364-3131경상남도 양산시 중앙로 168 , 2층(북부동)
895가4330-895대동이미지공인중개사사무소공인중개사윤재한대표055-367-8899경상남도 양산시 대운로 352 상가동 101호(삼호동,대동이미지타운1단지)
896가4330-934대박공인중개사사무소공인중개사김영숙대표055-383-0049경상남도 양산시 물금읍 백호로 64 , 112호(센텀시티프라자)
897가4330-935삼보공인중개사사무소공인중개사신정화대표055-366-3230경상남도 양산시 물금읍 오봉로 169 , 상가동 405-1호(양산범어대동타운)
898가4330-948만경부동산공인중개사사무소공인중개사정병하대표055-383-8345경상남도 양산시 물금읍 황산로 647
899가4330-986주토공인중개사사무소공인중개사윤진국대표055-365-0025경상남도 양산시 동면 곡리1길 3
900가4330-995신바람공인중개사사무소공인중개사안복선대표055-385-2003경상남도 양산시 물금읍 황산로 709 ,102호(경민아파트 상가)