Overview

Dataset statistics

Number of variables8
Number of observations129
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory65.0 B

Variable types

Text5
DateTime1
Categorical2

Dataset

Description논산시 부동산중개업소 등록현황 파일데이터로 등록번호, 등록일자, 업소구분, 업소명, 행정동, 소재지도로명주소, 소재지지번주소, 전화번호 정보를 제공하고 있습니다.
Author충청남도 논산시
URLhttps://www.data.go.kr/data/3078244/fileData.do

Alerts

업소구분 is highly imbalanced (55.4%)Imbalance
등록번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:31:54.913573
Analysis finished2024-03-14 16:31:56.430486
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct129
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T01:31:57.235168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length10.44186
Min length1

Characters and Unicode

Total characters1347
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

Unique129 ?
Unique (%)100.0%

Sample

1st row7
2nd row9
3rd row18
4th row22
5th row23
ValueCountFrequency (%)
7 1
 
0.8%
44230-2016-00012 1
 
0.8%
44230-2020-00002 1
 
0.8%
44230-2020-00001 1
 
0.8%
44230-2019-00015 1
 
0.8%
44230-2019-00013 1
 
0.8%
44230-2019-00012 1
 
0.8%
44230-2019-00010 1
 
0.8%
44230-2019-00009 1
 
0.8%
44230-2019-00008 1
 
0.8%
Other values (119) 119
92.2%
2024-03-15T01:31:58.523382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 454
33.7%
2 230
17.1%
4 165
 
12.2%
- 150
 
11.1%
3 130
 
9.7%
1 93
 
6.9%
8 32
 
2.4%
9 26
 
1.9%
7 23
 
1.7%
5 23
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1197
88.9%
Dash Punctuation 150
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 454
37.9%
2 230
19.2%
4 165
 
13.8%
3 130
 
10.9%
1 93
 
7.8%
8 32
 
2.7%
9 26
 
2.2%
7 23
 
1.9%
5 23
 
1.9%
6 21
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1347
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 454
33.7%
2 230
17.1%
4 165
 
12.2%
- 150
 
11.1%
3 130
 
9.7%
1 93
 
6.9%
8 32
 
2.4%
9 26
 
1.9%
7 23
 
1.7%
5 23
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 454
33.7%
2 230
17.1%
4 165
 
12.2%
- 150
 
11.1%
3 130
 
9.7%
1 93
 
6.9%
8 32
 
2.4%
9 26
 
1.9%
7 23
 
1.7%
5 23
 
1.7%

등록일자
Date

Distinct125
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum1984-06-11 00:00:00
Maximum2023-10-19 00:00:00
2024-03-15T01:31:58.919072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:31:59.291130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
공인중개사
117 
중개인
12 

Length

Max length5
Median length5
Mean length4.8139535
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공인중개사 117
90.7%
중개인 12
 
9.3%

Length

2024-03-15T01:31:59.753206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:32:00.067583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 117
90.7%
중개인 12
 
9.3%

업소명
Text

Distinct127
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T01:32:00.788255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length9.8682171
Min length5

Characters and Unicode

Total characters1273
Distinct characters143
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)96.9%

Sample

1st row대명부동산중개인
2nd row벌곡신신부동산중개사무소
3rd row부적부동산중개인
4th row영진부동산사무소
5th row가야부동산중개인
ValueCountFrequency (%)
미소공인중개사사무소 2
 
1.5%
중개사 2
 
1.5%
리벤하임공인중개사사무소 2
 
1.5%
바로부동산공인중개사사무소 1
 
0.8%
논산대성공인중개사 1
 
0.8%
논산박사공인중개사사무소 1
 
0.8%
신화공인중개사사무소 1
 
0.8%
다모인공인중개사사무소 1
 
0.8%
한일부동산중개인 1
 
0.8%
복돼지공인중개사사무소 1
 
0.8%
Other values (120) 120
90.2%
2024-03-15T01:32:01.980448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 212
16.7%
중 126
9.9%
개 125
9.8%
인 122
9.6%
공 114
 
9.0%
무 100
 
7.9%
소 100
 
7.9%
산 30
 
2.4%
동 26
 
2.0%
부 22
 
1.7%
Other values (133) 296
23.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1266
99.5%
Space Separator 4
 
0.3%
Uppercase Letter 2
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 212
16.7%
중 126
10.0%
개 125
9.9%
인 122
9.6%
공 114
 
9.0%
무 100
 
7.9%
소 100
 
7.9%
산 30
 
2.4%
동 26
 
2.1%
부 22
 
1.7%
Other values (129) 289
22.8%
Uppercase Letter
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1266
99.5%
Common 5
 
0.4%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 212
16.7%
중 126
10.0%
개 125
9.9%
인 122
9.6%
공 114
 
9.0%
무 100
 
7.9%
소 100
 
7.9%
산 30
 
2.4%
동 26
 
2.1%
부 22
 
1.7%
Other values (129) 289
22.8%
Common
ValueCountFrequency (%)
4
80.0%
1 1
 
20.0%
Latin
ValueCountFrequency (%)
O 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1266
99.5%
ASCII 7
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 212
16.7%
중 126
10.0%
개 125
9.9%
인 122
9.6%
공 114
 
9.0%
무 100
 
7.9%
소 100
 
7.9%
산 30
 
2.4%
동 26
 
2.1%
부 22
 
1.7%
Other values (129) 289
22.8%
ASCII
ValueCountFrequency (%)
4
57.1%
O 1
 
14.3%
K 1
 
14.3%
1 1
 
14.3%

행정동
Categorical

Distinct12
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
취암동
84 
연산면
18 
부창동
 
8
연무읍
 
5
상월면
 
3
Other values (7)
11 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)3.1%

Sample

1st row상월면
2nd row벌곡면
3rd row부적면
4th row취암동
5th row부창동

Common Values

ValueCountFrequency (%)
취암동 84
65.1%
연산면 18
 
14.0%
부창동 8
 
6.2%
연무읍 5
 
3.9%
상월면 3
 
2.3%
벌곡면 3
 
2.3%
은진면 2
 
1.6%
강경읍 2
 
1.6%
부적면 1
 
0.8%
광석면 1
 
0.8%
Other values (2) 2
 
1.6%

Length

2024-03-15T01:32:02.384275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취암동 84
65.1%
연산면 18
 
14.0%
부창동 8
 
6.2%
연무읍 5
 
3.9%
상월면 3
 
2.3%
벌곡면 3
 
2.3%
은진면 2
 
1.6%
강경읍 2
 
1.6%
부적면 1
 
0.8%
광석면 1
 
0.8%
Other values (2) 2
 
1.6%

소재지도로명주소
Text

Distinct117
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T01:32:03.720124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length19.72093
Min length14

Characters and Unicode

Total characters2544
Distinct characters92
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)83.7%

Sample

1st row충청남도 논산시 상월면 선비로 1089
2nd row충청남도 논산시 벌곡면 황룡재로 601
3rd row충청남도 논산시 부적면 덕평1길 32-5
4th row충청남도 논산시 시민로 322
5th row충청남도 논산시 해월로 35
ValueCountFrequency (%)
충청남도 129
22.7%
논산시 129
22.7%
중앙로 23
 
4.0%
연산면 18
 
3.2%
황산벌로 12
 
2.1%
시민로 12
 
2.1%
계백로 8
 
1.4%
연무읍 5
 
0.9%
시민로258번길 4
 
0.7%
시민로307번길 4
 
0.7%
Other values (158) 225
39.5%
2024-03-15T01:32:05.551482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
443
17.4%
산 161
 
6.3%
시 158
 
6.2%
청 130
 
5.1%
충 129
 
5.1%
남 129
 
5.1%
도 129
 
5.1%
논 129
 
5.1%
로 124
 
4.9%
1 122
 
4.8%
Other values (82) 890
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1527
60.0%
Decimal Number 522
 
20.5%
Space Separator 443
 
17.4%
Dash Punctuation 37
 
1.5%
Other Punctuation 11
 
0.4%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 161
10.5%
시 158
10.3%
청 130
 
8.5%
충 129
 
8.4%
남 129
 
8.4%
도 129
 
8.4%
논 129
 
8.4%
로 124
 
8.1%
번 46
 
3.0%
길 44
 
2.9%
Other values (67) 348
22.8%
Decimal Number
ValueCountFrequency (%)
1 122
23.4%
2 72
13.8%
3 61
11.7%
4 55
10.5%
8 45
 
8.6%
0 40
 
7.7%
9 39
 
7.5%
5 33
 
6.3%
7 28
 
5.4%
6 27
 
5.2%
Space Separator
ValueCountFrequency (%)
443
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1527
60.0%
Common 1017
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 161
10.5%
시 158
10.3%
청 130
 
8.5%
충 129
 
8.4%
남 129
 
8.4%
도 129
 
8.4%
논 129
 
8.4%
로 124
 
8.1%
번 46
 
3.0%
길 44
 
2.9%
Other values (67) 348
22.8%
Common
ValueCountFrequency (%)
443
43.6%
1 122
 
12.0%
2 72
 
7.1%
3 61
 
6.0%
4 55
 
5.4%
8 45
 
4.4%
0 40
 
3.9%
9 39
 
3.8%
- 37
 
3.6%
5 33
 
3.2%
Other values (5) 70
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1527
60.0%
ASCII 1017
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
443
43.6%
1 122
 
12.0%
2 72
 
7.1%
3 61
 
6.0%
4 55
 
5.4%
8 45
 
4.4%
0 40
 
3.9%
9 39
 
3.8%
- 37
 
3.6%
5 33
 
3.2%
Other values (5) 70
 
6.9%
Hangul
ValueCountFrequency (%)
산 161
10.5%
시 158
10.3%
청 130
 
8.5%
충 129
 
8.4%
남 129
 
8.4%
도 129
 
8.4%
논 129
 
8.4%
로 124
 
8.1%
번 46
 
3.0%
길 44
 
2.9%
Other values (67) 348
22.8%

소재지지번주소
Text

Distinct117
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T01:32:06.778830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28
Mean length21.689922
Min length14

Characters and Unicode

Total characters2798
Distinct characters96
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

Unique108 ?
Unique (%)83.7%

Sample

1st row충청남도 논산시 상월면 대우리 261-1번지
2nd row충청남도 논산시 벌곡면 한삼천리 243-8번지
3rd row충청남도 논산시 부적면 덕평리 331번지
4th row충청남도 논산시 취암동 460-30번지
5th row충청남도 논산시 부창동 314-7번지
ValueCountFrequency (%)
충청남도 129
22.8%
논산시 129
22.8%
취암동 48
 
8.5%
내동 30
 
5.3%
연산면 18
 
3.2%
연산리 15
 
2.6%
연무읍 5
 
0.9%
160-1번지 4
 
0.7%
반월동 4
 
0.7%
강산동 3
 
0.5%
Other values (153) 182
32.1%
2024-03-15T01:32:08.722882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
543
19.4%
산 170
 
6.1%
논 132
 
4.7%
충 130
 
4.6%
남 130
 
4.6%
청 130
 
4.6%
도 129
 
4.6%
시 129
 
4.6%
1 116
 
4.1%
지 108
 
3.9%
Other values (86) 1081
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1644
58.8%
Space Separator 543
 
19.4%
Decimal Number 523
 
18.7%
Dash Punctuation 88
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 170
10.3%
논 132
 
8.0%
충 130
 
7.9%
남 130
 
7.9%
청 130
 
7.9%
도 129
 
7.8%
시 129
 
7.8%
지 108
 
6.6%
번 104
 
6.3%
동 96
 
5.8%
Other values (74) 386
23.5%
Decimal Number
ValueCountFrequency (%)
1 116
22.2%
2 62
11.9%
4 55
10.5%
0 49
9.4%
3 46
 
8.8%
7 44
 
8.4%
9 41
 
7.8%
6 40
 
7.6%
5 40
 
7.6%
8 30
 
5.7%
Space Separator
ValueCountFrequency (%)
543
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1644
58.8%
Common 1154
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 170
10.3%
논 132
 
8.0%
충 130
 
7.9%
남 130
 
7.9%
청 130
 
7.9%
도 129
 
7.8%
시 129
 
7.8%
지 108
 
6.6%
번 104
 
6.3%
동 96
 
5.8%
Other values (74) 386
23.5%
Common
ValueCountFrequency (%)
543
47.1%
1 116
 
10.1%
- 88
 
7.6%
2 62
 
5.4%
4 55
 
4.8%
0 49
 
4.2%
3 46
 
4.0%
7 44
 
3.8%
9 41
 
3.6%
6 40
 
3.5%
Other values (2) 70
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1644
58.8%
ASCII 1154
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
543
47.1%
1 116
 
10.1%
- 88
 
7.6%
2 62
 
5.4%
4 55
 
4.8%
0 49
 
4.2%
3 46
 
4.0%
7 44
 
3.8%
9 41
 
3.6%
6 40
 
3.5%
Other values (2) 70
 
6.1%
Hangul
ValueCountFrequency (%)
산 170
10.3%
논 132
 
8.0%
충 130
 
7.9%
남 130
 
7.9%
청 130
 
7.9%
도 129
 
7.8%
시 129
 
7.8%
지 108
 
6.6%
번 104
 
6.3%
동 96
 
5.8%
Other values (74) 386
23.5%

전화번호
Text

Distinct115
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-15T01:32:09.784831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.573643
Min length6

Characters and Unicode

Total characters1493
Distinct characters17
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

Unique109 ?
Unique (%)84.5%

Sample

1st row041-732-4761
2nd row041-733-7882
3rd row041-732-7587
4th row041-732-2333
5th row041-735-2559
ValueCountFrequency (%)
데이터미집계 10
 
7.8%
041-734-4945 2
 
1.6%
041-733-7006 2
 
1.6%
041-736-0089 2
 
1.6%
041-732-5770 2
 
1.6%
041-735-9200 2
 
1.6%
041-735-4980 1
 
0.8%
041-733-8377 1
 
0.8%
041-734-5001 1
 
0.8%
041-735-8980 1
 
0.8%
Other values (105) 105
81.4%
2024-03-15T01:32:11.070931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 238
15.9%
0 190
12.7%
4 182
12.2%
3 179
12.0%
7 170
11.4%
1 160
10.7%
5 76
 
5.1%
8 69
 
4.6%
2 65
 
4.4%
6 53
 
3.5%
Other values (7) 111
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1195
80.0%
Dash Punctuation 238
 
15.9%
Other Letter 60
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 190
15.9%
4 182
15.2%
3 179
15.0%
7 170
14.2%
1 160
13.4%
5 76
 
6.4%
8 69
 
5.8%
2 65
 
5.4%
6 53
 
4.4%
9 51
 
4.3%
Other Letter
ValueCountFrequency (%)
이 10
16.7%
계 10
16.7%
집 10
16.7%
미 10
16.7%
터 10
16.7%
데 10
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 238
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1433
96.0%
Hangul 60
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 238
16.6%
0 190
13.3%
4 182
12.7%
3 179
12.5%
7 170
11.9%
1 160
11.2%
5 76
 
5.3%
8 69
 
4.8%
2 65
 
4.5%
6 53
 
3.7%
Hangul
ValueCountFrequency (%)
이 10
16.7%
계 10
16.7%
집 10
16.7%
미 10
16.7%
터 10
16.7%
데 10
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1433
96.0%
Hangul 60
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 238
16.6%
0 190
13.3%
4 182
12.7%
3 179
12.5%
7 170
11.9%
1 160
11.2%
5 76
 
5.3%
8 69
 
4.8%
2 65
 
4.5%
6 53
 
3.7%
Hangul
ValueCountFrequency (%)
이 10
16.7%
계 10
16.7%
집 10
16.7%
미 10
16.7%
터 10
16.7%
데 10
16.7%

Correlations

2024-03-15T01:32:11.332032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분행정동
업소구분1.0000.452
행정동0.4521.000
2024-03-15T01:32:11.567482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분행정동
업소구분1.0000.337
행정동0.3371.000
2024-03-15T01:32:11.795424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분행정동
업소구분1.0000.337
행정동0.3371.000

Missing values

2024-03-15T01:31:55.620279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:31:56.148216image/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

등록번호등록일자업소구분업소명행정동소재지도로명주소소재지지번주소전화번호
071984-06-11중개인대명부동산중개인상월면충청남도 논산시 상월면 선비로 1089충청남도 논산시 상월면 대우리 261-1번지041-732-4761
191984-06-13중개인벌곡신신부동산중개사무소벌곡면충청남도 논산시 벌곡면 황룡재로 601충청남도 논산시 벌곡면 한삼천리 243-8번지041-733-7882
2181984-08-28중개인부적부동산중개인부적면충청남도 논산시 부적면 덕평1길 32-5충청남도 논산시 부적면 덕평리 331번지041-732-7587
3221985-02-04중개인영진부동산사무소취암동충청남도 논산시 시민로 322충청남도 논산시 취암동 460-30번지041-732-2333
4231985-02-09중개인가야부동산중개인부창동충청남도 논산시 해월로 35충청남도 논산시 부창동 314-7번지041-735-2559
5311985-08-17중개인동진부동산중개인취암동충청남도 논산시 계백로 1014충청남도 논산시 취암동 1040-22번지041-732-2377
6341985-11-07중개인신흥부동산연산면충청남도 논산시 연산면 연산리 79-8충청남도 논산시 연산면 연산리 79-8번지041-734-1879
7391986-02-20중개인대림부동산중개인취암동충청남도 논산시 계백로 1007-14충청남도 논산시 취암동 612-4번지041-735-2434
8631987-09-09중개인대신부동산취암동충청남도 논산시 중앙로 469충청남도 논산시 반월동 104-2번지041-735-0074
9641987-09-09중개인동양부동산중개인사무소취암동충청남도 논산시 계백로 1012충청남도 논산시 취암동 1040-21번지041-735-6314
등록번호등록일자업소구분업소명행정동소재지도로명주소소재지지번주소전화번호
11944230-2022-000082022-07-14공인중개사계룡랜드공인중개사사무소상월면충청남도 논산시 상월면 백일헌로 1053충청남도 논산시 상월면 신충리 58-5데이터미집계
12044230-2022-000092022-07-22공인중개사케이엠공인중개사사무소취암동충청남도 논산시 중앙로 359, 202호충청남도 논산시 취암동 427-20507-1315-9736
12144230-2022-000102019-05-24공인중개사미르공인중개사사무소취암동충청남도 논산시 중앙로 510충청남도 논산시 대교동 109-9041-732-2588
12244230-2022-000112022-11-15공인중개사호박공인중개사사무소연무읍충청남도 논산시 연무읍 연무로 181충청남도 논산시 연무읍 안심리 1-4데이터미집계
12344230-2023-000022023-01-09공인중개사아성부동산공인중개사무소취암동충청남도 논산시 중앙로 301 2층충청남도 논산시 취암동 137-12041-736-2266
12444230-2023-000032023-02-20공인중개사정일공인중개사취암동충청남도 논산시 시민로 339충청남도 논산시 취암동 898데이터미집계
12544230-2023-000052023-03-07공인중개사조흥공인중개사사무소강경읍충청남도 논산시 강경읍 대흥로5번길 39 2층충청남도 논산시 강경읍 대흥리 35041-745-1075
12644230-2023-000072023-05-03공인중개사믿음공인중개사사무소취암동충청남도 논산시 중앙로398번길 33-1충청남도 논산시 취암동 1058-7데이터미집계
12744230-2023-000082023-07-13공인중개사바로부동산공인중개사사무소취암동충청남도 논산시 중앙로 221 1층충청남도 논산시 내동 634041-732-2929
12844230-2023-000092023-10-19공인중개사국민공인중개사사무소취암동충청남도 논산시 중앙로 359, 202호충청남도 논산시 취암동 427-2041-736-9736