Overview

Dataset statistics

Number of variables7
Number of observations227
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.8 KiB
Average record size in memory57.6 B

Variable types

Numeric1
Text5
DateTime1

Dataset

Description전라남도 광양시에 위치한 부동산 중개사무소 현황에 대한 정보입니다. 소재지, 연락처, 등록번호가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15102829/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 has unique valuesUnique
등록번호 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:15:37.242422
Analysis finished2023-12-12 13:15:37.872103
Duration0.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114
Minimum1
Maximum227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2023-12-12T22:15:38.228581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.3
Q157.5
median114
Q3170.5
95-th percentile215.7
Maximum227
Range226
Interquartile range (IQR)113

Descriptive statistics

Standard deviation65.673435
Coefficient of variation (CV)0.57608276
Kurtosis-1.2
Mean114
Median Absolute Deviation (MAD)57
Skewness0
Sum25878
Variance4313
MonotonicityStrictly increasing
2023-12-12T22:15:38.376286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
144 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
Other values (217) 217
95.6%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
227 1
0.4%
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%

등록번호
Text

UNIQUE 

Distinct227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:15:38.586502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length13.488987
Min length8

Characters and Unicode

Total characters3062
Distinct characters12
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

Unique227 ?
Unique (%)100.0%

Sample

1st row46230-2016-00039
2nd row가4128-185
3rd row46230-2019-00006
4th row46230-2021-00021
5th row46230-2017-00009
ValueCountFrequency (%)
46230-2016-00039 1
 
0.4%
46230-2020-00008 1
 
0.4%
가4128-340 1
 
0.4%
46230-2021-00011 1
 
0.4%
46230-2015-00010 1
 
0.4%
46230-2017-00010 1
 
0.4%
46230-2020-00015 1
 
0.4%
46230-2018-00011 1
 
0.4%
46230-2022-00002 1
 
0.4%
46230-2022-00007 1
 
0.4%
Other values (217) 217
95.6%
2023-12-12T22:15:38.896786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 833
27.2%
2 533
17.4%
- 374
12.2%
1 294
 
9.6%
4 285
 
9.3%
3 215
 
7.0%
6 189
 
6.2%
8 129
 
4.2%
가 81
 
2.6%
7 50
 
1.6%
Other values (2) 79
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2607
85.1%
Dash Punctuation 374
 
12.2%
Other Letter 81
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 833
32.0%
2 533
20.4%
1 294
 
11.3%
4 285
 
10.9%
3 215
 
8.2%
6 189
 
7.2%
8 129
 
4.9%
7 50
 
1.9%
9 40
 
1.5%
5 39
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 374
100.0%
Other Letter
ValueCountFrequency (%)
가 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2981
97.4%
Hangul 81
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 833
27.9%
2 533
17.9%
- 374
12.5%
1 294
 
9.9%
4 285
 
9.6%
3 215
 
7.2%
6 189
 
6.3%
8 129
 
4.3%
7 50
 
1.7%
9 40
 
1.3%
Hangul
ValueCountFrequency (%)
가 81
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2981
97.4%
Hangul 81
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 833
27.9%
2 533
17.9%
- 374
12.5%
1 294
 
9.9%
4 285
 
9.6%
3 215
 
7.2%
6 189
 
6.3%
8 129
 
4.3%
7 50
 
1.7%
9 40
 
1.3%
Hangul
ValueCountFrequency (%)
가 81
100.0%

상호명
Text

UNIQUE 

Distinct227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:15:39.158473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length10
Mean length10.713656
Min length7

Characters and Unicode

Total characters2432
Distinct characters224
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)100.0%

Sample

1st row1등공인중개사사무소
2nd row21세기공인중개사사무소
3rd row365공인중개사사무소
4th row88공인중개사사무소
5th rowOK부동산중개사무소
ValueCountFrequency (%)
유한회사덕례믿음부동산중개사무소 2
 
0.9%
공인중개사사무소 2
 
0.9%
1등공인중개사사무소 1
 
0.4%
온세상부동산중개사사무소 1
 
0.4%
용강공인중개사사무소 1
 
0.4%
에이스공인중개사사무소 1
 
0.4%
엘에프공인중개사사무소 1
 
0.4%
예스공인중개사사무소 1
 
0.4%
오네뜨114공인중개사사무소 1
 
0.4%
오네뜨부동산중개사무소 1
 
0.4%
Other values (218) 218
94.8%
2023-12-12T22:15:39.558655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 443
18.2%
중 229
9.4%
소 229
9.4%
개 227
9.3%
무 225
9.3%
인 219
 
9.0%
공 210
 
8.6%
동 35
 
1.4%
부 31
 
1.3%
산 30
 
1.2%
Other values (214) 554
22.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2402
98.8%
Decimal Number 18
 
0.7%
Uppercase Letter 5
 
0.2%
Space Separator 3
 
0.1%
Lowercase Letter 3
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 443
18.4%
중 229
9.5%
소 229
9.5%
개 227
9.5%
무 225
9.4%
인 219
9.1%
공 210
8.7%
동 35
 
1.5%
부 31
 
1.3%
산 30
 
1.2%
Other values (197) 524
21.8%
Decimal Number
ValueCountFrequency (%)
1 8
44.4%
4 3
 
16.7%
8 2
 
11.1%
5 1
 
5.6%
6 1
 
5.6%
3 1
 
5.6%
2 1
 
5.6%
7 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
T 1
20.0%
M 1
20.0%
S 1
20.0%
K 1
20.0%
O 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
h 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2402
98.8%
Common 22
 
0.9%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 443
18.4%
중 229
9.5%
소 229
9.5%
개 227
9.5%
무 225
9.4%
인 219
9.1%
공 210
8.7%
동 35
 
1.5%
부 31
 
1.3%
산 30
 
1.2%
Other values (197) 524
21.8%
Common
ValueCountFrequency (%)
1 8
36.4%
4 3
 
13.6%
3
 
13.6%
8 2
 
9.1%
- 1
 
4.5%
5 1
 
4.5%
6 1
 
4.5%
3 1
 
4.5%
2 1
 
4.5%
7 1
 
4.5%
Latin
ValueCountFrequency (%)
e 2
25.0%
h 1
12.5%
T 1
12.5%
M 1
12.5%
S 1
12.5%
K 1
12.5%
O 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2402
98.8%
ASCII 30
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 443
18.4%
중 229
9.5%
소 229
9.5%
개 227
9.5%
무 225
9.4%
인 219
9.1%
공 210
8.7%
동 35
 
1.5%
부 31
 
1.3%
산 30
 
1.2%
Other values (197) 524
21.8%
ASCII
ValueCountFrequency (%)
1 8
26.7%
4 3
 
10.0%
3
 
10.0%
8 2
 
6.7%
e 2
 
6.7%
- 1
 
3.3%
h 1
 
3.3%
T 1
 
3.3%
M 1
 
3.3%
S 1
 
3.3%
Other values (7) 7
23.3%

성명(대표자)
Text

Distinct225
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:15:39.929003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9955947
Min length2

Characters and Unicode

Total characters680
Distinct characters146
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

Unique223 ?
Unique (%)98.2%

Sample

1st row김행임
2nd row김진욱
3rd row손재숙
4th row강선화
5th row선복규
ValueCountFrequency (%)
이미라 2
 
0.9%
이미숙 2
 
0.9%
고경주 1
 
0.4%
박정미 1
 
0.4%
조경숙 1
 
0.4%
민인식 1
 
0.4%
김행임 1
 
0.4%
이상배 1
 
0.4%
이은주 1
 
0.4%
오연서 1
 
0.4%
Other values (215) 215
94.7%
2023-12-12T22:15:40.527835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 40
 
5.9%
이 33
 
4.9%
정 32
 
4.7%
박 25
 
3.7%
영 22
 
3.2%
미 18
 
2.6%
진 17
 
2.5%
현 16
 
2.4%
경 15
 
2.2%
희 15
 
2.2%
Other values (136) 447
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 680
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 40
 
5.9%
이 33
 
4.9%
정 32
 
4.7%
박 25
 
3.7%
영 22
 
3.2%
미 18
 
2.6%
진 17
 
2.5%
현 16
 
2.4%
경 15
 
2.2%
희 15
 
2.2%
Other values (136) 447
65.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 680
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 40
 
5.9%
이 33
 
4.9%
정 32
 
4.7%
박 25
 
3.7%
영 22
 
3.2%
미 18
 
2.6%
진 17
 
2.5%
현 16
 
2.4%
경 15
 
2.2%
희 15
 
2.2%
Other values (136) 447
65.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 680
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 40
 
5.9%
이 33
 
4.9%
정 32
 
4.7%
박 25
 
3.7%
영 22
 
3.2%
미 18
 
2.6%
진 17
 
2.5%
현 16
 
2.4%
경 15
 
2.2%
희 15
 
2.2%
Other values (136) 447
65.7%

소재지
Text

Distinct219
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:15:40.864597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length23.220264
Min length15

Characters and Unicode

Total characters5271
Distinct characters162
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique211 ?
Unique (%)93.0%

Sample

1st row전라남도 광양시 광양읍 용강로 31
2nd row전라남도 광양시 무등4길 36-1(중동)
3rd row전라남도 광양시 사동로 244
4th row전라남도 광양시 오류로 43
5th row전라남도 광양시 광양읍 신재로 36-1
ValueCountFrequency (%)
전라남도 227
19.7%
광양시 226
19.6%
광양읍 94
 
8.1%
1층 24
 
2.1%
인덕로 17
 
1.5%
상가동 16
 
1.4%
2층 13
 
1.1%
사동로 12
 
1.0%
대림오성로 10
 
0.9%
중마로 10
 
0.9%
Other values (319) 506
43.8%
2023-12-12T22:15:41.424510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
928
17.6%
광 363
 
6.9%
양 341
 
6.5%
1 259
 
4.9%
시 235
 
4.5%
남 231
 
4.4%
전 227
 
4.3%
도 227
 
4.3%
라 227
 
4.3%
로 151
 
2.9%
Other values (152) 2082
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3214
61.0%
Space Separator 928
 
17.6%
Decimal Number 841
 
16.0%
Other Punctuation 108
 
2.0%
Close Punctuation 71
 
1.3%
Open Punctuation 71
 
1.3%
Dash Punctuation 37
 
0.7%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 363
 
11.3%
양 341
 
10.6%
시 235
 
7.3%
남 231
 
7.2%
전 227
 
7.1%
도 227
 
7.1%
라 227
 
7.1%
로 151
 
4.7%
동 109
 
3.4%
읍 105
 
3.3%
Other values (135) 998
31.1%
Decimal Number
ValueCountFrequency (%)
1 259
30.8%
2 116
13.8%
0 103
 
12.2%
3 76
 
9.0%
7 60
 
7.1%
9 56
 
6.7%
4 54
 
6.4%
6 47
 
5.6%
5 47
 
5.6%
8 23
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 105
97.2%
@ 3
 
2.8%
Space Separator
ValueCountFrequency (%)
928
100.0%
Close Punctuation
ValueCountFrequency (%)
) 71
100.0%
Open Punctuation
ValueCountFrequency (%)
( 71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3214
61.0%
Common 2056
39.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 363
 
11.3%
양 341
 
10.6%
시 235
 
7.3%
남 231
 
7.2%
전 227
 
7.1%
도 227
 
7.1%
라 227
 
7.1%
로 151
 
4.7%
동 109
 
3.4%
읍 105
 
3.3%
Other values (135) 998
31.1%
Common
ValueCountFrequency (%)
928
45.1%
1 259
 
12.6%
2 116
 
5.6%
, 105
 
5.1%
0 103
 
5.0%
3 76
 
3.7%
) 71
 
3.5%
( 71
 
3.5%
7 60
 
2.9%
9 56
 
2.7%
Other values (6) 211
 
10.3%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3214
61.0%
ASCII 2057
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
928
45.1%
1 259
 
12.6%
2 116
 
5.6%
, 105
 
5.1%
0 103
 
5.0%
3 76
 
3.7%
) 71
 
3.5%
( 71
 
3.5%
7 60
 
2.9%
9 56
 
2.7%
Other values (7) 212
 
10.3%
Hangul
ValueCountFrequency (%)
광 363
 
11.3%
양 341
 
10.6%
시 235
 
7.3%
남 231
 
7.2%
전 227
 
7.1%
도 227
 
7.1%
라 227
 
7.1%
로 151
 
4.7%
동 109
 
3.4%
읍 105
 
3.3%
Other values (135) 998
31.1%

전화
Text

Distinct181
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T22:15:41.783628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.991189
Min length9

Characters and Unicode

Total characters2722
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

Unique178 ?
Unique (%)78.4%

Sample

1st row061-762-8879
2nd row061-794-7779
3rd row061-000-0000
4th row061-000-0000
5th row061-762-1088
ValueCountFrequency (%)
061-000-0000 45
 
19.8%
061-761-4646 2
 
0.9%
061-794-6611 2
 
0.9%
061-763-1601 1
 
0.4%
061-791-8080 1
 
0.4%
061-761-6222 1
 
0.4%
061-794-4388 1
 
0.4%
061-762-8879 1
 
0.4%
061-795-3223 1
 
0.4%
061-763-0007 1
 
0.4%
Other values (171) 171
75.3%
2023-12-12T22:15:42.280958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 664
24.4%
- 453
16.6%
1 359
13.2%
6 358
13.2%
7 262
 
9.6%
9 191
 
7.0%
2 99
 
3.6%
8 87
 
3.2%
4 86
 
3.2%
3 84
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2269
83.4%
Dash Punctuation 453
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 664
29.3%
1 359
15.8%
6 358
15.8%
7 262
 
11.5%
9 191
 
8.4%
2 99
 
4.4%
8 87
 
3.8%
4 86
 
3.8%
3 84
 
3.7%
5 79
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 453
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2722
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 664
24.4%
- 453
16.6%
1 359
13.2%
6 358
13.2%
7 262
 
9.6%
9 191
 
7.0%
2 99
 
3.6%
8 87
 
3.2%
4 86
 
3.2%
3 84
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2722
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 664
24.4%
- 453
16.6%
1 359
13.2%
6 358
13.2%
7 262
 
9.6%
9 191
 
7.0%
2 99
 
3.6%
8 87
 
3.2%
4 86
 
3.2%
3 84
 
3.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2023-07-18 00:00:00
Maximum2023-07-18 00:00:00
2023-12-12T22:15:42.423272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:15:42.539455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T22:15:37.578330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T22:15:37.705487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:15:37.829040image/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

연번등록번호상호명성명(대표자)소재지전화데이터기준일
0146230-2016-000391등공인중개사사무소김행임전라남도 광양시 광양읍 용강로 31061-762-88792023-07-18
12가4128-18521세기공인중개사사무소김진욱전라남도 광양시 무등4길 36-1(중동)061-794-77792023-07-18
2346230-2019-00006365공인중개사사무소손재숙전라남도 광양시 사동로 244061-000-00002023-07-18
3446230-2021-0002188공인중개사사무소강선화전라남도 광양시 오류로 43061-000-00002023-07-18
4546230-2017-00009OK부동산중개사무소선복규전라남도 광양시 광양읍 신재로 36-1061-762-10882023-07-18
56가4128-280SM 공인중개사사무소황인엽전라남도 광양시 중마청룡길 22(중동)061-791-99302023-07-18
6746230-2021-00004The키움공인중개사사무소이경희전라남도 광양시 광양읍 대림오성로 99-1, 1층061-000-00002023-07-18
7846230-2016-00002가교공인중개사사무소황윤정전라남도 광양시 광영로 102061-791-24532023-07-18
89가4128-250가나공인중개사사무소강공임전라남도 광양시 오류로 43(중동)061-791-09702023-07-18
91046230-2017-00016가야공인중개사사무소정인덕전라남도 광양시 사동로 245, 1층061-793-56332023-07-18
연번등록번호상호명성명(대표자)소재지전화데이터기준일
217218가4128-170호반공인중개사사무소정선미전라남도 광양시 광양읍 서평6길 23061-791-80802023-07-18
21821946230-2017-00033호주공인중개사사무소백순자전라남도 광양시 광양읍 인덕로 1016, 나동061-000-00002023-07-18
219220가4128-25화신부동산중개인사무소우동현전라남도 광양시 광양읍 서천1길 27061-763-16012023-07-18
220221가4128-74황금부동산중개인사무소김한칠전라남도 광양시 광양읍 희양현로 39(광양읍)061-762-06682023-07-18
221222가4128-375황금알공인중개사사무소김성천전라남도 광양시 발섬4길 7-10, 2층061-793-07092023-07-18
22222346230-2016-00033황금황길공인중개사사무소이미숙전라남도 광양시 항만9로 103-7(중동)061-792-79262023-07-18
22322446230-2017-00001황소공인중개사사무소고경주전라남도 광양시 광양읍 대림오성로 128061-761-74992023-07-18
22422546230-2019-00013후공인중개사사무소정보라전라남도 광양시 광양읍 인덕로 976-1061-000-00002023-07-18
22522646230-2021-00008흙사랑공인중개사사무소박미란전라남도 광양시 광양읍 희양현로 72-1061-000-00002023-07-18
22622746230-2017-00021-004유한회사덕례믿음부동산중개사무소 순천분사무소김정화전라남도 순천시 태봉길 31, 상가 212동 107호061-000-00002023-07-18