Overview

Dataset statistics

Number of variables8
Number of observations50
Missing cells8
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.3 KiB
Average record size in memory67.6 B

Variable types

Numeric1
Text5
Categorical1
DateTime1

Dataset

Description경상남도 하동군 부동산중개업 (상호명, 소재지, 소재지(도로명), 등록일자, 연락처 등) 정보를 제공하고 있습니다
Author경상남도 하동군
URLhttps://www.data.go.kr/data/15084800/fileData.do

Alerts

연번 is highly overall correlated with 소재지High correlation
소재지 is highly overall correlated with 연번High correlation
연락처 has 8 (16.0%) missing valuesMissing
연번 has unique valuesUnique
중개업등록번호 has unique valuesUnique
상호 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:24:11.367814
Analysis finished2023-12-12 02:24:12.408903
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2023-12-12T11:24:12.505127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2023-12-12T11:24:12.669849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

중개업등록번호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T11:24:12.938515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16.5
Mean length13.54
Min length8

Characters and Unicode

Total characters677
Distinct characters14
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

Unique50 ?
Unique (%)100.0%

Sample

1st row가4348-170
2nd row48850-2017-00001
3rd row48850-2015-00002
4th row48850-2016-00001
5th row가-14-559호
ValueCountFrequency (%)
가4348-170 1
 
2.0%
가43480000-0125 1
 
2.0%
가4348-0073 1
 
2.0%
48850-2020-00004 1
 
2.0%
48850-2018-00002 1
 
2.0%
가43480000-0056 1
 
2.0%
가43480000-0010 1
 
2.0%
가43480000-0050 1
 
2.0%
가43480000-0054 1
 
2.0%
가4348-0140 1
 
2.0%
Other values (40) 40
80.0%
2023-12-12T11:24:13.388377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 221
32.6%
8 82
 
12.1%
4 81
 
12.0%
- 77
 
11.4%
1 47
 
6.9%
2 43
 
6.4%
5 41
 
6.1%
3 29
 
4.3%
가 22
 
3.2%
7 12
 
1.8%
Other values (4) 22
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 576
85.1%
Dash Punctuation 77
 
11.4%
Other Letter 24
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 221
38.4%
8 82
 
14.2%
4 81
 
14.1%
1 47
 
8.2%
2 43
 
7.5%
5 41
 
7.1%
3 29
 
5.0%
7 12
 
2.1%
6 12
 
2.1%
9 8
 
1.4%
Other Letter
ValueCountFrequency (%)
가 22
91.7%
호 1
 
4.2%
나 1
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 653
96.5%
Hangul 24
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 221
33.8%
8 82
 
12.6%
4 81
 
12.4%
- 77
 
11.8%
1 47
 
7.2%
2 43
 
6.6%
5 41
 
6.3%
3 29
 
4.4%
7 12
 
1.8%
6 12
 
1.8%
Hangul
ValueCountFrequency (%)
가 22
91.7%
호 1
 
4.2%
나 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 653
96.5%
Hangul 24
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 221
33.8%
8 82
 
12.6%
4 81
 
12.4%
- 77
 
11.8%
1 47
 
7.2%
2 43
 
6.6%
5 41
 
6.3%
3 29
 
4.4%
7 12
 
1.8%
6 12
 
1.8%
Hangul
ValueCountFrequency (%)
가 22
91.7%
호 1
 
4.2%
나 1
 
4.2%

상호
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T11:24:13.700146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length11
Min length7

Characters and Unicode

Total characters550
Distinct characters87
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row섬진강공인중개사사무소
2nd row한다사공인중개사사무소
3rd row박상국공인중개사사무소
4th row장수공인중개사사무소
5th row하동공인중개사사무소
ValueCountFrequency (%)
부동산중개인사무소 2
 
3.4%
섬진강공인중개사사무소 1
 
1.7%
옥종부동산공인중개사사무소 1
 
1.7%
덕천부동산중개사무소 1
 
1.7%
대양 1
 
1.7%
부동산 1
 
1.7%
중개인사무소 1
 
1.7%
고남 1
 
1.7%
대우 1
 
1.7%
부동산중개사무소 1
 
1.7%
Other values (47) 47
81.0%
2023-12-12T11:24:14.227387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 86
15.6%
개 51
9.3%
소 50
9.1%
중 50
9.1%
무 49
8.9%
인 40
 
7.3%
공 36
 
6.5%
동 25
 
4.5%
산 21
 
3.8%
부 20
 
3.6%
Other values (77) 122
22.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 534
97.1%
Space Separator 8
 
1.5%
Decimal Number 7
 
1.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 86
16.1%
개 51
9.6%
소 50
9.4%
중 50
9.4%
무 49
9.2%
인 40
 
7.5%
공 36
 
6.7%
동 25
 
4.7%
산 21
 
3.9%
부 20
 
3.7%
Other values (69) 106
19.9%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
5 1
14.3%
4 1
14.3%
2 1
14.3%
8 1
14.3%
3 1
14.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 534
97.1%
Common 16
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 86
16.1%
개 51
9.6%
소 50
9.4%
중 50
9.4%
무 49
9.2%
인 40
 
7.5%
공 36
 
6.7%
동 25
 
4.7%
산 21
 
3.9%
부 20
 
3.7%
Other values (69) 106
19.9%
Common
ValueCountFrequency (%)
8
50.0%
1 2
 
12.5%
5 1
 
6.2%
4 1
 
6.2%
2 1
 
6.2%
8 1
 
6.2%
· 1
 
6.2%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 534
97.1%
ASCII 15
 
2.7%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 86
16.1%
개 51
9.6%
소 50
9.4%
중 50
9.4%
무 49
9.2%
인 40
 
7.5%
공 36
 
6.7%
동 25
 
4.7%
산 21
 
3.9%
부 20
 
3.7%
Other values (69) 106
19.9%
ASCII
ValueCountFrequency (%)
8
53.3%
1 2
 
13.3%
5 1
 
6.7%
4 1
 
6.7%
2 1
 
6.7%
8 1
 
6.7%
3 1
 
6.7%
None
ValueCountFrequency (%)
· 1
100.0%

소재지
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
금남면
13 
하동읍
7 
금성면
6 
진교면
5 
화개면
4 
Other values (8)
15 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)8.0%

Sample

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

Common Values

ValueCountFrequency (%)
금남면 13
26.0%
하동읍 7
14.0%
금성면 6
12.0%
진교면 5
 
10.0%
화개면 4
 
8.0%
악양면 3
 
6.0%
북천면 3
 
6.0%
옥종면 3
 
6.0%
고전면 2
 
4.0%
적량면 1
 
2.0%
Other values (3) 3
 
6.0%

Length

2023-12-12T11:24:14.394881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금남면 13
26.0%
하동읍 7
14.0%
금성면 6
12.0%
진교면 5
 
10.0%
화개면 4
 
8.0%
악양면 3
 
6.0%
북천면 3
 
6.0%
옥종면 3
 
6.0%
고전면 2
 
4.0%
적량면 1
 
2.0%
Other values (3) 3
 
6.0%

소재지(도로명)
Text

Distinct48
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T11:24:14.668613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length13.26
Min length9

Characters and Unicode

Total characters663
Distinct characters84
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

Unique46 ?
Unique (%)92.0%

Sample

1st row하동읍 경서대로 126
2nd row하동읍 경서대로 144
3rd row하동읍 경서대로 174
4th row하동읍 경서대로 219
5th row하동읍 군청로 36
ValueCountFrequency (%)
금남면 14
 
8.6%
섬진강대로 9
 
5.6%
경서대로 8
 
4.9%
하동읍 7
 
4.3%
금성면 5
 
3.1%
진교면 5
 
3.1%
화개면 4
 
2.5%
북천면 3
 
1.9%
옥종면 3
 
1.9%
악양면 3
 
1.9%
Other values (86) 101
62.3%
2023-12-12T11:24:15.220470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
114
 
17.2%
면 43
 
6.5%
로 34
 
5.1%
1 33
 
5.0%
2 24
 
3.6%
금 20
 
3.0%
7 19
 
2.9%
4 18
 
2.7%
대 18
 
2.7%
진 17
 
2.6%
Other values (74) 323
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 366
55.2%
Decimal Number 164
24.7%
Space Separator 114
 
17.2%
Dash Punctuation 14
 
2.1%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 43
 
11.7%
로 34
 
9.3%
금 20
 
5.5%
대 18
 
4.9%
진 17
 
4.6%
길 15
 
4.1%
남 15
 
4.1%
경 12
 
3.3%
동 12
 
3.3%
하 10
 
2.7%
Other values (59) 170
46.4%
Decimal Number
ValueCountFrequency (%)
1 33
20.1%
2 24
14.6%
7 19
11.6%
4 18
11.0%
3 16
9.8%
0 15
9.1%
6 14
8.5%
9 12
 
7.3%
8 8
 
4.9%
5 5
 
3.0%
Space Separator
ValueCountFrequency (%)
114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 366
55.2%
Common 297
44.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 43
 
11.7%
로 34
 
9.3%
금 20
 
5.5%
대 18
 
4.9%
진 17
 
4.6%
길 15
 
4.1%
남 15
 
4.1%
경 12
 
3.3%
동 12
 
3.3%
하 10
 
2.7%
Other values (59) 170
46.4%
Common
ValueCountFrequency (%)
114
38.4%
1 33
 
11.1%
2 24
 
8.1%
7 19
 
6.4%
4 18
 
6.1%
3 16
 
5.4%
0 15
 
5.1%
6 14
 
4.7%
- 14
 
4.7%
9 12
 
4.0%
Other values (5) 18
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 366
55.2%
ASCII 297
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
114
38.4%
1 33
 
11.1%
2 24
 
8.1%
7 19
 
6.4%
4 18
 
6.1%
3 16
 
5.4%
0 15
 
5.1%
6 14
 
4.7%
- 14
 
4.7%
9 12
 
4.0%
Other values (5) 18
 
6.1%
Hangul
ValueCountFrequency (%)
면 43
 
11.7%
로 34
 
9.3%
금 20
 
5.5%
대 18
 
4.9%
진 17
 
4.6%
길 15
 
4.1%
남 15
 
4.1%
경 12
 
3.3%
동 12
 
3.3%
하 10
 
2.7%
Other values (59) 170
46.4%

등록일자
Date

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
Minimum1981-07-30 00:00:00
Maximum2021-10-01 00:00:00
2023-12-12T11:24:15.359999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:24:15.551710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

대표자
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2023-12-12T11:24:15.820838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters150
Distinct characters77
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

Unique50 ?
Unique (%)100.0%

Sample

1st row김봉관
2nd row류재윤
3rd row박상국
4th row이장수
5th row정호영
ValueCountFrequency (%)
김봉관 1
 
2.0%
이종율 1
 
2.0%
한충영 1
 
2.0%
조재식 1
 
2.0%
박정숙 1
 
2.0%
김평정 1
 
2.0%
김중하 1
 
2.0%
강상집 1
 
2.0%
추종만 1
 
2.0%
정정용 1
 
2.0%
Other values (40) 40
80.0%
2023-12-12T11:24:16.204885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
9.3%
정 9
 
6.0%
박 6
 
4.0%
용 5
 
3.3%
이 5
 
3.3%
최 4
 
2.7%
재 4
 
2.7%
영 4
 
2.7%
규 3
 
2.0%
식 3
 
2.0%
Other values (67) 93
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
9.3%
정 9
 
6.0%
박 6
 
4.0%
용 5
 
3.3%
이 5
 
3.3%
최 4
 
2.7%
재 4
 
2.7%
영 4
 
2.7%
규 3
 
2.0%
식 3
 
2.0%
Other values (67) 93
62.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
9.3%
정 9
 
6.0%
박 6
 
4.0%
용 5
 
3.3%
이 5
 
3.3%
최 4
 
2.7%
재 4
 
2.7%
영 4
 
2.7%
규 3
 
2.0%
식 3
 
2.0%
Other values (67) 93
62.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
9.3%
정 9
 
6.0%
박 6
 
4.0%
용 5
 
3.3%
이 5
 
3.3%
최 4
 
2.7%
재 4
 
2.7%
영 4
 
2.7%
규 3
 
2.0%
식 3
 
2.0%
Other values (67) 93
62.0%

연락처
Text

MISSING 

Distinct42
Distinct (%)100.0%
Missing8
Missing (%)16.0%
Memory size532.0 B
2023-12-12T11:24:16.502457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.142857
Min length12

Characters and Unicode

Total characters510
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

Unique42 ?
Unique (%)100.0%

Sample

1st row055-884-2030
2nd row055-884-1445
3rd row055-883-0398
4th row055-883-1444
5th row055-883-4989
ValueCountFrequency (%)
0507-1337-2615 1
 
2.4%
055-884-4588 1
 
2.4%
055-882-9002 1
 
2.4%
055-884-7734 1
 
2.4%
055-884-4253 1
 
2.4%
055-884-0091 1
 
2.4%
055-882-1181 1
 
2.4%
055-882-9001 1
 
2.4%
055-883-7571 1
 
2.4%
055-882-5252 1
 
2.4%
Other values (32) 32
76.2%
2023-12-12T11:24:16.990692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 100
19.6%
5 97
19.0%
- 84
16.5%
0 70
13.7%
4 36
 
7.1%
1 27
 
5.3%
2 27
 
5.3%
3 25
 
4.9%
9 20
 
3.9%
7 15
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 426
83.5%
Dash Punctuation 84
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 100
23.5%
5 97
22.8%
0 70
16.4%
4 36
 
8.5%
1 27
 
6.3%
2 27
 
6.3%
3 25
 
5.9%
9 20
 
4.7%
7 15
 
3.5%
6 9
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 510
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 100
19.6%
5 97
19.0%
- 84
16.5%
0 70
13.7%
4 36
 
7.1%
1 27
 
5.3%
2 27
 
5.3%
3 25
 
4.9%
9 20
 
3.9%
7 15
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 100
19.6%
5 97
19.0%
- 84
16.5%
0 70
13.7%
4 36
 
7.1%
1 27
 
5.3%
2 27
 
5.3%
3 25
 
4.9%
9 20
 
3.9%
7 15
 
2.9%

Interactions

2023-12-12T11:24:11.965575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:24:17.116917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번중개업등록번호상호소재지소재지(도로명)등록일자대표자연락처
연번1.0001.0001.0000.8931.0000.9341.0001.000
중개업등록번호1.0001.0001.0001.0001.0001.0001.0001.000
상호1.0001.0001.0001.0001.0001.0001.0001.000
소재지0.8931.0001.0001.0001.0000.9861.0001.000
소재지(도로명)1.0001.0001.0001.0001.0000.9891.0001.000
등록일자0.9341.0001.0000.9860.9891.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
2023-12-12T11:24:17.253500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지
연번1.0000.627
소재지0.6271.000

Missing values

2023-12-12T11:24:12.146332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:24:12.336769image/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

연번중개업등록번호상호소재지소재지(도로명)등록일자대표자연락처
01가4348-170섬진강공인중개사사무소하동읍하동읍 경서대로 1262013-06-28김봉관055-884-2030
1248850-2017-00001한다사공인중개사사무소하동읍하동읍 경서대로 1442017-04-21류재윤055-884-1445
2348850-2015-00002박상국공인중개사사무소하동읍하동읍 경서대로 1742015-03-11박상국<NA>
3448850-2016-00001장수공인중개사사무소하동읍하동읍 경서대로 2192016-02-04이장수055-883-0398
45가-14-559호하동공인중개사사무소하동읍하동읍 군청로 362004-11-23정호영055-883-1444
5648850-2018-00008한빛부동산중개사사무소하동읍하동읍 군청로 57-152018-11-30김연자055-883-4989
67나4348-0004최학용 하동부동산중개사무소하동읍하동읍 경서대로 2031981-07-30최학용055-883-0186
7848850-2021-00004화개공인중개사사무소화개면화개면 섬진강대로 3670-122021-03-29김주야055-884-0097
8948850-2021-00008플러스공인중개사사무소화개면화개면 화개로 13 1층2021-10-01이성준055-883-4549
910가43480000-0064옥로공인중개사 사무소화개면경상남도 하동군 화개면 탑리 710-11995-04-18배재현055-884-0018
연번중개업등록번호상호소재지소재지(도로명)등록일자대표자연락처
404148850-2021-00003소쿠리테 공인중개사사무소진교면진교면 하평안길 282021-02-01김철수055-882-6900
4142가4348-163백경부동산중개사무소진교면진교면 경충로 10992012-05-21정희성055-882-3589
4243가4348-169경남공인중개사사무소양보면양보면 진양로 7312013-05-15김인영<NA>
434448850-2019-00001애성부동산공인중개사사무소북천면북천면 경서대로 20092019-01-22황순덕055-884-4980
444548850-2018-00006북천부동산공인중개사사무소북천면북천면 경서대로 24412016-12-26최학연<NA>
454648850-2018-00009행복한부동산중개사사무소북천면북천면 경서대로 24472018-12-19오주환<NA>
464748850-2015-00004청학골부동산중개사무소청암면청암면 대밭땀길 12-322015-06-02노하식055-884-7289
474848850-2020-00002다판다공인중개사사무소옥종면옥종면 옥단로 10222020-03-23홍점이055-884-8161
4849가4348-0073옥종부동산공인중개사사무소옥종면옥종면 옥종중앙길 542000-04-07한충영055-882-5114
495048850-2015-000001하동부동산공인중개사사무소옥종면옥종면 옥종중앙길 61-12015-01-06최낙원055-884-8280