Overview

Dataset statistics

Number of variables8
Number of observations531
Missing cells189
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.4 KiB
Average record size in memory66.2 B

Variable types

Categorical1
Text3
DateTime2
Numeric2

Dataset

Description진주시 읍면동 별 경로당 현황을(주소, 신고일자, 면적 등) 공개함, 현재 보유하고 있는 자료를 공공데이터 등록 함.
URLhttps://www.data.go.kr/data/15045218/fileData.do

Alerts

기준일자 has constant value ""Constant
경로당 전화번호 has 189 (35.6%) missing valuesMissing
대지면적 is highly skewed (γ1 = 22.74833522)Skewed

Reproduction

Analysis started2023-12-12 22:27:44.288688
Analysis finished2023-12-12 22:27:45.247598
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct30
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
명석면
 
31
문산읍
 
29
금산면
 
27
수곡면
 
27
일반성면
 
26
Other values (25)
391 

Length

Max length4
Median length3
Mean length3.1035782
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
명석면 31
 
5.8%
문산읍 29
 
5.5%
금산면 27
 
5.1%
수곡면 27
 
5.1%
일반성면 26
 
4.9%
이반성면 24
 
4.5%
대곡면 24
 
4.5%
금곡면 24
 
4.5%
정촌면 23
 
4.3%
천전동 23
 
4.3%
Other values (20) 273
51.4%

Length

2023-12-13T07:27:45.321833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
명석면 31
 
5.8%
문산읍 29
 
5.5%
금산면 27
 
5.1%
수곡면 27
 
5.1%
일반성면 26
 
4.9%
이반성면 24
 
4.5%
대곡면 24
 
4.5%
금곡면 24
 
4.5%
정촌면 23
 
4.3%
천전동 23
 
4.3%
Other values (20) 273
51.4%

경로당명
Text

Distinct478
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T07:27:45.584402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length5
Mean length6.007533
Min length5

Characters and Unicode

Total characters3190
Distinct characters255
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

Unique439 ?
Unique (%)82.7%

Sample

1st row갈곡경로당
2nd row갈곡노인경로당
3rd row계리경로당
4th row남동경로당
5th row남서경로당
ValueCountFrequency (%)
신촌경로당 5
 
0.9%
덕곡경로당 4
 
0.8%
중촌경로당 4
 
0.8%
상촌경로당 4
 
0.8%
오동경로당 3
 
0.6%
원당경로당 3
 
0.6%
하촌경로당 3
 
0.6%
원동경로당 3
 
0.6%
남성경로당 3
 
0.6%
대동경로당 2
 
0.4%
Other values (469) 498
93.6%
2023-12-13T07:27:45.944356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 543
17.0%
당 538
16.9%
로 534
16.7%
동 86
 
2.7%
대 55
 
1.7%
A 49
 
1.5%
촌 38
 
1.2%
곡 35
 
1.1%
지 34
 
1.1%
신 33
 
1.0%
Other values (245) 1245
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3094
97.0%
Uppercase Letter 57
 
1.8%
Decimal Number 34
 
1.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 543
17.6%
당 538
17.4%
로 534
17.3%
동 86
 
2.8%
대 55
 
1.8%
촌 38
 
1.2%
곡 35
 
1.1%
지 34
 
1.1%
신 33
 
1.1%
주 30
 
1.0%
Other values (231) 1168
37.8%
Decimal Number
ValueCountFrequency (%)
2 13
38.2%
1 11
32.4%
3 4
 
11.8%
4 3
 
8.8%
5 2
 
5.9%
8 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
A 49
86.0%
L 4
 
7.0%
H 4
 
7.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3094
97.0%
Latin 58
 
1.8%
Common 38
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 543
17.6%
당 538
17.4%
로 534
17.3%
동 86
 
2.8%
대 55
 
1.8%
촌 38
 
1.2%
곡 35
 
1.1%
지 34
 
1.1%
신 33
 
1.1%
주 30
 
1.0%
Other values (231) 1168
37.8%
Common
ValueCountFrequency (%)
2 13
34.2%
1 11
28.9%
3 4
 
10.5%
4 3
 
7.9%
5 2
 
5.3%
) 1
 
2.6%
( 1
 
2.6%
1
 
2.6%
- 1
 
2.6%
8 1
 
2.6%
Latin
ValueCountFrequency (%)
A 49
84.5%
L 4
 
6.9%
H 4
 
6.9%
e 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3094
97.0%
ASCII 96
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 543
17.6%
당 538
17.4%
로 534
17.3%
동 86
 
2.8%
대 55
 
1.8%
촌 38
 
1.2%
곡 35
 
1.1%
지 34
 
1.1%
신 33
 
1.1%
주 30
 
1.0%
Other values (231) 1168
37.8%
ASCII
ValueCountFrequency (%)
A 49
51.0%
2 13
 
13.5%
1 11
 
11.5%
L 4
 
4.2%
H 4
 
4.2%
3 4
 
4.2%
4 3
 
3.1%
5 2
 
2.1%
) 1
 
1.0%
( 1
 
1.0%
Other values (4) 4
 
4.2%

도로명주소
Text

Distinct530
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T07:27:46.260582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length36
Mean length25.212806
Min length18

Characters and Unicode

Total characters13388
Distinct characters252
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique529 ?
Unique (%)99.6%

Sample

1st row경상남도 진주시 문산읍 갈곡길 24
2nd row경상남도 진주시 문산읍 문산로 696
3rd row경상남도 진주시 문산읍 두산길5번길 1
4th row경상남도 진주시 문산읍 소문길17번길 6(2층)
5th row경상남도 진주시 문산읍 월아산로1094번길 7
ValueCountFrequency (%)
경상남도 531
21.1%
진주시 531
21.1%
명석면 31
 
1.2%
문산읍 29
 
1.2%
금산면 27
 
1.1%
수곡면 27
 
1.1%
일반성면 26
 
1.0%
이반성면 24
 
1.0%
금곡면 24
 
1.0%
대곡면 24
 
1.0%
Other values (865) 1239
49.3%
2023-12-13T07:27:46.711029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1987
 
14.8%
진 631
 
4.7%
주 603
 
4.5%
상 578
 
4.3%
남 565
 
4.2%
경 549
 
4.1%
도 542
 
4.0%
시 539
 
4.0%
1 457
 
3.4%
길 416
 
3.1%
Other values (242) 6521
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8404
62.8%
Decimal Number 2202
 
16.4%
Space Separator 1987
 
14.8%
Open Punctuation 220
 
1.6%
Close Punctuation 219
 
1.6%
Other Punctuation 143
 
1.1%
Dash Punctuation 138
 
1.0%
Uppercase Letter 72
 
0.5%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 631
 
7.5%
주 603
 
7.2%
상 578
 
6.9%
남 565
 
6.7%
경 549
 
6.5%
도 542
 
6.4%
시 539
 
6.4%
길 416
 
5.0%
로 401
 
4.8%
면 324
 
3.9%
Other values (219) 3256
38.7%
Decimal Number
ValueCountFrequency (%)
1 457
20.8%
2 337
15.3%
5 222
10.1%
3 212
9.6%
4 189
8.6%
9 170
 
7.7%
7 167
 
7.6%
6 163
 
7.4%
8 143
 
6.5%
0 142
 
6.4%
Other Punctuation
ValueCountFrequency (%)
, 134
93.7%
. 7
 
4.9%
@ 2
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
A 64
88.9%
L 4
 
5.6%
H 4
 
5.6%
Math Symbol
ValueCountFrequency (%)
< 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
1987
100.0%
Open Punctuation
ValueCountFrequency (%)
( 220
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8404
62.8%
Common 4911
36.7%
Latin 73
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 631
 
7.5%
주 603
 
7.2%
상 578
 
6.9%
남 565
 
6.7%
경 549
 
6.5%
도 542
 
6.4%
시 539
 
6.4%
길 416
 
5.0%
로 401
 
4.8%
면 324
 
3.9%
Other values (219) 3256
38.7%
Common
ValueCountFrequency (%)
1987
40.5%
1 457
 
9.3%
2 337
 
6.9%
5 222
 
4.5%
( 220
 
4.5%
) 219
 
4.5%
3 212
 
4.3%
4 189
 
3.8%
9 170
 
3.5%
7 167
 
3.4%
Other values (9) 731
 
14.9%
Latin
ValueCountFrequency (%)
A 64
87.7%
L 4
 
5.5%
H 4
 
5.5%
e 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8404
62.8%
ASCII 4984
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1987
39.9%
1 457
 
9.2%
2 337
 
6.8%
5 222
 
4.5%
( 220
 
4.4%
) 219
 
4.4%
3 212
 
4.3%
4 189
 
3.8%
9 170
 
3.4%
7 167
 
3.4%
Other values (13) 804
16.1%
Hangul
ValueCountFrequency (%)
진 631
 
7.5%
주 603
 
7.2%
상 578
 
6.9%
남 565
 
6.7%
경 549
 
6.5%
도 542
 
6.4%
시 539
 
6.4%
길 416
 
5.0%
로 401
 
4.8%
면 324
 
3.9%
Other values (219) 3256
38.7%

신고일자
Date

Distinct339
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum1955-04-18 00:00:00
Maximum2018-04-06 00:00:00
2023-12-13T07:27:46.837757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:46.961088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

경로당 전화번호
Text

MISSING 

Distinct339
Distinct (%)99.1%
Missing189
Missing (%)35.6%
Memory size4.3 KiB
2023-12-13T07:27:47.177620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.002924
Min length12

Characters and Unicode

Total characters4105
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

Unique336 ?
Unique (%)98.2%

Sample

1st row055-055-8236
2nd row055-761-7187
3rd row055-759-4614
4th row055-761-5256
5th row055-759-6828
ValueCountFrequency (%)
055-758-6673 2
 
0.6%
055-758-8229 2
 
0.6%
055-746-4485 2
 
0.6%
055-747-0623 1
 
0.3%
055-746-4955 1
 
0.3%
055-755-0921 1
 
0.3%
055-755-3552 1
 
0.3%
055-755-7838 1
 
0.3%
055-753-3294 1
 
0.3%
055-762-5546 1
 
0.3%
Other values (329) 329
96.2%
2023-12-13T07:27:47.562032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1032
25.1%
- 684
16.7%
7 482
11.7%
0 481
11.7%
4 355
 
8.6%
6 223
 
5.4%
8 200
 
4.9%
1 178
 
4.3%
2 176
 
4.3%
3 150
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3421
83.3%
Dash Punctuation 684
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1032
30.2%
7 482
14.1%
0 481
14.1%
4 355
 
10.4%
6 223
 
6.5%
8 200
 
5.8%
1 178
 
5.2%
2 176
 
5.1%
3 150
 
4.4%
9 144
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4105
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1032
25.1%
- 684
16.7%
7 482
11.7%
0 481
11.7%
4 355
 
8.6%
6 223
 
5.4%
8 200
 
4.9%
1 178
 
4.3%
2 176
 
4.3%
3 150
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1032
25.1%
- 684
16.7%
7 482
11.7%
0 481
11.7%
4 355
 
8.6%
6 223
 
5.4%
8 200
 
4.9%
1 178
 
4.3%
2 176
 
4.3%
3 150
 
3.7%

대지면적
Real number (ℝ)

SKEWED 

Distinct389
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean385.78714
Minimum18
Maximum64279
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-13T07:27:47.707961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile45.725
Q1122.99
median201
Q3314
95-th percentile673.5
Maximum64279
Range64261
Interquartile range (IQR)191.01

Descriptive statistics

Standard deviation2789.9939
Coefficient of variation (CV)7.2319515
Kurtosis521.84795
Mean385.78714
Median Absolute Deviation (MAD)89
Skewness22.748335
Sum204852.97
Variance7784065.9
MonotonicityNot monotonic
2023-12-13T07:27:47.861460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
218.0 7
 
1.3%
155.0 5
 
0.9%
182.0 5
 
0.9%
200.0 4
 
0.8%
188.0 4
 
0.8%
116.0 4
 
0.8%
212.0 4
 
0.8%
225.0 4
 
0.8%
321.0 4
 
0.8%
283.0 4
 
0.8%
Other values (379) 486
91.5%
ValueCountFrequency (%)
18.0 1
0.2%
21.0 1
0.2%
21.5 1
0.2%
22.2 1
0.2%
23.5 1
0.2%
24.48 1
0.2%
25.35 1
0.2%
26.0 1
0.2%
28.0 1
0.2%
29.6 1
0.2%
ValueCountFrequency (%)
64279.0 1
0.2%
2314.0 1
0.2%
2172.0 1
0.2%
1904.0 1
0.2%
1656.3 1
0.2%
1515.0 1
0.2%
1500.7 1
0.2%
1263.0 1
0.2%
1209.6 1
0.2%
1154.97 1
0.2%

건물면적
Real number (ℝ)

Distinct479
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.31183
Minimum21
Maximum838.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-13T07:27:47.999491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile38.67
Q172.75
median90.04
Q3123.44
95-th percentile226.85
Maximum838.19
Range817.19
Interquartile range (IQR)50.69

Descriptive statistics

Standard deviation69.886822
Coefficient of variation (CV)0.64523719
Kurtosis27.572925
Mean108.31183
Median Absolute Deviation (MAD)21.54
Skewness3.8609413
Sum57513.583
Variance4884.1679
MonotonicityNot monotonic
2023-12-13T07:27:48.155509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103.2 6
 
1.1%
106.84 5
 
0.9%
80.0 4
 
0.8%
100.8 4
 
0.8%
87.9 3
 
0.6%
168.0 3
 
0.6%
75.6 3
 
0.6%
76.83 2
 
0.4%
64.8 2
 
0.4%
70.0 2
 
0.4%
Other values (469) 497
93.6%
ValueCountFrequency (%)
21.0 1
0.2%
21.5 1
0.2%
21.8 1
0.2%
22.2 1
0.2%
23.5 1
0.2%
24.48 1
0.2%
25.35 1
0.2%
25.49 1
0.2%
25.67 1
0.2%
27.0 1
0.2%
ValueCountFrequency (%)
838.19 1
0.2%
552.8 1
0.2%
477.71 1
0.2%
406.02 1
0.2%
372.78 1
0.2%
341.6 1
0.2%
334.29 1
0.2%
333.9 1
0.2%
329.4 1
0.2%
324.69 1
0.2%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2023-05-01 00:00:00
Maximum2023-05-01 00:00:00
2023-12-13T07:27:48.265014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:48.355713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T07:27:44.859334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:44.699408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:44.940976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:27:44.775143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:27:48.428156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동대지면적건물면적
읍면동1.0000.4290.342
대지면적0.4291.0000.000
건물면적0.3420.0001.000
2023-12-13T07:27:48.511856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지면적건물면적읍면동
대지면적1.0000.4290.333
건물면적0.4291.0000.138
읍면동0.3330.1381.000

Missing values

2023-12-13T07:27:45.073302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:27:45.202382image/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

읍면동경로당명도로명주소신고일자경로당 전화번호대지면적건물면적기준일자
0문산읍갈곡경로당경상남도 진주시 문산읍 갈곡길 241999-01-09<NA>652.0149.522023-05-01
1문산읍갈곡노인경로당경상남도 진주시 문산읍 문산로 6961994-02-21<NA>918.0256.32023-05-01
2문산읍계리경로당경상남도 진주시 문산읍 두산길5번길 11997-12-16<NA>168.090.042023-05-01
3문산읍남동경로당경상남도 진주시 문산읍 소문길17번길 6(2층)2009-11-13<NA>158.094.442023-05-01
4문산읍남서경로당경상남도 진주시 문산읍 월아산로1094번길 72001-08-28<NA>218.065.02023-05-01
5문산읍대호경로당경상남도 진주시 문산읍 문정로540번길 132001-01-16055-055-8236208.088.112023-05-01
6문산읍덕남경로당경상남도 진주시 문산읍 동부로 5642011-11-24<NA>165.084.62023-05-01
7문산읍덕동경로당경상남도 진주시 문산읍 동부로587번길 92006-04-04<NA>196.086.762023-05-01
8문산읍덕촌경로당경상남도 진주시 문산읍 동부로591번길 6-1(2층)2008-06-23055-761-718794.0112.42023-05-01
9문산읍동방경로당경상남도 진주시 문산읍 정자천로 2041996-04-22055-759-4614218.0196.82023-05-01
읍면동경로당명도로명주소신고일자경로당 전화번호대지면적건물면적기준일자
521가호동가호에일린의뜰경로당경상남도 진주시 강변길 31(가좌동,가호에일린의뜰)2013-01-29055-753-2372122.98122.982023-05-01
522가호동대경빌라트경로당경상남도 진주시 가호로 79(호탄동,대경빌라트)2002-12-02055-753-2884102.69102.692023-05-01
523가호동대동아파트경로당경상남도 진주시 가호로44번길 7(호탄동,대동A)2004-03-05055-762-9011204.7204.72023-05-01
524가호동주개경로당경상남도 진주시 진주대로404번길 20-21,2층(가좌동)2008-06-05<NA>560.1141.62023-05-01
525가호동호탄경로당경상남도 진주시 동부로 89(호탄동)2008-04-23<NA>119.935.52023-05-01
526충무공동경남혁신도시LH1단지경로당경상남도 진주시 사들로 157((충무공동,혁신도시LH아파트1단지)2014-05-01055-763-5778120.43120.432023-05-01
527충무공동경남혁신도시LH4단지경로당경상남도 진주시 사들로 126(충무공동,혁신도시LH아파트 4단지)2014-09-22055-759-2170146.4146.42023-05-01
528충무공동경남혁신도시LH5단지경로당경상남도 진주시 충의로 67(충무공동,혁신도시LH아파트 5단지)2016-07-22<NA>164.17164.172023-05-01
529충무공동한림풀에버아파트경로당경상남도 진주시 소호로 39(충무공동, 한림풀에버A)2016-10-18<NA>271.9579271.95792023-05-01
530충무공동혁신도시LH아파트8단지경로당경상남도 진주시 사들로 35 (충무공동, 경남혁신도시LH8단지@)2017-11-30<NA>139.51139.512023-05-01