Overview

Dataset statistics

Number of variables10
Number of observations209
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.3 KiB
Average record size in memory84.6 B

Variable types

Numeric4
Categorical5
Text1

Dataset

Description민방위비상대피시설목록177월
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202918

Alerts

시도명 has constant value ""Constant
시군구 has constant value ""Constant
대피소 구분 has constant value ""Constant
연번 is highly overall correlated with 읍면동High correlation
면적 is highly overall correlated with 수용 인원(명)High correlation
수용 인원(명) is highly overall correlated with 면적High correlation
읍면동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:18:04.584479
Analysis finished2024-03-14 01:18:06.825252
Duration2.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct209
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105
Minimum1
Maximum209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T10:18:06.885807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.4
Q153
median105
Q3157
95-th percentile198.6
Maximum209
Range208
Interquartile range (IQR)104

Descriptive statistics

Standard deviation60.477268
Coefficient of variation (CV)0.57597399
Kurtosis-1.2
Mean105
Median Absolute Deviation (MAD)52
Skewness0
Sum21945
Variance3657.5
MonotonicityStrictly increasing
2024-03-14T10:18:07.014595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
158 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
Other values (199) 199
95.2%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
전라북도
209 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 209
100.0%

Length

2024-03-14T10:18:07.114866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:18:07.198539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 209
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
전주시
209 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 209
100.0%

Length

2024-03-14T10:18:07.274501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:18:07.349994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 209
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
완산구 평화2동
18 
덕진구 우아1동
 
12
덕진구 우아2동
 
10
완산구 효자2동
 
10
완산구 서신동
 
10
Other values (28)
149 

Length

Max length9
Median length8
Mean length7.7368421
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row완산구 노송동
2nd row완산구 노송동
3rd row완산구 노송동
4th row완산구 노송동
5th row완산구 노송동

Common Values

ValueCountFrequency (%)
완산구 평화2동 18
 
8.6%
덕진구 우아1동 12
 
5.7%
덕진구 우아2동 10
 
4.8%
완산구 효자2동 10
 
4.8%
완산구 서신동 10
 
4.8%
완산구 효자4동 9
 
4.3%
덕진구 인후3동 9
 
4.3%
덕진구 송천2동 8
 
3.8%
덕진구 덕진동 8
 
3.8%
완산구 평화1동 8
 
3.8%
Other values (23) 107
51.2%

Length

2024-03-14T10:18:07.439776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완산구 113
27.0%
덕진구 96
23.0%
평화2동 18
 
4.3%
우아1동 12
 
2.9%
우아2동 10
 
2.4%
효자2동 10
 
2.4%
서신동 10
 
2.4%
효자4동 9
 
2.2%
인후3동 9
 
2.2%
송천2동 8
 
1.9%
Other values (25) 123
29.4%

대피소 구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
공공
209 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공 209
100.0%

Length

2024-03-14T10:18:07.535279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:18:07.606338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공 209
100.0%

설치년도
Real number (ℝ)

Distinct59
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20060160
Minimum19800902
Maximum20170208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T10:18:07.686516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19800902
5-th percentile19960902
Q120030108
median20050315
Q320110120
95-th percentile20110120
Maximum20170208
Range369306
Interquartile range (IQR)80012

Descriptive statistics

Standard deviation56782.637
Coefficient of variation (CV)0.0028306174
Kurtosis1.8823354
Mean20060160
Median Absolute Deviation (MAD)50893
Skewness-0.92096224
Sum4.1925734 × 109
Variance3.2242679 × 109
MonotonicityNot monotonic
2024-03-14T10:18:07.809472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110120 44
21.1%
20050315 24
 
11.5%
20050314 20
 
9.6%
20030101 10
 
4.8%
20110106 9
 
4.3%
20030302 9
 
4.3%
20000101 8
 
3.8%
20070101 7
 
3.3%
20101230 5
 
2.4%
20101229 4
 
1.9%
Other values (49) 69
33.0%
ValueCountFrequency (%)
19800902 1
0.5%
19881020 1
0.5%
19900101 1
0.5%
19910310 1
0.5%
19921001 1
0.5%
19930330 1
0.5%
19931001 1
0.5%
19950102 1
0.5%
19950201 1
0.5%
19950501 1
0.5%
ValueCountFrequency (%)
20170208 3
 
1.4%
20170206 2
 
1.0%
20170202 1
 
0.5%
20161207 1
 
0.5%
20120705 1
 
0.5%
20111229 1
 
0.5%
20110701 1
 
0.5%
20110120 44
21.1%
20110106 9
 
4.3%
20110104 2
 
1.0%

대피소위치
Text

Distinct208
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T10:18:08.017838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length36
Mean length30.325359
Min length25

Characters and Unicode

Total characters6338
Distinct characters286
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

Unique207 ?
Unique (%)99.0%

Sample

1st row풍남초등학교(전라북도 전주시 완산구 견훤왕궁로 16)
2nd row기린봉아파트(전라북도 전주시 완산구 견훤로 100)
3rd row대우빌딩(전라북도 전주시 완산구 기린대로 213)
4th row전주시청 대피소(전라북도 전주시 완산구 노송광장로 10)
5th row우성해오름아파트(전라북도 전주시 완산구 인봉남로 56)
ValueCountFrequency (%)
전주시 209
 
19.0%
완산구 113
 
10.3%
덕진구 96
 
8.7%
10 14
 
1.3%
앞(전라북도 11
 
1.0%
기린대로 9
 
0.8%
견훤로 8
 
0.7%
평화로 7
 
0.6%
8 6
 
0.5%
장승배기로 6
 
0.5%
Other values (464) 623
56.5%
2024-03-14T10:18:08.306354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
893
 
14.1%
전 448
 
7.1%
주 247
 
3.9%
도 222
 
3.5%
북 220
 
3.5%
시 219
 
3.5%
구 216
 
3.4%
라 215
 
3.4%
( 210
 
3.3%
) 209
 
3.3%
Other values (276) 3239
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4324
68.2%
Space Separator 893
 
14.1%
Decimal Number 669
 
10.6%
Open Punctuation 210
 
3.3%
Close Punctuation 209
 
3.3%
Dash Punctuation 16
 
0.3%
Uppercase Letter 11
 
0.2%
Other Punctuation 3
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 448
 
10.4%
주 247
 
5.7%
도 222
 
5.1%
북 220
 
5.1%
시 219
 
5.1%
구 216
 
5.0%
라 215
 
5.0%
아 156
 
3.6%
로 142
 
3.3%
파 138
 
3.2%
Other values (250) 2101
48.6%
Decimal Number
ValueCountFrequency (%)
1 156
23.3%
2 107
16.0%
0 86
12.9%
5 78
11.7%
3 57
 
8.5%
4 43
 
6.4%
7 40
 
6.0%
6 37
 
5.5%
9 35
 
5.2%
8 30
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 2
18.2%
S 2
18.2%
G 2
18.2%
T 1
9.1%
A 1
9.1%
B 1
9.1%
V 1
9.1%
L 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
w 1
33.3%
e 1
33.3%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
893
100.0%
Open Punctuation
ValueCountFrequency (%)
( 210
100.0%
Close Punctuation
ValueCountFrequency (%)
) 209
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4324
68.2%
Common 2000
31.6%
Latin 14
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 448
 
10.4%
주 247
 
5.7%
도 222
 
5.1%
북 220
 
5.1%
시 219
 
5.1%
구 216
 
5.0%
라 215
 
5.0%
아 156
 
3.6%
로 142
 
3.3%
파 138
 
3.2%
Other values (250) 2101
48.6%
Common
ValueCountFrequency (%)
893
44.6%
( 210
 
10.5%
) 209
 
10.4%
1 156
 
7.8%
2 107
 
5.3%
0 86
 
4.3%
5 78
 
3.9%
3 57
 
2.9%
4 43
 
2.1%
7 40
 
2.0%
Other values (5) 121
 
6.0%
Latin
ValueCountFrequency (%)
K 2
14.3%
S 2
14.3%
G 2
14.3%
T 1
7.1%
A 1
7.1%
B 1
7.1%
V 1
7.1%
w 1
7.1%
e 1
7.1%
i 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4324
68.2%
ASCII 2014
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
893
44.3%
( 210
 
10.4%
) 209
 
10.4%
1 156
 
7.7%
2 107
 
5.3%
0 86
 
4.3%
5 78
 
3.9%
3 57
 
2.8%
4 43
 
2.1%
7 40
 
2.0%
Other values (16) 135
 
6.7%
Hangul
ValueCountFrequency (%)
전 448
 
10.4%
주 247
 
5.7%
도 222
 
5.1%
북 220
 
5.1%
시 219
 
5.1%
구 216
 
5.0%
라 215
 
5.0%
아 156
 
3.6%
로 142
 
3.3%
파 138
 
3.2%
Other values (250) 2101
48.6%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4118.5885
Minimum24
Maximum32800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T10:18:08.451958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile207.2
Q1904
median2126
Q34953
95-th percentile16664.8
Maximum32800
Range32776
Interquartile range (IQR)4049

Descriptive statistics

Standard deviation5241.1797
Coefficient of variation (CV)1.272567
Kurtosis7.2521113
Mean4118.5885
Median Absolute Deviation (MAD)1643
Skewness2.5111822
Sum860785
Variance27469965
MonotonicityNot monotonic
2024-03-14T10:18:08.612582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
255 3
 
1.4%
1887 3
 
1.4%
616 3
 
1.4%
825 3
 
1.4%
600 2
 
1.0%
2000 2
 
1.0%
1805 2
 
1.0%
1320 2
 
1.0%
424 2
 
1.0%
1951 2
 
1.0%
Other values (181) 185
88.5%
ValueCountFrequency (%)
24 1
0.5%
66 2
1.0%
132 1
0.5%
140 1
0.5%
150 1
0.5%
174 1
0.5%
188 1
0.5%
192 1
0.5%
197 1
0.5%
204 1
0.5%
ValueCountFrequency (%)
32800 1
0.5%
24777 1
0.5%
24408 1
0.5%
22514 1
0.5%
20196 1
0.5%
20064 1
0.5%
20001 1
0.5%
18011 1
0.5%
17193 1
0.5%
17055 1
0.5%

수용 인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4992.6603
Minimum30
Maximum39758
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T10:18:08.970502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile251.6
Q11096
median2577
Q36004
95-th percentile20200.2
Maximum39758
Range39728
Interquartile range (IQR)4908

Descriptive statistics

Standard deviation6352.9377
Coefficient of variation (CV)1.2724554
Kurtosis7.2520565
Mean4992.6603
Median Absolute Deviation (MAD)1991
Skewness2.511169
Sum1043466
Variance40359817
MonotonicityNot monotonic
2024-03-14T10:18:09.092395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 3
 
1.4%
2288 3
 
1.4%
747 3
 
1.4%
1000 3
 
1.4%
728 2
 
1.0%
2425 2
 
1.0%
2188 2
 
1.0%
1600 2
 
1.0%
514 2
 
1.0%
2365 2
 
1.0%
Other values (181) 185
88.5%
ValueCountFrequency (%)
30 1
0.5%
80 2
1.0%
160 1
0.5%
170 1
0.5%
182 1
0.5%
211 1
0.5%
228 1
0.5%
233 1
0.5%
239 1
0.5%
248 1
0.5%
ValueCountFrequency (%)
39758 1
0.5%
30033 1
0.5%
29586 1
0.5%
27290 1
0.5%
24480 1
0.5%
24320 1
0.5%
24244 1
0.5%
21832 1
0.5%
20840 1
0.5%
20673 1
0.5%

내진설계여부
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
○
186 
×
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row×
2nd row○
3rd row○
4th row×
5th row○

Common Values

ValueCountFrequency (%)
○ 186
89.0%
× 23
 
11.0%

Length

2024-03-14T10:18:09.197552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:18:09.290423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
○ 186
89.0%
× 23
 
11.0%

Interactions

2024-03-14T10:18:06.248369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:04.991432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.449722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.879921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:06.351971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.104804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.552058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.945341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:06.431518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.220623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.719614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:06.017493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:06.526933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.339355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:05.804905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:06.088619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:18:09.361277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동설치년도면적수용 인원(명)내진설계여부
연번1.0000.9940.5570.0000.0000.403
읍면동0.9941.0000.8080.5350.5350.592
설치년도0.5570.8081.0000.0000.0000.357
면적0.0000.5350.0001.0001.0000.200
수용\n인원(명)0.0000.5350.0001.0001.0000.200
내진설계여부0.4030.5920.3570.2000.2001.000
2024-03-14T10:18:09.466953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동내진설계여부
읍면동1.0000.467
내진설계여부0.4671.000
2024-03-14T10:18:09.537563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치년도면적수용 인원(명)읍면동내진설계여부
연번1.0000.055-0.082-0.0820.8930.308
설치년도0.0551.0000.2130.2130.4220.317
면적-0.0820.2131.0001.0000.2120.196
수용\n인원(명)-0.0820.2131.0001.0000.2120.196
읍면동0.8930.4220.2120.2121.0000.467
내진설계여부0.3080.3170.1960.1960.4671.000

Missing values

2024-03-14T10:18:06.671832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:18:06.781093image/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

연번시도명시군구읍면동대피소 구분설치년도대피소위치면적수용 인원(명)내진설계여부
01전라북도전주시완산구 노송동공공19881020풍남초등학교(전라북도 전주시 완산구 견훤왕궁로 16)8401019×
12전라북도전주시완산구 노송동공공19930330기린봉아파트(전라북도 전주시 완산구 견훤로 100)18312220○
23전라북도전주시완산구 노송동공공20030102대우빌딩(전라북도 전주시 완산구 기린대로 213)1719320840○
34전라북도전주시완산구 노송동공공20030526전주시청 대피소(전라북도 전주시 완산구 노송광장로 10)13721664×
45전라북도전주시완산구 노송동공공20060501우성해오름아파트(전라북도 전주시 완산구 인봉남로 56)40624924○
56전라북도전주시완산구 동서학동공공20000103진흥하이츠아파트(전라북도 전주시 완산구 학봉2길 11)16431992○
67전라북도전주시완산구 동서학동공공20000101영동고덕아파트 A동(전라북도 전주시 완산구 고덕산2길 9)14061705○
78전라북도전주시완산구 동서학동공공20000101영동고덕아파트 B동(전라북도 전주시 완산구 고덕산2길 9)10971330○
89전라북도전주시완산구 동서학동공공20110120대아산성아파트(전라북도 전주시 완산구 남고산성1길 37-0)10671294○
910전라북도전주시완산구 동서학동공공20170202국립무형유산원(전라북도 전주시 완산구 서학로 95)64487816○
연번시도명시군구읍면동대피소 구분설치년도대피소위치면적수용 인원(명)내진설계여부
199200전라북도전주시덕진구 팔복동공공19931001팔복동주민센터(전라북도 전주시 덕진구 신복5길 6-0)357433○
200201전라북도전주시덕진구 팔복동공공20061030남양아파트(전라북도 전주시 덕진구 팔복1길 6-0)46205600○
201202전라북도전주시덕진구 팔복동공공20110106코스타빌아파트(전라북도 전주시 덕진구 추천1길 6-0)752912○
202203전라북도전주시덕진구 팔복동공공20110106팔복거성아파트(전라북도 전주시 덕진구 신복5길 18)8371015×
203204전라북도전주시덕진구 팔복동공공20110106전라북도경제통상진흥원(전라북도 전주시 덕진구 팔과정로 164-0)9531156○
204205전라북도전주시덕진구 호성동공공19950501LG동아아파트(전라북도 전주시 덕진구 호성로 40)23302825○
205206전라북도전주시덕진구 호성동공공19971101주공아파트(전라북도 전주시 덕진구 소리로 179)57436962○
206207전라북도전주시덕진구 호성동공공20061024진흥더블파크1단지아파트(전라북도 전주시 덕진구 호성로 132)81509879○
207208전라북도전주시덕진구 호성동공공20110104다경마을일신아파트(전라북도 전주시 덕진구 호성1길 8-9)13431628○
208209전라북도전주시덕진구 호성동공공20110104진흥더블파크3단지아파트(전라북도 전주시 덕진구 호성로 170)1240115032○