Overview

Dataset statistics

Number of variables10
Number of observations564
Missing cells798
Missing cells (%)14.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.3 KiB
Average record size in memory82.2 B

Variable types

Categorical2
Text3
DateTime3
Numeric2

Dataset

Description광주광역시 남구 원룸 및 오피스텔 현황(위치, 용도, 가구수, 대지위치, 허가일, 사용승인일 등) 정보를 제공합니다.
Author광주광역시 남구
URLhttps://www.data.go.kr/data/15077370/fileData.do

Alerts

건축구분 has constant value ""Constant
데이터기준일 has constant value ""Constant
호수 is highly overall correlated with 가구수 and 1 other fieldsHigh correlation
가구수 is highly overall correlated with 호수 and 1 other fieldsHigh correlation
주용도 is highly overall correlated with 호수 and 1 other fieldsHigh correlation
사용승인일 has 82 (14.5%) missing valuesMissing
부속용도 has 11 (2.0%) missing valuesMissing
호수 has 518 (91.8%) missing valuesMissing
가구수 has 187 (33.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:11:08.243034
Analysis finished2023-12-12 08:11:09.593750
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
신축
564 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 564
100.0%

Length

2023-12-12T17:11:09.694965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:11:09.817031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 564
100.0%

허가번호
Text

Distinct561
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-12T17:11:10.038353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length16.262411
Min length15

Characters and Unicode

Total characters9172
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

Unique558 ?
Unique (%)98.9%

Sample

1st row1987-건축과-신축허가-171
2nd row1987-건축과-신축허가-220
3rd row1987-건축과-신축허가-232
4th row1987-건축과-신축허가-236
5th row1987-건축과-신축허가-373
ValueCountFrequency (%)
2013-건축과-신축허가-9 2
 
0.4%
2013-건축과-신축허가-12 2
 
0.4%
2013-건축과-신축허가-8 2
 
0.4%
2010-건축과-신축허가-26 1
 
0.2%
2014-건축과-신축허가-111 1
 
0.2%
2014-건축과-신축허가-141 1
 
0.2%
2014-건축과-신축허가-79 1
 
0.2%
2014-건축과-신축허가-78 1
 
0.2%
2014-건축과-신축허가-92 1
 
0.2%
2014-건축과-신축허가-100 1
 
0.2%
Other values (551) 551
97.7%
2023-12-12T17:11:10.501280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1692
18.4%
축 1128
12.3%
1 818
8.9%
2 780
8.5%
0 764
8.3%
가 564
 
6.1%
허 564
 
6.1%
신 564
 
6.1%
과 564
 
6.1%
건 564
 
6.1%
Other values (7) 1170
12.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3948
43.0%
Decimal Number 3532
38.5%
Dash Punctuation 1692
18.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 818
23.2%
2 780
22.1%
0 764
21.6%
3 192
 
5.4%
9 189
 
5.4%
8 187
 
5.3%
4 169
 
4.8%
5 161
 
4.6%
7 149
 
4.2%
6 123
 
3.5%
Other Letter
ValueCountFrequency (%)
축 1128
28.6%
가 564
14.3%
허 564
14.3%
신 564
14.3%
과 564
14.3%
건 564
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 1692
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5224
57.0%
Hangul 3948
43.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1692
32.4%
1 818
15.7%
2 780
14.9%
0 764
14.6%
3 192
 
3.7%
9 189
 
3.6%
8 187
 
3.6%
4 169
 
3.2%
5 161
 
3.1%
7 149
 
2.9%
Hangul
ValueCountFrequency (%)
축 1128
28.6%
가 564
14.3%
허 564
14.3%
신 564
14.3%
과 564
14.3%
건 564
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5224
57.0%
Hangul 3948
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1692
32.4%
1 818
15.7%
2 780
14.9%
0 764
14.6%
3 192
 
3.7%
9 189
 
3.6%
8 187
 
3.6%
4 169
 
3.2%
5 161
 
3.1%
7 149
 
2.9%
Hangul
ValueCountFrequency (%)
축 1128
28.6%
가 564
14.3%
허 564
14.3%
신 564
14.3%
과 564
14.3%
건 564
14.3%

대지위치
Text

Distinct559
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2023-12-12T17:11:11.055325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.485816
Min length14

Characters and Unicode

Total characters10990
Distinct characters43
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

Unique554 ?
Unique (%)98.2%

Sample

1st row광주광역시 남구 사동 58-7
2nd row광주광역시 남구 주월동 507
3rd row광주광역시 남구 월산동 1002-20 외1필지
4th row광주광역시 남구 주월동 970-2 외1필지
5th row광주광역시 남구 구동 37-83
ValueCountFrequency (%)
광주광역시 564
23.4%
남구 564
23.4%
월산동 120
 
5.0%
외1필지 113
 
4.7%
백운동 108
 
4.5%
주월동 76
 
3.1%
진월동 53
 
2.2%
봉선동 32
 
1.3%
행암동 32
 
1.3%
임암동 28
 
1.2%
Other values (564) 723
30.0%
2023-12-12T17:11:11.680902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1849
16.8%
광 1128
 
10.3%
주 640
 
5.8%
구 569
 
5.2%
시 564
 
5.1%
남 564
 
5.1%
동 564
 
5.1%
역 564
 
5.1%
1 529
 
4.8%
- 477
 
4.3%
Other values (33) 3542
32.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6077
55.3%
Decimal Number 2587
23.5%
Space Separator 1849
 
16.8%
Dash Punctuation 477
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 1128
18.6%
주 640
10.5%
구 569
9.4%
시 564
9.3%
남 564
9.3%
동 564
9.3%
역 564
9.3%
월 250
 
4.1%
지 162
 
2.7%
필 158
 
2.6%
Other values (21) 914
15.0%
Decimal Number
ValueCountFrequency (%)
1 529
20.4%
2 325
12.6%
3 309
11.9%
5 244
9.4%
6 244
9.4%
4 224
8.7%
0 209
 
8.1%
9 206
 
8.0%
7 150
 
5.8%
8 147
 
5.7%
Space Separator
ValueCountFrequency (%)
1849
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 477
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6077
55.3%
Common 4913
44.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 1128
18.6%
주 640
10.5%
구 569
9.4%
시 564
9.3%
남 564
9.3%
동 564
9.3%
역 564
9.3%
월 250
 
4.1%
지 162
 
2.7%
필 158
 
2.6%
Other values (21) 914
15.0%
Common
ValueCountFrequency (%)
1849
37.6%
1 529
 
10.8%
- 477
 
9.7%
2 325
 
6.6%
3 309
 
6.3%
5 244
 
5.0%
6 244
 
5.0%
4 224
 
4.6%
0 209
 
4.3%
9 206
 
4.2%
Other values (2) 297
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6077
55.3%
ASCII 4913
44.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1849
37.6%
1 529
 
10.8%
- 477
 
9.7%
2 325
 
6.6%
3 309
 
6.3%
5 244
 
5.0%
6 244
 
5.0%
4 224
 
4.6%
0 209
 
4.3%
9 206
 
4.2%
Other values (2) 297
 
6.0%
Hangul
ValueCountFrequency (%)
광 1128
18.6%
주 640
10.5%
구 569
9.4%
시 564
9.3%
남 564
9.3%
동 564
9.3%
역 564
9.3%
월 250
 
4.1%
지 162
 
2.7%
필 158
 
2.6%
Other values (21) 914
15.0%

허가일
Date

Distinct492
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum1987-03-09 00:00:00
Maximum2021-02-05 00:00:00
2023-12-12T17:11:11.860647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:12.072430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct429
Distinct (%)89.0%
Missing82
Missing (%)14.5%
Memory size4.5 KiB
Minimum1987-06-29 00:00:00
Maximum2021-01-20 00:00:00
2023-12-12T17:11:12.263768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:12.474603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주용도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
단독주택
386 
공동주택
153 
업무시설
 
25

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단독주택 386
68.4%
공동주택 153
 
27.1%
업무시설 25
 
4.4%

Length

2023-12-12T17:11:12.643124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:11:12.771136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 386
68.4%
공동주택 153
 
27.1%
업무시설 25
 
4.4%

부속용도
Text

MISSING 

Distinct164
Distinct (%)29.7%
Missing11
Missing (%)2.0%
Memory size4.5 KiB
2023-12-12T17:11:13.044197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length5
Mean length7.6256781
Min length2

Characters and Unicode

Total characters4217
Distinct characters93
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

Unique124 ?
Unique (%)22.4%

Sample

1st row다세대주택,점포
2nd row다세대주택
3rd row다세대주택
4th row다세대주택
5th row다세대주택
ValueCountFrequency (%)
다가구주택 253
39.8%
다세대주택 85
 
13.4%
다가구 26
 
4.1%
오피스텔 17
 
2.7%
근린생활시설 17
 
2.7%
연립주택 13
 
2.0%
소매점 10
 
1.6%
및 10
 
1.6%
다가구주택,소매점 6
 
0.9%
근린생활시설(소매점 4
 
0.6%
Other values (134) 194
30.6%
2023-12-12T17:11:13.500737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 494
 
11.7%
택 490
 
11.6%
다 479
 
11.4%
구 411
 
9.7%
가 409
 
9.7%
, 152
 
3.6%
대 106
 
2.5%
세 105
 
2.5%
소 87
 
2.1%
83
 
2.0%
Other values (83) 1401
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3717
88.1%
Other Punctuation 177
 
4.2%
Space Separator 83
 
2.0%
Decimal Number 80
 
1.9%
Close Punctuation 76
 
1.8%
Open Punctuation 76
 
1.8%
Dash Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 494
13.3%
택 490
13.2%
다 479
12.9%
구 411
11.1%
가 409
11.0%
대 106
 
2.9%
세 105
 
2.8%
소 87
 
2.3%
점 82
 
2.2%
시 80
 
2.2%
Other values (59) 974
26.2%
Decimal Number
ValueCountFrequency (%)
1 36
45.0%
2 13
 
16.2%
5 7
 
8.8%
9 6
 
7.5%
3 5
 
6.2%
7 4
 
5.0%
8 4
 
5.0%
4 2
 
2.5%
6 2
 
2.5%
0 1
 
1.2%
Other Punctuation
ValueCountFrequency (%)
, 152
85.9%
/ 16
 
9.0%
& 7
 
4.0%
. 2
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
P 1
25.0%
C 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 74
97.4%
] 2
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 74
97.4%
[ 2
 
2.6%
Space Separator
ValueCountFrequency (%)
83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3717
88.1%
Common 496
 
11.8%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 494
13.3%
택 490
13.2%
다 479
12.9%
구 411
11.1%
가 409
11.0%
대 106
 
2.9%
세 105
 
2.8%
소 87
 
2.3%
점 82
 
2.2%
시 80
 
2.2%
Other values (59) 974
26.2%
Common
ValueCountFrequency (%)
, 152
30.6%
83
16.7%
) 74
14.9%
( 74
14.9%
1 36
 
7.3%
/ 16
 
3.2%
2 13
 
2.6%
& 7
 
1.4%
5 7
 
1.4%
9 6
 
1.2%
Other values (10) 28
 
5.6%
Latin
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
P 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3717
88.1%
ASCII 500
 
11.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 494
13.3%
택 490
13.2%
다 479
12.9%
구 411
11.1%
가 409
11.0%
대 106
 
2.9%
세 105
 
2.8%
소 87
 
2.3%
점 82
 
2.2%
시 80
 
2.2%
Other values (59) 974
26.2%
ASCII
ValueCountFrequency (%)
, 152
30.4%
83
16.6%
) 74
14.8%
( 74
14.8%
1 36
 
7.2%
/ 16
 
3.2%
2 13
 
2.6%
& 7
 
1.4%
5 7
 
1.4%
9 6
 
1.2%
Other values (14) 32
 
6.4%

호수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)54.3%
Missing518
Missing (%)91.8%
Infinite0
Infinite (%)0.0%
Mean30.652174
Minimum1
Maximum241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T17:11:13.648829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q334.5
95-th percentile141
Maximum241
Range240
Interquartile range (IQR)30.5

Descriptive statistics

Standard deviation53.09037
Coefficient of variation (CV)1.7320263
Kurtosis7.5346084
Mean30.652174
Median Absolute Deviation (MAD)6.5
Skewness2.7467351
Sum1410
Variance2818.5874
MonotonicityNot monotonic
2023-12-12T17:11:13.797094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 5
 
0.9%
4 4
 
0.7%
6 3
 
0.5%
5 3
 
0.5%
3 3
 
0.5%
36 3
 
0.5%
2 3
 
0.5%
30 2
 
0.4%
7 2
 
0.4%
14 2
 
0.4%
Other values (15) 16
 
2.8%
(Missing) 518
91.8%
ValueCountFrequency (%)
1 5
0.9%
2 3
0.5%
3 3
0.5%
4 4
0.7%
5 3
0.5%
6 3
0.5%
7 2
 
0.4%
9 1
 
0.2%
11 1
 
0.2%
12 1
 
0.2%
ValueCountFrequency (%)
241 1
 
0.2%
213 1
 
0.2%
146 1
 
0.2%
126 1
 
0.2%
93 1
 
0.2%
87 1
 
0.2%
45 1
 
0.2%
42 1
 
0.2%
37 1
 
0.2%
36 3
0.5%

가구수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)4.8%
Missing187
Missing (%)33.2%
Infinite0
Infinite (%)0.0%
Mean10.32626
Minimum2
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2023-12-12T17:11:13.905418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q16
median10
Q315
95-th percentile18
Maximum19
Range17
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.8769077
Coefficient of variation (CV)0.4722821
Kurtosis-1.1163194
Mean10.32626
Median Absolute Deviation (MAD)4
Skewness-0.025106938
Sum3893
Variance23.784229
MonotonicityNot monotonic
2023-12-12T17:11:14.028316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
15 51
 
9.0%
9 41
 
7.3%
12 30
 
5.3%
4 23
 
4.1%
2 22
 
3.9%
8 22
 
3.9%
7 22
 
3.9%
18 21
 
3.7%
6 20
 
3.5%
5 19
 
3.4%
Other values (8) 106
18.8%
(Missing) 187
33.2%
ValueCountFrequency (%)
2 22
3.9%
3 13
 
2.3%
4 23
4.1%
5 19
3.4%
6 20
3.5%
7 22
3.9%
8 22
3.9%
9 41
7.3%
10 16
 
2.8%
11 10
 
1.8%
ValueCountFrequency (%)
19 10
 
1.8%
18 21
3.7%
17 10
 
1.8%
16 16
 
2.8%
15 51
9.0%
14 12
 
2.1%
13 19
 
3.4%
12 30
5.3%
11 10
 
1.8%
10 16
 
2.8%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2021-02-17 00:00:00
Maximum2021-02-17 00:00:00
2023-12-12T17:11:14.151900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:14.244831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T17:11:08.726914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:08.584674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:08.804242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:11:08.655983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:11:14.316191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도호수가구수
주용도1.0000.684NaN
호수0.6841.000NaN
가구수NaNNaN1.000
2023-12-12T17:11:14.430686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호수가구수주용도
호수1.0000.6940.564
가구수0.6941.0001.000
주용도0.5641.0001.000

Missing values

2023-12-12T17:11:08.917712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:11:09.054172image/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.
2023-12-12T17:11:09.520029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

건축구분허가번호대지위치허가일사용승인일주용도부속용도호수가구수데이터기준일
0신축1987-건축과-신축허가-171광주광역시 남구 사동 58-71987-03-091987-07-15공동주택다세대주택,점포<NA><NA>2021-02-17
1신축1987-건축과-신축허가-220광주광역시 남구 주월동 5071987-03-181987-08-22공동주택다세대주택<NA><NA>2021-02-17
2신축1987-건축과-신축허가-232광주광역시 남구 월산동 1002-20 외1필지1987-03-231987-07-03공동주택다세대주택<NA><NA>2021-02-17
3신축1987-건축과-신축허가-236광주광역시 남구 주월동 970-2 외1필지1987-03-231987-07-10공동주택다세대주택<NA><NA>2021-02-17
4신축1987-건축과-신축허가-373광주광역시 남구 구동 37-831987-04-181987-06-29공동주택다세대주택<NA><NA>2021-02-17
5신축1987-건축과-신축허가-423광주광역시 남구 주월동 448-91987-04-251987-08-20공동주택다세대주택<NA><NA>2021-02-17
6신축1987-건축과-신축허가-442광주광역시 남구 송하동 127-301987-05-021987-08-25공동주택다세대주택<NA><NA>2021-02-17
7신축1987-건축과-신축허가-456광주광역시 남구 월산동 911-281987-05-071987-10-13공동주택다세대주택<NA><NA>2021-02-17
8신축1987-건축과-신축허가-629광주광역시 남구 주월동 683-41987-06-181987-11-02공동주택다세대주택<NA><NA>2021-02-17
9신축1987-건축과-신축허가-983광주광역시 남구 방림동 353-21987-09-141987-12-26공동주택다세대주택<NA><NA>2021-02-17
건축구분허가번호대지위치허가일사용승인일주용도부속용도호수가구수데이터기준일
554신축2010-건축과-신축허가-24광주광역시 남구 백운동 651-102010-03-302011-02-23단독주택다다구주택<NA>132021-02-17
555신축2010-건축과-신축허가-26광주광역시 남구 서동 66-242010-03-302011-12-23단독주택다가구주택<NA>122021-02-17
556신축2010-건축과-신축허가-27광주광역시 남구 서동 66-52010-03-302011-10-19단독주택다가구주택<NA>122021-02-17
557신축2010-건축과-신축허가-23광주광역시 남구 방림동 54-202010-03-262011-02-01단독주택다가구주택<NA>102021-02-17
558신축2010-건축과-신축허가-22광주광역시 남구 백운동 623-92010-03-232011-08-16단독주택다가구주택<NA>142021-02-17
559신축2010-건축과-신축허가-21광주광역시 남구 월산동 1025-102010-03-162011-08-12단독주택다가구주택<NA>192021-02-17
560신축2010-건축과-신축허가-15광주광역시 남구 봉선동 155-3 외1필지2010-02-222010-09-28단독주택근생,다가구주택<NA>72021-02-17
561신축2010-건축과-신축허가-11광주광역시 남구 백운동 580-1 외1필지2010-02-022011-01-10단독주택다가구주택<NA>162021-02-17
562신축2010-건축과-신축허가-9광주광역시 남구 양림동 284 외1필지2010-01-292010-06-30단독주택다가구주택<NA>122021-02-17
563신축2010-건축과-신축허가-1광주광역시 남구 백운동 597-1 외1필지2010-01-082010-05-13단독주택다가구주택<NA><NA>2021-02-17