Overview

Dataset statistics

Number of variables6
Number of observations9293
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory453.9 KiB
Average record size in memory50.0 B

Variable types

Text3
Numeric2
Categorical1

Dataset

Description지자체 , 공동주택별 RFID음식물종량기기 설치 현황에 대한 데이터로 지자체명, 공동주택명, 공동주택 주소, 설치대수를 제공합니다.
Author한국환경공단
URLhttps://www.data.go.kr/data/15081380/fileData.do

Alerts

기준일자 has constant value ""Constant
세대수 is highly overall correlated with 설치대수High correlation
설치대수 is highly overall correlated with 세대수High correlation

Reproduction

Analysis started2023-12-12 09:14:49.429678
Analysis finished2023-12-12 09:14:51.783224
Duration2.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지자체
Text

Distinct143
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size72.7 KiB
2023-12-12T18:14:52.065502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.4631443
Min length7

Characters and Unicode

Total characters78648
Distinct characters111
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.2%

Sample

1st row강원도 강릉시
2nd row강원도 강릉시
3rd row강원도 강릉시
4th row강원도 강릉시
5th row강원도 강릉시
ValueCountFrequency (%)
서울특별시 2461
 
13.2%
경기도 1696
 
9.1%
부산광역시 1164
 
6.3%
광주광역시 610
 
3.3%
경상북도 608
 
3.3%
대구광역시 548
 
2.9%
용인시 538
 
2.9%
경상남도 503
 
2.7%
인천광역시 422
 
2.3%
강원도 356
 
1.9%
Other values (127) 9680
52.1%
2023-12-12T18:14:52.615959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9293
 
11.8%
시 9154
 
11.6%
구 6688
 
8.5%
도 4029
 
5.1%
광 3806
 
4.8%
서 3311
 
4.2%
역 2958
 
3.8%
경 2915
 
3.7%
울 2574
 
3.3%
별 2462
 
3.1%
Other values (101) 31458
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 69355
88.2%
Space Separator 9293
 
11.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 9154
 
13.2%
구 6688
 
9.6%
도 4029
 
5.8%
광 3806
 
5.5%
서 3311
 
4.8%
역 2958
 
4.3%
경 2915
 
4.2%
울 2574
 
3.7%
별 2462
 
3.5%
특 2462
 
3.5%
Other values (100) 28996
41.8%
Space Separator
ValueCountFrequency (%)
9293
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69355
88.2%
Common 9293
 
11.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 9154
 
13.2%
구 6688
 
9.6%
도 4029
 
5.8%
광 3806
 
5.5%
서 3311
 
4.8%
역 2958
 
4.3%
경 2915
 
4.2%
울 2574
 
3.7%
별 2462
 
3.5%
특 2462
 
3.5%
Other values (100) 28996
41.8%
Common
ValueCountFrequency (%)
9293
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 69355
88.2%
ASCII 9293
 
11.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9293
100.0%
Hangul
ValueCountFrequency (%)
시 9154
 
13.2%
구 6688
 
9.6%
도 4029
 
5.8%
광 3806
 
5.5%
서 3311
 
4.8%
역 2958
 
4.3%
경 2915
 
4.2%
울 2574
 
3.7%
별 2462
 
3.5%
특 2462
 
3.5%
Other values (100) 28996
41.8%

공동주택명
Text

Distinct9075
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size72.7 KiB
2023-12-12T18:14:53.016811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length7.8437534
Min length2

Characters and Unicode

Total characters72892
Distinct characters640
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8918 ?
Unique (%)96.0%

Sample

1st row극동아파트
2nd row강릉아이파크
3rd row노암3차한라아파트
4th row강릉회산LH아파트
5th row입암6주공아파트
ValueCountFrequency (%)
아파트 92
 
0.9%
오피스텔 34
 
0.3%
2차 32
 
0.3%
2단지 26
 
0.2%
e편한세상 26
 
0.2%
1단지 24
 
0.2%
1차 21
 
0.2%
힐스테이트 17
 
0.2%
창동 16
 
0.1%
현대 15
 
0.1%
Other values (9285) 10427
97.2%
2023-12-12T18:14:53.553351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 3041
 
4.2%
파 2681
 
3.7%
트 2640
 
3.6%
지 1750
 
2.4%
1602
 
2.2%
차 1598
 
2.2%
스 1402
 
1.9%
동 1392
 
1.9%
단 1234
 
1.7%
대 1223
 
1.7%
Other values (630) 54329
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65263
89.5%
Decimal Number 3349
 
4.6%
Space Separator 1602
 
2.2%
Uppercase Letter 918
 
1.3%
Dash Punctuation 840
 
1.2%
Lowercase Letter 244
 
0.3%
Close Punctuation 221
 
0.3%
Open Punctuation 221
 
0.3%
Connector Punctuation 118
 
0.2%
Other Punctuation 114
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 3041
 
4.7%
파 2681
 
4.1%
트 2640
 
4.0%
지 1750
 
2.7%
차 1598
 
2.4%
스 1402
 
2.1%
동 1392
 
2.1%
단 1234
 
1.9%
대 1223
 
1.9%
이 1084
 
1.7%
Other values (562) 47218
72.4%
Uppercase Letter
ValueCountFrequency (%)
S 167
18.2%
L 141
15.4%
H 124
13.5%
K 88
9.6%
C 63
 
6.9%
G 59
 
6.4%
E 38
 
4.1%
I 33
 
3.6%
A 33
 
3.6%
W 27
 
2.9%
Other values (15) 145
15.8%
Lowercase Letter
ValueCountFrequency (%)
e 184
75.4%
n 8
 
3.3%
k 6
 
2.5%
s 6
 
2.5%
i 6
 
2.5%
l 6
 
2.5%
t 5
 
2.0%
h 5
 
2.0%
c 3
 
1.2%
r 3
 
1.2%
Other values (7) 12
 
4.9%
Decimal Number
ValueCountFrequency (%)
2 1098
32.8%
1 1003
29.9%
3 463
13.8%
4 201
 
6.0%
5 180
 
5.4%
6 133
 
4.0%
7 79
 
2.4%
8 69
 
2.1%
0 64
 
1.9%
9 59
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 73
64.0%
. 20
 
17.5%
& 11
 
9.6%
/ 3
 
2.6%
# 3
 
2.6%
' 2
 
1.8%
· 2
 
1.8%
Close Punctuation
ValueCountFrequency (%)
) 215
97.3%
] 6
 
2.7%
Open Punctuation
ValueCountFrequency (%)
( 215
97.3%
[ 6
 
2.7%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
1602
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 840
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65261
89.5%
Common 6465
 
8.9%
Latin 1164
 
1.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 3041
 
4.7%
파 2681
 
4.1%
트 2640
 
4.0%
지 1750
 
2.7%
차 1598
 
2.4%
스 1402
 
2.1%
동 1392
 
2.1%
단 1234
 
1.9%
대 1223
 
1.9%
이 1084
 
1.7%
Other values (560) 47216
72.3%
Latin
ValueCountFrequency (%)
e 184
15.8%
S 167
14.3%
L 141
12.1%
H 124
10.7%
K 88
 
7.6%
C 63
 
5.4%
G 59
 
5.1%
E 38
 
3.3%
I 33
 
2.8%
A 33
 
2.8%
Other values (34) 234
20.1%
Common
ValueCountFrequency (%)
1602
24.8%
2 1098
17.0%
1 1003
15.5%
- 840
13.0%
3 463
 
7.2%
) 215
 
3.3%
( 215
 
3.3%
4 201
 
3.1%
5 180
 
2.8%
6 133
 
2.1%
Other values (14) 515
 
8.0%
Han
ValueCountFrequency (%)
休 1
50.0%
家 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65261
89.5%
ASCII 7625
 
10.5%
None 2
 
< 0.1%
Number Forms 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 3041
 
4.7%
파 2681
 
4.1%
트 2640
 
4.0%
지 1750
 
2.7%
차 1598
 
2.4%
스 1402
 
2.1%
동 1392
 
2.1%
단 1234
 
1.9%
대 1223
 
1.9%
이 1084
 
1.7%
Other values (560) 47216
72.3%
ASCII
ValueCountFrequency (%)
1602
21.0%
2 1098
14.4%
1 1003
13.2%
- 840
11.0%
3 463
 
6.1%
) 215
 
2.8%
( 215
 
2.8%
4 201
 
2.6%
e 184
 
2.4%
5 180
 
2.4%
Other values (55) 1624
21.3%
None
ValueCountFrequency (%)
· 2
100.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
CJK
ValueCountFrequency (%)
休 1
50.0%
家 1
50.0%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1669
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean525.90261
Minimum1
Maximum6867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.8 KiB
2023-12-12T18:14:53.744054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile69.6
Q1203
median395
Q3699
95-th percentile1402.8
Maximum6867
Range6866
Interquartile range (IQR)496

Descriptive statistics

Standard deviation496.14429
Coefficient of variation (CV)0.94341476
Kurtosis17.457376
Mean525.90261
Median Absolute Deviation (MAD)221
Skewness3.0343754
Sum4887213
Variance246159.16
MonotonicityNot monotonic
2023-12-12T18:14:53.919165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
301 32
 
0.3%
302 29
 
0.3%
242 28
 
0.3%
100 28
 
0.3%
201 25
 
0.3%
61 25
 
0.3%
300 25
 
0.3%
115 24
 
0.3%
501 24
 
0.3%
123 24
 
0.3%
Other values (1659) 9029
97.2%
ValueCountFrequency (%)
1 3
< 0.1%
2 2
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
11 4
< 0.1%
12 1
 
< 0.1%
15 1
 
< 0.1%
16 3
< 0.1%
17 2
< 0.1%
18 4
< 0.1%
ValueCountFrequency (%)
6867 1
< 0.1%
5680 1
< 0.1%
5564 1
< 0.1%
5551 1
< 0.1%
5287 1
< 0.1%
5242 1
< 0.1%
5150 1
< 0.1%
5080 1
< 0.1%
4936 1
< 0.1%
4495 1
< 0.1%

주소
Text

Distinct8625
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size72.7 KiB
2023-12-12T18:14:54.318395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length43
Mean length24.520499
Min length6

Characters and Unicode

Total characters227869
Distinct characters635
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8278 ?
Unique (%)89.1%

Sample

1st row강원도 강릉시 주문진읍 웃사다리4길 20(극동아파트)
2nd row강원도 강릉시 경강로 2511(송정동, 강릉아이파크아파트)
3rd row강원도 강릉시 강남동 노암동
4th row강원도 강릉시 강변로 94(회산동, 회산주공아파트)
5th row강원도 강릉시 성덕동 입암동
ValueCountFrequency (%)
서울특별시 1988
 
4.6%
경기 933
 
2.1%
경기도 741
 
1.7%
부산 607
 
1.4%
부산광역시 548
 
1.3%
서울 454
 
1.0%
수원시 417
 
1.0%
광주광역시 397
 
0.9%
용인시 396
 
0.9%
북구 351
 
0.8%
Other values (14428) 36694
84.3%
2023-12-12T18:14:54.947877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34244
 
15.0%
동 8592
 
3.8%
시 7958
 
3.5%
구 7950
 
3.5%
로 7699
 
3.4%
1 6534
 
2.9%
) 4680
 
2.1%
( 4680
 
2.1%
2 4615
 
2.0%
서 4023
 
1.8%
Other values (625) 136894
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148782
65.3%
Space Separator 34244
 
15.0%
Decimal Number 30267
 
13.3%
Close Punctuation 4705
 
2.1%
Open Punctuation 4705
 
2.1%
Other Punctuation 3576
 
1.6%
Dash Punctuation 1078
 
0.5%
Uppercase Letter 375
 
0.2%
Lowercase Letter 133
 
0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8592
 
5.8%
시 7958
 
5.3%
구 7950
 
5.3%
로 7699
 
5.2%
서 4023
 
2.7%
길 3982
 
2.7%
산 3433
 
2.3%
경 3152
 
2.1%
광 2921
 
2.0%
대 2754
 
1.9%
Other values (560) 96318
64.7%
Uppercase Letter
ValueCountFrequency (%)
S 46
12.3%
L 42
11.2%
K 32
 
8.5%
H 31
 
8.3%
C 29
 
7.7%
E 25
 
6.7%
I 25
 
6.7%
A 18
 
4.8%
D 17
 
4.5%
W 16
 
4.3%
Other values (13) 94
25.1%
Lowercase Letter
ValueCountFrequency (%)
e 90
67.7%
l 6
 
4.5%
i 6
 
4.5%
s 5
 
3.8%
a 5
 
3.8%
t 5
 
3.8%
h 4
 
3.0%
p 2
 
1.5%
m 2
 
1.5%
w 2
 
1.5%
Other values (5) 6
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 6534
21.6%
2 4615
15.2%
3 3492
11.5%
5 2676
8.8%
4 2657
8.8%
6 2336
 
7.7%
0 2203
 
7.3%
7 2125
 
7.0%
8 1841
 
6.1%
9 1788
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 3527
98.6%
* 25
 
0.7%
. 12
 
0.3%
/ 5
 
0.1%
; 2
 
0.1%
& 2
 
0.1%
· 2
 
0.1%
@ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
50.0%
Ⅱ 1
25.0%
Ⅲ 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 4680
99.5%
] 25
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 4680
99.5%
[ 25
 
0.5%
Space Separator
ValueCountFrequency (%)
34244
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1078
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148779
65.3%
Common 78575
34.5%
Latin 512
 
0.2%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8592
 
5.8%
시 7958
 
5.3%
구 7950
 
5.3%
로 7699
 
5.2%
서 4023
 
2.7%
길 3982
 
2.7%
산 3433
 
2.3%
경 3152
 
2.1%
광 2921
 
2.0%
대 2754
 
1.9%
Other values (558) 96315
64.7%
Latin
ValueCountFrequency (%)
e 90
17.6%
S 46
 
9.0%
L 42
 
8.2%
K 32
 
6.2%
H 31
 
6.1%
C 29
 
5.7%
E 25
 
4.9%
I 25
 
4.9%
A 18
 
3.5%
D 17
 
3.3%
Other values (31) 157
30.7%
Common
ValueCountFrequency (%)
34244
43.6%
1 6534
 
8.3%
) 4680
 
6.0%
( 4680
 
6.0%
2 4615
 
5.9%
, 3527
 
4.5%
3 3492
 
4.4%
5 2676
 
3.4%
4 2657
 
3.4%
6 2336
 
3.0%
Other values (14) 9134
 
11.6%
Han
ValueCountFrequency (%)
家 2
66.7%
秀 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148779
65.3%
ASCII 79081
34.7%
Number Forms 4
 
< 0.1%
CJK 3
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34244
43.3%
1 6534
 
8.3%
) 4680
 
5.9%
( 4680
 
5.9%
2 4615
 
5.8%
, 3527
 
4.5%
3 3492
 
4.4%
5 2676
 
3.4%
4 2657
 
3.4%
6 2336
 
3.0%
Other values (51) 9640
 
12.2%
Hangul
ValueCountFrequency (%)
동 8592
 
5.8%
시 7958
 
5.3%
구 7950
 
5.3%
로 7699
 
5.2%
서 4023
 
2.7%
길 3982
 
2.7%
산 3433
 
2.3%
경 3152
 
2.1%
광 2921
 
2.0%
대 2754
 
1.9%
Other values (558) 96315
64.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
50.0%
Ⅱ 1
25.0%
Ⅲ 1
25.0%
CJK
ValueCountFrequency (%)
家 2
66.7%
秀 1
33.3%
None
ValueCountFrequency (%)
· 2
100.0%

설치대수
Real number (ℝ)

HIGH CORRELATION 

Distinct73
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7672442
Minimum1
Maximum117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size81.8 KiB
2023-12-12T18:14:55.119218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q310
95-th percentile22
Maximum117
Range116
Interquartile range (IQR)7

Descriptive statistics

Standard deviation7.7643369
Coefficient of variation (CV)0.9996257
Kurtosis22.829582
Mean7.7672442
Median Absolute Deviation (MAD)3
Skewness3.4511823
Sum72181
Variance60.284928
MonotonicityNot monotonic
2023-12-12T18:14:55.313400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1420
15.3%
3 987
10.6%
4 937
10.1%
6 738
 
7.9%
1 638
 
6.9%
5 624
 
6.7%
8 600
 
6.5%
7 438
 
4.7%
10 408
 
4.4%
9 363
 
3.9%
Other values (63) 2140
23.0%
ValueCountFrequency (%)
1 638
6.9%
2 1420
15.3%
3 987
10.6%
4 937
10.1%
5 624
6.7%
6 738
7.9%
7 438
 
4.7%
8 600
6.5%
9 363
 
3.9%
10 408
 
4.4%
ValueCountFrequency (%)
117 1
< 0.1%
98 1
< 0.1%
97 1
< 0.1%
96 1
< 0.1%
92 1
< 0.1%
87 2
< 0.1%
78 2
< 0.1%
73 1
< 0.1%
72 1
< 0.1%
68 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size72.7 KiB
2021-04-30
9293 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-30
2nd row2021-04-30
3rd row2021-04-30
4th row2021-04-30
5th row2021-04-30

Common Values

ValueCountFrequency (%)
2021-04-30 9293
100.0%

Length

2023-12-12T18:14:55.455367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:14:55.552701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-30 9293
100.0%

Interactions

2023-12-12T18:14:51.198699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:14:50.940701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:14:51.346340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:14:51.073832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:14:55.607129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수설치대수
세대수1.0000.928
설치대수0.9281.000
2023-12-12T18:14:55.706321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수설치대수
세대수1.0000.932
설치대수0.9321.000

Missing values

2023-12-12T18:14:51.530820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:14:51.692516image/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

지자체공동주택명세대수주소설치대수기준일자
0강원도 강릉시극동아파트204강원도 강릉시 주문진읍 웃사다리4길 20(극동아파트)22021-04-30
1강원도 강릉시강릉아이파크493강원도 강릉시 경강로 2511(송정동, 강릉아이파크아파트)72021-04-30
2강원도 강릉시노암3차한라아파트497강원도 강릉시 강남동 노암동62021-04-30
3강원도 강릉시강릉회산LH아파트309강원도 강릉시 강변로 94(회산동, 회산주공아파트)42021-04-30
4강원도 강릉시입암6주공아파트1622강원도 강릉시 성덕동 입암동242021-04-30
5강원도 강릉시강릉역 블루핀 오피스텔473강원도 강릉시 강릉대로 285(교동)52021-04-30
6강원도 강릉시강변코아루오투리움430강원도 강릉시 월대산로 23(입암동)52021-04-30
7강원도 강릉시홍제한신휴플러스393강원도 강릉시 홍제동 홍제동62021-04-30
8강원도 강릉시노암 신화아파트494강원도 강릉시 강남동 노암동82021-04-30
9강원도 강릉시롯데캐슬2단지296강원도 강릉시 교1동 교동42021-04-30
지자체공동주택명세대수주소설치대수기준일자
9283충청북도 청주시성화누리안1,2차175충청북도 청주시 상당구 단재로115번길 44-1(영운동, 성화누리안1차아파트)22021-04-30
9284충청북도 청주시동산빌리지145충청북도 청주시 상당구 월평로253번길 110(용암동, 동산빌리지)32021-04-30
9285충청북도 청주시오송휴먼시아2단지469충청북도 청주시 흥덕구 오송읍 오송생명5로 201(오송마을휴먼시아2단지)72021-04-30
9286충청북도 청주시분평-계룡리슈빌아파트325충청북도 청주시 서원구 매봉로 26-1(분평동, 분평계룡리슈빌아파트)42021-04-30
9287충청북도 청주시청주지웰시티푸르지오519충청북도 청주시 흥덕구 대농로 45(복대동, 청주지웰시티푸르지오)72021-04-30
9288충청북도 청주시센토피아 롯데오피스텔126충청북도 청주시 청원구 오창읍 중부로 760(오창센토피아)12021-04-30
9289충청북도 청주시청주동남파밀리에4단지1080충북 청주시 상당구 용암동 2943-100182021-04-30
9290충청북도 청주시오창센토피아롯데캐슬2563충청북도 청주시 청원구 오창읍 중부로 760(오창센토피아)322021-04-30
9291충청북도 청주시대원칸타빌더테라스1단지679충청북도 청주시 상당구 중고개로 140(용암동, 칸타빌 더 테라스 1단지)162021-04-30
9292충청북도 청주시대원칸타빌더테라스2단지710충청북도 청주시 상당구 중고개로 104(용암동, 칸타빌 더 테라스 2단지)142021-04-30