Overview

Dataset statistics

Number of variables16
Number of observations285
Missing cells287
Missing cells (%)6.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.1 KiB
Average record size in memory133.5 B

Variable types

Numeric5
Text6
Categorical4
DateTime1

Dataset

Description대전광역시 서구 공동주택 현황입니다.(순번, 공동주택명, 위치, 지번주소, 도로명주소, 행정동명, 행정동코드, 법정동명, 법정동코드, 층수, 동수, 세대수, 사용승인일, 의무관리대상여부, 공동주택구분, 비고)
URLhttps://www.data.go.kr/data/15104512/fileData.do

Alerts

법정동명 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
동수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 동수High correlation
의무관리대상여부 is highly imbalanced (52.0%)Imbalance
비고 has 279 (97.9%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:34:47.470777
Analysis finished2023-12-12 16:34:52.146225
Duration4.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143
Minimum1
Maximum285
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T01:34:52.214477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.2
Q172
median143
Q3214
95-th percentile270.8
Maximum285
Range284
Interquartile range (IQR)142

Descriptive statistics

Standard deviation82.416625
Coefficient of variation (CV)0.57634003
Kurtosis-1.2
Mean143
Median Absolute Deviation (MAD)71
Skewness0
Sum40755
Variance6792.5
MonotonicityStrictly increasing
2023-12-13T01:34:52.349735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
189 1
 
0.4%
195 1
 
0.4%
194 1
 
0.4%
193 1
 
0.4%
192 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
188 1
 
0.4%
197 1
 
0.4%
Other values (275) 275
96.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
285 1
0.4%
284 1
0.4%
283 1
0.4%
282 1
0.4%
281 1
0.4%
280 1
0.4%
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%

공동주택명
Text

Distinct275
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T01:34:52.608884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length4.7964912
Min length2

Characters and Unicode

Total characters1367
Distinct characters257
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)93.7%

Sample

1st row성신연립
2nd row삼성연립
3rd row금강연립
4th row초원연립
5th row대중
ValueCountFrequency (%)
시티팰리스 4
 
1.3%
삼정하이츠 3
 
1.0%
도시형생활주택 3
 
1.0%
삼창 2
 
0.7%
나이스타운 2
 
0.7%
대림연립 2
 
0.7%
씨티캐슬 2
 
0.7%
복음 2
 
0.7%
복음맨션 2
 
0.7%
포도힐 2
 
0.7%
Other values (277) 281
92.1%
2023-12-13T01:34:52.994024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 47
 
3.4%
지 45
 
3.3%
리 45
 
3.3%
빌 41
 
3.0%
단 37
 
2.7%
이 29
 
2.1%
마 27
 
2.0%
2 25
 
1.8%
1 24
 
1.8%
아 22
 
1.6%
Other values (247) 1025
75.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1216
89.0%
Decimal Number 79
 
5.8%
Space Separator 21
 
1.5%
Close Punctuation 17
 
1.2%
Open Punctuation 17
 
1.2%
Uppercase Letter 7
 
0.5%
Dash Punctuation 6
 
0.4%
Lowercase Letter 3
 
0.2%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 47
 
3.9%
지 45
 
3.7%
리 45
 
3.7%
빌 41
 
3.4%
단 37
 
3.0%
이 29
 
2.4%
마 27
 
2.2%
아 22
 
1.8%
한 19
 
1.6%
을 19
 
1.6%
Other values (227) 885
72.8%
Decimal Number
ValueCountFrequency (%)
2 25
31.6%
1 24
30.4%
3 8
 
10.1%
5 6
 
7.6%
4 5
 
6.3%
8 4
 
5.1%
9 3
 
3.8%
7 3
 
3.8%
6 1
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
42.9%
B 1
 
14.3%
S 1
 
14.3%
T 1
 
14.3%
L 1
 
14.3%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1217
89.0%
Common 140
 
10.2%
Latin 10
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 47
 
3.9%
지 45
 
3.7%
리 45
 
3.7%
빌 41
 
3.4%
단 37
 
3.0%
이 29
 
2.4%
마 27
 
2.2%
아 22
 
1.8%
한 19
 
1.6%
을 19
 
1.6%
Other values (228) 886
72.8%
Common
ValueCountFrequency (%)
2 25
17.9%
1 24
17.1%
21
15.0%
) 17
12.1%
( 17
12.1%
3 8
 
5.7%
- 6
 
4.3%
5 6
 
4.3%
4 5
 
3.6%
8 4
 
2.9%
Other values (3) 7
 
5.0%
Latin
ValueCountFrequency (%)
K 3
30.0%
e 3
30.0%
B 1
 
10.0%
S 1
 
10.0%
T 1
 
10.0%
L 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1216
89.0%
ASCII 150
 
11.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 47
 
3.9%
지 45
 
3.7%
리 45
 
3.7%
빌 41
 
3.4%
단 37
 
3.0%
이 29
 
2.4%
마 27
 
2.2%
아 22
 
1.8%
한 19
 
1.6%
을 19
 
1.6%
Other values (227) 885
72.8%
ASCII
ValueCountFrequency (%)
2 25
16.7%
1 24
16.0%
21
14.0%
) 17
11.3%
( 17
11.3%
3 8
 
5.3%
- 6
 
4.0%
5 6
 
4.0%
4 5
 
3.3%
8 4
 
2.7%
Other values (9) 17
11.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

위치
Text

Distinct275
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T01:34:53.369681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length8.0736842
Min length4

Characters and Unicode

Total characters2301
Distinct characters46
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

Unique269 ?
Unique (%)94.4%

Sample

1st row도마동334-2
2nd row도마동 91-28
3rd row도마동 130-7
4th row변동 62-8
5th row내동 39-20 외2
ValueCountFrequency (%)
둔산동 46
 
8.0%
갈마동 31
 
5.4%
탄방동 28
 
4.9%
도마동 25
 
4.4%
관저동 23
 
4.0%
월평동 21
 
3.7%
용문동 20
 
3.5%
변동 14
 
2.4%
정림동 14
 
2.4%
내동 13
 
2.3%
Other values (283) 337
58.9%
2023-12-13T01:34:53.866917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
288
 
12.5%
동 285
 
12.4%
1 228
 
9.9%
2 123
 
5.3%
- 113
 
4.9%
9 105
 
4.6%
3 104
 
4.5%
8 89
 
3.9%
4 89
 
3.9%
6 87
 
3.8%
Other values (36) 790
34.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1041
45.2%
Other Letter 854
37.1%
Space Separator 288
 
12.5%
Dash Punctuation 113
 
4.9%
Other Punctuation 3
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 285
33.4%
마 58
 
6.8%
산 47
 
5.5%
둔 46
 
5.4%
도 34
 
4.0%
갈 31
 
3.6%
탄 28
 
3.3%
방 28
 
3.3%
정 27
 
3.2%
관 23
 
2.7%
Other values (21) 247
28.9%
Decimal Number
ValueCountFrequency (%)
1 228
21.9%
2 123
11.8%
9 105
10.1%
3 104
10.0%
8 89
 
8.5%
4 89
 
8.5%
6 87
 
8.4%
7 73
 
7.0%
0 72
 
6.9%
5 71
 
6.8%
Space Separator
ValueCountFrequency (%)
288
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 113
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1447
62.9%
Hangul 854
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 285
33.4%
마 58
 
6.8%
산 47
 
5.5%
둔 46
 
5.4%
도 34
 
4.0%
갈 31
 
3.6%
탄 28
 
3.3%
방 28
 
3.3%
정 27
 
3.2%
관 23
 
2.7%
Other values (21) 247
28.9%
Common
ValueCountFrequency (%)
288
19.9%
1 228
15.8%
2 123
8.5%
- 113
 
7.8%
9 105
 
7.3%
3 104
 
7.2%
8 89
 
6.2%
4 89
 
6.2%
6 87
 
6.0%
7 73
 
5.0%
Other values (5) 148
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1447
62.9%
Hangul 854
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
288
19.9%
1 228
15.8%
2 123
8.5%
- 113
 
7.8%
9 105
 
7.3%
3 104
 
7.2%
8 89
 
6.2%
4 89
 
6.2%
6 87
 
6.0%
7 73
 
5.0%
Other values (5) 148
10.2%
Hangul
ValueCountFrequency (%)
동 285
33.4%
마 58
 
6.8%
산 47
 
5.5%
둔 46
 
5.4%
도 34
 
4.0%
갈 31
 
3.6%
탄 28
 
3.3%
방 28
 
3.3%
정 27
 
3.2%
관 23
 
2.7%
Other values (21) 247
28.9%

지번주소
Text

Distinct273
Distinct (%)96.5%
Missing2
Missing (%)0.7%
Memory size2.4 KiB
2023-12-13T01:34:54.261369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.932862
Min length13

Characters and Unicode

Total characters4792
Distinct characters47
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

Unique267 ?
Unique (%)94.3%

Sample

1st row대전광역시 서구 도마동334-2
2nd row대전광역시 서구 도마동 91-28
3rd row대전광역시 서구 도마동 130-7
4th row대전광역시 서구 변동 62-8
5th row대전광역시 서구 내동 39-20 외2
ValueCountFrequency (%)
대전광역시 283
25.0%
서구 283
25.0%
둔산동 46
 
4.1%
갈마동 31
 
2.7%
탄방동 28
 
2.5%
도마동 25
 
2.2%
관저동 23
 
2.0%
월평동 21
 
1.9%
용문동 19
 
1.7%
정림동 14
 
1.2%
Other values (279) 360
31.8%
2023-12-13T01:34:54.761288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
850
17.7%
대 283
 
5.9%
광 283
 
5.9%
역 283
 
5.9%
시 283
 
5.9%
서 283
 
5.9%
구 283
 
5.9%
동 283
 
5.9%
전 283
 
5.9%
1 222
 
4.6%
Other values (37) 1456
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2817
58.8%
Decimal Number 1015
 
21.2%
Space Separator 850
 
17.7%
Dash Punctuation 110
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 283
10.0%
광 283
10.0%
역 283
10.0%
시 283
10.0%
서 283
10.0%
구 283
10.0%
동 283
10.0%
전 283
10.0%
마 58
 
2.1%
산 47
 
1.7%
Other values (25) 448
15.9%
Decimal Number
ValueCountFrequency (%)
1 222
21.9%
2 120
11.8%
9 104
10.2%
3 100
9.9%
6 86
 
8.5%
8 86
 
8.5%
4 83
 
8.2%
7 73
 
7.2%
5 72
 
7.1%
0 69
 
6.8%
Space Separator
ValueCountFrequency (%)
850
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2817
58.8%
Common 1975
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 283
10.0%
광 283
10.0%
역 283
10.0%
시 283
10.0%
서 283
10.0%
구 283
10.0%
동 283
10.0%
전 283
10.0%
마 58
 
2.1%
산 47
 
1.7%
Other values (25) 448
15.9%
Common
ValueCountFrequency (%)
850
43.0%
1 222
 
11.2%
2 120
 
6.1%
- 110
 
5.6%
9 104
 
5.3%
3 100
 
5.1%
6 86
 
4.4%
8 86
 
4.4%
4 83
 
4.2%
7 73
 
3.7%
Other values (2) 141
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2817
58.8%
ASCII 1975
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
850
43.0%
1 222
 
11.2%
2 120
 
6.1%
- 110
 
5.6%
9 104
 
5.3%
3 100
 
5.1%
6 86
 
4.4%
8 86
 
4.4%
4 83
 
4.2%
7 73
 
3.7%
Other values (2) 141
 
7.1%
Hangul
ValueCountFrequency (%)
대 283
10.0%
광 283
10.0%
역 283
10.0%
시 283
10.0%
서 283
10.0%
구 283
10.0%
동 283
10.0%
전 283
10.0%
마 58
 
2.1%
산 47
 
1.7%
Other values (25) 448
15.9%

도로명주소
Text

Distinct273
Distinct (%)96.5%
Missing2
Missing (%)0.7%
Memory size2.4 KiB
2023-12-13T01:34:55.071783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length17.865724
Min length11

Characters and Unicode

Total characters5056
Distinct characters70
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

Unique267 ?
Unique (%)94.3%

Sample

1st row대전광역시 서구 배재로91번길 8
2nd row대전광역시 서구 도마9길 23
3rd row대전광역시 서구 도마4길 37
4th row대전광역시 서구 도산로 164
5th row대전광역시 서구 갈마로212번길 29
ValueCountFrequency (%)
서구 285
25.1%
대전광역시 283
24.9%
둔산로 10
 
0.9%
청사로 8
 
0.7%
11 8
 
0.7%
둔지로 7
 
0.6%
대덕대로167번길 7
 
0.6%
대덕대로168번길 7
 
0.6%
문정로2번길 7
 
0.6%
23 6
 
0.5%
Other values (273) 507
44.7%
2023-12-13T01:34:55.562680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
853
16.9%
대 346
 
6.8%
서 307
 
6.1%
구 289
 
5.7%
역 288
 
5.7%
전 286
 
5.7%
광 283
 
5.6%
시 283
 
5.6%
로 271
 
5.4%
1 199
 
3.9%
Other values (60) 1651
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3200
63.3%
Decimal Number 988
 
19.5%
Space Separator 853
 
16.9%
Dash Punctuation 15
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 346
10.8%
서 307
9.6%
구 289
9.0%
역 288
9.0%
전 286
8.9%
광 283
8.8%
시 283
8.8%
로 271
8.5%
길 133
 
4.2%
번 121
 
3.8%
Other values (48) 593
18.5%
Decimal Number
ValueCountFrequency (%)
1 199
20.1%
2 140
14.2%
6 111
11.2%
5 100
10.1%
3 93
9.4%
0 79
 
8.0%
4 76
 
7.7%
7 70
 
7.1%
8 61
 
6.2%
9 59
 
6.0%
Space Separator
ValueCountFrequency (%)
853
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3200
63.3%
Common 1856
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 346
10.8%
서 307
9.6%
구 289
9.0%
역 288
9.0%
전 286
8.9%
광 283
8.8%
시 283
8.8%
로 271
8.5%
길 133
 
4.2%
번 121
 
3.8%
Other values (48) 593
18.5%
Common
ValueCountFrequency (%)
853
46.0%
1 199
 
10.7%
2 140
 
7.5%
6 111
 
6.0%
5 100
 
5.4%
3 93
 
5.0%
0 79
 
4.3%
4 76
 
4.1%
7 70
 
3.8%
8 61
 
3.3%
Other values (2) 74
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3200
63.3%
ASCII 1856
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
853
46.0%
1 199
 
10.7%
2 140
 
7.5%
6 111
 
6.0%
5 100
 
5.4%
3 93
 
5.0%
0 79
 
4.3%
4 76
 
4.1%
7 70
 
3.8%
8 61
 
3.3%
Other values (2) 74
 
4.0%
Hangul
ValueCountFrequency (%)
대 346
10.8%
서 307
9.6%
구 289
9.0%
역 288
9.0%
전 286
8.9%
광 283
8.8%
시 283
8.8%
로 271
8.5%
길 133
 
4.2%
번 121
 
3.8%
Other values (48) 593
18.5%

행정동명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
둔산2동
32 
탄방동
28 
갈마2동
22 
용문동
19 
관저2동
18 
Other values (19)
166 

Length

Max length4
Median length4
Mean length3.4526316
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도마2동
2nd row도마1동
3rd row도마1동
4th row변동
5th row내동

Common Values

ValueCountFrequency (%)
둔산2동 32
 
11.2%
탄방동 28
 
9.8%
갈마2동 22
 
7.7%
용문동 19
 
6.7%
관저2동 18
 
6.3%
도마1동 17
 
6.0%
변동 14
 
4.9%
정림동 14
 
4.9%
내동 13
 
4.6%
괴정동 13
 
4.6%
Other values (14) 95
33.3%

Length

2023-12-13T01:34:55.743295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산2동 32
 
11.2%
탄방동 28
 
9.8%
갈마2동 22
 
7.7%
용문동 19
 
6.7%
관저2동 18
 
6.3%
도마1동 17
 
6.0%
변동 14
 
4.9%
정림동 14
 
4.9%
내동 13
 
4.6%
괴정동 13
 
4.6%
Other values (14) 95
33.3%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)7.8%
Missing2
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean3.0170577 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T01:34:55.870296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017055 × 109
median3.0170581 × 109
Q33.0170597 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)4700

Descriptive statistics

Standard deviation4026.7193
Coefficient of variation (CV)1.3346511 × 10-6
Kurtosis-0.66328678
Mean3.0170577 × 109
Median Absolute Deviation (MAD)2600
Skewness0.41355231
Sum8.5382733 × 1011
Variance16214468
MonotonicityNot monotonic
2023-12-13T01:34:56.055791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
3017064000 32
 
11.2%
3017055500 28
 
9.8%
3017058200 22
 
7.7%
3017055000 19
 
6.7%
3017059700 18
 
6.3%
3017052000 17
 
6.0%
3017054000 14
 
4.9%
3017059000 14
 
4.9%
3017053500 14
 
4.9%
3017057500 13
 
4.6%
Other values (12) 92
32.3%
ValueCountFrequency (%)
3017051000 10
 
3.5%
3017052000 17
6.0%
3017053000 10
 
3.5%
3017053500 14
4.9%
3017054000 14
4.9%
3017055000 19
6.7%
3017055500 28
9.8%
3017056000 13
4.6%
3017057000 2
 
0.7%
3017057500 13
4.6%
ValueCountFrequency (%)
3017066000 9
 
3.2%
3017065000 8
 
2.8%
3017064000 32
11.2%
3017063000 5
 
1.8%
3017059700 18
6.3%
3017059600 5
 
1.8%
3017059000 14
4.9%
3017058800 6
 
2.1%
3017058700 9
 
3.2%
3017058600 6
 
2.1%

법정동명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
둔산동
46 
갈마동
31 
탄방동
28 
도마동
27 
관저동
23 
Other values (12)
130 

Length

Max length4
Median length3
Mean length2.9333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도마동
2nd row도마동
3rd row도마동
4th row변동
5th row내동

Common Values

ValueCountFrequency (%)
둔산동 46
16.1%
갈마동 31
10.9%
탄방동 28
9.8%
도마동 27
9.5%
관저동 23
8.1%
월평동 21
7.4%
용문동 19
 
6.7%
정림동 14
 
4.9%
변동 14
 
4.9%
괴정동 13
 
4.6%
Other values (7) 49
17.2%

Length

2023-12-13T01:34:56.197410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산동 46
16.1%
갈마동 31
10.9%
탄방동 28
9.8%
도마동 27
9.5%
관저동 23
8.1%
월평동 21
7.4%
용문동 19
 
6.7%
변동 14
 
4.9%
정림동 14
 
4.9%
괴정동 13
 
4.6%
Other values (7) 49
17.2%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)5.7%
Missing2
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean3.0170109 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T01:34:56.342873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170102 × 109
Q13.0170105 × 109
median3.0170111 × 109
Q33.0170112 × 109
95-th percentile3.0170116 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)700

Descriptive statistics

Standard deviation549.59825
Coefficient of variation (CV)1.8216648 × 10-7
Kurtosis1.6602111
Mean3.0170109 × 109
Median Absolute Deviation (MAD)500
Skewness0.84117534
Sum8.538141 × 1011
Variance302058.24
MonotonicityNot monotonic
2023-12-13T01:34:56.461482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3017011200 46
16.1%
3017011100 31
10.9%
3017010600 28
9.8%
3017010300 27
9.5%
3017011600 23
8.1%
3017011300 21
7.4%
3017010500 19
6.7%
3017010400 14
 
4.9%
3017010200 14
 
4.9%
3017011000 13
 
4.6%
Other values (6) 47
16.5%
ValueCountFrequency (%)
3017010100 10
 
3.5%
3017010200 14
4.9%
3017010300 27
9.5%
3017010400 14
4.9%
3017010500 19
6.7%
3017010600 28
9.8%
3017010800 13
4.6%
3017010900 2
 
0.7%
3017011000 13
4.6%
3017011100 31
10.9%
ValueCountFrequency (%)
3017012800 8
 
2.8%
3017011600 23
8.1%
3017011500 8
 
2.8%
3017011400 6
 
2.1%
3017011300 21
7.4%
3017011200 46
16.1%
3017011100 31
10.9%
3017011000 13
 
4.6%
3017010900 2
 
0.7%
3017010800 13
 
4.6%

층수
Text

Distinct92
Distinct (%)32.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T01:34:56.688381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.3263158
Min length3

Characters and Unicode

Total characters1233
Distinct characters16
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)18.9%

Sample

1st row0/4
2nd row1/2
3rd row1/2
4th row1/3
5th row1/3
ValueCountFrequency (%)
1/15 47
 
16.4%
0/5 23
 
8.0%
1/10 11
 
3.8%
2/12 10
 
3.5%
1/6 9
 
3.1%
2/15 8
 
2.8%
1/9 8
 
2.8%
2/10 7
 
2.4%
1/12 7
 
2.4%
1/3 6
 
2.1%
Other values (83) 150
52.4%
2023-12-13T01:34:57.193857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 384
31.1%
/ 285
23.1%
2 158
12.8%
5 130
 
10.5%
0 70
 
5.7%
3 58
 
4.7%
∼ 50
 
4.1%
4 31
 
2.5%
6 19
 
1.5%
7 14
 
1.1%
Other values (6) 34
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 886
71.9%
Other Punctuation 285
 
23.1%
Math Symbol 58
 
4.7%
Other Letter 2
 
0.2%
Space Separator 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 384
43.3%
2 158
17.8%
5 130
 
14.7%
0 70
 
7.9%
3 58
 
6.5%
4 31
 
3.5%
6 19
 
2.1%
7 14
 
1.6%
9 13
 
1.5%
8 9
 
1.0%
Math Symbol
ValueCountFrequency (%)
∼ 50
86.2%
~ 8
 
13.8%
Other Punctuation
ValueCountFrequency (%)
/ 285
100.0%
Other Letter
ValueCountFrequency (%)
지 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1231
99.8%
Hangul 2
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 384
31.2%
/ 285
23.2%
2 158
12.8%
5 130
 
10.6%
0 70
 
5.7%
3 58
 
4.7%
∼ 50
 
4.1%
4 31
 
2.5%
6 19
 
1.5%
7 14
 
1.1%
Other values (5) 32
 
2.6%
Hangul
ValueCountFrequency (%)
지 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1181
95.8%
Math Operators 50
 
4.1%
Hangul 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 384
32.5%
/ 285
24.1%
2 158
13.4%
5 130
 
11.0%
0 70
 
5.9%
3 58
 
4.9%
4 31
 
2.6%
6 19
 
1.6%
7 14
 
1.2%
9 13
 
1.1%
Other values (4) 19
 
1.6%
Math Operators
ValueCountFrequency (%)
∼ 50
100.0%
Hangul
ValueCountFrequency (%)
지 2
100.0%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0666667
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T01:34:57.365663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q38
95-th percentile16
Maximum27
Range26
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.5053538
Coefficient of variation (CV)1.086583
Kurtosis2.4091963
Mean5.0666667
Median Absolute Deviation (MAD)1
Skewness1.611086
Sum1444
Variance30.30892
MonotonicityNot monotonic
2023-12-13T01:34:57.519183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 124
43.5%
2 20
 
7.0%
3 17
 
6.0%
6 15
 
5.3%
4 14
 
4.9%
8 13
 
4.6%
9 12
 
4.2%
5 11
 
3.9%
12 10
 
3.5%
10 8
 
2.8%
Other values (14) 41
 
14.4%
ValueCountFrequency (%)
1 124
43.5%
2 20
 
7.0%
3 17
 
6.0%
4 14
 
4.9%
5 11
 
3.9%
6 15
 
5.3%
7 7
 
2.5%
8 13
 
4.6%
9 12
 
4.2%
10 8
 
2.8%
ValueCountFrequency (%)
27 2
 
0.7%
25 1
 
0.4%
24 1
 
0.4%
22 2
 
0.7%
20 3
1.1%
19 1
 
0.4%
18 1
 
0.4%
17 3
1.1%
16 3
1.1%
15 5
1.8%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct196
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean445.90877
Minimum20
Maximum2910
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-13T01:34:57.661922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile28
Q164
median154
Q3700
95-th percentile1632
Maximum2910
Range2890
Interquartile range (IQR)636

Descriptive statistics

Standard deviation540.69144
Coefficient of variation (CV)1.2125607
Kurtosis2.4558837
Mean445.90877
Median Absolute Deviation (MAD)119
Skewness1.6358776
Sum127084
Variance292347.24
MonotonicityNot monotonic
2023-12-13T01:34:57.812650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24 6
 
2.1%
36 6
 
2.1%
80 6
 
2.1%
78 6
 
2.1%
50 5
 
1.8%
48 5
 
1.8%
99 5
 
1.8%
60 4
 
1.4%
49 4
 
1.4%
30 3
 
1.1%
Other values (186) 235
82.5%
ValueCountFrequency (%)
20 2
 
0.7%
21 1
 
0.4%
22 2
 
0.7%
24 6
2.1%
26 2
 
0.7%
28 3
1.1%
29 3
1.1%
30 3
1.1%
35 1
 
0.4%
36 6
2.1%
ValueCountFrequency (%)
2910 1
0.4%
2398 1
0.4%
2200 1
0.4%
2199 1
0.4%
2010 1
0.4%
1980 2
0.7%
1950 1
0.4%
1881 1
0.4%
1762 1
0.4%
1734 1
0.4%

사용승인일
Date

Distinct265
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1979-08-17 00:00:00
Maximum2023-06-01 00:00:00
2023-12-13T01:34:57.940689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:58.086679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

의무관리대상여부
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
비의무
141 
의무
140 
의무(통합관리)
 
2
비의무(통합관리)
 
1
비의
 
1

Length

Max length9
Median length8
Mean length2.5614035
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
비의무 141
49.5%
의무 140
49.1%
의무(통합관리) 2
 
0.7%
비의무(통합관리) 1
 
0.4%
비의 1
 
0.4%

Length

2023-12-13T01:34:58.262262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:34:58.392205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비의무 141
49.5%
의무 140
49.1%
의무(통합관리 2
 
0.7%
비의무(통합관리 1
 
0.4%
비의 1
 
0.4%

공동주택구분
Categorical

Distinct5
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
아파트
174 
주상복합
77 
연립주택
27 
다세대주택
 
5
도시형생활주택(원룸형)
 
2

Length

Max length12
Median length3
Mean length3.4631579
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연립주택
2nd row아파트
3rd row아파트
4th row아파트
5th row아파트

Common Values

ValueCountFrequency (%)
아파트 174
61.1%
주상복합 77
27.0%
연립주택 27
 
9.5%
다세대주택 5
 
1.8%
도시형생활주택(원룸형) 2
 
0.7%

Length

2023-12-13T01:34:58.511389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:34:58.613029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 174
61.1%
주상복합 77
27.0%
연립주택 27
 
9.5%
다세대주택 5
 
1.8%
도시형생활주택(원룸형 2
 
0.7%

비고
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing279
Missing (%)97.9%
Memory size2.4 KiB
2023-12-13T01:34:58.790720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length17
Mean length9.3333333
Min length4

Characters and Unicode

Total characters56
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row영구임대
2nd row영구임대
3rd row20년이상(2002.3.31 이전 준공단지 적용)
4th row도시형(연립)
5th row도시형(원룸)
ValueCountFrequency (%)
영구임대 2
22.2%
도시형(원룸 2
22.2%
20년이상(2002.3.31 1
11.1%
이전 1
11.1%
준공단지 1
11.1%
적용 1
11.1%
도시형(연립 1
11.1%
2023-12-13T01:34:59.126533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 4
 
7.1%
) 4
 
7.1%
0 3
 
5.4%
3
 
5.4%
도 3
 
5.4%
시 3
 
5.4%
형 3
 
5.4%
2 3
 
5.4%
영 2
 
3.6%
3 2
 
3.6%
Other values (19) 26
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 34
60.7%
Decimal Number 9
 
16.1%
Open Punctuation 4
 
7.1%
Close Punctuation 4
 
7.1%
Space Separator 3
 
5.4%
Other Punctuation 2
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 3
 
8.8%
시 3
 
8.8%
형 3
 
8.8%
영 2
 
5.9%
구 2
 
5.9%
이 2
 
5.9%
룸 2
 
5.9%
원 2
 
5.9%
대 2
 
5.9%
임 2
 
5.9%
Other values (11) 11
32.4%
Decimal Number
ValueCountFrequency (%)
0 3
33.3%
2 3
33.3%
3 2
22.2%
1 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 34
60.7%
Common 22
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 3
 
8.8%
시 3
 
8.8%
형 3
 
8.8%
영 2
 
5.9%
구 2
 
5.9%
이 2
 
5.9%
룸 2
 
5.9%
원 2
 
5.9%
대 2
 
5.9%
임 2
 
5.9%
Other values (11) 11
32.4%
Common
ValueCountFrequency (%)
( 4
18.2%
) 4
18.2%
0 3
13.6%
3
13.6%
2 3
13.6%
3 2
9.1%
. 2
9.1%
1 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 34
60.7%
ASCII 22
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 4
18.2%
) 4
18.2%
0 3
13.6%
3
13.6%
2 3
13.6%
3 2
9.1%
. 2
9.1%
1 1
 
4.5%
Hangul
ValueCountFrequency (%)
도 3
 
8.8%
시 3
 
8.8%
형 3
 
8.8%
영 2
 
5.9%
구 2
 
5.9%
이 2
 
5.9%
룸 2
 
5.9%
원 2
 
5.9%
대 2
 
5.9%
임 2
 
5.9%
Other values (11) 11
32.4%

Interactions

2023-12-13T01:34:50.818648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:48.516862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.086655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.698622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.284290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.921106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:48.616024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.211355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.804256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.379722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:51.038391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:48.740257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.342010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.939148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.502953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:51.144823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:48.853111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.459771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.044698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.630944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:51.245679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:48.974209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:49.576300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.155328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:50.730957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:34:59.224298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동명행정동코드법정동명법정동코드층수동수세대수의무관리대상여부공동주택구분비고
순번1.0000.7270.4870.6370.4960.8640.4620.5310.5940.7781.000
행정동명0.7271.0001.0001.0001.0000.9070.6610.6830.5500.6281.000
행정동코드0.4871.0001.0000.9660.9350.8190.4320.4740.4200.4871.000
법정동명0.6371.0000.9661.0001.0000.8910.5330.6290.5420.5731.000
법정동코드0.4961.0000.9351.0001.0000.8480.3920.4840.3690.3331.000
층수0.8640.9070.8190.8910.8481.0000.8000.8750.0000.8121.000
동수0.4620.6610.4320.5330.3920.8001.0000.9380.6530.5531.000
세대수0.5310.6830.4740.6290.4840.8750.9381.0000.7130.5700.000
의무관리대상여부0.5940.5500.4200.5420.3690.0000.6530.7131.0000.6721.000
공동주택구분0.7780.6280.4870.5730.3330.8120.5530.5700.6721.0001.000
비고1.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.000
2023-12-13T01:34:59.356901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의무관리대상여부법정동명공동주택구분행정동명
의무관리대상여부1.0000.3060.3090.298
법정동명0.3061.0000.3300.987
공동주택구분0.3090.3301.0000.358
행정동명0.2980.9870.3581.000
2023-12-13T01:34:59.460963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드법정동코드동수세대수행정동명법정동명의무관리대상여부공동주택구분
순번1.0000.0680.092-0.342-0.1670.3610.3080.2840.430
행정동코드0.0681.0000.9120.1790.3600.9740.8450.2360.286
법정동코드0.0920.9121.0000.2870.4220.9710.9840.2240.204
동수-0.3420.1790.2871.0000.7970.3010.2380.3250.259
세대수-0.1670.3600.4220.7971.0000.3230.3020.3710.269
행정동명0.3610.9740.9710.3010.3231.0000.9870.2980.358
법정동명0.3080.8450.9840.2380.3020.9871.0000.3060.330
의무관리대상여부0.2840.2360.2240.3250.3710.2980.3061.0000.309
공동주택구분0.4300.2860.2040.2590.2690.3580.3300.3091.000

Missing values

2023-12-13T01:34:51.409260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:34:51.654923image/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.
2023-12-13T01:34:52.073281image/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

순번공동주택명위치지번주소도로명주소행정동명행정동코드법정동명법정동코드층수동수세대수사용승인일의무관리대상여부공동주택구분비고
01성신연립도마동334-2대전광역시 서구 도마동334-2대전광역시 서구 배재로91번길 8도마2동3017053000도마동30170103000/42301979-08-17비의무연립주택<NA>
12삼성연립도마동 91-28대전광역시 서구 도마동 91-28대전광역시 서구 도마9길 23도마1동3017052000도마동30170103001/23241980-01-07비의무아파트<NA>
23금강연립도마동 130-7대전광역시 서구 도마동 130-7대전광역시 서구 도마4길 37도마1동3017052000도마동30170103001/23241980-09-09비의무아파트<NA>
34초원연립변동 62-8대전광역시 서구 변동 62-8대전광역시 서구 도산로 164변동3017054000변동30170102001/32361980-10-17비의무아파트<NA>
45대중내동 39-20 외2대전광역시 서구 내동 39-20 외2대전광역시 서구 갈마로212번길 29내동3017057500내동30170110001/32301980-12-23비의무아파트<NA>
56우진연립괴정동 48-9대전광역시 서구 괴정동 48-9대전광역시 서구 도솔로 366괴정동3017056000괴정동30170108001/32241980-12-30비의무아파트<NA>
67신진상가아파트괴정동 97-1대전광역시 서구 괴정동 97-1대전광역시 서구 도솔로305번길 23괴정동3017056000괴정동30170108001/31441981-02-23비의무아파트<NA>
78대성연립용문동 231-1 외4<NA><NA><NA><NA><NA><NA>1/32381981-03-07비의무아파트<NA>
89대건연립도마동 68-1대전광역시 서구 도마동 68-1대전광역시 서구 용화4길 52도마1동3017052000도마동30170103001/25501981-05-28비의무아파트<NA>
910무지개연립용문동 258-16대전광역시 서구 용문동 258-16대전광역시 서구 도산로370번길 11용문동3017055000용문동30170105000/2∼351031981-08-26비의무연립주택<NA>
순번공동주택명위치지번주소도로명주소행정동명행정동코드법정동명법정동코드층수동수세대수사용승인일의무관리대상여부공동주택구분비고
275276토르괴정동 123-7대전광역시 서구 괴정동 123-7대전광역시 서구 괴정로22번길 20괴정동3017056000괴정동30170108000/51282021-01-05비의무아파트<NA>
276277더빅토리아월평동 25-75대전광역시 서구 월평동 25-75대전광역시 서구 계룡로264번길 89월평1동3017058600월평동30170113001/131222021-04-08비의무아파트<NA>
277278트리풀시티레이크포레도안동 2354대전광역시 서구 도안동 2354대전광역시 서구 도안동로 234도안동3017059000도안동3017011500지2/272717622021-10-07의무아파트<NA>
278279용문동 도시형생활주택용문동 269-7대전광역시 서구 용문동 269-7대전광역시 서구 도산로341번길 30용문동3017055000용문동30170105000/51292021-10-27비의무연립주택도시형(연립)
279280BL 캐슬괴정동 431대전광역시 서구 괴정동 431대전광역시 서구 갈마로219번길 29괴정동3017056000괴정동30170108000/51362021-11-16비의무연립주택도시형(원룸)
280281행복한 가괴정동 432대전광역시 서구 괴정동 432대전광역시 서구 갈마로219번길 25괴정동3017056000괴정동30170108000/51362021-11-17비의무연립주택도시형(원룸)
281282그레이스 K5만년동 369대전광역시 서구 만년동 369대전광역시 서구 만년로68번길 52만년동3017065000만년동3017012800지2/151782021-12-06비의무아파트<NA>
282283씨티캐슬괴정동 135-7대전광역시 서구 괴정동 135-7대전광역시 서구 갈마로 180괴정동3017056000괴정동30170108000/51262021-12-06비의무연립주택<NA>
283284도마e편한세상포레나도마동 584대전광역시 서구 도마동 584대전광역시 서구 도산로8도마1동3017052000도마동30170103000/342018812022-07-28의무아파트<NA>
284285씨티캐슬용문동 262-5대전광역시 서구 용문동 262-5대전광역시 용문로94용문동3017055000용문동30170105000/51202023-06-01비의연립주택<NA>