Overview

Dataset statistics

Number of variables9
Number of observations190
Missing cells4
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.9 KiB
Average record size in memory74.7 B

Variable types

Text4
DateTime3
Numeric2

Dataset

Description경기도 김포시 아파트 현황 정보에 대한 데이터로 명칭, 소재지주소, 승인일, 준공일, 층수, 동수, 세대수, 관리사무소 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15036624/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 동수High correlation
관리사무소 전화번호 has 4 (2.1%) missing valuesMissing
소재지주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:35:14.489537
Analysis finished2023-12-12 15:35:15.807872
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

Distinct188
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T00:35:16.085175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length9.1947368
Min length2

Characters and Unicode

Total characters1747
Distinct characters221
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)97.9%

Sample

1st row태산
2nd row함성1차
3rd row한일함성1차
4th row함성2차
5th row고촌 길훈1차
ValueCountFrequency (%)
고창마을 9
 
2.5%
풍년마을 9
 
2.5%
1단지 7
 
2.0%
현대 7
 
2.0%
더 6
 
1.7%
월드 6
 
1.7%
곡촌마을 6
 
1.7%
2단지 6
 
1.7%
주공 6
 
1.7%
한강신도시 6
 
1.7%
Other values (218) 290
81.0%
2023-12-13T00:35:16.596708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168
 
9.6%
마 101
 
5.8%
을 96
 
5.5%
지 52
 
3.0%
한 47
 
2.7%
단 42
 
2.4%
2 32
 
1.8%
강 31
 
1.8%
1 29
 
1.7%
차 28
 
1.6%
Other values (211) 1121
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1437
82.3%
Space Separator 168
 
9.6%
Decimal Number 92
 
5.3%
Lowercase Letter 31
 
1.8%
Uppercase Letter 18
 
1.0%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 101
 
7.0%
을 96
 
6.7%
지 52
 
3.6%
한 47
 
3.3%
단 42
 
2.9%
강 31
 
2.2%
차 28
 
1.9%
이 28
 
1.9%
풍 26
 
1.8%
트 24
 
1.7%
Other values (183) 962
66.9%
Lowercase Letter
ValueCountFrequency (%)
e 8
25.8%
s 3
 
9.7%
w 2
 
6.5%
t 2
 
6.5%
h 2
 
6.5%
p 2
 
6.5%
g 2
 
6.5%
a 2
 
6.5%
r 2
 
6.5%
v 2
 
6.5%
Other values (2) 4
12.9%
Decimal Number
ValueCountFrequency (%)
2 32
34.8%
1 29
31.5%
3 15
16.3%
5 6
 
6.5%
4 4
 
4.3%
6 2
 
2.2%
9 1
 
1.1%
7 1
 
1.1%
8 1
 
1.1%
0 1
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
L 6
33.3%
H 6
33.3%
C 4
22.2%
K 2
 
11.1%
Space Separator
ValueCountFrequency (%)
168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1437
82.3%
Common 261
 
14.9%
Latin 49
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 101
 
7.0%
을 96
 
6.7%
지 52
 
3.6%
한 47
 
3.3%
단 42
 
2.9%
강 31
 
2.2%
차 28
 
1.9%
이 28
 
1.9%
풍 26
 
1.8%
트 24
 
1.7%
Other values (183) 962
66.9%
Latin
ValueCountFrequency (%)
e 8
16.3%
L 6
12.2%
H 6
12.2%
C 4
 
8.2%
s 3
 
6.1%
w 2
 
4.1%
K 2
 
4.1%
t 2
 
4.1%
h 2
 
4.1%
p 2
 
4.1%
Other values (6) 12
24.5%
Common
ValueCountFrequency (%)
168
64.4%
2 32
 
12.3%
1 29
 
11.1%
3 15
 
5.7%
5 6
 
2.3%
4 4
 
1.5%
6 2
 
0.8%
9 1
 
0.4%
- 1
 
0.4%
7 1
 
0.4%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1437
82.3%
ASCII 310
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
54.2%
2 32
 
10.3%
1 29
 
9.4%
3 15
 
4.8%
e 8
 
2.6%
L 6
 
1.9%
5 6
 
1.9%
H 6
 
1.9%
C 4
 
1.3%
4 4
 
1.3%
Other values (18) 32
 
10.3%
Hangul
ValueCountFrequency (%)
마 101
 
7.0%
을 96
 
6.7%
지 52
 
3.6%
한 47
 
3.3%
단 42
 
2.9%
강 31
 
2.2%
차 28
 
1.9%
이 28
 
1.9%
풍 26
 
1.8%
트 24
 
1.7%
Other values (183) 962
66.9%

소재지주소
Text

UNIQUE 

Distinct190
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T00:35:16.998731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length19.526316
Min length13

Characters and Unicode

Total characters3710
Distinct characters119
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

Unique190 ?
Unique (%)100.0%

Sample

1st row경기도 김포시 봉화로21번길 6
2nd row경기도 김포시 김포대로 1037-16
3rd row경기도 김포시 북변중로 104-5
4th row경기도 김포시 중봉1로 56,58
5th row경기도 김포시 고촌읍 장차로 25
ValueCountFrequency (%)
경기도 190
23.3%
김포시 189
23.2%
김포한강2로 17
 
2.1%
고촌읍 15
 
1.8%
양촌읍 15
 
1.8%
통진읍 13
 
1.6%
김포한강8로 13
 
1.6%
김포한강11로 9
 
1.1%
김포대로926번길 5
 
0.6%
수기로 5
 
0.6%
Other values (237) 345
42.3%
2023-12-13T00:35:17.529649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
629
17.0%
포 273
 
7.4%
김 264
 
7.1%
기 197
 
5.3%
도 193
 
5.2%
경 190
 
5.1%
시 190
 
5.1%
로 188
 
5.1%
1 158
 
4.3%
3 103
 
2.8%
Other values (109) 1325
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2246
60.5%
Decimal Number 753
 
20.3%
Space Separator 629
 
17.0%
Dash Punctuation 28
 
0.8%
Other Punctuation 15
 
0.4%
Close Punctuation 15
 
0.4%
Open Punctuation 15
 
0.4%
Uppercase Letter 8
 
0.2%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 273
12.2%
김 264
11.8%
기 197
 
8.8%
도 193
 
8.6%
경 190
 
8.5%
시 190
 
8.5%
로 188
 
8.4%
강 68
 
3.0%
한 67
 
3.0%
길 65
 
2.9%
Other values (89) 551
24.5%
Decimal Number
ValueCountFrequency (%)
1 158
21.0%
3 103
13.7%
2 99
13.1%
8 68
9.0%
7 62
 
8.2%
5 57
 
7.6%
6 55
 
7.3%
4 55
 
7.3%
9 54
 
7.2%
0 42
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
L 3
37.5%
H 2
25.0%
A 2
25.0%
B 1
 
12.5%
Space Separator
ValueCountFrequency (%)
629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Lowercase Letter
ValueCountFrequency (%)
c 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2246
60.5%
Common 1455
39.2%
Latin 9
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 273
12.2%
김 264
11.8%
기 197
 
8.8%
도 193
 
8.6%
경 190
 
8.5%
시 190
 
8.5%
로 188
 
8.4%
강 68
 
3.0%
한 67
 
3.0%
길 65
 
2.9%
Other values (89) 551
24.5%
Common
ValueCountFrequency (%)
629
43.2%
1 158
 
10.9%
3 103
 
7.1%
2 99
 
6.8%
8 68
 
4.7%
7 62
 
4.3%
5 57
 
3.9%
6 55
 
3.8%
4 55
 
3.8%
9 54
 
3.7%
Other values (5) 115
 
7.9%
Latin
ValueCountFrequency (%)
L 3
33.3%
H 2
22.2%
A 2
22.2%
B 1
 
11.1%
c 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2246
60.5%
ASCII 1464
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
629
43.0%
1 158
 
10.8%
3 103
 
7.0%
2 99
 
6.8%
8 68
 
4.6%
7 62
 
4.2%
5 57
 
3.9%
6 55
 
3.8%
4 55
 
3.8%
9 54
 
3.7%
Other values (10) 124
 
8.5%
Hangul
ValueCountFrequency (%)
포 273
12.2%
김 264
11.8%
기 197
 
8.8%
도 193
 
8.6%
경 190
 
8.5%
시 190
 
8.5%
로 188
 
8.4%
강 68
 
3.0%
한 67
 
3.0%
길 65
 
2.9%
Other values (89) 551
24.5%

승인일
Date

Distinct145
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1985-11-27 00:00:00
Maximum2020-07-10 00:00:00
2023-12-13T00:35:17.708009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:17.888357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

준공일
Date

Distinct167
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum1986-07-08 00:00:00
Maximum2023-04-26 00:00:00
2023-12-13T00:35:18.034819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:18.173377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

층수
Text

Distinct86
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-13T00:35:18.464418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length3.2894737
Min length1

Characters and Unicode

Total characters625
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)30.5%

Sample

1st row5
2nd row5
3rd row6
4th row5
5th row14
ValueCountFrequency (%)
15 35
 
18.4%
20 17
 
8.9%
18 13
 
6.8%
13 5
 
2.6%
29 4
 
2.1%
14 4
 
2.1%
17 4
 
2.1%
20~29 4
 
2.1%
9~15 3
 
1.6%
5 3
 
1.6%
Other values (76) 98
51.6%
2023-12-13T00:35:18.926393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 170
27.2%
2 106
17.0%
~ 88
14.1%
5 82
13.1%
0 40
 
6.4%
8 29
 
4.6%
9 28
 
4.5%
3 25
 
4.0%
6 21
 
3.4%
4 19
 
3.0%
Other values (3) 17
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 535
85.6%
Math Symbol 88
 
14.1%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 170
31.8%
2 106
19.8%
5 82
15.3%
0 40
 
7.5%
8 29
 
5.4%
9 28
 
5.2%
3 25
 
4.7%
6 21
 
3.9%
4 19
 
3.6%
7 15
 
2.8%
Math Symbol
ValueCountFrequency (%)
~ 88
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 625
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 170
27.2%
2 106
17.0%
~ 88
14.1%
5 82
13.1%
0 40
 
6.4%
8 29
 
4.6%
9 28
 
4.5%
3 25
 
4.0%
6 21
 
3.4%
4 19
 
3.0%
Other values (3) 17
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 170
27.2%
2 106
17.0%
~ 88
14.1%
5 82
13.1%
0 40
 
6.4%
8 29
 
4.6%
9 28
 
4.5%
3 25
 
4.0%
6 21
 
3.4%
4 19
 
3.0%
Other values (3) 17
 
2.7%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5421053
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T00:35:19.115290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median8
Q312
95-th percentile23.55
Maximum36
Range35
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.6225377
Coefficient of variation (CV)0.69403319
Kurtosis2.674098
Mean9.5421053
Median Absolute Deviation (MAD)3
Skewness1.5157916
Sum1813
Variance43.858006
MonotonicityNot monotonic
2023-12-13T00:35:19.279408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
5 23
12.1%
8 18
 
9.5%
4 16
 
8.4%
6 14
 
7.4%
10 13
 
6.8%
7 12
 
6.3%
14 12
 
6.3%
2 10
 
5.3%
9 9
 
4.7%
11 9
 
4.7%
Other values (20) 54
28.4%
ValueCountFrequency (%)
1 5
 
2.6%
2 10
5.3%
3 7
 
3.7%
4 16
8.4%
5 23
12.1%
6 14
7.4%
7 12
6.3%
8 18
9.5%
9 9
 
4.7%
10 13
6.8%
ValueCountFrequency (%)
36 1
 
0.5%
35 1
 
0.5%
32 1
 
0.5%
28 1
 
0.5%
27 3
1.6%
26 1
 
0.5%
25 1
 
0.5%
24 1
 
0.5%
23 1
 
0.5%
22 3
1.6%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct182
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean731.76316
Minimum40
Maximum3481
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-13T00:35:19.478717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile147.25
Q1353.25
median573
Q3968.75
95-th percentile1819
Maximum3481
Range3441
Interquartile range (IQR)615.5

Descriptive statistics

Standard deviation557.4822
Coefficient of variation (CV)0.7618342
Kurtosis3.7733742
Mean731.76316
Median Absolute Deviation (MAD)273.5
Skewness1.6904146
Sum139035
Variance310786.4
MonotonicityNot monotonic
2023-12-13T00:35:19.990794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500 2
 
1.1%
228 2
 
1.1%
150 2
 
1.1%
384 2
 
1.1%
574 2
 
1.1%
220 2
 
1.1%
446 2
 
1.1%
242 2
 
1.1%
1136 1
 
0.5%
845 1
 
0.5%
Other values (172) 172
90.5%
ValueCountFrequency (%)
40 1
0.5%
70 1
0.5%
71 1
0.5%
93 1
0.5%
130 1
0.5%
133 1
0.5%
138 1
0.5%
140 1
0.5%
143 1
0.5%
145 1
0.5%
ValueCountFrequency (%)
3481 1
0.5%
2712 1
0.5%
2467 1
0.5%
2456 1
0.5%
2255 1
0.5%
2230 1
0.5%
1942 1
0.5%
1872 1
0.5%
1860 1
0.5%
1846 1
0.5%

관리사무소 전화번호
Text

MISSING 

Distinct185
Distinct (%)99.5%
Missing4
Missing (%)2.1%
Memory size1.6 KiB
2023-12-13T00:35:20.258946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010753
Min length12

Characters and Unicode

Total characters2234
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

Unique184 ?
Unique (%)98.9%

Sample

1st row031-983-6809
2nd row031-986-2870
3rd row031-982-4735
4th row031-984-9087
5th row031-986-7670
ValueCountFrequency (%)
031-989-0268 2
 
1.1%
031-996-6889 1
 
0.5%
031-986-7636 1
 
0.5%
031-989-0878 1
 
0.5%
031-985-5860 1
 
0.5%
031-996-1324 1
 
0.5%
031-997-7320 1
 
0.5%
031-996-3190 1
 
0.5%
031-984-2572 1
 
0.5%
031-985-4215 1
 
0.5%
Other values (175) 175
94.1%
2023-12-13T00:35:20.695405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 372
16.7%
9 315
14.1%
0 282
12.6%
1 274
12.3%
3 273
12.2%
8 224
10.0%
2 118
 
5.3%
6 110
 
4.9%
7 102
 
4.6%
5 88
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1862
83.3%
Dash Punctuation 372
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 315
16.9%
0 282
15.1%
1 274
14.7%
3 273
14.7%
8 224
12.0%
2 118
 
6.3%
6 110
 
5.9%
7 102
 
5.5%
5 88
 
4.7%
4 76
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2234
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 372
16.7%
9 315
14.1%
0 282
12.6%
1 274
12.3%
3 273
12.2%
8 224
10.0%
2 118
 
5.3%
6 110
 
4.9%
7 102
 
4.6%
5 88
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 372
16.7%
9 315
14.1%
0 282
12.6%
1 274
12.3%
3 273
12.2%
8 224
10.0%
2 118
 
5.3%
6 110
 
4.9%
7 102
 
4.6%
5 88
 
3.9%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2023-07-13 00:00:00
Maximum2023-07-13 00:00:00
2023-12-13T00:35:20.856764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:20.989457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T00:35:15.251920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:15.009589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:15.384520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:35:15.136225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:35:21.094750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층수동수세대수
층수1.0000.8080.832
동수0.8081.0000.833
세대수0.8320.8331.000
2023-12-13T00:35:21.211096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수
동수1.0000.886
세대수0.8861.000

Missing values

2023-12-13T00:35:15.556676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:35:15.728031image/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

아파트명소재지주소승인일준공일층수동수세대수관리사무소 전화번호데이터기준일자
0태산경기도 김포시 봉화로21번길 61985-11-271986-07-085140<NA>2023-07-13
1함성1차경기도 김포시 김포대로 1037-161987-10-121988-10-195170<NA>2023-07-13
2한일함성1차경기도 김포시 북변중로 104-51989-09-181990-11-0662150031-983-68092023-07-13
3함성2차경기도 김포시 중봉1로 56,581990-03-061991-06-1857140<NA>2023-07-13
4고촌 길훈1차경기도 김포시 고촌읍 장차로 251990-06-271991-12-24142275031-986-28702023-07-13
5신한경기도 김포시 감정로3 (감정동, 신한아파트)1991-08-311992-11-2162202031-982-47352023-07-13
6풍무 길훈1차경기도 김포시 장릉로 561991-07-111993-05-03154496031-984-90872023-07-13
7성창경기도 김포시 운양로 1761993-05-311994-11-3064162031-986-76702023-07-13
8현대경기도 김포시 중구로 931993-01-061995-02-11101130031-983-28162023-07-13
9대우산호경기도 김포시 봉화로182번길 331993-06-241995-03-30136543031-982-35822023-07-13
아파트명소재지주소승인일준공일층수동수세대수관리사무소 전화번호데이터기준일자
180캐슬앤파밀리에시티1단지경기도 김포시 태리로 2362018-03-232020-11-2316362255031-986-75152023-07-13
181한강신도시 동일스위트 the park view 1단지경기도 김포한강8로 173-882017-08-302020-12-1720~29121021031-983-59562023-07-13
182한강신도시 동일스위트 the park view 2단지경기도 김포한강8로 1272017-12-072020-12-1725~268711031-8049-76072023-07-13
183김포한강엘에이치1단지경기도 김포시 허산길 502016-12-142021-02-0949443031-996-15522023-07-13
184메트로타워 예미지경기도 김포시 솔터로 222017-09-192021-02-1728/45~465701031-997-69722023-07-13
185김포마송엘에이치3단지경기도 김포시 통진읍 마송1로 43번길2017-11-012021-03-1012~1581088031-996-10822023-07-13
186김포마송엘에이치5단지경기도 김포시 통진읍 율마로438번길 512016-12-222021-04-22182500031-996-57962023-07-13
187e편한세상 김포로얄하임경기도 김포시 통진읍 마송1로 1222019-06-042021-06-0817~187574031-996-57602023-07-13
188e편한세상 김포어반베뉴경기도 김포시 통진읍 율마로438번길 522020-06-052022-09-06187544031-988-59412023-07-13
189김포마송1차 대방엘리움 센트럴파크경기도 김포시 통진읍 마송공원길 352020-07-102023-04-2615~1713841031-984-92882023-07-13