Overview

Dataset statistics

Number of variables17
Number of observations21
Missing cells15
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory148.3 B

Variable types

Text6
Numeric6
Categorical4
DateTime1

Dataset

Description경기도 김포시 지식산업센터 현황 정보에 대한 데이터로 명칭, 소재지주소, 공사진행상황, 준공연도, 사용승인일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15037669/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 유치가능업체수 and 3 other fieldsHigh correlation
부지면적 is highly overall correlated with 공장시설면적 and 2 other fieldsHigh correlation
공장시설면적 is highly overall correlated with 부지면적 and 2 other fieldsHigh correlation
지원시설면적 is highly overall correlated with 부지면적 and 2 other fieldsHigh correlation
유치가능업체수 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
용도지역 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
분양형태 is highly overall correlated with 위도High correlation
공사진행상황 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
분양형태 is highly imbalanced (54.6%)Imbalance
소재지도로명주소 has 3 (14.3%) missing valuesMissing
준공연도 has 1 (4.8%) missing valuesMissing
사용승인일 has 3 (14.3%) missing valuesMissing
관리사무소 전화번호 has 8 (38.1%) missing valuesMissing
지식산업센터명칭 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
공장시설면적 has unique valuesUnique
지원시설면적 has unique valuesUnique
유치가능업체수 has 1 (4.8%) zerosZeros

Reproduction

Analysis started2023-12-12 10:45:03.115525
Analysis finished2023-12-12 10:45:09.088673
Duration5.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지식산업센터명칭
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T19:45:09.202275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length8
Mean length6.5714286
Min length2

Characters and Unicode

Total characters138
Distinct characters82
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row이젠
2nd row일호
3rd row좋은밸리
4th rowThe Big Barn
5th row대성지식산업센터
ValueCountFrequency (%)
디원시티 2
 
8.3%
이젠 1
 
4.2%
김포테라비즈 1
 
4.2%
리브타워 1
 
4.2%
김포한강듀클래스 1
 
4.2%
시그니처 1
 
4.2%
김포한강르네상스첨단비즈나인 1
 
4.2%
샹보르영무파라드김포한강 1
 
4.2%
금광하이테크시티 1
 
4.2%
금광테크노벨리 1
 
4.2%
Other values (13) 13
54.2%
2023-12-12T19:45:09.511734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 6
 
4.3%
한 4
 
2.9%
티 4
 
2.9%
포 4
 
2.9%
김 4
 
2.9%
강 4
 
2.9%
즈 4
 
2.9%
비 4
 
2.9%
디 3
 
2.2%
르 3
 
2.2%
Other values (72) 98
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
89.1%
Lowercase Letter 7
 
5.1%
Uppercase Letter 4
 
2.9%
Space Separator 3
 
2.2%
Other Symbol 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 6
 
4.9%
한 4
 
3.3%
티 4
 
3.3%
포 4
 
3.3%
김 4
 
3.3%
강 4
 
3.3%
즈 4
 
3.3%
비 4
 
3.3%
디 3
 
2.4%
르 3
 
2.4%
Other values (60) 83
67.5%
Lowercase Letter
ValueCountFrequency (%)
a 1
14.3%
n 1
14.3%
g 1
14.3%
i 1
14.3%
e 1
14.3%
h 1
14.3%
r 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
T 1
25.0%
G 1
25.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
89.9%
Latin 11
 
8.0%
Common 3
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 6
 
4.8%
한 4
 
3.2%
티 4
 
3.2%
포 4
 
3.2%
김 4
 
3.2%
강 4
 
3.2%
즈 4
 
3.2%
비 4
 
3.2%
디 3
 
2.4%
르 3
 
2.4%
Other values (61) 84
67.7%
Latin
ValueCountFrequency (%)
B 2
18.2%
a 1
9.1%
n 1
9.1%
g 1
9.1%
i 1
9.1%
e 1
9.1%
h 1
9.1%
T 1
9.1%
G 1
9.1%
r 1
9.1%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
89.1%
ASCII 14
 
10.1%
None 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 6
 
4.9%
한 4
 
3.3%
티 4
 
3.3%
포 4
 
3.3%
김 4
 
3.3%
강 4
 
3.3%
즈 4
 
3.3%
비 4
 
3.3%
디 3
 
2.4%
르 3
 
2.4%
Other values (60) 83
67.5%
ASCII
ValueCountFrequency (%)
3
21.4%
B 2
14.3%
a 1
 
7.1%
n 1
 
7.1%
g 1
 
7.1%
i 1
 
7.1%
e 1
 
7.1%
h 1
 
7.1%
T 1
 
7.1%
G 1
 
7.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T19:45:09.700888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length20.904762
Min length18

Characters and Unicode

Total characters439
Distinct characters35
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 김포시 양촌읍 학운리 2979번지
2nd row경기도 김포시 양촌읍 학운리 3050,3050-1
3rd row경기도 김포시 양촌읍 학운리 2980번지
4th row경기도 김포시 양촌읍 학운리 2980-1번지
5th row경기도 김포시 양촌읍 학운리 2980-2번지
ValueCountFrequency (%)
경기도 21
22.8%
김포시 21
22.8%
양촌읍 7
 
7.6%
학운리 7
 
7.6%
구래동 7
 
7.6%
장기동 6
 
6.5%
2980번지 1
 
1.1%
2008-4,-5 1
 
1.1%
6871-16 1
 
1.1%
6877-5 1
 
1.1%
Other values (19) 19
20.7%
2023-12-12T19:45:10.007073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
71
16.2%
기 27
 
6.2%
경 21
 
4.8%
도 21
 
4.8%
김 21
 
4.8%
포 21
 
4.8%
시 21
 
4.8%
- 21
 
4.8%
0 20
 
4.6%
8 19
 
4.3%
Other values (25) 176
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 227
51.7%
Decimal Number 115
26.2%
Space Separator 71
 
16.2%
Dash Punctuation 21
 
4.8%
Other Punctuation 4
 
0.9%
Math Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 27
11.9%
경 21
 
9.3%
도 21
 
9.3%
김 21
 
9.3%
포 21
 
9.3%
시 21
 
9.3%
동 13
 
5.7%
리 8
 
3.5%
읍 8
 
3.5%
촌 8
 
3.5%
Other values (11) 58
25.6%
Decimal Number
ValueCountFrequency (%)
0 20
17.4%
8 19
16.5%
2 18
15.7%
1 13
11.3%
7 12
10.4%
6 10
8.7%
9 8
 
7.0%
3 7
 
6.1%
5 5
 
4.3%
4 3
 
2.6%
Space Separator
ValueCountFrequency (%)
71
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 227
51.7%
Common 212
48.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 27
11.9%
경 21
 
9.3%
도 21
 
9.3%
김 21
 
9.3%
포 21
 
9.3%
시 21
 
9.3%
동 13
 
5.7%
리 8
 
3.5%
읍 8
 
3.5%
촌 8
 
3.5%
Other values (11) 58
25.6%
Common
ValueCountFrequency (%)
71
33.5%
- 21
 
9.9%
0 20
 
9.4%
8 19
 
9.0%
2 18
 
8.5%
1 13
 
6.1%
7 12
 
5.7%
6 10
 
4.7%
9 8
 
3.8%
3 7
 
3.3%
Other values (4) 13
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 227
51.7%
ASCII 212
48.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
71
33.5%
- 21
 
9.9%
0 20
 
9.4%
8 19
 
9.0%
2 18
 
8.5%
1 13
 
6.1%
7 12
 
5.7%
6 10
 
4.7%
9 8
 
3.8%
3 7
 
3.3%
Other values (4) 13
 
6.1%
Hangul
ValueCountFrequency (%)
기 27
11.9%
경 21
 
9.3%
도 21
 
9.3%
김 21
 
9.3%
포 21
 
9.3%
시 21
 
9.3%
동 13
 
5.7%
리 8
 
3.5%
읍 8
 
3.5%
촌 8
 
3.5%
Other values (11) 58
25.6%

소재지도로명주소
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
2023-12-12T19:45:10.207577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length18.277778
Min length15

Characters and Unicode

Total characters329
Distinct characters29
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

Unique18 ?
Unique (%)100.0%

Sample

1st row경기도 김포시 황금로 117
2nd row경기도 김포시 황금1로80번길 130
3rd row경기도 김포시 황금로127번길 69
4th row경기도 김포시 황금로109번길 74
5th row경기도 김포시 황금1로80번길 39
ValueCountFrequency (%)
경기도 18
25.0%
김포시 18
25.0%
태장로 5
 
6.9%
황금1로80번길 3
 
4.2%
김포한강10로133번길 3
 
4.2%
황금로109번길 2
 
2.8%
황금로 1
 
1.4%
김포한강5로 1
 
1.4%
751 1
 
1.4%
107 1
 
1.4%
Other values (19) 19
26.4%
2023-12-12T19:45:10.530130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
16.4%
김 22
 
6.7%
포 22
 
6.7%
1 22
 
6.7%
경 18
 
5.5%
도 18
 
5.5%
시 18
 
5.5%
로 18
 
5.5%
기 18
 
5.5%
7 11
 
3.3%
Other values (19) 108
32.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
58.1%
Decimal Number 84
25.5%
Space Separator 54
 
16.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 22
11.5%
포 22
11.5%
경 18
9.4%
도 18
9.4%
시 18
9.4%
로 18
9.4%
기 18
9.4%
번 10
 
5.2%
길 10
 
5.2%
금 7
 
3.7%
Other values (8) 30
15.7%
Decimal Number
ValueCountFrequency (%)
1 22
26.2%
7 11
13.1%
0 11
13.1%
3 10
11.9%
5 9
10.7%
9 6
 
7.1%
8 5
 
6.0%
2 4
 
4.8%
6 4
 
4.8%
4 2
 
2.4%
Space Separator
ValueCountFrequency (%)
54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
58.1%
Common 138
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 22
11.5%
포 22
11.5%
경 18
9.4%
도 18
9.4%
시 18
9.4%
로 18
9.4%
기 18
9.4%
번 10
 
5.2%
길 10
 
5.2%
금 7
 
3.7%
Other values (8) 30
15.7%
Common
ValueCountFrequency (%)
54
39.1%
1 22
15.9%
7 11
 
8.0%
0 11
 
8.0%
3 10
 
7.2%
5 9
 
6.5%
9 6
 
4.3%
8 5
 
3.6%
2 4
 
2.9%
6 4
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
58.1%
ASCII 138
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
39.1%
1 22
15.9%
7 11
 
8.0%
0 11
 
8.0%
3 10
 
7.2%
5 9
 
6.5%
9 6
 
4.3%
8 5
 
3.6%
2 4
 
2.9%
6 4
 
2.9%
Hangul
ValueCountFrequency (%)
김 22
11.5%
포 22
11.5%
경 18
9.4%
도 18
9.4%
시 18
9.4%
로 18
9.4%
기 18
9.4%
번 10
 
5.2%
길 10
 
5.2%
금 7
 
3.7%
Other values (8) 30
15.7%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.63137
Minimum37.593519
Maximum37.6529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:10.655416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.593519
5-th percentile37.615009
Q137.615458
median37.63974
Q337.6416
95-th percentile37.6505
Maximum37.6529
Range0.05938084
Interquartile range (IQR)0.02614228

Descriptive statistics

Standard deviation0.016079827
Coefficient of variation (CV)0.00042729847
Kurtosis-0.48053225
Mean37.63137
Median Absolute Deviation (MAD)0.00626824
Skewness-0.70667454
Sum790.25876
Variance0.00025856083
MonotonicityNot monotonic
2023-12-12T19:45:10.776842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
37.61651114 1
 
4.8%
37.61513362 1
 
4.8%
37.6402 1
 
4.8%
37.6416 1
 
4.8%
37.6529 1
 
4.8%
37.6432 1
 
4.8%
37.6505 1
 
4.8%
37.646008 1
 
4.8%
37.63807705 1
 
4.8%
37.64435056 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
37.59351916 1
4.8%
37.6150093 1
4.8%
37.61513362 1
4.8%
37.61514242 1
4.8%
37.61515671 1
4.8%
37.61545772 1
4.8%
37.61570211 1
4.8%
37.61651114 1
4.8%
37.63807705 1
4.8%
37.63844331 1
4.8%
ValueCountFrequency (%)
37.6529 1
4.8%
37.6505 1
4.8%
37.646008 1
4.8%
37.64435056 1
4.8%
37.6432 1
4.8%
37.6416 1
4.8%
37.6410507 1
4.8%
37.64075921 1
4.8%
37.64030235 1
4.8%
37.6402 1
4.8%

경도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60292.952
Minimum126.61792
Maximum1263619
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:10.897094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.61792
5-th percentile126.6186
Q1126.62137
median126.62603
Q3126.68188
95-th percentile126.79624
Maximum1263619
Range1263492.4
Interquartile range (IQR)0.0605094

Descriptive statistics

Standard deviation275716.64
Coefficient of variation (CV)4.5729497
Kurtosis21
Mean60292.952
Median Absolute Deviation (MAD)0.0081102
Skewness4.5825757
Sum1266152
Variance7.6019663 × 1010
MonotonicityNot monotonic
2023-12-12T19:45:11.025641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
126.6213082 1
 
4.8%
126.6260341 1
 
4.8%
126.6195 1
 
4.8%
1263619.0 1
 
4.8%
126.6384 1
 
4.8%
126.6186 1
 
4.8%
126.6368 1
 
4.8%
126.618826 1
 
4.8%
126.6800767 1
 
4.8%
126.6179239 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
126.6179239 1
4.8%
126.6186 1
4.8%
126.618826 1
4.8%
126.6195 1
4.8%
126.6213082 1
4.8%
126.6213729 1
4.8%
126.6215511 1
4.8%
126.6221489 1
4.8%
126.6222406 1
4.8%
126.6226017 1
4.8%
ValueCountFrequency (%)
1263619.0 1
4.8%
126.796237 1
4.8%
126.6835535 1
4.8%
126.6830651 1
4.8%
126.6824953 1
4.8%
126.6818823 1
4.8%
126.6800767 1
4.8%
126.6798088 1
4.8%
126.6384 1
4.8%
126.6368 1
4.8%

용도지역
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
준주거
13 
일반공업
8 

Length

Max length4
Median length3
Mean length3.3809524
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
준주거 13
61.9%
일반공업 8
38.1%

Length

2023-12-12T19:45:11.177307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:45:11.283857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준주거 13
61.9%
일반공업 8
38.1%

부지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10054.143
Minimum1674
Maximum51238
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:11.402146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1674
5-th percentile2414
Q14089
median7045
Q310251
95-th percentile32919
Maximum51238
Range49564
Interquartile range (IQR)6162

Descriptive statistics

Standard deviation11535.707
Coefficient of variation (CV)1.1473585
Kurtosis8.5781395
Mean10054.143
Median Absolute Deviation (MAD)3206
Skewness2.8496814
Sum211137
Variance1.3307253 × 108
MonotonicityNot monotonic
2023-12-12T19:45:11.523074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3759 2
 
9.5%
51238 1
 
4.8%
5205 1
 
4.8%
7459 1
 
4.8%
2495 1
 
4.8%
13825 1
 
4.8%
9488 1
 
4.8%
12286 1
 
4.8%
4935 1
 
4.8%
8111 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
1674 1
4.8%
2414 1
4.8%
2495 1
4.8%
3759 2
9.5%
4089 1
4.8%
4935 1
4.8%
5161 1
4.8%
5179 1
4.8%
5205 1
4.8%
7045 1
4.8%
ValueCountFrequency (%)
51238 1
4.8%
32919 1
4.8%
13825 1
4.8%
12286 1
4.8%
11561 1
4.8%
10251 1
4.8%
9488 1
4.8%
8284 1
4.8%
8111 1
4.8%
7459 1
4.8%

층수(지하_지상)
Text

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T19:45:11.669705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.3809524
Min length4

Characters and Unicode

Total characters92
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)38.1%

Sample

1st rowB1/9
2nd rowB1/10
3rd rowB1/6
4th rowB1/5
5th rowB1/4
ValueCountFrequency (%)
b3/7 6
28.6%
b3/10 4
19.0%
b1/4 3
14.3%
b1/9 1
 
4.8%
b1/10 1
 
4.8%
b1/6 1
 
4.8%
b1/5 1
 
4.8%
b2/6 1
 
4.8%
b4/10 1
 
4.8%
b3/15 1
 
4.8%
2023-12-12T19:45:11.991724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 21
22.8%
/ 21
22.8%
1 15
16.3%
3 11
12.0%
7 6
 
6.5%
0 6
 
6.5%
4 4
 
4.3%
5 3
 
3.3%
6 2
 
2.2%
2 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
54.3%
Uppercase Letter 21
22.8%
Other Punctuation 21
22.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
30.0%
3 11
22.0%
7 6
 
12.0%
0 6
 
12.0%
4 4
 
8.0%
5 3
 
6.0%
6 2
 
4.0%
2 2
 
4.0%
9 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
B 21
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
77.2%
Latin 21
 
22.8%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 21
29.6%
1 15
21.1%
3 11
15.5%
7 6
 
8.5%
0 6
 
8.5%
4 4
 
5.6%
5 3
 
4.2%
6 2
 
2.8%
2 2
 
2.8%
9 1
 
1.4%
Latin
ValueCountFrequency (%)
B 21
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
B 21
22.8%
/ 21
22.8%
1 15
16.3%
3 11
12.0%
7 6
 
6.5%
0 6
 
6.5%
4 4
 
4.3%
5 3
 
3.3%
6 2
 
2.2%
2 2
 
2.2%

공장시설면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26597.81
Minimum2482
Maximum115258
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:12.147497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2482
5-th percentile2579
Q110548
median16722
Q328977
95-th percentile100522
Maximum115258
Range112776
Interquartile range (IQR)18429

Descriptive statistics

Standard deviation29296.914
Coefficient of variation (CV)1.1014784
Kurtosis5.0290463
Mean26597.81
Median Absolute Deviation (MAD)8275
Skewness2.3105116
Sum558554
Variance8.5830917 × 108
MonotonicityNot monotonic
2023-12-12T19:45:12.270526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
115258 1
 
4.8%
34727 1
 
4.8%
21666 1
 
4.8%
10548 1
 
4.8%
100522 1
 
4.8%
29992 1
 
4.8%
48699 1
 
4.8%
15536 1
 
4.8%
21076 1
 
4.8%
23362 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
2482 1
4.8%
2579 1
4.8%
6457 1
4.8%
8182 1
4.8%
8447 1
4.8%
10548 1
4.8%
12551 1
4.8%
15191 1
4.8%
15449 1
4.8%
15536 1
4.8%
ValueCountFrequency (%)
115258 1
4.8%
100522 1
4.8%
48699 1
4.8%
34727 1
4.8%
29992 1
4.8%
28977 1
4.8%
23362 1
4.8%
21666 1
4.8%
21076 1
4.8%
20131 1
4.8%

지원시설면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4805.619
Minimum563
Maximum24130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:12.393860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum563
5-th percentile600
Q11350
median2173
Q35448
95-th percentile11941
Maximum24130
Range23567
Interquartile range (IQR)4098

Descriptive statistics

Standard deviation5658.3128
Coefficient of variation (CV)1.1774368
Kurtosis6.1515249
Mean4805.619
Median Absolute Deviation (MAD)1572
Skewness2.2938466
Sum100918
Variance32016503
MonotonicityNot monotonic
2023-12-12T19:45:12.540808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
24130 1
 
4.8%
11941 1
 
4.8%
3728 1
 
4.8%
1886 1
 
4.8%
11518 1
 
4.8%
5448 1
 
4.8%
2087 1
 
4.8%
3562 1
 
4.8%
3944 1
 
4.8%
9777 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
563 1
4.8%
600 1
4.8%
601 1
4.8%
730 1
4.8%
1225 1
4.8%
1350 1
4.8%
1673 1
4.8%
1886 1
4.8%
1900 1
4.8%
2087 1
4.8%
ValueCountFrequency (%)
24130 1
4.8%
11941 1
4.8%
11518 1
4.8%
9777 1
4.8%
7356 1
4.8%
5448 1
4.8%
4726 1
4.8%
3944 1
4.8%
3728 1
4.8%
3562 1
4.8%

유치가능업체수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334.33333
Minimum0
Maximum1280
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T19:45:12.670141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q112
median298
Q3420
95-th percentile810
Maximum1280
Range1280
Interquartile range (IQR)408

Descriptive statistics

Standard deviation338.3209
Coefficient of variation (CV)1.0119269
Kurtosis1.5575165
Mean334.33333
Median Absolute Deviation (MAD)286
Skewness1.2238769
Sum7021
Variance114461.03
MonotonicityNot monotonic
2023-12-12T19:45:12.820092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
12 3
 
14.3%
420 2
 
9.5%
606 1
 
4.8%
298 1
 
4.8%
1280 1
 
4.8%
810 1
 
4.8%
798 1
 
4.8%
610 1
 
4.8%
350 1
 
4.8%
397 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
0 1
 
4.8%
5 1
 
4.8%
10 1
 
4.8%
12 3
14.3%
100 1
 
4.8%
117 1
 
4.8%
150 1
 
4.8%
240 1
 
4.8%
298 1
 
4.8%
350 1
 
4.8%
ValueCountFrequency (%)
1280 1
4.8%
810 1
4.8%
798 1
4.8%
610 1
4.8%
606 1
4.8%
420 2
9.5%
397 1
4.8%
374 1
4.8%
350 1
4.8%
298 1
4.8%

분양형태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
분양
19 
임대
2 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row분양
2nd row분양
3rd row임대
4th row분양
5th row분양

Common Values

ValueCountFrequency (%)
분양 19
90.5%
임대 2
 
9.5%

Length

2023-12-12T19:45:12.967905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:45:13.085493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 19
90.5%
임대 2
 
9.5%

공사진행상황
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
준공
17 
건설중
4 

Length

Max length3
Median length2
Mean length2.1904762
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
준공 17
81.0%
건설중 4
 
19.0%

Length

2023-12-12T19:45:13.223510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:45:13.352930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
준공 17
81.0%
건설중 4
 
19.0%

준공연도
Text

MISSING 

Distinct11
Distinct (%)55.0%
Missing1
Missing (%)4.8%
Memory size300.0 B
2023-12-12T19:45:13.503875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.6
Min length4

Characters and Unicode

Total characters92
Distinct characters12
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

Unique5 ?
Unique (%)25.0%

Sample

1st row2009
2nd row2013
3rd row2014
4th row2014
5th row2018
ValueCountFrequency (%)
2019 4
20.0%
2018 3
15.0%
2014 2
10.0%
2020 2
10.0%
2022 2
10.0%
2023(예정 2
10.0%
2009 1
 
5.0%
2013 1
 
5.0%
2016 1
 
5.0%
2021 1
 
5.0%
2023-12-12T19:45:13.827598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30
32.6%
0 23
25.0%
1 12
 
13.0%
9 5
 
5.4%
8 3
 
3.3%
4 3
 
3.3%
3 3
 
3.3%
( 3
 
3.3%
예 3
 
3.3%
정 3
 
3.3%
Other values (2) 4
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
87.0%
Other Letter 6
 
6.5%
Open Punctuation 3
 
3.3%
Close Punctuation 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
37.5%
0 23
28.7%
1 12
 
15.0%
9 5
 
6.2%
8 3
 
3.8%
4 3
 
3.8%
3 3
 
3.8%
6 1
 
1.2%
Other Letter
ValueCountFrequency (%)
예 3
50.0%
정 3
50.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 86
93.5%
Hangul 6
 
6.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30
34.9%
0 23
26.7%
1 12
 
14.0%
9 5
 
5.8%
8 3
 
3.5%
4 3
 
3.5%
3 3
 
3.5%
( 3
 
3.5%
) 3
 
3.5%
6 1
 
1.2%
Hangul
ValueCountFrequency (%)
예 3
50.0%
정 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
93.5%
Hangul 6
 
6.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30
34.9%
0 23
26.7%
1 12
 
14.0%
9 5
 
5.8%
8 3
 
3.5%
4 3
 
3.5%
3 3
 
3.5%
( 3
 
3.5%
) 3
 
3.5%
6 1
 
1.2%
Hangul
ValueCountFrequency (%)
예 3
50.0%
정 3
50.0%

사용승인일
Date

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
Minimum2009-03-10 00:00:00
Maximum2022-12-14 00:00:00
2023-12-12T19:45:13.967019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:14.096334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)

관리사무소 전화번호
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing8
Missing (%)38.1%
Memory size300.0 B
2023-12-12T19:45:14.288772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.384615
Min length12

Characters and Unicode

Total characters161
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

Unique13 ?
Unique (%)100.0%

Sample

1st row031-999-7114
2nd row031-985-8601
3rd row031-8049-3920
4th row031-996-3181
5th row031-998-0005
ValueCountFrequency (%)
031-999-7114 1
 
7.7%
031-985-8601 1
 
7.7%
031-8049-3920 1
 
7.7%
031-996-3181 1
 
7.7%
031-998-0005 1
 
7.7%
031-989-4135 1
 
7.7%
031-987-0630 1
 
7.7%
031-5175-7777 1
 
7.7%
031-986-9974 1
 
7.7%
031-996-1446 1
 
7.7%
Other values (3) 3
23.1%
2023-12-12T19:45:14.760862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26
16.1%
- 26
16.1%
1 24
14.9%
9 21
13.0%
3 16
9.9%
7 12
7.5%
8 10
 
6.2%
4 8
 
5.0%
5 8
 
5.0%
6 8
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 135
83.9%
Dash Punctuation 26
 
16.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26
19.3%
1 24
17.8%
9 21
15.6%
3 16
11.9%
7 12
8.9%
8 10
 
7.4%
4 8
 
5.9%
5 8
 
5.9%
6 8
 
5.9%
2 2
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26
16.1%
- 26
16.1%
1 24
14.9%
9 21
13.0%
3 16
9.9%
7 12
7.5%
8 10
 
6.2%
4 8
 
5.0%
5 8
 
5.0%
6 8
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26
16.1%
- 26
16.1%
1 24
14.9%
9 21
13.0%
3 16
9.9%
7 12
7.5%
8 10
 
6.2%
4 8
 
5.0%
5 8
 
5.0%
6 8
 
5.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-07-20
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-20
2nd row2023-07-20
3rd row2023-07-20
4th row2023-07-20
5th row2023-07-20

Common Values

ValueCountFrequency (%)
2023-07-20 21
100.0%

Length

2023-12-12T19:45:14.956745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:45:15.101215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-20 21
100.0%

Interactions

2023-12-12T19:45:07.606556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:03.897266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.666722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.454139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.173134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.891020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.731578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.021247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.808460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.576598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.276899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.023815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.831406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.155506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.942599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.716597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.413505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.166647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.963653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.303286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.073065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.836420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.529437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.279941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:08.412016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.430661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.203078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.964524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.627957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.390247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:08.489197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:04.548581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:05.326423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.067297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:06.749876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:45:07.487075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:45:15.230862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지식산업센터명칭소재지지번주소소재지도로명주소위도경도용도지역부지면적층수(지하_지상)공장시설면적지원시설면적유치가능업체수분양형태공사진행상황준공연도사용승인일관리사무소 전화번호
지식산업센터명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.0001.0000.8360.9370.6370.2790.4170.5320.5060.7121.0001.000
경도1.0001.000NaN0.0001.0000.0000.0000.0000.0000.0000.4800.0000.0000.000NaNNaN
용도지역1.0001.0001.0001.0000.0001.0000.3221.0000.5480.4820.7220.1840.2131.0001.0001.000
부지면적1.0001.0001.0000.8360.0000.3221.0000.9270.8540.7190.0000.0000.4640.9601.0001.000
층수(지하_지상)1.0001.0001.0000.9370.0001.0000.9271.0000.9030.8390.0001.0000.6590.9011.0001.000
공장시설면적1.0001.0001.0000.6370.0000.5480.8540.9031.0000.9050.5620.0000.7260.7631.0001.000
지원시설면적1.0001.0001.0000.2790.0000.4820.7190.8390.9051.0000.6460.0000.0000.7861.0001.000
유치가능업체수1.0001.0001.0000.4170.4800.7220.0000.0000.5620.6461.0000.0000.7780.7991.0001.000
분양형태1.0001.0001.0000.5320.0000.1840.0001.0000.0000.0000.0001.0000.0000.0001.0001.000
공사진행상황1.0001.0001.0000.5060.0000.2130.4640.6590.7260.0000.7780.0001.0000.8311.000NaN
준공연도1.0001.0001.0000.7120.0001.0000.9600.9010.7630.7860.7990.0000.8311.0001.0001.000
사용승인일1.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
관리사무소 전화번호1.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.000
2023-12-12T19:45:15.466869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도지역공사진행상황분양형태
용도지역1.0000.1270.107
공사진행상황0.1271.0000.000
분양형태0.1070.0001.000
2023-12-12T19:45:15.570987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도부지면적공장시설면적지원시설면적유치가능업체수용도지역분양형태공사진행상황
위도1.000-0.0490.2600.4650.4880.6710.9180.5860.558
경도-0.0491.0000.014-0.100-0.148-0.1430.0000.0000.000
부지면적0.2600.0141.0000.9540.7580.3900.3590.0000.520
공장시설면적0.465-0.1000.9541.0000.8340.5960.3980.0000.476
지원시설면적0.488-0.1480.7580.8341.0000.6390.3220.0000.000
유치가능업체수0.671-0.1430.3900.5960.6391.0000.6670.0000.721
용도지역0.9180.0000.3590.3980.3220.6671.0000.1070.127
분양형태0.5860.0000.0000.0000.0000.0000.1071.0000.000
공사진행상황0.5580.0000.5200.4760.0000.7210.1270.0001.000

Missing values

2023-12-12T19:45:08.617664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:45:08.874613image/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.
2023-12-12T19:45:09.019046image/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

지식산업센터명칭소재지지번주소소재지도로명주소위도경도용도지역부지면적층수(지하_지상)공장시설면적지원시설면적유치가능업체수분양형태공사진행상황준공연도사용승인일관리사무소 전화번호데이터기준일자
0이젠경기도 김포시 양촌읍 학운리 2979번지경기도 김포시 황금로 11737.616511126.621308일반공업51238B1/911525824130606분양준공20092009-03-10031-999-71142023-07-20
1일호경기도 김포시 양촌읍 학운리 3050,3050-1경기도 김포시 황금1로80번길 13037.615134126.626034일반공업32919B1/103472711941117분양준공20132013-05-13<NA>2023-07-20
2좋은밸리경기도 김포시 양촌읍 학운리 2980번지경기도 김포시 황금로127번길 6937.615458126.621373일반공업3759B1/664575635임대준공20142014-05-19031-985-86012023-07-20
3The Big Barn경기도 김포시 양촌읍 학운리 2980-1번지경기도 김포시 황금로109번길 7437.615702126.622241일반공업3759B1/5844713500분양준공20142014-05-02031-8049-39202023-07-20
4대성지식산업센터경기도 김포시 양촌읍 학운리 2980-2번지경기도 김포시 황금1로80번길 3937.615009126.621551일반공업4089B1/48182122512분양준공20182018-01-24031-996-31812023-07-20
5㈜디아이엠경기도 김포시 양촌읍 학운리 2980-4번지경기도 김포시 황금로109번길 8037.615157126.622602일반공업2414B1/4257960012분양준공20182016-06-24031-998-00052023-07-20
6뉴아트경기도 김포시 양촌읍 학운리 2980-3번지경기도 김포시 황금1로80번길 5537.615142126.622149일반공업1674B1/4248273012분양준공20162016-03-25031-989-41352023-07-20
7라보진경기도 김포시 고촌읍 전호리 722번지경기도 김포시 아라육로 1637.593519126.796237일반공업10251B2/61672260110임대준공20182015-10-19<NA>2023-07-20
8마스터비즈파크경기도 김포시 장기동 2083-6경기도 김포시 태장로795번길 2337.638443126.679809준주거7045B3/7201312173374분양준공20192019-07-19031-987-06302023-07-20
9한강신도시G타워경기도 김포시 장기동 2008-2경기도 김포시 태장로 75537.640302126.682495준주거5161B3/7151911900100분양준공20192019-10-23031-5175-77772023-07-20
지식산업센터명칭소재지지번주소소재지도로명주소위도경도용도지역부지면적층수(지하_지상)공장시설면적지원시설면적유치가능업체수분양형태공사진행상황준공연도사용승인일관리사무소 전화번호데이터기준일자
11경동미르웰시티경기도 김포시 장기동 2008-4,-5경기도 김포시 태장로 74137.641051126.683554준주거11561B3/7289777356150분양준공20202020-06-15031-996-14462023-07-20
12금광테크노벨리경기도 김포시 장기동 2008-1경기도 김포시 태장로 76537.63974126.681882준주거5205B3/7154491673298분양준공20192019-11-30031-986-76502023-07-20
13디원시티경기도 김포시 구래동 6871-7,-8,-9경기도 김포시 김포한강10로133번길 12737.644351126.617924준주거8284B4/10233629777397분양준공20202020-12-110507-1410-24002023-07-20
14금광하이테크시티경기도 김포시 장기동 2083-4경기도 김포시 태장로 78937.638077126.680077준주거8111B3/7210763944420분양준공20212021-11-30031-5177-89912023-07-20
15샹보르영무파라드김포한강경기도 김포시 구래동 6871-61경기도 김포시 김포한강10로133번길 16537.646008126.618826준주거4935B3/10155363562420분양준공20222022-03-08<NA>2023-07-20
16김포한강르네상스첨단비즈나인경기도 김포시 구래동 6877-10<NA>37.6505126.6368준주거12286B3/15486992087350분양건설중2023(예정)<NA><NA>2023-07-20
17디원시티 시그니처경기도 김포시 구래동 6871-12~15경기도 김포시 김포한강10로133번길 10737.6432126.6186준주거9488B3/10299925448610분양준공<NA>2022-04-08<NA>2023-07-20
18김포한강듀클래스경기도 김포시 구래동 6877-5경기도 김포시 김포한강5로 32137.6529126.6384준주거13825B2/1510052211518798분양건설중20222022-12-14<NA>2023-07-20
19리브타워경기도 김포시 구래동 6871-16<NA>37.64161263619.0준주거2495B3/10105481886810분양건설중2023(예정)<NA><NA>2023-07-20
20센트레비즈경기도 김포시 구래동 6871-23<NA>37.6402126.6195준주거7459B3/102166637281280분양건설중2024(예정)<NA><NA>2023-07-20