Overview

Dataset statistics

Number of variables20
Number of observations27
Missing cells6
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory172.9 B

Variable types

Categorical11
Numeric6
Text3

Dataset

Description해당 데이터는 인천광역시 남동구의 건축위원회심의결과에 관련된 자료로서, 인천광역시 남동구 건축위원회심의결과의 연도, 회차, 안건, 심의목적, 운영기관, 심의일자, 건축종별, 건축주, 대지위치, 지번, 대지면적(제곱미터), 용도지역, 건축면적, 건폐율(퍼센트), 주용도, 구조, 최고높이(미터), 용적률(퍼센트), 심의결과의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15105801&srcSe=7661IVAWM27C61E190

Alerts

운영기관 has constant value ""Constant
데이터기준일 has constant value ""Constant
회차 is highly overall correlated with 심의일자High correlation
대지면적(제곱미터) is highly overall correlated with 건축면적 and 4 other fieldsHigh correlation
건축면적 is highly overall correlated with 대지면적(제곱미터) and 3 other fieldsHigh correlation
건폐율(퍼센트) is highly overall correlated with 건축면적 and 2 other fieldsHigh correlation
최고높이(미터) is highly overall correlated with 용적률(퍼센트) and 2 other fieldsHigh correlation
용적률(퍼센트) is highly overall correlated with 최고높이(미터)High correlation
연도 is highly overall correlated with 건폐율(퍼센트) and 3 other fieldsHigh correlation
심의목적 is highly overall correlated with 대지면적(제곱미터) and 5 other fieldsHigh correlation
심의일자 is highly overall correlated with 회차 and 1 other fieldsHigh correlation
건축종별 is highly overall correlated with 대지면적(제곱미터) and 3 other fieldsHigh correlation
대지위치 is highly overall correlated with 대지면적(제곱미터) and 2 other fieldsHigh correlation
주용도 is highly overall correlated with 대지면적(제곱미터) and 6 other fieldsHigh correlation
구조 is highly overall correlated with 심의목적 and 2 other fieldsHigh correlation
연도 is highly imbalanced (61.9%)Imbalance
건축종별 is highly imbalanced (61.8%)Imbalance
용도지역 has 2 (7.4%) missing valuesMissing
건폐율(퍼센트) has 1 (3.7%) missing valuesMissing
최고높이(미터) has 2 (7.4%) missing valuesMissing
용적률(퍼센트) has 1 (3.7%) missing valuesMissing

Reproduction

Analysis started2024-01-28 11:30:59.628659
Analysis finished2024-01-28 11:31:03.459875
Duration3.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
2022
25 
2023
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 25
92.6%
2023 2
 
7.4%

Length

2024-01-28T20:31:03.508430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:03.575873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 25
92.6%
2023 2
 
7.4%

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1111111
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:03.636702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35.5
95-th percentile8.7
Maximum9
Range8
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.5919006
Coefficient of variation (CV)0.63046231
Kurtosis-0.89885671
Mean4.1111111
Median Absolute Deviation (MAD)2
Skewness0.51228286
Sum111
Variance6.7179487
MonotonicityNot monotonic
2024-01-28T20:31:03.721895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 5
18.5%
5 5
18.5%
3 5
18.5%
2 4
14.8%
9 2
 
7.4%
8 2
 
7.4%
7 2
 
7.4%
6 1
 
3.7%
4 1
 
3.7%
ValueCountFrequency (%)
1 5
18.5%
2 4
14.8%
3 5
18.5%
4 1
 
3.7%
5 5
18.5%
6 1
 
3.7%
7 2
 
7.4%
8 2
 
7.4%
9 2
 
7.4%
ValueCountFrequency (%)
9 2
 
7.4%
8 2
 
7.4%
7 2
 
7.4%
6 1
 
3.7%
5 5
18.5%
4 1
 
3.7%
3 5
18.5%
2 4
14.8%
1 5
18.5%

안건
Categorical

Distinct5
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Memory size348.0 B
1
10 
2
8 
3
4 
4
3 
5
2 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 10
37.0%
2 8
29.6%
3 4
 
14.8%
4 3
 
11.1%
5 2
 
7.4%

Length

2024-01-28T20:31:03.829645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:03.926730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10
37.0%
2 8
29.6%
3 4
 
14.8%
4 3
 
11.1%
5 2
 
7.4%

심의목적
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
분양을 목적으로 하는 건축물
17 
다중이용 건축물
2 
화재안전성능보강 계획 승인
2 
분양대상 건축물
 
1
적용의 완화신청
 
1
Other values (4)
4 

Length

Max length18
Median length15
Mean length13.296296
Min length4

Unique

Unique6 ?
Unique (%)22.2%

Sample

1st row분양대상 건축물
2nd row적용의 완화신청
3rd row다중이용 건축물
4th row논현2지구 상업용지 건축물
5th row다중이용 건축물

Common Values

ValueCountFrequency (%)
분양을 목적으로 하는 건축물 17
63.0%
다중이용 건축물 2
 
7.4%
화재안전성능보강 계획 승인 2
 
7.4%
분양대상 건축물 1
 
3.7%
적용의 완화신청 1
 
3.7%
논현2지구 상업용지 건축물 1
 
3.7%
리모델링이 쉬운 구조에 대한 평가 1
 
3.7%
공공청사 건축물 1
 
3.7%
도로지정 1
 
3.7%

Length

2024-01-28T20:31:04.034998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:04.131310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물 22
23.7%
분양을 17
18.3%
하는 17
18.3%
목적으로 17
18.3%
다중이용 2
 
2.2%
화재안전성능보강 2
 
2.2%
계획 2
 
2.2%
승인 2
 
2.2%
쉬운 1
 
1.1%
공공청사 1
 
1.1%
Other values (10) 10
10.8%

운영기관
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
남동구 건축과
27 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남동구 건축과
2nd row남동구 건축과
3rd row남동구 건축과
4th row남동구 건축과
5th row남동구 건축과

Common Values

ValueCountFrequency (%)
남동구 건축과 27
100.0%

Length

2024-01-28T20:31:04.229751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:04.295246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 27
50.0%
건축과 27
50.0%

심의일자
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2022-07-21
5 
2022-05-30
5 
2022-04-20
4 
2022-02-28
3 
2023-01-30
2 
Other values (5)
8 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row2023-01-30
2nd row2023-01-30
3rd row2022-12-20
4th row2022-12-20
5th row2022-11-23

Common Values

ValueCountFrequency (%)
2022-07-21 5
18.5%
2022-05-30 5
18.5%
2022-04-20 4
14.8%
2022-02-28 3
11.1%
2023-01-30 2
 
7.4%
2022-12-20 2
 
7.4%
2022-11-23 2
 
7.4%
2022-10-06 2
 
7.4%
2022-09-05 1
 
3.7%
2022-06-22 1
 
3.7%

Length

2024-01-28T20:31:04.372082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:04.461089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-07-21 5
18.5%
2022-05-30 5
18.5%
2022-04-20 4
14.8%
2022-02-28 3
11.1%
2023-01-30 2
 
7.4%
2022-12-20 2
 
7.4%
2022-11-23 2
 
7.4%
2022-10-06 2
 
7.4%
2022-09-05 1
 
3.7%
2022-06-22 1
 
3.7%

건축종별
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
신축
24 
기타
 
2
증축
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
신축 24
88.9%
기타 2
 
7.4%
증축 1
 
3.7%

Length

2024-01-28T20:31:04.561970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:04.631894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 24
88.9%
기타 2
 
7.4%
증축 1
 
3.7%

건축주
Text

Distinct21
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-01-28T20:31:04.755120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11
Mean length6.962963
Min length2

Characters and Unicode

Total characters188
Distinct characters83
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

Unique15 ?
Unique (%)55.6%

Sample

1st row만수동5의19번지 소규모재건축정비사업조합
2nd row코리아신탁㈜
3rd row㈜이마트
4th row인천논현역개발 주식회사
5th row㈜이마트
ValueCountFrequency (%)
외 5
 
12.5%
만수동5의19번지 2
 
5.0%
김동식 2
 
5.0%
소규모재건축정비사업조합 2
 
5.0%
1 2
 
5.0%
2인 2
 
5.0%
김창동 2
 
5.0%
이동재 2
 
5.0%
이질용 2
 
5.0%
㈜이마트 2
 
5.0%
Other values (17) 17
42.5%
2024-01-28T20:31:05.001922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
6.9%
이 10
 
5.3%
동 9
 
4.8%
외 5
 
2.7%
㈜ 5
 
2.7%
정 5
 
2.7%
재 4
 
2.1%
식 4
 
2.1%
인 4
 
2.1%
주 4
 
2.1%
Other values (73) 125
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
82.4%
Space Separator 13
 
6.9%
Decimal Number 11
 
5.9%
Other Symbol 5
 
2.7%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
 
6.5%
동 9
 
5.8%
외 5
 
3.2%
정 5
 
3.2%
재 4
 
2.6%
식 4
 
2.6%
인 4
 
2.6%
주 4
 
2.6%
사 4
 
2.6%
현 4
 
2.6%
Other values (64) 102
65.8%
Decimal Number
ValueCountFrequency (%)
1 4
36.4%
2 2
18.2%
5 2
18.2%
9 2
18.2%
4 1
 
9.1%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
85.1%
Common 28
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
 
6.2%
동 9
 
5.6%
외 5
 
3.1%
㈜ 5
 
3.1%
정 5
 
3.1%
재 4
 
2.5%
식 4
 
2.5%
인 4
 
2.5%
주 4
 
2.5%
사 4
 
2.5%
Other values (65) 106
66.2%
Common
ValueCountFrequency (%)
13
46.4%
1 4
 
14.3%
) 2
 
7.1%
( 2
 
7.1%
2 2
 
7.1%
5 2
 
7.1%
9 2
 
7.1%
4 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
82.4%
ASCII 28
 
14.9%
None 5
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
46.4%
1 4
 
14.3%
) 2
 
7.1%
( 2
 
7.1%
2 2
 
7.1%
5 2
 
7.1%
9 2
 
7.1%
4 1
 
3.6%
Hangul
ValueCountFrequency (%)
이 10
 
6.5%
동 9
 
5.8%
외 5
 
3.2%
정 5
 
3.2%
재 4
 
2.6%
식 4
 
2.6%
인 4
 
2.6%
주 4
 
2.6%
사 4
 
2.6%
현 4
 
2.6%
Other values (64) 102
65.8%
None
ValueCountFrequency (%)
㈜ 5
100.0%

대지위치
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
인천광역시 남동구 만수동
6 
인천광역시 남동구 간석동
4 
인천광역시 남동구 구월동
4 
인천광역시 남동구 구월동
3 
인천광역시 남동구 논현동
2 
Other values (5)
8 

Length

Max length14
Median length13
Mean length13.296296
Min length13

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row인천광역시 남동구 만수동
2nd row인천광역시 남동구 간석동
3rd row인천광역시 남동구 구월동
4th row인천광역시 남동구 논현동
5th row인천광역시 남동구 구월동

Common Values

ValueCountFrequency (%)
인천광역시 남동구 만수동 6
22.2%
인천광역시 남동구 간석동 4
14.8%
인천광역시 남동구 구월동 4
14.8%
인천광역시 남동구 구월동 3
11.1%
인천광역시 남동구 논현동 2
 
7.4%
인천광역시 남동구 남촌동 2
 
7.4%
인천광역시 남동구 간석동 2
 
7.4%
인천광역시 남동구 고잔동 2
 
7.4%
인천광역시 남동구 남촌동 1
 
3.7%
인천광역시 남동구 운연동 1
 
3.7%

Length

2024-01-28T20:31:05.106175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:05.196514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 27
33.3%
남동구 27
33.3%
구월동 7
 
8.6%
만수동 6
 
7.4%
간석동 6
 
7.4%
남촌동 3
 
3.7%
논현동 2
 
2.5%
고잔동 2
 
2.5%
운연동 1
 
1.2%

지번
Text

Distinct21
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-01-28T20:31:05.342456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.4814815
Min length6

Characters and Unicode

Total characters229
Distinct characters16
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

Unique15 ?
Unique (%)55.6%

Sample

1st row5-19번지
2nd row189-2번지
3rd row1549번지
4th row731-4번지
5th row1549번지
ValueCountFrequency (%)
외 7
17.1%
618-8번지 3
 
7.3%
5-19번지 2
 
4.9%
884-8번지 2
 
4.9%
1549번지 2
 
4.9%
1134 2
 
4.9%
2필지 2
 
4.9%
4필지 2
 
4.9%
124-6 2
 
4.9%
920-27번지 1
 
2.4%
Other values (16) 16
39.0%
2024-01-28T20:31:05.590183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 27
11.8%
26
11.4%
1 24
10.5%
- 23
10.0%
번 18
7.9%
4 16
 
7.0%
8 16
 
7.0%
2 14
 
6.1%
3 13
 
5.7%
5 10
 
4.4%
Other values (6) 42
18.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 121
52.8%
Other Letter 59
25.8%
Space Separator 26
 
11.4%
Dash Punctuation 23
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
19.8%
4 16
13.2%
8 16
13.2%
2 14
11.6%
3 13
10.7%
5 10
8.3%
6 10
8.3%
9 6
 
5.0%
0 6
 
5.0%
7 6
 
5.0%
Other Letter
ValueCountFrequency (%)
지 27
45.8%
번 18
30.5%
외 7
 
11.9%
필 7
 
11.9%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 170
74.2%
Hangul 59
 
25.8%

Most frequent character per script

Common
ValueCountFrequency (%)
26
15.3%
1 24
14.1%
- 23
13.5%
4 16
9.4%
8 16
9.4%
2 14
8.2%
3 13
7.6%
5 10
 
5.9%
6 10
 
5.9%
9 6
 
3.5%
Other values (2) 12
7.1%
Hangul
ValueCountFrequency (%)
지 27
45.8%
번 18
30.5%
외 7
 
11.9%
필 7
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 170
74.2%
Hangul 59
 
25.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 27
45.8%
번 18
30.5%
외 7
 
11.9%
필 7
 
11.9%
ASCII
ValueCountFrequency (%)
26
15.3%
1 24
14.1%
- 23
13.5%
4 16
9.4%
8 16
9.4%
2 14
8.2%
3 13
7.6%
5 10
 
5.9%
6 10
 
5.9%
9 6
 
3.5%
Other values (2) 12
7.1%

대지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)74.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5182.7267
Minimum113.1
Maximum32007.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:05.682185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113.1
5-th percentile407.18
Q1986.05
median1963.8
Q33438.9
95-th percentile29651.274
Maximum32007.78
Range31894.68
Interquartile range (IQR)2452.85

Descriptive statistics

Standard deviation8924.2267
Coefficient of variation (CV)1.7219173
Kurtosis5.5555369
Mean5182.7267
Median Absolute Deviation (MAD)1352
Skewness2.5932366
Sum139933.62
Variance79641822
MonotonicityNot monotonic
2024-01-28T20:31:05.771973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
3438.9 3
 
11.1%
3315.8 3
 
11.1%
32007.78 2
 
7.4%
913.3 2
 
7.4%
897.6 2
 
7.4%
1945.5 1
 
3.7%
197.0 1
 
3.7%
3607.9 1
 
3.7%
1980.6 1
 
3.7%
1159.9 1
 
3.7%
Other values (10) 10
37.0%
ValueCountFrequency (%)
113.1 1
3.7%
197.0 1
3.7%
897.6 2
7.4%
913.3 2
7.4%
973.8 1
3.7%
998.3 1
3.7%
1159.9 1
3.7%
1174.9 1
3.7%
1736.2 1
3.7%
1945.5 1
3.7%
ValueCountFrequency (%)
32007.78 2
7.4%
24152.76 1
 
3.7%
6607.4 1
 
3.7%
3607.9 1
 
3.7%
3473.0 1
 
3.7%
3438.9 3
11.1%
3315.8 3
11.1%
1980.6 1
 
3.7%
1963.8 1
 
3.7%
1948.0 1
 
3.7%

용도지역
Text

MISSING 

Distinct15
Distinct (%)60.0%
Missing2
Missing (%)7.4%
Memory size348.0 B
2024-01-28T20:31:05.891600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length11.96
Min length5

Characters and Unicode

Total characters299
Distinct characters36
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

Unique10 ?
Unique (%)40.0%

Sample

1st row준주거지역
2nd row제2종일반주거지역
3rd row일반상업지역, 제1종지구단위계획
4th row일반상업지역, 지구단위계획(논현2)
5th row일반상업지역, 제1종지구단위계획
ValueCountFrequency (%)
일반상업지역 14
35.0%
준주거지역 7
17.5%
제1종지구단위계획 4
 
10.0%
국가산업단지 3
 
7.5%
철도보호지구 2
 
5.0%
일반공업지역 2
 
5.0%
제2종일반주거지역 1
 
2.5%
지구단위계획(논현2 1
 
2.5%
지구단위계획(소래논현 1
 
2.5%
제1종지구단위계획구역 1
 
2.5%
Other values (4) 4
 
10.0%
2024-01-28T20:31:06.336509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 40
 
13.4%
역 27
 
9.0%
업 20
 
6.7%
일 18
 
6.0%
반 18
 
6.0%
17
 
5.7%
, 15
 
5.0%
상 14
 
4.7%
구 14
 
4.7%
단 12
 
4.0%
Other values (26) 104
34.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
85.3%
Space Separator 17
 
5.7%
Other Punctuation 15
 
5.0%
Decimal Number 8
 
2.7%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 40
15.7%
역 27
 
10.6%
업 20
 
7.8%
일 18
 
7.1%
반 18
 
7.1%
상 14
 
5.5%
구 14
 
5.5%
단 12
 
4.7%
거 9
 
3.5%
주 9
 
3.5%
Other values (20) 74
29.0%
Decimal Number
ValueCountFrequency (%)
1 6
75.0%
2 2
 
25.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
85.3%
Common 44
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 40
15.7%
역 27
 
10.6%
업 20
 
7.8%
일 18
 
7.1%
반 18
 
7.1%
상 14
 
5.5%
구 14
 
5.5%
단 12
 
4.7%
거 9
 
3.5%
주 9
 
3.5%
Other values (20) 74
29.0%
Common
ValueCountFrequency (%)
17
38.6%
, 15
34.1%
1 6
 
13.6%
( 2
 
4.5%
) 2
 
4.5%
2 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
85.3%
ASCII 44
 
14.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 40
15.7%
역 27
 
10.6%
업 20
 
7.8%
일 18
 
7.1%
반 18
 
7.1%
상 14
 
5.5%
구 14
 
5.5%
단 12
 
4.7%
거 9
 
3.5%
주 9
 
3.5%
Other values (20) 74
29.0%
ASCII
ValueCountFrequency (%)
17
38.6%
, 15
34.1%
1 6
 
13.6%
( 2
 
4.5%
) 2
 
4.5%
2 2
 
4.5%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3123.7239
Minimum69.355
Maximum22372.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:06.437498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum69.355
5-th percentile93.723
Q1578.845
median1037.37
Q32635.68
95-th percentile17674.494
Maximum22372.71
Range22303.355
Interquartile range (IQR)2056.835

Descriptive statistics

Standard deviation5757.4689
Coefficient of variation (CV)1.8431427
Kurtosis8.7676333
Mean3123.7239
Median Absolute Deviation (MAD)925.3
Skewness3.0601641
Sum84340.545
Variance33148448
MonotonicityNot monotonic
2024-01-28T20:31:06.521525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2635.68 3
 
11.1%
2207.16 2
 
7.4%
22372.71 2
 
7.4%
537.43 2
 
7.4%
981.98 1
 
3.7%
112.07 1
 
3.7%
2877.12 1
 
3.7%
1319.58 1
 
3.7%
671.97 1
 
3.7%
560.37 1
 
3.7%
Other values (12) 12
44.4%
ValueCountFrequency (%)
69.355 1
3.7%
85.86 1
3.7%
112.07 1
3.7%
537.43 2
7.4%
547.74 1
3.7%
560.37 1
3.7%
597.32 1
3.7%
671.97 1
3.7%
678.9 1
3.7%
691.56 1
3.7%
ValueCountFrequency (%)
22372.71 2
7.4%
6711.99 1
 
3.7%
5237.1 1
 
3.7%
2877.12 1
 
3.7%
2635.68 3
11.1%
2207.16 2
7.4%
2026.38 1
 
3.7%
1319.58 1
 
3.7%
1175.22 1
 
3.7%
1037.37 1
 
3.7%

건폐율(퍼센트)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct21
Distinct (%)80.8%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean63.407077
Minimum27.78
Maximum79.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:06.614082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27.78
5-th percentile33.7075
Q159.77
median62.771
Q369.9
95-th percentile79.48
Maximum79.74
Range51.96
Interquartile range (IQR)10.13

Descriptive statistics

Standard deviation13.37205
Coefficient of variation (CV)0.21089207
Kurtosis2.2639329
Mean63.407077
Median Absolute Deviation (MAD)6.32
Skewness-1.2398615
Sum1648.584
Variance178.81171
MonotonicityNot monotonic
2024-01-28T20:31:06.716167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
79.48 3
 
11.1%
64.182 2
 
7.4%
69.9 2
 
7.4%
59.87 2
 
7.4%
50.47 1
 
3.7%
56.89 1
 
3.7%
79.74 1
 
3.7%
66.63 1
 
3.7%
57.93 1
 
3.7%
61.36 1
 
3.7%
Other values (11) 11
40.7%
ValueCountFrequency (%)
27.78 1
3.7%
28.12 1
3.7%
50.47 1
3.7%
56.89 1
3.7%
57.93 1
3.7%
58.35 1
3.7%
59.75 1
3.7%
59.83 1
3.7%
59.84 1
3.7%
59.87 2
7.4%
ValueCountFrequency (%)
79.74 1
 
3.7%
79.48 3
11.1%
79.26 1
 
3.7%
75.72 1
 
3.7%
69.9 2
7.4%
69.72 1
 
3.7%
69.53 1
 
3.7%
66.63 1
 
3.7%
64.182 2
7.4%
61.36 1
 
3.7%

주용도
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
업무시설(오피스텔)
9 
공장(지식산업센터)
4 
공동주택
2 
판매시설
2 
노유자시설
2 
Other values (8)
8 

Length

Max length12
Median length10
Mean length8.2962963
Min length2

Unique

Unique8 ?
Unique (%)29.6%

Sample

1st row공동주택
2nd row공동주택
3rd row판매시설
4th row운수시설, 근린생활
5th row판매시설

Common Values

ValueCountFrequency (%)
업무시설(오피스텔) 9
33.3%
공장(지식산업센터) 4
14.8%
공동주택 2
 
7.4%
판매시설 2
 
7.4%
노유자시설 2
 
7.4%
운수시설, 근린생활 1
 
3.7%
공동주택, 업무시설 1
 
3.7%
제1,2종 근린생활시설 1
 
3.7%
업무시설, 근린생활시설 1
 
3.7%
업무시설,근생 1
 
3.7%
Other values (3) 3
 
11.1%

Length

2024-01-28T20:31:06.816700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설(오피스텔 9
29.0%
공장(지식산업센터 4
12.9%
공동주택 3
 
9.7%
판매시설 2
 
6.5%
노유자시설 2
 
6.5%
업무시설 2
 
6.5%
근린생활시설 2
 
6.5%
운수시설 1
 
3.2%
근린생활 1
 
3.2%
제1,2종 1
 
3.2%
Other values (4) 4
12.9%

구조
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
철근콘크리트조
21 
철근콘크리트구조
5 
일반철골구조
 
1

Length

Max length8
Median length7
Mean length7.1481481
Min length6

Unique

Unique1 ?
Unique (%)3.7%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트조 21
77.8%
철근콘크리트구조 5
 
18.5%
일반철골구조 1
 
3.7%

Length

2024-01-28T20:31:06.910941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:06.990085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근콘크리트조 21
77.8%
철근콘크리트구조 5
 
18.5%
일반철골구조 1
 
3.7%

최고높이(미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)76.0%
Missing2
Missing (%)7.4%
Infinite0
Infinite (%)0.0%
Mean44.0232
Minimum10.63
Maximum62.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:07.078942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.63
5-th percentile16.54
Q132.9
median49.9
Q357.7
95-th percentile61.9
Maximum62.1
Range51.47
Interquartile range (IQR)24.8

Descriptive statistics

Standard deviation15.402781
Coefficient of variation (CV)0.34987872
Kurtosis-0.46894257
Mean44.0232
Median Absolute Deviation (MAD)8.1
Skewness-0.79866849
Sum1100.58
Variance237.24566
MonotonicityNot monotonic
2024-01-28T20:31:07.185542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
49.9 4
14.8%
22.7 2
 
7.4%
62.1 2
 
7.4%
46.8 2
 
7.4%
59.9 1
 
3.7%
10.63 1
 
3.7%
57.7 1
 
3.7%
48.0 1
 
3.7%
38.2 1
 
3.7%
50.5 1
 
3.7%
Other values (9) 9
33.3%
(Missing) 2
 
7.4%
ValueCountFrequency (%)
10.63 1
3.7%
15.0 1
3.7%
22.7 2
7.4%
23.0 1
3.7%
30.0 1
3.7%
32.9 1
3.7%
38.2 1
3.7%
44.0 1
3.7%
46.8 2
7.4%
48.0 1
3.7%
ValueCountFrequency (%)
62.1 2
7.4%
61.1 1
 
3.7%
59.9 1
 
3.7%
58.0 1
 
3.7%
57.85 1
 
3.7%
57.7 1
 
3.7%
51.0 1
 
3.7%
50.5 1
 
3.7%
49.9 4
14.8%
48.0 1
 
3.7%

용적률(퍼센트)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)88.5%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean443.13692
Minimum53.13
Maximum893.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-01-28T20:31:07.274762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53.13
5-th percentile86.81
Q1269.8275
median403.775
Q3647.845
95-th percentile866.3275
Maximum893.21
Range840.08
Interquartile range (IQR)378.0175

Descriptive statistics

Standard deviation256.49205
Coefficient of variation (CV)0.57880993
Kurtosis-0.83877288
Mean443.13692
Median Absolute Deviation (MAD)178.815
Skewness0.30781027
Sum11521.56
Variance65788.172
MonotonicityNot monotonic
2024-01-28T20:31:07.362898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
86.81 2
 
7.4%
386.55 2
 
7.4%
439.17 2
 
7.4%
355.74 1
 
3.7%
388.2 1
 
3.7%
96.16 1
 
3.7%
382.68 1
 
3.7%
893.21 1
 
3.7%
441.07 1
 
3.7%
867.77 1
 
3.7%
Other values (13) 13
48.1%
ValueCountFrequency (%)
53.13 1
3.7%
86.81 2
7.4%
96.16 1
3.7%
182.63 1
3.7%
208.73 1
3.7%
241.19 1
3.7%
355.74 1
3.7%
357.69 1
3.7%
382.68 1
3.7%
386.55 2
7.4%
ValueCountFrequency (%)
893.21 1
3.7%
867.77 1
3.7%
862.0 1
3.7%
763.75 1
3.7%
755.86 1
3.7%
755.82 1
3.7%
699.16 1
3.7%
493.9 1
3.7%
478.46 1
3.7%
441.07 1
3.7%

심의결과
Categorical

Distinct3
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size348.0 B
조건부 의결
15 
원안 의결
6 
재검토 의결
6 

Length

Max length6
Median length6
Mean length5.7777778
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row조건부 의결
2nd row원안 의결
3rd row조건부 의결
4th row조건부 의결
5th row재검토 의결

Common Values

ValueCountFrequency (%)
조건부 의결 15
55.6%
원안 의결 6
 
22.2%
재검토 의결 6
 
22.2%

Length

2024-01-28T20:31:07.448992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:07.532169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의결 27
50.0%
조건부 15
27.8%
원안 6
 
11.1%
재검토 6
 
11.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-06-13
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-13
2nd row2023-06-13
3rd row2023-06-13
4th row2023-06-13
5th row2023-06-13

Common Values

ValueCountFrequency (%)
2023-06-13 27
100.0%

Length

2024-01-28T20:31:07.615650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T20:31:07.683780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-13 27
100.0%

Interactions

2024-01-28T20:31:02.654301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:00.455588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.087219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.518853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.887046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.249485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.728225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:00.524763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.170603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.587934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.957239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.327701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.805061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:00.590841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.249331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.656022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.018919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.408388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.873404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:00.650707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.319070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.714145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.074574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.476265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.935707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:00.938709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.389783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.771752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.133973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.535115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:03.009170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.016543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.457310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:01.833765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.193409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T20:31:02.594988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T20:31:07.738996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차안건심의목적심의일자건축종별건축주대지위치지번대지면적(제곱미터)용도지역건축면적건폐율(퍼센트)주용도구조최고높이(미터)용적률(퍼센트)심의결과
연도1.0000.2820.0001.0001.0000.0000.0000.0000.0000.0000.2970.0000.5851.0000.0000.0000.5860.000
회차0.2821.0000.0000.4511.0000.7020.7660.5790.7660.7800.5850.7020.0000.7280.1540.3370.0000.492
안건0.0000.0001.0000.5370.0000.3750.9300.3210.9300.0000.8050.0000.3730.6100.3390.3090.4610.000
심의목적1.0000.4510.5371.0000.6171.0000.9340.6530.9340.7740.8670.7320.7620.9680.8860.8840.8040.747
심의일자1.0001.0000.0000.6171.0000.5020.8040.6800.8040.8920.6640.7150.1490.8000.4430.0000.0000.207
건축종별0.0000.7020.3751.0000.5021.0001.0000.4681.0000.6771.0000.4110.3891.0000.0001.0000.4840.625
건축주0.0000.7660.9300.9340.8041.0001.0001.0001.0001.0000.9711.0000.8950.9811.0001.0001.0000.000
대지위치0.0000.5790.3210.6530.6800.4681.0001.0001.0000.9160.9760.8520.7150.8390.7980.5840.7810.266
지번0.0000.7660.9300.9340.8041.0001.0001.0001.0001.0000.9711.0000.8950.9811.0001.0001.0000.000
대지면적(제곱미터)0.0000.7800.0000.7740.8920.6771.0000.9161.0001.0000.9850.8810.6070.8440.0000.7470.5710.000
용도지역0.2970.5850.8050.8670.6641.0000.9710.9760.9710.9851.0000.9390.7470.9430.8920.8360.9230.000
건축면적0.0000.7020.0000.7320.7150.4111.0000.8521.0000.8810.9391.0000.6780.9180.0000.8590.5690.065
건폐율(퍼센트)0.5850.0000.3730.7620.1490.3890.8950.7150.8950.6070.7470.6781.0000.8530.1450.2900.4090.000
주용도1.0000.7280.6100.9680.8001.0000.9810.8390.9810.8440.9430.9180.8531.0000.8360.9240.8260.202
구조0.0000.1540.3390.8860.4430.0001.0000.7981.0000.0000.8920.0000.1450.8361.0000.4640.0000.421
최고높이(미터)0.0000.3370.3090.8840.0001.0001.0000.5841.0000.7470.8360.8590.2900.9240.4641.0000.8150.454
용적률(퍼센트)0.5860.0000.4610.8040.0000.4841.0000.7811.0000.5710.9230.5690.4090.8260.0000.8151.0000.000
심의결과0.0000.4920.0000.7470.2070.6250.0000.2660.0000.0000.0000.0650.0000.2020.4210.4540.0001.000
2024-01-28T20:31:07.866875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지위치심의목적심의일자건축종별심의결과구조연도주용도안건
대지위치1.0000.3350.2320.2440.0750.5730.0000.4840.006
심의목적0.3351.0000.3030.8660.3780.5260.8490.7730.295
심의일자0.2320.3031.0000.2720.0000.2230.8250.4270.000
건축종별0.2440.8660.2721.0000.2870.0000.0000.7640.284
심의결과0.0750.3780.0000.2871.0000.1480.0000.0000.000
구조0.5730.5260.2230.0000.1481.0000.0000.5340.250
연도0.0000.8490.8250.0000.0000.0001.0000.7480.000
주용도0.4840.7730.4270.7640.0000.5340.7481.0000.280
안건0.0060.2950.0000.2840.0000.2500.0000.2801.000
2024-01-28T20:31:07.965257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회차대지면적(제곱미터)건축면적건폐율(퍼센트)최고높이(미터)용적률(퍼센트)연도안건심의목적심의일자건축종별대지위치주용도구조심의결과
회차1.0000.3050.2700.099-0.128-0.2380.2150.0000.0950.9720.3400.2710.3430.0000.187
대지면적(제곱미터)0.3051.0000.8440.3180.051-0.1700.0000.0000.5260.4960.6210.5350.5200.0000.000
건축면적0.2700.8441.0000.501-0.013-0.1680.0000.0000.4970.4340.3890.5960.6300.0000.000
건폐율(퍼센트)0.0990.3180.5011.0000.1480.1770.5550.2150.5010.0000.2400.4120.4960.0000.000
최고높이(미터)-0.1280.051-0.0130.1481.0000.6350.0000.1370.4840.0000.8600.2750.6120.2730.265
용적률(퍼센트)-0.238-0.170-0.1680.1770.6351.0000.4880.2320.3570.0000.1770.4730.4570.0000.000
연도0.2150.0000.0000.5550.0000.4881.0000.0000.8490.8250.0000.0000.7480.0000.000
안건0.0000.0000.0000.2150.1370.2320.0001.0000.2950.0000.2840.0060.2800.2500.000
심의목적0.0950.5260.4970.5010.4840.3570.8490.2951.0000.3030.8660.3350.7730.5260.378
심의일자0.9720.4960.4340.0000.0000.0000.8250.0000.3031.0000.2720.2320.4270.2230.000
건축종별0.3400.6210.3890.2400.8600.1770.0000.2840.8660.2721.0000.2440.7640.0000.287
대지위치0.2710.5350.5960.4120.2750.4730.0000.0060.3350.2320.2441.0000.4840.5730.075
주용도0.3430.5200.6300.4960.6120.4570.7480.2800.7730.4270.7640.4841.0000.5340.000
구조0.0000.0000.0000.0000.2730.0000.0000.2500.5260.2230.0000.5730.5341.0000.148
심의결과0.1870.0000.0000.0000.2650.0000.0000.0000.3780.0000.2870.0750.0000.1481.000

Missing values

2024-01-28T20:31:03.125230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T20:31:03.305789image/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.
2024-01-28T20:31:03.409954image/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

연도회차안건심의목적운영기관심의일자건축종별건축주대지위치지번대지면적(제곱미터)용도지역건축면적건폐율(퍼센트)주용도구조최고높이(미터)용적률(퍼센트)심의결과데이터기준일
0202311분양대상 건축물남동구 건축과2023-01-30신축만수동5의19번지 소규모재건축정비사업조합인천광역시 남동구 만수동5-19번지1945.5준주거지역981.9850.47공동주택철근콘크리트조58.0355.74조건부 의결2023-06-13
1202312적용의 완화신청남동구 건축과2023-01-30신축코리아신탁㈜인천광역시 남동구 간석동189-2번지1736.2제2종일반주거지역1037.3759.75공동주택철근콘크리트조15.0241.19원안 의결2023-06-13
2202291다중이용 건축물남동구 건축과2022-12-20신축㈜이마트인천광역시 남동구 구월동1549번지32007.78일반상업지역, 제1종지구단위계획22372.7169.9판매시설철근콘크리트조22.786.81조건부 의결2023-06-13
3202292논현2지구 상업용지 건축물남동구 건축과2022-12-20증축인천논현역개발 주식회사인천광역시 남동구 논현동731-4번지24152.76일반상업지역, 지구단위계획(논현2)6711.9927.78운수시설, 근린생활철근콘크리트조30.053.13조건부 의결2023-06-13
4202281다중이용 건축물남동구 건축과2022-11-23신축㈜이마트인천광역시 남동구 구월동1549번지32007.78일반상업지역, 제1종지구단위계획22372.7169.9판매시설철근콘크리트조22.786.81재검토 의결2023-06-13
5202282리모델링이 쉬운 구조에 대한 평가남동구 건축과2022-11-23신축만수동5의19번지 소규모재건축정비사업조합인천광역시 남동구 만수동5-19번지1948.0준주거지역547.7428.12공동주택, 업무시설철근콘크리트조57.85357.69원안 의결2023-06-13
6202271분양을 목적으로 하는 건축물남동구 건축과2022-10-06신축홍엽인천광역시 남동구 구월동1450-1번지973.8일반상업지역, 제1종지구단위계획678.969.72제1,2종 근린생활시설철근콘크리트조32.9478.46조건부 의결2023-06-13
7202272분양을 목적으로 하는 건축물남동구 건축과2022-10-06신축문창미 외 4인인천광역시 남동구 논현동751-2번지3473.0일반상업지역, 지구단위계획(소래논현)2026.3858.35업무시설, 근린생활시설철근콘크리트조61.1763.75조건부 의결2023-06-13
8202261분양을 목적으로 하는 건축물남동구 건축과2022-09-05신축㈜록키지산인천광역시 남동구 남촌동618-8번지3315.8일반상업지역, 국가산업단지2635.6879.48공장(지식산업센터)철근콘크리트조49.9386.55조건부 의결2023-06-13
9202251분양을 목적으로 하는 건축물남동구 건축과2022-07-21신축이질용인천광역시 남동구 남촌동618-8번지3315.8일반상업지역, 국가산업단지2635.6879.48공장(지식산업센터)철근콘크리트조49.9386.55재검토 의결2023-06-13
연도회차안건심의목적운영기관심의일자건축종별건축주대지위치지번대지면적(제곱미터)용도지역건축면적건폐율(퍼센트)주용도구조최고높이(미터)용적률(퍼센트)심의결과데이터기준일
17202233분양을 목적으로 하는 건축물남동구 건축과2022-05-30신축김창동인천광역시 남동구 만수동884-8번지897.6준주거지역, 철도보호지구537.4359.87업무시설(오피스텔)철근콘크리트조46.8439.17재검토 의결2023-06-13
18202234화재안전성능보강 계획 승인남동구 건축과2022-05-30기타시온예능어린이집인천광역시 남동구 간석동920-27번지113.1준주거지역69.35561.32노유자시설철근콘크리트조<NA>182.63원안 의결2023-06-13
19202235화재안전성능보강 계획 승인남동구 건축과2022-05-30기타아이마루어린이집인천광역시 남동구 구월동1301-37지3438.9<NA>85.86<NA>노유자시설철근콘크리트조<NA><NA>원안 의결2023-06-13
20202221분양을 목적으로 하는 건축물남동구 건축과2022-04-20신축김동식 외 2인인천광역시 남동구 구월동1134 외 2필지3438.9일반상업지역2207.1664.182업무시설(오피스텔)철근콘크리트조50.5755.82재검토 의결2023-06-13
21202222분양을 목적으로 하는 건축물남동구 건축과2022-04-20신축씨엔에스개발주식회사인천광역시 남동구 만수동884-3 외 3필지1963.8준주거지역1175.2259.84업무시설(오피스텔)철근콘크리트구조38.2493.9조건부 의결2023-06-13
22202223분양을 목적으로 하는 건축물남동구 건축과2022-04-20신축이동재인천광역시 남동구 간석동124-6 외 4필지913.3일반상업지역560.3761.36업무시설(오피스텔)철근콘크리트구조62.1867.77재검토 의결2023-06-13
23202224분양을 목적으로 하는 건축물남동구 건축과2022-04-20신축정민기인천광역시 남동구 만수동865-20 외 10필지1159.9준주거지역671.9757.93업무시설(오피스텔)철근콘크리트구조48.0441.07조건부 의결2023-06-13
24202211분양을 목적으로 하는 건축물남동구 건축과2022-02-28신축초정개발(주) 외 1인천광역시 남동구 간석동123-23 외 6필지1980.6일반상업지역1319.5866.63업무시설(오피스텔)철근콘크리트조57.7893.21원안 의결2023-06-13
25202212분양을 목적으로 하는 건축물남동구 건축과2022-02-28신축정현길인천광역시 남동구 고잔동627-7번지3607.9일반공업지역2877.1279.74공장철근콘크리트구조49.9382.68조건부 의결2023-06-13
26202213도로지정남동구 건축과2022-02-28신축강수현 외 1인천광역시 남동구 운연동43-5번지197.0제1종일반주거지역112.0756.89제2종근린생활시설일반철골구조10.6396.16원안 의결2023-06-13