Overview

Dataset statistics

Number of variables12
Number of observations113
Missing cells6
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory102.2 B

Variable types

Numeric4
Categorical3
Text2
DateTime3

Dataset

Description서울특별시 관악구 민간공사장 현황 데이터로 건축구분, 대지위치, 건축면적, 연면적, 허가일, 착공처리일자, 최대지상층, 최대지하층, 주용도, 부속용도, 데이터기준일 등을 제공합니다
URLhttps://www.data.go.kr/data/15117092/fileData.do

Alerts

데이터기준일 has constant value ""Constant
대지면적 is highly overall correlated with 건축면적 and 1 other fieldsHigh correlation
건축면적 is highly overall correlated with 대지면적High correlation
최대지상층수 is highly overall correlated with 최대지하층수High correlation
최대지하층수 is highly overall correlated with 최대지상층수High correlation
주용도 is highly overall correlated with 대지면적High correlation
건축구분 is highly imbalanced (55.9%)Imbalance
부속용도 has 6 (5.3%) missing valuesMissing
연번 has unique valuesUnique
대지위치 has unique valuesUnique
건축면적 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:30:57.915341
Analysis finished2023-12-12 07:31:01.326800
Duration3.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57
Minimum1
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:31:01.437099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.6
Q129
median57
Q385
95-th percentile107.4
Maximum113
Range112
Interquartile range (IQR)56

Descriptive statistics

Standard deviation32.76431
Coefficient of variation (CV)0.57481245
Kurtosis-1.2
Mean57
Median Absolute Deviation (MAD)28
Skewness0
Sum6441
Variance1073.5
MonotonicityStrictly increasing
2023-12-12T16:31:01.629183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
86 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%

건축구분
Categorical

IMBALANCE 

Distinct4
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
신축
94 
증축
10 
대수선
 
7
용도변경
 
2

Length

Max length4
Median length2
Mean length2.0973451
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 94
83.2%
증축 10
 
8.8%
대수선 7
 
6.2%
용도변경 2
 
1.8%

Length

2023-12-12T16:31:01.829910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:01.961197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 94
83.2%
증축 10
 
8.8%
대수선 7
 
6.2%
용도변경 2
 
1.8%

대지위치
Text

UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T16:31:02.306743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.185841
Min length18

Characters and Unicode

Total characters2394
Distinct characters31
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

Unique113 ?
Unique (%)100.0%

Sample

1st row서울특별시 관악구 신림동 산 56-1
2nd row서울특별시 관악구 신림동 1579-2 외1필지
3rd row서울특별시 관악구 봉천동 702-30
4th row서울특별시 관악구 신림동 1419-28
5th row서울특별시 관악구 신림동 1463-16
ValueCountFrequency (%)
서울특별시 113
23.6%
관악구 113
23.6%
신림동 64
13.4%
봉천동 44
 
9.2%
외1필지 19
 
4.0%
남현동 5
 
1.0%
외2필지 4
 
0.8%
산 3
 
0.6%
533-19 1
 
0.2%
1429-45 1
 
0.2%
Other values (111) 111
23.2%
2023-12-12T16:31:02.830841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
365
 
15.2%
1 138
 
5.8%
서 113
 
4.7%
동 113
 
4.7%
특 113
 
4.7%
별 113
 
4.7%
시 113
 
4.7%
관 113
 
4.7%
악 113
 
4.7%
구 113
 
4.7%
Other values (21) 987
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1315
54.9%
Decimal Number 602
25.1%
Space Separator 365
 
15.2%
Dash Punctuation 112
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 113
8.6%
동 113
8.6%
특 113
8.6%
별 113
8.6%
시 113
8.6%
관 113
8.6%
악 113
8.6%
구 113
8.6%
울 113
8.6%
림 64
 
4.9%
Other values (9) 234
17.8%
Decimal Number
ValueCountFrequency (%)
1 138
22.9%
6 65
10.8%
2 65
10.8%
4 65
10.8%
5 55
 
9.1%
0 51
 
8.5%
3 50
 
8.3%
8 43
 
7.1%
9 36
 
6.0%
7 34
 
5.6%
Space Separator
ValueCountFrequency (%)
365
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1315
54.9%
Common 1079
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 113
8.6%
동 113
8.6%
특 113
8.6%
별 113
8.6%
시 113
8.6%
관 113
8.6%
악 113
8.6%
구 113
8.6%
울 113
8.6%
림 64
 
4.9%
Other values (9) 234
17.8%
Common
ValueCountFrequency (%)
365
33.8%
1 138
 
12.8%
- 112
 
10.4%
6 65
 
6.0%
2 65
 
6.0%
4 65
 
6.0%
5 55
 
5.1%
0 51
 
4.7%
3 50
 
4.6%
8 43
 
4.0%
Other values (2) 70
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1315
54.9%
ASCII 1079
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
365
33.8%
1 138
 
12.8%
- 112
 
10.4%
6 65
 
6.0%
2 65
 
6.0%
4 65
 
6.0%
5 55
 
5.1%
0 51
 
4.7%
3 50
 
4.6%
8 43
 
4.0%
Other values (2) 70
 
6.5%
Hangul
ValueCountFrequency (%)
서 113
8.6%
동 113
8.6%
특 113
8.6%
별 113
8.6%
시 113
8.6%
관 113
8.6%
악 113
8.6%
구 113
8.6%
울 113
8.6%
림 64
 
4.9%
Other values (9) 234
17.8%

대지면적
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69215.877
Minimum84.3
Maximum3895659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:31:03.038990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum84.3
5-th percentile111.124
Q1160.24
median202
Q3331.7
95-th percentile1026.24
Maximum3895659
Range3895574.7
Interquartile range (IQR)171.46

Descriptive statistics

Standard deviation515468.25
Coefficient of variation (CV)7.4472545
Kurtosis53.927533
Mean69215.877
Median Absolute Deviation (MAD)68.5
Skewness7.4143875
Sum7821394.1
Variance2.6570752 × 1011
MonotonicityNot monotonic
2023-12-12T16:31:03.233804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182.0 2
 
1.8%
132.0 2
 
1.8%
325.6 2
 
1.8%
336.0 2
 
1.8%
3895659.0 1
 
0.9%
164.6 1
 
0.9%
181.01 1
 
0.9%
203.0 1
 
0.9%
246.8 1
 
0.9%
264.0 1
 
0.9%
Other values (99) 99
87.6%
ValueCountFrequency (%)
84.3 1
0.9%
93.9 1
0.9%
101.8 1
0.9%
107.45 1
0.9%
108.13 1
0.9%
109.06 1
0.9%
112.5 1
0.9%
121.05 1
0.9%
121.58 1
0.9%
124.46 1
0.9%
ValueCountFrequency (%)
3895659.0 1
0.9%
3889012.0 1
0.9%
3730.0 1
0.9%
2122.67 1
0.9%
1927.6 1
0.9%
1043.1 1
0.9%
1015.0 1
0.9%
850.3 1
0.9%
829.0 1
0.9%
756.9 1
0.9%

건축면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct113
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191.18525
Minimum50.54
Maximum1832.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:31:03.442769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50.54
5-th percentile64.238
Q191.66
median118.57
Q3188.56
95-th percentile496.0648
Maximum1832.45
Range1781.91
Interquartile range (IQR)96.9

Descriptive statistics

Standard deviation233.82224
Coefficient of variation (CV)1.223014
Kurtosis24.800379
Mean191.18525
Median Absolute Deviation (MAD)38.3
Skewness4.5065789
Sum21603.933
Variance54672.839
MonotonicityNot monotonic
2023-12-12T16:31:03.621416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
991.33 1
 
0.9%
75.45 1
 
0.9%
93.43 1
 
0.9%
119.07 1
 
0.9%
142.4 1
 
0.9%
155.72 1
 
0.9%
157.86 1
 
0.9%
96.1 1
 
0.9%
77.22 1
 
0.9%
156.87 1
 
0.9%
Other values (103) 103
91.2%
ValueCountFrequency (%)
50.54 1
0.9%
56.31 1
0.9%
60.35 1
0.9%
60.83 1
0.9%
62.21 1
0.9%
63.53 1
0.9%
64.71 1
0.9%
64.9 1
0.9%
69.0 1
0.9%
71.91 1
0.9%
ValueCountFrequency (%)
1832.45 1
0.9%
1098.53 1
0.9%
1003.9 1
0.9%
991.33 1
0.9%
607.18 1
0.9%
504.37 1
0.9%
490.528 1
0.9%
438.78 1
0.9%
415.3602 1
0.9%
411.44 1
0.9%

최대지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5309735
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T16:31:03.779870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q14
median5
Q36
95-th percentile9.4
Maximum18
Range17
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.467904
Coefficient of variation (CV)0.44619704
Kurtosis9.3351172
Mean5.5309735
Median Absolute Deviation (MAD)1
Skewness2.6779843
Sum625
Variance6.0905499
MonotonicityNot monotonic
2023-12-12T16:31:03.917246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
5 40
35.4%
4 33
29.2%
6 15
 
13.3%
8 6
 
5.3%
3 5
 
4.4%
9 4
 
3.5%
7 3
 
2.7%
12 1
 
0.9%
15 1
 
0.9%
18 1
 
0.9%
Other values (4) 4
 
3.5%
ValueCountFrequency (%)
1 1
 
0.9%
3 5
 
4.4%
4 33
29.2%
5 40
35.4%
6 15
 
13.3%
7 3
 
2.7%
8 6
 
5.3%
9 4
 
3.5%
10 1
 
0.9%
11 1
 
0.9%
ValueCountFrequency (%)
18 1
 
0.9%
16 1
 
0.9%
15 1
 
0.9%
12 1
 
0.9%
11 1
 
0.9%
10 1
 
0.9%
9 4
 
3.5%
8 6
 
5.3%
7 3
 
2.7%
6 15
13.3%

최대지하층수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
1
62 
0
41 
2
8 
4
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 62
54.9%
0 41
36.3%
2 8
 
7.1%
4 1
 
0.9%
3 1
 
0.9%

Length

2023-12-12T16:31:04.102284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:04.218389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 62
54.9%
0 41
36.3%
2 8
 
7.1%
4 1
 
0.9%
3 1
 
0.9%

허가신고일
Date

Distinct87
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2019-04-08 00:00:00
Maximum2023-06-29 00:00:00
2023-12-12T16:31:04.358769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:04.527536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

Distinct78
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2022-11-02 00:00:00
Maximum2023-07-18 00:00:00
2023-12-12T16:31:04.698165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:04.853002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주용도
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
단독주택
44 
제2종근린생활시설
24 
공동주택
24 
업무시설
9 
제1종근린생활시설
8 
Other values (3)
 
4

Length

Max length9
Median length4
Mean length5.4778761
Min length4

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row교육연구시설
2nd row단독주택
3rd row제1종근린생활시설
4th row업무시설
5th row업무시설

Common Values

ValueCountFrequency (%)
단독주택 44
38.9%
제2종근린생활시설 24
21.2%
공동주택 24
21.2%
업무시설 9
 
8.0%
제1종근린생활시설 8
 
7.1%
교육연구시설 2
 
1.8%
교정및군사시설 1
 
0.9%
종교시설 1
 
0.9%

Length

2023-12-12T16:31:05.046303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:31:05.171022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독주택 44
38.9%
제2종근린생활시설 24
21.2%
공동주택 24
21.2%
업무시설 9
 
8.0%
제1종근린생활시설 8
 
7.1%
교육연구시설 2
 
1.8%
교정및군사시설 1
 
0.9%
종교시설 1
 
0.9%

부속용도
Text

MISSING 

Distinct69
Distinct (%)64.5%
Missing6
Missing (%)5.3%
Memory size1.0 KiB
2023-12-12T16:31:05.388355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length20
Mean length11.616822
Min length3

Characters and Unicode

Total characters1243
Distinct characters80
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)47.7%

Sample

1st row연구실
2nd row제2종근린생활시설
3rd row근린생활시설및다중주택
4th row다세대주택/근린생활시설
5th row근생 및 오피스텔
ValueCountFrequency (%)
다중주택 20
 
12.7%
및 20
 
12.7%
근린생활시설 12
 
7.6%
제2종근린생활시설 6
 
3.8%
근생및다중주택 5
 
3.2%
근린생활시설및다중주택 4
 
2.5%
다중주택및근생 4
 
2.5%
도시형생활주택(단지형다세대주택 4
 
2.5%
단독(다중)주택 4
 
2.5%
근생 4
 
2.5%
Other values (59) 75
47.5%
2023-12-12T16:31:05.773071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 102
 
8.2%
택 101
 
8.1%
다 79
 
6.4%
생 75
 
6.0%
시 62
 
5.0%
활 57
 
4.6%
근 54
 
4.3%
중 53
 
4.3%
51
 
4.1%
및 41
 
3.3%
Other values (70) 568
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1036
83.3%
Space Separator 51
 
4.1%
Open Punctuation 48
 
3.9%
Close Punctuation 48
 
3.9%
Decimal Number 34
 
2.7%
Math Symbol 19
 
1.5%
Dash Punctuation 4
 
0.3%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 102
 
9.8%
택 101
 
9.7%
다 79
 
7.6%
생 75
 
7.2%
시 62
 
6.0%
활 57
 
5.5%
근 54
 
5.2%
중 53
 
5.1%
및 41
 
4.0%
설 41
 
4.0%
Other values (55) 371
35.8%
Decimal Number
ValueCountFrequency (%)
2 18
52.9%
1 11
32.4%
7 1
 
2.9%
0 1
 
2.9%
5 1
 
2.9%
4 1
 
2.9%
6 1
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 41
85.4%
[ 7
 
14.6%
Close Punctuation
ValueCountFrequency (%)
) 41
85.4%
] 7
 
14.6%
Space Separator
ValueCountFrequency (%)
51
100.0%
Math Symbol
ValueCountFrequency (%)
+ 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1036
83.3%
Common 207
 
16.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 102
 
9.8%
택 101
 
9.7%
다 79
 
7.6%
생 75
 
7.2%
시 62
 
6.0%
활 57
 
5.5%
근 54
 
5.2%
중 53
 
5.1%
및 41
 
4.0%
설 41
 
4.0%
Other values (55) 371
35.8%
Common
ValueCountFrequency (%)
51
24.6%
( 41
19.8%
) 41
19.8%
+ 19
 
9.2%
2 18
 
8.7%
1 11
 
5.3%
[ 7
 
3.4%
] 7
 
3.4%
- 4
 
1.9%
/ 3
 
1.4%
Other values (5) 5
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1036
83.3%
ASCII 207
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 102
 
9.8%
택 101
 
9.7%
다 79
 
7.6%
생 75
 
7.2%
시 62
 
6.0%
활 57
 
5.5%
근 54
 
5.2%
중 53
 
5.1%
및 41
 
4.0%
설 41
 
4.0%
Other values (55) 371
35.8%
ASCII
ValueCountFrequency (%)
51
24.6%
( 41
19.8%
) 41
19.8%
+ 19
 
9.2%
2 18
 
8.7%
1 11
 
5.3%
[ 7
 
3.4%
] 7
 
3.4%
- 4
 
1.9%
/ 3
 
1.4%
Other values (5) 5
 
2.4%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2023-07-24 00:00:00
Maximum2023-07-24 00:00:00
2023-12-12T16:31:05.919679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:06.036194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T16:31:00.584364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.816419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.258653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.714324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:00.692702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:58.912327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.372122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.836887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:00.797172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.055053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.490926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.983128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:00.913547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.170013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:30:59.611722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:31:00.471568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:31:06.113731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축구분대지면적건축면적최대지상층수최대지하층수허가신고일착공처리일주용도부속용도
연번1.0000.2870.0000.0790.0000.3620.9920.7380.0000.574
건축구분0.2871.0000.4240.4740.4110.0650.7680.5080.5930.843
대지면적0.0000.4241.0000.9510.0000.0000.0000.0001.0001.000
건축면적0.0790.4740.9511.0000.7440.6020.0000.0000.6660.973
최대지상층수0.0000.4110.0000.7441.0000.7150.0000.8020.7010.971
최대지하층수0.3620.0650.0000.6020.7151.0000.0000.6790.4260.640
허가신고일0.9920.7680.0000.0000.0000.0001.0000.9560.0000.000
착공처리일0.7380.5080.0000.0000.8020.6790.9561.0000.8480.267
주용도0.0000.5931.0000.6660.7010.4260.0000.8481.0000.983
부속용도0.5740.8431.0000.9730.9710.6400.0000.2670.9831.000
2023-12-12T16:31:06.273778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도최대지하층수건축구분
주용도1.0000.2730.292
최대지하층수0.2731.0000.050
건축구분0.2920.0501.000
2023-12-12T16:31:06.406889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번대지면적건축면적최대지상층수건축구분최대지하층수주용도
연번1.000-0.039-0.028-0.0920.1680.1520.000
대지면적-0.0391.0000.9880.3720.2820.0000.973
건축면적-0.0280.9881.0000.3380.3200.4600.445
최대지상층수-0.0920.3720.3381.0000.2670.5080.437
건축구분0.1680.2820.3200.2671.0000.0500.292
최대지하층수0.1520.0000.4600.5080.0501.0000.273
주용도0.0000.9730.4450.4370.2920.2731.000

Missing values

2023-12-12T16:31:01.078031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:31:01.257408image/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

연번건축구분대지위치대지면적건축면적최대지상층수최대지하층수허가신고일착공처리일주용도부속용도데이터기준일
01증축서울특별시 관악구 신림동 산 56-13895659.0991.33612023-06-292023-07-14교육연구시설연구실2023-07-24
12용도변경서울특별시 관악구 신림동 1579-2 외1필지236.4138.55402023-06-142023-06-21단독주택제2종근린생활시설2023-07-24
23신축서울특별시 관악구 봉천동 702-30182.090.68502023-05-312023-07-12제1종근린생활시설근린생활시설및다중주택2023-07-24
34대수선서울특별시 관악구 신림동 1419-28185.5101.13802023-05-182023-05-25업무시설다세대주택/근린생활시설2023-07-24
45증축서울특별시 관악구 신림동 1463-16382.99207.7812023-05-182023-06-07업무시설근생 및 오피스텔2023-07-24
56증축서울특별시 관악구 봉천동 891-2984.350.54402023-05-092023-05-23제2종근린생활시설및 다중주택2023-07-24
67신축서울특별시 관악구 신림동 486-38165.197.29402023-04-282023-05-15제2종근린생활시설근린생활시설및다중주택2023-07-24
78신축서울특별시 관악구 신림동 486-2144.085.23402023-04-282023-05-15제1종근린생활시설근린생활시설및다중주택2023-07-24
89신축서울특별시 관악구 봉천동 47-2 외1필지408.68244.45512023-04-252023-06-20단독주택근린생활시설 및 주택2023-07-24
910신축서울특별시 관악구 남현동 602-144340.0192.94502023-04-192023-05-02공동주택도시형생활주택2023-07-24
연번건축구분대지위치대지면적건축면적최대지상층수최대지하층수허가신고일착공처리일주용도부속용도데이터기준일
103104신축서울특별시 관악구 신림동 567-40197.7118.57412022-04-262022-12-01단독주택다중주택+제2종근린생활시설(사무소)2023-07-24
104105신축서울특별시 관악구 봉천동 685-23254.0131.17512022-04-212022-11-18제2종근린생활시설제1+2종근린생활시설2023-07-24
105106신축서울특별시 관악구 봉천동 964-2173.9104.03402022-04-152022-12-01단독주택다중주택2023-07-24
106107신축서울특별시 관악구 봉천동 956-2341.5159.4612022-03-162023-02-28제2종근린생활시설사무소+다세대주택2023-07-24
107108신축서울특별시 관악구 신림동 10-619129.077.0422022-02-252023-01-06단독주택다중주택및근생2023-07-24
108109신축서울특별시 관악구 신림동 706-7287.5172.26502022-02-242022-12-30단독주택근린생활시설 및 다중주택2023-07-24
109110신축서울특별시 관악구 신림동 1409-3 외1필지756.9438.78522021-07-192023-03-24종교시설대순진리회 신림회관2023-07-24
110111신축서울특별시 관악구 봉천동 1612-40183.0109.74402021-03-222023-02-20제2종근린생활시설<NA>2023-07-24
111112신축서울특별시 관악구 신림동 652-103112.564.9412020-03-182022-11-18단독주택다가구주택2023-07-24
112113신축서울특별시 관악구 신림동 718-15304.0142.48502019-04-082023-04-04단독주택다가구2023-07-24