Overview

Dataset statistics

Number of variables13
Number of observations43
Missing cells52
Missing cells (%)9.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory113.1 B

Variable types

Categorical7
Text2
Numeric2
DateTime2

Dataset

Description경상남도 남해군에 소재하고 있는 미준공 신축 건축물 인허가 현황에 대한 데이터(출처: 건축행정시스템, 2018년~2023년 8월 기준)로 건축구분, 대지위치, 연면적, 최대지상층수, 최대지하층수, 주용도, 부속용도, 시공자사무소명 등의 항목을 제공하고 있습니다. * 데이터 부존재, 미집계, 개인정보 포함 등의 사유로 데이터값에 공란이 존재할 수 있습니다.
URLhttps://www.data.go.kr/data/15121765/fileData.do

Alerts

건축구분 has constant value ""Constant
세대수 is highly overall correlated with 연면적 and 4 other fieldsHigh correlation
최대지하층수 is highly overall correlated with 연면적 and 5 other fieldsHigh correlation
주용도 is highly overall correlated with 최대지상층수 and 4 other fieldsHigh correlation
부속용도 is highly overall correlated with 연면적 and 4 other fieldsHigh correlation
연면적 is highly overall correlated with 최대지상층수 and 4 other fieldsHigh correlation
최대지상층수 is highly overall correlated with 연면적 and 5 other fieldsHigh correlation
가구수 is highly overall correlated with 연면적 and 3 other fieldsHigh correlation
세대수 is highly imbalanced (76.2%)Imbalance
호수 is highly imbalanced (84.1%)Imbalance
가구수 is highly imbalanced (60.7%)Imbalance
착공처리일 has 17 (39.5%) missing valuesMissing
시공자사무소명 has 35 (81.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:54:09.694089
Analysis finished2023-12-12 18:54:11.944771
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
신축
43 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축 43
100.0%

Length

2023-12-13T03:54:12.078022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:12.254855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 43
100.0%

대지위치
Text

Distinct42
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
2023-12-13T03:54:12.646890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length23.790698
Min length18

Characters and Unicode

Total characters1023
Distinct characters67
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

Unique41 ?
Unique (%)95.3%

Sample

1st row경상남도 남해군 남해읍 북변리 461-4 외1필지
2nd row경상남도 남해군 남해읍 서변리 375
3rd row경상남도 남해군 상주면 양아리 237 외10필지
4th row경상남도 남해군 남면 선구리 674 외1필지
5th row경상남도 남해군 미조면 송정리 880
ValueCountFrequency (%)
경상남도 43
18.0%
남해군 43
18.0%
남해읍 10
 
4.2%
외1필지 10
 
4.2%
남면 7
 
2.9%
송정리 5
 
2.1%
미조면 5
 
2.1%
산 5
 
2.1%
상주면 5
 
2.1%
창선면 5
 
2.1%
Other values (75) 101
42.3%
2023-12-13T03:54:13.273152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
196
19.2%
남 103
 
10.1%
해 53
 
5.2%
상 52
 
5.1%
도 44
 
4.3%
1 44
 
4.3%
경 43
 
4.2%
리 43
 
4.2%
군 43
 
4.2%
면 33
 
3.2%
Other values (57) 369
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 614
60.0%
Space Separator 196
 
19.2%
Decimal Number 186
 
18.2%
Dash Punctuation 27
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 103
16.8%
해 53
 
8.6%
상 52
 
8.5%
도 44
 
7.2%
경 43
 
7.0%
리 43
 
7.0%
군 43
 
7.0%
면 33
 
5.4%
지 21
 
3.4%
외 19
 
3.1%
Other values (45) 160
26.1%
Decimal Number
ValueCountFrequency (%)
1 44
23.7%
2 22
11.8%
3 19
10.2%
9 16
 
8.6%
8 16
 
8.6%
4 15
 
8.1%
5 14
 
7.5%
0 14
 
7.5%
6 14
 
7.5%
7 12
 
6.5%
Space Separator
ValueCountFrequency (%)
196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 614
60.0%
Common 409
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 103
16.8%
해 53
 
8.6%
상 52
 
8.5%
도 44
 
7.2%
경 43
 
7.0%
리 43
 
7.0%
군 43
 
7.0%
면 33
 
5.4%
지 21
 
3.4%
외 19
 
3.1%
Other values (45) 160
26.1%
Common
ValueCountFrequency (%)
196
47.9%
1 44
 
10.8%
- 27
 
6.6%
2 22
 
5.4%
3 19
 
4.6%
9 16
 
3.9%
8 16
 
3.9%
4 15
 
3.7%
5 14
 
3.4%
0 14
 
3.4%
Other values (2) 26
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 614
60.0%
ASCII 409
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
196
47.9%
1 44
 
10.8%
- 27
 
6.6%
2 22
 
5.4%
3 19
 
4.6%
9 16
 
3.9%
8 16
 
3.9%
4 15
 
3.7%
5 14
 
3.4%
0 14
 
3.4%
Other values (2) 26
 
6.4%
Hangul
ValueCountFrequency (%)
남 103
16.8%
해 53
 
8.6%
상 52
 
8.5%
도 44
 
7.2%
경 43
 
7.0%
리 43
 
7.0%
군 43
 
7.0%
면 33
 
5.4%
지 21
 
3.4%
외 19
 
3.1%
Other values (45) 160
26.1%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2677.7442
Minimum32
Maximum86763
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T03:54:13.969093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile40.7
Q196
median199
Q3598
95-th percentile3742.4
Maximum86763
Range86731
Interquartile range (IQR)502

Descriptive statistics

Standard deviation13172.637
Coefficient of variation (CV)4.9193039
Kurtosis42.379769
Mean2677.7442
Median Absolute Deviation (MAD)139
Skewness6.489517
Sum115143
Variance1.7351838 × 108
MonotonicityNot monotonic
2023-12-13T03:54:14.165697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
199 3
 
7.0%
96 3
 
7.0%
66 2
 
4.7%
193 1
 
2.3%
602 1
 
2.3%
191 1
 
2.3%
150 1
 
2.3%
101 1
 
2.3%
77 1
 
2.3%
60 1
 
2.3%
Other values (28) 28
65.1%
ValueCountFrequency (%)
32 1
 
2.3%
37 1
 
2.3%
40 1
 
2.3%
47 1
 
2.3%
60 1
 
2.3%
65 1
 
2.3%
66 2
4.7%
77 1
 
2.3%
84 1
 
2.3%
96 3
7.0%
ValueCountFrequency (%)
86763 1
2.3%
4933 1
2.3%
3748 1
2.3%
3692 1
2.3%
1897 1
2.3%
1686 1
2.3%
1635 1
2.3%
1357 1
2.3%
1192 1
2.3%
1188 1
2.3%

허가일
Date

Distinct40
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
Minimum2018-11-26 00:00:00
Maximum2023-07-17 00:00:00
2023-12-13T03:54:14.373556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:14.579986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

착공처리일
Date

MISSING 

Distinct25
Distinct (%)96.2%
Missing17
Missing (%)39.5%
Memory size476.0 B
Minimum2019-05-31 00:00:00
Maximum2023-07-17 00:00:00
2023-12-13T03:54:14.767903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:14.968869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

최대지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9534884
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-13T03:54:15.130495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32.5
95-th percentile4
Maximum7
Range6
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.3964835
Coefficient of variation (CV)0.71486654
Kurtosis2.8910497
Mean1.9534884
Median Absolute Deviation (MAD)0
Skewness1.681922
Sum84
Variance1.9501661
MonotonicityNot monotonic
2023-12-13T03:54:15.292665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 24
55.8%
2 8
 
18.6%
4 5
 
11.6%
3 4
 
9.3%
5 1
 
2.3%
7 1
 
2.3%
ValueCountFrequency (%)
1 24
55.8%
2 8
 
18.6%
3 4
 
9.3%
4 5
 
11.6%
5 1
 
2.3%
7 1
 
2.3%
ValueCountFrequency (%)
7 1
 
2.3%
5 1
 
2.3%
4 5
 
11.6%
3 4
 
9.3%
2 8
 
18.6%
1 24
55.8%

최대지하층수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
0
35 
1
7 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
81.4%
1 7
 
16.3%
2 1
 
2.3%

Length

2023-12-13T03:54:15.491939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:15.654425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
81.4%
1 7
 
16.3%
2 1
 
2.3%

주용도
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size476.0 B
제2종근린생활시설
31 
숙박시설
9 
공동주택
 
3

Length

Max length9
Median length9
Mean length7.6046512
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공동주택
2nd row공동주택
3rd row제2종근린생활시설
4th row숙박시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
제2종근린생활시설 31
72.1%
숙박시설 9
 
20.9%
공동주택 3
 
7.0%

Length

2023-12-13T03:54:15.830836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:16.005980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2종근린생활시설 31
72.1%
숙박시설 9
 
20.9%
공동주택 3
 
7.0%

부속용도
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
15 
사무소
9 
일반음식점
4 
생활숙박시설
4 
다세대주택
2 
Other values (8)
9 

Length

Max length8
Median length6
Mean length4.3488372
Min length3

Unique

Unique7 ?
Unique (%)16.3%

Sample

1st row다세대주택
2nd row연립주택
3rd row휴게음식점
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 15
34.9%
사무소 9
20.9%
일반음식점 4
 
9.3%
생활숙박시설 4
 
9.3%
다세대주택 2
 
4.7%
제조업소 2
 
4.7%
연립주택 1
 
2.3%
휴게음식점 1
 
2.3%
생활형 숙박시설 1
 
2.3%
관광숙박시설 1
 
2.3%
Other values (3) 3
 
7.0%

Length

2023-12-13T03:54:16.239349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 15
34.1%
사무소 9
20.5%
일반음식점 4
 
9.1%
생활숙박시설 4
 
9.1%
다세대주택 2
 
4.5%
제조업소 2
 
4.5%
연립주택 1
 
2.3%
휴게음식점 1
 
2.3%
생활형 1
 
2.3%
숙박시설 1
 
2.3%
Other values (4) 4
 
9.1%

세대수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
40 
16
 
1
28
 
1
15
 
1

Length

Max length4
Median length4
Mean length3.8604651
Min length2

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row16
2nd row28
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 40
93.0%
16 1
 
2.3%
28 1
 
2.3%
15 1
 
2.3%

Length

2023-12-13T03:54:16.453307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:16.666142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
93.0%
16 1
 
2.3%
28 1
 
2.3%
15 1
 
2.3%

호수
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
42 
34
 
1

Length

Max length4
Median length4
Mean length3.9534884
Min length2

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 42
97.7%
34 1
 
2.3%

Length

2023-12-13T03:54:16.878930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:17.094628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 42
97.7%
34 1
 
2.3%

가구수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
<NA>
36 
1
4 
8
 
1
4
 
1
3
 
1

Length

Max length4
Median length4
Mean length3.5116279
Min length1

Unique

Unique3 ?
Unique (%)7.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 36
83.7%
1 4
 
9.3%
8 1
 
2.3%
4 1
 
2.3%
3 1
 
2.3%

Length

2023-12-13T03:54:17.286372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:17.486796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 36
83.7%
1 4
 
9.3%
8 1
 
2.3%
4 1
 
2.3%
3 1
 
2.3%

시공자사무소명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing35
Missing (%)81.4%
Memory size476.0 B
2023-12-13T03:54:17.705096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.75
Min length5

Characters and Unicode

Total characters70
Distinct characters35
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

Unique8 ?
Unique (%)100.0%

Sample

1st row영우종합건설(주)
2nd row주식회사 라안종합건설
3rd row(주)이누테크
4th row유담건설주식회사
5th row(주)휘성종합건설
ValueCountFrequency (%)
주식회사 2
20.0%
영우종합건설(주 1
10.0%
라안종합건설 1
10.0%
주)이누테크 1
10.0%
유담건설주식회사 1
10.0%
주)휘성종합건설 1
10.0%
씨지종합건설(주 1
10.0%
소노인터내셔널 1
10.0%
이수하우징 1
10.0%
2023-12-13T03:54:18.245914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 7
 
10.0%
건 5
 
7.1%
설 5
 
7.1%
종 4
 
5.7%
합 4
 
5.7%
( 4
 
5.7%
) 4
 
5.7%
식 3
 
4.3%
사 3
 
4.3%
회 3
 
4.3%
Other values (25) 28
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
85.7%
Open Punctuation 4
 
5.7%
Close Punctuation 4
 
5.7%
Space Separator 2
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 7
 
11.7%
건 5
 
8.3%
설 5
 
8.3%
종 4
 
6.7%
합 4
 
6.7%
식 3
 
5.0%
사 3
 
5.0%
회 3
 
5.0%
이 2
 
3.3%
우 2
 
3.3%
Other values (22) 22
36.7%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
85.7%
Common 10
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 7
 
11.7%
건 5
 
8.3%
설 5
 
8.3%
종 4
 
6.7%
합 4
 
6.7%
식 3
 
5.0%
사 3
 
5.0%
회 3
 
5.0%
이 2
 
3.3%
우 2
 
3.3%
Other values (22) 22
36.7%
Common
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
85.7%
ASCII 10
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 7
 
11.7%
건 5
 
8.3%
설 5
 
8.3%
종 4
 
6.7%
합 4
 
6.7%
식 3
 
5.0%
사 3
 
5.0%
회 3
 
5.0%
이 2
 
3.3%
우 2
 
3.3%
Other values (22) 22
36.7%
ASCII
ValueCountFrequency (%)
( 4
40.0%
) 4
40.0%
2
20.0%

Interactions

2023-12-13T03:54:10.710046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:10.448285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:11.000996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:10.571003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:54:18.488874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대지위치연면적허가일착공처리일최대지상층수최대지하층수주용도부속용도세대수가구수시공자사무소명
대지위치1.0001.0001.0000.9941.0001.0001.0001.0001.0001.0001.000
연면적1.0001.0001.0001.0001.0001.0000.1291.000NaNNaN1.000
허가일1.0001.0001.0001.0000.0000.9011.0000.9511.0001.0001.000
착공처리일0.9941.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
최대지상층수1.0001.0000.0001.0001.0000.9960.9460.9471.0000.9401.000
최대지하층수1.0001.0000.9011.0000.9961.0000.8601.0001.0001.0001.000
주용도1.0000.1291.0001.0000.9460.8601.0001.000NaN1.0001.000
부속용도1.0001.0000.9511.0000.9471.0001.0001.0001.0000.9131.000
세대수1.000NaN1.0000.0001.0001.000NaN1.0001.000NaN0.000
가구수1.000NaN1.0001.0000.9401.0001.0000.913NaN1.0000.000
시공자사무소명1.0001.0001.0001.0001.0001.0001.0001.0000.0000.0001.000
2023-12-13T03:54:18.735571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
호수세대수최대지하층수가구수주용도부속용도
호수1.000NaNNaNNaNNaNNaN
세대수NaN1.0001.000NaN1.0001.000
최대지하층수NaN1.0001.0000.7750.5480.800
가구수NaNNaN0.7751.0000.7750.000
주용도NaN1.0000.5480.7751.0000.800
부속용도NaN1.0000.8000.0000.8001.000
2023-12-13T03:54:18.952803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적최대지상층수최대지하층수주용도부속용도세대수호수가구수
연면적1.0000.7320.9880.2080.7841.000NaN1.000
최대지상층수0.7321.0000.8860.6900.5691.000NaN0.612
최대지하층수0.9880.8861.0000.5480.8001.000NaN0.775
주용도0.2080.6900.5481.0000.8001.000NaN0.775
부속용도0.7840.5690.8000.8001.0001.000NaN0.000
세대수1.0001.0001.0001.0001.0001.0000.0000.000
호수NaNNaNNaNNaNNaN0.0001.0000.000
가구수1.0000.6120.7750.7750.0000.0000.0001.000

Missing values

2023-12-13T03:54:11.223868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:54:11.545245image/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.
2023-12-13T03:54:11.799235image/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

건축구분대지위치연면적허가일착공처리일최대지상층수최대지하층수주용도부속용도세대수호수가구수시공자사무소명
0신축경상남도 남해군 남해읍 북변리 461-4 외1필지13572023-03-272023-04-1250공동주택다세대주택16<NA><NA>영우종합건설(주)
1신축경상남도 남해군 남해읍 서변리 37511922023-03-27<NA>41공동주택연립주택28<NA><NA><NA>
2신축경상남도 남해군 상주면 양아리 237 외10필지3222022-12-272023-07-0710제2종근린생활시설휴게음식점<NA><NA><NA>주식회사 라안종합건설
3신축경상남도 남해군 남면 선구리 674 외1필지16352022-11-30<NA>31숙박시설<NA><NA><NA><NA><NA>
4신축경상남도 남해군 미조면 송정리 8801232022-10-18<NA>10제2종근린생활시설<NA><NA><NA><NA><NA>
5신축경상남도 남해군 상주면 상주리 9585942022-10-062022-12-2120제2종근린생활시설일반음식점<NA><NA>8(주)이누테크
6신축경상남도 남해군 창선면 대벽리 산 1-6116862022-01-26<NA>41숙박시설생활숙박시설<NA><NA><NA><NA>
7신축경상남도 남해군 창선면 대벽리 178-4349332022-01-18<NA>41숙박시설생활숙박시설<NA><NA>4<NA>
8신축경상남도 남해군 창선면 동대리 476-6 외1필지5002022-01-052023-07-1730제2종근린생활시설<NA><NA><NA>1유담건설주식회사
9신축경상남도 남해군 남해읍 북변리 1-16 외1필지2292021-10-282022-10-2010제2종근린생활시설제조업소<NA><NA><NA><NA>
건축구분대지위치연면적허가일착공처리일최대지상층수최대지하층수주용도부속용도세대수호수가구수시공자사무소명
33신축경상남도 남해군 삼동면 지족리 343-1662021-04-20<NA>10제2종근린생활시설사무소<NA><NA><NA><NA>
34신축경상남도 남해군 고현면 대곡리 4652021-03-262021-04-1410제2종근린생활시설사무소<NA><NA><NA><NA>
35신축경상남도 남해군 이동면 다정리 7921992020-11-292022-08-0820제2종근린생활시설<NA><NA><NA>1<NA>
36신축경상남도 남해군 남면 당항리 2057-8402020-11-242020-11-3010제2종근린생활시설<NA><NA><NA><NA><NA>
37신축경상남도 남해군 남해읍 입현리 959-1 외1필지962020-10-222021-05-2710제2종근린생활시설사무소<NA><NA><NA><NA>
38신축경상남도 남해군 남해읍 입현리 959-2962020-10-222021-05-2710제2종근린생활시설사무소<NA><NA><NA><NA>
39신축경상남도 남해군 남해읍 입현리 959-2962020-10-222021-05-2610제2종근린생활시설사무소<NA><NA><NA><NA>
40신축경상남도 남해군 이동면 용소리 1281-52322020-04-142020-04-1710제2종근린생활시설<NA><NA><NA><NA><NA>
41신축경상남도 남해군 남해읍 북변리 89-5 외1필지372019-05-222019-05-3120제2종근린생활시설<NA><NA><NA><NA><NA>
42신축경상남도 남해군 창선면 대벽리 산 29-64492019-05-122019-11-1110제2종근린생활시설단독주택<NA><NA>3<NA>