Overview

Dataset statistics

Number of variables9
Number of observations3646
Missing cells3616
Missing cells (%)11.0%
Duplicate rows9
Duplicate rows (%)0.2%
Total size in memory267.2 KiB
Average record size in memory75.0 B

Variable types

Categorical2
Text3
Numeric3
DateTime1

Dataset

Description경상남도 진주시내 건축허가 현황 자료(건축인허가 대지 위치, 연면적 m2, 허가일 등의 정보)를 제공하고 있습니다. (제공기간: 2015.1.1. ~ 2023.8.15.)
URLhttps://www.data.go.kr/data/15118770/fileData.do

Alerts

건축구분 has constant value ""Constant
Dataset has 9 (0.2%) duplicate rowsDuplicates
연면적(제곱미티) is highly overall correlated with 최대지상층수High correlation
최대지상층수 is highly overall correlated with 연면적(제곱미티)High correlation
주용도 is highly imbalanced (53.1%)Imbalance
부속용도 has 1079 (29.6%) missing valuesMissing
시공자사무소명 has 2537 (69.6%) missing valuesMissing
연면적(제곱미티) is highly skewed (γ1 = 25.2760167)Skewed
최대지하층수 has 3408 (93.5%) zerosZeros

Reproduction

Analysis started2023-12-12 21:35:51.966456
Analysis finished2023-12-12 21:35:54.105064
Duration2.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
신축
3646 

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 3646
100.0%

Length

2023-12-13T06:35:54.167968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:35:54.259366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 3646
100.0%

대지위치
Text

Distinct3611
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
2023-12-13T06:35:54.584505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length36
Mean length20.228744
Min length14

Characters and Unicode

Total characters73754
Distinct characters146
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

Unique3591 ?
Unique (%)98.5%

Sample

1st row경상남도 진주시 충무공동 47-1
2nd row경상남도 진주시 진성면 상촌리 621 외5필지
3rd row경상남도 진주시 충무공동 252-12
4th row경상남도 진주시 충무공동 135-35
5th row경상남도 진주시 정촌면 예하리 1395-9
ValueCountFrequency (%)
경상남도 3646
22.6%
진주시 3646
22.6%
충무공동 656
 
4.1%
외1필지 340
 
2.1%
초전동 305
 
1.9%
평거동 251
 
1.6%
상대동 220
 
1.4%
금산면 201
 
1.2%
하대동 199
 
1.2%
정촌면 183
 
1.1%
Other values (3552) 6515
40.3%
2023-12-13T06:35:55.089001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12518
17.0%
상 4117
 
5.6%
1 3788
 
5.1%
진 3697
 
5.0%
경 3695
 
5.0%
주 3686
 
5.0%
남 3682
 
5.0%
시 3649
 
4.9%
도 3647
 
4.9%
- 3132
 
4.2%
Other values (136) 28143
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41883
56.8%
Decimal Number 16219
 
22.0%
Space Separator 12518
 
17.0%
Dash Punctuation 3132
 
4.2%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 4117
 
9.8%
진 3697
 
8.8%
경 3695
 
8.8%
주 3686
 
8.8%
남 3682
 
8.8%
시 3649
 
8.7%
도 3647
 
8.7%
동 2783
 
6.6%
리 962
 
2.3%
면 842
 
2.0%
Other values (122) 11123
26.6%
Decimal Number
ValueCountFrequency (%)
1 3788
23.4%
2 2155
13.3%
3 1815
11.2%
4 1509
 
9.3%
5 1268
 
7.8%
7 1234
 
7.6%
6 1163
 
7.2%
0 1121
 
6.9%
9 1091
 
6.7%
8 1075
 
6.6%
Space Separator
ValueCountFrequency (%)
12518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3132
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41883
56.8%
Common 31871
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 4117
 
9.8%
진 3697
 
8.8%
경 3695
 
8.8%
주 3686
 
8.8%
남 3682
 
8.8%
시 3649
 
8.7%
도 3647
 
8.7%
동 2783
 
6.6%
리 962
 
2.3%
면 842
 
2.0%
Other values (122) 11123
26.6%
Common
ValueCountFrequency (%)
12518
39.3%
1 3788
 
11.9%
- 3132
 
9.8%
2 2155
 
6.8%
3 1815
 
5.7%
4 1509
 
4.7%
5 1268
 
4.0%
7 1234
 
3.9%
6 1163
 
3.6%
0 1121
 
3.5%
Other values (4) 2168
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41883
56.8%
ASCII 31871
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12518
39.3%
1 3788
 
11.9%
- 3132
 
9.8%
2 2155
 
6.8%
3 1815
 
5.7%
4 1509
 
4.7%
5 1268
 
4.0%
7 1234
 
3.9%
6 1163
 
3.6%
0 1121
 
3.5%
Other values (4) 2168
 
6.8%
Hangul
ValueCountFrequency (%)
상 4117
 
9.8%
진 3697
 
8.8%
경 3695
 
8.8%
주 3686
 
8.8%
남 3682
 
8.8%
시 3649
 
8.7%
도 3647
 
8.7%
동 2783
 
6.6%
리 962
 
2.3%
면 842
 
2.0%
Other values (122) 11123
26.6%

연면적(제곱미티)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct3420
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean943.61598
Minimum67.57
Maximum191739.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.2 KiB
2023-12-13T06:35:55.256110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum67.57
5-th percentile139.395
Q1215.18
median372.27
Q3580.835
95-th percentile2830.9412
Maximum191739.55
Range191671.98
Interquartile range (IQR)365.655

Descriptive statistics

Standard deviation4775.4247
Coefficient of variation (CV)5.0607713
Kurtosis834.86503
Mean943.61598
Median Absolute Deviation (MAD)171.155
Skewness25.276017
Sum3440423.9
Variance22804681
MonotonicityNot monotonic
2023-12-13T06:35:55.431342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 9
 
0.2%
136.68 8
 
0.2%
196.0 5
 
0.1%
149.68 5
 
0.1%
199.56 4
 
0.1%
490.0 4
 
0.1%
396.0 3
 
0.1%
186.0 3
 
0.1%
199.61 3
 
0.1%
124.8 3
 
0.1%
Other values (3410) 3599
98.7%
ValueCountFrequency (%)
67.57 1
 
< 0.1%
104.61 1
 
< 0.1%
105.33 1
 
< 0.1%
105.8 1
 
< 0.1%
105.84 1
 
< 0.1%
106.5 1
 
< 0.1%
107.82 2
0.1%
107.83 3
0.1%
108.54 1
 
< 0.1%
109.11 1
 
< 0.1%
ValueCountFrequency (%)
191739.55 1
< 0.1%
99184.24 1
< 0.1%
98634.62 1
< 0.1%
85609.26 1
< 0.1%
60520.8878 1
< 0.1%
43918.6252 1
< 0.1%
42965.28 1
< 0.1%
36401.3453 1
< 0.1%
30727.65 1
< 0.1%
29553.29 1
< 0.1%

허가일
Date

Distinct1534
Distinct (%)42.1%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
Minimum2015-01-02 00:00:00
Maximum2023-07-31 00:00:00
2023-12-13T06:35:55.582819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:55.729664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8565551
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.2 KiB
2023-12-13T06:35:55.856294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum39
Range38
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7605631
Coefficient of variation (CV)0.61632388
Kurtosis88.897585
Mean2.8565551
Median Absolute Deviation (MAD)1
Skewness6.2342223
Sum10415
Variance3.0995825
MonotonicityNot monotonic
2023-12-13T06:35:56.000420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2 1311
36.0%
4 860
23.6%
3 698
19.1%
1 507
 
13.9%
5 168
 
4.6%
6 46
 
1.3%
7 16
 
0.4%
9 11
 
0.3%
10 5
 
0.1%
8 4
 
0.1%
Other values (11) 20
 
0.5%
ValueCountFrequency (%)
1 507
 
13.9%
2 1311
36.0%
3 698
19.1%
4 860
23.6%
5 168
 
4.6%
6 46
 
1.3%
7 16
 
0.4%
8 4
 
0.1%
9 11
 
0.3%
10 5
 
0.1%
ValueCountFrequency (%)
39 1
< 0.1%
29 1
< 0.1%
27 2
0.1%
19 1
< 0.1%
18 1
< 0.1%
16 2
0.1%
15 2
0.1%
14 2
0.1%
13 2
0.1%
12 2
0.1%

최대지하층수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.094898519
Minimum0
Maximum6
Zeros3408
Zeros (%)93.5%
Negative0
Negative (%)0.0%
Memory size32.2 KiB
2023-12-13T06:35:56.123730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.44787721
Coefficient of variation (CV)4.7195385
Kurtosis68.289251
Mean0.094898519
Median Absolute Deviation (MAD)0
Skewness7.2862169
Sum346
Variance0.200594
MonotonicityNot monotonic
2023-12-13T06:35:56.250405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 3408
93.5%
1 186
 
5.1%
2 25
 
0.7%
3 10
 
0.3%
4 9
 
0.2%
5 4
 
0.1%
6 4
 
0.1%
ValueCountFrequency (%)
0 3408
93.5%
1 186
 
5.1%
2 25
 
0.7%
3 10
 
0.3%
4 9
 
0.2%
5 4
 
0.1%
6 4
 
0.1%
ValueCountFrequency (%)
6 4
 
0.1%
5 4
 
0.1%
4 9
 
0.2%
3 10
 
0.3%
2 25
 
0.7%
1 186
 
5.1%
0 3408
93.5%

주용도
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size28.6 KiB
단독주택
2062 
제2종근린생활시설
587 
제1종근린생활시설
457 
공장
 
120
창고시설
 
104
Other values (20)
316 

Length

Max length10
Median length4
Mean length5.5293472
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row단독주택
2nd row공장
3rd row단독주택
4th row단독주택
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 2062
56.6%
제2종근린생활시설 587
 
16.1%
제1종근린생활시설 457
 
12.5%
공장 120
 
3.3%
창고시설 104
 
2.9%
업무시설 60
 
1.6%
동물및식물관련시설 58
 
1.6%
자동차관련시설 50
 
1.4%
노유자시설 27
 
0.7%
교육연구시설 20
 
0.5%
Other values (15) 101
 
2.8%

Length

2023-12-13T06:35:56.418371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 2062
56.6%
제2종근린생활시설 587
 
16.1%
제1종근린생활시설 457
 
12.5%
공장 120
 
3.3%
창고시설 104
 
2.9%
업무시설 60
 
1.6%
동물및식물관련시설 58
 
1.6%
자동차관련시설 50
 
1.4%
노유자시설 27
 
0.7%
교육연구시설 20
 
0.5%
Other values (15) 101
 
2.8%

부속용도
Text

MISSING 

Distinct738
Distinct (%)28.7%
Missing1079
Missing (%)29.6%
Memory size28.6 KiB
2023-12-13T06:35:56.710308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length7.5664199
Min length1

Characters and Unicode

Total characters19423
Distinct characters223
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique564 ?
Unique (%)22.0%

Sample

1st row물품제조공장/기숙사및사무실
2nd row소매점
3rd row일반음식점, 휴게음식점
4th row단독주택
5th row제2종근린생활시설(휴게음식점,사무소)/제1종근린생활시설(소매점)
ValueCountFrequency (%)
다가구주택 677
20.4%
단독주택 340
 
10.3%
및 261
 
7.9%
소매점 202
 
6.1%
다가구 101
 
3.0%
사무소 87
 
2.6%
근린생활시설 83
 
2.5%
다중주택 76
 
2.3%
일반음식점 66
 
2.0%
다중생활시설 64
 
1.9%
Other values (566) 1355
40.9%
2023-12-13T06:35:57.239767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1381
 
7.1%
택 1347
 
6.9%
다 1081
 
5.6%
구 951
 
4.9%
가 948
 
4.9%
751
 
3.9%
시 702
 
3.6%
생 685
 
3.5%
설 678
 
3.5%
점 617
 
3.2%
Other values (213) 10282
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16769
86.3%
Space Separator 751
 
3.9%
Other Punctuation 582
 
3.0%
Decimal Number 484
 
2.5%
Open Punctuation 409
 
2.1%
Close Punctuation 406
 
2.1%
Dash Punctuation 22
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1381
 
8.2%
택 1347
 
8.0%
다 1081
 
6.4%
구 951
 
5.7%
가 948
 
5.7%
시 702
 
4.2%
생 685
 
4.1%
설 678
 
4.0%
점 617
 
3.7%
근 595
 
3.5%
Other values (196) 7784
46.4%
Decimal Number
ValueCountFrequency (%)
2 253
52.3%
1 220
45.5%
8 3
 
0.6%
9 3
 
0.6%
5 2
 
0.4%
4 2
 
0.4%
6 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 438
75.3%
/ 123
 
21.1%
. 20
 
3.4%
: 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 408
99.8%
[ 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 405
99.8%
] 1
 
0.2%
Space Separator
ValueCountFrequency (%)
751
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16769
86.3%
Common 2654
 
13.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1381
 
8.2%
택 1347
 
8.0%
다 1081
 
6.4%
구 951
 
5.7%
가 948
 
5.7%
시 702
 
4.2%
생 685
 
4.1%
설 678
 
4.0%
점 617
 
3.7%
근 595
 
3.5%
Other values (196) 7784
46.4%
Common
ValueCountFrequency (%)
751
28.3%
, 438
16.5%
( 408
15.4%
) 405
15.3%
2 253
 
9.5%
1 220
 
8.3%
/ 123
 
4.6%
- 22
 
0.8%
. 20
 
0.8%
8 3
 
0.1%
Other values (7) 11
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16769
86.3%
ASCII 2654
 
13.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1381
 
8.2%
택 1347
 
8.0%
다 1081
 
6.4%
구 951
 
5.7%
가 948
 
5.7%
시 702
 
4.2%
생 685
 
4.1%
설 678
 
4.0%
점 617
 
3.7%
근 595
 
3.5%
Other values (196) 7784
46.4%
ASCII
ValueCountFrequency (%)
751
28.3%
, 438
16.5%
( 408
15.4%
) 405
15.3%
2 253
 
9.5%
1 220
 
8.3%
/ 123
 
4.6%
- 22
 
0.8%
. 20
 
0.8%
8 3
 
0.1%
Other values (7) 11
 
0.4%

시공자사무소명
Text

MISSING 

Distinct514
Distinct (%)46.3%
Missing2537
Missing (%)69.6%
Memory size28.6 KiB
2023-12-13T06:35:57.508749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length8.5662759
Min length5

Characters and Unicode

Total characters9500
Distinct characters212
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

Unique315 ?
Unique (%)28.4%

Sample

1st row태건건설(주)
2nd row주식회사보림종합건설
3rd row하나로산업
4th row(주)명린종합건설
5th row금아종합건설주식회사
ValueCountFrequency (%)
주식회사 75
 
6.3%
주)우석종합건설 22
 
1.8%
주)주안종합건설 20
 
1.7%
주)명린종합건설 18
 
1.5%
제이에스종합건설(주 13
 
1.1%
삼성종합건설(주 13
 
1.1%
주)윤환종합건설 13
 
1.1%
가양종합건설(주 13
 
1.1%
신율종합건설(주 12
 
1.0%
주)천일종합건설 12
 
1.0%
Other values (506) 981
82.3%
2023-12-13T06:35:58.259917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1123
11.8%
건 995
 
10.5%
설 956
 
10.1%
( 900
 
9.5%
) 900
 
9.5%
종 634
 
6.7%
합 626
 
6.6%
사 199
 
2.1%
회 193
 
2.0%
식 191
 
2.0%
Other values (202) 2783
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7617
80.2%
Open Punctuation 900
 
9.5%
Close Punctuation 900
 
9.5%
Space Separator 83
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1123
14.7%
건 995
 
13.1%
설 956
 
12.6%
종 634
 
8.3%
합 626
 
8.2%
사 199
 
2.6%
회 193
 
2.5%
식 191
 
2.5%
이 121
 
1.6%
우 81
 
1.1%
Other values (199) 2498
32.8%
Open Punctuation
ValueCountFrequency (%)
( 900
100.0%
Close Punctuation
ValueCountFrequency (%)
) 900
100.0%
Space Separator
ValueCountFrequency (%)
83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7617
80.2%
Common 1883
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1123
14.7%
건 995
 
13.1%
설 956
 
12.6%
종 634
 
8.3%
합 626
 
8.2%
사 199
 
2.6%
회 193
 
2.5%
식 191
 
2.5%
이 121
 
1.6%
우 81
 
1.1%
Other values (199) 2498
32.8%
Common
ValueCountFrequency (%)
( 900
47.8%
) 900
47.8%
83
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7617
80.2%
ASCII 1883
 
19.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1123
14.7%
건 995
 
13.1%
설 956
 
12.6%
종 634
 
8.3%
합 626
 
8.2%
사 199
 
2.6%
회 193
 
2.5%
식 191
 
2.5%
이 121
 
1.6%
우 81
 
1.1%
Other values (199) 2498
32.8%
ASCII
ValueCountFrequency (%)
( 900
47.8%
) 900
47.8%
83
 
4.4%

Interactions

2023-12-13T06:35:53.385148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:52.637455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:53.010613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:53.537700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:52.771126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:53.158923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:53.657382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:52.896010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:35:53.279296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:35:58.361534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(제곱미티)최대지상층수최대지하층수주용도
연면적(제곱미티)1.0000.8660.7930.551
최대지상층수0.8661.0000.7360.581
최대지하층수0.7930.7361.0000.526
주용도0.5510.5810.5261.000
2023-12-13T06:35:58.486590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적(제곱미티)최대지상층수최대지하층수주용도
연면적(제곱미티)1.0000.5100.2880.271
최대지상층수0.5101.0000.2070.273
최대지하층수0.2880.2071.0000.255
주용도0.2710.2730.2551.000

Missing values

2023-12-13T06:35:53.800759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:35:53.936641image/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.
2023-12-13T06:35:54.048171image/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

건축구분대지위치연면적(제곱미티)허가일최대지상층수최대지하층수주용도부속용도시공자사무소명
0신축경상남도 진주시 충무공동 47-1197.422023-07-3120단독주택<NA><NA>
1신축경상남도 진주시 진성면 상촌리 621 외5필지4520.02023-07-3141공장물품제조공장/기숙사및사무실<NA>
2신축경상남도 진주시 충무공동 252-12199.762023-07-3120단독주택<NA><NA>
3신축경상남도 진주시 충무공동 135-35199.562023-07-2720단독주택<NA><NA>
4신축경상남도 진주시 정촌면 예하리 1395-9492.22023-07-2610제1종근린생활시설소매점<NA>
5신축경상남도 진주시 초전동 694 외11필지923.952023-07-2611제2종근린생활시설일반음식점, 휴게음식점<NA>
6신축경상남도 진주시 문산읍 소문리 128-60135.142023-07-2520단독주택<NA><NA>
7신축경상남도 진주시 평거동 164-18185.362023-07-2530단독주택단독주택<NA>
8신축경상남도 진주시 하대동 674-1 외6필지1050.02023-07-2110제2종근린생활시설제2종근린생활시설(휴게음식점,사무소)/제1종근린생활시설(소매점)태건건설(주)
9신축경상남도 진주시 장재동 876-22197.982023-07-1910단독주택단독주택<NA>
건축구분대지위치연면적(제곱미티)허가일최대지상층수최대지하층수주용도부속용도시공자사무소명
3636신축경상남도 진주시 신안동 883-44550.722015-01-1361업무시설오피스텔서봉종합건설주
3637신축경상남도 진주시 충무공동 504-61922.772015-01-1240업무시설근린생활시설(주)포스건설
3638신축경상남도 진주시 가좌동 1045-1329.62015-01-0810제2종근린생활시설제조업소, 창고<NA>
3639신축경상남도 진주시 사봉면 사곡리 1820-31827.112015-01-0750공장<NA>(주)동방종합건설
3640신축경상남도 진주시 금산면 송백리 520-2295.812015-01-0710창고시설창고<NA>
3641신축경상남도 진주시 사봉면 사곡리 1806-4 외1필지1578.712015-01-0720공장<NA>수광종합건설(주)대표 강기생
3642신축경상남도 진주시 집현면 봉강리 299-9284.492015-01-0520제2종근린생활시설(일반음식점)/제1종근린생활시설(소매점)/단독주택<NA>
3643신축경상남도 진주시 충무공동 3599184.242015-01-0574판매시설문화및집회시설롯데건설(주)
3644신축경상남도 진주시 인사동 192-12243.742015-01-0220단독주택다가구주택, 제2종근,생(제조업소)<NA>
3645신축경상남도 진주시 충무공동 289-67117.852015-01-0250자동차관련시설주차장(주)갑을건설

Duplicate rows

Most frequently occurring

건축구분대지위치연면적(제곱미티)허가일최대지상층수최대지하층수주용도부속용도시공자사무소명# duplicates
2신축경상남도 진주시 금산면 용아리 산 90149.682018-07-0620단독주택<NA><NA>5
6신축경상남도 진주시 평거동 340124.82021-08-0210제2종근린생활시설(일반음식점)<NA>3
7신축경상남도 진주시 평거동 473-4147.532021-07-1930단독주택<NA><NA>3
0신축경상남도 진주시 금산면 용아리 415-3 외2필지136.682019-02-2720단독주택<NA><NA>2
1신축경상남도 진주시 금산면 용아리 434-1136.682019-02-2720단독주택<NA><NA>2
3신축경상남도 진주시 장재동 905-3171.442018-09-2120단독주택<NA><NA>2
4신축경상남도 진주시 지수면 압사리 99-1 외1필지476.02015-07-1610제2종근린생활시설제조업소<NA>2
5신축경상남도 진주시 초전동 910-4659.612022-10-0740단독주택다가구주택디케이(주)2
8신축경상남도 진주시 하대동 592-3505.742016-03-2940단독주택<NA><NA>2