Overview

Dataset statistics

Number of variables9
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory78.3 B

Variable types

Numeric3
Text3
DateTime1
Categorical2

Dataset

Description부산광역시연제구_공개공지현황_20230420
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15030143

Alerts

연면적 is highly overall correlated with 공개공지면적 High correlation
공개공지면적 is highly overall correlated with 연면적 and 1 other fieldsHigh correlation
용도 is highly overall correlated with 공개공지면적 High correlation
연번 has unique valuesUnique
건축물명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번 has unique valuesUnique
공개공지면적 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:05:33.231867
Analysis finished2023-12-10 16:05:35.292212
Duration2.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29
Minimum1
Maximum57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-11T01:05:35.726173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.8
Q115
median29
Q343
95-th percentile54.2
Maximum57
Range56
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.598193
Coefficient of variation (CV)0.57235147
Kurtosis-1.2
Mean29
Median Absolute Deviation (MAD)14
Skewness0
Sum1653
Variance275.5
MonotonicityStrictly increasing
2023-12-11T01:05:36.028093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
44 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
39 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
57 1
1.8%
56 1
1.8%
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%

건축물명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T01:05:36.373982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.1052632
Min length3

Characters and Unicode

Total characters405
Distinct characters149
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row아이비젼사옥
2nd row하이트맥주 사옥
3rd rowKT&G사옥
4th row㈜부원 사옥
5th row협성법조빌딩
ValueCountFrequency (%)
시청역 3
 
3.7%
오피스텔 3
 
3.7%
연산역 2
 
2.5%
연산동 2
 
2.5%
사옥 2
 
2.5%
홈플러스 2
 
2.5%
연산점 2
 
2.5%
명품블루파크 1
 
1.2%
일호센텀누리 1
 
1.2%
엘리시움 1
 
1.2%
Other values (62) 62
76.5%
2023-12-11T01:05:36.912500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
6.2%
스 23
 
5.7%
이 13
 
3.2%
산 12
 
3.0%
시 12
 
3.0%
연 10
 
2.5%
티 7
 
1.7%
트 7
 
1.7%
역 7
 
1.7%
마 7
 
1.7%
Other values (139) 282
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
86.7%
Space Separator 25
 
6.2%
Uppercase Letter 19
 
4.7%
Decimal Number 3
 
0.7%
Dash Punctuation 2
 
0.5%
Lowercase Letter 1
 
0.2%
Other Symbol 1
 
0.2%
Other Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 23
 
6.6%
이 13
 
3.7%
산 12
 
3.4%
시 12
 
3.4%
연 10
 
2.8%
티 7
 
2.0%
트 7
 
2.0%
역 7
 
2.0%
마 7
 
2.0%
타 7
 
2.0%
Other values (121) 246
70.1%
Uppercase Letter
ValueCountFrequency (%)
W 4
21.1%
S 3
15.8%
K 3
15.8%
E 2
10.5%
V 2
10.5%
I 2
10.5%
C 1
 
5.3%
G 1
 
5.3%
T 1
 
5.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 352
86.9%
Common 33
 
8.1%
Latin 20
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 23
 
6.5%
이 13
 
3.7%
산 12
 
3.4%
시 12
 
3.4%
연 10
 
2.8%
티 7
 
2.0%
트 7
 
2.0%
역 7
 
2.0%
마 7
 
2.0%
타 7
 
2.0%
Other values (122) 247
70.2%
Latin
ValueCountFrequency (%)
W 4
20.0%
S 3
15.0%
K 3
15.0%
E 2
10.0%
V 2
10.0%
I 2
10.0%
C 1
 
5.0%
e 1
 
5.0%
G 1
 
5.0%
T 1
 
5.0%
Common
ValueCountFrequency (%)
25
75.8%
2 2
 
6.1%
- 2
 
6.1%
3 1
 
3.0%
& 1
 
3.0%
) 1
 
3.0%
( 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
86.7%
ASCII 53
 
13.1%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
47.2%
W 4
 
7.5%
S 3
 
5.7%
K 3
 
5.7%
2 2
 
3.8%
E 2
 
3.8%
- 2
 
3.8%
V 2
 
3.8%
I 2
 
3.8%
C 1
 
1.9%
Other values (7) 7
 
13.2%
Hangul
ValueCountFrequency (%)
스 23
 
6.6%
이 13
 
3.7%
산 12
 
3.4%
시 12
 
3.4%
연 10
 
2.8%
티 7
 
2.0%
트 7
 
2.0%
역 7
 
2.0%
마 7
 
2.0%
타 7
 
2.0%
Other values (121) 246
70.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T01:05:37.265804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.8421053
Min length5

Characters and Unicode

Total characters504
Distinct characters53
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

Unique57 ?
Unique (%)100.0%

Sample

1st row거제대로 295
2nd row반송로 69
3rd row월드컵대로 83
4th row중앙대로 1117
5th row법원남로 16
ValueCountFrequency (%)
중앙대로 5
 
4.3%
법원로 5
 
4.3%
반송로 4
 
3.5%
과정로 3
 
2.6%
20 3
 
2.6%
월드컵대로 3
 
2.6%
거제천로230번길 3
 
2.6%
34 3
 
2.6%
12 3
 
2.6%
7 2
 
1.7%
Other values (72) 81
70.4%
2023-12-11T01:05:37.749619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
11.7%
1 56
 
11.1%
로 56
 
11.1%
2 29
 
5.8%
길 22
 
4.4%
번 21
 
4.2%
0 21
 
4.2%
4 19
 
3.8%
3 18
 
3.6%
대 17
 
3.4%
Other values (43) 186
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
50.0%
Decimal Number 192
38.1%
Space Separator 59
 
11.7%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 56
22.2%
길 22
 
8.7%
번 21
 
8.3%
대 17
 
6.7%
제 12
 
4.8%
중 11
 
4.4%
앙 11
 
4.4%
천 9
 
3.6%
원 9
 
3.6%
거 9
 
3.6%
Other values (31) 75
29.8%
Decimal Number
ValueCountFrequency (%)
1 56
29.2%
2 29
15.1%
0 21
 
10.9%
4 19
 
9.9%
3 18
 
9.4%
5 13
 
6.8%
6 11
 
5.7%
8 10
 
5.2%
7 9
 
4.7%
9 6
 
3.1%
Space Separator
ValueCountFrequency (%)
59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 252
50.0%
Hangul 252
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 56
22.2%
길 22
 
8.7%
번 21
 
8.3%
대 17
 
6.7%
제 12
 
4.8%
중 11
 
4.4%
앙 11
 
4.4%
천 9
 
3.6%
원 9
 
3.6%
거 9
 
3.6%
Other values (31) 75
29.8%
Common
ValueCountFrequency (%)
59
23.4%
1 56
22.2%
2 29
11.5%
0 21
 
8.3%
4 19
 
7.5%
3 18
 
7.1%
5 13
 
5.2%
6 11
 
4.4%
8 10
 
4.0%
7 9
 
3.6%
Other values (2) 7
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
50.0%
Hangul 252
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
23.4%
1 56
22.2%
2 29
11.5%
0 21
 
8.3%
4 19
 
7.5%
3 18
 
7.1%
5 13
 
5.2%
6 11
 
4.4%
8 10
 
4.0%
7 9
 
3.6%
Other values (2) 7
 
2.8%
Hangul
ValueCountFrequency (%)
로 56
22.2%
길 22
 
8.7%
번 21
 
8.3%
대 17
 
6.7%
제 12
 
4.8%
중 11
 
4.4%
앙 11
 
4.4%
천 9
 
3.6%
원 9
 
3.6%
거 9
 
3.6%
Other values (31) 75
29.8%

지번
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-11T01:05:38.055665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.5263158
Min length7

Characters and Unicode

Total characters543
Distinct characters18
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

Unique57 ?
Unique (%)100.0%

Sample

1st row거제동 46-4
2nd row연산동 582-6
3rd row연산동 717-14
4th row연산동 1124-7
5th row거제동 1489-4
ValueCountFrequency (%)
연산동 42
36.8%
거제동 14
 
12.3%
1361-9 1
 
0.9%
1361-7 1
 
0.9%
859-2 1
 
0.9%
588-7 1
 
0.9%
1355-6 1
 
0.9%
1366-1 1
 
0.9%
1143-2 1
 
0.9%
150-8 1
 
0.9%
Other values (50) 50
43.9%
2023-12-11T01:05:38.570148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 62
11.4%
61
11.2%
동 57
10.5%
- 52
9.6%
연 43
 
7.9%
산 43
 
7.9%
4 32
 
5.9%
2 29
 
5.3%
8 27
 
5.0%
5 22
 
4.1%
Other values (8) 115
21.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
47.5%
Other Letter 172
31.7%
Space Separator 61
 
11.2%
Dash Punctuation 52
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 62
24.0%
4 32
12.4%
2 29
11.2%
8 27
10.5%
5 22
 
8.5%
3 20
 
7.8%
7 19
 
7.4%
0 18
 
7.0%
6 16
 
6.2%
9 13
 
5.0%
Other Letter
ValueCountFrequency (%)
동 57
33.1%
연 43
25.0%
산 43
25.0%
거 14
 
8.1%
제 14
 
8.1%
외 1
 
0.6%
Space Separator
ValueCountFrequency (%)
61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 371
68.3%
Hangul 172
31.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 62
16.7%
61
16.4%
- 52
14.0%
4 32
8.6%
2 29
7.8%
8 27
7.3%
5 22
 
5.9%
3 20
 
5.4%
7 19
 
5.1%
0 18
 
4.9%
Other values (2) 29
7.8%
Hangul
ValueCountFrequency (%)
동 57
33.1%
연 43
25.0%
산 43
25.0%
거 14
 
8.1%
제 14
 
8.1%
외 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 371
68.3%
Hangul 172
31.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 62
16.7%
61
16.4%
- 52
14.0%
4 32
8.6%
2 29
7.8%
8 27
7.3%
5 22
 
5.9%
3 20
 
5.4%
7 19
 
5.1%
0 18
 
4.9%
Other values (2) 29
7.8%
Hangul
ValueCountFrequency (%)
동 57
33.1%
연 43
25.0%
산 43
25.0%
거 14
 
8.1%
제 14
 
8.1%
외 1
 
0.6%

사용승인일자
Date

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum1996-05-02 00:00:00
Maximum2022-05-20 00:00:00
2023-12-11T01:05:38.787863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:38.983027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct56
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21759.145
Minimum1192.23
Maximum153590.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-11T01:05:39.165188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1192.23
5-th percentile3909.412
Q17040.2
median10530
Q319070
95-th percentile65739.442
Maximum153590.73
Range152398.5
Interquartile range (IQR)12029.8

Descriptive statistics

Standard deviation26727.933
Coefficient of variation (CV)1.228354
Kurtosis10.069248
Mean21759.145
Median Absolute Deviation (MAD)5442.2
Skewness2.8094942
Sum1240271.3
Variance7.143824 × 108
MonotonicityNot monotonic
2023-12-11T01:05:39.379190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19010.8 2
 
3.5%
14270.0 1
 
1.8%
7960.21 1
 
1.8%
19070.0 1
 
1.8%
15237.9 1
 
1.8%
17403.2 1
 
1.8%
52413.1 1
 
1.8%
9569.6 1
 
1.8%
9942.4 1
 
1.8%
2853.3 1
 
1.8%
Other values (46) 46
80.7%
ValueCountFrequency (%)
1192.23 1
1.8%
2753.44 1
1.8%
2853.3 1
1.8%
4173.44 1
1.8%
4503.5 1
1.8%
4983.3 1
1.8%
5087.8 1
1.8%
5751.7 1
1.8%
5891.86 1
1.8%
5924.06 1
1.8%
ValueCountFrequency (%)
153590.73 1
1.8%
87946.71 1
1.8%
67400.01 1
1.8%
65324.3 1
1.8%
64516.7 1
1.8%
62816.73 1
1.8%
52827.4 1
1.8%
52413.1 1
1.8%
49922.5 1
1.8%
43431.7 1
1.8%

용도
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size588.0 B
업무시설
19 
공동주택
10 
공동주택 업무시설
4 
공동주택, 업무시설
4 
공공업무
3 
Other values (13)
17 

Length

Max length18
Median length4
Mean length6.4736842
Min length4

Unique

Unique10 ?
Unique (%)17.5%

Sample

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

Common Values

ValueCountFrequency (%)
업무시설 19
33.3%
공동주택 10
17.5%
공동주택 업무시설 4
 
7.0%
공동주택, 업무시설 4
 
7.0%
공공업무 3
 
5.3%
의료시설 3
 
5.3%
판매시설 2
 
3.5%
공동주택, 업무시설, 근린생활시설 2
 
3.5%
숙박시설, 위락시설, 근린생활시설 1
 
1.8%
판매시설 운동시설 문화및집회 1
 
1.8%
Other values (8) 8
14.0%

Length

2023-12-11T01:05:39.620882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 31
40.8%
공동주택 21
27.6%
근린생활시설 4
 
5.3%
공공업무 3
 
3.9%
의료시설 3
 
3.9%
판매시설 3
 
3.9%
근생 1
 
1.3%
업무시설(오 1
 
1.3%
업무시설(오피스텔 1
 
1.3%
숙박시설(관광숙박시설 1
 
1.3%
Other values (7) 7
 
9.2%

공개공지면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean587.75965
Minimum16.75
Maximum12008.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-11T01:05:39.824856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.75
5-th percentile46.97
Q175.84
median186.86
Q3347.2
95-th percentile1843.412
Maximum12008.98
Range11992.23
Interquartile range (IQR)271.36

Descriptive statistics

Standard deviation1633.3676
Coefficient of variation (CV)2.7789719
Kurtosis44.422051
Mean587.75965
Median Absolute Deviation (MAD)121.18
Skewness6.3720198
Sum33502.3
Variance2667889.6
MonotonicityNot monotonic
2023-12-11T01:05:40.050890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
136.5 1
 
1.8%
196.01 1
 
1.8%
309.43 1
 
1.8%
115.87 1
 
1.8%
113.16 1
 
1.8%
347.2 1
 
1.8%
151.01 1
 
1.8%
47.98 1
 
1.8%
248.19 1
 
1.8%
56.96 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
16.75 1
1.8%
37.03 1
1.8%
46.69 1
1.8%
47.04 1
1.8%
47.98 1
1.8%
50.77 1
1.8%
51.98 1
1.8%
52.21 1
1.8%
56.84 1
1.8%
56.96 1
1.8%
ValueCountFrequency (%)
12008.98 1
1.8%
2401.7 1
1.8%
2299.86 1
1.8%
1729.3 1
1.8%
1604.0 1
1.8%
1492.3 1
1.8%
1227.44 1
1.8%
1126.0 1
1.8%
863.02 1
1.8%
595.41 1
1.8%

개소
Categorical

Distinct3
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size588.0 B
1
38 
2
17 
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 38
66.7%
2 17
29.8%
3 2
 
3.5%

Length

2023-12-11T01:05:40.281198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:05:40.430499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 38
66.7%
2 17
29.8%
3 2
 
3.5%

Interactions

2023-12-11T01:05:34.555330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:33.737064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:34.118878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:34.693340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:33.859076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:34.249800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:34.846009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:33.996516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:05:34.410556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:05:40.535891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건축물명도로명주소지번사용승인일자연면적용도공개공지면적개소
연번1.0001.0001.0001.0001.0000.0790.8220.1370.000
건축물명1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
지번1.0001.0001.0001.0001.0001.0001.0001.0001.000
사용승인일자1.0001.0001.0001.0001.0000.0000.7430.0001.000
연면적0.0791.0001.0001.0000.0001.0000.0000.6260.398
용도0.8221.0001.0001.0000.7430.0001.0000.9470.000
공개공지면적0.1371.0001.0001.0000.0000.6260.9471.0000.725
개소0.0001.0001.0001.0001.0000.3980.0000.7251.000
2023-12-11T01:05:40.699059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도개소
용도1.0000.000
개소0.0001.000
2023-12-11T01:05:40.831208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적공개공지면적용도개소
연번1.000-0.151-0.2470.4230.000
연면적-0.1511.0000.7020.0000.282
공개공지면적-0.2470.7021.0000.6410.381
용도0.4230.0000.6411.0000.000
개소0.0000.2820.3810.0001.000

Missing values

2023-12-11T01:05:35.048989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:05:35.227444image/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

연번건축물명도로명주소지번사용승인일자연면적용도공개공지면적개소
01아이비젼사옥거제대로 295거제동 46-41996-05-0214270.0업무시설136.51
12하이트맥주 사옥반송로 69연산동 582-61996-07-047891.7업무시설350.01
23KT&G사옥월드컵대로 83연산동 717-141997-05-299242.2업무시설230.01
34㈜부원 사옥중앙대로 1117연산동 1124-71997-07-0710530.0업무시설68.022
45협성법조빌딩법원남로 16거제동 1489-42001-08-206353.7업무시설142.02
56부산법조타운법원로 28거제동 1490-12001-08-2415250.6업무시설195.291
67세종빌딩법원로 18거제동 1492-12001-08-278396.3업무시설210.261
78로윈타워법원로 12거제동 1497-12001-08-308806.3업무시설184.592
89로제스티빌딩법원로 20거제동 1491-12001-08-319230.6업무시설149.481
910벽산e-메타폴리스온천천공원길 4거제동 139-12005-09-2752827.4공동주택312.371
연번건축물명도로명주소지번사용승인일자연면적용도공개공지면적개소
4748아르반시티호텔반송로 20연산동 603-102019-09-207235.96숙박시설, 위락시설, 근린생활시설47.041
4849제이에스레그노 3차배산북로12번길 30연산동 2124-12020-02-131192.23공동주택16.751
4950시청역 비스타동원연제로30연산동 23622019-12-24153590.73공동주택1227.442
5051이마트트레더스 연산점좌수영로 241연산동 137-52021-01-2262816.73판매시설2299.863
5152스마트리치거제천로152번길 59연산동 1244-42021-07-0216395.64업무시설(오233.841
5253부산시티관광호텔신촌로 19연산동 1356-122021-08-279153.94숙박시설(관광숙박시설)50.771
5354더웰스위트엠명륜로2번길 11거제동 42-12021-10-175891.86업무시설(오피스텔)52.212
5455이편한세상반송로 40연산동23802021-09-2987946.71공동주택1604.01
5556어반스테이더시티중앙대로 1116-8연산동 726-122021-09-297792.8숙박시설(생화숙박시설)37.031
5657포커스빌딩법원남로 12거제동 1489-32022-05-205924.06업무시설(사무소)186.861