Overview

Dataset statistics

Number of variables15
Number of observations132
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory124.0 B

Variable types

Text7
DateTime3
Categorical3
Numeric2

Dataset

Description부산광역시 부산진구 관내 공개공지 현황(건축물명, 공개공지 면적, 허가일, 사용승인일, 건축물용도, 위치정보 등)
Author부산광역시 부산진구
URLhttps://www.data.go.kr/data/15065179/fileData.do

Alerts

구군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
용도 is highly overall correlated with 공개공지개소High correlation
공개공지개소 is highly overall correlated with 용도High correlation
공개공지개소 is highly imbalanced (50.1%)Imbalance
공개공지편의시설 has 2 (1.5%) missing valuesMissing
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:48:49.476033
Analysis finished2024-01-14 13:48:51.593093
Duration2.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축물명
Text

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:51.834846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.6666667
Min length3

Characters and Unicode

Total characters1012
Distinct characters249
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)98.5%

Sample

1st row도시개발공사
2nd row㈜kdb생명보험
3rd row전문건설회관
4th row부산진구청사
5th row한국외환은행
ValueCountFrequency (%)
서면 7
 
3.4%
더 6
 
2.9%
오피스텔 5
 
2.5%
대동레미안 3
 
1.5%
파크 3
 
1.5%
더블루 3
 
1.5%
더파크 2
 
1.0%
뷰 2
 
1.0%
지원 2
 
1.0%
연지 2
 
1.0%
Other values (165) 169
82.8%
2024-01-14T22:48:52.310235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
7.1%
스 40
 
4.0%
리 26
 
2.6%
서 22
 
2.2%
트 21
 
2.1%
면 21
 
2.1%
시 18
 
1.8%
이 18
 
1.8%
아 18
 
1.8%
티 17
 
1.7%
Other values (239) 739
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 895
88.4%
Space Separator 72
 
7.1%
Uppercase Letter 25
 
2.5%
Decimal Number 13
 
1.3%
Lowercase Letter 3
 
0.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 40
 
4.5%
리 26
 
2.9%
서 22
 
2.5%
트 21
 
2.3%
면 21
 
2.3%
시 18
 
2.0%
이 18
 
2.0%
아 18
 
2.0%
티 17
 
1.9%
동 16
 
1.8%
Other values (208) 678
75.8%
Uppercase Letter
ValueCountFrequency (%)
S 3
12.0%
D 2
 
8.0%
T 2
 
8.0%
U 2
 
8.0%
O 2
 
8.0%
E 2
 
8.0%
R 2
 
8.0%
F 1
 
4.0%
J 1
 
4.0%
A 1
 
4.0%
Other values (7) 7
28.0%
Decimal Number
ValueCountFrequency (%)
2 7
53.8%
4 2
 
15.4%
5 1
 
7.7%
6 1
 
7.7%
3 1
 
7.7%
8 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
33.3%
d 1
33.3%
b 1
33.3%
Space Separator
ValueCountFrequency (%)
72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 896
88.5%
Common 88
 
8.7%
Latin 28
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 40
 
4.5%
리 26
 
2.9%
서 22
 
2.5%
트 21
 
2.3%
면 21
 
2.3%
시 18
 
2.0%
이 18
 
2.0%
아 18
 
2.0%
티 17
 
1.9%
동 16
 
1.8%
Other values (209) 679
75.8%
Latin
ValueCountFrequency (%)
S 3
 
10.7%
D 2
 
7.1%
T 2
 
7.1%
U 2
 
7.1%
O 2
 
7.1%
E 2
 
7.1%
R 2
 
7.1%
F 1
 
3.6%
J 1
 
3.6%
A 1
 
3.6%
Other values (10) 10
35.7%
Common
ValueCountFrequency (%)
72
81.8%
2 7
 
8.0%
4 2
 
2.3%
5 1
 
1.1%
( 1
 
1.1%
) 1
 
1.1%
6 1
 
1.1%
3 1
 
1.1%
- 1
 
1.1%
8 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 895
88.4%
ASCII 116
 
11.5%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
62.1%
2 7
 
6.0%
S 3
 
2.6%
D 2
 
1.7%
T 2
 
1.7%
U 2
 
1.7%
O 2
 
1.7%
4 2
 
1.7%
E 2
 
1.7%
R 2
 
1.7%
Other values (20) 20
 
17.2%
Hangul
ValueCountFrequency (%)
스 40
 
4.5%
리 26
 
2.9%
서 22
 
2.5%
트 21
 
2.3%
면 21
 
2.3%
시 18
 
2.0%
이 18
 
2.0%
아 18
 
2.0%
티 17
 
1.9%
동 16
 
1.8%
Other values (208) 678
75.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

공개공지면적
Text

Distinct128
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:52.667168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.3333333
Min length3

Characters and Unicode

Total characters836
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)93.9%

Sample

1st row339.99㎡
2nd row198.87㎡
3rd row137.79㎡
4th row610㎡
5th row54.83㎡
ValueCountFrequency (%)
42㎡ 2
 
1.5%
26.66㎡ 2
 
1.5%
457.89㎡ 2
 
1.5%
62.63㎡ 2
 
1.5%
112.66㎡ 1
 
0.8%
144㎡ 1
 
0.8%
102.39㎡ 1
 
0.8%
445.55㎡ 1
 
0.8%
131.12㎡ 1
 
0.8%
265.92㎡ 1
 
0.8%
Other values (118) 118
89.4%
2024-01-14T22:48:53.227395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㎡ 132
15.8%
. 119
14.2%
1 87
10.4%
2 67
8.0%
6 67
8.0%
3 66
7.9%
5 62
7.4%
4 58
6.9%
8 56
6.7%
0 44
 
5.3%
Other values (2) 78
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 585
70.0%
Other Symbol 132
 
15.8%
Other Punctuation 119
 
14.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 87
14.9%
2 67
11.5%
6 67
11.5%
3 66
11.3%
5 62
10.6%
4 58
9.9%
8 56
9.6%
0 44
7.5%
7 41
7.0%
9 37
6.3%
Other Symbol
ValueCountFrequency (%)
㎡ 132
100.0%
Other Punctuation
ValueCountFrequency (%)
. 119
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
㎡ 132
15.8%
. 119
14.2%
1 87
10.4%
2 67
8.0%
6 67
8.0%
3 66
7.9%
5 62
7.4%
4 58
6.9%
8 56
6.7%
0 44
 
5.3%
Other values (2) 78
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 704
84.2%
CJK Compat 132
 
15.8%

Most frequent character per block

CJK Compat
ValueCountFrequency (%)
㎡ 132
100.0%
ASCII
ValueCountFrequency (%)
. 119
16.9%
1 87
12.4%
2 67
9.5%
6 67
9.5%
3 66
9.4%
5 62
8.8%
4 58
8.2%
8 56
8.0%
0 44
 
6.2%
7 41
 
5.8%

도로명주소
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:53.595543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length24
Mean length19.954545
Min length16

Characters and Unicode

Total characters2634
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

Unique132 ?
Unique (%)100.0%

Sample

1st row부산광역시 부산진구 신천대로 156
2nd row부산광역시 부산진구 중앙대로 766
3rd row부산광역시 부산진구 황령대로30번길 30
4th row부산광역시 부산진구 시민공원로 30
5th row부산광역시 부산진구 중앙대로 743
ValueCountFrequency (%)
부산진구 132
24.5%
부산광역시 131
24.3%
중앙대로 21
 
3.9%
전포대로 8
 
1.5%
동평로 8
 
1.5%
부전로 8
 
1.5%
가야대로 6
 
1.1%
30 5
 
0.9%
동천로 4
 
0.7%
서면로 4
 
0.7%
Other values (163) 212
39.3%
2024-01-14T22:48:54.036252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
407
15.5%
부 273
 
10.4%
산 264
 
10.0%
시 135
 
5.1%
로 132
 
5.0%
광 132
 
5.0%
진 132
 
5.0%
구 132
 
5.0%
역 131
 
5.0%
1 83
 
3.2%
Other values (57) 813
30.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1777
67.5%
Decimal Number 442
 
16.8%
Space Separator 407
 
15.5%
Dash Punctuation 8
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 273
15.4%
산 264
14.9%
시 135
7.6%
로 132
7.4%
광 132
7.4%
진 132
7.4%
구 132
7.4%
역 131
7.4%
대 65
 
3.7%
번 54
 
3.0%
Other values (45) 327
18.4%
Decimal Number
ValueCountFrequency (%)
1 83
18.8%
6 56
12.7%
9 49
11.1%
2 45
10.2%
4 41
9.3%
7 39
8.8%
3 38
8.6%
5 33
 
7.5%
0 31
 
7.0%
8 27
 
6.1%
Space Separator
ValueCountFrequency (%)
407
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1777
67.5%
Common 857
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 273
15.4%
산 264
14.9%
시 135
7.6%
로 132
7.4%
광 132
7.4%
진 132
7.4%
구 132
7.4%
역 131
7.4%
대 65
 
3.7%
번 54
 
3.0%
Other values (45) 327
18.4%
Common
ValueCountFrequency (%)
407
47.5%
1 83
 
9.7%
6 56
 
6.5%
9 49
 
5.7%
2 45
 
5.3%
4 41
 
4.8%
7 39
 
4.6%
3 38
 
4.4%
5 33
 
3.9%
0 31
 
3.6%
Other values (2) 35
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1777
67.5%
ASCII 857
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
407
47.5%
1 83
 
9.7%
6 56
 
6.5%
9 49
 
5.7%
2 45
 
5.3%
4 41
 
4.8%
7 39
 
4.6%
3 38
 
4.4%
5 33
 
3.9%
0 31
 
3.6%
Other values (2) 35
 
4.1%
Hangul
ValueCountFrequency (%)
부 273
15.4%
산 264
14.9%
시 135
7.6%
로 132
7.4%
광 132
7.4%
진 132
7.4%
구 132
7.4%
역 131
7.4%
대 65
 
3.7%
번 54
 
3.0%
Other values (45) 327
18.4%

지번주소
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:54.335670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length20.666667
Min length16

Characters and Unicode

Total characters2728
Distinct characters37
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

Unique132 ?
Unique (%)100.0%

Sample

1st row부산광역시 부산진구 부전동 384-7
2nd row부산광역시 부산진구 부전동 91-5
3rd row부산광역시 부산진구 범천동 853-40
4th row부산광역시 부산진구 부암동 666-16
5th row부산광역시 부산진구 부전동 260-1
ValueCountFrequency (%)
부산광역시 132
26.1%
부산진구 131
25.9%
부전동 22
 
4.3%
외 17
 
3.4%
양정동 16
 
3.2%
전포동 14
 
2.8%
범천동 9
 
1.8%
외1필지 5
 
1.0%
외3필지 4
 
0.8%
개금동 3
 
0.6%
Other values (146) 153
30.2%
2024-01-14T22:48:54.783571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
374
13.7%
부 312
 
11.4%
산 264
 
9.7%
광 132
 
4.8%
역 132
 
4.8%
시 132
 
4.8%
진 132
 
4.8%
구 132
 
4.8%
동 132
 
4.8%
- 120
 
4.4%
Other values (27) 866
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1655
60.7%
Decimal Number 579
 
21.2%
Space Separator 374
 
13.7%
Dash Punctuation 120
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 312
18.9%
산 264
16.0%
광 132
8.0%
역 132
8.0%
시 132
8.0%
진 132
8.0%
구 132
8.0%
동 132
8.0%
전 62
 
3.7%
외 35
 
2.1%
Other values (15) 190
11.5%
Decimal Number
ValueCountFrequency (%)
1 91
15.7%
3 78
13.5%
4 74
12.8%
8 64
11.1%
6 60
10.4%
2 58
10.0%
5 51
8.8%
7 42
7.3%
9 37
6.4%
0 24
 
4.1%
Space Separator
ValueCountFrequency (%)
374
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1655
60.7%
Common 1073
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 312
18.9%
산 264
16.0%
광 132
8.0%
역 132
8.0%
시 132
8.0%
진 132
8.0%
구 132
8.0%
동 132
8.0%
전 62
 
3.7%
외 35
 
2.1%
Other values (15) 190
11.5%
Common
ValueCountFrequency (%)
374
34.9%
- 120
 
11.2%
1 91
 
8.5%
3 78
 
7.3%
4 74
 
6.9%
8 64
 
6.0%
6 60
 
5.6%
2 58
 
5.4%
5 51
 
4.8%
7 42
 
3.9%
Other values (2) 61
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1655
60.7%
ASCII 1073
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
374
34.9%
- 120
 
11.2%
1 91
 
8.5%
3 78
 
7.3%
4 74
 
6.9%
8 64
 
6.0%
6 60
 
5.6%
2 58
 
5.4%
5 51
 
4.8%
7 42
 
3.9%
Other values (2) 61
 
5.7%
Hangul
ValueCountFrequency (%)
부 312
18.9%
산 264
16.0%
광 132
8.0%
역 132
8.0%
시 132
8.0%
진 132
8.0%
구 132
8.0%
동 132
8.0%
전 62
 
3.7%
외 35
 
2.1%
Other values (15) 190
11.5%

허가일자
Date

Distinct120
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1992-11-11 00:00:00
Maximum2022-06-13 00:00:00
2024-01-14T22:48:54.970664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:48:55.157307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일자
Date

Distinct128
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1995-11-10 00:00:00
Maximum2023-08-25 00:00:00
2024-01-14T22:48:55.370469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:48:55.873275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연면적
Text

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:56.579151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.8484848
Min length5

Characters and Unicode

Total characters1036
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)98.5%

Sample

1st row14706.843
2nd row24977.39
3rd row11245.69
4th row35952.12
5th row12444.53
ValueCountFrequency (%)
4687.93 2
 
1.5%
12987.1182 1
 
0.8%
57238.54 1
 
0.8%
12911.4 1
 
0.8%
23695.02 1
 
0.8%
37701.8978 1
 
0.8%
16505.2143 1
 
0.8%
15952.1111 1
 
0.8%
13875.203 1
 
0.8%
14393.79 1
 
0.8%
Other values (121) 121
91.7%
2024-01-14T22:48:57.440170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 131
12.6%
1 110
10.6%
2 108
10.4%
5 104
10.0%
4 95
9.2%
8 93
9.0%
3 90
8.7%
9 88
8.5%
7 84
8.1%
6 74
7.1%
Other values (2) 59
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 904
87.3%
Other Punctuation 132
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 110
12.2%
2 108
11.9%
5 104
11.5%
4 95
10.5%
8 93
10.3%
3 90
10.0%
9 88
9.7%
7 84
9.3%
6 74
8.2%
0 58
6.4%
Other Punctuation
ValueCountFrequency (%)
. 131
99.2%
, 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1036
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 131
12.6%
1 110
10.6%
2 108
10.4%
5 104
10.0%
4 95
9.2%
8 93
9.0%
3 90
8.7%
9 88
8.5%
7 84
8.1%
6 74
7.1%
Other values (2) 59
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 131
12.6%
1 110
10.6%
2 108
10.4%
5 104
10.0%
4 95
9.2%
8 93
9.0%
3 90
8.7%
9 88
8.5%
7 84
8.1%
6 74
7.1%
Other values (2) 59
5.7%

층수
Text

Distinct71
Distinct (%)53.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-14T22:48:57.815214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length7.9090909
Min length4

Characters and Unicode

Total characters1044
Distinct characters17
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

Unique46 ?
Unique (%)34.8%

Sample

1st row지하3/지상13
2nd row지하6/지상20
3rd row지하3/지상13
4th row지하2/지상15 5동
5th row지하5/지상15
ValueCountFrequency (%)
지하1/지상20 13
 
9.4%
지하2/지상20 11
 
7.9%
지하1/지상15 10
 
7.2%
지하2/지상15 6
 
4.3%
지하1/지상14 4
 
2.9%
지하3/지상15 3
 
2.2%
지하2/지상7 3
 
2.2%
지하1/지상18 3
 
2.2%
지하1/지상19 3
 
2.2%
지하5/지상20 2
 
1.4%
Other values (64) 81
58.3%
2024-01-14T22:48:58.736403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 258
24.7%
상 132
12.6%
/ 126
12.1%
하 126
12.1%
1 118
11.3%
2 98
 
9.4%
0 39
 
3.7%
5 38
 
3.6%
3 28
 
2.7%
4 17
 
1.6%
Other values (7) 64
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 522
50.0%
Decimal Number 387
37.1%
Other Punctuation 128
 
12.3%
Space Separator 7
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 118
30.5%
2 98
25.3%
0 39
 
10.1%
5 38
 
9.8%
3 28
 
7.2%
4 17
 
4.4%
8 15
 
3.9%
9 12
 
3.1%
7 12
 
3.1%
6 10
 
2.6%
Other Letter
ValueCountFrequency (%)
지 258
49.4%
상 132
25.3%
하 126
24.1%
동 6
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 126
98.4%
, 2
 
1.6%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 522
50.0%
Common 522
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 126
24.1%
1 118
22.6%
2 98
18.8%
0 39
 
7.5%
5 38
 
7.3%
3 28
 
5.4%
4 17
 
3.3%
8 15
 
2.9%
9 12
 
2.3%
7 12
 
2.3%
Other values (3) 19
 
3.6%
Hangul
ValueCountFrequency (%)
지 258
49.4%
상 132
25.3%
하 126
24.1%
동 6
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 522
50.0%
ASCII 522
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 258
49.4%
상 132
25.3%
하 126
24.1%
동 6
 
1.1%
ASCII
ValueCountFrequency (%)
/ 126
24.1%
1 118
22.6%
2 98
18.8%
0 39
 
7.5%
5 38
 
7.3%
3 28
 
5.4%
4 17
 
3.3%
8 15
 
2.9%
9 12
 
2.3%
7 12
 
2.3%
Other values (3) 19
 
3.6%

용도
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
업무시설
51 
공동주택
32 
업무시설,근생
6 
공동주택,업무시설
6 
숙박시설
 
5
Other values (25)
32 

Length

Max length25
Median length4
Mean length5.9924242
Min length4

Unique

Unique21 ?
Unique (%)15.9%

Sample

1st row업무시설
2nd row업무시설,근생
3rd row업무시설 관람및집회 교육연구 근생
4th row업무시설
5th row업무시설

Common Values

ValueCountFrequency (%)
업무시설 51
38.6%
공동주택 32
24.2%
업무시설,근생 6
 
4.5%
공동주택,업무시설 6
 
4.5%
숙박시설 5
 
3.8%
의료시설 4
 
3.0%
공동주택,업무시설,근생 3
 
2.3%
업무시설, 근린생활시설 2
 
1.5%
공동주택,근생 2
 
1.5%
공동주택,업무시설,근생,운동시설 1
 
0.8%
Other values (20) 20
 
15.2%

Length

2024-01-14T22:48:58.947194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
업무시설 61
39.4%
공동주택 36
23.2%
업무시설,근생 6
 
3.9%
공동주택,업무시설 6
 
3.9%
숙박시설 5
 
3.2%
근생 5
 
3.2%
의료시설 4
 
2.6%
판매시설 4
 
2.6%
공동주택,업무시설,근생 3
 
1.9%
근린생활시설 3
 
1.9%
Other values (17) 22
 
14.2%

공개공지개소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1
94 
2
30 
3
 
5
5
 
2
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row1
2nd row1
3rd row1
4th row5
5th row1

Common Values

ValueCountFrequency (%)
1 94
71.2%
2 30
 
22.7%
3 5
 
3.8%
5 2
 
1.5%
8 1
 
0.8%

Length

2024-01-14T22:48:59.132157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:48:59.294759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 94
71.2%
2 30
 
22.7%
3 5
 
3.8%
5 2
 
1.5%
8 1
 
0.8%

공개공지편의시설
Text

MISSING 

Distinct81
Distinct (%)62.3%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2024-01-14T22:48:59.563533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length10.346154
Min length2

Characters and Unicode

Total characters1345
Distinct characters67
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)46.2%

Sample

1st row의자, 표지판
2nd row의자, 조형물, 표지판 1
3rd row의자, 조형물, 표지판 1
4th row의자, 표지판 1
5th row표지판 1
ValueCountFrequency (%)
표지판 56
16.0%
의자 49
14.0%
1 46
13.1%
표지판1 30
 
8.5%
파고라 22
 
6.3%
조명 11
 
3.1%
의자2 11
 
3.1%
의자4 10
 
2.8%
조형물 9
 
2.6%
표지판2 9
 
2.6%
Other values (58) 98
27.9%
2024-01-14T22:49:00.102069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
221
16.4%
, 163
12.1%
자 111
 
8.3%
의 110
 
8.2%
1 100
 
7.4%
표 96
 
7.1%
지 96
 
7.1%
판 96
 
7.1%
2 36
 
2.7%
조 34
 
2.5%
Other values (57) 282
21.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 755
56.1%
Space Separator 221
 
16.4%
Decimal Number 198
 
14.7%
Other Punctuation 163
 
12.1%
Uppercase Letter 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 111
14.7%
의 110
14.6%
표 96
12.7%
지 96
12.7%
판 96
12.7%
조 34
 
4.5%
라 27
 
3.6%
파 26
 
3.4%
고 26
 
3.4%
명 15
 
2.0%
Other values (42) 118
15.6%
Decimal Number
ValueCountFrequency (%)
1 100
50.5%
2 36
 
18.2%
3 19
 
9.6%
4 16
 
8.1%
6 10
 
5.1%
5 8
 
4.0%
8 3
 
1.5%
9 3
 
1.5%
0 2
 
1.0%
7 1
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
T 2
25.0%
V 2
25.0%
Space Separator
ValueCountFrequency (%)
221
100.0%
Other Punctuation
ValueCountFrequency (%)
, 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 755
56.1%
Common 582
43.3%
Latin 8
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 111
14.7%
의 110
14.6%
표 96
12.7%
지 96
12.7%
판 96
12.7%
조 34
 
4.5%
라 27
 
3.6%
파 26
 
3.4%
고 26
 
3.4%
명 15
 
2.0%
Other values (42) 118
15.6%
Common
ValueCountFrequency (%)
221
38.0%
, 163
28.0%
1 100
17.2%
2 36
 
6.2%
3 19
 
3.3%
4 16
 
2.7%
6 10
 
1.7%
5 8
 
1.4%
8 3
 
0.5%
9 3
 
0.5%
Other values (2) 3
 
0.5%
Latin
ValueCountFrequency (%)
C 4
50.0%
T 2
25.0%
V 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 755
56.1%
ASCII 590
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
221
37.5%
, 163
27.6%
1 100
16.9%
2 36
 
6.1%
3 19
 
3.2%
4 16
 
2.7%
6 10
 
1.7%
5 8
 
1.4%
C 4
 
0.7%
8 3
 
0.5%
Other values (5) 10
 
1.7%
Hangul
ValueCountFrequency (%)
자 111
14.7%
의 110
14.6%
표 96
12.7%
지 96
12.7%
판 96
12.7%
조 34
 
4.5%
라 27
 
3.6%
파 26
 
3.4%
고 26
 
3.4%
명 15
 
2.0%
Other values (42) 118
15.6%

구군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
부산광역시 부산진구
132 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 부산진구
2nd row부산광역시 부산진구
3rd row부산광역시 부산진구
4th row부산광역시 부산진구
5th row부산광역시 부산진구

Common Values

ValueCountFrequency (%)
부산광역시 부산진구 132
100.0%

Length

2024-01-14T22:49:00.291964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:49:00.436090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 132
50.0%
부산진구 132
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-12-19 00:00:00
Maximum2023-12-19 00:00:00
2024-01-14T22:49:00.533910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:49:00.636555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

위도
Real number (ℝ)

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.158791
Minimum35.14177
Maximum35.178038
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-14T22:49:00.768369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.14177
5-th percentile35.144674
Q135.151425
median35.157693
Q335.164445
95-th percentile35.175779
Maximum35.178038
Range0.0362676
Interquartile range (IQR)0.01302085

Descriptive statistics

Standard deviation0.0095820409
Coefficient of variation (CV)0.00027253613
Kurtosis-0.77647628
Mean35.158791
Median Absolute Deviation (MAD)0.006455
Skewness0.44642273
Sum4640.9604
Variance9.1815508 × 10-5
MonotonicityNot monotonic
2024-01-14T22:49:00.929435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17488492 2
 
1.5%
35.15595306 1
 
0.8%
35.1572119 1
 
0.8%
35.1587312 1
 
0.8%
35.1658702 1
 
0.8%
35.1446954 1
 
0.8%
35.1623672 1
 
0.8%
35.1481805 1
 
0.8%
35.1712511 1
 
0.8%
35.1486073 1
 
0.8%
Other values (121) 121
91.7%
ValueCountFrequency (%)
35.1417699 1
0.8%
35.143413 1
0.8%
35.1440028 1
0.8%
35.1441378 1
0.8%
35.1442955 1
0.8%
35.1445757 1
0.8%
35.1446485 1
0.8%
35.1446954 1
0.8%
35.1456886 1
0.8%
35.1461242 1
0.8%
ValueCountFrequency (%)
35.1780375 1
0.8%
35.1775462 1
0.8%
35.1774385 1
0.8%
35.1774189 1
0.8%
35.1773394 1
0.8%
35.1770942 1
0.8%
35.1758781 1
0.8%
35.1756975 1
0.8%
35.1756125 1
0.8%
35.17488492 2
1.5%

경도
Real number (ℝ)

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.0582
Minimum129.01939
Maximum129.07509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-14T22:49:01.120955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.01939
5-th percentile129.03273
Q1129.05445
median129.05969
Q3129.06441
95-th percentile129.07215
Maximum129.07509
Range0.0557025
Interquartile range (IQR)0.009959475

Descriptive statistics

Standard deviation0.011040865
Coefficient of variation (CV)8.5549505 × 10-5
Kurtosis4.2268563
Mean129.0582
Median Absolute Deviation (MAD)0.0049291
Skewness-1.770716
Sum17035.682
Variance0.0001219007
MonotonicityNot monotonic
2024-01-14T22:49:01.313297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0682111 2
 
1.5%
129.051566 1
 
0.8%
129.048148 1
 
0.8%
129.061124 1
 
0.8%
129.064717 1
 
0.8%
129.058224 1
 
0.8%
129.054499 1
 
0.8%
129.056239 1
 
0.8%
129.056709 1
 
0.8%
129.020141 1
 
0.8%
Other values (121) 121
91.7%
ValueCountFrequency (%)
129.0193905 1
0.8%
129.020141 1
0.8%
129.020614 1
0.8%
129.022372 1
0.8%
129.022507 1
0.8%
129.0225569 1
0.8%
129.024159 1
0.8%
129.039748 1
0.8%
129.043427 1
0.8%
129.0443871 1
0.8%
ValueCountFrequency (%)
129.075093 1
0.8%
129.0749468 1
0.8%
129.074639 1
0.8%
129.073945 1
0.8%
129.0731711 1
0.8%
129.0725113 1
0.8%
129.0723813 1
0.8%
129.0719528 1
0.8%
129.070834 1
0.8%
129.0706522 1
0.8%

Interactions

2024-01-14T22:48:50.760627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:48:50.456478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:48:50.910981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:48:50.600076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:49:01.428113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
층수용도공개공지개소공개공지편의시설위도경도
층수1.0000.9450.9540.8160.6690.553
용도0.9451.0000.8980.0000.5210.763
공개공지개소0.9540.8981.0000.8190.0000.000
공개공지편의시설0.8160.0000.8191.0000.8220.485
위도0.6690.5210.0000.8221.0000.652
경도0.5530.7630.0000.4850.6521.000
2024-01-14T22:49:01.580535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도공개공지개소
용도1.0000.561
공개공지개소0.5611.000
2024-01-14T22:49:01.692542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도용도공개공지개소
위도1.0000.3260.1700.000
경도0.3261.0000.3960.000
용도0.1700.3961.0000.561
공개공지개소0.0000.0000.5611.000

Missing values

2024-01-14T22:48:51.129539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:48:51.471162image/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

건축물명공개공지면적도로명주소지번주소허가일자사용승인일자연면적층수용도공개공지개소공개공지편의시설구군명데이터기준일자위도경도
0도시개발공사339.99㎡부산광역시 부산진구 신천대로 156부산광역시 부산진구 부전동 384-71993-01-081995-11-1014706.843지하3/지상13업무시설1의자, 표지판부산광역시 부산진구2023-12-1935.155953129.051566
1㈜kdb생명보험198.87㎡부산광역시 부산진구 중앙대로 766부산광역시 부산진구 부전동 91-51992-11-111997-01-1124977.39지하6/지상20업무시설,근생1의자, 조형물, 표지판 1부산광역시 부산진구2023-12-1935.160504129.061816
2전문건설회관137.79㎡부산광역시 부산진구 황령대로30번길 30부산광역시 부산진구 범천동 853-401995-03-231998-03-2311245.69지하3/지상13업무시설 관람및집회 교육연구 근생1의자, 조형물, 표지판 1부산광역시 부산진구2023-12-1935.147097129.060358
3부산진구청사610㎡부산광역시 부산진구 시민공원로 30부산광역시 부산진구 부암동 666-161994-12-311998-11-1635952.12지하2/지상15 5동업무시설5의자, 표지판 1부산광역시 부산진구2023-12-1935.162647129.050996
4한국외환은행54.83㎡부산광역시 부산진구 중앙대로 743부산광역시 부산진구 부전동 260-11995-11-281999-06-2112444.53지하5/지상15업무시설1표지판 1부산광역시 부산진구2023-12-1935.159419129.057163
5지오플레이스1234.57㎡부산광역시 부산진구 동천로 4부산광역시 부산진구 전포동 891-38 외1997-03-242000-05-2588666.52지하6/지상8판매및영업문화및집회 위락시설2의자, 조형물, 표지판 1부산광역시 부산진구2023-12-1935.149552129.062663
6디씨티1800.76㎡부산광역시 부산진구 동천로 92부산광역시 부산진구 전포동 668-11996-09-252000-08-3082599.97지하2/지상7판매및영업문화및집회 업무시설 운동시설 근생1의자, 조명, 간이무대, 표지판 1부산광역시 부산진구2023-12-1935.157041129.060835
7대한생명부산사옥460㎡부산광역시 부산진구 중앙대로 659부산광역시 부산진구 부전동 535-51997-01-292001-03-0629807.84지하9/지상19업무시설2의자, 조형물, 표지판 1부산광역시 부산진구2023-12-1935.151544129.056467
8이마트953.67㎡부산광역시 부산진구 시민공원로 31부산광역시 부산진구 부암동 932000-09-062002-03-2244063.89지하2/지상6판매및영업1의자, 파고라, 자전거보관소, 표지판 1부산광역시 부산진구2023-12-1935.163914129.050405
9부산진경찰서188.67㎡부산광역시 부산진구 부전로111번길 6부산광역시 부산진구 부전동 408-42000-02-282002-08-0911491.05지하3/지상8업무시설1파고라, 의자, 표지판 1부산광역시 부산진구2023-12-1935.160195129.052292
건축물명공개공지면적도로명주소지번주소허가일자사용승인일자연면적층수용도공개공지개소공개공지편의시설구군명데이터기준일자위도경도
122병산프리덤81.06㎡부산광역시 부산진구 부전로 111번길 24부산광역시 부산진구 부전동 414-262019-03-252020-07-233543.37지하1/지상14업무시설1의자2부산광역시 부산진구2023-12-1935.160037129.053404
123서면루미랑스아파트26.66㎡부산광역시 부산진구 가야대로 747번길 62부산광역시 부산진구 부암동 680-182017-04-212019-04-253934.38지하1/지상20업무시설1긴의자3, 연석의자3부산광역시 부산진구2023-12-1935.160573129.052829
124로지라이프오피스텔26.66㎡부산광역시 부산진구 동천로 107번길 13부산광역시 부산진구 부전동 143-42020-07-242022-05-164482.35지하1/지상20업무시설1표지판1부산광역시 부산진구2023-12-1935.158145129.061545
125동하오피스텔41.86㎡부산광역시 부산진구 가야대로 765번길 30부산광역시 부산진구 부전동 474-882017-09-292020-06-182346.23지하1/지상14업무시설1벤치3, 벽부등3, 조경부산광역시 부산진구2023-12-1935.159117129.055423
126위드에코하임84.63㎡부산광역시 부산진구 중앙대로 970번가길 8부산광역시 부산진구 양정동 139-12020-08-182022-05-112504.21지하1/지상13업무시설1평의자2부산광역시 부산진구2023-12-1935.175612129.074947
127더한다22.663㎡부산광역시 부산진구 중앙대로 969번길 30-13부산광역시 부산진구 양정동 158-22022-06-132023-07-251707.46지하1/지상11공동주택,업무시설1벤치2부산광역시 부산진구2023-12-1935.177546129.072381
128큐브빌클라세40.54㎡부산광역시 부산진구 동평로 397번길 33부산광역시 부산진구 양정동 314-32020-07-242021-11-241754.81지상11공동주택,업무시설1평의자2, 표지판1부산광역시 부산진구2023-12-1935.175697129.069426
129노블파크42㎡부산광역시 부산진구 거제대로 36번가길 41부산광역시 부산진구 양정동 387-62019-06-272022-08-304687.93지하1/지상18공동주택,업무시설1벤치4부산광역시 부산진구2023-12-1935.173636129.068136
130아트온부전27.38㎡부산광역시 부산진구 부전로 94-1부산광역시 부산진구 부전동 469-162020-07-012021-08-232232.5지하1/지상14업무시설1평의자2, 표지판1부산광역시 부산진구2023-12-1935.158752129.054924
131메그레즈타워50.061㎡부산광역시 부산진구 동평로 405번길 96부산광역시 부산진구 양정동 1582022-06-132023-08-251982.6지하1/지상11업무시설1벤치2부산광역시 부산진구2023-12-1935.177419129.072511