Overview

Dataset statistics

Number of variables14
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory118.7 B

Variable types

Numeric5
Categorical6
Text3

Dataset

Description부산광역시 공공건축물 석면 현황에 대한 데이터로 번호, 구분, 구군, 소유자 , 건축물명(상호), 동명, 주소, 위도, 경도, 석면건축 여부, 안전관리인 지정여부, 연면적, 석면(자재)면적, 데이터기준일자 항목정보를 제공합니다.
URLhttps://www.data.go.kr/data/15103460/fileData.do

Alerts

구분 has constant value ""Constant
소유자 has constant value ""Constant
석면건축 여부 has constant value ""Constant
안전관리인 지정여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 구군High correlation
위도 is highly overall correlated with 구군High correlation
경도 is highly overall correlated with 구군High correlation
연면적 is highly overall correlated with 석면(자재)면적High correlation
석면(자재)면적 is highly overall correlated with 연면적High correlation
구군 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 has unique valuesUnique
석면(자재)면적 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:24:03.952072
Analysis finished2023-12-12 05:24:08.338122
Duration4.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.5
Minimum1
Maximum78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T14:24:08.429929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.85
Q120.25
median39.5
Q358.75
95-th percentile74.15
Maximum78
Range77
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation22.660538
Coefficient of variation (CV)0.57368452
Kurtosis-1.2
Mean39.5
Median Absolute Deviation (MAD)19.5
Skewness0
Sum3081
Variance513.5
MonotonicityStrictly increasing
2023-12-12T14:24:08.619392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.3%
51 1
 
1.3%
58 1
 
1.3%
57 1
 
1.3%
56 1
 
1.3%
55 1
 
1.3%
54 1
 
1.3%
53 1
 
1.3%
52 1
 
1.3%
50 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
1 1
1.3%
2 1
1.3%
3 1
1.3%
4 1
1.3%
5 1
1.3%
6 1
1.3%
7 1
1.3%
8 1
1.3%
9 1
1.3%
10 1
1.3%
ValueCountFrequency (%)
78 1
1.3%
77 1
1.3%
76 1
1.3%
75 1
1.3%
74 1
1.3%
73 1
1.3%
72 1
1.3%
71 1
1.3%
70 1
1.3%
69 1
1.3%

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
공공건축물
78 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공건축물 78
100.0%

Length

2023-12-12T14:24:08.756723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:08.848481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공건축물 78
100.0%

구군
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)19.2%
Missing0
Missing (%)0.0%
Memory size756.0 B
강서구
15 
동래구
11 
사상구
10 
남구
9 
금정구
6 
Other values (10)
27 

Length

Max length4
Median length3
Mean length2.8333333
Min length2

Unique

Unique3 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
강서구 15
19.2%
동래구 11
14.1%
사상구 10
12.8%
남구 9
11.5%
금정구 6
 
7.7%
서구 6
 
7.7%
부산진구 4
 
5.1%
해운대구 4
 
5.1%
북구 3
 
3.8%
중구 3
 
3.8%
Other values (5) 7
9.0%

Length

2023-12-12T14:24:08.973709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 15
19.2%
동래구 11
14.1%
사상구 10
12.8%
남구 9
11.5%
금정구 6
 
7.7%
서구 6
 
7.7%
부산진구 4
 
5.1%
해운대구 4
 
5.1%
북구 3
 
3.8%
중구 3
 
3.8%
Other values (5) 7
9.0%

소유자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
부산시
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산시 78
100.0%

Length

2023-12-12T14:24:09.118574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:09.242827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산시 78
100.0%

건축물명(상호)
Text

Distinct52
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T14:24:09.514663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length10.525641
Min length4

Characters and Unicode

Total characters821
Distinct characters117
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)53.8%

Sample

1st row부산광역시 체육시설관리사업소
2nd row녹산협업화사업장
3rd row부산환경공단 서부사업소
4th row부산환경공단 서부사업소
5th row부산환경공단 명지사업소
ValueCountFrequency (%)
부산환경공단 18
 
16.1%
엄궁농산물도매시장관리사업소 7
 
6.2%
수영사업소 6
 
5.4%
부산광역시 6
 
5.4%
체육시설관리사업소 5
 
4.5%
부산환경공단중앙사업소 4
 
3.6%
상수도사업본부 4
 
3.6%
녹산사업소 4
 
3.6%
문화회관 3
 
2.7%
금정체육공원 3
 
2.7%
Other values (47) 52
46.4%
2023-12-12T14:24:10.002511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 54
 
6.6%
사 52
 
6.3%
부 49
 
6.0%
업 46
 
5.6%
소 41
 
5.0%
36
 
4.4%
관 33
 
4.0%
시 31
 
3.8%
공 29
 
3.5%
경 27
 
3.3%
Other values (107) 423
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 778
94.8%
Space Separator 36
 
4.4%
Close Punctuation 3
 
0.4%
Open Punctuation 3
 
0.4%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 54
 
6.9%
사 52
 
6.7%
부 49
 
6.3%
업 46
 
5.9%
소 41
 
5.3%
관 33
 
4.2%
시 31
 
4.0%
공 29
 
3.7%
경 27
 
3.5%
환 25
 
3.2%
Other values (103) 391
50.3%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 778
94.8%
Common 43
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 54
 
6.9%
사 52
 
6.7%
부 49
 
6.3%
업 46
 
5.9%
소 41
 
5.3%
관 33
 
4.2%
시 31
 
4.0%
공 29
 
3.7%
경 27
 
3.5%
환 25
 
3.2%
Other values (103) 391
50.3%
Common
ValueCountFrequency (%)
36
83.7%
) 3
 
7.0%
( 3
 
7.0%
- 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 778
94.8%
ASCII 43
 
5.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 54
 
6.9%
사 52
 
6.7%
부 49
 
6.3%
업 46
 
5.9%
소 41
 
5.3%
관 33
 
4.2%
시 31
 
4.0%
공 29
 
3.7%
경 27
 
3.5%
환 25
 
3.2%
Other values (103) 391
50.3%
ASCII
ValueCountFrequency (%)
36
83.7%
) 3
 
7.0%
( 3
 
7.0%
- 1
 
2.3%

동명
Text

Distinct71
Distinct (%)91.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T14:24:10.342016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length6.7307692
Min length1

Characters and Unicode

Total characters525
Distinct characters149
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)87.2%

Sample

1st row실내체육관
2nd row녹산협업화사업장
3rd row탈수기동
4th row관리동
5th row공장동
ValueCountFrequency (%)
탈수기동 4
 
4.3%
관리동 4
 
4.3%
본관 3
 
3.2%
제2전시관 2
 
2.2%
실내체육관 2
 
2.2%
요트경기장 2
 
2.2%
항도청과 1
 
1.1%
강변사업소(관리동 1
 
1.1%
부산환경공단 1
 
1.1%
본사 1
 
1.1%
Other values (72) 72
77.4%
2023-12-12T14:24:10.820829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 32
 
6.1%
관 28
 
5.3%
장 23
 
4.4%
16
 
3.0%
수 13
 
2.5%
지 13
 
2.5%
기 12
 
2.3%
리 12
 
2.3%
사 12
 
2.3%
산 11
 
2.1%
Other values (139) 353
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 468
89.1%
Decimal Number 21
 
4.0%
Space Separator 16
 
3.0%
Close Punctuation 7
 
1.3%
Open Punctuation 7
 
1.3%
Math Symbol 4
 
0.8%
Dash Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 32
 
6.8%
관 28
 
6.0%
장 23
 
4.9%
수 13
 
2.8%
지 13
 
2.8%
기 12
 
2.6%
리 12
 
2.6%
사 12
 
2.6%
산 11
 
2.4%
층 10
 
2.1%
Other values (127) 302
64.5%
Decimal Number
ValueCountFrequency (%)
1 9
42.9%
2 4
19.0%
4 3
 
14.3%
3 3
 
14.3%
9 1
 
4.8%
6 1
 
4.8%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 468
89.1%
Common 56
 
10.7%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 32
 
6.8%
관 28
 
6.0%
장 23
 
4.9%
수 13
 
2.8%
지 13
 
2.8%
기 12
 
2.6%
리 12
 
2.6%
사 12
 
2.6%
산 11
 
2.4%
층 10
 
2.1%
Other values (127) 302
64.5%
Common
ValueCountFrequency (%)
16
28.6%
1 9
16.1%
) 7
12.5%
( 7
12.5%
~ 4
 
7.1%
2 4
 
7.1%
4 3
 
5.4%
3 3
 
5.4%
9 1
 
1.8%
- 1
 
1.8%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 468
89.1%
ASCII 57
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 32
 
6.8%
관 28
 
6.0%
장 23
 
4.9%
수 13
 
2.8%
지 13
 
2.8%
기 12
 
2.6%
리 12
 
2.6%
사 12
 
2.6%
산 11
 
2.4%
층 10
 
2.1%
Other values (127) 302
64.5%
ASCII
ValueCountFrequency (%)
16
28.1%
1 9
15.8%
) 7
12.3%
( 7
12.3%
~ 4
 
7.0%
2 4
 
7.0%
4 3
 
5.3%
3 3
 
5.3%
9 1
 
1.8%
- 1
 
1.8%
Other values (2) 2
 
3.5%

주소
Text

Distinct56
Distinct (%)71.8%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T14:24:11.241128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length38.5
Mean length27.666667
Min length20

Characters and Unicode

Total characters2158
Distinct characters150
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

Unique45 ?
Unique (%)57.7%

Sample

1st row부산광역시 강서구 체육공원로 43 (대저1동)
2nd row부산광역시 강서구 녹산산단 382로 14번길 55
3rd row부산광역시 강서구 강동신덕1길 13 (강동동)
4th row부산광역시 강서구 강동신덕1길 13 (강동동)
5th row부산광역시 강서구 명지오션시티 13로 12-11 (공장동)
ValueCountFrequency (%)
부산광역시 78
 
19.8%
강서구 15
 
3.8%
동래구 11
 
2.8%
사상구 10
 
2.5%
남구 9
 
2.3%
엄궁동 7
 
1.8%
대연동 6
 
1.5%
서구 6
 
1.5%
금정구 6
 
1.5%
온천천남로 6
 
1.5%
Other values (151) 240
60.9%
2023-12-12T14:24:11.835804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316
 
14.6%
산 105
 
4.9%
동 103
 
4.8%
부 93
 
4.3%
시 93
 
4.3%
) 90
 
4.2%
( 90
 
4.2%
구 87
 
4.0%
역 79
 
3.7%
광 79
 
3.7%
Other values (140) 1023
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1389
64.4%
Space Separator 316
 
14.6%
Decimal Number 267
 
12.4%
Close Punctuation 90
 
4.2%
Open Punctuation 90
 
4.2%
Dash Punctuation 3
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 105
 
7.6%
동 103
 
7.4%
부 93
 
6.7%
시 93
 
6.7%
구 87
 
6.3%
역 79
 
5.7%
광 79
 
5.7%
로 75
 
5.4%
대 34
 
2.4%
길 28
 
2.0%
Other values (125) 613
44.1%
Decimal Number
ValueCountFrequency (%)
1 50
18.7%
3 37
13.9%
2 35
13.1%
9 29
10.9%
5 27
10.1%
4 25
9.4%
6 20
 
7.5%
8 19
 
7.1%
7 19
 
7.1%
0 6
 
2.2%
Space Separator
ValueCountFrequency (%)
316
100.0%
Close Punctuation
ValueCountFrequency (%)
) 90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1389
64.4%
Common 769
35.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 105
 
7.6%
동 103
 
7.4%
부 93
 
6.7%
시 93
 
6.7%
구 87
 
6.3%
역 79
 
5.7%
광 79
 
5.7%
로 75
 
5.4%
대 34
 
2.4%
길 28
 
2.0%
Other values (125) 613
44.1%
Common
ValueCountFrequency (%)
316
41.1%
) 90
 
11.7%
( 90
 
11.7%
1 50
 
6.5%
3 37
 
4.8%
2 35
 
4.6%
9 29
 
3.8%
5 27
 
3.5%
4 25
 
3.3%
6 20
 
2.6%
Other values (5) 50
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1389
64.4%
ASCII 769
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316
41.1%
) 90
 
11.7%
( 90
 
11.7%
1 50
 
6.5%
3 37
 
4.8%
2 35
 
4.6%
9 29
 
3.8%
5 27
 
3.5%
4 25
 
3.3%
6 20
 
2.6%
Other values (5) 50
 
6.5%
Hangul
ValueCountFrequency (%)
산 105
 
7.6%
동 103
 
7.4%
부 93
 
6.7%
시 93
 
6.7%
구 87
 
6.3%
역 79
 
5.7%
광 79
 
5.7%
로 75
 
5.4%
대 34
 
2.4%
길 28
 
2.0%
Other values (125) 613
44.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.155506
Minimum35.05445
Maximum35.289122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T14:24:12.061216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.05445
5-th percentile35.070632
Q135.125823
median35.144853
Q335.189818
95-th percentile35.26857
Maximum35.289122
Range0.23467225
Interquartile range (IQR)0.063995545

Descriptive statistics

Standard deviation0.057681625
Coefficient of variation (CV)0.0016407565
Kurtosis-0.21259913
Mean35.155506
Median Absolute Deviation (MAD)0.04414825
Skewness0.41086302
Sum2742.1295
Variance0.0033271699
MonotonicityNot monotonic
2023-12-12T14:24:12.251313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.18900098 6
 
7.7%
35.16970737 4
 
5.1%
35.05444974 4
 
5.1%
35.12718603 4
 
5.1%
35.28912199 3
 
3.8%
35.08663089 3
 
3.8%
35.12582289 3
 
3.8%
35.23307387 2
 
2.6%
35.1305142 2
 
2.6%
35.15980122 2
 
2.6%
Other values (44) 45
57.7%
ValueCountFrequency (%)
35.05444974 4
5.1%
35.07348753 1
 
1.3%
35.08287925 1
 
1.3%
35.08663089 3
3.8%
35.08709383 1
 
1.3%
35.0871168 1
 
1.3%
35.08860879 1
 
1.3%
35.08864227 1
 
1.3%
35.0905938 1
 
1.3%
35.09832485 1
 
1.3%
ValueCountFrequency (%)
35.28912199 3
3.8%
35.270815 1
 
1.3%
35.26817352 1
 
1.3%
35.25207995 1
 
1.3%
35.24591647 1
 
1.3%
35.23307387 2
2.6%
35.22506382 1
 
1.3%
35.22195558 1
 
1.3%
35.21096031 1
 
1.3%
35.20115386 1
 
1.3%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct54
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.03206
Minimum128.85328
Maximum129.22345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T14:24:12.432791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.85328
5-th percentile128.8639
Q1128.96747
median129.04453
Q3129.10642
95-th percentile129.14196
Maximum129.22345
Range0.3701744
Interquartile range (IQR)0.13894885

Descriptive statistics

Standard deviation0.084506875
Coefficient of variation (CV)0.00065492929
Kurtosis-0.44521101
Mean129.03206
Median Absolute Deviation (MAD)0.06699815
Skewness-0.37979778
Sum10064.501
Variance0.0071414119
MonotonicityNot monotonic
2023-12-12T14:24:12.627216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.1115329 6
 
7.7%
128.9558839 4
 
5.1%
129.012877 4
 
5.1%
129.0934767 4
 
5.1%
129.1070421 3
 
3.8%
128.8639016 3
 
3.8%
129.1164108 3
 
3.8%
129.122758 2
 
2.6%
128.9683723 2
 
2.6%
129.1419557 2
 
2.6%
Other values (44) 45
57.7%
ValueCountFrequency (%)
128.8532798 1
 
1.3%
128.853291 1
 
1.3%
128.8639016 3
3.8%
128.8725317 1
 
1.3%
128.8783934 1
 
1.3%
128.89885 1
 
1.3%
128.9305222 2
2.6%
128.9541776 1
 
1.3%
128.9558839 4
5.1%
128.9639869 1
 
1.3%
ValueCountFrequency (%)
129.2234542 1
 
1.3%
129.1849393 1
 
1.3%
129.1483299 1
 
1.3%
129.1419557 2
 
2.6%
129.1297709 1
 
1.3%
129.122758 2
 
2.6%
129.1164108 3
3.8%
129.1115329 6
7.7%
129.1070421 3
3.8%
129.1045436 1
 
1.3%

석면건축 여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
해당
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해당 78
100.0%

Length

2023-12-12T14:24:12.837888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:12.986229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당 78
100.0%

안전관리인 지정여부
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
지정
78 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지정 78
100.0%

Length

2023-12-12T14:24:13.133368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:13.241952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 78
100.0%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct77
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8535.189
Minimum518.03
Maximum94115.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T14:24:13.379534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum518.03
5-th percentile637.5275
Q11104.4875
median3968.185
Q311547.352
95-th percentile22906.496
Maximum94115.02
Range93596.99
Interquartile range (IQR)10442.865

Descriptive statistics

Standard deviation13030.919
Coefficient of variation (CV)1.5267288
Kurtosis23.868269
Mean8535.189
Median Absolute Deviation (MAD)3107.425
Skewness4.1273199
Sum665744.74
Variance1.6980484 × 108
MonotonicityNot monotonic
2023-12-12T14:24:13.548157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20832.6 2
 
2.6%
21440.38 1
 
1.3%
1123.95 1
 
1.3%
2311.6 1
 
1.3%
4552.86 1
 
1.3%
2255.88 1
 
1.3%
5089.5 1
 
1.3%
4276.08 1
 
1.3%
11187.0 1
 
1.3%
4247.11 1
 
1.3%
Other values (67) 67
85.9%
ValueCountFrequency (%)
518.03 1
1.3%
601.56 1
1.3%
621.0 1
1.3%
634.51 1
1.3%
638.06 1
1.3%
645.48 1
1.3%
651.75 1
1.3%
692.44 1
1.3%
714.24 1
1.3%
730.78 1
1.3%
ValueCountFrequency (%)
94115.02 1
1.3%
36541.63 1
1.3%
36406.3 1
1.3%
31041.71 1
1.3%
21470.87 1
1.3%
21440.38 1
1.3%
21075.06 1
1.3%
20832.6 2
2.6%
20663.1 1
1.3%
20337.0 1
1.3%

석면(자재)면적
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1746.4086
Minimum62.4
Maximum19138.33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T14:24:13.706499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62.4
5-th percentile96.72
Q1239.5725
median702.35
Q31752.0975
95-th percentile6159.7825
Maximum19138.33
Range19075.93
Interquartile range (IQR)1512.525

Descriptive statistics

Standard deviation2986.7146
Coefficient of variation (CV)1.7102038
Kurtosis16.642754
Mean1746.4086
Median Absolute Deviation (MAD)548.36
Skewness3.6660653
Sum136219.87
Variance8920464.1
MonotonicityNot monotonic
2023-12-12T14:24:13.851790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1696.23 1
 
1.3%
1486.15 1
 
1.3%
2691.13 1
 
1.3%
228.45 1
 
1.3%
245.14 1
 
1.3%
747.1 1
 
1.3%
62.4 1
 
1.3%
1566.38 1
 
1.3%
90.6 1
 
1.3%
723.6 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
62.4 1
1.3%
75.21 1
1.3%
90.6 1
1.3%
94.0 1
1.3%
97.2 1
1.3%
98.71 1
1.3%
102.14 1
1.3%
111.6 1
1.3%
117.26 1
1.3%
124.95 1
1.3%
ValueCountFrequency (%)
19138.33 1
1.3%
12996.99 1
1.3%
8902.77 1
1.3%
6877.65 1
1.3%
6033.1 1
1.3%
5376.18 1
1.3%
5289.77 1
1.3%
5212.5 1
1.3%
4608.97 1
1.3%
4393.45 1
1.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-08-22
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-22
2nd row2023-08-22
3rd row2023-08-22
4th row2023-08-22
5th row2023-08-22

Common Values

ValueCountFrequency (%)
2023-08-22 78
100.0%

Length

2023-12-12T14:24:13.984544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:24:14.067436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-22 78
100.0%

Interactions

2023-12-12T14:24:07.030331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:04.761042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.359194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.013788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.528935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.143573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:04.867335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.467040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.131400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.616913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.589414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.002900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.554996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.222851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.720255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.786890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.129242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.716782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.346030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.829852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:07.903398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.235874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:05.881696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.430844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:06.933324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:24:14.129312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호구군건축물명(상호)동명주소위도경도연면적석면(자재)면적
번호1.0000.9500.9560.7930.9720.8580.8620.1610.000
구군0.9501.0001.0000.9861.0000.9000.9240.6200.000
건축물명(상호)0.9561.0001.0000.9920.9960.9970.9960.9730.986
동명0.7930.9860.9921.0000.9790.6560.9231.0000.985
주소0.9721.0000.9960.9791.0001.0001.0000.9400.994
위도0.8580.9000.9970.6561.0001.0000.8630.1040.000
경도0.8620.9240.9960.9231.0000.8631.0000.6160.792
연면적0.1610.6200.9731.0000.9400.1040.6161.0000.662
석면(자재)면적0.0000.0000.9860.9850.9940.0000.7920.6621.000
2023-12-12T14:24:14.275136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호위도경도연면적석면(자재)면적구군
번호1.000-0.1910.2500.0650.1210.716
위도-0.1911.0000.4310.115-0.0710.589
경도0.2500.4311.0000.1130.0100.647
연면적0.0650.1150.1131.0000.5910.291
석면(자재)면적0.121-0.0710.0100.5911.0000.000
구군0.7160.5890.6470.2910.0001.000

Missing values

2023-12-12T14:24:08.065147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:24:08.266368image/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

번호구분구군소유자건축물명(상호)동명주소위도경도석면건축 여부안전관리인 지정여부연면적석면(자재)면적데이터기준일자
01공공건축물강서구부산시부산광역시 체육시설관리사업소실내체육관부산광역시 강서구 체육공원로 43 (대저1동)35.21096128.972217해당지정21440.381696.232023-08-22
12공공건축물강서구부산시녹산협업화사업장녹산협업화사업장부산광역시 강서구 녹산산단 382로 14번길 5535.087117128.853291해당지정12487.05212.52023-08-22
23공공건축물강서구부산시부산환경공단 서부사업소탈수기동부산광역시 강서구 강동신덕1길 13 (강동동)35.196325128.930522해당지정767.075.212023-08-22
34공공건축물강서구부산시부산환경공단 서부사업소관리동부산광역시 강서구 강동신덕1길 13 (강동동)35.196325128.930522해당지정1418.01116.422023-08-22
45공공건축물강서구부산시부산환경공단 명지사업소공장동부산광역시 강서구 명지오션시티 13로 12-11 (공장동)35.090594128.89885해당지정12043.428902.772023-08-22
56공공건축물강서구부산시부산환경공단 녹산사업소관리동부산광역시 강서구 르노삼성대로 14 (신호동)35.088642128.872532해당지정1047.0612.152023-08-22
67공공건축물강서구부산시부산환경공단 녹산사업소탈수기동부산광역시 강서구 녹산산단382로49번길 39 (송정동)35.086631128.863902해당지정2516.0281.442023-08-22
78공공건축물강서구부산시부산환경공단 녹산사업소송풍기동부산광역시 강서구 녹산산단382로49번길 39 (송정동)35.086631128.863902해당지정621.0196.222023-08-22
89공공건축물강서구부산시부산환경공단 녹산사업소방류펌프동부산광역시 강서구 녹산산단382로49번길 39 (송정동)35.086631128.863902해당지정1098.0284.312023-08-22
910공공건축물강서구부산시부산환경공단생곡사업소-관리사무소관리사무소부산광역시 강서구 생곡산단로 88 (생곡동)생곡동35.132012128.878393해당지정814.32171.52023-08-22
번호구분구군소유자건축물명(상호)동명주소위도경도석면건축 여부안전관리인 지정여부연면적석면(자재)면적데이터기준일자
6869공공건축물영도구부산시영도도서관 남항분관영도도서관 남항분관부산광역시 영도구 절영로 71 (남항동2가)35.088609129.038929해당지정7470.34001.492023-08-22
6970공공건축물영도구부산시영도사격장영도사격장부산광역시 영도구 절영로 319 (동삼동)35.073488129.054076해당지정730.78111.62023-08-22
7071공공건축물중구부산시민주공원영주동부산광역시 중구 민주공원길 19 (영주동)35.109687129.02803해당지정20337.0905.362023-08-22
7172공공건축물중구부산시남포지하도상가남포지하도상가부산광역시 중구 구덕로 지하44 (남포동5가)35.098325129.030618해당지정17747.013250.472023-08-22
7273공공건축물중구부산시부산광역시립중앙도서관중구 망양로 193번길 146부산광역시 중구 망양로193번길 146 (보수동1가)35.109975129.026925해당지정6062.02121.662023-08-22
7374공공건축물해운대구부산시시립반송도서관-부산광역시 해운대구 아랫반송로 22 (반송동)35.225064129.14833해당지정1802.71420.02023-08-22
7475공공건축물해운대구부산시체육시설관리사업소요트경기장 프레스센터부산광역시 해운대구 해운대해변로 84 (우동)35.159801129.141956해당지정907.2698.22023-08-22
7576공공건축물해운대구부산시체육시설관리사업소요트경기장 본관부산광역시 해운대구 해운대해변로 84 (우동)35.159801129.141956해당지정6411.96237.752023-08-22
7677공공건축물해운대구부산시부산환경공단 해운대사업소소각동 및 하수처리장부산광역시 해운대구 해운대로 898 (좌동)35.175784129.184939해당지정17862.6612996.992023-08-22
7778공공건축물수영구부산시수산업협동조합수산업협동조합부산광역시 수영구 민락수변로92(민락동)35.1542129.129771해당지정1050.0500.112023-08-22