Overview

Dataset statistics

Number of variables6
Number of observations112
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory52.2 B

Variable types

Text1
Numeric3
Categorical2

Dataset

Description부산광역시 인공어초 설치 현황에 대한 데이터로 관리번호, 설치년도, 설치위치, 어초종류, 설치면적, 시설물량 항목 정보를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/3076269/fileData.do

Alerts

설치년도 is highly overall correlated with 설치면적(헥타르) and 1 other fieldsHigh correlation
설치면적(헥타르) is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
시설물량(개) is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
설치위치 is highly overall correlated with 어초종류High correlation
어초종류 is highly overall correlated with 설치위치High correlation
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:53:48.149392
Analysis finished2023-12-12 18:53:50.456475
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct112
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T03:53:50.846164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.8839286
Min length5

Characters and Unicode

Total characters659
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)100.0%

Sample

1st rowBS-01
2nd rowBS-02
3rd rowBS-03
4th rowBS-04
5th rowBS-05
ValueCountFrequency (%)
2 2
 
1.7%
bs-65 2
 
1.7%
bs-01 1
 
0.9%
bs-69-3 1
 
0.9%
bs-69-2 1
 
0.9%
bs-69-1 1
 
0.9%
bs-68-7 1
 
0.9%
bs-68-6 1
 
0.9%
bs-68-5 1
 
0.9%
bs-68-4 1
 
0.9%
Other values (103) 103
89.6%
2023-12-13T03:53:51.572301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 160
24.3%
B 112
17.0%
S 112
17.0%
7 43
 
6.5%
6 37
 
5.6%
1 33
 
5.0%
2 32
 
4.9%
4 31
 
4.7%
3 30
 
4.6%
5 24
 
3.6%
Other values (4) 45
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 272
41.3%
Uppercase Letter 224
34.0%
Dash Punctuation 160
24.3%
Space Separator 3
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 43
15.8%
6 37
13.6%
1 33
12.1%
2 32
11.8%
4 31
11.4%
3 30
11.0%
5 24
8.8%
0 19
7.0%
8 13
 
4.8%
9 10
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 112
50.0%
S 112
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 160
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 435
66.0%
Latin 224
34.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 160
36.8%
7 43
 
9.9%
6 37
 
8.5%
1 33
 
7.6%
2 32
 
7.4%
4 31
 
7.1%
3 30
 
6.9%
5 24
 
5.5%
0 19
 
4.4%
8 13
 
3.0%
Other values (2) 13
 
3.0%
Latin
ValueCountFrequency (%)
B 112
50.0%
S 112
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 160
24.3%
B 112
17.0%
S 112
17.0%
7 43
 
6.5%
6 37
 
5.6%
1 33
 
5.0%
2 32
 
4.9%
4 31
 
4.7%
3 30
 
4.6%
5 24
 
3.6%
Other values (4) 45
 
6.8%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2009.3661
Minimum1987
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T03:53:51.796272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1987
5-th percentile1992.1
Q12004
median2011
Q32017
95-th percentile2019.45
Maximum2020
Range33
Interquartile range (IQR)13

Descriptive statistics

Standard deviation8.6960647
Coefficient of variation (CV)0.0043277653
Kurtosis-0.28075385
Mean2009.3661
Median Absolute Deviation (MAD)6.5
Skewness-0.73335201
Sum225049
Variance75.621541
MonotonicityIncreasing
2023-12-13T03:53:52.016324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
2019 10
 
8.9%
2017 8
 
7.1%
2018 7
 
6.2%
2016 7
 
6.2%
2015 7
 
6.2%
2004 6
 
5.4%
2020 6
 
5.4%
2002 5
 
4.5%
2005 4
 
3.6%
2010 4
 
3.6%
Other values (23) 48
42.9%
ValueCountFrequency (%)
1987 1
0.9%
1988 2
1.8%
1989 1
0.9%
1990 1
0.9%
1991 1
0.9%
1993 1
0.9%
1994 1
0.9%
1995 1
0.9%
1996 1
0.9%
1997 1
0.9%
ValueCountFrequency (%)
2020 6
5.4%
2019 10
8.9%
2018 7
6.2%
2017 8
7.1%
2016 7
6.2%
2015 7
6.2%
2014 3
 
2.7%
2013 4
 
3.6%
2012 2
 
1.8%
2011 3
 
2.7%

설치위치
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
사하구 남형제도
19 
사하구 목도
17 
해운대 청사포
11 
사하 북형제도
9 
남구 용호
8 
Other values (29)
48 

Length

Max length8
Median length7
Mean length6.2142857
Min length5

Unique

Unique18 ?
Unique (%)16.1%

Sample

1st row해운대 청사포
2nd row해운대 청사포
3rd row해운대 청사포
4th row남구 용호
5th row해운대 청사포

Common Values

ValueCountFrequency (%)
사하구 남형제도 19
17.0%
사하구 목도 17
15.2%
해운대 청사포 11
 
9.8%
사하 북형제도 9
 
8.0%
남구 용호 8
 
7.1%
남구 오륙도 5
 
4.5%
영도구 동삼 5
 
4.5%
사하 목도 4
 
3.6%
기장 동백 2
 
1.8%
사하 서도 2
 
1.8%
Other values (24) 30
26.8%

Length

2023-12-13T03:53:52.249900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사하구 36
16.1%
목도 21
 
9.4%
사하 20
 
9.0%
남형제도 19
 
8.5%
기장 14
 
6.3%
해운대 14
 
6.3%
남구 14
 
6.3%
청사포 12
 
5.4%
북형제도 9
 
4.0%
용호 8
 
3.6%
Other values (31) 56
25.1%

어초종류
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
팔각반구형대형
37 
사각형어초
26 
석재조합식
11 
2단상자형강제
8 
패조류용세라믹
7 
Other values (10)
23 

Length

Max length7
Median length7
Mean length6.1517857
Min length4

Unique

Unique4 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
팔각반구형대형 37
33.0%
사각형어초 26
23.2%
석재조합식 11
 
9.8%
2단상자형강제 8
 
7.1%
패조류용세라믹 7
 
6.2%
팔각반구형중형 7
 
6.2%
반구형어초 4
 
3.6%
패조류용 2
 
1.8%
팔각반구형소형 2
 
1.8%
강제침선어초 2
 
1.8%
Other values (5) 6
 
5.4%

Length

2023-12-13T03:53:52.500613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
팔각반구형대형 37
33.0%
사각형어초 26
23.2%
석재조합식 11
 
9.8%
2단상자형강제 8
 
7.1%
패조류용세라믹 7
 
6.2%
팔각반구형중형 7
 
6.2%
반구형어초 4
 
3.6%
패조류용 2
 
1.8%
팔각반구형소형 2
 
1.8%
강제침선어초 2
 
1.8%
Other values (5) 6
 
5.4%

설치면적(헥타르)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.696429
Minimum4
Maximum176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T03:53:52.712672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4
Q18
median8
Q332
95-th percentile103.2
Maximum176
Range172
Interquartile range (IQR)24

Descriptive statistics

Standard deviation37.505517
Coefficient of variation (CV)1.2629639
Kurtosis3.0034438
Mean29.696429
Median Absolute Deviation (MAD)4
Skewness1.8661993
Sum3326
Variance1406.6638
MonotonicityNot monotonic
2023-12-13T03:53:52.946855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
8 35
31.2%
4 17
15.2%
16 14
 
12.5%
32 12
 
10.7%
64 8
 
7.1%
7 8
 
7.1%
96 5
 
4.5%
80 3
 
2.7%
128 2
 
1.8%
134 1
 
0.9%
Other values (7) 7
 
6.2%
ValueCountFrequency (%)
4 17
15.2%
7 8
 
7.1%
8 35
31.2%
16 14
 
12.5%
20 1
 
0.9%
32 12
 
10.7%
48 1
 
0.9%
64 8
 
7.1%
80 3
 
2.7%
83 1
 
0.9%
ValueCountFrequency (%)
176 1
 
0.9%
160 1
 
0.9%
134 1
 
0.9%
128 2
 
1.8%
112 1
 
0.9%
96 5
4.5%
93 1
 
0.9%
83 1
 
0.9%
80 3
 
2.7%
64 8
7.1%

시설물량(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct37
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130.625
Minimum1
Maximum1150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T03:53:53.239451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q3115.5
95-th percentile600
Maximum1150
Range1149
Interquartile range (IQR)114.5

Descriptive statistics

Standard deviation245.64958
Coefficient of variation (CV)1.8805709
Kurtosis3.6773999
Mean130.625
Median Absolute Deviation (MAD)2
Skewness2.0482107
Sum14630
Variance60343.714
MonotonicityNot monotonic
2023-12-13T03:53:53.618062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 50
44.6%
600 5
 
4.5%
2 5
 
4.5%
4 4
 
3.6%
6 4
 
3.6%
5 3
 
2.7%
27 3
 
2.7%
100 2
 
1.8%
3 2
 
1.8%
8 2
 
1.8%
Other values (27) 32
28.6%
ValueCountFrequency (%)
1 50
44.6%
2 5
 
4.5%
3 2
 
1.8%
4 4
 
3.6%
5 3
 
2.7%
6 4
 
3.6%
8 2
 
1.8%
11 1
 
0.9%
15 1
 
0.9%
19 1
 
0.9%
ValueCountFrequency (%)
1150 1
 
0.9%
980 1
 
0.9%
840 1
 
0.9%
800 1
 
0.9%
700 1
 
0.9%
600 5
4.5%
580 1
 
0.9%
570 1
 
0.9%
520 1
 
0.9%
510 1
 
0.9%

Interactions

2023-12-13T03:53:49.638730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:48.579131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:49.158397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:49.814117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:48.767192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:49.325594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:49.994751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:48.958660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:53:49.493104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:53:53.793387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도설치위치어초종류설치면적(헥타르)시설물량(개)
설치년도1.0000.8860.7680.7070.819
설치위치0.8861.0000.9530.7570.525
어초종류0.7680.9531.0000.1640.325
설치면적(헥타르)0.7070.7570.1641.0000.852
시설물량(개)0.8190.5250.3250.8521.000
2023-12-13T03:53:53.979613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
어초종류설치위치
어초종류1.0000.610
설치위치0.6101.000
2023-12-13T03:53:54.134065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도설치면적(헥타르)시설물량(개)설치위치어초종류
설치년도1.000-0.611-0.8990.5000.404
설치면적(헥타르)-0.6111.0000.5500.3440.055
시설물량(개)-0.8990.5501.0000.1790.119
설치위치0.5000.3440.1791.0000.610
어초종류0.4040.0550.1190.6101.000

Missing values

2023-12-13T03:53:50.205741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:53:50.377981image/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

관리번호설치년도설치위치어초종류설치면적(헥타르)시설물량(개)
0BS-011987해운대 청사포사각형어초96600
1BS-021988해운대 청사포사각형어초64400
2BS-031988해운대 청사포사각형어초32200
3BS-041989남구 용호사각형어초96570
4BS-051990해운대 청사포사각형어초1761150
5BS-061991해운대 청사포사각형어초96600
6BS-071993해운대 청사포사각형어초112700
7BS-081994남구 용호사각형어초83520
8BS-091995남구 용호사각형어초93580
9BS-101996남구 용호사각형어초96600
관리번호설치년도설치위치어초종류설치면적(헥타르)시설물량(개)
102BS-73-22019사하구 남형제도석재조합식81
103BS-73-32019사하구 남형제도석재조합식81
104BS-73-42019사하구 남형제도석재조합식81
105BS-73-52019사하구 남형제도석재조합식81
106BS-74-12020사하구 목도석재조합식81
107BS-74-22020사하구 목도석재조합식81
108BS-74-32020사하구 목도석재조합식81
109BS-74-42020사하구 목도석재조합식81
110BS-74-52020사하구 목도석재조합식81
111BS-74-62020사하구 목도석재조합식81