Overview

Dataset statistics

Number of variables8
Number of observations374
Missing cells75
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory67.4 B

Variable types

Categorical3
Text2
Numeric3

Dataset

Description여수시 관내 인공어초 설치현황(어초종류, 시설년도, 위치 등) 에 대한 데이터로 해당시군명 읍면 리동 확인 수량등의 자료를 제공합니다. 위치 정보값인 위도와 경도의 값으로 위치값을 제공하며 현재 시점 현행화 하여 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15047444/fileData.do

Alerts

시군명 has constant value ""Constant
시설년도 is highly overall correlated with 어초종류High correlation
어초종류 is highly overall correlated with 시설년도High correlation
경도 has 39 (10.4%) missing valuesMissing
확인 수량 has 35 (9.4%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:13:28.243026
Analysis finished2023-12-11 23:13:29.600053
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
여수시
374 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여수시 374
100.0%

Length

2023-12-12T08:13:29.659544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:29.767315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여수시 374
100.0%

읍면
Categorical

Distinct9
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
삼산면
145 
남면
109 
돌산읍
59 
화정면
56 
오촌동
 
1
Other values (4)
 
4

Length

Max length4
Median length3
Mean length2.7085561
Min length2

Unique

Unique5 ?
Unique (%)1.3%

Sample

1st row돌산읍
2nd row돌산읍
3rd row화정면
4th row화정면
5th row화정면

Common Values

ValueCountFrequency (%)
삼산면 145
38.8%
남면 109
29.1%
돌산읍 59
15.8%
화정면 56
 
15.0%
오촌동 1
 
0.3%
화양면 1
 
0.3%
경호 1
 
0.3%
오천동 1
 
0.3%
화정면 1
 
0.3%

Length

2023-12-12T08:13:29.870473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:13:30.021947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼산면 145
38.8%
남면 109
29.1%
돌산읍 59
15.8%
화정면 57
 
15.2%
오촌동 1
 
0.3%
화양면 1
 
0.3%
경호 1
 
0.3%
오천동 1
 
0.3%

리동
Text

Distinct107
Distinct (%)28.7%
Missing1
Missing (%)0.3%
Memory size3.1 KiB
2023-12-12T08:13:30.300789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length2
Mean length2.6648794
Min length2

Characters and Unicode

Total characters994
Distinct characters87
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)15.0%

Sample

1st row금성
2nd row금성
3rd row하화
4th row하화
5th row하화
ValueCountFrequency (%)
동도 30
 
8.0%
서도 21
 
5.6%
유송 19
 
5.1%
손죽 15
 
4.0%
신기 11
 
2.9%
덕촌 11
 
2.9%
대동a 10
 
2.7%
연도2 10
 
2.7%
작금 10
 
2.7%
두모 9
 
2.4%
Other values (97) 227
60.9%
2023-12-12T08:13:30.728079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 110
 
11.1%
동 48
 
4.8%
유 42
 
4.2%
지 41
 
4.1%
송 36
 
3.6%
단 36
 
3.6%
두 35
 
3.5%
금 35
 
3.5%
서 31
 
3.1%
촌 30
 
3.0%
Other values (77) 550
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 857
86.2%
Decimal Number 62
 
6.2%
Uppercase Letter 48
 
4.8%
Close Punctuation 10
 
1.0%
Open Punctuation 10
 
1.0%
Space Separator 4
 
0.4%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 110
 
12.8%
동 48
 
5.6%
유 42
 
4.9%
지 41
 
4.8%
송 36
 
4.2%
단 36
 
4.2%
두 35
 
4.1%
금 35
 
4.1%
서 31
 
3.6%
촌 30
 
3.5%
Other values (64) 413
48.2%
Decimal Number
ValueCountFrequency (%)
2 24
38.7%
1 20
32.3%
3 9
 
14.5%
4 5
 
8.1%
5 2
 
3.2%
6 2
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
A 25
52.1%
B 16
33.3%
C 7
 
14.6%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 857
86.2%
Common 89
 
9.0%
Latin 48
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 110
 
12.8%
동 48
 
5.6%
유 42
 
4.9%
지 41
 
4.8%
송 36
 
4.2%
단 36
 
4.2%
두 35
 
4.1%
금 35
 
4.1%
서 31
 
3.6%
촌 30
 
3.5%
Other values (64) 413
48.2%
Common
ValueCountFrequency (%)
2 24
27.0%
1 20
22.5%
) 10
11.2%
( 10
11.2%
3 9
 
10.1%
4 5
 
5.6%
4
 
4.5%
, 3
 
3.4%
5 2
 
2.2%
6 2
 
2.2%
Latin
ValueCountFrequency (%)
A 25
52.1%
B 16
33.3%
C 7
 
14.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 857
86.2%
ASCII 137
 
13.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 110
 
12.8%
동 48
 
5.6%
유 42
 
4.9%
지 41
 
4.8%
송 36
 
4.2%
단 36
 
4.2%
두 35
 
4.1%
금 35
 
4.1%
서 31
 
3.6%
촌 30
 
3.5%
Other values (64) 413
48.2%
ASCII
ValueCountFrequency (%)
A 25
18.2%
2 24
17.5%
1 20
14.6%
B 16
11.7%
) 10
 
7.3%
( 10
 
7.3%
3 9
 
6.6%
C 7
 
5.1%
4 5
 
3.6%
4
 
2.9%
Other values (3) 7
 
5.1%

어초종류
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
사각형어초
80 
테트라형
46 
2단상자형강제어초
25 
강제침선어초
24 
육교형어초
24 
Other values (30)
175 

Length

Max length11
Median length9
Mean length6.0935829
Min length2

Unique

Unique4 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
사각형어초 80
21.4%
테트라형 46
12.3%
2단상자형강제어초 25
 
6.7%
강제침선어초 24
 
6.4%
육교형어초 24
 
6.4%
사각전주어초 18
 
4.8%
뿔삼각형어초 14
 
3.7%
연약지반용강제어초 12
 
3.2%
반구형어초 11
 
2.9%
강제증식어초 10
 
2.7%
Other values (25) 110
29.4%

Length

2023-12-12T08:13:30.902930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사각형어초 80
21.4%
테트라형 46
12.3%
2단상자형강제어초 25
 
6.7%
강제침선어초 24
 
6.4%
육교형어초 24
 
6.4%
사각전주어초 18
 
4.8%
뿔삼각형어초 14
 
3.7%
연약지반용강제어초 12
 
3.2%
반구형어초 11
 
2.9%
강제증식어초 10
 
2.7%
Other values (25) 110
29.4%

시설년도
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.1711
Minimum1971
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T08:13:31.027643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1971
5-th percentile1998
Q12002
median2004
Q32010
95-th percentile2019
Maximum2020
Range49
Interquartile range (IQR)8

Descriptive statistics

Standard deviation7.3161191
Coefficient of variation (CV)0.0036468071
Kurtosis2.7146642
Mean2006.1711
Median Absolute Deviation (MAD)3
Skewness-0.2523259
Sum750308
Variance53.525598
MonotonicityNot monotonic
2023-12-12T08:13:31.163890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2002 56
15.0%
2004 48
12.8%
2003 35
 
9.4%
2019 25
 
6.7%
2001 22
 
5.9%
2008 17
 
4.5%
2005 15
 
4.0%
2010 15
 
4.0%
2000 15
 
4.0%
2020 14
 
3.7%
Other values (17) 112
29.9%
ValueCountFrequency (%)
1971 2
 
0.5%
1981 3
 
0.8%
1995 1
 
0.3%
1997 9
 
2.4%
1998 13
 
3.5%
1999 4
 
1.1%
2000 15
 
4.0%
2001 22
 
5.9%
2002 56
15.0%
2003 35
9.4%
ValueCountFrequency (%)
2020 14
3.7%
2019 25
6.7%
2018 10
 
2.7%
2017 3
 
0.8%
2016 5
 
1.3%
2015 6
 
1.6%
2014 8
 
2.1%
2013 6
 
1.6%
2012 1
 
0.3%
2011 11
2.9%

위도
Text

Distinct363
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T08:13:31.504796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length11
Mean length11.352941
Min length5

Characters and Unicode

Total characters4246
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique353 ?
Unique (%)94.4%

Sample

1st row34.58471667
2nd row34.58995
3rd row34.60186667
4th row34.60345
5th row34.60463333
ValueCountFrequency (%)
34° 4
 
1.0%
127° 4
 
1.0%
34.54188333 3
 
0.7%
34.75944444 2
 
0.5%
34.57166667 2
 
0.5%
34.23203333 2
 
0.5%
34.55076667 2
 
0.5%
34.56063333 2
 
0.5%
34.31944444 2
 
0.5%
34.48506667 2
 
0.5%
Other values (394) 396
94.1%
2023-12-12T08:13:32.009253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 910
21.4%
4 590
13.9%
6 433
10.2%
. 413
9.7%
5 293
 
6.9%
7 289
 
6.8%
1 256
 
6.0%
0 240
 
5.7%
8 204
 
4.8%
2 202
 
4.8%
Other values (6) 416
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3551
83.6%
Other Punctuation 491
 
11.6%
Other Symbol 78
 
1.8%
Uppercase Letter 78
 
1.8%
Space Separator 48
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 910
25.6%
4 590
16.6%
6 433
12.2%
5 293
 
8.3%
7 289
 
8.1%
1 256
 
7.2%
0 240
 
6.8%
8 204
 
5.7%
2 202
 
5.7%
9 134
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 413
84.1%
′ 78
 
15.9%
Uppercase Letter
ValueCountFrequency (%)
N 39
50.0%
E 39
50.0%
Other Symbol
ValueCountFrequency (%)
° 78
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4168
98.2%
Latin 78
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3 910
21.8%
4 590
14.2%
6 433
10.4%
. 413
9.9%
5 293
 
7.0%
7 289
 
6.9%
1 256
 
6.1%
0 240
 
5.8%
8 204
 
4.9%
2 202
 
4.8%
Other values (4) 338
 
8.1%
Latin
ValueCountFrequency (%)
N 39
50.0%
E 39
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4090
96.3%
None 78
 
1.8%
Punctuation 78
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 910
22.2%
4 590
14.4%
6 433
10.6%
. 413
10.1%
5 293
 
7.2%
7 289
 
7.1%
1 256
 
6.3%
0 240
 
5.9%
8 204
 
5.0%
2 202
 
4.9%
Other values (4) 260
 
6.4%
None
ValueCountFrequency (%)
° 78
100.0%
Punctuation
ValueCountFrequency (%)
′ 78
100.0%

경도
Real number (ℝ)

MISSING 

Distinct317
Distinct (%)94.6%
Missing39
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean127.58279
Minimum127.21123
Maximum127.89889
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T08:13:32.202369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.21123
5-th percentile127.26818
Q1127.35776
median127.6983
Q3127.75583
95-th percentile127.80551
Maximum127.89889
Range0.6876556
Interquartile range (IQR)0.398075

Descriptive statistics

Standard deviation0.20351396
Coefficient of variation (CV)0.0015951522
Kurtosis-1.4170556
Mean127.58279
Median Absolute Deviation (MAD)0.1063
Skewness-0.45628458
Sum42740.235
Variance0.041417934
MonotonicityNot monotonic
2023-12-12T08:13:32.371778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.7327778 2
 
0.5%
127.74165 2
 
0.5%
127.6424 2
 
0.5%
127.3182667 2
 
0.5%
127.7650833 2
 
0.5%
127.2665333 2
 
0.5%
127.64475 2
 
0.5%
127.7997167 2
 
0.5%
127.80815 2
 
0.5%
127.2827667 2
 
0.5%
Other values (307) 315
84.2%
(Missing) 39
 
10.4%
ValueCountFrequency (%)
127.2112333 1
0.3%
127.21455 1
0.3%
127.2230833 2
0.5%
127.2234833 1
0.3%
127.2239 1
0.3%
127.2247667 1
0.3%
127.2254833 1
0.3%
127.22585 1
0.3%
127.24235 1
0.3%
127.2663167 1
0.3%
ValueCountFrequency (%)
127.8988889 1
0.3%
127.8897222 1
0.3%
127.8308333 1
0.3%
127.8227167 1
0.3%
127.8155833 1
0.3%
127.8082 2
0.5%
127.80815 2
0.5%
127.8081333 1
0.3%
127.8078667 1
0.3%
127.8078333 1
0.3%

확인 수량
Real number (ℝ)

MISSING 

Distinct119
Distinct (%)35.1%
Missing35
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean75.610619
Minimum1
Maximum1190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-12T08:13:32.565473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median34
Q3100
95-th percentile240.4
Maximum1190
Range1189
Interquartile range (IQR)99

Descriptive statistics

Standard deviation124.47723
Coefficient of variation (CV)1.646293
Kurtosis36.319587
Mean75.610619
Median Absolute Deviation (MAD)33
Skewness5.0089887
Sum25632
Variance15494.582
MonotonicityNot monotonic
2023-12-12T08:13:32.756018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 94
25.1%
100 23
 
6.1%
3 11
 
2.9%
24 7
 
1.9%
166 6
 
1.6%
208 5
 
1.3%
32 5
 
1.3%
101 5
 
1.3%
200 5
 
1.3%
102 4
 
1.1%
Other values (109) 174
46.5%
(Missing) 35
 
9.4%
ValueCountFrequency (%)
1 94
25.1%
2 3
 
0.8%
3 11
 
2.9%
5 2
 
0.5%
6 1
 
0.3%
7 1
 
0.3%
8 1
 
0.3%
10 3
 
0.8%
11 2
 
0.5%
12 3
 
0.8%
ValueCountFrequency (%)
1190 1
0.3%
1119 1
0.3%
800 1
0.3%
500 1
0.3%
498 1
0.3%
493 1
0.3%
359 1
0.3%
330 1
0.3%
328 1
0.3%
315 1
0.3%

Interactions

2023-12-12T08:13:29.037099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.518879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.787364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:29.120033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.604246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.868274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:29.209581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.701927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:13:28.952107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:13:32.876603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면어초종류시설년도경도확인 수량
읍면1.0000.7200.3700.7410.119
어초종류0.7201.0000.9050.8200.396
시설년도0.3700.9051.0000.4410.512
경도0.7410.8200.4411.0000.292
확인 수량0.1190.3960.5120.2921.000
2023-12-12T08:13:33.007054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면어초종류
읍면1.0000.350
어초종류0.3501.000
2023-12-12T08:13:33.422646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설년도경도확인 수량읍면어초종류
시설년도1.000-0.0890.0120.1900.583
경도-0.0891.0000.0380.4550.442
확인 수량0.0120.0381.0000.0620.165
읍면0.1900.4550.0621.0000.350
어초종류0.5830.4420.1650.3501.000

Missing values

2023-12-12T08:13:29.312996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:13:29.420086image/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.
2023-12-12T08:13:29.538643image/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

시군명읍면리동어초종류시설년도위도경도확인 수량
0여수시돌산읍금성사각형어초197134.58471667127.79128344
1여수시돌산읍금성반원가지형어초197134.58995127.80813355
2여수시화정면하화사각형어초198134.60186667127.63311788
3여수시화정면하화사각형어초198134.60345127.63386758
4여수시화정면하화사각형어초198134.60463333127.63386798
5여수시화정면제도반구형어초199534.60461667127.656383252
6여수시돌산읍신기육교형어초199734.5908127.75828339
7여수시돌산읍신기육교형어초199734.59218333127.75398344
8여수시돌산읍신기육교형어초199734.59241667127.7494557
9여수시돌산읍신기육교형어초199734.59228333127.7487518
시군명읍면리동어초종류시설년도위도경도확인 수량
364여수시삼산면유촌테트라형202034°03.616′N 127°18.155′E<NA><NA>
365여수시삼산면유촌테트라형202034°03.649′N 127°18.070′E<NA><NA>
366여수시삼산면덕촌테트라형202034°01.134′N 127°19.318′E<NA>3
367여수시삼산면덕촌테트라형202034°01.099′N 127°19.587′E<NA><NA>
368여수시삼산면덕촌테트라형202034°00.811′N 127°19.741′E<NA><NA>
369여수시삼산면덕촌테트라형202034°00.648′N 127°19.714′E<NA><NA>
370여수시삼산면덕촌테트라형202034°00.667′N 127°19.647′E<NA><NA>
371여수시삼산면덕촌테트라형202034°00.812′N 127°19.617′E<NA><NA>
372여수시삼산면덕촌테트라형202034°00.978′N 127°19.456′E<NA><NA>
373여수시삼산면덕촌테트라형202034°00.997′N 127°19.275′E<NA><NA>