Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory595.8 KiB
Average record size in memory61.0 B

Variable types

Numeric4
Text1
Categorical2

Dataset

Description어선 항적도는 어선이 항해하는 경로와 위치를 기록하는 지도나 차트를 말합니다. 이는 어부나 선장들이 바다에서 항해할 때 어디를 가야 하는지, 어떤 경로를 피해야 하는지 등을 파악하기 위해 사용됩니다.
Author해양수산부
URLhttps://www.data.go.kr/data/15126806/fileData.do

Alerts

낚시어선여부 has constant value ""Constant
낚시어선여부명 has constant value ""Constant
어선길이(KM) is highly overall correlated with 어선너비(KM) and 1 other fieldsHigh correlation
어선너비(KM) is highly overall correlated with 어선길이(KM) and 1 other fieldsHigh correlation
어선톤수(톤) is highly overall correlated with 어선길이(KM) and 1 other fieldsHigh correlation
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 17:03:05.862738
Analysis finished2024-03-14 17:03:12.072827
Duration6.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5000.5
Minimum1
Maximum10000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-03-15T02:03:12.296479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile500.95
Q12500.75
median5000.5
Q37500.25
95-th percentile9500.05
Maximum10000
Range9999
Interquartile range (IQR)4999.5

Descriptive statistics

Standard deviation2886.8957
Coefficient of variation (CV)0.5773214
Kurtosis-1.2
Mean5000.5
Median Absolute Deviation (MAD)2500
Skewness0
Sum50005000
Variance8334166.7
MonotonicityStrictly increasing
2024-03-15T02:03:12.666883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
6672 1
 
< 0.1%
6665 1
 
< 0.1%
6666 1
 
< 0.1%
6667 1
 
< 0.1%
6668 1
 
< 0.1%
6669 1
 
< 0.1%
6670 1
 
< 0.1%
6671 1
 
< 0.1%
6673 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
10000 1
< 0.1%
9999 1
< 0.1%
9998 1
< 0.1%
9997 1
< 0.1%
9996 1
< 0.1%
9995 1
< 0.1%
9994 1
< 0.1%
9993 1
< 0.1%
9992 1
< 0.1%
9991 1
< 0.1%

암호화된어선아이디
Text

Distinct6205
Distinct (%)62.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
2024-03-15T02:03:13.617846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120000
Distinct characters26
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

Unique2629 ?
Unique (%)26.3%

Sample

1st rowMzYwMTYxNTA=
2nd rowMzYxMTAyMDE=
3rd rowMzYyMDIwNzE=
4th rowMzYzMTA3Mjc=
5th rowMzYzMTAxMTA=
ValueCountFrequency (%)
mze3mdi0mda 4
 
< 0.1%
mzywmdyynjc 4
 
< 0.1%
mzyymdq3mzy 4
 
< 0.1%
mzqxmdaxodu 4
 
< 0.1%
mzewmta2ndm 4
 
< 0.1%
mzexmdayndm 4
 
< 0.1%
mzqymda3mte 4
 
< 0.1%
mzyzmdg1nja 3
 
< 0.1%
mzyxmdiymju 3
 
< 0.1%
mzewmdgznty 3
 
< 0.1%
Other values (6195) 9963
99.6%
2024-03-15T02:03:15.057041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 26394
22.0%
z 15098
12.6%
D 11018
 
9.2%
= 10000
 
8.3%
Y 5408
 
4.5%
A 5084
 
4.2%
w 5064
 
4.2%
E 5063
 
4.2%
T 5045
 
4.2%
N 3983
 
3.3%
Other values (16) 27843
23.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 71858
59.9%
Lowercase Letter 32334
26.9%
Math Symbol 10000
 
8.3%
Decimal Number 5808
 
4.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 26394
36.7%
D 11018
15.3%
Y 5408
 
7.5%
A 5084
 
7.1%
E 5063
 
7.0%
T 5045
 
7.0%
N 3983
 
5.5%
I 2984
 
4.2%
Q 2639
 
3.7%
U 2218
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
z 15098
46.7%
w 5064
 
15.7%
x 3362
 
10.4%
y 2598
 
8.0%
j 2007
 
6.2%
g 1455
 
4.5%
k 1426
 
4.4%
c 1324
 
4.1%
Decimal Number
ValueCountFrequency (%)
0 1343
23.1%
3 1295
22.3%
2 946
16.3%
1 907
15.6%
4 692
11.9%
5 625
10.8%
Math Symbol
ValueCountFrequency (%)
= 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 104192
86.8%
Common 15808
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 26394
25.3%
z 15098
14.5%
D 11018
10.6%
Y 5408
 
5.2%
A 5084
 
4.9%
w 5064
 
4.9%
E 5063
 
4.9%
T 5045
 
4.8%
N 3983
 
3.8%
x 3362
 
3.2%
Other values (9) 18673
17.9%
Common
ValueCountFrequency (%)
= 10000
63.3%
0 1343
 
8.5%
3 1295
 
8.2%
2 946
 
6.0%
1 907
 
5.7%
4 692
 
4.4%
5 625
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 26394
22.0%
z 15098
12.6%
D 11018
 
9.2%
= 10000
 
8.3%
Y 5408
 
4.5%
A 5084
 
4.2%
w 5064
 
4.2%
E 5063
 
4.2%
T 5045
 
4.2%
N 3983
 
3.3%
Other values (16) 27843
23.2%

낚시어선여부
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2024-03-15T02:03:15.476765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:03:15.933987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

낚시어선여부명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
어선
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어선 10000
100.0%

Length

2024-03-15T02:03:16.130209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:03:16.349448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어선 10000
100.0%

어선길이(KM)
Real number (ℝ)

HIGH CORRELATION 

Distinct1364
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.962136
Minimum3.51
Maximum44.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-03-15T02:03:16.669093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.51
5-th percentile6.21
Q18.15
median10.4
Q314.45
95-th percentile23.2515
Maximum44.19
Range40.68
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation5.348219
Coefficient of variation (CV)0.44709565
Kurtosis1.7629068
Mean11.962136
Median Absolute Deviation (MAD)2.91
Skewness1.3455672
Sum119621.36
Variance28.603447
MonotonicityNot monotonic
2024-03-15T02:03:17.125725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.5 85
 
0.9%
14.5 79
 
0.8%
9.0 77
 
0.8%
6.48 74
 
0.7%
10.8 66
 
0.7%
8.37 64
 
0.6%
11.9 60
 
0.6%
7.9 59
 
0.6%
8.1 56
 
0.6%
8.0 56
 
0.6%
Other values (1354) 9324
93.2%
ValueCountFrequency (%)
3.51 1
 
< 0.1%
3.66 1
 
< 0.1%
3.76 1
 
< 0.1%
3.78 2
 
< 0.1%
3.98 1
 
< 0.1%
4.08 6
0.1%
4.37 1
 
< 0.1%
4.39 1
 
< 0.1%
4.43 1
 
< 0.1%
4.46 2
 
< 0.1%
ValueCountFrequency (%)
44.19 1
 
< 0.1%
41.83 2
< 0.1%
36.39 2
< 0.1%
35.15 4
< 0.1%
34.98 1
 
< 0.1%
33.81 2
< 0.1%
33.78 4
< 0.1%
33.64 2
< 0.1%
33.56 3
< 0.1%
33.25 2
< 0.1%

어선너비(KM)
Real number (ℝ)

HIGH CORRELATION 

Distinct460
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.354326
Minimum1.35
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-03-15T02:03:17.560488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.35
5-th percentile1.88
Q12.38
median3.1
Q34.14
95-th percentile5.77
Maximum8
Range6.65
Interquartile range (IQR)1.76

Descriptive statistics

Standard deviation1.2110179
Coefficient of variation (CV)0.36103167
Kurtosis0.26115865
Mean3.354326
Median Absolute Deviation (MAD)0.82
Skewness0.86656974
Sum33543.26
Variance1.4665644
MonotonicityNot monotonic
2024-03-15T02:03:18.097377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.0 210
 
2.1%
2.6 197
 
2.0%
4.5 152
 
1.5%
2.78 106
 
1.1%
2.18 97
 
1.0%
3.85 96
 
1.0%
2.77 93
 
0.9%
2.2 91
 
0.9%
2.4 90
 
0.9%
2.28 90
 
0.9%
Other values (450) 8778
87.8%
ValueCountFrequency (%)
1.35 1
 
< 0.1%
1.36 1
 
< 0.1%
1.44 1
 
< 0.1%
1.45 2
 
< 0.1%
1.46 2
 
< 0.1%
1.47 2
 
< 0.1%
1.51 5
0.1%
1.53 2
 
< 0.1%
1.54 5
0.1%
1.55 2
 
< 0.1%
ValueCountFrequency (%)
8.0 1
 
< 0.1%
7.8 2
 
< 0.1%
7.7 6
 
0.1%
7.6 2
 
< 0.1%
7.5 13
0.1%
7.4 6
 
0.1%
7.3 5
 
0.1%
7.2 4
 
< 0.1%
7.15 2
 
< 0.1%
7.0 29
0.3%

어선톤수(톤)
Real number (ℝ)

HIGH CORRELATION 

Distinct668
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.394591
Minimum0.23
Maximum235
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size88.0 KiB
2024-03-15T02:03:18.436882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.23
5-th percentile1.07
Q12.46
median4.95
Q39.77
95-th percentile35
Maximum235
Range234.77
Interquartile range (IQR)7.31

Descriptive statistics

Standard deviation14.726054
Coefficient of variation (CV)1.5675034
Kurtosis28.310838
Mean9.394591
Median Absolute Deviation (MAD)2.98
Skewness4.3362589
Sum93945.91
Variance216.85666
MonotonicityNot monotonic
2024-03-15T02:03:18.688978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.77 1260
 
12.6%
7.93 612
 
6.1%
4.99 331
 
3.3%
2.99 328
 
3.3%
29.0 283
 
2.8%
3.0 216
 
2.2%
6.67 211
 
2.1%
24.0 186
 
1.9%
7.31 157
 
1.6%
1.99 98
 
1.0%
Other values (658) 6318
63.2%
ValueCountFrequency (%)
0.23 3
< 0.1%
0.27 1
 
< 0.1%
0.31 1
 
< 0.1%
0.34 6
0.1%
0.36 1
 
< 0.1%
0.37 1
 
< 0.1%
0.4 3
< 0.1%
0.41 2
 
< 0.1%
0.43 2
 
< 0.1%
0.44 2
 
< 0.1%
ValueCountFrequency (%)
235.0 2
 
< 0.1%
153.95 2
 
< 0.1%
143.0 1
 
< 0.1%
141.97 2
 
< 0.1%
139.0 7
 
0.1%
99.73 2
 
< 0.1%
99.0 1
 
< 0.1%
98.0 2
 
< 0.1%
89.0 45
0.4%
85.0 8
 
0.1%

Interactions

2024-03-15T02:03:10.596788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:06.665574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:08.247637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:09.570036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:10.755487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:07.112871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:08.539582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:09.845482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:10.930830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:07.651766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:08.836756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:10.210824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:11.137768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:07.970721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:09.163766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T02:03:10.438804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:03:18.843179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호어선길이(KM)어선너비(KM)어선톤수(톤)
일련번호1.0000.2320.2390.065
어선길이(KM)0.2321.0000.9110.840
어선너비(KM)0.2390.9111.0000.717
어선톤수(톤)0.0650.8400.7171.000
2024-03-15T02:03:19.005621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호어선길이(KM)어선너비(KM)어선톤수(톤)
일련번호1.000-0.015-0.030-0.012
어선길이(KM)-0.0151.0000.9520.984
어선너비(KM)-0.0300.9521.0000.957
어선톤수(톤)-0.0120.9840.9571.000

Missing values

2024-03-15T02:03:11.498870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:03:11.900133image/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

일련번호암호화된어선아이디낚시어선여부낚시어선여부명어선길이(KM)어선너비(KM)어선톤수(톤)
01MzYwMTYxNTA=0어선8.52.782.99
12MzYxMTAyMDE=0어선8.73.022.81
23MzYyMDIwNzE=0어선4.081.610.34
34MzYzMTA3Mjc=0어선15.84.259.77
45MzYzMTAxMTA=0어선9.02.772.99
56MzEwMDAzNzE=0어선9.43.14.37
67MzEwMDExNTk=0어선8.642.22.22
78MzMyMDA2NDY=0어선25.025.146.0
89MzUyMDA0NzE=0어선24.895.2840.0
910MzYwMTU3NDc=0어선11.03.524.99
일련번호암호화된어선아이디낚시어선여부낚시어선여부명어선길이(KM)어선너비(KM)어선톤수(톤)
99909991MzYwMDI1Nzg=0어선8.542.383.0
99919992MzYwMDIxMDI=0어선10.262.864.99
99929993MzYwMDI2MzE=0어선10.223.364.92
99939994MzYwMDI2MzY=0어선10.223.424.83
99949995MzYwMDI2NDA=0어선6.841.951.59
99959996MzYwMDI2OTE=0어선7.562.162.28
99969997MzYwMDYyODE=0어선9.953.084.93
99979998MzYwMDYzNzM=0어선9.13.024.0
99989999MzYwMDI3MDY=0어선7.21.731.3
999910000MzYwMDI3MDc=0어선8.042.181.99