Overview

Dataset statistics

Number of variables8
Number of observations507
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.8 KiB
Average record size in memory70.3 B

Variable types

Categorical2
Numeric5
Text1

Dataset

Description전국 VTS 관제구역도에 대한 데이터로서 구분,지점번호,위도(도),위도(분),위도(초),경도(도),경도(분),경도(초) 등의 항목을 제공합니다.
Author해양경찰청
URLhttps://www.data.go.kr/data/15013201/fileData.do

Alerts

경도(도) is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 경도(도) and 1 other fieldsHigh correlation
위도(도) is highly overall correlated with 구분High correlation
위도(분) has 19 (3.7%) zerosZeros
위도(초) has 59 (11.6%) zerosZeros
경도(분) has 18 (3.6%) zerosZeros

Reproduction

Analysis started2023-12-12 03:05:21.337170
Analysis finished2023-12-12 03:05:25.876983
Duration4.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
여수광양항구역
66 
부산항구역
52 
완도항구역
49 
통영연안구역
33 
대산항구역
31 
Other values (30)
276 

Length

Max length9
Median length8
Mean length5.9704142
Min length5

Unique

Unique12 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
여수광양항구역 66
13.0%
부산항구역 52
 
10.3%
완도항구역 49
 
9.7%
통영연안구역 33
 
6.5%
대산항구역 31
 
6.1%
평택당진구역 29
 
5.7%
인천항구역 27
 
5.3%
목포항구역(2) 24
 
4.7%
포항항구역 22
 
4.3%
부산신항구역 22
 
4.3%
Other values (25) 152
30.0%

Length

2023-12-12T12:05:25.998677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수광양항구역 66
13.0%
부산항구역 52
 
10.3%
완도항구역 49
 
9.7%
통영연안구역 33
 
6.5%
대산항구역 31
 
6.1%
평택당진구역 29
 
5.7%
인천항구역 27
 
5.3%
목포항구역(2 24
 
4.7%
포항항구역 22
 
4.3%
부산신항구역 22
 
4.3%
Other values (25) 152
30.0%

지점번호
Real number (ℝ)

Distinct66
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.086785
Minimum1
Maximum66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T12:05:26.198085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3
Q15
median12
Q325
95-th percentile47.7
Maximum66
Range65
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.949598
Coefficient of variation (CV)0.87492164
Kurtosis0.51133398
Mean17.086785
Median Absolute Deviation (MAD)8
Skewness1.1324806
Sum8663
Variance223.49048
MonotonicityNot monotonic
2023-12-12T12:05:26.398238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 26
 
5.1%
4 26
 
5.1%
2 26
 
5.1%
3 26
 
5.1%
5 25
 
4.9%
6 23
 
4.5%
7 22
 
4.3%
8 18
 
3.6%
9 18
 
3.6%
11 18
 
3.6%
Other values (56) 279
55.0%
ValueCountFrequency (%)
1 26
5.1%
2 26
5.1%
3 26
5.1%
4 26
5.1%
5 25
4.9%
6 23
4.5%
7 22
4.3%
8 18
3.6%
9 18
3.6%
10 18
3.6%
ValueCountFrequency (%)
66 1
0.2%
65 1
0.2%
64 1
0.2%
63 1
0.2%
62 1
0.2%
61 1
0.2%
60 1
0.2%
59 1
0.2%
58 1
0.2%
57 1
0.2%

위도(도)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
34
236 
37
106 
35
92 
36
58 
33
 
15

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row37
2nd row37
3rd row37
4th row37
5th row37

Common Values

ValueCountFrequency (%)
34 236
46.5%
37 106
20.9%
35 92
 
18.1%
36 58
 
11.4%
33 15
 
3.0%

Length

2023-12-12T12:05:26.567415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:05:26.693704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
34 236
46.5%
37 106
20.9%
35 92
 
18.1%
36 58
 
11.4%
33 15
 
3.0%

위도(분)
Real number (ℝ)

ZEROS 

Distinct60
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.877712
Minimum0
Maximum59
Zeros19
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T12:05:26.847892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q18
median26
Q348
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)40

Descriptive statistics

Standard deviation19.781335
Coefficient of variation (CV)0.70957528
Kurtosis-1.5102101
Mean27.877712
Median Absolute Deviation (MAD)19
Skewness0.091734676
Sum14134
Variance391.30122
MonotonicityNot monotonic
2023-12-12T12:05:27.038938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
51 31
 
6.1%
19 24
 
4.7%
4 21
 
4.1%
3 21
 
4.1%
0 19
 
3.7%
7 18
 
3.6%
5 17
 
3.4%
45 16
 
3.2%
50 14
 
2.8%
54 14
 
2.8%
Other values (50) 312
61.5%
ValueCountFrequency (%)
0 19
3.7%
1 8
 
1.6%
2 11
2.2%
3 21
4.1%
4 21
4.1%
5 17
3.4%
6 11
2.2%
7 18
3.6%
8 11
2.2%
9 4
 
0.8%
ValueCountFrequency (%)
59 8
 
1.6%
58 14
2.8%
57 6
 
1.2%
56 11
 
2.2%
55 8
 
1.6%
54 14
2.8%
53 8
 
1.6%
52 3
 
0.6%
51 31
6.1%
50 14
2.8%

위도(초)
Real number (ℝ)

ZEROS 

Distinct134
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.058718
Minimum0
Maximum59.9
Zeros59
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T12:05:27.240458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112
median30
Q345
95-th percentile54.442
Maximum59.9
Range59.9
Interquartile range (IQR)33

Descriptive statistics

Standard deviation18.413903
Coefficient of variation (CV)0.65626317
Kurtosis-1.2671532
Mean28.058718
Median Absolute Deviation (MAD)16
Skewness-0.10843783
Sum14225.77
Variance339.07184
MonotonicityNot monotonic
2023-12-12T12:05:27.446783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 59
 
11.6%
30.0 24
 
4.7%
24.0 16
 
3.2%
32.0 14
 
2.8%
45.0 14
 
2.8%
36.0 13
 
2.6%
12.0 12
 
2.4%
47.0 10
 
2.0%
41.0 10
 
2.0%
48.0 9
 
1.8%
Other values (124) 326
64.3%
ValueCountFrequency (%)
0.0 59
11.6%
0.9 1
 
0.2%
1.0 4
 
0.8%
1.32 1
 
0.2%
2.0 4
 
0.8%
2.5 1
 
0.2%
2.8 1
 
0.2%
3.0 6
 
1.2%
4.0 3
 
0.6%
4.1 2
 
0.4%
ValueCountFrequency (%)
59.9 1
 
0.2%
59.6 2
0.4%
59.49 1
 
0.2%
59.0 3
0.6%
58.8 1
 
0.2%
58.0 3
0.6%
57.4 1
 
0.2%
57.0 2
0.4%
56.7 1
 
0.2%
56.3 1
 
0.2%

경도(도)
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.93688
Minimum124
Maximum129
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T12:05:27.600431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum124
5-th percentile125.3
Q1126
median126
Q3128
95-th percentile129
Maximum129
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2667692
Coefficient of variation (CV)0.0099795199
Kurtosis-0.88648593
Mean126.93688
Median Absolute Deviation (MAD)1
Skewness0.34735325
Sum64357
Variance1.6047041
MonotonicityNot monotonic
2023-12-12T12:05:27.740595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
126 232
45.8%
129 89
 
17.6%
128 82
 
16.2%
127 78
 
15.4%
125 18
 
3.6%
124 8
 
1.6%
ValueCountFrequency (%)
124 8
 
1.6%
125 18
 
3.6%
126 232
45.8%
127 78
 
15.4%
128 82
 
16.2%
129 89
 
17.6%
ValueCountFrequency (%)
129 89
 
17.6%
128 82
 
16.2%
127 78
 
15.4%
126 232
45.8%
125 18
 
3.6%
124 8
 
1.6%

경도(분)
Real number (ℝ)

ZEROS 

Distinct59
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.566075
Minimum0
Maximum59
Zeros18
Zeros (%)3.6%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2023-12-12T12:05:27.910903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q116
median29
Q344
95-th percentile51
Maximum59
Range59
Interquartile range (IQR)28

Descriptive statistics

Standard deviation16.537927
Coefficient of variation (CV)0.57893593
Kurtosis-1.0979499
Mean28.566075
Median Absolute Deviation (MAD)15
Skewness-0.14857439
Sum14483
Variance273.50304
MonotonicityNot monotonic
2023-12-12T12:05:28.065916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 26
 
5.1%
44 22
 
4.3%
0 18
 
3.6%
43 17
 
3.4%
46 16
 
3.2%
26 15
 
3.0%
7 15
 
3.0%
47 14
 
2.8%
4 14
 
2.8%
21 14
 
2.8%
Other values (49) 336
66.3%
ValueCountFrequency (%)
0 18
3.6%
1 4
 
0.8%
2 9
1.8%
3 11
2.2%
4 14
2.8%
5 10
2.0%
6 11
2.2%
7 15
3.0%
8 4
 
0.8%
9 3
 
0.6%
ValueCountFrequency (%)
59 9
1.8%
58 2
 
0.4%
57 7
1.4%
56 2
 
0.4%
54 2
 
0.4%
53 1
 
0.2%
52 2
 
0.4%
51 2
 
0.4%
50 12
2.4%
49 11
2.2%

경도(초)
Text

Distinct139
Distinct (%)27.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2023-12-12T12:05:28.356387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.1676529
Min length1

Characters and Unicode

Total characters1099
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)12.6%

Sample

1st row0
2nd row48
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 67
 
13.2%
30 27
 
5.3%
24 21
 
4.2%
54 14
 
2.8%
48 13
 
2.6%
12 13
 
2.6%
6 11
 
2.2%
20 10
 
2.0%
18 9
 
1.8%
3 9
 
1.8%
Other values (128) 312
61.7%
2023-12-12T12:05:28.836913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 146
13.3%
0 136
12.4%
4 136
12.4%
3 129
11.7%
1 117
10.6%
5 113
10.3%
. 99
9.0%
6 86
7.8%
8 58
 
5.3%
7 43
 
3.9%
Other values (2) 36
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 999
90.9%
Other Punctuation 99
 
9.0%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 146
14.6%
0 136
13.6%
4 136
13.6%
3 129
12.9%
1 117
11.7%
5 113
11.3%
6 86
8.6%
8 58
 
5.8%
7 43
 
4.3%
9 35
 
3.5%
Other Punctuation
ValueCountFrequency (%)
. 99
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1099
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 146
13.3%
0 136
12.4%
4 136
12.4%
3 129
11.7%
1 117
10.6%
5 113
10.3%
. 99
9.0%
6 86
7.8%
8 58
 
5.3%
7 43
 
3.9%
Other values (2) 36
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1099
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 146
13.3%
0 136
12.4%
4 136
12.4%
3 129
11.7%
1 117
10.6%
5 113
10.3%
. 99
9.0%
6 86
7.8%
8 58
 
5.3%
7 43
 
3.9%
Other values (2) 36
 
3.3%

Interactions

2023-12-12T12:05:24.865741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:21.747605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:22.857632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.570337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.253608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:25.038845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:21.901577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.022002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.716952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.370886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:25.154383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:22.027160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.155939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.852083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.488056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:25.261092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:22.535563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.281484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.981340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.626802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:25.405345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:22.702042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:23.430022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.114039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:05:24.743078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:05:28.951869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지점번호위도(도)위도(분)위도(초)경도(도)경도(분)
구분1.0000.6610.9860.8330.4870.9610.785
지점번호0.6611.0000.4720.5010.2660.2980.596
위도(도)0.9860.4721.0000.6700.3530.5550.545
위도(분)0.8330.5010.6701.0000.3490.5470.608
위도(초)0.4870.2660.3530.3491.0000.1490.246
경도(도)0.9610.2980.5550.5470.1491.0000.556
경도(분)0.7850.5960.5450.6080.2460.5561.000
2023-12-12T12:05:29.087810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분위도(도)
구분1.0000.830
위도(도)0.8301.000
2023-12-12T12:05:29.206026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점번호위도(분)위도(초)경도(도)경도(분)구분위도(도)
지점번호1.0000.0540.0560.1160.1260.2840.212
위도(분)0.0541.000-0.003-0.0870.1640.4540.339
위도(초)0.056-0.0031.0000.0470.0020.1830.153
경도(도)0.116-0.0870.0471.000-0.1690.7940.417
경도(분)0.1260.1640.002-0.1691.0000.3940.255
구분0.2840.4540.1830.7940.3941.0000.830
위도(도)0.2120.3390.1530.4170.2550.8301.000

Missing values

2023-12-12T12:05:25.593121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:05:25.797090image/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

구분지점번호위도(도)위도(분)위도(초)경도(도)경도(분)경도(초)
0경인연안구역137570.0124440
1경인연안구역2375030.01244348
2경인연안구역3374530.0124410
3경인연안구역4374318.0124290
4경인연안구역537240.0124370
5경인연안구역63740.01255430
6경인연안구역7371130.01255430
7경인연안구역8371730.0126430
8경인연안구역9372027.01262124
9경인연안구역1037250.012600
구분지점번호위도(도)위도(분)위도(초)경도(도)경도(분)경도(초)
497제주항구역(1)2333446.01264625
498제주항구역(1)3334126.01264020
499제주항구역(1)433430.01262935
500제주항구역(1)5333741.01262037
501제주항구역(1)6332853.01261841
502제주항구역(2)1331350.0126293
503제주항구역(2)2331323.01263920
504제주항구역(2)333823.01263920
505제주항구역(2)433823.01262449
506제주항구역(2)5331323.01262449