Overview

Dataset statistics

Number of variables14
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory124.3 B

Variable types

Categorical3
Numeric9
Text2

Dataset

Description해양수산부에서는 어법별어선 정보를 제공하고 있습니다."통계년도","통계코드","컬럼명","컬럼영문명","전체척수","전체톤수","전체마력","동력척수","동력톤수","동력마력","무동력척수","무동력톤수","최초생성시점","최종변경시점" 입니다.
Author해양수산부
URLhttps://www.data.go.kr/data/15127583/fileData.do

Alerts

통계년도 has constant value ""Constant
최초생성시점 has constant value ""Constant
최종변경시점 has constant value ""Constant
통계코드 is highly overall correlated with 무동력척수 and 1 other fieldsHigh correlation
전체척수 is highly overall correlated with 전체톤수 and 6 other fieldsHigh correlation
전체톤수 is highly overall correlated with 전체척수 and 4 other fieldsHigh correlation
전체마력 is highly overall correlated with 전체척수 and 6 other fieldsHigh correlation
동력척수 is highly overall correlated with 전체척수 and 6 other fieldsHigh correlation
동력톤수 is highly overall correlated with 전체척수 and 4 other fieldsHigh correlation
동력마력 is highly overall correlated with 전체척수 and 6 other fieldsHigh correlation
무동력척수 is highly overall correlated with 통계코드 and 5 other fieldsHigh correlation
무동력톤수 is highly overall correlated with 통계코드 and 5 other fieldsHigh correlation
통계코드 has unique valuesUnique
컬럼명 has unique valuesUnique
통계코드 has 1 (1.8%) zerosZeros
전체척수 has 8 (14.0%) zerosZeros
전체톤수 has 8 (14.0%) zerosZeros
전체마력 has 8 (14.0%) zerosZeros
동력척수 has 8 (14.0%) zerosZeros
동력톤수 has 8 (14.0%) zerosZeros
동력마력 has 8 (14.0%) zerosZeros
무동력척수 has 41 (71.9%) zerosZeros
무동력톤수 has 41 (71.9%) zerosZeros

Reproduction

Analysis started2024-04-21 02:35:06.968998
Analysis finished2024-04-21 02:35:16.093758
Duration9.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2022
57 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 57
100.0%

Length

2024-04-21T11:35:16.151213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:35:16.236646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 57
100.0%

통계코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2729.0175
Minimum0
Maximum6990
Zeros1
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:16.349566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1018
Q12040
median2161
Q33100
95-th percentile6012
Maximum6990
Range6990
Interquartile range (IQR)1060

Descriptive statistics

Standard deviation1452.1336
Coefficient of variation (CV)0.53210856
Kurtosis1.2270523
Mean2729.0175
Median Absolute Deviation (MAD)889
Skewness1.1143335
Sum155554
Variance2108692
MonotonicityStrictly increasing
2024-04-21T11:35:16.481422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
1.8%
3110 1
 
1.8%
2180 1
 
1.8%
3000 1
 
1.8%
3010 1
 
1.8%
3020 1
 
1.8%
3030 1
 
1.8%
3040 1
 
1.8%
3050 1
 
1.8%
3060 1
 
1.8%
Other values (47) 47
82.5%
ValueCountFrequency (%)
0 1
1.8%
1000 1
1.8%
1010 1
1.8%
1020 1
1.8%
1030 1
1.8%
1040 1
1.8%
1050 1
1.8%
1060 1
1.8%
1070 1
1.8%
1990 1
1.8%
ValueCountFrequency (%)
6990 1
1.8%
6030 1
1.8%
6020 1
1.8%
6010 1
1.8%
6000 1
1.8%
5010 1
1.8%
5000 1
1.8%
4010 1
1.8%
4000 1
1.8%
3990 1
1.8%

컬럼명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-04-21T11:35:16.671459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length25.421053
Min length20

Characters and Unicode

Total characters1449
Distinct characters72
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

Unique57 ?
Unique (%)100.0%

Sample

1st row총 계
2nd row원 양 어 업
3rd row - 원 양 연 승 어 업
4th row - 원 양 트 롤 어 업
5th row - 원 양 선 망 어 업
ValueCountFrequency (%)
50
 
13.3%
어 48
 
12.8%
업 46
 
12.2%
망 20
 
5.3%
연 16
 
4.3%
안 15
 
4.0%
해 13
 
3.5%
양 11
 
2.9%
근 11
 
2.9%
기 10
 
2.7%
Other values (61) 136
36.2%
2024-04-21T11:35:16.985803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1023
70.6%
어 52
 
3.6%
업 50
 
3.5%
- 50
 
3.5%
망 24
 
1.7%
연 16
 
1.1%
안 15
 
1.0%
해 14
 
1.0%
선 14
 
1.0%
기 14
 
1.0%
Other values (62) 177
 
12.2%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1023
70.6%
Other Letter 364
 
25.1%
Dash Punctuation 50
 
3.5%
Open Punctuation 6
 
0.4%
Close Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 52
 
14.3%
업 50
 
13.7%
망 24
 
6.6%
연 16
 
4.4%
안 15
 
4.1%
해 14
 
3.8%
선 14
 
3.8%
기 14
 
3.8%
양 11
 
3.0%
근 11
 
3.0%
Other values (58) 143
39.3%
Space Separator
ValueCountFrequency (%)
1023
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1085
74.9%
Hangul 364
 
25.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 52
 
14.3%
업 50
 
13.7%
망 24
 
6.6%
연 16
 
4.4%
안 15
 
4.1%
해 14
 
3.8%
선 14
 
3.8%
기 14
 
3.8%
양 11
 
3.0%
근 11
 
3.0%
Other values (58) 143
39.3%
Common
ValueCountFrequency (%)
1023
94.3%
- 50
 
4.6%
( 6
 
0.6%
) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1085
74.9%
Hangul 364
 
25.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1023
94.3%
- 50
 
4.6%
( 6
 
0.6%
) 6
 
0.6%
Hangul
ValueCountFrequency (%)
어 52
 
14.3%
업 50
 
13.7%
망 24
 
6.6%
연 16
 
4.4%
안 15
 
4.1%
해 14
 
3.8%
선 14
 
3.8%
기 14
 
3.8%
양 11
 
3.0%
근 11
 
3.0%
Other values (58) 143
39.3%

컬럼영문명
Text

Distinct53
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2024-04-21T11:35:17.189009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length26
Mean length18.754386
Min length5

Characters and Unicode

Total characters1069
Distinct characters43
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)87.7%

Sample

1st rowTotal
2nd rowDistant Waters Angling
3rd rowLong Line
4th rowOtter Trawl
5th rowDistant Waters Purse Seines
ValueCountFrequency (%)
coastal 13
 
8.3%
net 10
 
6.4%
off-shore 9
 
5.8%
waters 8
 
5.1%
trawl 8
 
5.1%
distant 6
 
3.8%
others 4
 
2.6%
fisheries 4
 
2.6%
angling 4
 
2.6%
nets 4
 
2.6%
Other values (51) 86
55.1%
2024-04-21T11:35:17.529023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 108
 
10.1%
99
 
9.3%
t 87
 
8.1%
a 82
 
7.7%
r 70
 
6.5%
s 69
 
6.5%
i 58
 
5.4%
o 53
 
5.0%
l 48
 
4.5%
n 46
 
4.3%
Other values (33) 349
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 780
73.0%
Uppercase Letter 163
 
15.2%
Space Separator 99
 
9.3%
Dash Punctuation 14
 
1.3%
Close Punctuation 6
 
0.6%
Open Punctuation 6
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 108
13.8%
t 87
11.2%
a 82
10.5%
r 70
9.0%
s 69
8.8%
i 58
7.4%
o 53
6.8%
l 48
 
6.2%
n 46
 
5.9%
h 32
 
4.1%
Other values (12) 127
16.3%
Uppercase Letter
ValueCountFrequency (%)
S 27
16.6%
O 19
11.7%
C 16
9.8%
D 14
8.6%
N 14
8.6%
T 14
8.6%
L 11
6.7%
F 9
 
5.5%
W 8
 
4.9%
B 7
 
4.3%
Other values (6) 24
14.7%
Space Separator
ValueCountFrequency (%)
99
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 943
88.2%
Common 126
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 108
 
11.5%
t 87
 
9.2%
a 82
 
8.7%
r 70
 
7.4%
s 69
 
7.3%
i 58
 
6.2%
o 53
 
5.6%
l 48
 
5.1%
n 46
 
4.9%
h 32
 
3.4%
Other values (28) 290
30.8%
Common
ValueCountFrequency (%)
99
78.6%
- 14
 
11.1%
) 6
 
4.8%
( 6
 
4.8%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 108
 
10.1%
99
 
9.3%
t 87
 
8.1%
a 82
 
7.7%
r 70
 
6.5%
s 69
 
6.5%
i 58
 
5.4%
o 53
 
5.0%
l 48
 
4.5%
n 46
 
4.3%
Other values (33) 349
32.6%

전체척수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3388.6842
Minimum0
Maximum64385
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:17.850372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median110
Q3404
95-th percentile19148
Maximum64385
Range64385
Interquartile range (IQR)389

Descriptive statistics

Standard deviation10401.405
Coefficient of variation (CV)3.0694524
Kurtosis22.709472
Mean3388.6842
Median Absolute Deviation (MAD)110
Skewness4.4919113
Sum193155
Variance1.0818922 × 108
MonotonicityNot monotonic
2024-04-21T11:35:17.978740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 8
 
14.0%
28 3
 
5.3%
42 3
 
5.3%
9 2
 
3.5%
15 2
 
3.5%
2943 2
 
3.5%
19148 2
 
3.5%
16611 1
 
1.8%
260 1
 
1.8%
36694 1
 
1.8%
Other values (32) 32
56.1%
ValueCountFrequency (%)
0 8
14.0%
1 1
 
1.8%
2 1
 
1.8%
5 1
 
1.8%
9 2
 
3.5%
15 2
 
3.5%
28 3
 
5.3%
34 1
 
1.8%
39 1
 
1.8%
41 1
 
1.8%
ValueCountFrequency (%)
64385 1
1.8%
36694 1
1.8%
19148 2
3.5%
16611 1
1.8%
12170 1
1.8%
4628 1
1.8%
3034 1
1.8%
2943 2
3.5%
2462 1
1.8%
2372 1
1.8%

전체톤수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28089.554
Minimum0
Maximum533701.52
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:18.112223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1470.34
median5547.54
Q322344.65
95-th percentile115976.49
Maximum533701.52
Range533701.52
Interquartile range (IQR)21874.31

Descriptive statistics

Standard deviation75222.61
Coefficient of variation (CV)2.6779568
Kurtosis37.588407
Mean28089.554
Median Absolute Deviation (MAD)5547.54
Skewness5.7252008
Sum1601104.6
Variance5.6584411 × 109
MonotonicityNot monotonic
2024-04-21T11:35:18.240541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 8
 
14.0%
2026.01 2
 
3.5%
63331.45 2
 
3.5%
533701.52 1
 
1.8%
40.43 1
 
1.8%
115.77 1
 
1.8%
470.34 1
 
1.8%
8547.04 1
 
1.8%
120959.87 1
 
1.8%
40115.4 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
0.0 8
14.0%
21.77 1
 
1.8%
40.43 1
 
1.8%
60.0 1
 
1.8%
115.77 1
 
1.8%
401.01 1
 
1.8%
468.12 1
 
1.8%
470.34 1
 
1.8%
567.12 1
 
1.8%
865.0 1
 
1.8%
ValueCountFrequency (%)
533701.52 1
1.8%
131907.84 1
1.8%
120959.87 1
1.8%
114730.65 1
1.8%
100745.7 1
1.8%
63331.45 2
3.5%
49994.0 1
1.8%
49325.59 1
1.8%
42936.03 1
1.8%
40115.4 1
1.8%

전체마력
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean897134.63
Minimum0
Maximum17045558
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:18.390908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112722
median106110
Q3226041
95-th percentile4019188
Maximum17045558
Range17045558
Interquartile range (IQR)213319

Descriptive statistics

Standard deviation2688019.2
Coefficient of variation (CV)2.9962272
Kurtosis25.058465
Mean897134.63
Median Absolute Deviation (MAD)98104
Skewness4.7240695
Sum51136674
Variance7.2254471 × 1012
MonotonicityNot monotonic
2024-04-21T11:35:18.536699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 8
 
14.0%
193382 2
 
3.5%
4005032 2
 
3.5%
17045558 1
 
1.8%
2517 1
 
1.8%
4687 1
 
1.8%
24651 1
 
1.8%
200460 1
 
1.8%
9617008 1
 
1.8%
3420832 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
0 8
14.0%
480 1
 
1.8%
1020 1
 
1.8%
2517 1
 
1.8%
4687 1
 
1.8%
8006 1
 
1.8%
8800 1
 
1.8%
12722 1
 
1.8%
20965 1
 
1.8%
24651 1
 
1.8%
ValueCountFrequency (%)
17045558 1
1.8%
9617008 1
1.8%
4075812 1
1.8%
4005032 2
3.5%
3420832 1
1.8%
1897468 1
1.8%
1163329 1
1.8%
977643 1
1.8%
480902 1
1.8%
411610 1
1.8%

동력척수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct42
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3351
Minimum0
Maximum63669
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:18.682008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q115
median110
Q3404
95-th percentile19071
Maximum63669
Range63669
Interquartile range (IQR)389

Descriptive statistics

Standard deviation10301.494
Coefficient of variation (CV)3.0741553
Kurtosis22.583102
Mean3351
Median Absolute Deviation (MAD)110
Skewness4.4805296
Sum191007
Variance1.0612079 × 108
MonotonicityNot monotonic
2024-04-21T11:35:18.804671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 8
 
14.0%
28 3
 
5.3%
42 3
 
5.3%
9 2
 
3.5%
15 2
 
3.5%
2711 2
 
3.5%
19071 2
 
3.5%
16501 1
 
1.8%
260 1
 
1.8%
36376 1
 
1.8%
Other values (32) 32
56.1%
ValueCountFrequency (%)
0 8
14.0%
1 1
 
1.8%
2 1
 
1.8%
5 1
 
1.8%
9 2
 
3.5%
15 2
 
3.5%
28 3
 
5.3%
34 1
 
1.8%
39 1
 
1.8%
41 1
 
1.8%
ValueCountFrequency (%)
63669 1
1.8%
36376 1
1.8%
19071 2
3.5%
16501 1
1.8%
12089 1
1.8%
4611 1
1.8%
2945 1
1.8%
2711 2
3.5%
2380 1
1.8%
2372 1
1.8%

동력톤수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28021.689
Minimum0
Maximum532412.09
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:18.927365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1470.34
median5473.05
Q322344.65
95-th percentile115807.79
Maximum532412.09
Range532412.09
Interquartile range (IQR)21874.31

Descriptive statistics

Standard deviation75042.773
Coefficient of variation (CV)2.6780246
Kurtosis37.58456
Mean28021.689
Median Absolute Deviation (MAD)5473.05
Skewness5.7248711
Sum1597236.3
Variance5.6314177 × 109
MonotonicityNot monotonic
2024-04-21T11:35:19.079245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.0 8
 
14.0%
1966.25 2
 
3.5%
63155.87 2
 
3.5%
532412.09 1
 
1.8%
40.43 1
 
1.8%
115.77 1
 
1.8%
470.34 1
 
1.8%
8547.04 1
 
1.8%
120116.33 1
 
1.8%
39831.52 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
0.0 8
14.0%
21.77 1
 
1.8%
40.43 1
 
1.8%
60.0 1
 
1.8%
115.77 1
 
1.8%
389.85 1
 
1.8%
468.12 1
 
1.8%
470.34 1
 
1.8%
567.12 1
 
1.8%
865.0 1
 
1.8%
ValueCountFrequency (%)
532412.09 1
1.8%
131907.84 1
1.8%
120116.33 1
1.8%
114730.65 1
1.8%
100535.15 1
1.8%
63155.87 2
3.5%
49994.0 1
1.8%
48984.14 1
1.8%
42936.03 1
1.8%
39831.52 1
1.8%

동력마력
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean897134.63
Minimum0
Maximum17045558
Zeros8
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:19.202918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112722
median106110
Q3226041
95-th percentile4019188
Maximum17045558
Range17045558
Interquartile range (IQR)213319

Descriptive statistics

Standard deviation2688019.2
Coefficient of variation (CV)2.9962272
Kurtosis25.058465
Mean897134.63
Median Absolute Deviation (MAD)98104
Skewness4.7240695
Sum51136674
Variance7.2254471 × 1012
MonotonicityNot monotonic
2024-04-21T11:35:19.335264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 8
 
14.0%
193382 2
 
3.5%
4005032 2
 
3.5%
17045558 1
 
1.8%
2517 1
 
1.8%
4687 1
 
1.8%
24651 1
 
1.8%
200460 1
 
1.8%
9617008 1
 
1.8%
3420832 1
 
1.8%
Other values (38) 38
66.7%
ValueCountFrequency (%)
0 8
14.0%
480 1
 
1.8%
1020 1
 
1.8%
2517 1
 
1.8%
4687 1
 
1.8%
8006 1
 
1.8%
8800 1
 
1.8%
12722 1
 
1.8%
20965 1
 
1.8%
24651 1
 
1.8%
ValueCountFrequency (%)
17045558 1
1.8%
9617008 1
1.8%
4075812 1
1.8%
4005032 2
3.5%
3420832 1
1.8%
1897468 1
1.8%
1163329 1
1.8%
977643 1
1.8%
480902 1
1.8%
411610 1
1.8%

무동력척수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.684211
Minimum0
Maximum716
Zeros41
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:19.449258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile232
Maximum716
Range716
Interquartile range (IQR)7

Descriptive statistics

Standard deviation110.9915
Coefficient of variation (CV)2.9453051
Kurtosis25.760299
Mean37.684211
Median Absolute Deviation (MAD)0
Skewness4.7010945
Sum2148
Variance12319.113
MonotonicityNot monotonic
2024-04-21T11:35:19.548323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 41
71.9%
77 2
 
3.5%
232 2
 
3.5%
716 1
 
1.8%
318 1
 
1.8%
81 1
 
1.8%
3 1
 
1.8%
17 1
 
1.8%
110 1
 
1.8%
33 1
 
1.8%
Other values (5) 5
 
8.8%
ValueCountFrequency (%)
0 41
71.9%
3 1
 
1.8%
7 1
 
1.8%
17 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
42 1
 
1.8%
77 2
 
3.5%
81 1
 
1.8%
82 1
 
1.8%
ValueCountFrequency (%)
716 1
1.8%
318 1
1.8%
232 2
3.5%
110 1
1.8%
89 1
1.8%
82 1
1.8%
81 1
1.8%
77 2
3.5%
42 1
1.8%
33 1
1.8%

무동력톤수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct15
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.864737
Minimum0
Maximum1289.43
Zeros41
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size645.0 B
2024-04-21T11:35:19.660921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q311.16
95-th percentile295.394
Maximum1289.43
Range1289.43
Interquartile range (IQR)11.16

Descriptive statistics

Standard deviation210.0258
Coefficient of variation (CV)3.0947707
Kurtosis23.375423
Mean67.864737
Median Absolute Deviation (MAD)0
Skewness4.6218624
Sum3868.29
Variance44110.835
MonotonicityNot monotonic
2024-04-21T11:35:19.758301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 41
71.9%
175.58 2
 
3.5%
59.76 2
 
3.5%
1289.43 1
 
1.8%
843.54 1
 
1.8%
283.88 1
 
1.8%
7.03 1
 
1.8%
46.15 1
 
1.8%
341.45 1
 
1.8%
74.49 1
 
1.8%
Other values (5) 5
 
8.8%
ValueCountFrequency (%)
0.0 41
71.9%
7.03 1
 
1.8%
11.16 1
 
1.8%
28.1 1
 
1.8%
46.15 1
 
1.8%
59.76 2
 
3.5%
74.49 1
 
1.8%
79.38 1
 
1.8%
175.58 2
 
3.5%
182.45 1
 
1.8%
ValueCountFrequency (%)
1289.43 1
1.8%
843.54 1
1.8%
341.45 1
1.8%
283.88 1
1.8%
210.55 1
1.8%
182.45 1
1.8%
175.58 2
3.5%
79.38 1
1.8%
74.49 1
1.8%
59.76 2
3.5%

최초생성시점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023/08/23
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023/08/23
2nd row2023/08/23
3rd row2023/08/23
4th row2023/08/23
5th row2023/08/23

Common Values

ValueCountFrequency (%)
2023/08/23 57
100.0%

Length

2024-04-21T11:35:19.875633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:35:19.954942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023/08/23 57
100.0%

최종변경시점
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023/08/23
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023/08/23
2nd row2023/08/23
3rd row2023/08/23
4th row2023/08/23
5th row2023/08/23

Common Values

ValueCountFrequency (%)
2023/08/23 57
100.0%

Length

2024-04-21T11:35:20.034282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:35:20.124958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023/08/23 57
100.0%

Interactions

2024-04-21T11:35:15.014649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:08.816270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.608587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.321493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.021493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.796697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.774490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.486954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.254066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.111396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:08.951042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.690866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.403175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.102387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.898794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.850208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.570975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.334322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.202373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.031184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.776320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.478096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.185894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.989551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.931310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.650272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.414498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.281420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.107352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.854384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.547113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.270664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.072878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.002182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.729188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.503031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.380070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.211728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.942929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.636013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.373759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.164049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.081370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.824989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.601960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.476615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.290659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.017927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.711755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.450470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.245066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.157745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.917309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.680815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.560779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.369565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.087970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.784315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.523331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.319904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.233453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.000513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.766362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.642168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.452083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.169316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.864674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.599885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.411287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.325943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.088862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.852141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:15.723620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:09.534126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.246963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:10.945775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:11.692162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:12.487696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:13.409281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.175447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:35:14.932375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:35:20.187617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계코드컬럼명컬럼영문명전체척수전체톤수전체마력동력척수동력톤수동력마력무동력척수무동력톤수
통계코드1.0001.0000.0000.7290.7980.7140.7290.7980.7140.8730.776
컬럼명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
컬럼영문명0.0001.0001.0001.0000.0001.0001.0000.0001.0000.9560.912
전체척수0.7291.0001.0001.0000.7860.9901.0000.7860.9900.9800.990
전체톤수0.7981.0000.0000.7861.0000.8230.7861.0000.8230.7950.840
전체마력0.7141.0001.0000.9900.8231.0000.9900.8231.0000.9800.983
동력척수0.7291.0001.0001.0000.7860.9901.0000.7860.9900.9800.990
동력톤수0.7981.0000.0000.7861.0000.8230.7861.0000.8230.7950.840
동력마력0.7141.0001.0000.9900.8231.0000.9900.8231.0000.9800.983
무동력척수0.8731.0000.9560.9800.7950.9800.9800.7950.9801.0000.990
무동력톤수0.7761.0000.9120.9900.8400.9830.9900.8400.9830.9901.000
2024-04-21T11:35:20.304422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통계코드전체척수전체톤수전체마력동력척수동력톤수동력마력무동력척수무동력톤수
통계코드1.0000.346-0.0410.2170.342-0.0410.2170.5090.500
전체척수0.3461.0000.7370.9471.0000.7370.9470.7540.759
전체톤수-0.0410.7371.0000.8780.7361.0000.8780.4020.434
전체마력0.2170.9470.8781.0000.9480.8781.0000.6420.661
동력척수0.3421.0000.7360.9481.0000.7360.9480.7510.755
동력톤수-0.0410.7371.0000.8780.7361.0000.8780.4020.434
동력마력0.2170.9470.8781.0000.9480.8781.0000.6420.661
무동력척수0.5090.7540.4020.6420.7510.4020.6421.0000.991
무동력톤수0.5000.7590.4340.6610.7550.4340.6610.9911.000

Missing values

2024-04-21T11:35:15.850382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:35:16.028202image/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

통계년도통계코드컬럼명컬럼영문명전체척수전체톤수전체마력동력척수동력톤수동력마력무동력척수무동력톤수최초생성시점최종변경시점
020220총 계Total64385533701.521704555863669532412.09170455587161289.432023/08/232023/08/23
120221000원 양 어 업Distant Waters Angling194131907.84355025194131907.8435502500.02023/08/232023/08/23
220221010- 원 양 연 승 어 업Long Line11749994.014020011749994.014020000.02023/08/232023/08/23
320221020- 원 양 트 롤 어 업Otter Trawl1527788.23419251527788.234192500.02023/08/232023/08/23
420221030- 원 양 선 망 어 업Distant Waters Purse Seines2839042.651157502839042.6511575000.02023/08/232023/08/23
520221040- 원 양 유 자 망 어 업Distant Waters Floating Gill Net00.0000.0000.02023/08/232023/08/23
620221050- 원 양 봉 수 망 어 업Distant Waters Stick-held Dip Net52643.0880052643.0880000.02023/08/232023/08/23
720221060- 원 양 채 낚 기 어 업Distant Waters Angling2812379.96478702812379.964787000.02023/08/232023/08/23
820221070- 원 양 통 발 어 업Distant Waters Trap160.0480160.048000.02023/08/232023/08/23
920221990- 기 타 원 양 어 업Others00.0000.0000.02023/08/232023/08/23
통계년도통계코드컬럼명컬럼영문명전체척수전체톤수전체마력동력척수동력톤수동력마력무동력척수무동력톤수최초생성시점최종변경시점
4720223990- 연 안 기 타Coastal Others00.0000.0000.02023/08/232023/08/23
4820224000양 식 업Culture1914863331.4540050321907163155.87400503277175.582023/08/232023/08/23
4920224010- 천 해 양 식Shallow Sea Culture1914863331.4540050321907163155.87400503277175.582023/08/232023/08/23
5020225000내 수 면 어 업Inland Waters Fisheries29432026.0119338227111966.2519338223259.762023/08/232023/08/23
5120225010- 내 수 면 어 업Inland Waters Fisheries29432026.0119338227111966.2519338223259.762023/08/232023/08/23
5220226000기 타 어 업Others3034100745.79776432945100535.1597764389210.552023/08/232023/08/23
5320226010- 어 획 물 운 반 선Fish Carrier37623623.9822604136923595.88226041728.12023/08/232023/08/23
5420226020- 지 도 단 속 선Patrol Boats15442936.0321299915442936.0321299900.02023/08/232023/08/23
5520226030- 시 험 및 교 습 선Experiment & Education Boats4222344.65577014222344.655770100.02023/08/232023/08/23
5620226990- 기 타Others246211841.04480902238011658.5948090282182.452023/08/232023/08/23