Overview

Dataset statistics

Number of variables11
Number of observations1018
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory88.6 KiB
Average record size in memory89.1 B

Variable types

Categorical7
DateTime1
Text2
Numeric1

Dataset

Description선박검역중 수입고철에 대한 소독 결과 정보 (검역구분, 검역일시, 선박명, 선박국적, 출항국가, 고철적재량, 수입국가, 수입자, 소독대행업체, 소독일시, 소독약품)
Author질병관리청
URLhttps://www.data.go.kr/data/3074713/fileData.do

Alerts

출항국가 is highly overall correlated with 수입국가High correlation
수입국가 is highly overall correlated with 출항국가High correlation
수입자 is highly overall correlated with 소독대행업체 and 1 other fieldsHigh correlation
소독대행업체 is highly overall correlated with 수입자 and 1 other fieldsHigh correlation
소독약품 is highly overall correlated with 수입자 and 1 other fieldsHigh correlation
검역구분 is highly imbalanced (53.8%)Imbalance
출항국가 is highly imbalanced (71.3%)Imbalance
수입국가 is highly imbalanced (84.0%)Imbalance

Reproduction

Analysis started2023-12-12 23:02:35.106753
Analysis finished2023-12-12 23:02:36.102676
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

검역구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
전자
849 
승선
150 
완료
 
19

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전자
2nd row전자
3rd row전자
4th row승선
5th row전자

Common Values

ValueCountFrequency (%)
전자 849
83.4%
승선 150
 
14.7%
완료 19
 
1.9%

Length

2023-12-13T08:02:36.167469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:02:36.289217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전자 849
83.4%
승선 150
 
14.7%
완료 19
 
1.9%

검역일시
Date

Distinct683
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
Minimum2022-01-01 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T08:02:36.421959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:02:36.593717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

선박명
Text

Distinct366
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-13T08:02:36.921699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.3447937
Min length2

Characters and Unicode

Total characters9513
Distinct characters37
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)15.6%

Sample

1st rowAN LAN
2nd rowWEN XIANG
3rd rowKS SUNRISE
4th rowYU LIN
5th rowQING RU
ValueCountFrequency (%)
sheng 61
 
2.9%
yuan 48
 
2.3%
yang 48
 
2.3%
qing 44
 
2.1%
xin 43
 
2.0%
xiang 42
 
2.0%
star 41
 
1.9%
da 39
 
1.8%
hong 37
 
1.8%
ocean 35
 
1.7%
Other values (341) 1672
79.2%
2023-12-13T08:02:37.452986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1226
12.9%
1092
11.5%
A 853
 
9.0%
I 772
 
8.1%
G 644
 
6.8%
E 571
 
6.0%
O 512
 
5.4%
H 456
 
4.8%
U 437
 
4.6%
S 418
 
4.4%
Other values (27) 2532
26.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8162
85.8%
Space Separator 1092
 
11.5%
Decimal Number 230
 
2.4%
Other Punctuation 23
 
0.2%
Dash Punctuation 6
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1226
15.0%
A 853
10.5%
I 772
 
9.5%
G 644
 
7.9%
E 571
 
7.0%
O 512
 
6.3%
H 456
 
5.6%
U 437
 
5.4%
S 418
 
5.1%
R 341
 
4.2%
Other values (16) 1932
23.7%
Decimal Number
ValueCountFrequency (%)
1 62
27.0%
9 34
14.8%
7 33
14.3%
6 27
11.7%
8 24
 
10.4%
5 24
 
10.4%
2 14
 
6.1%
3 12
 
5.2%
Space Separator
ValueCountFrequency (%)
1092
100.0%
Other Punctuation
ValueCountFrequency (%)
. 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8162
85.8%
Common 1351
 
14.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1226
15.0%
A 853
10.5%
I 772
 
9.5%
G 644
 
7.9%
E 571
 
7.0%
O 512
 
6.3%
H 456
 
5.6%
U 437
 
5.4%
S 418
 
5.1%
R 341
 
4.2%
Other values (16) 1932
23.7%
Common
ValueCountFrequency (%)
1092
80.8%
1 62
 
4.6%
9 34
 
2.5%
7 33
 
2.4%
6 27
 
2.0%
8 24
 
1.8%
5 24
 
1.8%
. 23
 
1.7%
2 14
 
1.0%
3 12
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1226
12.9%
1092
11.5%
A 853
 
9.0%
I 772
 
8.1%
G 644
 
6.8%
E 571
 
6.0%
O 512
 
5.4%
H 456
 
4.8%
U 437
 
4.6%
S 418
 
4.4%
Other values (27) 2532
26.6%

선박국적
Categorical

Distinct25
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
벨리즈
418 
파나마
224 
시에라리온
112 
토고
88 
한국
83 
Other values (20)
93 

Length

Max length12
Median length3
Mean length3.0874263
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row벨리즈
2nd row파나마
3rd row한국
4th row토고
5th row벨리즈

Common Values

ValueCountFrequency (%)
벨리즈 418
41.1%
파나마 224
22.0%
시에라리온 112
 
11.0%
토고 88
 
8.6%
한국 83
 
8.2%
홍콩 15
 
1.5%
중국 12
 
1.2%
팔라우 11
 
1.1%
라이베리아 7
 
0.7%
자메이카 6
 
0.6%
Other values (15) 42
 
4.1%

Length

2023-12-13T08:02:37.621914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벨리즈 418
40.7%
파나마 224
21.8%
시에라리온 112
 
10.9%
토고 88
 
8.6%
한국 83
 
8.1%
홍콩 15
 
1.5%
중국 12
 
1.2%
팔라우 11
 
1.1%
라이베리아 7
 
0.7%
자메이카 6
 
0.6%
Other values (18) 50
 
4.9%

출항국가
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
일본
857 
한국
88 
러시아연방
 
25
중국
 
22
미국
 
12
Other values (5)
 
14

Length

Max length5
Median length2
Mean length2.0884086
Min length2

Unique

Unique2 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
일본 857
84.2%
한국 88
 
8.6%
러시아연방 25
 
2.5%
중국 22
 
2.2%
미국 12
 
1.2%
호주 5
 
0.5%
파나마 4
 
0.4%
말레이지아 3
 
0.3%
홍콩 1
 
0.1%
뉴질랜드 1
 
0.1%

Length

2023-12-13T08:02:37.743819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:02:37.865570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일본 857
84.2%
한국 88
 
8.6%
러시아연방 25
 
2.5%
중국 22
 
2.2%
미국 12
 
1.2%
호주 5
 
0.5%
파나마 4
 
0.4%
말레이지아 3
 
0.3%
홍콩 1
 
0.1%
뉴질랜드 1
 
0.1%

고철적재량(M-TON)
Real number (ℝ)

Distinct503
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2762.8576
Minimum21
Maximum46370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2023-12-13T08:02:38.004974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile909.35
Q11971.25
median2095
Q32860
95-th percentile5000.9
Maximum46370
Range46349
Interquartile range (IQR)888.75

Descriptive statistics

Standard deviation3415.5272
Coefficient of variation (CV)1.2362299
Kurtosis66.028643
Mean2762.8576
Median Absolute Deviation (MAD)251.5
Skewness7.502397
Sum2812589
Variance11665826
MonotonicityNot monotonic
2023-12-13T08:02:38.160125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 65
 
6.4%
2100 44
 
4.3%
3000 23
 
2.3%
2099 20
 
2.0%
2095 13
 
1.3%
2098 12
 
1.2%
2625 12
 
1.2%
2097 11
 
1.1%
1500 11
 
1.1%
1000 11
 
1.1%
Other values (493) 796
78.2%
ValueCountFrequency (%)
21 1
0.1%
24 1
0.1%
41 1
0.1%
61 1
0.1%
62 1
0.1%
72 2
0.2%
80 1
0.1%
96 1
0.1%
98 1
0.1%
113 1
0.1%
ValueCountFrequency (%)
46370 1
0.1%
35233 1
0.1%
35201 1
0.1%
34000 1
0.1%
29884 1
0.1%
28392 1
0.1%
27000 1
0.1%
26000 1
0.1%
25000 1
0.1%
24576 1
0.1%

수입국가
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct15
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
일본
937 
러시아
 
21
파나마
 
20
미국
 
18
한국
 
5
Other values (10)
 
17

Length

Max length6
Median length2
Mean length2.0618861
Min length2

Unique

Unique7 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
일본 937
92.0%
러시아 21
 
2.1%
파나마 20
 
2.0%
미국 18
 
1.8%
한국 5
 
0.5%
과테말라 5
 
0.5%
중국 3
 
0.3%
일본ㅂ 2
 
0.2%
홍콩 1
 
0.1%
스위스 1
 
0.1%
Other values (5) 5
 
0.5%

Length

2023-12-13T08:02:38.326092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일본 937
92.0%
러시아 21
 
2.1%
파나마 20
 
2.0%
미국 19
 
1.9%
한국 5
 
0.5%
과테말라 5
 
0.5%
중국 3
 
0.3%
일본ㅂ 2
 
0.2%
홍콩 1
 
0.1%
스위스 1
 
0.1%
Other values (5) 5
 
0.5%

수입자
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
현대제철
294 
동국제강
169 
SEAH BESTEEL CO-
132 
YK스틸
67 
대한제강
55 
Other values (40)
301 

Length

Max length16
Median length4
Mean length5.8359528
Min length2

Unique

Unique12 ?
Unique (%)1.2%

Sample

1st row현대제철
2nd row현대제철
3rd row현대제철
4th row동국제강
5th row현대제철

Common Values

ValueCountFrequency (%)
현대제철 294
28.9%
동국제강 169
16.6%
SEAH BESTEEL CO- 132
13.0%
YK스틸 67
 
6.6%
대한제강 55
 
5.4%
POSCO 40
 
3.9%
한국철강 32
 
3.1%
포스코 32
 
3.1%
덕인 15
 
1.5%
동성로지스틱 13
 
1.3%
Other values (35) 169
16.6%

Length

2023-12-13T08:02:38.486395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
현대제철 294
22.7%
동국제강 169
13.0%
seah 132
10.2%
besteel 132
10.2%
co 132
10.2%
yk스틸 67
 
5.2%
대한제강 55
 
4.2%
posco 40
 
3.1%
한국철강 32
 
2.5%
포스코 32
 
2.5%
Other values (40) 212
16.3%

소독대행업체
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
거륭
274 
아주종합방제
139 
태관주택종합관리
134 
제일방역공사
132 
국제종합방제
119 
Other values (11)
220 

Length

Max length11
Median length10
Mean length5.1119843
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row거륭방제
2nd row웨스턴방역
3rd row거륭방제
4th row거륭
5th row거륭방제

Common Values

ValueCountFrequency (%)
거륭 274
26.9%
아주종합방제 139
13.7%
태관주택종합관리 134
13.2%
제일방역공사 132
13.0%
국제종합방제 119
11.7%
HR-PORT 68
 
6.7%
영화기업사 40
 
3.9%
웨스턴방역 37
 
3.6%
국제방제 35
 
3.4%
거륭방제 20
 
2.0%
Other values (6) 20
 
2.0%

Length

2023-12-13T08:02:38.629894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거륭 274
26.9%
아주종합방제 139
13.6%
태관주택종합관리 134
13.2%
제일방역공사 132
13.0%
국제종합방제 119
11.7%
hr-port 68
 
6.7%
영화기업사 40
 
3.9%
웨스턴방역 37
 
3.6%
국제방제 35
 
3.4%
거륭방제 20
 
2.0%
Other values (7) 21
 
2.1%

소독일시1
Text

Distinct696
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2023-12-13T08:02:38.896522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23414
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

Unique482 ?
Unique (%)47.3%

Sample

1st row2022-01-01 - 2022-01-02
2nd row2022-01-01 - 2022-01-02
3rd row2022-01-02 - 2022-01-03
4th row2022-01-02 - 2022-01-03
5th row2022-01-02 - 2022-01-03
ValueCountFrequency (%)
1018
33.3%
2022-04-28 16
 
0.5%
2022-11-16 15
 
0.5%
2022-02-17 14
 
0.5%
2022-02-23 14
 
0.5%
2022-09-28 13
 
0.4%
2022-11-09 13
 
0.4%
2022-03-22 13
 
0.4%
2022-09-15 12
 
0.4%
2022-11-15 12
 
0.4%
Other values (348) 1914
62.7%
2023-12-13T08:02:39.291083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 7368
31.5%
- 5090
21.7%
0 4508
19.3%
2036
 
8.7%
1 1704
 
7.3%
3 502
 
2.1%
4 438
 
1.9%
5 377
 
1.6%
8 375
 
1.6%
9 355
 
1.5%
Other values (2) 661
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16288
69.6%
Dash Punctuation 5090
 
21.7%
Space Separator 2036
 
8.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7368
45.2%
0 4508
27.7%
1 1704
 
10.5%
3 502
 
3.1%
4 438
 
2.7%
5 377
 
2.3%
8 375
 
2.3%
9 355
 
2.2%
6 340
 
2.1%
7 321
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 5090
100.0%
Space Separator
ValueCountFrequency (%)
2036
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23414
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 7368
31.5%
- 5090
21.7%
0 4508
19.3%
2036
 
8.7%
1 1704
 
7.3%
3 502
 
2.1%
4 438
 
1.9%
5 377
 
1.6%
8 375
 
1.6%
9 355
 
1.5%
Other values (2) 661
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23414
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 7368
31.5%
- 5090
21.7%
0 4508
19.3%
2036
 
8.7%
1 1704
 
7.3%
3 502
 
2.1%
4 438
 
1.9%
5 377
 
1.6%
8 375
 
1.6%
9 355
 
1.5%
Other values (2) 661
 
2.8%

소독약품
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
싸이퍼골드유제
294 
메가유제
294 
델타싸이드
140 
싸이퍼킬
137 
람다킬15유제
72 
Other values (4)
81 

Length

Max length7
Median length6
Mean length5.2770138
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row싸이퍼골드유제
2nd row롱다운플러스
3rd row싸이퍼골드유제
4th row싸이퍼골드유제
5th row싸이퍼골드유제

Common Values

ValueCountFrequency (%)
싸이퍼골드유제 294
28.9%
메가유제 294
28.9%
델타싸이드 140
13.8%
싸이퍼킬 137
13.5%
람다킬15유제 72
 
7.1%
롱다운플러스 46
 
4.5%
HCN 32
 
3.1%
크린델타 A 2
 
0.2%
MB 1
 
0.1%

Length

2023-12-13T08:02:39.464818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:02:39.598384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
싸이퍼골드유제 294
28.8%
메가유제 294
28.8%
델타싸이드 140
13.7%
싸이퍼킬 137
13.4%
람다킬15유제 72
 
7.1%
롱다운플러스 46
 
4.5%
hcn 32
 
3.1%
크린델타 2
 
0.2%
a 2
 
0.2%
mb 1
 
0.1%

Interactions

2023-12-13T08:02:35.724813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:02:39.717211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
검역구분선박국적출항국가고철적재량(M-TON)수입국가수입자소독대행업체소독약품
검역구분1.0000.2780.4190.1800.1520.2080.2890.297
선박국적0.2781.0000.7680.6310.7660.5920.4920.184
출항국가0.4190.7681.0000.7380.9090.6720.3290.251
고철적재량(M-TON)0.1800.6310.7381.0000.7250.4750.1690.232
수입국가0.1520.7660.9090.7251.0000.5660.4030.234
수입자0.2080.5920.6720.4750.5661.0000.9590.958
소독대행업체0.2890.4920.3290.1690.4030.9591.0000.963
소독약품0.2970.1840.2510.2320.2340.9580.9631.000
2023-12-13T08:02:39.843401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수입국가수입자출항국가선박국적소독대행업체검역구분소독약품
수입국가1.0000.1750.6310.3410.1460.0680.097
수입자0.1751.0000.2910.1640.6700.0950.701
출항국가0.6310.2911.0000.3920.1340.2770.117
선박국적0.3410.1640.3921.0000.1670.1470.070
소독대행업체0.1460.6700.1340.1671.0000.1620.845
검역구분0.0680.0950.2770.1470.1621.0000.136
소독약품0.0970.7010.1170.0700.8450.1361.000
2023-12-13T08:02:39.956252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고철적재량(M-TON)검역구분선박국적출항국가수입국가수입자소독대행업체소독약품
고철적재량(M-TON)1.0000.0790.2980.4520.3970.1760.0700.076
검역구분0.0791.0000.1470.2770.0680.0950.1620.136
선박국적0.2980.1471.0000.3920.3410.1640.1670.070
출항국가0.4520.2770.3921.0000.6310.2910.1340.117
수입국가0.3970.0680.3410.6311.0000.1750.1460.097
수입자0.1760.0950.1640.2910.1751.0000.6700.701
소독대행업체0.0700.1620.1670.1340.1460.6701.0000.845
소독약품0.0760.1360.0700.1170.0970.7010.8451.000

Missing values

2023-12-13T08:02:35.866528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:02:36.031336image/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

검역구분검역일시선박명선박국적출항국가고철적재량(M-TON)수입국가수입자소독대행업체소독일시1소독약품
0전자2022-01-01 00:00AN LAN벨리즈일본20085일본현대제철거륭방제2022-01-01 - 2022-01-02싸이퍼골드유제
1전자2022-01-02 00:00WEN XIANG파나마일본2000일본현대제철웨스턴방역2022-01-01 - 2022-01-02롱다운플러스
2전자2022-01-02 10:00KS SUNRISE한국일본3142일본현대제철거륭방제2022-01-02 - 2022-01-03싸이퍼골드유제
3승선2022-01-02 20:39YU LIN토고일본2092일본동국제강거륭2022-01-02 - 2022-01-03싸이퍼골드유제
4전자2022-01-02 00:00QING RU벨리즈일본1920일본현대제철거륭방제2022-01-02 - 2022-01-03싸이퍼골드유제
5전자2022-01-03 10:00KAI DA토고일본2100일본현대제철거륭방제2022-01-03 - 2022-01-04싸이퍼골드유제
6전자2022-01-02 10:00SJ ANGEL한국일본2234일본동성로지스틱국제종합방제2022-01-03 - 2022-01-05메가유제
7전자2022-01-04 00:00BAO YUE파나마일본3150일본동국제강거륭2022-01-04 - 2022-01-05싸이퍼골드유제
8전자2022-01-04 19:19MV. POLARIS NH벨리즈일본2000일본YK스틸아주종합방제2022-01-05 - 2022-01-06메가유제
9전자2022-01-05 00:00WEN XIANG파나마한국1972일본동국제강거륭2022-01-05 - 2022-01-06싸이퍼골드유제
검역구분검역일시선박명선박국적출항국가고철적재량(M-TON)수입국가수입자소독대행업체소독일시1소독약품
1008승선2022-12-27 00:00MING DA시에라리온일본2010일본현대제철(주)(주)태관주택종합관리2022-12-27 - 2022-12-28델타싸이드
1009전자2022-12-28 12:30EVER SUNNY파나마일본2617일본동국제강(주)거륭2022-12-28 - 2022-12-29싸이퍼골드유제
1010전자2022-12-27 00:00SJ HONOR한국일본835일본세아국제종합방제2022-12-27 - 2022-12-29메가유제
1011전자2022-12-27 00:00KUN YI파나마일본2625일본대한제강아주종합방제2022-12-28 - 2022-12-30메가유제
1012전자2022-12-27 00:00WEN SHAN파나마일본2606일본대한제강아주종합방제2022-12-28 - 2022-12-30메가유제
1013승선2022-12-29 18:50DONG YUAN 17토고한국3130일본동국제강(주)거륭2022-12-29 - 2022-12-30싸이퍼골드유제
1014전자2022-12-26 10:30XINXIWANGMINGYUAN벨리즈일본3148일본동성로지스틱국제종합방제2022-12-26 - 2022-12-30메가유제
1015전자2022-12-29 00:00SHENG WEI 1벨리즈일본3267일본현대제철(주)(주)태관주택종합관리2022-12-29 - 2022-12-30델타싸이드
1016완료2022-12-30 18:00DORIS카메룬한국1935일본동국제강(주)거륭2022-12-30 - 2022-12-31싸이퍼골드유제
1017전자2022-12-31 00:00SHENG SHI 569팔라우한국1917일본현대제철(주)(주)태관주택종합관리2022-12-31 - 2022-12-31델타싸이드