Overview

Dataset statistics

Number of variables21
Number of observations49
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.9 KiB
Average record size in memory185.7 B

Variable types

Numeric15
Text1
Categorical3
DateTime2

Dataset

DescriptionSample
Author올시데이터
URLhttps://www.bigdata-sea.kr/datasearch/base/view.do?prodId=PROD_001286

Alerts

SHIP_KIND is highly imbalanced (85.6%)Imbalance
MMSI has unique valuesUnique
IMO_IDNTF_NO has unique valuesUnique
SHIP_NM has unique valuesUnique
DPTRP_LA has unique valuesUnique
DPTRP_LO has unique valuesUnique
DTNT_LA has unique valuesUnique
DTNT_LO has unique valuesUnique
FRGHT_CNVNC_QTY has unique valuesUnique
FRGHT_CNVNC_QTY_TONM has unique valuesUnique
RN has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:54:03.100431
Analysis finished2023-12-10 14:54:03.478555
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

MMSI
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5300014 × 108
Minimum5.4221533 × 108
Maximum5.5965733 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:03.598880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.4221533 × 108
5-th percentile5.5166131 × 108
Q15.5169193 × 108
median5.5353933 × 108
Q35.5374033 × 108
95-th percentile5.5383233 × 108
Maximum5.5965733 × 108
Range17442000
Interquartile range (IQR)2048400

Descriptive statistics

Standard deviation2035029.1
Coefficient of variation (CV)0.0036799794
Kurtosis18.19942
Mean5.5300014 × 108
Median Absolute Deviation (MAD)208000
Skewness-2.5286243
Sum2.7097007 × 1010
Variance4.1413435 × 1012
MonotonicityNot monotonic
2023-12-10T23:54:03.807735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
542215333 1
 
2.0%
551668233 1
 
2.0%
553722333 1
 
2.0%
553834333 1
 
2.0%
553836333 1
 
2.0%
553826333 1
 
2.0%
553828333 1
 
2.0%
553829333 1
 
2.0%
553820333 1
 
2.0%
553821333 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
542215333 1
2.0%
551361693 1
2.0%
551660233 1
2.0%
551662933 1
2.0%
551668233 1
2.0%
551672933 1
2.0%
551673233 1
2.0%
551675233 1
2.0%
551686933 1
2.0%
551687933 1
2.0%
ValueCountFrequency (%)
559657333 1
2.0%
553836333 1
2.0%
553834333 1
2.0%
553829333 1
2.0%
553828333 1
2.0%
553826333 1
2.0%
553821333 1
2.0%
553820333 1
2.0%
553749333 1
2.0%
553748333 1
2.0%

IMO_IDNTF_NO
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2595514.8
Minimum2132158
Maximum2965323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:04.091367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2132158
5-th percentile2144320.4
Q12578077
median2635112
Q32654871
95-th percentile2783964.2
Maximum2965323
Range833165
Interquartile range (IQR)76794

Descriptive statistics

Standard deviation160089.19
Coefficient of variation (CV)0.061679164
Kurtosis3.899412
Mean2595514.8
Median Absolute Deviation (MAD)47273
Skewness-1.5866014
Sum1.2718023 × 108
Variance2.5628548 × 1010
MonotonicityNot monotonic
2023-12-10T23:54:04.370230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
2548412 1
 
2.0%
2522016 1
 
2.0%
2654869 1
 
2.0%
2654871 1
 
2.0%
2654883 1
 
2.0%
2682335 1
 
2.0%
2682359 1
 
2.0%
2682361 1
 
2.0%
2682373 1
 
2.0%
2682385 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
2132158 1
2.0%
2132160 1
2.0%
2132172 1
2.0%
2162543 1
2.0%
2522016 1
2.0%
2522028 1
2.0%
2522133 1
2.0%
2522951 1
2.0%
2522987 1
2.0%
2527602 1
2.0%
ValueCountFrequency (%)
2965323 1
2.0%
2783971 1
2.0%
2783969 1
2.0%
2783957 1
2.0%
2764963 1
2.0%
2695667 1
2.0%
2682385 1
2.0%
2682373 1
2.0%
2682361 1
2.0%
2682359 1
2.0%

SHIP_NM
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-10T23:54:04.752099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length16
Mean length12.55102
Min length10

Characters and Unicode

Total characters615
Distinct characters35
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st rowMrkdqqhvPdhuvn
2nd rowPrjhqvPdhuvn
3rd rowFkduorwwhPdhuvn
4th rowFruqholdPdhuvn
5th rowFroxpelqhPdhuvn
ValueCountFrequency (%)
mrkdqqhvpdhuvn 1
 
2.0%
hyhobqpdhuvn 1
 
2.0%
hoobpdhuvn 1
 
2.0%
hglwkpdhuvn 1
 
2.0%
hxjhqpdhuvn 1
 
2.0%
jhuqhupdhuvn 1
 
2.0%
jxqkloghpdhuvn 1
 
2.0%
jxvwdypdhuvn 1
 
2.0%
jxwkruppdhuvn 1
 
2.0%
jhugdpdhuvn 1
 
2.0%
Other values (39) 39
79.6%
2023-12-10T23:54:05.357921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
h 69
11.2%
d 68
 
11.1%
u 67
 
10.9%
P 64
 
10.4%
v 42
 
6.8%
n 34
 
5.5%
F 29
 
4.7%
o 25
 
4.1%
J 23
 
3.7%
w 23
 
3.7%
Other values (25) 171
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 451
73.3%
Uppercase Letter 164
 
26.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
h 69
15.3%
d 68
15.1%
u 67
14.9%
v 42
9.3%
n 34
7.5%
o 25
 
5.5%
w 23
 
5.1%
r 22
 
4.9%
q 22
 
4.9%
l 15
 
3.3%
Other values (12) 64
14.2%
Uppercase Letter
ValueCountFrequency (%)
P 64
39.0%
F 29
17.7%
J 23
 
14.0%
D 20
 
12.2%
H 8
 
4.9%
I 4
 
2.4%
R 4
 
2.4%
W 3
 
1.8%
O 2
 
1.2%
V 2
 
1.2%
Other values (3) 5
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 615
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
h 69
11.2%
d 68
 
11.1%
u 67
 
10.9%
P 64
 
10.4%
v 42
 
6.8%
n 34
 
5.5%
F 29
 
4.7%
o 25
 
4.1%
J 23
 
3.7%
w 23
 
3.7%
Other values (25) 171
27.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
h 69
11.2%
d 68
 
11.1%
u 67
 
10.9%
P 64
 
10.4%
v 42
 
6.8%
n 34
 
5.5%
F 29
 
4.7%
o 25
 
4.1%
J 23
 
3.7%
w 23
 
3.7%
Other values (25) 171
27.8%

SHIP_KIND
Categorical

IMBALANCE 

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
Container
48 
Container(add)
 
1

Length

Max length14
Median length9
Mean length9.1020408
Min length9

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
Container 48
98.0%
Container(add) 1
 
2.0%

Length

2023-12-10T23:54:05.581256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:54:05.721944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
container 48
98.0%
container(add 1
 
2.0%

SHIP_WDTH
Real number (ℝ)

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.269388
Minimum23
Maximum61.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:05.840857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile29.2
Q142.8
median42.8
Q342.8
95-th percentile56.4
Maximum61.3
Range38.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.6452589
Coefficient of variation (CV)0.19980081
Kurtosis0.093521089
Mean43.269388
Median Absolute Deviation (MAD)0
Skewness0.14267482
Sum2120.2
Variance74.740502
MonotonicityNot monotonic
2023-12-10T23:54:05.999545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
42.8 28
57.1%
56.4 8
 
16.3%
32.2 4
 
8.2%
35.6 3
 
6.1%
27.2 2
 
4.1%
59.0 1
 
2.0%
37.3 1
 
2.0%
23.0 1
 
2.0%
61.3 1
 
2.0%
ValueCountFrequency (%)
23.0 1
 
2.0%
27.2 2
 
4.1%
32.2 4
 
8.2%
35.6 3
 
6.1%
37.3 1
 
2.0%
42.8 28
57.1%
56.4 8
 
16.3%
59.0 1
 
2.0%
61.3 1
 
2.0%
ValueCountFrequency (%)
61.3 1
 
2.0%
59.0 1
 
2.0%
56.4 8
 
16.3%
42.8 28
57.1%
37.3 1
 
2.0%
35.6 3
 
6.1%
32.2 4
 
8.2%
27.2 2
 
4.1%
23.0 1
 
2.0%

SHIP_LNTH
Real number (ℝ)

Distinct17
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean313.50816
Minimum104.4
Maximum393.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:06.153662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104.4
5-th percentile170.92
Q1314.7
median336.4
Q3351.1
95-th percentile376
Maximum393.9
Range289.5
Interquartile range (IQR)36.4

Descriptive statistics

Standard deviation69.031722
Coefficient of variation (CV)0.22019115
Kurtosis1.0962734
Mean313.50816
Median Absolute Deviation (MAD)17.4
Skewness-1.3949856
Sum15361.9
Variance4765.3787
MonotonicityNot monotonic
2023-12-10T23:54:06.338244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
351.1 10
20.4%
376.0 8
16.3%
336.4 6
12.2%
331.5 4
 
8.2%
314.7 3
 
6.1%
210.0 3
 
6.1%
319.0 3
 
6.1%
224.8 2
 
4.1%
154.6 2
 
4.1%
333.4 1
 
2.0%
Other values (7) 7
14.3%
ValueCountFrequency (%)
104.4 1
 
2.0%
154.6 2
4.1%
195.4 1
 
2.0%
210.0 3
6.1%
224.0 1
 
2.0%
224.8 2
4.1%
252.4 1
 
2.0%
314.7 3
6.1%
319.0 3
6.1%
328.9 1
 
2.0%
ValueCountFrequency (%)
393.9 1
 
2.0%
376.2 1
 
2.0%
376.0 8
16.3%
351.1 10
20.4%
336.4 6
12.2%
333.4 1
 
2.0%
331.5 4
 
8.2%
328.9 1
 
2.0%
319.0 3
 
6.1%
314.7 3
 
6.1%

SHIP_HGHT
Real number (ℝ)

Distinct13
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.095918
Minimum14
Maximum33.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:06.524103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile15.68
Q124.1
median24.1
Q324.6
95-th percentile30.2
Maximum33.5
Range19.5
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation4.5522869
Coefficient of variation (CV)0.18892357
Kurtosis-0.020859702
Mean24.095918
Median Absolute Deviation (MAD)0.5
Skewness-0.32704816
Sum1180.7
Variance20.723316
MonotonicityNot monotonic
2023-12-10T23:54:06.805578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
24.1 20
40.8%
30.2 8
 
16.3%
24.6 6
 
12.2%
18.3 3
 
6.1%
18.5 2
 
4.1%
14.0 2
 
4.1%
27.3 2
 
4.1%
16.4 1
 
2.0%
30.3 1
 
2.0%
18.2 1
 
2.0%
Other values (3) 3
 
6.1%
ValueCountFrequency (%)
14.0 2
 
4.1%
15.2 1
 
2.0%
16.4 1
 
2.0%
18.2 1
 
2.0%
18.3 3
 
6.1%
18.5 2
 
4.1%
21.4 1
 
2.0%
24.1 20
40.8%
24.6 6
 
12.2%
27.3 2
 
4.1%
ValueCountFrequency (%)
33.5 1
 
2.0%
30.3 1
 
2.0%
30.2 8
 
16.3%
27.3 2
 
4.1%
24.6 6
 
12.2%
24.1 20
40.8%
21.4 1
 
2.0%
18.5 2
 
4.1%
18.3 3
 
6.1%
18.2 1
 
2.0%

SHIP_OWNER_NM
Categorical

Distinct4
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
Pdhuvn
34 
FPDFJP
11 
3
 
2
Pduiuhw
 
2

Length

Max length7
Median length6
Mean length5.8367347
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Pdhuvn 34
69.4%
FPDFJP 11
 
22.4%
3 2
 
4.1%
Pduiuhw 2
 
4.1%

Length

2023-12-10T23:54:07.033590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:54:07.208691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pdhuvn 34
69.4%
fpdfjp 11
 
22.4%
3 2
 
4.1%
pduiuhw 2
 
4.1%

DRAFT
Real number (ℝ)

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.214286
Minimum8.2
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:07.734663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.2
5-th percentile10.36
Q114.5
median14.5
Q315
95-th percentile16
Maximum17
Range8.8
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation1.8527007
Coefficient of variation (CV)0.13034075
Kurtosis1.7677261
Mean14.214286
Median Absolute Deviation (MAD)0.5
Skewness-1.3644998
Sum696.5
Variance3.4325
MonotonicityNot monotonic
2023-12-10T23:54:07.895787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
14.5 20
40.8%
16.0 11
22.4%
12.0 6
 
12.2%
15.0 6
 
12.2%
9.8 2
 
4.1%
11.2 1
 
2.0%
17.0 1
 
2.0%
12.5 1
 
2.0%
8.2 1
 
2.0%
ValueCountFrequency (%)
8.2 1
 
2.0%
9.8 2
 
4.1%
11.2 1
 
2.0%
12.0 6
 
12.2%
12.5 1
 
2.0%
14.5 20
40.8%
15.0 6
 
12.2%
16.0 11
22.4%
17.0 1
 
2.0%
ValueCountFrequency (%)
17.0 1
 
2.0%
16.0 11
22.4%
15.0 6
 
12.2%
14.5 20
40.8%
12.5 1
 
2.0%
12.0 6
 
12.2%
11.2 1
 
2.0%
9.8 2
 
4.1%
8.2 1
 
2.0%

SHPYRD_NM
Categorical

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
RghqvhOlqgr
29 
Yronvzhuiw
4 
KbxqgdlKLXovdq
4 
KbxqgdlVdpkrKL
3 
VdpvxqjKL
3 
Other values (4)
6 

Length

Max length15
Median length11
Mean length11.612245
Min length9

Unique

Unique3 ?
Unique (%)6.1%

Sample

1st rowYronvzhuiw
2nd rowGdhzrrGVPH
3rd rowRghqvhOlqgr
4th rowRghqvhOlqgr
5th rowRghqvhOlqgr

Common Values

ValueCountFrequency (%)
RghqvhOlqgr 29
59.2%
Yronvzhuiw 4
 
8.2%
KbxqgdlKLXovdq 4
 
8.2%
KbxqgdlVdpkrKL 3
 
6.1%
VdpvxqjKL 3
 
6.1%
FRVFRKLCkrxvkdq 3
 
6.1%
GdhzrrGVPH 1
 
2.0%
UhprqwrzdUhsdlu 1
 
2.0%
VFVVklsexloglqj 1
 
2.0%

Length

2023-12-10T23:54:08.071414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:54:08.262225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rghqvholqgr 29
59.2%
yronvzhuiw 4
 
8.2%
kbxqgdlklxovdq 4
 
8.2%
kbxqgdlvdpkrkl 3
 
6.1%
vdpvxqjkl 3
 
6.1%
frvfrklckrxvkdq 3
 
6.1%
gdhzrrgvph 1
 
2.0%
uhprqwrzduhsdlu 1
 
2.0%
vfvvklsexloglqj 1
 
2.0%

BULD_YR
Real number (ℝ)

Distinct13
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2006.9184
Minimum2001
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:08.427262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2002
Q12004
median2006
Q32008
95-th percentile2019
Maximum2021
Range20
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.6629601
Coefficient of variation (CV)0.0023234429
Kurtosis2.4034699
Mean2006.9184
Median Absolute Deviation (MAD)2
Skewness1.593759
Sum98339
Variance21.743197
MonotonicityNot monotonic
2023-12-10T23:54:08.603020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2003 7
14.3%
2006 7
14.3%
2005 6
12.2%
2007 6
12.2%
2008 5
10.2%
2002 4
8.2%
2004 3
6.1%
2011 3
6.1%
2019 3
6.1%
2009 2
 
4.1%
Other values (3) 3
6.1%
ValueCountFrequency (%)
2001 1
 
2.0%
2002 4
8.2%
2003 7
14.3%
2004 3
6.1%
2005 6
12.2%
2006 7
14.3%
2007 6
12.2%
2008 5
10.2%
2009 2
 
4.1%
2011 3
6.1%
ValueCountFrequency (%)
2021 1
 
2.0%
2019 3
6.1%
2014 1
 
2.0%
2011 3
6.1%
2009 2
 
4.1%
2008 5
10.2%
2007 6
12.2%
2006 7
14.3%
2005 6
12.2%
2004 3
6.1%

DDWGHT
Real number (ℝ)

Distinct17
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108039.9
Minimum8800
Maximum221250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:08.781049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8800
5-th percentile26796
Q1101612
median109000
Q3115993
95-th percentile174239
Maximum221250
Range212450
Interquartile range (IQR)14381

Descriptive statistics

Standard deviation50033.602
Coefficient of variation (CV)0.46310301
Kurtosis-0.1232713
Mean108039.9
Median Absolute Deviation (MAD)7190
Skewness0.052864078
Sum5293955
Variance2.5033614 × 109
MonotonicityNot monotonic
2023-12-10T23:54:08.927704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
115993 10
20.4%
174239 8
16.3%
109000 6
12.2%
38840 3
 
6.1%
104600 3
 
6.1%
41028 3
 
6.1%
101612 3
 
6.1%
101818 2
 
4.1%
113964 2
 
4.1%
21262 2
 
4.1%
Other values (7) 7
14.3%
ValueCountFrequency (%)
8800 1
 
2.0%
21262 2
4.1%
35097 1
 
2.0%
38840 3
6.1%
41028 3
6.1%
63200 1
 
2.0%
101612 3
6.1%
101810 1
 
2.0%
101818 2
4.1%
104600 3
6.1%
ValueCountFrequency (%)
221250 1
 
2.0%
213971 1
 
2.0%
174239 8
16.3%
115993 10
20.4%
113964 2
 
4.1%
109657 1
 
2.0%
109000 6
12.2%
104600 3
 
6.1%
101818 2
 
4.1%
101810 1
 
2.0%

DPTR_HMS
Date

Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
Minimum2023-01-01 00:00:02
Maximum2023-01-02 22:30:51
2023-12-10T23:54:09.080774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:09.313149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)

ARVL_HMS
Date

Distinct47
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
Minimum2023-01-31 23:49:34
Maximum2023-04-30 23:59:57
2023-12-10T23:54:09.523629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:09.749680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)

DPTRP_LA
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.068818
Minimum-37.973701
Maximum66.941902
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)6.1%
Memory size573.0 B
2023-12-10T23:54:09.980195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-37.973701
5-th percentile-13.947612
Q113.9283
median30.478901
Q336.938702
95-th percentile52.387479
Maximum66.941902
Range104.9156
Interquartile range (IQR)23.010402

Descriptive statistics

Standard deviation20.609665
Coefficient of variation (CV)0.79058685
Kurtosis1.7487754
Mean26.068818
Median Absolute Deviation (MAD)10.719601
Skewness-1.0083321
Sum1277.3721
Variance424.75829
MonotonicityNot monotonic
2023-12-10T23:54:10.215374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1.21557 1
 
2.0%
35.693699 1
 
2.0%
49.596001 1
 
2.0%
12.2146 1
 
2.0%
14.0867 1
 
2.0%
31.9578 1
 
2.0%
36.77 1
 
2.0%
36.787498 1
 
2.0%
40.664902 1
 
2.0%
22.888599 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
-37.973701 1
2.0%
-26.7813 1
2.0%
-24.0564 1
2.0%
1.21557 1
2.0%
1.76955 1
2.0%
5.99 1
2.0%
8.82977 1
2.0%
10.0783 1
2.0%
11.7161 1
2.0%
12.1016 1
2.0%
ValueCountFrequency (%)
66.941902 1
2.0%
53.597099 1
2.0%
52.657799 1
2.0%
51.981998 1
2.0%
50.535599 1
2.0%
49.596001 1
2.0%
48.34 1
2.0%
44.4184 1
2.0%
43.7206 1
2.0%
40.664902 1
2.0%

DPTRP_LO
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.822911
Minimum-160.41701
Maximum144.87199
Zeros0
Zeros (%)0.0%
Negative22
Negative (%)44.9%
Memory size573.0 B
2023-12-10T23:54:10.429949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-160.41701
5-th percentile-113.2826
Q1-74.144798
median6.27167
Q3103.562
95-th percentile127.4328
Maximum144.87199
Range305.289
Interquartile range (IQR)177.70679

Descriptive statistics

Standard deviation87.21604
Coefficient of variation (CV)8.0584641
Kurtosis-1.28253
Mean10.822911
Median Absolute Deviation (MAD)81.588374
Skewness-0.035312928
Sum530.32264
Variance7606.6376
MonotonicityNot monotonic
2023-12-10T23:54:10.648348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
103.561996 1
 
2.0%
120.921997 1
 
2.0%
-3.8624 1
 
2.0%
58.401501 1
 
2.0%
49.9767 1
 
2.0%
125.790001 1
 
2.0%
-75.506699 1
 
2.0%
-75.566704 1
 
2.0%
-74.144798 1
 
2.0%
117.348 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
-160.417007 1
2.0%
-130.516006 1
2.0%
-118.126999 1
2.0%
-106.015999 1
2.0%
-95.117699 1
2.0%
-90.790001 1
2.0%
-82.133301 1
2.0%
-79.521599 1
2.0%
-75.566704 1
2.0%
-75.506699 1
2.0%
ValueCountFrequency (%)
144.871994 1
2.0%
128.679993 1
2.0%
128.528 1
2.0%
125.790001 1
2.0%
124.955002 1
2.0%
122.800003 1
2.0%
122.523003 1
2.0%
122.288002 1
2.0%
120.921997 1
2.0%
120.705002 1
2.0%

DTNT_LA
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.29029
Minimum-37.698299
Maximum61.307301
Zeros0
Zeros (%)0.0%
Negative3
Negative (%)6.1%
Memory size573.0 B
2023-12-10T23:54:10.893670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-37.698299
5-th percentile-0.904498
Q111.2
median24.4055
Q334.8895
95-th percentile50.553279
Maximum61.307301
Range99.0056
Interquartile range (IQR)23.6895

Descriptive statistics

Standard deviation19.065788
Coefficient of variation (CV)0.81861529
Kurtosis2.1601928
Mean23.29029
Median Absolute Deviation (MAD)11.137202
Skewness-0.89667679
Sum1141.2242
Variance363.50426
MonotonicityNot monotonic
2023-12-10T23:54:11.137095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1.28469 1
 
2.0%
18.7967 1
 
2.0%
36.487499 1
 
2.0%
31.4333 1
 
2.0%
12.1567 1
 
2.0%
30.3633 1
 
2.0%
22.0783 1
 
2.0%
33.321602 1
 
2.0%
10.0267 1
 
2.0%
22.508301 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
-37.698299 1
2.0%
-32.495098 1
2.0%
-2.35273 1
2.0%
1.26785 1
2.0%
1.28469 1
2.0%
6.00225 1
2.0%
7.2282 1
2.0%
8.81153 1
2.0%
8.87042 1
2.0%
9.925 1
2.0%
ValueCountFrequency (%)
61.307301 1
2.0%
54.285 1
2.0%
51.286598 1
2.0%
49.4533 1
2.0%
48.516602 1
2.0%
47.728298 1
2.0%
40.669998 1
2.0%
40.006302 1
2.0%
36.487499 1
2.0%
36.3279 1
2.0%

DTNT_LO
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5883858
Minimum-162.907
Maximum142.199
Zeros0
Zeros (%)0.0%
Negative22
Negative (%)44.9%
Memory size573.0 B
2023-12-10T23:54:11.354311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-162.907
5-th percentile-128.7944
Q1-75.876999
median15.7535
Q395.160103
95-th percentile125.6974
Maximum142.199
Range305.106
Interquartile range (IQR)171.0371

Descriptive statistics

Standard deviation90.435601
Coefficient of variation (CV)16.182777
Kurtosis-1.3411598
Mean5.5883858
Median Absolute Deviation (MAD)89.895201
Skewness-0.081675629
Sum273.8309
Variance8178.5979
MonotonicityNot monotonic
2023-12-10T23:54:11.555368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
103.918999 1
 
2.0%
72.621696 1
 
2.0%
14.3198 1
 
2.0%
32.4753 1
 
2.0%
72.696701 1
 
2.0%
122.769997 1
 
2.0%
114.232002 1
 
2.0%
26.8172 1
 
2.0%
71.366096 1
 
2.0%
-110.550003 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
-162.906998 1
2.0%
-153.897003 1
2.0%
-130.360001 1
2.0%
-126.445999 1
2.0%
-110.550003 1
2.0%
-95.008301 1
2.0%
-90.536697 1
2.0%
-84.761703 1
2.0%
-79.987099 1
2.0%
-79.5354 1
2.0%
ValueCountFrequency (%)
142.199005 1
2.0%
132.740005 1
2.0%
127.649002 1
2.0%
122.769997 1
2.0%
122.059998 1
2.0%
122.041 1
2.0%
116.362999 1
2.0%
114.285004 1
2.0%
114.232002 1
2.0%
114.116997 1
2.0%

FRGHT_CNVNC_QTY
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2683678 × 108
Minimum23742200
Maximum3.86347 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:11.730782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23742200
5-th percentile74983900
Q11.73391 × 108
median2.21312 × 108
Q32.89778 × 108
95-th percentile3.717266 × 108
Maximum3.86347 × 108
Range3.626048 × 108
Interquartile range (IQR)1.16387 × 108

Descriptive statistics

Standard deviation91335042
Coefficient of variation (CV)0.40264653
Kurtosis-0.41066361
Mean2.2683678 × 108
Median Absolute Deviation (MAD)63144000
Skewness-0.12860025
Sum1.1115002 × 1010
Variance8.3420899 × 1015
MonotonicityNot monotonic
2023-12-10T23:54:11.907880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
133592000 1
 
2.0%
179741000 1
 
2.0%
259754000 1
 
2.0%
182113000 1
 
2.0%
372827000 1
 
2.0%
142029000 1
 
2.0%
182757000 1
 
2.0%
307853000 1
 
2.0%
252061000 1
 
2.0%
327447000 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
23742200 1
2.0%
25269900 1
2.0%
72321500 1
2.0%
78977500 1
2.0%
119740000 1
2.0%
133592000 1
2.0%
137666000 1
2.0%
142029000 1
2.0%
147305000 1
2.0%
149246000 1
2.0%
ValueCountFrequency (%)
386347000 1
2.0%
374348000 1
2.0%
372827000 1
2.0%
370076000 1
2.0%
366596000 1
2.0%
354159000 1
2.0%
352004000 1
2.0%
347397000 1
2.0%
327447000 1
2.0%
307853000 1
2.0%

FRGHT_CNVNC_QTY_TONM
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336240.16
Minimum88478
Maximum722830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:12.119734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum88478
5-th percentile131741.2
Q1227960
median314142
Q3405408
95-th percentile567735.2
Maximum722830
Range634352
Interquartile range (IQR)177448

Descriptive statistics

Standard deviation149466.6
Coefficient of variation (CV)0.44452333
Kurtosis-0.069505353
Mean336240.16
Median Absolute Deviation (MAD)88642
Skewness0.63878353
Sum16475768
Variance2.2340264 × 1010
MonotonicityNot monotonic
2023-12-10T23:54:12.278893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
561536 1
 
2.0%
243704 1
 
2.0%
285524 1
 
2.0%
399750 1
 
2.0%
722830 1
 
2.0%
129970 1
 
2.0%
262646 1
 
2.0%
254610 1
 
2.0%
134398 1
 
2.0%
314142 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
88478 1
2.0%
103566 1
2.0%
129970 1
2.0%
134398 1
2.0%
143090 1
2.0%
171380 1
2.0%
198030 1
2.0%
211232 1
2.0%
214266 1
2.0%
216398 1
2.0%
ValueCountFrequency (%)
722830 1
2.0%
685848 1
2.0%
568260 1
2.0%
566948 1
2.0%
561536 1
2.0%
533492 1
2.0%
530212 1
2.0%
520700 1
2.0%
508154 1
2.0%
504956 1
2.0%

RN
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26
Minimum2
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-10T23:54:12.482674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4.4
Q114
median26
Q338
95-th percentile47.6
Maximum50
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.54956501
Kurtosis-1.2
Mean26
Median Absolute Deviation (MAD)12
Skewness0
Sum1274
Variance204.16667
MonotonicityStrictly increasing
2023-12-10T23:54:12.731759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
2 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
11 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

Sample

MMSIIMO_IDNTF_NOSHIP_NMSHIP_KINDSHIP_WDTHSHIP_LNTHSHIP_HGHTSHIP_OWNER_NMDRAFTSHPYRD_NMBULD_YRDDWGHTDPTR_HMSARVL_HMSDPTRP_LADPTRP_LODTNT_LADTNT_LOFRGHT_CNVNC_QTYFRGHT_CNVNC_QTY_TONMRN
05422153332548412MrkdqqhvPdhuvnContainer32.2195.416.4Pdhuvn11.2Yronvzhuiw20013509702-Jan-2023 22:30:5130-Apr-2023 23:48:281.21557103.5619961.28469103.9189991335920005615362
15533433332965323PrjhqvPdhuvnContainer59.0376.230.3Pdhuvn17.0GdhzrrGVPH201421397101-Jan-2023 04:42:1430-Apr-2023 23:59:3153.5970998.5164516.04050141.3370022647940002325523
25533823332578077FkduorwwhPdhuvnContainer42.8331.524.1Pdhuvn14.5RghqvhOlqgr200210965701-Jan-2023 00:00:0230-Apr-2023 23:56:21-26.7813-95.1176998.81153-79.53541473050002112324
35533943332578089FruqholdPdhuvnContainer42.8331.524.1Pdhuvn14.5RghqvhOlqgr200210460001-Jan-2023 00:05:3030-Apr-2023 23:59:5634.068501128.67999340.006302-61.8182982897780003203745
45534523332578091FroxpelqhPdhuvnContainer42.8331.524.1Pdhuvn14.5RghqvhOlqgr200210460001-Jan-2023 00:00:4730-Apr-2023 23:59:5722.294537.65969822.3323114.1169972172080001035666
55534973332578003FohphqwlqhPdhuvnContainer42.8331.524.1Pdhuvn14.5RghqvhOlqgr200210460001-Jan-2023 00:00:5031-Jan-2023 23:49:3430.478901122.28800232.2076142.19900523742200884787
65534103332593742DahoPdhuvnContainer42.8336.424.1Pdhuvn14.5RghqvhOlqgr200310900001-Jan-2023 00:01:3530-Apr-2023 23:59:2639.9823-65.00050425.56010135.5971981533330002163988
75534213332584947RojdPdhuvnContainer32.2224.818.2Pdhuvn12.0Yronvzhuiw20034102801-Jan-2023 00:01:4330-Apr-2023 23:59:3625.248301-73.516701-37.698299132.7400053473970005081549
85534223332593754DqqdPdhuvnContainer42.8336.424.1Pdhuvn14.5RghqvhOlqgr200310900001-Jan-2023 00:00:1530-Apr-2023 23:58:3852.657799-130.51600654.285-130.36000128445600036932810
95535393332593766DuqrogPdhuvnContainer42.8336.424.1Pdhuvn14.5RghqvhOlqgr200310900001-Jan-2023 00:05:4730-Apr-2023 23:45:4725.953335.29499826.530001-78.76329824375500035342011
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