Overview

Dataset statistics

Number of variables35
Number of observations10000
Missing cells29961
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 MiB
Average record size in memory308.0 B

Variable types

Numeric19
DateTime3
Categorical3
Text10

Dataset

Description지능형 해상교통정보시스템(바다내비)에서 선내 시스템 원격 모니터링 서비스(SV20)를 위핸 여객선 운항전 검사에 대한 데이터 테이블임
Author해양수산부
URLhttps://www.data.go.kr/data/15121569/fileData.do

Alerts

안전점검표상태코드 is highly imbalanced (92.4%)Imbalance
화물적재한도중량 has 1664 (16.6%) missing valuesMissing
실제화물적재중량 has 1663 (16.6%) missing valuesMissing
차량화물수 has 1669 (16.7%) missing valuesMissing
차량화물단위값 has 1663 (16.6%) missing valuesMissing
일반화물단위값 has 1663 (16.6%) missing valuesMissing
컨테이너수 has 1665 (16.7%) missing valuesMissing
컨테이너단위값 has 1663 (16.6%) missing valuesMissing
수정자ID has 9890 (98.9%) missing valuesMissing
흘수비고내용 has 8291 (82.9%) missing valuesMissing
출항시간 has 117 (1.2%) missing valuesMissing
흘수선수값 is highly skewed (γ1 = 99.67894788)Skewed
흘수중앙값 is highly skewed (γ1 = 62.16018986)Skewed
흘수선미값 is highly skewed (γ1 = 75.36391198)Skewed
실제임시승선인원수 is highly skewed (γ1 = 43.64666637)Skewed
컨테이너수 is highly skewed (γ1 = 27.78531737)Skewed
안전점검표순번 has unique valuesUnique
흘수선수값 has 781 (7.8%) zerosZeros
흘수중앙값 has 8569 (85.7%) zerosZeros
흘수선미값 has 1321 (13.2%) zerosZeros
최대임시승선인원수 has 9216 (92.2%) zerosZeros
여객대인인원수 has 134 (1.3%) zerosZeros
여객소인인원수 has 5272 (52.7%) zerosZeros
여객유아인원수 has 9295 (93.0%) zerosZeros
실제임시승선인원수 has 9853 (98.5%) zerosZeros
실제화물적재중량 has 439 (4.4%) zerosZeros
차량화물수 has 470 (4.7%) zerosZeros
차량화물단위값 has 476 (4.8%) zerosZeros
일반화물단위값 has 7206 (72.1%) zerosZeros
컨테이너수 has 7940 (79.4%) zerosZeros
컨테이너단위값 has 7937 (79.4%) zerosZeros

Reproduction

Analysis started2023-12-12 03:03:34.259901
Analysis finished2023-12-12 03:03:35.806599
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전점검표순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239740.35
Minimum212277
Maximum274359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:35.891275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum212277
5-th percentile214866.55
Q1226108.25
median239425.5
Q3253198.25
95-th percentile265529.1
Maximum274359
Range62082
Interquartile range (IQR)27090

Descriptive statistics

Standard deviation16141.268
Coefficient of variation (CV)0.067328127
Kurtosis-1.156811
Mean239740.35
Median Absolute Deviation (MAD)13586
Skewness0.06024386
Sum2.3974035 × 109
Variance2.6054055 × 108
MonotonicityNot monotonic
2023-12-12T12:03:36.070738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
257624 1
 
< 0.1%
218230 1
 
< 0.1%
222816 1
 
< 0.1%
227759 1
 
< 0.1%
253152 1
 
< 0.1%
212831 1
 
< 0.1%
221202 1
 
< 0.1%
265207 1
 
< 0.1%
238381 1
 
< 0.1%
265192 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
212277 1
< 0.1%
212280 1
< 0.1%
212283 1
< 0.1%
212285 1
< 0.1%
212291 1
< 0.1%
212292 1
< 0.1%
212293 1
< 0.1%
212295 1
< 0.1%
212299 1
< 0.1%
212300 1
< 0.1%
ValueCountFrequency (%)
274359 1
< 0.1%
274358 1
< 0.1%
274352 1
< 0.1%
272018 1
< 0.1%
269365 1
< 0.1%
269355 1
< 0.1%
269350 1
< 0.1%
269349 1
< 0.1%
269333 1
< 0.1%
269329 1
< 0.1%
Distinct7879
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-08-03 10:20:00
Maximum2021-12-18 08:00:00
2023-12-12T12:03:36.274582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:36.458573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
8338 
1
1662 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 8338
83.4%
1 1662
 
16.6%

Length

2023-12-12T12:03:36.621106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:03:37.049783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 8338
83.4%
1 1662
 
16.6%
Distinct52
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:03:37.262781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowG000
2nd rowF000
3rd rowL060
4th rowL000
5th rowL000
ValueCountFrequency (%)
l000 1171
 
11.7%
f000 864
 
8.6%
e000 796
 
8.0%
e002 792
 
7.9%
k000 512
 
5.1%
e054 505
 
5.1%
h008 448
 
4.5%
l060 429
 
4.3%
g000 414
 
4.1%
h016 381
 
3.8%
Other values (42) 3688
36.9%
2023-12-12T12:03:37.679497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 21858
54.6%
E 2648
 
6.6%
L 2065
 
5.2%
H 1449
 
3.6%
F 1448
 
3.6%
2 1206
 
3.0%
6 1101
 
2.8%
4 1095
 
2.7%
1 1081
 
2.7%
5 1020
 
2.5%
Other values (11) 5029
 
12.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30000
75.0%
Uppercase Letter 10000
 
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2648
26.5%
L 2065
20.6%
H 1449
14.5%
F 1448
14.5%
G 664
 
6.6%
K 618
 
6.2%
J 486
 
4.9%
M 336
 
3.4%
N 156
 
1.6%
C 79
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 21858
72.9%
2 1206
 
4.0%
6 1101
 
3.7%
4 1095
 
3.6%
1 1081
 
3.6%
5 1020
 
3.4%
3 837
 
2.8%
8 735
 
2.5%
9 689
 
2.3%
7 378
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 30000
75.0%
Latin 10000
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2648
26.5%
L 2065
20.6%
H 1449
14.5%
F 1448
14.5%
G 664
 
6.6%
K 618
 
6.2%
J 486
 
4.9%
M 336
 
3.4%
N 156
 
1.6%
C 79
 
0.8%
Common
ValueCountFrequency (%)
0 21858
72.9%
2 1206
 
4.0%
6 1101
 
3.7%
4 1095
 
3.6%
1 1081
 
3.6%
5 1020
 
3.4%
3 837
 
2.8%
8 735
 
2.5%
9 689
 
2.3%
7 378
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 21858
54.6%
E 2648
 
6.6%
L 2065
 
5.2%
H 1449
 
3.6%
F 1448
 
3.6%
2 1206
 
3.0%
6 1101
 
2.8%
4 1095
 
2.7%
1 1081
 
2.7%
5 1020
 
2.5%
Other values (11) 5029
 
12.6%
Distinct153
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:03:38.114377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.9496
Min length7

Characters and Unicode

Total characters89496
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st rowMPR156209
2nd rowMPR156214
3rd rowCMR164405
4th rowCMR194402
5th rowSPR992939
ValueCountFrequency (%)
ysr015689 210
 
2.1%
9819480 206
 
2.1%
cmr087839 171
 
1.7%
dsr069014 167
 
1.7%
ysr182817 165
 
1.7%
dsr177814 162
 
1.6%
spr992939 161
 
1.6%
wdr166705 147
 
1.5%
ksr155801 146
 
1.5%
mpr166212 144
 
1.4%
Other values (143) 8321
83.2%
2023-12-12T12:03:38.743839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11690
13.1%
R 9612
10.7%
0 9382
10.5%
4 7185
 
8.0%
6 6083
 
6.8%
8 5541
 
6.2%
7 4773
 
5.3%
2 4627
 
5.2%
9 4586
 
5.1%
M 4545
 
5.1%
Other values (16) 21472
24.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60255
67.3%
Uppercase Letter 29241
32.7%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 9612
32.9%
M 4545
15.5%
P 3429
 
11.7%
S 3056
 
10.5%
D 2228
 
7.6%
C 1634
 
5.6%
W 1452
 
5.0%
Y 1386
 
4.7%
H 481
 
1.6%
K 472
 
1.6%
Other values (6) 946
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 11690
19.4%
0 9382
15.6%
4 7185
11.9%
6 6083
10.1%
8 5541
9.2%
7 4773
7.9%
2 4627
 
7.7%
9 4586
 
7.6%
5 3582
 
5.9%
3 2806
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Common 60255
67.3%
Latin 29241
32.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 9612
32.9%
M 4545
15.5%
P 3429
 
11.7%
S 3056
 
10.5%
D 2228
 
7.6%
C 1634
 
5.6%
W 1452
 
5.0%
Y 1386
 
4.7%
H 481
 
1.6%
K 472
 
1.6%
Other values (6) 946
 
3.2%
Common
ValueCountFrequency (%)
1 11690
19.4%
0 9382
15.6%
4 7185
11.9%
6 6083
10.1%
8 5541
9.2%
7 4773
7.9%
2 4627
 
7.7%
9 4586
 
7.6%
5 3582
 
5.9%
3 2806
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89496
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11690
13.1%
R 9612
10.7%
0 9382
10.5%
4 7185
 
8.0%
6 6083
 
6.8%
8 5541
 
6.2%
7 4773
 
5.3%
2 4627
 
5.2%
9 4586
 
5.1%
M 4545
 
5.1%
Other values (16) 21472
24.0%
Distinct157
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:03:39.131436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.6798
Min length2

Characters and Unicode

Total characters56798
Distinct characters162
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

Unique3 ?
Unique (%)< 0.1%

Sample

1st row퀸스타2호
2nd row남신안농협5호
3rd row아평호
4th row한산농협카페리
5th row세종1호
ValueCountFrequency (%)
평화훼리5호 210
 
2.1%
실버클라우드 207
 
2.1%
세종1호 184
 
1.8%
아일랜드 171
 
1.7%
신한고속훼리호 167
 
1.7%
한려페리7호 165
 
1.6%
가자섬으로 162
 
1.6%
완농페리3호 147
 
1.5%
개야카훼리 146
 
1.5%
섬드리비금농협고속페리 144
 
1.4%
Other values (148) 8309
83.0%
2023-12-12T12:03:39.664519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6356
 
11.2%
4366
 
7.7%
1871
 
3.3%
1629
 
2.9%
1568
 
2.8%
1499
 
2.6%
1345
 
2.4%
1254
 
2.2%
1 1075
 
1.9%
932
 
1.6%
Other values (152) 34903
61.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52560
92.5%
Decimal Number 4220
 
7.4%
Space Separator 12
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6356
 
12.1%
4366
 
8.3%
1871
 
3.6%
1629
 
3.1%
1568
 
3.0%
1499
 
2.9%
1345
 
2.6%
1254
 
2.4%
932
 
1.8%
914
 
1.7%
Other values (140) 30826
58.6%
Decimal Number
ValueCountFrequency (%)
1 1075
25.5%
3 897
21.3%
2 682
16.2%
5 623
14.8%
7 356
 
8.4%
9 355
 
8.4%
0 88
 
2.1%
8 76
 
1.8%
6 68
 
1.6%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52560
92.5%
Common 4238
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6356
 
12.1%
4366
 
8.3%
1871
 
3.6%
1629
 
3.1%
1568
 
3.0%
1499
 
2.9%
1345
 
2.6%
1254
 
2.4%
932
 
1.8%
914
 
1.7%
Other values (140) 30826
58.6%
Common
ValueCountFrequency (%)
1 1075
25.4%
3 897
21.2%
2 682
16.1%
5 623
14.7%
7 356
 
8.4%
9 355
 
8.4%
0 88
 
2.1%
8 76
 
1.8%
6 68
 
1.6%
12
 
0.3%
Other values (2) 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52560
92.5%
ASCII 4238
 
7.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6356
 
12.1%
4366
 
8.3%
1871
 
3.6%
1629
 
3.1%
1568
 
3.0%
1499
 
2.9%
1345
 
2.6%
1254
 
2.4%
932
 
1.8%
914
 
1.7%
Other values (140) 30826
58.6%
ASCII
ValueCountFrequency (%)
1 1075
25.4%
3 897
21.2%
2 682
16.1%
5 623
14.7%
7 356
 
8.4%
9 355
 
8.4%
0 88
 
2.1%
8 76
 
1.8%
6 68
 
1.6%
12
 
0.3%
Other values (2) 6
 
0.1%
Distinct239
Distinct (%)2.4%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T12:03:40.074575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length8.1185237
Min length5

Characters and Unicode

Total characters81169
Distinct characters190
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.4%

Sample

1st row제주-추자-우수영
2nd row목포-동리(중간)
3rd row삼-국(편)
4th row통-제-의-통(순)
5th row통영-용초(신규/오후)
ValueCountFrequency (%)
땅끝-산양 547
 
5.4%
삼-욕(편 313
 
3.1%
남강-가산 312
 
3.1%
제주-완도 301
 
3.0%
화흥포-동천-소안 261
 
2.6%
완도-청산 252
 
2.5%
일정-당목 213
 
2.1%
땅끝-넙도 204
 
2.0%
대천-장고도(고대도 198
 
2.0%
목포-제주 189
 
1.9%
Other values (232) 7310
72.4%
2023-12-12T12:03:40.585779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 13710
 
16.9%
( 4956
 
6.1%
) 4956
 
6.1%
4034
 
5.0%
2464
 
3.0%
2115
 
2.6%
1952
 
2.4%
1814
 
2.2%
1567
 
1.9%
1454
 
1.8%
Other values (180) 42147
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54501
67.1%
Dash Punctuation 13710
 
16.9%
Open Punctuation 4956
 
6.1%
Close Punctuation 4956
 
6.1%
Decimal Number 2048
 
2.5%
Other Punctuation 752
 
0.9%
Space Separator 102
 
0.1%
Uppercase Letter 90
 
0.1%
Connector Punctuation 29
 
< 0.1%
Lowercase Letter 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4034
 
7.4%
2464
 
4.5%
2115
 
3.9%
1952
 
3.6%
1814
 
3.3%
1567
 
2.9%
1454
 
2.7%
1270
 
2.3%
998
 
1.8%
974
 
1.8%
Other values (158) 35859
65.8%
Decimal Number
ValueCountFrequency (%)
1 700
34.2%
3 342
16.7%
2 313
15.3%
6 273
 
13.3%
7 121
 
5.9%
8 121
 
5.9%
5 62
 
3.0%
0 54
 
2.6%
4 33
 
1.6%
9 29
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 608
80.9%
/ 142
 
18.9%
. 2
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
O 86
95.6%
X 4
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 13710
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4956
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4956
100.0%
Space Separator
ValueCountFrequency (%)
102
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 29
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 21
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54501
67.1%
Common 26557
32.7%
Latin 111
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4034
 
7.4%
2464
 
4.5%
2115
 
3.9%
1952
 
3.6%
1814
 
3.3%
1567
 
2.9%
1454
 
2.7%
1270
 
2.3%
998
 
1.8%
974
 
1.8%
Other values (158) 35859
65.8%
Common
ValueCountFrequency (%)
- 13710
51.6%
( 4956
 
18.7%
) 4956
 
18.7%
1 700
 
2.6%
, 608
 
2.3%
3 342
 
1.3%
2 313
 
1.2%
6 273
 
1.0%
/ 142
 
0.5%
7 121
 
0.5%
Other values (9) 436
 
1.6%
Latin
ValueCountFrequency (%)
O 86
77.5%
x 21
 
18.9%
X 4
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54501
67.1%
ASCII 26668
32.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 13710
51.4%
( 4956
 
18.6%
) 4956
 
18.6%
1 700
 
2.6%
, 608
 
2.3%
3 342
 
1.3%
2 313
 
1.2%
6 273
 
1.0%
/ 142
 
0.5%
7 121
 
0.5%
Other values (12) 547
 
2.1%
Hangul
ValueCountFrequency (%)
4034
 
7.4%
2464
 
4.5%
2115
 
3.9%
1952
 
3.6%
1814
 
3.3%
1567
 
2.9%
1454
 
2.7%
1270
 
2.3%
998
 
1.8%
974
 
1.8%
Other values (158) 35859
65.8%

흘수선수값
Real number (ℝ)

SKEWED  ZEROS 

Distinct314
Distinct (%)3.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1.9666877
Minimum0
Maximum5978
Zeros781
Zeros (%)7.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:40.770928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.85
median1.07
Q31.35
95-th percentile4.81
Maximum5978
Range5978
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation59.833457
Coefficient of variation (CV)30.423467
Kurtosis9956.1867
Mean1.9666877
Median Absolute Deviation (MAD)0.25
Skewness99.678948
Sum19664.91
Variance3580.0425
MonotonicityNot monotonic
2023-12-12T12:03:40.965488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8 1030
 
10.3%
1.0 792
 
7.9%
0.0 781
 
7.8%
1.1 646
 
6.5%
1.2 643
 
6.4%
0.9 590
 
5.9%
1.3 503
 
5.0%
1.4 498
 
5.0%
0.85 209
 
2.1%
1.5 193
 
1.9%
Other values (304) 4114
41.1%
ValueCountFrequency (%)
0.0 781
7.8%
0.02 1
 
< 0.1%
0.1 1
 
< 0.1%
0.2 1
 
< 0.1%
0.5 2
 
< 0.1%
0.6 148
 
1.5%
0.61 2
 
< 0.1%
0.62 1
 
< 0.1%
0.63 2
 
< 0.1%
0.65 149
 
1.5%
ValueCountFrequency (%)
5978.0 1
 
< 0.1%
215.0 1
 
< 0.1%
99.0 1
 
< 0.1%
90.0 1
 
< 0.1%
17.0 1
 
< 0.1%
6.5 1
 
< 0.1%
6.35 1
 
< 0.1%
6.3 4
< 0.1%
6.25 1
 
< 0.1%
6.2 7
0.1%

흘수중앙값
Real number (ℝ)

SKEWED  ZEROS 

Distinct238
Distinct (%)2.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.55613161
Minimum0
Maximum240
Zeros8569
Zeros (%)85.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:41.142538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.15
Maximum240
Range240
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8120295
Coefficient of variation (CV)5.0564102
Kurtosis5258.8818
Mean0.55613161
Median Absolute Deviation (MAD)0
Skewness62.16019
Sum5560.76
Variance7.9075101
MonotonicityNot monotonic
2023-12-12T12:03:41.303889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8569
85.7%
1.7 99
 
1.0%
1.6 45
 
0.4%
5.2 35
 
0.4%
1.8 32
 
0.3%
5.3 31
 
0.3%
5.1 31
 
0.3%
5.05 29
 
0.3%
4.9 28
 
0.3%
5.35 28
 
0.3%
Other values (228) 1072
 
10.7%
ValueCountFrequency (%)
0.0 8569
85.7%
1.0 2
 
< 0.1%
1.12 1
 
< 0.1%
1.15 1
 
< 0.1%
1.16 1
 
< 0.1%
1.19 1
 
< 0.1%
1.25 1
 
< 0.1%
1.27 1
 
< 0.1%
1.28 1
 
< 0.1%
1.35 1
 
< 0.1%
ValueCountFrequency (%)
240.0 1
 
< 0.1%
6.55 1
 
< 0.1%
6.5 2
 
< 0.1%
6.45 1
 
< 0.1%
6.4 4
 
< 0.1%
6.35 4
 
< 0.1%
6.3 8
0.1%
6.25 5
0.1%
6.23 1
 
< 0.1%
6.2 10
0.1%

흘수선미값
Real number (ℝ)

SKEWED  ZEROS 

Distinct304
Distinct (%)3.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.1922732
Minimum0
Maximum554
Zeros1321
Zeros (%)13.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:41.476752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.65
median2.1
Q32.4
95-th percentile5.5
Maximum554
Range554
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation6.2998447
Coefficient of variation (CV)2.8736585
Kurtosis6239.8188
Mean2.1922732
Median Absolute Deviation (MAD)0.35
Skewness75.363912
Sum21920.54
Variance39.688043
MonotonicityNot monotonic
2023-12-12T12:03:41.664055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1321
 
13.2%
2.4 690
 
6.9%
2.2 676
 
6.8%
2.0 661
 
6.6%
2.3 639
 
6.4%
1.8 618
 
6.2%
1.9 469
 
4.7%
2.5 325
 
3.2%
2.1 306
 
3.1%
2.6 243
 
2.4%
Other values (294) 4051
40.5%
ValueCountFrequency (%)
0.0 1321
13.2%
0.6 1
 
< 0.1%
0.9 1
 
< 0.1%
1.0 5
 
0.1%
1.08 1
 
< 0.1%
1.09 7
 
0.1%
1.1 27
 
0.3%
1.11 6
 
0.1%
1.12 10
 
0.1%
1.13 13
 
0.1%
ValueCountFrequency (%)
554.0 1
 
< 0.1%
275.0 1
 
< 0.1%
22.0 1
 
< 0.1%
18.0 1
 
< 0.1%
6.9 1
 
< 0.1%
6.8 1
 
< 0.1%
6.7 2
 
< 0.1%
6.65 1
 
< 0.1%
6.6 6
0.1%
6.55 5
0.1%

최대승선인원수
Real number (ℝ)

Distinct131
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean343.2792
Minimum8
Maximum1465
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:41.846250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile69
Q1177
median284
Q3427
95-th percentile889
Maximum1465
Range1457
Interquartile range (IQR)250

Descriptive statistics

Standard deviation264.92006
Coefficient of variation (CV)0.77173352
Kurtosis4.0656748
Mean343.2792
Median Absolute Deviation (MAD)120
Skewness1.9396825
Sum3432792
Variance70182.641
MonotonicityNot monotonic
2023-12-12T12:03:42.011399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
284 340
 
3.4%
233 290
 
2.9%
69 261
 
2.6%
54 251
 
2.5%
354 234
 
2.3%
450 220
 
2.2%
187 210
 
2.1%
304 207
 
2.1%
1211 206
 
2.1%
704 195
 
1.9%
Other values (121) 7586
75.9%
ValueCountFrequency (%)
8 1
 
< 0.1%
53 1
 
< 0.1%
54 251
2.5%
65 22
 
0.2%
69 261
2.6%
70 145
1.5%
78 30
 
0.3%
80 77
 
0.8%
84 165
1.7%
85 50
 
0.5%
ValueCountFrequency (%)
1465 5
 
0.1%
1317 76
 
0.8%
1300 110
1.1%
1280 14
 
0.1%
1248 15
 
0.1%
1211 206
2.1%
1209 1
 
< 0.1%
983 4
 
< 0.1%
981 64
 
0.6%
891 1
 
< 0.1%

최대여객인원수
Real number (ℝ)

Distinct127
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336.2835
Minimum5
Maximum1425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:42.181774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile65
Q1173
median280
Q3420
95-th percentile860
Maximum1425
Range1420
Interquartile range (IQR)247

Descriptive statistics

Standard deviation258.77087
Coefficient of variation (CV)0.76950214
Kurtosis3.8911989
Mean336.2835
Median Absolute Deviation (MAD)120
Skewness1.8940231
Sum3362835
Variance66962.365
MonotonicityNot monotonic
2023-12-12T12:03:42.354663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
350 395
 
4.0%
280 340
 
3.4%
300 291
 
2.9%
230 290
 
2.9%
250 274
 
2.7%
50 251
 
2.5%
80 215
 
2.1%
183 210
 
2.1%
1180 207
 
2.1%
700 185
 
1.8%
Other values (117) 7342
73.4%
ValueCountFrequency (%)
5 1
 
< 0.1%
48 1
 
< 0.1%
50 251
2.5%
60 22
 
0.2%
63 140
1.4%
65 145
1.5%
66 121
1.2%
73 30
 
0.3%
77 77
 
0.8%
80 215
2.1%
ValueCountFrequency (%)
1425 5
 
0.1%
1284 76
 
0.8%
1264 110
1.1%
1220 15
 
0.1%
1200 14
 
0.1%
1180 207
2.1%
948 68
 
0.7%
860 46
 
0.5%
818 106
1.1%
767 79
 
0.8%

최대선원인원수
Real number (ℝ)

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7928
Minimum2
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:42.522355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile3
Q14
median4
Q36
95-th percentile29
Maximum80
Range78
Interquartile range (IQR)2

Descriptive statistics

Standard deviation7.5021661
Coefficient of variation (CV)1.1044291
Kurtosis18.342909
Mean6.7928
Median Absolute Deviation (MAD)1
Skewness3.7879134
Sum67928
Variance56.282496
MonotonicityNot monotonic
2023-12-12T12:03:42.691103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
4 4120
41.2%
5 1669
16.7%
6 1166
 
11.7%
3 1147
 
11.5%
8 448
 
4.5%
7 406
 
4.1%
29 304
 
3.0%
36 157
 
1.6%
33 144
 
1.4%
10 124
 
1.2%
Other values (7) 315
 
3.1%
ValueCountFrequency (%)
2 78
 
0.8%
3 1147
 
11.5%
4 4120
41.2%
5 1669
16.7%
6 1166
 
11.7%
7 406
 
4.1%
8 448
 
4.5%
10 124
 
1.2%
12 3
 
< 0.1%
15 94
 
0.9%
ValueCountFrequency (%)
80 14
 
0.1%
40 5
 
0.1%
36 157
1.6%
33 144
1.4%
29 304
3.0%
28 15
 
0.1%
23 106
 
1.1%
15 94
 
0.9%
12 3
 
< 0.1%
10 124
1.2%

최대임시승선인원수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.20292029
Minimum0
Maximum10
Zeros9216
Zeros (%)92.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:42.856979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.024274
Coefficient of variation (CV)5.0476669
Kurtosis65.940862
Mean0.20292029
Median Absolute Deviation (MAD)0
Skewness7.6529474
Sum2029
Variance1.0491373
MonotonicityNot monotonic
2023-12-12T12:03:43.042873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 9216
92.2%
1 369
 
3.7%
2 248
 
2.5%
10 79
 
0.8%
4 47
 
0.5%
5 33
 
0.3%
3 7
 
0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 9216
92.2%
1 369
 
3.7%
2 248
 
2.5%
3 7
 
0.1%
4 47
 
0.5%
5 33
 
0.3%
10 79
 
0.8%
ValueCountFrequency (%)
10 79
 
0.8%
5 33
 
0.3%
4 47
 
0.5%
3 7
 
0.1%
2 248
 
2.5%
1 369
 
3.7%
0 9216
92.2%

여객대인인원수
Real number (ℝ)

ZEROS 

Distinct462
Distinct (%)4.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean62.973997
Minimum0
Maximum978
Zeros134
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:43.230607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q115
median33
Q372
95-th percentile242
Maximum978
Range978
Interquartile range (IQR)57

Descriptive statistics

Standard deviation85.294879
Coefficient of variation (CV)1.354446
Kurtosis13.247865
Mean62.973997
Median Absolute Deviation (MAD)22
Skewness3.0941744
Sum629677
Variance7275.2164
MonotonicityNot monotonic
2023-12-12T12:03:43.394168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 206
 
2.1%
16 200
 
2.0%
8 196
 
2.0%
10 188
 
1.9%
17 187
 
1.9%
11 181
 
1.8%
9 181
 
1.8%
15 180
 
1.8%
12 179
 
1.8%
22 178
 
1.8%
Other values (452) 8123
81.2%
ValueCountFrequency (%)
0 134
1.3%
1 124
1.2%
2 122
1.2%
3 124
1.2%
4 152
1.5%
5 132
1.3%
6 153
1.5%
7 157
1.6%
8 196
2.0%
9 181
1.8%
ValueCountFrequency (%)
978 1
< 0.1%
939 1
< 0.1%
931 1
< 0.1%
924 1
< 0.1%
764 1
< 0.1%
719 1
< 0.1%
696 1
< 0.1%
693 1
< 0.1%
682 1
< 0.1%
665 1
< 0.1%

여객소인인원수
Real number (ℝ)

ZEROS 

Distinct75
Distinct (%)0.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean3.0326033
Minimum0
Maximum122
Zeros5272
Zeros (%)52.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:43.602395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile14
Maximum122
Range122
Interquartile range (IQR)3

Descriptive statistics

Standard deviation7.3757723
Coefficient of variation (CV)2.4321587
Kurtosis66.575198
Mean3.0326033
Median Absolute Deviation (MAD)0
Skewness6.6408249
Sum30323
Variance54.402018
MonotonicityNot monotonic
2023-12-12T12:03:43.793686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5272
52.7%
1 1077
 
10.8%
2 818
 
8.2%
3 555
 
5.5%
4 396
 
4.0%
5 286
 
2.9%
6 242
 
2.4%
7 202
 
2.0%
8 144
 
1.4%
9 134
 
1.3%
Other values (65) 873
 
8.7%
ValueCountFrequency (%)
0 5272
52.7%
1 1077
 
10.8%
2 818
 
8.2%
3 555
 
5.5%
4 396
 
4.0%
5 286
 
2.9%
6 242
 
2.4%
7 202
 
2.0%
8 144
 
1.4%
9 134
 
1.3%
ValueCountFrequency (%)
122 1
 
< 0.1%
117 1
 
< 0.1%
116 1
 
< 0.1%
106 1
 
< 0.1%
105 1
 
< 0.1%
97 3
< 0.1%
95 1
 
< 0.1%
92 1
 
< 0.1%
91 2
< 0.1%
90 2
< 0.1%

여객유아인원수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.092309231
Minimum0
Maximum9
Zeros9295
Zeros (%)93.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:43.964299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.39142113
Coefficient of variation (CV)4.2403249
Kurtosis67.533762
Mean0.092309231
Median Absolute Deviation (MAD)0
Skewness6.5341276
Sum923
Variance0.1532105
MonotonicityNot monotonic
2023-12-12T12:03:44.085283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 9295
93.0%
1 561
 
5.6%
2 96
 
1.0%
3 30
 
0.3%
4 10
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
9 1
 
< 0.1%
(Missing) 1
 
< 0.1%
ValueCountFrequency (%)
0 9295
93.0%
1 561
 
5.6%
2 96
 
1.0%
3 30
 
0.3%
4 10
 
0.1%
5 5
 
0.1%
6 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
6 1
 
< 0.1%
5 5
 
0.1%
4 10
 
0.1%
3 30
 
0.3%
2 96
 
1.0%
1 561
 
5.6%
0 9295
93.0%

실제선원인수
Real number (ℝ)

Distinct33
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.3687369
Minimum0
Maximum40
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:44.226028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q14
median4
Q34
95-th percentile18
Maximum40
Range40
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.8704303
Coefficient of variation (CV)0.90718364
Kurtosis10.483988
Mean5.3687369
Median Absolute Deviation (MAD)0
Skewness3.316522
Sum53682
Variance23.721091
MonotonicityNot monotonic
2023-12-12T12:03:44.410844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4 5386
53.9%
3 2041
 
20.4%
5 644
 
6.4%
6 535
 
5.3%
2 264
 
2.6%
7 225
 
2.2%
17 84
 
0.8%
10 80
 
0.8%
26 80
 
0.8%
18 78
 
0.8%
Other values (23) 582
 
5.8%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 1
 
< 0.1%
2 264
 
2.6%
3 2041
 
20.4%
4 5386
53.9%
5 644
 
6.4%
6 535
 
5.3%
7 225
 
2.2%
8 49
 
0.5%
9 6
 
0.1%
ValueCountFrequency (%)
40 2
 
< 0.1%
33 1
 
< 0.1%
30 2
 
< 0.1%
29 17
 
0.2%
28 41
0.4%
27 65
0.7%
26 80
0.8%
25 37
0.4%
24 45
0.4%
23 36
0.4%

실제임시승선인원수
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.03850385
Minimum0
Maximum48
Zeros9853
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:44.589836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.77494368
Coefficient of variation (CV)20.126394
Kurtosis2228.6094
Mean0.03850385
Median Absolute Deviation (MAD)0
Skewness43.646666
Sum385
Variance0.60053771
MonotonicityNot monotonic
2023-12-12T12:03:44.754959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9853
98.5%
1 107
 
1.1%
2 18
 
0.2%
8 9
 
0.1%
3 5
 
0.1%
4 2
 
< 0.1%
31 1
 
< 0.1%
33 1
 
< 0.1%
48 1
 
< 0.1%
28 1
 
< 0.1%
ValueCountFrequency (%)
0 9853
98.5%
1 107
 
1.1%
2 18
 
0.2%
3 5
 
0.1%
4 2
 
< 0.1%
7 1
 
< 0.1%
8 9
 
0.1%
28 1
 
< 0.1%
31 1
 
< 0.1%
33 1
 
< 0.1%
ValueCountFrequency (%)
48 1
 
< 0.1%
33 1
 
< 0.1%
31 1
 
< 0.1%
28 1
 
< 0.1%
8 9
 
0.1%
7 1
 
< 0.1%
4 2
 
< 0.1%
3 5
 
0.1%
2 18
 
0.2%
1 107
1.1%
Distinct132
Distinct (%)1.6%
Missing1664
Missing (%)16.6%
Memory size156.2 KiB
2023-12-12T12:03:45.080780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length41
Mean length4.8276152
Min length1

Characters and Unicode

Total characters40243
Distinct characters25
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)0.1%

Sample

1st row158.9
2nd row9
3rd row200.2
4th row26.9
5th row138.7
ValueCountFrequency (%)
90.7 302
 
3.5%
135.8 210
 
2.5%
2772.4 206
 
2.4%
242.9 198
 
2.3%
65 197
 
2.3%
26.9 183
 
2.2%
71 171
 
2.0%
168.1 167
 
2.0%
180.9 162
 
1.9%
37.2 159
 
1.9%
Other values (126) 6553
77.0%
2023-12-12T12:03:45.601824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7366
18.3%
1 5571
13.8%
2 4571
11.4%
3 3427
8.5%
9 3405
8.5%
7 3006
7.5%
6 2851
 
7.1%
4 2745
 
6.8%
5 2327
 
5.8%
8 2159
 
5.4%
Other values (15) 2815
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31761
78.9%
Other Punctuation 7479
 
18.6%
Other Letter 476
 
1.2%
Space Separator 174
 
0.4%
Uppercase Letter 115
 
0.3%
Dash Punctuation 112
 
0.3%
Open Punctuation 63
 
0.2%
Close Punctuation 63
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5571
17.5%
2 4571
14.4%
3 3427
10.8%
9 3405
10.7%
7 3006
9.5%
6 2851
9.0%
4 2745
8.6%
5 2327
7.3%
8 2159
 
6.8%
0 1699
 
5.3%
Other Letter
ValueCountFrequency (%)
119
25.0%
119
25.0%
63
13.2%
63
13.2%
56
11.8%
56
11.8%
Other Punctuation
ValueCountFrequency (%)
. 7366
98.5%
/ 57
 
0.8%
, 56
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
M 58
50.4%
T 57
49.6%
Space Separator
ValueCountFrequency (%)
174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39652
98.5%
Hangul 476
 
1.2%
Latin 115
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7366
18.6%
1 5571
14.0%
2 4571
11.5%
3 3427
8.6%
9 3405
8.6%
7 3006
7.6%
6 2851
 
7.2%
4 2745
 
6.9%
5 2327
 
5.9%
8 2159
 
5.4%
Other values (7) 2224
 
5.6%
Hangul
ValueCountFrequency (%)
119
25.0%
119
25.0%
63
13.2%
63
13.2%
56
11.8%
56
11.8%
Latin
ValueCountFrequency (%)
M 58
50.4%
T 57
49.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39767
98.8%
Hangul 476
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7366
18.5%
1 5571
14.0%
2 4571
11.5%
3 3427
8.6%
9 3405
8.6%
7 3006
7.6%
6 2851
 
7.2%
4 2745
 
6.9%
5 2327
 
5.9%
8 2159
 
5.4%
Other values (9) 2339
 
5.9%
Hangul
ValueCountFrequency (%)
119
25.0%
119
25.0%
63
13.2%
63
13.2%
56
11.8%
56
11.8%

실제화물적재중량
Real number (ℝ)

MISSING  ZEROS 

Distinct3670
Distinct (%)44.0%
Missing1663
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean121.579
Minimum0
Maximum3613.565
Zeros439
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:45.776597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.4
median22.95
Q355.9
95-th percentile894.158
Maximum3613.565
Range3613.565
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation345.3251
Coefficient of variation (CV)2.8403351
Kurtosis22.868977
Mean121.579
Median Absolute Deviation (MAD)18.05
Skewness4.4912946
Sum1013604.1
Variance119249.42
MonotonicityNot monotonic
2023-12-12T12:03:46.268809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 439
 
4.4%
2.0 134
 
1.3%
6.0 62
 
0.6%
4.0 62
 
0.6%
1.5 58
 
0.6%
2.1 44
 
0.4%
3.0 43
 
0.4%
2.3 35
 
0.4%
12.0 35
 
0.4%
10.0 34
 
0.3%
Other values (3660) 7391
73.9%
(Missing) 1663
 
16.6%
ValueCountFrequency (%)
0.0 439
4.4%
0.001 1
 
< 0.1%
0.01 2
 
< 0.1%
0.013 1
 
< 0.1%
0.03 1
 
< 0.1%
0.05 3
 
< 0.1%
0.075 2
 
< 0.1%
0.1 8
 
0.1%
0.113 1
 
< 0.1%
0.145 1
 
< 0.1%
ValueCountFrequency (%)
3613.565 1
< 0.1%
3488.49 1
< 0.1%
3302.09 1
< 0.1%
3150.78 1
< 0.1%
3107.66 1
< 0.1%
3097.581 1
< 0.1%
3037.965 1
< 0.1%
2971.61 1
< 0.1%
2891.73 1
< 0.1%
2855.726 1
< 0.1%

차량화물수
Real number (ℝ)

MISSING  ZEROS 

Distinct245
Distinct (%)2.9%
Missing1669
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean20.825111
Minimum0
Maximum306
Zeros470
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:46.426451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q320
95-th percentile101
Maximum306
Range306
Interquartile range (IQR)16

Descriptive statistics

Standard deviation36.045493
Coefficient of variation (CV)1.7308668
Kurtosis15.157738
Mean20.825111
Median Absolute Deviation (MAD)7
Skewness3.656121
Sum173494
Variance1299.2776
MonotonicityNot monotonic
2023-12-12T12:03:46.636418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 502
 
5.0%
2 471
 
4.7%
0 470
 
4.7%
4 447
 
4.5%
3 437
 
4.4%
5 376
 
3.8%
6 363
 
3.6%
7 353
 
3.5%
8 333
 
3.3%
9 323
 
3.2%
Other values (235) 4256
42.6%
(Missing) 1669
 
16.7%
ValueCountFrequency (%)
0 470
4.7%
1 502
5.0%
2 471
4.7%
3 437
4.4%
4 447
4.5%
5 376
3.8%
6 363
3.6%
7 353
3.5%
8 333
3.3%
9 323
3.2%
ValueCountFrequency (%)
306 1
< 0.1%
290 1
< 0.1%
289 1
< 0.1%
287 1
< 0.1%
285 1
< 0.1%
281 1
< 0.1%
280 1
< 0.1%
276 1
< 0.1%
275 1
< 0.1%
263 1
< 0.1%

차량화물단위값
Real number (ℝ)

MISSING  ZEROS 

Distinct3238
Distinct (%)38.8%
Missing1663
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean119.15494
Minimum0
Maximum3582.05
Zeros476
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:46.803033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18.4
median22.95
Q355.9
95-th percentile858.344
Maximum3582.05
Range3582.05
Interquartile range (IQR)47.5

Descriptive statistics

Standard deviation337.56158
Coefficient of variation (CV)2.8329635
Kurtosis23.577296
Mean119.15494
Median Absolute Deviation (MAD)18.1
Skewness4.5423114
Sum993394.71
Variance113947.82
MonotonicityNot monotonic
2023-12-12T12:03:46.939364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 476
 
4.8%
2.0 142
 
1.4%
4.0 69
 
0.7%
6.0 63
 
0.6%
1.5 60
 
0.6%
3.0 49
 
0.5%
2.1 45
 
0.4%
12.0 44
 
0.4%
10.0 38
 
0.4%
5.0 37
 
0.4%
Other values (3228) 7314
73.1%
(Missing) 1663
 
16.6%
ValueCountFrequency (%)
0.0 476
4.8%
0.5 2
 
< 0.1%
0.9 2
 
< 0.1%
0.95 5
 
0.1%
1.0 15
 
0.1%
1.1 1
 
< 0.1%
1.15 6
 
0.1%
1.25 3
 
< 0.1%
1.5 60
 
0.6%
1.523 1
 
< 0.1%
ValueCountFrequency (%)
3582.05 1
< 0.1%
3477.35 1
< 0.1%
3285.01 1
< 0.1%
3119.935 1
< 0.1%
3099.84 1
< 0.1%
3067.46 1
< 0.1%
3009.57 1
< 0.1%
2926.28 1
< 0.1%
2864.99 1
< 0.1%
2842.51 1
< 0.1%

일반화물단위값
Real number (ℝ)

MISSING  ZEROS 

Distinct346
Distinct (%)4.2%
Missing1663
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean1.2359018
Minimum0
Maximum482.507
Zeros7206
Zeros (%)72.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:47.099166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.17
Maximum482.507
Range482.507
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.236286
Coefficient of variation (CV)13.137198
Kurtosis398.65346
Mean1.2359018
Median Absolute Deviation (MAD)0
Skewness18.669567
Sum10303.713
Variance263.61697
MonotonicityNot monotonic
2023-12-12T12:03:47.254196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7206
72.1%
0.1 116
 
1.2%
0.2 52
 
0.5%
0.04 49
 
0.5%
0.05 42
 
0.4%
0.02 40
 
0.4%
0.08 39
 
0.4%
0.01 38
 
0.4%
0.005 28
 
0.3%
0.03 24
 
0.2%
Other values (336) 703
 
7.0%
(Missing) 1663
 
16.6%
ValueCountFrequency (%)
0.0 7206
72.1%
0.001 9
 
0.1%
0.003 2
 
< 0.1%
0.004 2
 
< 0.1%
0.005 28
 
0.3%
0.01 38
 
0.4%
0.012 1
 
< 0.1%
0.013 2
 
< 0.1%
0.015 8
 
0.1%
0.016 5
 
0.1%
ValueCountFrequency (%)
482.507 1
< 0.1%
442.24 1
< 0.1%
408.493 1
< 0.1%
358.889 1
< 0.1%
357.736 1
< 0.1%
332.64 1
< 0.1%
323.431 1
< 0.1%
308.006 1
< 0.1%
292.413 1
< 0.1%
286.145 1
< 0.1%

컨테이너수
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct43
Distinct (%)0.5%
Missing1665
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean0.48842232
Minimum0
Maximum230
Zeros7940
Zeros (%)79.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:47.377237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum230
Range230
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9341629
Coefficient of variation (CV)8.0548386
Kurtosis1419.5563
Mean0.48842232
Median Absolute Deviation (MAD)0
Skewness27.785317
Sum4071
Variance15.477638
MonotonicityNot monotonic
2023-12-12T12:03:47.493591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0 7940
79.4%
1 102
 
1.0%
2 38
 
0.4%
4 20
 
0.2%
23 20
 
0.2%
12 18
 
0.2%
3 17
 
0.2%
8 16
 
0.2%
11 16
 
0.2%
6 15
 
0.1%
Other values (33) 133
 
1.3%
(Missing) 1665
 
16.7%
ValueCountFrequency (%)
0 7940
79.4%
1 102
 
1.0%
2 38
 
0.4%
3 17
 
0.2%
4 20
 
0.2%
5 11
 
0.1%
6 15
 
0.1%
7 6
 
0.1%
8 16
 
0.2%
9 8
 
0.1%
ValueCountFrequency (%)
230 1
 
< 0.1%
50 1
 
< 0.1%
46 1
 
< 0.1%
45 1
 
< 0.1%
44 1
 
< 0.1%
43 1
 
< 0.1%
38 3
< 0.1%
36 1
 
< 0.1%
35 2
< 0.1%
34 2
< 0.1%

컨테이너단위값
Real number (ℝ)

MISSING  ZEROS 

Distinct236
Distinct (%)2.8%
Missing1663
Missing (%)16.6%
Infinite0
Infinite (%)0.0%
Mean1.1881586
Minimum0
Maximum151.658
Zeros7937
Zeros (%)79.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:03:47.617188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum151.658
Range151.658
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.7907005
Coefficient of variation (CV)6.5569535
Kurtosis110.63241
Mean1.1881586
Median Absolute Deviation (MAD)0
Skewness9.3758125
Sum9905.678
Variance60.695015
MonotonicityNot monotonic
2023-12-12T12:03:47.759200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 7937
79.4%
43.24 20
 
0.2%
26.32 17
 
0.2%
24.44 9
 
0.1%
11.28 9
 
0.1%
9.4 9
 
0.1%
7.0 8
 
0.1%
1.88 8
 
0.1%
7.52 8
 
0.1%
15.04 7
 
0.1%
Other values (226) 305
 
3.0%
(Missing) 1663
 
16.6%
ValueCountFrequency (%)
0.0 7937
79.4%
0.005 1
 
< 0.1%
0.02 1
 
< 0.1%
0.1 1
 
< 0.1%
1.88 8
 
0.1%
2.0 3
 
< 0.1%
2.02 3
 
< 0.1%
2.03 1
 
< 0.1%
2.06 1
 
< 0.1%
2.1 1
 
< 0.1%
ValueCountFrequency (%)
151.658 1
< 0.1%
147.518 1
< 0.1%
139.283 1
< 0.1%
133.688 1
< 0.1%
124.75 1
< 0.1%
104.488 1
< 0.1%
103.969 1
< 0.1%
101.322 1
< 0.1%
94.0 1
< 0.1%
92.267 1
< 0.1%

안전점검표상태코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
STAT003
9907 
STAT001
 
93

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSTAT003
2nd rowSTAT003
3rd rowSTAT003
4th rowSTAT003
5th rowSTAT003

Common Values

ValueCountFrequency (%)
STAT003 9907
99.1%
STAT001 93
 
0.9%

Length

2023-12-12T12:03:47.885873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:03:47.981743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
stat003 9907
99.1%
stat001 93
 
0.9%
Distinct115
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:03:48.229815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.0148
Min length6

Characters and Unicode

Total characters70148
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowkomsa166
2nd rowkst032
3rd rowkst090
4th rowkomsa164
5th rowkomsa161
ValueCountFrequency (%)
komsa126 297
 
3.0%
kst003 287
 
2.9%
kst046 281
 
2.8%
kst073 235
 
2.4%
kst057 231
 
2.3%
kst087 186
 
1.9%
komsa161 183
 
1.8%
kst039 180
 
1.8%
jangbk716 180
 
1.8%
kimjhan 174
 
1.7%
Other values (105) 7766
77.7%
2023-12-12T12:03:48.669972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 9973
14.2%
s 9673
13.8%
1 6939
9.9%
0 6538
9.3%
t 5029
 
7.2%
a 4824
 
6.9%
m 4784
 
6.8%
o 4463
 
6.4%
6 2758
 
3.9%
3 2582
 
3.7%
Other values (16) 12585
17.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40183
57.3%
Decimal Number 29828
42.5%
Connector Punctuation 137
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 9973
24.8%
s 9673
24.1%
t 5029
12.5%
a 4824
12.0%
m 4784
11.9%
o 4463
11.1%
j 354
 
0.9%
n 354
 
0.9%
g 180
 
0.4%
b 180
 
0.4%
Other values (5) 369
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 6939
23.3%
0 6538
21.9%
6 2758
 
9.2%
3 2582
 
8.7%
7 2330
 
7.8%
5 2309
 
7.7%
2 2201
 
7.4%
4 2172
 
7.3%
8 1126
 
3.8%
9 873
 
2.9%
Connector Punctuation
ValueCountFrequency (%)
_ 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40183
57.3%
Common 29965
42.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 9973
24.8%
s 9673
24.1%
t 5029
12.5%
a 4824
12.0%
m 4784
11.9%
o 4463
11.1%
j 354
 
0.9%
n 354
 
0.9%
g 180
 
0.4%
b 180
 
0.4%
Other values (5) 369
 
0.9%
Common
ValueCountFrequency (%)
1 6939
23.2%
0 6538
21.8%
6 2758
 
9.2%
3 2582
 
8.6%
7 2330
 
7.8%
5 2309
 
7.7%
2 2201
 
7.3%
4 2172
 
7.2%
8 1126
 
3.8%
9 873
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 9973
14.2%
s 9673
13.8%
1 6939
9.9%
0 6538
9.3%
t 5029
 
7.2%
a 4824
 
6.9%
m 4784
 
6.8%
o 4463
 
6.4%
6 2758
 
3.9%
3 2582
 
3.7%
Other values (16) 12585
17.9%
Distinct9817
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-08-29 19:56:00
Maximum2021-12-18 09:10:00
2023-12-12T12:03:48.835654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:48.972081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정자ID
Text

MISSING 

Distinct60
Distinct (%)54.5%
Missing9890
Missing (%)98.9%
Memory size156.2 KiB
2023-12-12T12:03:49.221758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.0909091
Min length6

Characters and Unicode

Total characters780
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)26.4%

Sample

1st rowkst046
2nd rowkst034
3rd rowkomsa136
4th rowkomsa117
5th rowkomsa154
ValueCountFrequency (%)
jangbk716 6
 
5.5%
kst068 5
 
4.5%
kst049 5
 
4.5%
komsa117 4
 
3.6%
komsa131 4
 
3.6%
komsa138 3
 
2.7%
kst033 3
 
2.7%
komsa126 3
 
2.7%
komsa145 3
 
2.7%
kst052 3
 
2.7%
Other values (50) 71
64.5%
2023-12-12T12:03:49.629771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 111
14.2%
s 103
13.2%
1 82
10.5%
0 57
 
7.3%
a 56
 
7.2%
m 52
 
6.7%
t 51
 
6.5%
o 49
 
6.3%
6 34
 
4.4%
4 34
 
4.4%
Other values (13) 151
19.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 449
57.6%
Decimal Number 331
42.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
k 111
24.7%
s 103
22.9%
a 56
12.5%
m 52
11.6%
t 51
11.4%
o 49
10.9%
j 6
 
1.3%
b 6
 
1.3%
g 6
 
1.3%
n 6
 
1.3%
Other values (3) 3
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 82
24.8%
0 57
17.2%
6 34
10.3%
4 34
10.3%
3 28
 
8.5%
2 23
 
6.9%
7 23
 
6.9%
5 22
 
6.6%
8 15
 
4.5%
9 13
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 449
57.6%
Common 331
42.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
k 111
24.7%
s 103
22.9%
a 56
12.5%
m 52
11.6%
t 51
11.4%
o 49
10.9%
j 6
 
1.3%
b 6
 
1.3%
g 6
 
1.3%
n 6
 
1.3%
Other values (3) 3
 
0.7%
Common
ValueCountFrequency (%)
1 82
24.8%
0 57
17.2%
6 34
10.3%
4 34
10.3%
3 28
 
8.5%
2 23
 
6.9%
7 23
 
6.9%
5 22
 
6.6%
8 15
 
4.5%
9 13
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 111
14.2%
s 103
13.2%
1 82
10.5%
0 57
 
7.3%
a 56
 
7.2%
m 52
 
6.7%
t 51
 
6.5%
o 49
 
6.3%
6 34
 
4.4%
4 34
 
4.4%
Other values (13) 151
19.4%
Distinct9837
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-08-30 06:27:00
Maximum2021-12-18 09:28:00
2023-12-12T12:03:49.824050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:03:50.003671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

터미널명
Categorical

Distinct49
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
통영
1171 
목포
864 
완도
796 
땅끝
792 
대천
 
512
Other values (44)
5865 

Length

Max length6
Median length2
Mean length2.2719
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row제주
2nd row목포
3rd row삼덕
4th row통영
5th row통영

Common Values

ValueCountFrequency (%)
통영 1171
 
11.7%
목포 864
 
8.6%
완도 796
 
8.0%
땅끝 792
 
7.9%
대천 512
 
5.1%
당목 505
 
5.1%
제주 467
 
4.7%
녹동 448
 
4.5%
삼덕 429
 
4.3%
백야 381
 
3.8%
Other values (39) 3635
36.4%

Length

2023-12-12T12:03:50.161443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
통영 1171
 
11.7%
목포 864
 
8.6%
완도 796
 
8.0%
땅끝 792
 
7.9%
대천 512
 
5.1%
당목 505
 
5.1%
제주 467
 
4.7%
녹동 448
 
4.5%
삼덕 429
 
4.3%
백야 381
 
3.8%
Other values (39) 3635
36.4%

흘수비고내용
Text

MISSING 

Distinct81
Distinct (%)4.7%
Missing8291
Missing (%)82.9%
Memory size156.2 KiB
2023-12-12T12:03:50.449355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length7.1732007
Min length1

Characters and Unicode

Total characters12259
Distinct characters56
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)2.6%

Sample

1st row흘수확인
2nd row흘수확인
3rd row만재흘수선 확인
4th row흘수확인
5th row계산흘수 1.80
ValueCountFrequency (%)
만재흘수선확인 665
31.9%
흘수확인 363
17.4%
계산흘수 298
14.3%
만재흘수선 265
 
12.7%
확인 263
 
12.6%
만재흘수선양호 95
 
4.6%
1.67 8
 
0.4%
만재흘수선미초과 7
 
0.3%
1.47 5
 
0.2%
1.49 5
 
0.2%
Other values (73) 110
 
5.3%
2023-12-12T12:03:50.957452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1851
15.1%
1694
13.8%
1694
13.8%
1292
10.5%
1291
10.5%
1034
8.4%
1033
8.4%
1032
8.4%
298
 
2.4%
298
 
2.4%
Other values (46) 742
6.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9926
81.0%
Space Separator 1851
 
15.1%
Decimal Number 338
 
2.8%
Other Punctuation 104
 
0.8%
Lowercase Letter 40
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1694
17.1%
1694
17.1%
1292
13.0%
1291
13.0%
1034
10.4%
1033
10.4%
1032
10.4%
298
 
3.0%
298
 
3.0%
97
 
1.0%
Other values (31) 163
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 116
34.3%
7 42
 
12.4%
6 33
 
9.8%
8 31
 
9.2%
4 29
 
8.6%
5 28
 
8.3%
0 21
 
6.2%
3 14
 
4.1%
9 14
 
4.1%
2 10
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
m 24
60.0%
k 8
 
20.0%
g 8
 
20.0%
Space Separator
ValueCountFrequency (%)
1851
100.0%
Other Punctuation
ValueCountFrequency (%)
. 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9926
81.0%
Common 2293
 
18.7%
Latin 40
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1694
17.1%
1694
17.1%
1292
13.0%
1291
13.0%
1034
10.4%
1033
10.4%
1032
10.4%
298
 
3.0%
298
 
3.0%
97
 
1.0%
Other values (31) 163
 
1.6%
Common
ValueCountFrequency (%)
1851
80.7%
1 116
 
5.1%
. 104
 
4.5%
7 42
 
1.8%
6 33
 
1.4%
8 31
 
1.4%
4 29
 
1.3%
5 28
 
1.2%
0 21
 
0.9%
3 14
 
0.6%
Other values (2) 24
 
1.0%
Latin
ValueCountFrequency (%)
m 24
60.0%
k 8
 
20.0%
g 8
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9925
81.0%
ASCII 2333
 
19.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1851
79.3%
1 116
 
5.0%
. 104
 
4.5%
7 42
 
1.8%
6 33
 
1.4%
8 31
 
1.3%
4 29
 
1.2%
5 28
 
1.2%
m 24
 
1.0%
0 21
 
0.9%
Other values (5) 54
 
2.3%
Hangul
ValueCountFrequency (%)
1694
17.1%
1694
17.1%
1292
13.0%
1291
13.0%
1034
10.4%
1033
10.4%
1032
10.4%
298
 
3.0%
298
 
3.0%
97
 
1.0%
Other values (30) 162
 
1.6%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

출항시간
Text

MISSING 

Distinct82
Distinct (%)0.8%
Missing117
Missing (%)1.2%
Memory size156.2 KiB
2023-12-12T12:03:51.245993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length3.1228372
Min length1

Characters and Unicode

Total characters30863
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row3
2nd row02;10
3rd row1.2
4th row25
5th row2.8
ValueCountFrequency (%)
50 918
 
9.3%
25 721
 
7.3%
55 650
 
6.6%
30 604
 
6.1%
1시간30분 567
 
5.7%
120 382
 
3.9%
15 308
 
3.1%
80 268
 
2.7%
00-50 223
 
2.3%
330 221
 
2.2%
Other values (72) 5021
50.8%
2023-12-12T12:03:51.700618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7602
24.6%
5 4722
15.3%
2 3819
12.4%
3 3110
10.1%
1 3098
10.0%
1327
 
4.3%
4 1242
 
4.0%
959
 
3.1%
959
 
3.1%
. 860
 
2.8%
Other values (17) 3165
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25010
81.0%
Other Letter 3497
 
11.3%
Other Punctuation 1873
 
6.1%
Dash Punctuation 265
 
0.9%
Open Punctuation 109
 
0.4%
Close Punctuation 109
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7602
30.4%
5 4722
18.9%
2 3819
15.3%
3 3110
12.4%
1 3098
12.4%
4 1242
 
5.0%
8 624
 
2.5%
6 536
 
2.1%
7 181
 
0.7%
9 76
 
0.3%
Other Letter
ValueCountFrequency (%)
1327
37.9%
959
27.4%
959
27.4%
92
 
2.6%
92
 
2.6%
17
 
0.5%
17
 
0.5%
17
 
0.5%
17
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 860
45.9%
: 790
42.2%
; 128
 
6.8%
, 64
 
3.4%
/ 31
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 265
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 27366
88.7%
Hangul 3497
 
11.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7602
27.8%
5 4722
17.3%
2 3819
14.0%
3 3110
11.4%
1 3098
11.3%
4 1242
 
4.5%
. 860
 
3.1%
: 790
 
2.9%
8 624
 
2.3%
6 536
 
2.0%
Other values (8) 963
 
3.5%
Hangul
ValueCountFrequency (%)
1327
37.9%
959
27.4%
959
27.4%
92
 
2.6%
92
 
2.6%
17
 
0.5%
17
 
0.5%
17
 
0.5%
17
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27366
88.7%
Hangul 3497
 
11.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7602
27.8%
5 4722
17.3%
2 3819
14.0%
3 3110
11.4%
1 3098
11.3%
4 1242
 
4.5%
. 860
 
3.1%
: 790
 
2.9%
8 624
 
2.3%
6 536
 
2.0%
Other values (8) 963
 
3.5%
Hangul
ValueCountFrequency (%)
1327
37.9%
959
27.4%
959
27.4%
92
 
2.6%
92
 
2.6%
17
 
0.5%
17
 
0.5%
17
 
0.5%
17
 
0.5%
Distinct251
Distinct (%)2.5%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T12:03:52.062391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.9996999
Min length4

Characters and Unicode

Total characters49987
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)0.4%

Sample

1st rowG0601
2nd rowF0905
3rd rowL3001
4th rowL0601
5th rowL2212
ValueCountFrequency (%)
e0902 547
 
5.5%
l1401 313
 
3.1%
g0101 301
 
3.0%
e0203 261
 
2.6%
e0302 252
 
2.5%
f0424 209
 
2.1%
e0920 203
 
2.0%
k0117 198
 
2.0%
f0101 189
 
1.9%
l0209 184
 
1.8%
Other values (241) 7341
73.4%
2023-12-12T12:03:52.581912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14842
29.7%
1 8419
16.8%
2 5012
 
10.0%
3 2798
 
5.6%
4 2723
 
5.4%
E 2371
 
4.7%
L 2077
 
4.2%
9 1833
 
3.7%
F 1564
 
3.1%
6 1455
 
2.9%
Other values (13) 6893
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39988
80.0%
Uppercase Letter 9999
 
20.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 2371
23.7%
L 2077
20.8%
F 1564
15.6%
H 1016
10.2%
G 666
 
6.7%
K 618
 
6.2%
Q 610
 
6.1%
J 486
 
4.9%
M 334
 
3.3%
N 158
 
1.6%
Other values (3) 99
 
1.0%
Decimal Number
ValueCountFrequency (%)
0 14842
37.1%
1 8419
21.1%
2 5012
 
12.5%
3 2798
 
7.0%
4 2723
 
6.8%
9 1833
 
4.6%
6 1455
 
3.6%
5 1285
 
3.2%
7 1172
 
2.9%
8 449
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common 39988
80.0%
Latin 9999
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 2371
23.7%
L 2077
20.8%
F 1564
15.6%
H 1016
10.2%
G 666
 
6.7%
K 618
 
6.2%
Q 610
 
6.1%
J 486
 
4.9%
M 334
 
3.3%
N 158
 
1.6%
Other values (3) 99
 
1.0%
Common
ValueCountFrequency (%)
0 14842
37.1%
1 8419
21.1%
2 5012
 
12.5%
3 2798
 
7.0%
4 2723
 
6.8%
9 1833
 
4.6%
6 1455
 
3.6%
5 1285
 
3.2%
7 1172
 
2.9%
8 449
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14842
29.7%
1 8419
16.8%
2 5012
 
10.0%
3 2798
 
5.6%
4 2723
 
5.4%
E 2371
 
4.7%
L 2077
 
4.2%
9 1833
 
3.7%
F 1564
 
3.1%
6 1455
 
2.9%
Other values (13) 6893
13.8%

Sample

안전점검표순번출항일시선박종류코드터미널ID선박번호선박 명항로향해구역명흘수선수값흘수중앙값흘수선미값최대승선인원수최대여객인원수최대선원인원수최대임시승선인원수여객대인인원수여객소인인원수여객유아인원수실제선원인수실제임시승선인원수화물적재한도중량실제화물적재중량차량화물수차량화물단위값일반화물단위값컨테이너수컨테이너단위값안전점검표상태코드등록자ID등록일시수정자ID수정 일터미널명흘수비고내용출항시간운항항로 아이디
242792576242021-08-13 9:301G000MPR156209퀸스타2호제주-추자-우수영1.40.02.645044460605060<NA><NA><NA><NA><NA><NA><NA>STAT003komsa1662021-08-13 9:44<NA>2021-08-13 9:45제주<NA>3G0601
282192500912021-06-26 9:002F000MPR156214남신안농협5호목포-동리(중간)0.70.02.3304300401057140158.9111.831111.80.000.0STAT003kst0322021-06-26 9:13<NA>2021-06-26 9:15목포<NA>02;10F0905
37572178482020-10-12 7:302L060CMR164405아평호삼-국(편)0.00.00.0230220551003090.000.00.000.0STAT003kst0902020-10-12 13:38<NA>2020-10-12 13:39삼덕<NA>1.2L3001
226202361782021-03-21 7:152L000CMR194402한산농협카페리통-제-의-통(순)1.10.02.325425040280040200.216.3916.30.000.0STAT003komsa1642021-03-21 7:35<NA>2021-03-21 7:37통영흘수확인25L0601
13512150762020-09-22 15:002L000SPR992939세종1호통영-용초(신규/오후)0.750.01.752132094027004026.90.000.00.000.0STAT003komsa1612020-09-22 15:43<NA>2020-09-22 15:45통영흘수확인2.8L2212
70372191112020-10-20 14:002L060CMR114410욕지영동골드고속삼-욕(편)1.50.02.8256655970551050138.772.31972.30.000.0STAT003kst0742020-10-20 17:45<NA>2020-10-20 17:47삼덕<NA>55L1401
499642626562021-09-20 15:002E000MPR064841섬사랑7호완도-여서(청산1회)20.910.01.918580509004052.72.112.10.000.0STAT003komsa1242021-09-20 15:12<NA>2021-09-20 15:26완도<NA>180E0719
101722319672021-02-10 13:002L002CMR184403그랜드페리도산-사량1.850.02.652452040394040196.9100.914100.90.000.0STAT003kst_10302021-02-10 13:02<NA>2021-02-10 13:04가오치<NA>40L1001
440442581372021-08-16 13:002L060CMR114410욕지영동골드고속삼-욕(편)1.50.02.855665597011710060138.790.854390.850.000.0STAT003kst0832021-08-16 13:01<NA>2021-08-16 13:03삼덕<NA>55L1401
421152394262021-04-15 13:302E002WDR166707노화카훼리5호땅끝-산양0.980.02.4628428040231040242.9417.91217.90.000.0STAT003kst0032021-04-15 14:06<NA>2021-04-15 14:08땅끝<NA>30E0902
안전점검표순번출항일시선박종류코드터미널ID선박번호선박 명항로향해구역명흘수선수값흘수중앙값흘수선미값최대승선인원수최대여객인원수최대선원인원수최대임시승선인원수여객대인인원수여객소인인원수여객유아인원수실제선원인수실제임시승선인원수화물적재한도중량실제화물적재중량차량화물수차량화물단위값일반화물단위값컨테이너수컨테이너단위값안전점검표상태코드등록자ID등록일시수정자ID수정 일터미널명흘수비고내용출항시간운항항로 아이디
37832159372020-09-28 11:352J019KSR135802파장금카페리격포-위-격포(순환)1.450.01.935034640280040132.322.881322.80.0800.0STAT003komsa1212020-09-29 14:11<NA>2020-09-29 14:12격포<NA>00-50J0510
130892272022020-12-24 15:202E000MPR004861섬사랑2호완도-모도(순환)0.60.01.854504013004030.61.011.00.000.0STAT003kst0482020-12-24 17:37<NA>2020-12-24 17:38완도<NA>60E2701
191542552732021-07-30 13:402L031CMR194404욕지카훼리중-욕-연-중(순)1.20.02.534233840569140171.541.92441.90.000.0STAT003komsa1612021-07-30 17:09<NA>2021-07-30 17:12욕지<NA>65L3203
403962654362021-10-08 14:552E049WDR136701만세호화흥포-동천-소안0.830.00.030630060520040223.333.42033.40.000.0STAT003jangbk7162021-10-08 14:56<NA>2021-10-08 14:58화흥포만재흘수선 확인55E0203
199402495892021-06-23 7:002L000SPR992939세종1호통영-용초(신규/오전)0.80.01.852132094025004026.98.858.80.000.0STAT003kimjhan2021-06-23 7:10<NA>2021-06-23 7:12통영<NA>2.8L2211
254822390402021-04-12 11:302F004MPR044892비금아일랜드호남강-가산0.80.01.716616240280030201.459.51759.50.000.0STAT003komsa1632021-04-12 12:04<NA>2021-04-12 12:07가산<NA>40F0424
169772263872020-12-18 8:302K008DSR197807가의도호안흥신항-가의도1.10.01.89995402004022.12.012.00.000.0STAT003kst0132020-12-18 7:48<NA>2020-12-18 8:33안흥신항<NA>25K0401
109792314502021-02-05 13:002E002MPR024881장보고호땅끝-산양1.20.00.031931540111040166.816.0616.00.000.0STAT003komsa1262021-02-05 16:16<NA>2021-02-05 16:17땅끝만재흘수선확인30분E0902
276482497002021-06-23 14:302E000WDR077061청산아일랜드호완도-청산0.950.02.552251750304140166.525.71425.70.000.0STAT003kst0482021-06-23 16:08<NA>2021-06-23 16:10완도<NA>50E0302
319022523672021-07-12 10:002E000JJR181036한일블루나래제주-완도2.00.01.82972821508312110091.858.93258.90.000.0STAT003komsa1492021-07-12 13:16<NA>2021-07-12 13:18완도<NA>1.5G0101