Overview

Dataset statistics

Number of variables6
Number of observations300
Missing cells205
Missing cells (%)11.4%
Duplicate rows31
Duplicate rows (%)10.3%
Total size in memory14.2 KiB
Average record size in memory48.4 B

Variable types

Text2
Categorical1
Boolean1
DateTime2

Dataset

Description자동차관리법 및 자동차종합검사 시행등에 관한 규칙에 따라 한국교통안전공단(KOTSA)에서 관리하는 자동차검사 자료입니다.
Author한국교통안전공단
URLhttps://www.data.go.kr/data/15088058/fileData.do

Alerts

사용유무 has constant value ""Constant
등록일시 has constant value ""Constant
수정일시 has constant value ""Constant
Dataset has 31 (10.3%) duplicate rowsDuplicates
제원관리번호 has 41 (13.7%) missing valuesMissing
차명 has 41 (13.7%) missing valuesMissing
사용유무 has 41 (13.7%) missing valuesMissing
등록일시 has 41 (13.7%) missing valuesMissing
수정일시 has 41 (13.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 21:43:43.231488
Analysis finished2023-12-12 21:43:43.778451
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

제원관리번호
Text

MISSING 

Distinct75
Distinct (%)29.0%
Missing41
Missing (%)13.7%
Memory size2.5 KiB
2023-12-13T06:43:43.918091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length8
Mean length10.532819
Min length7

Characters and Unicode

Total characters2728
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)23.2%

Sample

1st row1.20001E+14
2nd row1.20002E+14
3rd row1.20002E+14
4th row1.20002E+14
5th row1.20002E+14
ValueCountFrequency (%)
3.62e+15 62
23.9%
1.12e+15 51
19.7%
1.22e+15 14
 
5.4%
1.62e+15 13
 
5.0%
1.20003e+14 10
 
3.9%
2.42001e+15 10
 
3.9%
1.20002e+14 8
 
3.1%
6.20001e+14 7
 
2.7%
3.20002e+14 5
 
1.9%
2.42e+15 4
 
1.5%
Other values (65) 75
29.0%
2023-12-13T06:43:44.241529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 665
24.4%
0 443
16.2%
2 267
9.8%
3 204
 
7.5%
. 204
 
7.5%
E 204
 
7.5%
+ 204
 
7.5%
5 173
 
6.3%
6 93
 
3.4%
4 80
 
2.9%
Other values (4) 191
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2061
75.5%
Uppercase Letter 259
 
9.5%
Other Punctuation 204
 
7.5%
Math Symbol 204
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 665
32.3%
0 443
21.5%
2 267
13.0%
3 204
 
9.9%
5 173
 
8.4%
6 93
 
4.5%
4 80
 
3.9%
9 66
 
3.2%
7 57
 
2.8%
8 13
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
E 204
78.8%
A 55
 
21.2%
Other Punctuation
ValueCountFrequency (%)
. 204
100.0%
Math Symbol
ValueCountFrequency (%)
+ 204
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2469
90.5%
Latin 259
 
9.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 665
26.9%
0 443
17.9%
2 267
10.8%
3 204
 
8.3%
. 204
 
8.3%
+ 204
 
8.3%
5 173
 
7.0%
6 93
 
3.8%
4 80
 
3.2%
9 66
 
2.7%
Other values (2) 70
 
2.8%
Latin
ValueCountFrequency (%)
E 204
78.8%
A 55
 
21.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 665
24.4%
0 443
16.2%
2 267
9.8%
3 204
 
7.5%
. 204
 
7.5%
E 204
 
7.5%
+ 204
 
7.5%
5 173
 
6.3%
6 93
 
3.4%
4 80
 
2.9%
Other values (4) 191
 
7.0%

차명
Text

MISSING 

Distinct64
Distinct (%)24.7%
Missing41
Missing (%)13.7%
Memory size2.5 KiB
2023-12-13T06:43:44.483477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length10
Min length3

Characters and Unicode

Total characters2590
Distinct characters87
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)11.6%

Sample

1st rowBMW 520d
2nd rowBMW X3 xDrive20d
3rd rowBMW X1 xDrive20d
4th rowBMW X1 xDrive23d
5th rowBMW 320d
ValueCountFrequency (%)
봉고트럭 51
 
10.6%
트랙터 51
 
10.6%
6x2 34
 
7.1%
fh 33
 
6.8%
bmw 19
 
3.9%
fm 18
 
3.7%
이베코6x2트랙터 14
 
2.9%
tdi 13
 
2.7%
actros(3355s 13
 
2.7%
actros(2648ls 13
 
2.7%
Other values (78) 223
46.3%
2023-12-13T06:43:44.857125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
223
 
8.6%
2 135
 
5.2%
트 116
 
4.5%
6 94
 
3.6%
t 80
 
3.1%
x 78
 
3.0%
r 74
 
2.9%
o 71
 
2.7%
3 70
 
2.7%
랙 65
 
2.5%
Other values (77) 1584
61.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 569
22.0%
Decimal Number 563
21.7%
Uppercase Letter 539
20.8%
Other Letter 535
20.7%
Space Separator 223
 
8.6%
Close Punctuation 62
 
2.4%
Open Punctuation 62
 
2.4%
Other Punctuation 23
 
0.9%
Dash Punctuation 10
 
0.4%
Letter Number 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 116
21.7%
랙 65
12.1%
터 65
12.1%
봉 55
10.3%
고 55
10.3%
럭 51
9.5%
베 14
 
2.6%
이 14
 
2.6%
코 14
 
2.6%
스 10
 
1.9%
Other values (21) 76
14.2%
Lowercase Letter
ValueCountFrequency (%)
t 80
14.1%
x 78
13.7%
r 74
13.0%
o 71
12.5%
c 51
9.0%
s 48
8.4%
e 35
6.2%
i 31
 
5.4%
d 20
 
3.5%
a 19
 
3.3%
Other values (10) 62
10.9%
Uppercase Letter
ValueCountFrequency (%)
A 62
11.5%
S 60
11.1%
D 55
10.2%
F 51
9.5%
M 44
 
8.2%
H 40
 
7.4%
T 35
 
6.5%
L 30
 
5.6%
X 28
 
5.2%
I 23
 
4.3%
Other values (10) 111
20.6%
Decimal Number
ValueCountFrequency (%)
2 135
24.0%
6 94
16.7%
3 70
12.4%
0 61
10.8%
4 57
10.1%
1 44
 
7.8%
5 42
 
7.5%
8 30
 
5.3%
9 24
 
4.3%
7 6
 
1.1%
Space Separator
ValueCountFrequency (%)
223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Other Punctuation
ValueCountFrequency (%)
. 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1112
42.9%
Common 943
36.4%
Hangul 535
20.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 80
 
7.2%
x 78
 
7.0%
r 74
 
6.7%
o 71
 
6.4%
A 62
 
5.6%
S 60
 
5.4%
D 55
 
4.9%
c 51
 
4.6%
F 51
 
4.6%
s 48
 
4.3%
Other values (31) 482
43.3%
Hangul
ValueCountFrequency (%)
트 116
21.7%
랙 65
12.1%
터 65
12.1%
봉 55
10.3%
고 55
10.3%
럭 51
9.5%
베 14
 
2.6%
이 14
 
2.6%
코 14
 
2.6%
스 10
 
1.9%
Other values (21) 76
14.2%
Common
ValueCountFrequency (%)
223
23.6%
2 135
14.3%
6 94
10.0%
3 70
 
7.4%
) 62
 
6.6%
( 62
 
6.6%
0 61
 
6.5%
4 57
 
6.0%
1 44
 
4.7%
5 42
 
4.5%
Other values (5) 93
9.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2051
79.2%
Hangul 535
 
20.7%
Number Forms 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
223
 
10.9%
2 135
 
6.6%
6 94
 
4.6%
t 80
 
3.9%
x 78
 
3.8%
r 74
 
3.6%
o 71
 
3.5%
3 70
 
3.4%
) 62
 
3.0%
( 62
 
3.0%
Other values (45) 1102
53.7%
Hangul
ValueCountFrequency (%)
트 116
21.7%
랙 65
12.1%
터 65
12.1%
봉 55
10.3%
고 55
10.3%
럭 51
9.5%
베 14
 
2.6%
이 14
 
2.6%
코 14
 
2.6%
스 10
 
1.9%
Other values (21) 76
14.2%
Number Forms
ValueCountFrequency (%)
Ⅲ 4
100.0%

예외사유
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
유로-4
178 
저공해자동차 3종
57 
<NA>
41 
유로-5
24 

Length

Max length9
Median length4
Mean length4.95
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row저공해자동차 3종
2nd row저공해자동차 3종
3rd row저공해자동차 3종
4th row저공해자동차 3종
5th row저공해자동차 3종

Common Values

ValueCountFrequency (%)
유로-4 178
59.3%
저공해자동차 3종 57
 
19.0%
<NA> 41
 
13.7%
유로-5 24
 
8.0%

Length

2023-12-13T06:43:44.979934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:43:45.141994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유로-4 178
49.9%
저공해자동차 57
 
16.0%
3종 57
 
16.0%
na 41
 
11.5%
유로-5 24
 
6.7%

사용유무
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing41
Missing (%)13.7%
Memory size732.0 B
True
259 
(Missing)
41 
ValueCountFrequency (%)
True 259
86.3%
(Missing) 41
 
13.7%
2023-12-13T06:43:45.294105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일시
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing41
Missing (%)13.7%
Memory size2.5 KiB
Minimum2011-03-21 00:00:00
Maximum2011-03-21 00:00:00
2023-12-13T06:43:45.412320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:43:45.542634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

수정일시
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing41
Missing (%)13.7%
Memory size2.5 KiB
Minimum2011-03-21 00:00:00
Maximum2011-03-21 00:00:00
2023-12-13T06:43:45.676561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:43:45.807080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-13T06:43:45.903220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제원관리번호차명예외사유
제원관리번호1.0000.8390.967
차명0.8391.0000.991
예외사유0.9670.9911.000

Missing values

2023-12-13T06:43:43.544824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:43:43.629118image/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.
2023-12-13T06:43:43.712548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

제원관리번호차명예외사유사용유무등록일시수정일시
01.20001E+14BMW 520d저공해자동차 3종Y2011-03-212011-03-21
11.20002E+14BMW X3 xDrive20d저공해자동차 3종Y2011-03-212011-03-21
21.20002E+14BMW X1 xDrive20d저공해자동차 3종Y2011-03-212011-03-21
31.20002E+14BMW X1 xDrive23d저공해자동차 3종Y2011-03-212011-03-21
41.20002E+14BMW 320d저공해자동차 3종Y2011-03-212011-03-21
51.20002E+14BMW 320d저공해자동차 3종Y2011-03-212011-03-21
61.20002E+14BMW X5 xDrive30d저공해자동차 3종Y2011-03-212011-03-21
71.20002E+14BMW X5 xDrive30d저공해자동차 3종Y2011-03-212011-03-21
81.20002E+14BMW X5 xDrive30d저공해자동차 3종Y2011-03-212011-03-21
91.20003E+14BMW X6 xDrive30d저공해자동차 3종Y2011-03-212011-03-21
제원관리번호차명예외사유사용유무등록일시수정일시
290<NA><NA><NA><NA><NA><NA>
291<NA><NA><NA><NA><NA><NA>
292<NA><NA><NA><NA><NA><NA>
293<NA><NA><NA><NA><NA><NA>
294<NA><NA><NA><NA><NA><NA>
295<NA><NA><NA><NA><NA><NA>
296<NA><NA><NA><NA><NA><NA>
297<NA><NA><NA><NA><NA><NA>
298<NA><NA><NA><NA><NA><NA>
299<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

제원관리번호차명예외사유사용유무등록일시수정일시# duplicates
30<NA><NA><NA><NA><NA><NA>41
01.12E+15FH 6x2 트랙터유로-4Y2011-03-212011-03-2122
91.22E+15이베코6x2트랙터유로-4Y2011-03-212011-03-2114
203.62E+15Actros(3355S)유로-4Y2011-03-212011-03-2113
31.12E+15FM 6x2 트랙터유로-4Y2011-03-212011-03-2112
11.12E+15FH 6x4 트랙터유로-4Y2011-03-212011-03-2111
173.62E+15Actros(2648LS)유로-4Y2011-03-212011-03-2111
111.62E+15TGX유로-5Y2011-03-212011-03-2110
223.62E+15Atego(1229)유로-4Y2011-03-212011-03-2110
21.12E+15FM 4x2 트랙터유로-4Y2011-03-212011-03-216