Overview

Dataset statistics

Number of variables6
Number of observations56
Missing cells15
Missing cells (%)4.5%
Duplicate rows1
Duplicate rows (%)1.8%
Total size in memory2.8 KiB
Average record size in memory51.4 B

Variable types

Text3
Categorical2
Numeric1

Dataset

Description한국교통안전공단 통합홈페이지시스템에서 관리하고 있는 연구교육지식 관련 정보입니다
Author한국교통안전공단
URLhttps://www.data.go.kr/data/15066110/fileData.do

Alerts

Dataset has 1 (1.8%) duplicate rowsDuplicates
파일확장자 is highly overall correlated with 최초등록일시High correlation
최초등록일시 is highly overall correlated with 파일확장자High correlation
저장파일명 has 5 (8.9%) missing valuesMissing
파일크기 has 5 (8.9%) missing valuesMissing
파일설명 has 5 (8.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 16:56:06.613526
Analysis finished2023-12-12 16:56:07.485710
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

원본파일명
Text

Distinct50
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-13T01:56:07.679672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length37
Mean length24.75
Min length3

Characters and Unicode

Total characters1386
Distinct characters224
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)83.9%

Sample

1st row비중표.xlsx
2nd row01.신규체험교육 프로그램 개발연구용역(2020)_최종보고서(최종).pdf
3rd row2020년_교통안전체험교육_운영_기본계획.hwp
4th row브로슈어_B5(182x257)안전속도5030.pdf
5th row브로슈어_B5(182x257)안전속도5030.pdf
ValueCountFrequency (%)
2019년 10
 
5.5%
연구.pdf 7
 
3.9%
flv 5
 
2.8%
및 4
 
2.2%
신청서.hwp 3
 
1.7%
교통안전체험교육 2
 
1.1%
0요약_최종.pdf 2
 
1.1%
건설기계 2
 
1.1%
교통안전 2
 
1.1%
첨부파일 2
 
1.1%
Other values (132) 142
78.5%
2023-12-13T01:56:08.107790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
9.0%
. 54
 
3.9%
p 49
 
3.5%
0 36
 
2.6%
f 35
 
2.5%
교 32
 
2.3%
_ 31
 
2.2%
d 30
 
2.2%
전 30
 
2.2%
2 29
 
2.1%
Other values (214) 935
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 789
56.9%
Lowercase Letter 191
 
13.8%
Decimal Number 130
 
9.4%
Space Separator 125
 
9.0%
Other Punctuation 54
 
3.9%
Connector Punctuation 31
 
2.2%
Close Punctuation 27
 
1.9%
Open Punctuation 27
 
1.9%
Uppercase Letter 7
 
0.5%
Dash Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
자 18
 
2.3%
서 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%
Lowercase Letter
ValueCountFrequency (%)
p 49
25.7%
f 35
18.3%
d 30
15.7%
h 19
 
9.9%
w 17
 
8.9%
l 9
 
4.7%
x 8
 
4.2%
v 5
 
2.6%
s 5
 
2.6%
e 3
 
1.6%
Other values (10) 11
 
5.8%
Decimal Number
ValueCountFrequency (%)
0 36
27.7%
2 29
22.3%
1 25
19.2%
9 15
11.5%
5 10
 
7.7%
8 6
 
4.6%
3 5
 
3.8%
7 3
 
2.3%
4 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
C 1
14.3%
D 1
14.3%
H 1
14.3%
I 1
14.3%
A 1
14.3%
Close Punctuation
ValueCountFrequency (%)
) 14
51.9%
] 13
48.1%
Open Punctuation
ValueCountFrequency (%)
( 14
51.9%
[ 13
48.1%
Space Separator
ValueCountFrequency (%)
125
100.0%
Other Punctuation
ValueCountFrequency (%)
. 54
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
56.9%
Common 399
28.8%
Latin 198
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
자 18
 
2.3%
서 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%
Latin
ValueCountFrequency (%)
p 49
24.7%
f 35
17.7%
d 30
15.2%
h 19
 
9.6%
w 17
 
8.6%
l 9
 
4.5%
x 8
 
4.0%
v 5
 
2.5%
s 5
 
2.5%
e 3
 
1.5%
Other values (16) 18
 
9.1%
Common
ValueCountFrequency (%)
125
31.3%
. 54
13.5%
0 36
 
9.0%
_ 31
 
7.8%
2 29
 
7.3%
1 25
 
6.3%
9 15
 
3.8%
) 14
 
3.5%
( 14
 
3.5%
[ 13
 
3.3%
Other values (7) 43
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
56.9%
ASCII 597
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
20.9%
. 54
 
9.0%
p 49
 
8.2%
0 36
 
6.0%
f 35
 
5.9%
_ 31
 
5.2%
d 30
 
5.0%
2 29
 
4.9%
1 25
 
4.2%
h 19
 
3.2%
Other values (33) 164
27.5%
Hangul
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
자 18
 
2.3%
서 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%

저장파일명
Text

MISSING 

Distinct51
Distinct (%)100.0%
Missing5
Missing (%)8.9%
Memory size580.0 B
2023-12-13T01:56:08.335880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length24.980392
Min length24

Characters and Unicode

Total characters1274
Distinct characters16
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

Unique51 ?
Unique (%)100.0%

Sample

1st rowkcmBBS_202002260551369660
2nd rowkcmBBS_202002170411479390
3rd rowkcmBBS_202002170405578680
4th rowkcmBBS_202002070258554410
5th rowkcmBBS_202002070257553460
ValueCountFrequency (%)
kcmbbs_202002170411479390 1
 
2.0%
kcmbbs_201907170926077400 1
 
2.0%
kcmbbs_201909161048116860 1
 
2.0%
kcmbbs_201909020949485251 1
 
2.0%
kcmbbs_201909020949485140 1
 
2.0%
kcmbbs_201908140314248131 1
 
2.0%
kcmbbs_201908140314248130 1
 
2.0%
kcmbbs_201908140313324375 1
 
2.0%
kcmbbs_201908140313324374 1
 
2.0%
kcmbbs_201908140313324363 1
 
2.0%
Other values (41) 41
80.4%
2023-12-13T01:56:08.748708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 256
20.1%
1 157
12.3%
2 122
9.6%
B 102
 
8.0%
3 97
 
7.6%
4 77
 
6.0%
9 61
 
4.8%
k 51
 
4.0%
c 51
 
4.0%
m 51
 
4.0%
Other values (6) 249
19.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 917
72.0%
Uppercase Letter 153
 
12.0%
Lowercase Letter 153
 
12.0%
Connector Punctuation 51
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 256
27.9%
1 157
17.1%
2 122
13.3%
3 97
 
10.6%
4 77
 
8.4%
9 61
 
6.7%
5 43
 
4.7%
8 42
 
4.6%
6 34
 
3.7%
7 28
 
3.1%
Lowercase Letter
ValueCountFrequency (%)
k 51
33.3%
c 51
33.3%
m 51
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 102
66.7%
S 51
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 968
76.0%
Latin 306
 
24.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 256
26.4%
1 157
16.2%
2 122
12.6%
3 97
 
10.0%
4 77
 
8.0%
9 61
 
6.3%
_ 51
 
5.3%
5 43
 
4.4%
8 42
 
4.3%
6 34
 
3.5%
Latin
ValueCountFrequency (%)
B 102
33.3%
k 51
16.7%
c 51
16.7%
m 51
16.7%
S 51
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 256
20.1%
1 157
12.3%
2 122
9.6%
B 102
 
8.0%
3 97
 
7.6%
4 77
 
6.0%
9 61
 
4.8%
k 51
 
4.0%
c 51
 
4.0%
m 51
 
4.0%
Other values (6) 249
19.5%

파일확장자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
pdf
30 
hwp
17 
flv
5 
xlsx
 
3
jpg
 
1

Length

Max length4
Median length3
Mean length3.0535714
Min length3

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowxlsx
2nd rowpdf
3rd rowhwp
4th rowpdf
5th rowpdf

Common Values

ValueCountFrequency (%)
pdf 30
53.6%
hwp 17
30.4%
flv 5
 
8.9%
xlsx 3
 
5.4%
jpg 1
 
1.8%

Length

2023-12-13T01:56:08.894353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:56:09.028890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pdf 30
53.6%
hwp 17
30.4%
flv 5
 
8.9%
xlsx 3
 
5.4%
jpg 1
 
1.8%

파일크기
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)94.1%
Missing5
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean20274149
Minimum15360
Maximum1.8390378 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-13T01:56:09.167389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15360
5-th percentile17408
Q144854
median1552737
Q318122114
95-th percentile79963643
Maximum1.8390378 × 108
Range1.8388842 × 108
Interquartile range (IQR)18077260

Descriptive statistics

Standard deviation38629521
Coefficient of variation (CV)1.9053584
Kurtosis7.608647
Mean20274149
Median Absolute Deviation (MAD)1532257
Skewness2.6205051
Sum1.0339816 × 109
Variance1.4922399 × 1015
MonotonicityNot monotonic
2023-12-13T01:56:09.320778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1294694 2
 
3.6%
37376 2
 
3.6%
16896 2
 
3.6%
13178835 1
 
1.8%
6976374 1
 
1.8%
59392 1
 
1.8%
71168 1
 
1.8%
28672 1
 
1.8%
20480 1
 
1.8%
17920 1
 
1.8%
Other values (38) 38
67.9%
(Missing) 5
 
8.9%
ValueCountFrequency (%)
15360 1
1.8%
16896 2
3.6%
17920 1
1.8%
18255 1
1.8%
18432 1
1.8%
20480 1
1.8%
25600 1
1.8%
28672 1
1.8%
36864 1
1.8%
37376 2
3.6%
ValueCountFrequency (%)
183903777 1
1.8%
151709223 1
1.8%
91107740 1
1.8%
68819546 1
1.8%
65099420 1
1.8%
64318727 1
1.8%
60946244 1
1.8%
57349307 1
1.8%
56623104 1
1.8%
46395231 1
1.8%

파일설명
Text

MISSING 

Distinct49
Distinct (%)96.1%
Missing5
Missing (%)8.9%
Memory size580.0 B
2023-12-13T01:56:09.594865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length33
Mean length22.823529
Min length3

Characters and Unicode

Total characters1164
Distinct characters218
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)92.2%

Sample

1st row비중표
2nd row01.신규체험교육 프로그램 개발연구용역(2020)_최종보고서(최종)
3rd row2020년_교통안전체험교육_운영_기본계획
4th row브로슈어_B5(182x257)안전속도5030
5th row브로슈어_B5(182x257)안전속도5030
ValueCountFrequency (%)
2019년 10
 
5.7%
연구 8
 
4.5%
및 4
 
2.3%
신청서 3
 
1.7%
2 2
 
1.1%
5030 2
 
1.1%
안전속도 2
 
1.1%
0요약_최종 2
 
1.1%
교통문화지수 2
 
1.1%
교통안전체험교육 2
 
1.1%
Other values (130) 139
79.0%
2023-12-13T01:56:10.097772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
125
 
10.7%
0 36
 
3.1%
교 32
 
2.7%
_ 31
 
2.7%
전 30
 
2.6%
안 29
 
2.5%
2 29
 
2.5%
1 25
 
2.1%
통 25
 
2.1%
사 23
 
2.0%
Other values (208) 779
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 789
67.8%
Decimal Number 130
 
11.2%
Space Separator 125
 
10.7%
Connector Punctuation 31
 
2.7%
Open Punctuation 27
 
2.3%
Close Punctuation 27
 
2.3%
Lowercase Letter 20
 
1.7%
Uppercase Letter 7
 
0.6%
Dash Punctuation 5
 
0.4%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
서 18
 
2.3%
자 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
m 2
10.0%
s 2
10.0%
h 2
10.0%
x 2
10.0%
u 1
 
5.0%
t 1
 
5.0%
a 1
 
5.0%
y 1
 
5.0%
r 1
 
5.0%
Other values (4) 4
20.0%
Decimal Number
ValueCountFrequency (%)
0 36
27.7%
2 29
22.3%
1 25
19.2%
9 15
11.5%
5 10
 
7.7%
8 6
 
4.6%
3 5
 
3.8%
7 3
 
2.3%
4 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
D 1
14.3%
C 1
14.3%
I 1
14.3%
A 1
14.3%
H 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 14
51.9%
[ 13
48.1%
Close Punctuation
ValueCountFrequency (%)
) 14
51.9%
] 13
48.1%
Space Separator
ValueCountFrequency (%)
125
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
67.8%
Common 348
29.9%
Latin 27
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
서 18
 
2.3%
자 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%
Latin
ValueCountFrequency (%)
e 3
 
11.1%
m 2
 
7.4%
s 2
 
7.4%
h 2
 
7.4%
B 2
 
7.4%
x 2
 
7.4%
D 1
 
3.7%
u 1
 
3.7%
t 1
 
3.7%
a 1
 
3.7%
Other values (10) 10
37.0%
Common
ValueCountFrequency (%)
125
35.9%
0 36
 
10.3%
_ 31
 
8.9%
2 29
 
8.3%
1 25
 
7.2%
9 15
 
4.3%
( 14
 
4.0%
) 14
 
4.0%
] 13
 
3.7%
[ 13
 
3.7%
Other values (7) 33
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
67.8%
ASCII 375
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
125
33.3%
0 36
 
9.6%
_ 31
 
8.3%
2 29
 
7.7%
1 25
 
6.7%
9 15
 
4.0%
( 14
 
3.7%
) 14
 
3.7%
] 13
 
3.5%
[ 13
 
3.5%
Other values (27) 60
16.0%
Hangul
ValueCountFrequency (%)
교 32
 
4.1%
전 30
 
3.8%
안 29
 
3.7%
통 25
 
3.2%
사 23
 
2.9%
시 20
 
2.5%
서 18
 
2.3%
자 18
 
2.3%
년 16
 
2.0%
차 14
 
1.8%
Other values (171) 564
71.5%

최초등록일시
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
2020-01-13
10 
2019-08-14
8 
2020-01-10
7 
<NA>
5 
2019-12-18
3 
Other values (15)
23 

Length

Max length10
Median length10
Mean length9.4642857
Min length4

Unique

Unique8 ?
Unique (%)14.3%

Sample

1st row2020-02-26
2nd row2020-02-17
3rd row2020-02-17
4th row2020-02-07
5th row2020-02-07

Common Values

ValueCountFrequency (%)
2020-01-13 10
17.9%
2019-08-14 8
14.3%
2020-01-10 7
12.5%
<NA> 5
8.9%
2019-12-18 3
 
5.4%
2019-03-08 3
 
5.4%
2020-02-17 2
 
3.6%
2019-01-22 2
 
3.6%
2019-03-13 2
 
3.6%
2019-09-02 2
 
3.6%
Other values (10) 12
21.4%

Length

2023-12-13T01:56:10.285168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-01-13 10
17.9%
2019-08-14 8
14.3%
2020-01-10 7
12.5%
na 5
8.9%
2019-12-18 3
 
5.4%
2019-03-08 3
 
5.4%
2019-09-02 2
 
3.6%
2020-01-31 2
 
3.6%
2020-02-07 2
 
3.6%
2019-03-13 2
 
3.6%
Other values (10) 12
21.4%

Interactions

2023-12-13T01:56:07.070060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:56:10.398231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
원본파일명저장파일명파일확장자파일크기파일설명최초등록일시
원본파일명1.0001.0001.0001.0001.0000.969
저장파일명1.0001.0001.0001.0001.0001.000
파일확장자1.0001.0001.0000.0001.0000.918
파일크기1.0001.0000.0001.0001.0000.000
파일설명1.0001.0001.0001.0001.0000.969
최초등록일시0.9691.0000.9180.0000.9691.000
2023-12-13T01:56:10.524905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
파일확장자최초등록일시
파일확장자1.0000.640
최초등록일시0.6401.000
2023-12-13T01:56:10.620352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
파일크기파일확장자최초등록일시
파일크기1.0000.0000.000
파일확장자0.0001.0000.640
최초등록일시0.0000.6401.000

Missing values

2023-12-13T01:56:07.195963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:56:07.300535image/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.
2023-12-13T01:56:07.413177image/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

원본파일명저장파일명파일확장자파일크기파일설명최초등록일시
0비중표.xlsxkcmBBS_202002260551369660xlsx18255비중표2020-02-26
101.신규체험교육 프로그램 개발연구용역(2020)_최종보고서(최종).pdfkcmBBS_202002170411479390pdf658961201.신규체험교육 프로그램 개발연구용역(2020)_최종보고서(최종)2020-02-17
22020년_교통안전체험교육_운영_기본계획.hwpkcmBBS_202002170405578680hwp11279362020년_교통안전체험교육_운영_기본계획2020-02-17
3브로슈어_B5(182x257)안전속도5030.pdfkcmBBS_202002070258554410pdf1294694브로슈어_B5(182x257)안전속도50302020-02-07
4브로슈어_B5(182x257)안전속도5030.pdfkcmBBS_202002070257553460pdf1294694브로슈어_B5(182x257)안전속도50302020-02-07
52019년 교통문화지수 실태조사(부록 보고서).pdfkcmBBS_202001310437329601pdf131788352019년 교통문화지수 실태조사(부록 보고서)2020-01-31
62019년_교통문화지수_실태조사(본_보고서).pdfkcmBBS_202001310437329410pdf92450492019년_교통문화지수_실태조사(본_보고서)2020-01-31
7[2019년] 사업용자동차 교통사고 원인조사 연구(법인택시).pdfkcmBBS_202001140425471730pdf57349307[2019년] 사업용자동차 교통사고 원인조사 연구(법인택시)2020-01-14
8[2019년] 사업용자동차 교통사고 원인조사 연구(법인택시).pdfkcmBBS_202001131109249660pdf56623104[2019년] 사업용자동차 교통사고 원인조사 연구(법인택시)2020-01-13
9[2019년] 생활주기를 반영한 화물버스 운전자의 졸음운전 영향 요인 실태조사 연구.pdfkcmBBS_202001130824069490pdf1692628[2019년] 생활주기를 반영한 화물버스 운전자의 졸음운전 영향 요인 실태조사 연구2020-01-13
원본파일명저장파일명파일확장자파일크기파일설명최초등록일시
46교통안전체험교육 교육과정 및 내용.hwpkcmBBS_201903080134394600hwp51712교통안전체험교육 교육과정 및 내용2019-03-08
472018년 교통문화지수 실태조사_보고서.pdfkcmBBS_201901310411267940pdf124827242018년 교통문화지수 실태조사_보고서2019-01-31
48교통안전특별실태조사-전남 여수시 0요약_최종.pdfkcmBBS_201901220437331470pdf183903777교통안전특별실태조사-전남 여수시 0요약_최종2019-01-22
49교통안전특별실태조사-부산 사하구 0요약_최종.pdfkcmBBS_201901220437074360pdf151709223교통안전특별실태조사-부산 사하구 0요약_최종2019-01-22
50Chrysanthemum.jpgkcmBBS_20140413035504911jpg879394Chrysanthemum2014-04-13
51flv<NA>flv<NA><NA><NA>
52flv<NA>flv<NA><NA><NA>
53flv<NA>flv<NA><NA><NA>
54flv<NA>flv<NA><NA><NA>
55flv<NA>flv<NA><NA><NA>

Duplicate rows

Most frequently occurring

원본파일명저장파일명파일확장자파일크기파일설명최초등록일시# duplicates
0flv<NA>flv<NA><NA><NA>5