Overview

Dataset statistics

Number of variables8
Number of observations10000
Missing cells6
Missing cells (%)< 0.1%
Duplicate rows13
Duplicate rows (%)0.1%
Total size in memory722.7 KiB
Average record size in memory74.0 B

Variable types

Categorical5
DateTime1
Text2

Dataset

Description인천광역시 교통행정종합관리시스템 단속대장조회(단속년도,자치단체,단속일시,차종,차명,단속장소,단속구분, 단속방법) 데이터 자료 입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15049221&srcSe=7661IVAWM27C61E190

Alerts

자치단체 has constant value ""Constant
단속구분 has constant value ""Constant
Dataset has 13 (0.1%) duplicate rowsDuplicates
차종 is highly imbalanced (73.2%)Imbalance

Reproduction

Analysis started2024-01-28 15:54:17.738414
Analysis finished2024-01-28 15:54:18.442185
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속년도
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2021
5343 
2022
4657 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 5343
53.4%
2022 4657
46.6%

Length

2024-01-29T00:54:18.492062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:54:18.580705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 5343
53.4%
2022 4657
46.6%

자치단체
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
28000
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row28000
2nd row28000
3rd row28000
4th row28000
5th row28000

Common Values

ValueCountFrequency (%)
28000 10000
100.0%

Length

2024-01-29T00:54:18.663674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:54:18.730901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
28000 10000
100.0%

단속일시
Date

Distinct9605
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-02 10:07:00
Maximum2022-11-30 20:38:00
2024-01-29T00:54:18.815783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:54:18.921525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차종
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
01 승용차
8589 
03 화물차(4t 이하)
1063 
02 승합차
 
234
04 화물차(4t 초과)
 
46
06 특수자동차
 
39
Other values (2)
 
29

Length

Max length13
Median length6
Mean length6.7861
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row01 승용차
2nd row01 승용차
3rd row01 승용차
4th row01 승용차
5th row03 화물차(4t 이하)

Common Values

ValueCountFrequency (%)
01 승용차 8589
85.9%
03 화물차(4t 이하) 1063
 
10.6%
02 승합차 234
 
2.3%
04 화물차(4t 초과) 46
 
0.5%
06 특수자동차 39
 
0.4%
05 건설기계 20
 
0.2%
08 이륜차 9
 
0.1%

Length

2024-01-29T00:54:19.022821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:54:19.123357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
01 8589
40.7%
승용차 8589
40.7%
화물차(4t 1109
 
5.3%
03 1063
 
5.0%
이하 1063
 
5.0%
02 234
 
1.1%
승합차 234
 
1.1%
04 46
 
0.2%
초과 46
 
0.2%
06 39
 
0.2%
Other values (5) 97
 
0.5%

차명
Text

Distinct959
Distinct (%)9.6%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2024-01-29T00:54:19.351011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length8.8558135
Min length2

Characters and Unicode

Total characters88505
Distinct characters338
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique482 ?
Unique (%)4.8%

Sample

1st rowK5
2nd row레이
3rd row카니발
4th row레이
5th row코란도스포츠
ValueCountFrequency (%)
쏘나타(sonata 890
 
5.8%
k5 504
 
3.3%
그랜저(grandeur 469
 
3.1%
모닝 396
 
2.6%
아반떼(avante 391
 
2.5%
카니발 347
 
2.3%
싼타페(santafe 319
 
2.1%
쏘렌토 308
 
2.0%
porterⅱ 288
 
1.9%
포터ⅱ 284
 
1.8%
Other values (865) 11174
72.7%
2024-01-29T00:54:19.712168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 5514
 
6.2%
5381
 
6.1%
( 3829
 
4.3%
) 3828
 
4.3%
T 3451
 
3.9%
N 3300
 
3.7%
E 2977
 
3.4%
R 2765
 
3.1%
S 2710
 
3.1%
O 2257
 
2.6%
Other values (328) 52493
59.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 35123
39.7%
Other Letter 27558
31.1%
Decimal Number 6179
 
7.0%
Space Separator 5381
 
6.1%
Lowercase Letter 4423
 
5.0%
Open Punctuation 3829
 
4.3%
Close Punctuation 3828
 
4.3%
Letter Number 1105
 
1.2%
Dash Punctuation 545
 
0.6%
Other Punctuation 533
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 1786
 
6.5%
타 1658
 
6.0%
쏘 1390
 
5.0%
나 1117
 
4.1%
포 857
 
3.1%
이 826
 
3.0%
랜 816
 
3.0%
그 813
 
3.0%
리 684
 
2.5%
아 661
 
2.4%
Other values (257) 16950
61.5%
Uppercase Letter
ValueCountFrequency (%)
A 5514
15.7%
T 3451
9.8%
N 3300
 
9.4%
E 2977
 
8.5%
R 2765
 
7.9%
S 2710
 
7.7%
O 2257
 
6.4%
D 1604
 
4.6%
C 1115
 
3.2%
G 1080
 
3.1%
Other values (16) 8350
23.8%
Lowercase Letter
ValueCountFrequency (%)
e 574
13.0%
i 474
10.7%
r 427
9.7%
o 385
 
8.7%
t 365
 
8.3%
d 324
 
7.3%
a 323
 
7.3%
u 214
 
4.8%
n 188
 
4.3%
c 172
 
3.9%
Other values (15) 977
22.1%
Decimal Number
ValueCountFrequency (%)
0 1463
23.7%
5 1177
19.0%
2 779
12.6%
1 753
12.2%
3 743
12.0%
4 396
 
6.4%
7 296
 
4.8%
6 289
 
4.7%
8 232
 
3.8%
9 51
 
0.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 871
78.8%
Ⅲ 234
 
21.2%
Dash Punctuation
ValueCountFrequency (%)
- 541
99.3%
－ 4
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 530
99.4%
¡ 3
 
0.6%
Space Separator
ValueCountFrequency (%)
5381
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3829
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3828
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40651
45.9%
Hangul 27558
31.1%
Common 20296
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 1786
 
6.5%
타 1658
 
6.0%
쏘 1390
 
5.0%
나 1117
 
4.1%
포 857
 
3.1%
이 826
 
3.0%
랜 816
 
3.0%
그 813
 
3.0%
리 684
 
2.5%
아 661
 
2.4%
Other values (257) 16950
61.5%
Latin
ValueCountFrequency (%)
A 5514
 
13.6%
T 3451
 
8.5%
N 3300
 
8.1%
E 2977
 
7.3%
R 2765
 
6.8%
S 2710
 
6.7%
O 2257
 
5.6%
D 1604
 
3.9%
C 1115
 
2.7%
G 1080
 
2.7%
Other values (43) 13878
34.1%
Common
ValueCountFrequency (%)
5381
26.5%
( 3829
18.9%
) 3828
18.9%
0 1463
 
7.2%
5 1177
 
5.8%
2 779
 
3.8%
1 753
 
3.7%
3 743
 
3.7%
- 541
 
2.7%
. 530
 
2.6%
Other values (8) 1272
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59835
67.6%
Hangul 27558
31.1%
Number Forms 1105
 
1.2%
None 7
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 5514
 
9.2%
5381
 
9.0%
( 3829
 
6.4%
) 3828
 
6.4%
T 3451
 
5.8%
N 3300
 
5.5%
E 2977
 
5.0%
R 2765
 
4.6%
S 2710
 
4.5%
O 2257
 
3.8%
Other values (57) 23823
39.8%
Hangul
ValueCountFrequency (%)
스 1786
 
6.5%
타 1658
 
6.0%
쏘 1390
 
5.0%
나 1117
 
4.1%
포 857
 
3.1%
이 826
 
3.0%
랜 816
 
3.0%
그 813
 
3.0%
리 684
 
2.5%
아 661
 
2.4%
Other values (257) 16950
61.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 871
78.8%
Ⅲ 234
 
21.2%
None
ValueCountFrequency (%)
－ 4
57.1%
¡ 3
42.9%

단속장소
Text

Distinct705
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:54:19.913286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length9.7204
Min length3

Characters and Unicode

Total characters97204
Distinct characters203
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)4.4%

Sample

1st row주안동 경인로 부근
2nd row간석레미안자이A
3rd row유동삼거리
4th row간석동 경인로 부근
5th row숭의동 참외전로 부근
ValueCountFrequency (%)
부근 2092
 
12.1%
관교동 1227
 
7.1%
롯데백화점(터미널점)앞(전일제 1177
 
6.8%
경인로 1047
 
6.1%
만수주공단지 825
 
4.8%
인천교통공사앞 788
 
4.6%
간석레미안자이a 743
 
4.3%
부평gm자동차앞 663
 
3.8%
간석동 637
 
3.7%
구월동 624
 
3.6%
Other values (625) 7436
43.1%
2024-01-29T00:54:20.225647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7260
 
7.5%
동 5539
 
5.7%
부 4702
 
4.8%
로 3877
 
4.0%
앞 3308
 
3.4%
인 3211
 
3.3%
근 2861
 
2.9%
) 2770
 
2.8%
( 2770
 
2.8%
점 2449
 
2.5%
Other values (193) 58457
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77515
79.7%
Space Separator 7260
 
7.5%
Decimal Number 3883
 
4.0%
Close Punctuation 2770
 
2.8%
Open Punctuation 2770
 
2.8%
Uppercase Letter 2411
 
2.5%
Dash Punctuation 321
 
0.3%
Other Punctuation 271
 
0.3%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5539
 
7.1%
부 4702
 
6.1%
로 3877
 
5.0%
앞 3308
 
4.3%
인 3211
 
4.1%
근 2861
 
3.7%
점 2449
 
3.2%
교 2059
 
2.7%
미 2002
 
2.6%
공 1665
 
2.1%
Other values (169) 45842
59.1%
Decimal Number
ValueCountFrequency (%)
1 614
15.8%
0 560
14.4%
3 463
11.9%
5 456
11.7%
7 389
10.0%
4 355
9.1%
2 346
8.9%
9 306
7.9%
6 213
 
5.5%
8 181
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 779
32.3%
M 663
27.5%
G 663
27.5%
B 100
 
4.1%
R 100
 
4.1%
T 100
 
4.1%
I 3
 
0.1%
C 3
 
0.1%
Space Separator
ValueCountFrequency (%)
7260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2770
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2770
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%
Other Punctuation
ValueCountFrequency (%)
. 271
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77515
79.7%
Common 17278
 
17.8%
Latin 2411
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5539
 
7.1%
부 4702
 
6.1%
로 3877
 
5.0%
앞 3308
 
4.3%
인 3211
 
4.1%
근 2861
 
3.7%
점 2449
 
3.2%
교 2059
 
2.7%
미 2002
 
2.6%
공 1665
 
2.1%
Other values (169) 45842
59.1%
Common
ValueCountFrequency (%)
7260
42.0%
) 2770
 
16.0%
( 2770
 
16.0%
1 614
 
3.6%
0 560
 
3.2%
3 463
 
2.7%
5 456
 
2.6%
7 389
 
2.3%
4 355
 
2.1%
2 346
 
2.0%
Other values (6) 1295
 
7.5%
Latin
ValueCountFrequency (%)
A 779
32.3%
M 663
27.5%
G 663
27.5%
B 100
 
4.1%
R 100
 
4.1%
T 100
 
4.1%
I 3
 
0.1%
C 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77515
79.7%
ASCII 19689
 
20.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7260
36.9%
) 2770
 
14.1%
( 2770
 
14.1%
A 779
 
4.0%
M 663
 
3.4%
G 663
 
3.4%
1 614
 
3.1%
0 560
 
2.8%
3 463
 
2.4%
5 456
 
2.3%
Other values (14) 2691
 
13.7%
Hangul
ValueCountFrequency (%)
동 5539
 
7.1%
부 4702
 
6.1%
로 3877
 
5.0%
앞 3308
 
4.3%
인 3211
 
4.1%
근 2861
 
3.7%
점 2449
 
3.2%
교 2059
 
2.7%
미 2002
 
2.6%
공 1665
 
2.1%
Other values (169) 45842
59.1%

단속구분
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
98 버스전용차로위반
10000 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row98 버스전용차로위반
2nd row98 버스전용차로위반
3rd row98 버스전용차로위반
4th row98 버스전용차로위반
5th row98 버스전용차로위반

Common Values

ValueCountFrequency (%)
98 버스전용차로위반 10000
100.0%

Length

2024-01-29T00:54:20.332976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:54:20.413462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
98 10000
50.0%
버스전용차로위반 10000
50.0%

단속방법
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
고정형CCTV
5607 
차량형CCTV
2086 
버스탑재형
994 
버스탑재형(SIDE)
710 
생활불편신고(국민신문고등)
603 

Length

Max length16
Median length9
Mean length9.5073
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row차량형CCTV
2nd row고정형CCTV
3rd row고정형CCTV
4th row차량형CCTV
5th row차량형CCTV

Common Values

ValueCountFrequency (%)
고정형CCTV 5607
56.1%
차량형CCTV 2086
 
20.9%
버스탑재형 994
 
9.9%
버스탑재형(SIDE) 710
 
7.1%
생활불편신고(국민신문고등) 603
 
6.0%

Length

2024-01-29T00:54:20.501918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:54:20.576300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형cctv 5607
56.1%
차량형cctv 2086
 
20.9%
버스탑재형 994
 
9.9%
버스탑재형(side 710
 
7.1%
생활불편신고(국민신문고등 603
 
6.0%

Correlations

2024-01-29T00:54:20.631490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속년도차종단속방법
단속년도1.0000.0290.146
차종0.0291.0000.113
단속방법0.1460.1131.000
2024-01-29T00:54:20.696569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차종단속방법단속년도
차종1.0000.0720.031
단속방법0.0721.0000.179
단속년도0.0310.1791.000
2024-01-29T00:54:20.760862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속년도차종단속방법
단속년도1.0000.0310.179
차종0.0311.0000.072
단속방법0.1790.0721.000

Missing values

2024-01-29T00:54:18.294624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:54:18.391186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

단속년도자치단체단속일시차종차명단속장소단속구분단속방법
451892022280002022-09-23 17:1601 승용차K5주안동 경인로 부근98 버스전용차로위반차량형CCTV
628072022280002022-01-27 18:2401 승용차레이간석레미안자이A98 버스전용차로위반고정형CCTV
7742021280002021-01-13 18:0901 승용차카니발유동삼거리98 버스전용차로위반고정형CCTV
153152021280002021-07-01 17:3801 승용차레이간석동 경인로 부근98 버스전용차로위반차량형CCTV
176282021280002021-07-23 7:3203 화물차(4t 이하)코란도스포츠숭의동 참외전로 부근98 버스전용차로위반차량형CCTV
657692022280002022-02-05 0:1701 승용차쏘렌토인하로부근98 버스전용차로위반버스탑재형(SIDE)
663712022280002022-10-25 8:3404 화물차(4t 초과)한국쓰리축14톤윙바디부평대로부근98 버스전용차로위반버스탑재형(SIDE)
414882022280002022-09-15 17:1901 승용차렉스턴주안동 경인로499번길 부근98 버스전용차로위반차량형CCTV
311532021280002021-11-18 7:3601 승용차K8 하이브리드만수주공단지98 버스전용차로위반고정형CCTV
149212021280002021-06-28 18:2001 승용차렉서스 ES300h부평GM자동차앞98 버스전용차로위반고정형CCTV
단속년도자치단체단속일시차종차명단속장소단속구분단속방법
16302021280002021-01-23 18:5201 승용차K5관교동 롯데백화점(터미널점)앞(전일제)98 버스전용차로위반고정형CCTV
46062021280002021-03-04 7:3001 승용차스타렉스장축9인(STAREX)간석동 백범로 부근98 버스전용차로위반차량형CCTV
366442021280002021-12-31 8:0101 승용차싼타페(SANTAFE)신흥동3가 인중로 부근98 버스전용차로위반차량형CCTV
312002021280002021-11-18 17:2001 승용차그랜저(GRANDEUR)인천교통공사앞98 버스전용차로위반고정형CCTV
29992021280002021-02-15 7:1601 승용차마세라티 기블리간석동 경인로 부근98 버스전용차로위반차량형CCTV
52482021280002021-03-11 17:1201 승용차BMW 520d간석레미안자이A98 버스전용차로위반고정형CCTV
212932021280002021-08-30 18:0201 승용차A6 3.0 TFSI Quattro간석동 구월로 부근98 버스전용차로위반차량형CCTV
474542022280002022-04-15 19:4201 승용차K3인천교통공사앞98 버스전용차로위반고정형CCTV
596262022280002022-02-21 16:1001 승용차말리부 1-5 TURBO관교동 롯데백화점(터미널점)앞(전일제)98 버스전용차로위반고정형CCTV
1822021280002021-01-05 18:1401 승용차아반떼(AVANTE)부평GM자동차앞98 버스전용차로위반고정형CCTV

Duplicate rows

Most frequently occurring

단속년도자치단체단속일시차종차명단속장소단속구분단속방법# duplicates
02021280002021-01-11 17:3501 승용차쏘나타(SONATA)구월동 인하로507번길 부근98 버스전용차로위반차량형CCTV2
12021280002021-01-13 17:1101 승용차쏘나타(SONATA)구월동 인하로507번길 부근98 버스전용차로위반차량형CCTV2
22021280002021-01-19 19:5501 승용차쏘나타(SONATA)구월동 인하로 부근98 버스전용차로위반차량형CCTV2
32021280002021-02-25 17:5903 화물차(4t 이하)다마스밴도화동 경인로 부근98 버스전용차로위반차량형CCTV2
42021280002021-04-30 13:4401 승용차쏘나타(SONATA)구월동 인하로 부근98 버스전용차로위반차량형CCTV2
52021280002021-06-02 10:1601 승용차쏘나타(SONATA)구월동 인하로507번길 부근98 버스전용차로위반차량형CCTV2
62021280002021-06-16 10:1901 승용차쏘나타(SONATA)구월동 인하로507번길 부근98 버스전용차로위반차량형CCTV2
72021280002021-08-20 19:4101 승용차쏘나타(SONATA)구월동 인하로 부근98 버스전용차로위반차량형CCTV2
82021280002021-09-09 19:5301 승용차쏘나타(SONATA)인하로부근98 버스전용차로위반버스탑재형(SIDE)2
92021280002021-09-25 13:4701 승용차K5인하로부근98 버스전용차로위반버스탑재형(SIDE)2