Overview

Dataset statistics

Number of variables12
Number of observations5312
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows10
Duplicate rows (%)0.2%
Total size in memory513.7 KiB
Average record size in memory99.0 B

Variable types

DateTime1
Categorical7
Text3
Numeric1

Dataset

Description부천시 버스전용차로통행위반 과태료 정보로 2021.8 .~ 2022.7. 기간동안의 단속일시, 단속구분, 차량구분, 차명, 부과본세, 처리상태, 자료구분 등을 제공합니다.
URLhttps://www.data.go.kr/data/15064264/fileData.do

Alerts

Dataset has 10 (0.2%) duplicate rowsDuplicates
단속조 is highly overall correlated with 단속구분_출력High correlation
단속구분_출력 is highly overall correlated with 단속조High correlation
처리상태 is highly overall correlated with 자료구분High correlation
자료구분 is highly overall correlated with 처리상태High correlation
위반법규 is highly imbalanced (69.4%)Imbalance
차량구분 is highly imbalanced (91.6%)Imbalance
부과본세 is highly imbalanced (81.9%)Imbalance
자료구분 is highly imbalanced (83.1%)Imbalance
사진매수 is highly imbalanced (99.7%)Imbalance

Reproduction

Analysis started2023-12-12 06:24:09.303142
Analysis finished2023-12-12 06:24:10.722533
Duration1.42 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속일시
Date

Distinct4530
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
Minimum2022-08-01 07:18:51
Maximum2023-05-31 20:04:01
2023-12-12T15:24:10.823012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:24:10.997660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반법규
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
버스전용차로위반
4773 
버스전용차선위반
 
293
<NA>
 
183
전용차로위반
 
63

Length

Max length8
Median length8
Mean length7.8384789
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
버스전용차로위반 4773
89.9%
버스전용차선위반 293
 
5.5%
<NA> 183
 
3.4%
전용차로위반 63
 
1.2%

Length

2023-12-12T15:24:11.228184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:11.414489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
버스전용차로위반 4773
89.9%
버스전용차선위반 293
 
5.5%
na 183
 
3.4%
전용차로위반 63
 
1.2%

단속구분_출력
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
고정형CCTV
2968 
시민신고웹
2343 
일반도보
 
1

Length

Max length7
Median length7
Mean length6.1172816
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
고정형CCTV 2968
55.9%
시민신고웹 2343
44.1%
일반도보 1
 
< 0.1%

Length

2023-12-12T15:24:11.571697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:11.691252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형cctv 2968
55.9%
시민신고웹 2343
44.1%
일반도보 1
 
< 0.1%

차량구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
일반
5256 
중기
 
56

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 5256
98.9%
중기 56
 
1.1%

Length

2023-12-12T15:24:11.822354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:11.952449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 5256
98.9%
중기 56
 
1.1%

차명
Text

Distinct618
Distinct (%)11.6%
Missing3
Missing (%)0.1%
Memory size41.6 KiB
2023-12-12T15:24:12.213900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length31
Mean length9.3004332
Min length2

Characters and Unicode

Total characters49376
Distinct characters299
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique290 ?
Unique (%)5.5%

Sample

1st row트레일블레이저 1.35 TURBO FWD
2nd rowSM5
3rd rowSM5
4th row렉스턴스포츠
5th row포터Ⅱ (PORTERⅡ)
ValueCountFrequency (%)
쏘나타(sonata 347
 
4.1%
k5 216
 
2.6%
그랜저(grandeur 204
 
2.4%
아반떼(avante 198
 
2.3%
싼타페(santafe 172
 
2.0%
쏘렌토 170
 
2.0%
하이브리드 166
 
2.0%
카니발 158
 
1.9%
스포티지 155
 
1.8%
모닝 141
 
1.7%
Other values (630) 6507
77.2%
2023-12-12T15:24:12.735171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3129
 
6.3%
A 2714
 
5.5%
( 2030
 
4.1%
) 2030
 
4.1%
N 1838
 
3.7%
E 1752
 
3.5%
T 1731
 
3.5%
R 1576
 
3.2%
S 1399
 
2.8%
O 1050
 
2.1%
Other values (289) 30127
61.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 19370
39.2%
Other Letter 15253
30.9%
Decimal Number 3387
 
6.9%
Space Separator 3129
 
6.3%
Lowercase Letter 3031
 
6.1%
Open Punctuation 2030
 
4.1%
Close Punctuation 2030
 
4.1%
Letter Number 579
 
1.2%
Other Punctuation 449
 
0.9%
Dash Punctuation 97
 
0.2%
Other values (2) 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 991
 
6.5%
타 736
 
4.8%
쏘 618
 
4.1%
이 493
 
3.2%
드 480
 
3.1%
포 476
 
3.1%
나 476
 
3.1%
리 461
 
3.0%
그 442
 
2.9%
랜 440
 
2.9%
Other values (218) 9640
63.2%
Uppercase Letter
ValueCountFrequency (%)
A 2714
14.0%
N 1838
 
9.5%
E 1752
 
9.0%
T 1731
 
8.9%
R 1576
 
8.1%
S 1399
 
7.2%
O 1050
 
5.4%
D 852
 
4.4%
G 704
 
3.6%
I 663
 
3.4%
Other values (16) 5091
26.3%
Lowercase Letter
ValueCountFrequency (%)
e 508
16.8%
r 317
10.5%
i 253
 
8.3%
o 242
 
8.0%
d 214
 
7.1%
t 210
 
6.9%
a 196
 
6.5%
n 145
 
4.8%
u 137
 
4.5%
c 133
 
4.4%
Other values (15) 676
22.3%
Decimal Number
ValueCountFrequency (%)
0 795
23.5%
5 570
16.8%
2 428
12.6%
3 412
12.2%
1 387
11.4%
4 254
 
7.5%
6 188
 
5.6%
7 172
 
5.1%
8 153
 
4.5%
9 27
 
0.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 456
78.8%
Ⅲ 123
 
21.2%
Space Separator
ValueCountFrequency (%)
3129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2030
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2030
100.0%
Other Punctuation
ValueCountFrequency (%)
. 449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Math Symbol
ValueCountFrequency (%)
+ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22980
46.5%
Hangul 15253
30.9%
Common 11143
22.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 991
 
6.5%
타 736
 
4.8%
쏘 618
 
4.1%
이 493
 
3.2%
드 480
 
3.1%
포 476
 
3.1%
나 476
 
3.1%
리 461
 
3.0%
그 442
 
2.9%
랜 440
 
2.9%
Other values (218) 9640
63.2%
Latin
ValueCountFrequency (%)
A 2714
 
11.8%
N 1838
 
8.0%
E 1752
 
7.6%
T 1731
 
7.5%
R 1576
 
6.9%
S 1399
 
6.1%
O 1050
 
4.6%
D 852
 
3.7%
G 704
 
3.1%
I 663
 
2.9%
Other values (43) 8701
37.9%
Common
ValueCountFrequency (%)
3129
28.1%
( 2030
18.2%
) 2030
18.2%
0 795
 
7.1%
5 570
 
5.1%
. 449
 
4.0%
2 428
 
3.8%
3 412
 
3.7%
1 387
 
3.5%
4 254
 
2.3%
Other values (8) 659
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33543
67.9%
Hangul 15253
30.9%
Number Forms 579
 
1.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3129
 
9.3%
A 2714
 
8.1%
( 2030
 
6.1%
) 2030
 
6.1%
N 1838
 
5.5%
E 1752
 
5.2%
T 1731
 
5.2%
R 1576
 
4.7%
S 1399
 
4.2%
O 1050
 
3.1%
Other values (58) 14294
42.6%
Hangul
ValueCountFrequency (%)
스 991
 
6.5%
타 736
 
4.8%
쏘 618
 
4.1%
이 493
 
3.2%
드 480
 
3.1%
포 476
 
3.1%
나 476
 
3.1%
리 461
 
3.0%
그 442
 
2.9%
랜 440
 
2.9%
Other values (218) 9640
63.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 456
78.8%
Ⅲ 123
 
21.2%
None
ValueCountFrequency (%)
３ 1
100.0%

부과본세
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
50000
4893 
60000
 
401
25000
 
16
40000
 
1
<NA>
 
1

Length

Max length5
Median length5
Mean length4.9998117
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row50000
2nd row50000
3rd row50000
4th row50000
5th row50000

Common Values

ValueCountFrequency (%)
50000 4893
92.1%
60000 401
 
7.5%
25000 16
 
0.3%
40000 1
 
< 0.1%
<NA> 1
 
< 0.1%

Length

2023-12-12T15:24:12.872829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:12.969435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50000 4893
92.1%
60000 401
 
7.5%
25000 16
 
0.3%
40000 1
 
< 0.1%
na 1
 
< 0.1%

처리상태
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
자납납부
3406 
부과납부
506 
부과
 
329
압류
 
281
감액(부과취소)
 
161
Other values (12)
629 

Length

Max length10
Median length4
Mean length4.0041416
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row독촉납부
2nd row자납납부
3rd row자납납부
4th row자납납부
5th row압류

Common Values

ValueCountFrequency (%)
자납납부 3406
64.1%
부과납부 506
 
9.5%
부과 329
 
6.2%
압류 281
 
5.3%
감액(부과취소) 161
 
3.0%
자납부과 137
 
2.6%
독촉납부 120
 
2.3%
의견진술수용 119
 
2.2%
압류납부(압류해제) 89
 
1.7%
독촉 69
 
1.3%
Other values (7) 95
 
1.8%

Length

2023-12-12T15:24:13.124423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
자납납부 3406
64.1%
부과납부 506
 
9.5%
부과 329
 
6.2%
압류 281
 
5.3%
감액(부과취소 161
 
3.0%
자납부과 137
 
2.6%
독촉납부 120
 
2.3%
의견진술수용 119
 
2.2%
압류납부(압류해제 89
 
1.7%
독촉 69
 
1.3%
Other values (7) 95
 
1.8%

사전통지발송일
Text

Distinct164
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
2023-12-12T15:24:13.460727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9983057
Min length1

Characters and Unicode

Total characters53111
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)0.6%

Sample

1st row2022-11-04
2nd row2022-10-27
3rd row2022-10-27
4th row2022-10-06
5th row2022-10-27
ValueCountFrequency (%)
2023-03-30 151
 
2.8%
2023-04-06 138
 
2.6%
2022-10-20 134
 
2.5%
2022-09-16 133
 
2.5%
2022-10-27 118
 
2.2%
2023-03-20 105
 
2.0%
2023-04-24 103
 
1.9%
2023-03-09 100
 
1.9%
2023-05-15 96
 
1.8%
2022-11-11 94
 
1.8%
Other values (154) 4140
77.9%
2023-12-12T15:24:13.972680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16011
30.1%
0 11845
22.3%
- 10622
20.0%
1 5010
 
9.4%
3 4572
 
8.6%
5 1207
 
2.3%
4 1092
 
2.1%
9 849
 
1.6%
6 762
 
1.4%
8 578
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42489
80.0%
Dash Punctuation 10622
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16011
37.7%
0 11845
27.9%
1 5010
 
11.8%
3 4572
 
10.8%
5 1207
 
2.8%
4 1092
 
2.6%
9 849
 
2.0%
6 762
 
1.8%
8 578
 
1.4%
7 563
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 10622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53111
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16011
30.1%
0 11845
22.3%
- 10622
20.0%
1 5010
 
9.4%
3 4572
 
8.6%
5 1207
 
2.3%
4 1092
 
2.1%
9 849
 
1.6%
6 762
 
1.4%
8 578
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16011
30.1%
0 11845
22.3%
- 10622
20.0%
1 5010
 
9.4%
3 4572
 
8.6%
5 1207
 
2.3%
4 1092
 
2.1%
9 849
 
1.6%
6 762
 
1.4%
8 578
 
1.1%

사전통지납기일
Text

Distinct142
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
2023-12-12T15:24:14.293756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9983057
Min length1

Characters and Unicode

Total characters53111
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)0.5%

Sample

1st row2022-11-21
2nd row2022-11-11
3rd row2022-11-11
4th row2022-10-24
5th row2022-11-11
ValueCountFrequency (%)
2023-04-13 151
 
2.8%
2023-05-22 151
 
2.8%
2023-04-20 138
 
2.6%
2022-09-30 133
 
2.5%
2022-11-04 133
 
2.5%
2022-11-25 123
 
2.3%
2022-11-11 120
 
2.3%
2023-04-03 108
 
2.0%
2023-05-08 107
 
2.0%
2023-03-24 100
 
1.9%
Other values (132) 4048
76.2%
2023-12-12T15:24:14.791387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16083
30.3%
0 11509
21.7%
- 10622
20.0%
1 4998
 
9.4%
3 4676
 
8.8%
4 1451
 
2.7%
5 1222
 
2.3%
6 959
 
1.8%
8 687
 
1.3%
9 569
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 42489
80.0%
Dash Punctuation 10622
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16083
37.9%
0 11509
27.1%
1 4998
 
11.8%
3 4676
 
11.0%
4 1451
 
3.4%
5 1222
 
2.9%
6 959
 
2.3%
8 687
 
1.6%
9 569
 
1.3%
7 335
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 10622
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53111
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 16083
30.3%
0 11509
21.7%
- 10622
20.0%
1 4998
 
9.4%
3 4676
 
8.8%
4 1451
 
2.7%
5 1222
 
2.3%
6 959
 
1.8%
8 687
 
1.3%
9 569
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16083
30.3%
0 11509
21.7%
- 10622
20.0%
1 4998
 
9.4%
3 4676
 
8.8%
4 1451
 
2.7%
5 1222
 
2.3%
6 959
 
1.8%
8 687
 
1.3%
9 569
 
1.1%

자료구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
기타
5046 
기발송
 
146
의견진술
 
119
차적미처리
 
1

Length

Max length5
Median length2
Mean length2.0728539
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 5046
95.0%
기발송 146
 
2.7%
의견진술 119
 
2.2%
차적미처리 1
 
< 0.1%

Length

2023-12-12T15:24:14.959415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:15.101236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 5046
95.0%
기발송 146
 
2.7%
의견진술 119
 
2.2%
차적미처리 1
 
< 0.1%

단속조
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean505.12425
Minimum2
Maximum905
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.8 KiB
2023-12-12T15:24:15.216156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median901
Q3902
95-th percentile905
Maximum905
Range903
Interquartile range (IQR)900

Descriptive statistics

Standard deviation447.16161
Coefficient of variation (CV)0.88525074
Kurtosis-1.9447131
Mean505.12425
Median Absolute Deviation (MAD)4
Skewness-0.23662326
Sum2683220
Variance199953.51
MonotonicityIncreasing
2023-12-12T15:24:15.328369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2 2344
44.1%
901 1141
21.5%
902 826
 
15.5%
905 690
 
13.0%
904 156
 
2.9%
903 155
 
2.9%
ValueCountFrequency (%)
2 2344
44.1%
901 1141
21.5%
902 826
 
15.5%
903 155
 
2.9%
904 156
 
2.9%
905 690
 
13.0%
ValueCountFrequency (%)
905 690
 
13.0%
904 156
 
2.9%
903 155
 
2.9%
902 826
 
15.5%
901 1141
21.5%
2 2344
44.1%

사진매수
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size41.6 KiB
2
5311 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
2 5311
> 99.9%
1 1
 
< 0.1%

Length

2023-12-12T15:24:15.465372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:24:15.570278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 5311
> 99.9%
1 1
 
< 0.1%

Interactions

2023-12-12T15:24:10.226650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:24:15.639213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위반법규단속구분_출력차량구분부과본세처리상태자료구분단속조사진매수
위반법규1.0000.4520.0100.1620.1290.0750.1500.000
단속구분_출력0.4521.0000.0670.0000.1470.0841.0000.000
차량구분0.0100.0671.0000.5290.0450.0000.1720.000
부과본세0.1620.0000.5291.0000.1660.0730.0070.000
처리상태0.1290.1470.0450.1661.0000.9510.1380.000
자료구분0.0750.0840.0000.0730.9511.0000.1730.000
단속조0.1501.0000.1720.0070.1380.1731.0000.000
사진매수0.0000.0000.0000.0000.0000.0000.0001.000
2023-12-12T15:24:15.766172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자료구분사진매수처리상태단속구분_출력부과본세위반법규차량구분
자료구분1.0000.0000.8640.0800.0680.0710.000
사진매수0.0001.0000.0000.0000.0000.0000.000
처리상태0.8640.0001.0000.0790.0930.0690.040
단속구분_출력0.0800.0000.0791.0000.0000.1750.111
부과본세0.0680.0000.0930.0001.0000.1540.360
위반법규0.0710.0000.0690.1750.1541.0000.017
차량구분0.0000.0000.0400.1110.3600.0171.000
2023-12-12T15:24:15.881508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속조위반법규단속구분_출력차량구분부과본세처리상태자료구분사진매수
단속조1.0000.2481.0000.1100.0040.1240.1150.000
위반법규0.2481.0000.1750.0170.1540.0690.0710.000
단속구분_출력1.0000.1751.0000.1110.0000.0790.0800.000
차량구분0.1100.0170.1111.0000.3600.0400.0000.000
부과본세0.0040.1540.0000.3601.0000.0930.0680.000
처리상태0.1240.0690.0790.0400.0931.0000.8640.000
자료구분0.1150.0710.0800.0000.0680.8641.0000.000
사진매수0.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T15:24:10.373877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:24:10.628931image/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

단속일시위반법규단속구분_출력차량구분차명부과본세처리상태사전통지발송일사전통지납기일자료구분단속조사진매수
02022-10-07 07:51버스전용차로위반시민신고웹일반트레일블레이저 1.35 TURBO FWD50000독촉납부2022-11-042022-11-21기타22
12022-10-04 09:00버스전용차로위반시민신고웹일반SM550000자납납부2022-10-272022-11-11기타22
22022-09-30 08:45버스전용차로위반시민신고웹일반SM550000자납납부2022-10-272022-11-11기타22
32022-09-29 08:46버스전용차로위반시민신고웹일반렉스턴스포츠50000자납납부2022-10-062022-10-24기타22
42022-09-23 08:46버스전용차로위반시민신고웹일반포터Ⅱ (PORTERⅡ)50000압류2022-10-272022-11-11기타22
52022-10-05 08:39버스전용차로위반시민신고웹일반포터Ⅱ (PORTERⅡ)50000압류2022-10-272022-11-11기타22
62022-09-27 08:50버스전용차로위반시민신고웹일반투싼(TUCSON)50000자납납부2022-10-062022-10-24기타22
72022-09-29 08:46버스전용차로위반시민신고웹일반그랜드 카니발60000압류2022-10-062022-10-24기타22
82022-09-27 08:50버스전용차로위반시민신고웹일반아반떼 (AVANTE)50000압류예정2022-10-272022-11-11기타22
92022-10-06 08:19버스전용차로위반시민신고웹일반쏘렌토50000자납납부2022-10-122022-10-26기타22
단속일시위반법규단속구분_출력차량구분차명부과본세처리상태사전통지발송일사전통지납기일자료구분단속조사진매수
53022023-01-15 12:28:24<NA>고정형CCTV일반쏘나타(SONATA)50000자납납부2023-01-192023-02-06기타9052
53032023-05-17 13:56:32<NA>고정형CCTV일반포터Ⅱ (PORTERⅡ)50000자납부과2023-05-182023-06-01기발송9052
53042023-03-12 11:59:25<NA>고정형CCTV일반쏘나타(SONATA)50000자납납부2023-03-132023-03-28기타9052
53052023-05-07 13:22:42<NA>고정형CCTV일반렉서스 RX450h50000부과2023-05-222023-06-05기타9052
53062023-03-19 11:12:44<NA>고정형CCTV일반K550000자납납부2023-03-202023-04-03기타9052
53072022-11-02 12:09:06<NA>고정형CCTV일반스파크 1.0 DOHC50000자납납부2022-11-242022-12-12기타9052
53082023-03-13 16:52:24<NA>고정형CCTV일반K750000자납납부2023-03-202023-04-03기타9052
53092023-01-14 10:19:16<NA>고정형CCTV일반Explorer 2.350000자납납부2023-01-192023-02-06기타9052
53102023-01-15 10:05:01<NA>고정형CCTV일반제네시스(GENESIS)50000자납납부2023-02-082023-02-23기타9052
53112023-01-14 20:50:21<NA>고정형CCTV일반짚그랜드체로키50000자납납부2023-01-192023-02-06기타9052

Duplicate rows

Most frequently occurring

단속일시위반법규단속구분_출력차량구분차명부과본세처리상태사전통지발송일사전통지납기일자료구분단속조사진매수# duplicates
82023-05-04 13:13버스전용차로위반시민신고웹일반포터Ⅱ내장탑차 (PORTER Ⅱ)50000자납납부2023-05-112023-05-25기타223
02022-09-08 17:50버스전용차로위반시민신고웹일반싼타페(SANTAFE)50000자납납부2022-10-072022-10-24기타222
12022-09-19 08:39버스전용차로위반시민신고웹일반포터Ⅱ (PORTERⅡ)50000자납납부2022-09-272022-10-11기타222
22022-10-19 08:58버스전용차로위반시민신고웹중기덤프트럭60000감액(부과취소)2022-10-272022-11-11기타222
32022-10-19 08:58버스전용차로위반시민신고웹중기덤프트럭60000압류2022-10-272022-11-11기타222
42023-02-20 09:45버스전용차로위반시민신고웹일반봉고Ⅲ 1톤50000자납납부2023-03-092023-03-24기타222
52023-03-21 18:21버스전용차로위반시민신고웹일반팰리세이드(PALISADE)50000자납납부2023-03-302023-04-13기타222
62023-03-27 07:28버스전용차로위반시민신고웹일반아반떼(AVANTE)50000자납납부2023-03-302023-04-13기타222
72023-04-20 08:37버스전용차로위반시민신고웹일반쏘나타(SONATA)50000자납납부2023-04-272023-05-11기타222
92023-05-15 06:58버스전용차로위반시민신고웹일반쏘나타(SONATA)50000자납납부2023-05-222023-06-05기타222