Overview

Dataset statistics

Number of variables6
Number of observations3889
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory182.4 KiB
Average record size in memory48.0 B

Variable types

Categorical5
DateTime1

Dataset

Description광주광역시 서구 교통위반과태료이의신청현황의 단속구분, 단속일시, 위반내용, 심의결과, 진술유형, 처리상태 등에 대한 현황입니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15090266/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
심의결과 is highly overall correlated with 처리상태High correlation
처리상태 is highly overall correlated with 심의결과High correlation
위반내용 is highly imbalanced (64.4%)Imbalance
심의결과 is highly imbalanced (84.8%)Imbalance
진술유형 is highly imbalanced (50.0%)Imbalance
처리상태 is highly imbalanced (88.9%)Imbalance

Reproduction

Analysis started2024-03-14 23:49:32.055569
Analysis finished2024-03-14 23:49:33.876312
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속구분
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
고정형CCTV
2475 
안전신문고
940 
주행형CCTV
456 
버스장착형CCTV
 
15
일반도보
 
3

Length

Max length9
Median length7
Mean length6.5219851
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고정형CCTV 2475
63.6%
안전신문고 940
 
24.2%
주행형CCTV 456
 
11.7%
버스장착형CCTV 15
 
0.4%
일반도보 3
 
0.1%

Length

2024-03-15T08:49:34.187139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:49:34.587142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형cctv 2475
63.6%
안전신문고 940
 
24.2%
주행형cctv 456
 
11.7%
버스장착형cctv 15
 
0.4%
일반도보 3
 
0.1%

단속일시
Date

Distinct3885
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
Minimum2022-11-23 09:44:32
Maximum2023-12-26 15:34:01
2024-03-15T08:49:35.002124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T08:49:35.460731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반내용
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
32조위반
3028 
횡단보도
 
229
보도주차
 
175
소방시설주변 절대금지
 
157
교차로 모퉁이
 
102
Other values (11)
 
198

Length

Max length11
Median length5
Mean length5.1542813
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row32조위반
2nd row보도주차
3rd row32조위반
4th row32조위반
5th row보도주차

Common Values

ValueCountFrequency (%)
32조위반 3028
77.9%
횡단보도 229
 
5.9%
보도주차 175
 
4.5%
소방시설주변 절대금지 157
 
4.0%
교차로 모퉁이 102
 
2.6%
황색실선 40
 
1.0%
버스정류장 35
 
0.9%
모퉁이 33
 
0.8%
대각주차 29
 
0.7%
34조위반 14
 
0.4%
Other values (6) 47
 
1.2%

Length

2024-03-15T08:49:35.831011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
32조위반 3028
73.0%
횡단보도 229
 
5.5%
보도주차 175
 
4.2%
소방시설주변 157
 
3.8%
절대금지 157
 
3.8%
모퉁이 135
 
3.3%
교차로 102
 
2.5%
황색실선 40
 
1.0%
버스정류장 35
 
0.8%
대각주차 29
 
0.7%
Other values (7) 61
 
1.5%

심의결과
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
수용
3706 
경찰통보
 
70
미수용
 
70
자진취하
 
37
접수
 
6

Length

Max length4
Median length2
Mean length2.0730265
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수용 3706
95.3%
경찰통보 70
 
1.8%
미수용 70
 
1.8%
자진취하 37
 
1.0%
접수 6
 
0.2%

Length

2024-03-15T08:49:36.292079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T08:49:36.600604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수용 3706
95.3%
경찰통보 70
 
1.8%
미수용 70
 
1.8%
자진취하 37
 
1.0%
접수 6
 
0.2%

진술유형
Categorical

IMBALANCE 

Distinct31
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
기타
1711 
동일장소반복단속
870 
물건상하차
669 
공무수행
 
148
장애인관련
 
78
Other values (26)
413 

Length

Max length10
Median length9
Mean length4.390846
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
기타 1711
44.0%
동일장소반복단속 870
22.4%
물건상하차 669
 
17.2%
공무수행 148
 
3.8%
장애인관련 78
 
2.0%
공공업무수행 60
 
1.5%
장애인의승하차도움 58
 
1.5%
고장차량 57
 
1.5%
교통사고차량 52
 
1.3%
모범운전 43
 
1.1%
Other values (21) 143
 
3.7%

Length

2024-03-15T08:49:36.848588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타 1711
43.9%
동일장소반복단속 870
22.3%
물건상하차 669
 
17.1%
공무수행 148
 
3.8%
장애인관련 78
 
2.0%
공공업무수행 60
 
1.5%
장애인의승하차도움 58
 
1.5%
고장차량 57
 
1.5%
교통사고차량 52
 
1.3%
모범운전 43
 
1.1%
Other values (22) 155
 
4.0%

처리상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size30.5 KiB
의견진술수용
3706 
경찰서이첩
 
70
자납납부
 
42
부과납부
 
25
자납부과
 
10
Other values (7)
 
36

Length

Max length8
Median length6
Mean length5.9213165
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
의견진술수용 3706
95.3%
경찰서이첩 70
 
1.8%
자납납부 42
 
1.1%
부과납부 25
 
0.6%
자납부과 10
 
0.3%
압류 9
 
0.2%
부과 9
 
0.2%
의견진술접수 6
 
0.2%
독촉납부 5
 
0.1%
감액(부과취소) 4
 
0.1%
Other values (2) 3
 
0.1%

Length

2024-03-15T08:49:37.110023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의견진술수용 3706
95.3%
경찰서이첩 70
 
1.8%
자납납부 42
 
1.1%
부과납부 25
 
0.6%
자납부과 10
 
0.3%
압류 9
 
0.2%
부과 9
 
0.2%
의견진술접수 6
 
0.2%
독촉납부 5
 
0.1%
감액(부과취소 4
 
0.1%
Other values (2) 3
 
0.1%

Correlations

2024-03-15T08:49:37.262919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속구분위반내용심의결과진술유형처리상태
단속구분1.0000.7130.0750.2940.106
위반내용0.7131.0000.0700.1310.124
심의결과0.0750.0701.0000.6300.984
진술유형0.2940.1310.6301.0000.532
처리상태0.1060.1240.9840.5321.000
2024-03-15T08:49:37.437084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
심의결과처리상태단속구분진술유형위반내용
심의결과1.0000.9760.0280.3550.036
처리상태0.9761.0000.0580.2020.044
단속구분0.0280.0581.0000.1420.463
진술유형0.3550.2020.1421.0000.038
위반내용0.0360.0440.4630.0381.000
2024-03-15T08:49:37.701835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속구분위반내용심의결과진술유형처리상태
단속구분1.0000.4630.0280.1420.058
위반내용0.4631.0000.0360.0380.044
심의결과0.0280.0361.0000.3550.976
진술유형0.1420.0380.3551.0000.202
처리상태0.0580.0440.9760.2021.000

Missing values

2024-03-15T08:49:33.247555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T08:49:33.669932image/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

단속구분단속일시위반내용심의결과진술유형처리상태
0고정형CCTV2022-12-08 08:20:3832조위반수용응급환자의견진술수용
1안전신문고2022-11-24 16:56:00보도주차수용기타의견진술수용
2고정형CCTV2022-12-07 11:36:3132조위반수용장애인관련의견진술수용
3고정형CCTV2022-12-15 11:14:1332조위반수용기타의견진술수용
4안전신문고2022-12-22 10:40:07보도주차수용기타의견진술수용
5안전신문고2022-12-19 13:38:40소방시설주변 절대금지수용기타의견진술수용
6안전신문고2022-12-26 12:44:19횡단보도수용기타의견진술수용
7고정형CCTV2022-12-14 15:15:4932조위반수용기타의견진술수용
8고정형CCTV2023-01-14 14:56:4032조위반수용기타의견진술수용
9고정형CCTV2023-01-04 10:41:5432조위반수용기타의견진술수용
단속구분단속일시위반내용심의결과진술유형처리상태
3879고정형CCTV2023-12-11 08:35:1532조위반수용동일장소반복단속의견진술수용
3880고정형CCTV2023-12-18 17:39:1832조위반수용응급환자의견진술수용
3881고정형CCTV2023-11-06 14:52:2532조위반미수용기타자납부과
3882안전신문고2023-11-08 20:42:21보도주차수용동일장소반복단속의견진술수용
3883안전신문고2023-11-11 18:50:46보도주차수용동일장소반복단속의견진술수용
3884안전신문고2023-11-14 21:49:16보도주차수용동일장소반복단속의견진술수용
3885안전신문고2023-11-24 21:14:41횡단보도수용동일장소반복단속의견진술수용
3886안전신문고2023-11-25 21:11:39보도주차수용동일장소반복단속의견진술수용
3887안전신문고2023-12-09 22:57:33횡단보도수용동일장소반복단속의견진술수용
3888고정형CCTV2023-11-24 15:46:5532조위반수용동일장소반복단속의견진술수용

Duplicate rows

Most frequently occurring

단속구분단속일시위반내용심의결과진술유형처리상태# duplicates
0안전신문고2023-08-23 13:05:2032조위반수용기타의견진술수용2