Overview

Dataset statistics

Number of variables7
Number of observations1141
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory63.6 KiB
Average record size in memory57.1 B

Variable types

DateTime2
Categorical3
Text1
Numeric1

Dataset

Description광주광역시 서구 교통위반과태료면제차량의 서손일자, 서손사유, 단속일시, 단속구분, 단속지역에 대한 현황입니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15090263/fileData.do

Alerts

서손사유 is highly overall correlated with 단속구분High correlation
단속구분 is highly overall correlated with 서손사유 and 1 other fieldsHigh correlation
단속지역 is highly overall correlated with 단속구분High correlation

Reproduction

Analysis started2024-03-14 14:28:39.145153
Analysis finished2024-03-14 14:28:40.487868
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서손일자
Date

Distinct196
Distinct (%)17.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum2023-01-02 00:00:00
Maximum2023-12-22 00:00:00
2024-03-14T23:28:40.674378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:28:41.081630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

서손사유
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
행정착오
367 
2시간이내
295 
기타
200 
자진이동
95 
공무수행
81 
Other values (9)
103 

Length

Max length6
Median length4
Mean length3.9114812
Min length2

Unique

Unique4 ?
Unique (%)0.4%

Sample

1st row자진이동
2nd row기타
3rd row공무수행
4th row2시간이내
5th row기타

Common Values

ValueCountFrequency (%)
행정착오 367
32.2%
2시간이내 295
25.9%
기타 200
17.5%
자진이동 95
 
8.3%
공무수행 81
 
7.1%
착오부과 46
 
4.0%
재판독 19
 
1.7%
부과취소 13
 
1.1%
번호판독불가 11
 
1.0%
이중등록 10
 
0.9%
Other values (4) 4
 
0.4%

Length

2024-03-14T23:28:41.408372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
행정착오 367
32.2%
2시간이내 295
25.9%
기타 200
17.5%
자진이동 95
 
8.3%
공무수행 81
 
7.1%
착오부과 46
 
4.0%
재판독 19
 
1.7%
부과취소 13
 
1.1%
번호판독불가 11
 
1.0%
이중등록 10
 
0.9%
Other values (4) 4
 
0.4%

단속일시
Date

Distinct1140
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
Minimum1998-03-12 00:00:00
Maximum2023-12-19 09:51:14
2024-03-14T23:28:41.760446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:28:42.208746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
고정형CCTV
811 
주행형CCTV
194 
안전신문고
133 
버스장착형CCTV
 
2
일반도보
 
1

Length

Max length9
Median length7
Mean length6.7677476
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
고정형CCTV 811
71.1%
주행형CCTV 194
 
17.0%
안전신문고 133
 
11.7%
버스장착형CCTV 2
 
0.2%
일반도보 1
 
0.1%

Length

2024-03-14T23:28:42.645748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:28:43.205754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형cctv 811
71.1%
주행형cctv 194
 
17.0%
안전신문고 133
 
11.7%
버스장착형cctv 2
 
0.2%
일반도보 1
 
0.1%

단속지역
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
치평동
557 
풍암동
188 
화정동
137 
농성동
67 
쌍촌동
 
54
Other values (12)
138 

Length

Max length4
Median length3
Mean length2.9815951
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row양동
2nd row양동
3rd row화정동
4th row양동
5th row쌍촌동

Common Values

ValueCountFrequency (%)
치평동 557
48.8%
풍암동 188
 
16.5%
화정동 137
 
12.0%
농성동 67
 
5.9%
쌍촌동 54
 
4.7%
동천동 32
 
2.8%
금호동 31
 
2.7%
양동 23
 
2.0%
광천동 22
 
1.9%
매월동 13
 
1.1%
Other values (7) 17
 
1.5%

Length

2024-03-14T23:28:43.619733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
치평동 557
48.8%
풍암동 188
 
16.5%
화정동 137
 
12.0%
농성동 67
 
5.9%
쌍촌동 54
 
4.7%
동천동 32
 
2.8%
금호동 31
 
2.7%
양동 23
 
2.0%
광천동 22
 
1.9%
매월동 13
 
1.1%
Other values (7) 17
 
1.5%

단속장소
Text

Distinct251
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2024-03-14T23:28:44.929390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length10.617003
Min length3

Characters and Unicode

Total characters12114
Distinct characters232
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique138 ?
Unique (%)12.1%

Sample

1st row양동치안센터
2nd row양동치안센터
3rd row염주사거리
4th row경열로121번길부근
5th row상무대로부근
ValueCountFrequency (%)
부근 168
 
7.6%
치평동 149
 
6.7%
운리중학교 125
 
5.7%
시청로50번길 112
 
5.1%
상무나이트 110
 
5.0%
앞 109
 
4.9%
농성동 57
 
2.6%
사거리 54
 
2.4%
시청로 43
 
1.9%
치평동람바다사거리 39
 
1.8%
Other values (291) 1244
56.3%
2024-03-14T23:28:46.634161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1070
 
8.8%
로 461
 
3.8%
동 424
 
3.5%
1 362
 
3.0%
근 315
 
2.6%
부 315
 
2.6%
) 304
 
2.5%
( 304
 
2.5%
상 303
 
2.5%
리 300
 
2.5%
Other values (222) 7956
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8732
72.1%
Decimal Number 1592
 
13.1%
Space Separator 1070
 
8.8%
Close Punctuation 304
 
2.5%
Open Punctuation 304
 
2.5%
Dash Punctuation 58
 
0.5%
Uppercase Letter 53
 
0.4%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 461
 
5.3%
동 424
 
4.9%
근 315
 
3.6%
부 315
 
3.6%
상 303
 
3.5%
리 300
 
3.4%
평 300
 
3.4%
무 279
 
3.2%
치 245
 
2.8%
시 221
 
2.5%
Other values (199) 5569
63.8%
Decimal Number
ValueCountFrequency (%)
1 362
22.7%
2 215
13.5%
0 199
12.5%
5 188
11.8%
3 131
 
8.2%
8 124
 
7.8%
4 120
 
7.5%
6 105
 
6.6%
7 74
 
4.6%
9 74
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 14
26.4%
S 13
24.5%
K 12
22.6%
Y 4
 
7.5%
C 4
 
7.5%
P 2
 
3.8%
T 2
 
3.8%
A 2
 
3.8%
Space Separator
ValueCountFrequency (%)
1070
100.0%
Close Punctuation
ValueCountFrequency (%)
) 304
100.0%
Open Punctuation
ValueCountFrequency (%)
( 304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8732
72.1%
Common 3329
 
27.5%
Latin 53
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 461
 
5.3%
동 424
 
4.9%
근 315
 
3.6%
부 315
 
3.6%
상 303
 
3.5%
리 300
 
3.4%
평 300
 
3.4%
무 279
 
3.2%
치 245
 
2.8%
시 221
 
2.5%
Other values (199) 5569
63.8%
Common
ValueCountFrequency (%)
1070
32.1%
1 362
 
10.9%
) 304
 
9.1%
( 304
 
9.1%
2 215
 
6.5%
0 199
 
6.0%
5 188
 
5.6%
3 131
 
3.9%
8 124
 
3.7%
4 120
 
3.6%
Other values (5) 312
 
9.4%
Latin
ValueCountFrequency (%)
B 14
26.4%
S 13
24.5%
K 12
22.6%
Y 4
 
7.5%
C 4
 
7.5%
P 2
 
3.8%
T 2
 
3.8%
A 2
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8732
72.1%
ASCII 3382
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1070
31.6%
1 362
 
10.7%
) 304
 
9.0%
( 304
 
9.0%
2 215
 
6.4%
0 199
 
5.9%
5 188
 
5.6%
3 131
 
3.9%
8 124
 
3.7%
4 120
 
3.5%
Other values (13) 365
 
10.8%
Hangul
ValueCountFrequency (%)
로 461
 
5.3%
동 424
 
4.9%
근 315
 
3.6%
부 315
 
3.6%
상 303
 
3.5%
리 300
 
3.4%
평 300
 
3.4%
무 279
 
3.2%
치 245
 
2.8%
시 221
 
2.5%
Other values (199) 5569
63.8%

단속원금
Real number (ℝ)

Distinct7
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45898.335
Minimum10000
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.2 KiB
2024-03-14T23:28:46.985442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile40000
Q140000
median40000
Q340000
95-th percentile120000
Maximum130000
Range120000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19788.447
Coefficient of variation (CV)0.43113649
Kurtosis9.3642335
Mean45898.335
Median Absolute Deviation (MAD)0
Skewness3.2664105
Sum52370000
Variance3.9158264 × 108
MonotonicityNot monotonic
2024-03-14T23:28:47.332621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
40000 1001
87.7%
120000 65
 
5.7%
50000 45
 
3.9%
80000 22
 
1.9%
10000 4
 
0.4%
130000 3
 
0.3%
90000 1
 
0.1%
ValueCountFrequency (%)
10000 4
 
0.4%
40000 1001
87.7%
50000 45
 
3.9%
80000 22
 
1.9%
90000 1
 
0.1%
120000 65
 
5.7%
130000 3
 
0.3%
ValueCountFrequency (%)
130000 3
 
0.3%
120000 65
 
5.7%
90000 1
 
0.1%
80000 22
 
1.9%
50000 45
 
3.9%
40000 1001
87.7%
10000 4
 
0.4%

Interactions

2024-03-14T23:28:39.592305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:28:47.564867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서손사유단속구분단속지역단속원금
서손사유1.0000.7890.7600.419
단속구분0.7891.0000.7640.097
단속지역0.7600.7641.0000.343
단속원금0.4190.0970.3431.000
2024-03-14T23:28:47.819357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속구분단속지역서손사유
단속구분1.0000.5240.561
단속지역0.5241.0000.378
서손사유0.5610.3781.000
2024-03-14T23:28:47.977390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속원금서손사유단속구분단속지역
단속원금1.0000.2040.0420.162
서손사유0.2041.0000.5610.378
단속구분0.0420.5611.0000.524
단속지역0.1620.3780.5241.000

Missing values

2024-03-14T23:28:39.951283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:28:40.334337image/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

서손일자서손사유단속일시단속구분단속지역단속장소단속원금
02023-01-31자진이동2023-01-28 17:23:05고정형CCTV양동양동치안센터50000
12023-01-17기타2023-01-16 17:39:23고정형CCTV양동양동치안센터40000
22023-05-26공무수행2023-05-10 16:21:17고정형CCTV화정동염주사거리50000
32023-12-202시간이내2023-12-12 15:00:12버스장착형CCTV양동경열로121번길부근40000
42023-01-06기타2023-01-03 15:23:28버스장착형CCTV쌍촌동상무대로부근40000
52023-01-31자진이동2023-01-28 17:17:20고정형CCTV상무1동중흥S클래스40000
62023-01-11기타2023-01-10 16:48:00고정형CCTV내방동주공아파트앞40000
72023-08-22부과취소2023-08-10 16:17:16고정형CCTV쌍촌동상무푸르지오앞40000
82023-08-22부과취소2023-08-09 15:40:38고정형CCTV쌍촌동상무푸르지오앞40000
92023-08-22부과취소2023-07-28 17:33:29고정형CCTV쌍촌동상무푸르지오앞40000
서손일자서손사유단속일시단속구분단속지역단속장소단속원금
11312023-05-16기타2023-05-12 17:38:35고정형CCTV동천동동림시티40000
11322023-04-25기타2023-04-19 09:25:14고정형CCTV동천동동림시티40000
11332023-04-25이중등록2023-04-21 14:36:00고정형CCTV동천동동림시티40000
11342023-01-18자진이동2023-01-17 17:13:23고정형CCTV동천동동림시티40000
11352023-01-09자진이동2023-01-06 17:24:58고정형CCTV동천동동림시티40000
11362023-02-13착오부과2023-02-03 14:57:45주행형CCTV치평동치평동 상무시민로40000
11372023-02-072시간이내2023-02-03 15:35:24주행형CCTV치평동치평동 상무누리로40000
11382023-04-132시간이내2023-04-10 09:58:08주행형CCTV금호동금호동 화개1로79번길40000
11392023-11-13기타2023-11-11 14:13:13고정형CCTV치평동상무대라수아파트40000
11402023-09-192시간이내2023-09-11 10:29:09고정형CCTV치평동상무대라수아파트80000