Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows170
Duplicate rows (%)1.7%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

DateTime2
Text1

Dataset

Description대구광역시 동구 불법주정차 단속 현황 데이터입니다. 이 데이터는 단속일시, 위반시간, 단속 장소 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15063070/fileData.do

Alerts

Dataset has 170 (1.7%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 05:23:59.986659
Analysis finished2023-12-12 05:24:00.544986
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위반일자
Date

Distinct354
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-01 00:00:00
Maximum2022-07-21 00:00:00
2023-12-12T14:24:00.613354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:00.763925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반시간
Date

Distinct994
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-12 00:04:00
Maximum2023-12-12 23:59:00
2023-12-12T14:24:00.952606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:24:01.175698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소명
Text

Distinct1073
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T14:24:01.534857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length8.1056
Min length3

Characters and Unicode

Total characters81056
Distinct characters236
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique570 ?
Unique (%)5.7%

Sample

1st row안심로73길
2nd row아양로
3rd row휴먼시아 7단지 앞
4th row이시아 더샵 3차아파트
5th row신세계백화점 앞
ValueCountFrequency (%)
부근 1887
 
10.3%
앞 947
 
5.2%
성동고가교 532
 
2.9%
신세계백화점 378
 
2.1%
이시아 365
 
2.0%
현대시티 334
 
1.8%
아울렛 334
 
1.8%
구 330
 
1.8%
중앙고속 330
 
1.8%
신암동 327
 
1.8%
Other values (1097) 12496
68.4%
2023-12-12T14:24:02.081395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8361
 
10.3%
동 4206
 
5.2%
로 2642
 
3.3%
부 2471
 
3.0%
근 2120
 
2.6%
신 2091
 
2.6%
1 2071
 
2.6%
아 1938
 
2.4%
구 1696
 
2.1%
5 1424
 
1.8%
Other values (226) 52036
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60806
75.0%
Decimal Number 10319
 
12.7%
Space Separator 8361
 
10.3%
Dash Punctuation 986
 
1.2%
Uppercase Letter 254
 
0.3%
Open Punctuation 165
 
0.2%
Close Punctuation 165
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4206
 
6.9%
로 2642
 
4.3%
부 2471
 
4.1%
근 2120
 
3.5%
신 2091
 
3.4%
아 1938
 
3.2%
구 1696
 
2.8%
길 1383
 
2.3%
대 1271
 
2.1%
시 1257
 
2.1%
Other values (207) 39731
65.3%
Decimal Number
ValueCountFrequency (%)
1 2071
20.1%
5 1424
13.8%
2 1277
12.4%
3 1193
11.6%
7 814
 
7.9%
4 787
 
7.6%
8 741
 
7.2%
6 729
 
7.1%
9 643
 
6.2%
0 640
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
M 171
67.3%
T 24
 
9.4%
A 24
 
9.4%
P 24
 
9.4%
K 11
 
4.3%
Space Separator
ValueCountFrequency (%)
8361
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 986
100.0%
Open Punctuation
ValueCountFrequency (%)
( 165
100.0%
Close Punctuation
ValueCountFrequency (%)
) 165
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60806
75.0%
Common 19996
 
24.7%
Latin 254
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4206
 
6.9%
로 2642
 
4.3%
부 2471
 
4.1%
근 2120
 
3.5%
신 2091
 
3.4%
아 1938
 
3.2%
구 1696
 
2.8%
길 1383
 
2.3%
대 1271
 
2.1%
시 1257
 
2.1%
Other values (207) 39731
65.3%
Common
ValueCountFrequency (%)
8361
41.8%
1 2071
 
10.4%
5 1424
 
7.1%
2 1277
 
6.4%
3 1193
 
6.0%
- 986
 
4.9%
7 814
 
4.1%
4 787
 
3.9%
8 741
 
3.7%
6 729
 
3.6%
Other values (4) 1613
 
8.1%
Latin
ValueCountFrequency (%)
M 171
67.3%
T 24
 
9.4%
A 24
 
9.4%
P 24
 
9.4%
K 11
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60806
75.0%
ASCII 20250
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8361
41.3%
1 2071
 
10.2%
5 1424
 
7.0%
2 1277
 
6.3%
3 1193
 
5.9%
- 986
 
4.9%
7 814
 
4.0%
4 787
 
3.9%
8 741
 
3.7%
6 729
 
3.6%
Other values (9) 1867
 
9.2%
Hangul
ValueCountFrequency (%)
동 4206
 
6.9%
로 2642
 
4.3%
부 2471
 
4.1%
근 2120
 
3.5%
신 2091
 
3.4%
아 1938
 
3.2%
구 1696
 
2.8%
길 1383
 
2.3%
대 1271
 
2.1%
시 1257
 
2.1%
Other values (207) 39731
65.3%

Missing values

2023-12-12T14:24:00.418681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:24:00.506776image/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

위반일자위반시간위반장소명
801702022-05-0310:30안심로73길
413062021-12-0811:25아양로
397552021-12-0315:58휴먼시아 7단지 앞
829442022-05-1407:37이시아 더샵 3차아파트
585472022-02-1410:22신세계백화점 앞
92232021-08-3014:28한국폴리텍대학섬유캠퍼
10512021-08-0414:29타임스케어 부근
945222022-06-2815:08대구은행 동구청지점 앞
204842021-10-0807:00메리어트
264492021-10-2515:59방촌동 동촌로45길 5
위반일자위반시간위반장소명
705302022-04-0108:03새론초등학교
436552021-12-1517:24이시아 롯데아울렛 북문
582472022-02-1314:25구 중앙고속
975232022-07-0915:48복합환승센터 앞
495282022-01-0619:36큰고개 오거리
237852021-10-1810:23동촌로58길
562602022-02-0518:08성동고가교
479702021-12-3117:13동대구역 앞
951032022-06-3017:20휴먼시아 7단지 앞
826892022-05-1315:19이시아 롯데아울렛 남문

Duplicate rows

Most frequently occurring

위반일자위반시간위반장소명# duplicates
422021-10-0610:15동부로15길5
72021-08-0910:19동부로3
152021-08-2014:42송라로32길3
292021-09-0911:18동북로3
532021-10-2614:23송라로32길3
662021-11-0811:01반야월북로3
742021-11-1615:21첨단로8길3
942021-12-1714:42신성로3
972021-12-2408:11효목로19길3
1162022-02-1115:20반야월북로3