Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows162
Duplicate rows (%)1.6%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

DateTime2
Text1

Dataset

Description대구광역시 동구_불법주정차 단속현황_20230531
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15063070&dataSetDetailId=150630701f35e29dbdd8a&provdMethod=FILE

Alerts

Dataset has 162 (1.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-08-15 07:37:32.510267
Analysis finished2023-08-15 07:37:33.393832
Duration0.88 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
2023-08-15T16:37:33.543526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-15T16:37:33.887560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반시간
Date

Distinct1009
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-08-15 00:01:00
Maximum2023-08-15 23:56:00
2023-08-15T16:37:34.280110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-15T16:37:34.583834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소명
Text

Distinct1078
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-08-15T16:37:35.026329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.1753
Min length3

Characters and Unicode

Total characters81753
Distinct characters242
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

Unique547 ?
Unique (%)5.5%

Sample

1st row신천동M마트 부근
2nd row동부소방서 건너
3rd row방촌동 1113-117 부근
4th row(구)제이스호텔삼거리
5th row중앙신체검사소 사거리
ValueCountFrequency (%)
부근 1905
 
10.3%
앞 988
 
5.4%
성동고가교 552
 
3.0%
이시아 370
 
2.0%
신세계백화점 368
 
2.0%
신암동 356
 
1.9%
현대시티 329
 
1.8%
아울렛 329
 
1.8%
동대구역 322
 
1.7%
메리어트 311
 
1.7%
Other values (1110) 12608
68.4%
2023-08-15T16:37:35.754062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8550
 
10.5%
동 4221
 
5.2%
로 2626
 
3.2%
부 2469
 
3.0%
근 2134
 
2.6%
1 2126
 
2.6%
신 2100
 
2.6%
아 2010
 
2.5%
구 1710
 
2.1%
5 1414
 
1.7%
Other values (232) 52393
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61014
74.6%
Decimal Number 10575
 
12.9%
Space Separator 8550
 
10.5%
Dash Punctuation 990
 
1.2%
Uppercase Letter 273
 
0.3%
Close Punctuation 175
 
0.2%
Open Punctuation 175
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4221
 
6.9%
로 2626
 
4.3%
부 2469
 
4.0%
근 2134
 
3.5%
신 2100
 
3.4%
아 2010
 
3.3%
구 1710
 
2.8%
길 1392
 
2.3%
대 1297
 
2.1%
시 1261
 
2.1%
Other values (212) 39794
65.2%
Decimal Number
ValueCountFrequency (%)
1 2126
20.1%
5 1414
13.4%
2 1308
12.4%
3 1181
11.2%
4 845
 
8.0%
7 837
 
7.9%
8 778
 
7.4%
6 757
 
7.2%
0 671
 
6.3%
9 658
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
M 140
51.3%
T 40
 
14.7%
P 40
 
14.7%
A 40
 
14.7%
K 13
 
4.8%
Space Separator
ValueCountFrequency (%)
8550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 990
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61014
74.6%
Common 20466
 
25.0%
Latin 273
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4221
 
6.9%
로 2626
 
4.3%
부 2469
 
4.0%
근 2134
 
3.5%
신 2100
 
3.4%
아 2010
 
3.3%
구 1710
 
2.8%
길 1392
 
2.3%
대 1297
 
2.1%
시 1261
 
2.1%
Other values (212) 39794
65.2%
Common
ValueCountFrequency (%)
8550
41.8%
1 2126
 
10.4%
5 1414
 
6.9%
2 1308
 
6.4%
3 1181
 
5.8%
- 990
 
4.8%
4 845
 
4.1%
7 837
 
4.1%
8 778
 
3.8%
6 757
 
3.7%
Other values (5) 1680
 
8.2%
Latin
ValueCountFrequency (%)
M 140
51.3%
T 40
 
14.7%
P 40
 
14.7%
A 40
 
14.7%
K 13
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61014
74.6%
ASCII 20739
 
25.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8550
41.2%
1 2126
 
10.3%
5 1414
 
6.8%
2 1308
 
6.3%
3 1181
 
5.7%
- 990
 
4.8%
4 845
 
4.1%
7 837
 
4.0%
8 778
 
3.8%
6 757
 
3.7%
Other values (10) 1953
 
9.4%
Hangul
ValueCountFrequency (%)
동 4221
 
6.9%
로 2626
 
4.3%
부 2469
 
4.0%
근 2134
 
3.5%
신 2100
 
3.4%
아 2010
 
3.3%
구 1710
 
2.8%
길 1392
 
2.3%
대 1297
 
2.1%
시 1261
 
2.1%
Other values (212) 39794
65.2%

Missing values

2023-08-15T16:37:33.126266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-15T16:37:33.310940image/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
614262022-02-2515:38신천동M마트 부근
391152021-12-0116:57동부소방서 건너
783052022-04-2713:13방촌동 1113-117 부근
830662022-05-1417:08(구)제이스호텔삼거리
436082021-12-1514:20중앙신체검사소 사거리
919262022-06-1916:59(구)제이스호텔삼거리
46172021-08-1614:11효목동 647 부근
953362022-07-0107:43구 중앙고속
3912021-08-0211:32성동고가교
578692022-02-1117:21신기동 반야월로 158
위반일자위반시간위반장소명
984672022-07-1316:58K2입구
551222022-01-2719:50동대구역 앞
681992022-03-2417:38새론초등학교
380602021-11-2810:31현대시티 아울렛 후문
391912021-12-0121:11신세계백화점건너
649062022-03-1207:11동대구역 지하도부근
834382022-05-1614:36효서로
83092021-08-2710:51현대시티 아울렛 후문
340632021-11-1514:37동대구로
293462021-11-0214:42팔공로47길

Duplicate rows

Most frequently occurring

위반일자위반시간위반장소명# duplicates
212021-09-0914:48첨단로8길4
622021-11-1914:44첨단로8길4
42021-08-0915:36신서로3
62021-08-1118:45신암동 아양로 37-43
112021-08-2014:42송라로32길3
292021-10-0510:58반야월북로3
602021-11-1710:49동부로15길3
732021-12-1614:37율암로3
742021-12-1614:38율암로3
772021-12-2015:14첨단로8길3