Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows261
Duplicate rows (%)2.6%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

DateTime2
Text1

Dataset

Description2023. 1. 1. ~ 2023. 11. 30. 사이에 발생한 부산광역시 동구 불법주정차 단속현황입니다. 주정차 위반 날짜와 시각, 장소를 제공하고 있습니다.
Author부산광역시 동구
URLhttps://www.data.go.kr/data/15125437/fileData.do

Alerts

Dataset has 261 (2.6%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-23 07:33:07.818710
Analysis finished2023-12-23 07:33:13.999703
Duration6.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위반일자
Date

Distinct334
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 00:00:00
Maximum2023-11-30 00:00:00
2023-12-23T07:33:14.433942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:33:16.296368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반시간
Date

Distinct1114
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-12-23 00:00:00
Maximum2023-12-23 23:59:00
2023-12-23T07:33:17.338063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T07:33:18.539062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소명
Text

Distinct1675
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-23T07:33:19.881989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length10.1365
Min length5

Characters and Unicode

Total characters101365
Distinct characters415
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1044 ?
Unique (%)10.4%

Sample

1st row초량동 중앙대로260번길
2nd row범일동 조방로 덕원빌딩옆
3rd row범일동 1474-72
4th row 범일동 830-15
5th row범일동 830-15
ValueCountFrequency (%)
초량동 2995
 
13.7%
범일동 2783
 
12.7%
주변 1780
 
8.1%
수정동 842
 
3.8%
앞 794
 
3.6%
부산역 685
 
3.1%
830-15 663
 
3.0%
초량 474
 
2.2%
선상주차장 423
 
1.9%
광장빌딩 372
 
1.7%
Other values (1573) 10094
46.1%
2023-12-23T07:33:21.768496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11949
 
11.8%
동 8083
 
8.0%
1 4601
 
4.5%
초 4321
 
4.3%
량 4173
 
4.1%
범 2996
 
3.0%
일 2933
 
2.9%
주 2798
 
2.8%
2 2611
 
2.6%
- 2503
 
2.5%
Other values (405) 54397
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67555
66.6%
Decimal Number 18793
 
18.5%
Space Separator 11949
 
11.8%
Dash Punctuation 2503
 
2.5%
Uppercase Letter 261
 
0.3%
Close Punctuation 132
 
0.1%
Open Punctuation 113
 
0.1%
Lowercase Letter 48
 
< 0.1%
Other Punctuation 6
 
< 0.1%
Math Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 8083
 
12.0%
초 4321
 
6.4%
량 4173
 
6.2%
범 2996
 
4.4%
일 2933
 
4.3%
주 2798
 
4.1%
옆 1947
 
2.9%
변 1786
 
2.6%
산 1624
 
2.4%
부 1497
 
2.2%
Other values (358) 35397
52.4%
Uppercase Letter
ValueCountFrequency (%)
G 149
57.1%
B 19
 
7.3%
D 18
 
6.9%
L 14
 
5.4%
K 13
 
5.0%
S 11
 
4.2%
T 11
 
4.2%
H 6
 
2.3%
C 4
 
1.5%
O 4
 
1.5%
Other values (6) 12
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
c 9
18.8%
e 9
18.8%
s 6
12.5%
t 5
10.4%
g 4
8.3%
j 4
8.3%
w 2
 
4.2%
y 2
 
4.2%
a 2
 
4.2%
p 2
 
4.2%
Other values (3) 3
 
6.2%
Decimal Number
ValueCountFrequency (%)
1 4601
24.5%
2 2611
13.9%
3 2416
12.9%
0 2398
12.8%
8 1681
 
8.9%
5 1396
 
7.4%
4 1007
 
5.4%
7 940
 
5.0%
9 914
 
4.9%
6 829
 
4.4%
Math Symbol
ValueCountFrequency (%)
~ 4
80.0%
+ 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
66.7%
. 2
33.3%
Space Separator
ValueCountFrequency (%)
11949
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2503
100.0%
Close Punctuation
ValueCountFrequency (%)
) 132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67555
66.6%
Common 33501
33.0%
Latin 309
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 8083
 
12.0%
초 4321
 
6.4%
량 4173
 
6.2%
범 2996
 
4.4%
일 2933
 
4.3%
주 2798
 
4.1%
옆 1947
 
2.9%
변 1786
 
2.6%
산 1624
 
2.4%
부 1497
 
2.2%
Other values (358) 35397
52.4%
Latin
ValueCountFrequency (%)
G 149
48.2%
B 19
 
6.1%
D 18
 
5.8%
L 14
 
4.5%
K 13
 
4.2%
S 11
 
3.6%
T 11
 
3.6%
c 9
 
2.9%
e 9
 
2.9%
s 6
 
1.9%
Other values (19) 50
 
16.2%
Common
ValueCountFrequency (%)
11949
35.7%
1 4601
 
13.7%
2 2611
 
7.8%
- 2503
 
7.5%
3 2416
 
7.2%
0 2398
 
7.2%
8 1681
 
5.0%
5 1396
 
4.2%
4 1007
 
3.0%
7 940
 
2.8%
Other values (8) 1999
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67555
66.6%
ASCII 33810
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11949
35.3%
1 4601
 
13.6%
2 2611
 
7.7%
- 2503
 
7.4%
3 2416
 
7.1%
0 2398
 
7.1%
8 1681
 
5.0%
5 1396
 
4.1%
4 1007
 
3.0%
7 940
 
2.8%
Other values (37) 2308
 
6.8%
Hangul
ValueCountFrequency (%)
동 8083
 
12.0%
초 4321
 
6.4%
량 4173
 
6.2%
범 2996
 
4.4%
일 2933
 
4.3%
주 2798
 
4.1%
옆 1947
 
2.9%
변 1786
 
2.6%
산 1624
 
2.4%
부 1497
 
2.2%
Other values (358) 35397
52.4%

Missing values

2023-12-23T07:33:13.293221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T07:33:13.758358image/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
229412023-08-2214:17초량동 중앙대로260번길
349242023-11-1614:41범일동 조방로 덕원빌딩옆
206522023-08-0310:24범일동 1474-72
209252023-08-0512:05범일동 830-15
96302023-04-1612:59범일동 830-15
309532023-10-1909:48부산역 선상주차장 주변
236852023-08-2719:26부산화교중고등학교 주변
273942023-09-2223:15초량동 1127
307892023-10-1901:03초량동 1056-1
160462023-06-2115:39초량동 국민은행 앞
위반일자위반시간위반장소명
137922023-05-3018:50초량2동주민센터 주변
143602023-06-0517:18부산역 풍물거리 주변
144662023-06-0710:19초량동 초량로 111옆
26662023-02-0614:34초량동 초량로
269162023-09-1921:49초량동 144-16
333812023-11-0415:55초량동 1170
73462023-03-2414:51초량동 중앙대로214번길
213172023-08-0820:28부산역 선상주차장 주변
9042023-01-1110:25수정동 중앙대로
254472023-09-0810:37로미오와 줄리엣 인근

Duplicate rows

Most frequently occurring

위반일자위반시간위반장소명# duplicates
52023-01-0815:51범일동 조방로34번길5
1022023-06-1914:36범일동 자성로133번길5
1062023-06-3011:07범일동 조방로34번길5
1812023-09-1114:24범일동 자성로133번길5
2002023-09-2114:38범일동 자성로133번길5
2262023-10-1910:56수정동 수정중로11번길5
2432023-11-0310:46범일동 조방로26번길5
792023-05-1309:52범일동 중앙대로4
1202023-07-1911:07범일동 자성로133번길4
1332023-07-2914:30범일동 범상로4