Overview

Dataset statistics

Number of variables3
Number of observations7703
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory188.2 KiB
Average record size in memory25.0 B

Variable types

Numeric1
DateTime1
Text1

Dataset

Description수영구 2024년도 불법주정차 단속 현황으로 단속일시, 단속장소에 관한 정보를 제공합니다.공공데이터의 활용 목적은 주차난 해결을 위해 지자체별 불법 주차 구역 분석을 통해 최적의 위치에 주차장 확보를 위한 선행 연구입니다.
Author부산광역시 수영구
URLhttps://www.data.go.kr/data/15125388/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:04:51.973622
Analysis finished2024-04-06 08:04:53.208918
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct7703
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3852
Minimum1
Maximum7703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2024-04-06T17:04:53.700601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile386.1
Q11926.5
median3852
Q35777.5
95-th percentile7317.9
Maximum7703
Range7702
Interquartile range (IQR)3851

Descriptive statistics

Standard deviation2223.8089
Coefficient of variation (CV)0.5773128
Kurtosis-1.2
Mean3852
Median Absolute Deviation (MAD)1926
Skewness0
Sum29671956
Variance4945326
MonotonicityStrictly increasing
2024-04-06T17:04:54.222911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5057 1
 
< 0.1%
5145 1
 
< 0.1%
5144 1
 
< 0.1%
5143 1
 
< 0.1%
5142 1
 
< 0.1%
5141 1
 
< 0.1%
5140 1
 
< 0.1%
5139 1
 
< 0.1%
5138 1
 
< 0.1%
Other values (7693) 7693
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
7703 1
< 0.1%
7702 1
< 0.1%
7701 1
< 0.1%
7700 1
< 0.1%
7699 1
< 0.1%
7698 1
< 0.1%
7697 1
< 0.1%
7696 1
< 0.1%
7695 1
< 0.1%
7694 1
< 0.1%

위반일시
Date

Distinct6584
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
Minimum2024-01-01 00:01:00
Maximum2024-03-11 22:41:58
2024-04-06T17:04:54.526550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:04:54.833487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소명
Text

Distinct1307
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size60.3 KiB
2024-04-06T17:04:55.299971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length9.9297676
Min length5

Characters and Unicode

Total characters76489
Distinct characters403
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique657 ?
Unique (%)8.5%

Sample

1st row민락동 민락수변로
2nd row민락동 민락수변로
3rd row광안동 광남로120번길
4th row민락동 민락수변로
5th row민락동 민락수변로
ValueCountFrequency (%)
광안동 1320
 
9.3%
민락동 1028
 
7.2%
망미동 660
 
4.7%
남천동 458
 
3.2%
광안2동 412
 
2.9%
수영동 359
 
2.5%
남천1동 329
 
2.3%
주변 221
 
1.6%
779 209
 
1.5%
205 196
 
1.4%
Other values (1293) 8995
63.4%
2024-04-06T17:04:56.103972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6486
 
8.5%
동 6280
 
8.2%
안 3528
 
4.6%
광 3103
 
4.1%
1 2782
 
3.6%
로 1694
 
2.2%
2 1605
 
2.1%
수 1550
 
2.0%
0 1508
 
2.0%
민 1464
 
1.9%
Other values (393) 46489
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54618
71.4%
Decimal Number 12779
 
16.7%
Space Separator 6486
 
8.5%
Dash Punctuation 1133
 
1.5%
Open Punctuation 561
 
0.7%
Close Punctuation 559
 
0.7%
Uppercase Letter 170
 
0.2%
Other Punctuation 105
 
0.1%
Lowercase Letter 78
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6280
 
11.5%
안 3528
 
6.5%
광 3103
 
5.7%
로 1694
 
3.1%
수 1550
 
2.8%
민 1464
 
2.7%
락 1432
 
2.6%
남 1411
 
2.6%
천 1305
 
2.4%
영 1262
 
2.3%
Other values (364) 31589
57.8%
Decimal Number
ValueCountFrequency (%)
1 2782
21.8%
2 1605
12.6%
0 1508
11.8%
7 1282
10.0%
3 1143
8.9%
5 1126
8.8%
4 949
 
7.4%
8 897
 
7.0%
6 745
 
5.8%
9 742
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
P 58
34.1%
A 40
23.5%
S 25
14.7%
K 25
14.7%
B 17
 
10.0%
M 2
 
1.2%
C 2
 
1.2%
T 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
e 41
52.6%
p 20
25.6%
k 12
 
15.4%
s 4
 
5.1%
w 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
# 79
75.2%
@ 26
 
24.8%
Space Separator
ValueCountFrequency (%)
6486
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 559
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54618
71.4%
Common 21623
 
28.3%
Latin 248
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6280
 
11.5%
안 3528
 
6.5%
광 3103
 
5.7%
로 1694
 
3.1%
수 1550
 
2.8%
민 1464
 
2.7%
락 1432
 
2.6%
남 1411
 
2.6%
천 1305
 
2.4%
영 1262
 
2.3%
Other values (364) 31589
57.8%
Common
ValueCountFrequency (%)
6486
30.0%
1 2782
12.9%
2 1605
 
7.4%
0 1508
 
7.0%
7 1282
 
5.9%
3 1143
 
5.3%
- 1133
 
5.2%
5 1126
 
5.2%
4 949
 
4.4%
8 897
 
4.1%
Other values (6) 2712
12.5%
Latin
ValueCountFrequency (%)
P 58
23.4%
e 41
16.5%
A 40
16.1%
S 25
10.1%
K 25
10.1%
p 20
 
8.1%
B 17
 
6.9%
k 12
 
4.8%
s 4
 
1.6%
M 2
 
0.8%
Other values (3) 4
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54618
71.4%
ASCII 21871
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6486
29.7%
1 2782
12.7%
2 1605
 
7.3%
0 1508
 
6.9%
7 1282
 
5.9%
3 1143
 
5.2%
- 1133
 
5.2%
5 1126
 
5.1%
4 949
 
4.3%
8 897
 
4.1%
Other values (19) 2960
13.5%
Hangul
ValueCountFrequency (%)
동 6280
 
11.5%
안 3528
 
6.5%
광 3103
 
5.7%
로 1694
 
3.1%
수 1550
 
2.8%
민 1464
 
2.7%
락 1432
 
2.6%
남 1411
 
2.6%
천 1305
 
2.4%
영 1262
 
2.3%
Other values (364) 31589
57.8%

Interactions

2024-04-06T17:04:52.631958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-06T17:04:52.988683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:04:53.138792image/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

연번위반일시위반장소명
012024-01-01 07:49:00민락동 민락수변로
122024-01-01 07:46:00민락동 민락수변로
232024-01-01 17:18:00광안동 광남로120번길
342024-01-01 17:41:00민락동 민락수변로
452024-01-01 17:41:00민락동 민락수변로
562024-01-01 17:42:00민락동 민락수변로
672024-01-01 09:03:00수영삼정그린코아사거리
782024-01-01 09:10:00도도어울림센터앞
892024-01-01 09:10:00수영사적공원앞
9102024-01-01 09:12:00씨플렉스앞 사거리
연번위반일시위반장소명
769376942024-02-21 18:10:50씨플렉스앞 사거리
769476952024-02-19 18:48:19남천동해변시장
769576962024-02-14 17:37:22광안동 779(안전신문고)
769676972024-02-16 20:30:27광안동 779(안전신문고)
769776982024-03-02 19:12:51광안동 205(안전신문고)
769876992024-03-07 10:13:00남천1동 황령산로인도
769977002024-02-02 20:25:00민락동 781
770077012024-03-10 18:20:57아우디서비스 매장앞#1
770177022024-03-05 10:59:55수영동 443(안전신문고)
770277032024-02-28 14:17:15수변공원 공중화장실