Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows2114
Duplicate rows (%)21.1%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

DateTime2
Text1

Dataset

Description전라남도 나주시 관내 불법주정차 단속내역(단속일자, 단속위치 등) 정보를 제공하며
Author전라남도 나주시
URLhttps://www.data.go.kr/data/15094896/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 2114 (21.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 02:20:34.278828
Analysis finished2023-12-12 02:20:34.618205
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위반일자
Date

Distinct302
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-01 00:00:00
Maximum2021-10-31 00:00:00
2023-12-12T11:20:34.705965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:34.854763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소명
Text

Distinct602
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:20:35.180475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length8.04
Min length3

Characters and Unicode

Total characters80400
Distinct characters138
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

Unique362 ?
Unique (%)3.6%

Sample

1st row영산한의원
2nd row나주터미널
3rd rowKDN사거리
4th rowKDN사거리
5th row금성관
ValueCountFrequency (%)
나주터미널 1356
 
8.4%
빛가람동 1011
 
6.2%
kdn사거리 855
 
5.3%
영산한의원 781
 
4.8%
중앙로 679
 
4.2%
사거리 679
 
4.2%
횡단보도 572
 
3.5%
구)광주은행 548
 
3.4%
성원아파트 490
 
3.0%
금성관 413
 
2.5%
Other values (404) 8829
54.5%
2023-12-12T11:20:35.674474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6216
 
7.7%
주 3178
 
4.0%
사 3072
 
3.8%
동 2842
 
3.5%
빛 2397
 
3.0%
람 2366
 
2.9%
가 2366
 
2.9%
리 2072
 
2.6%
0 2013
 
2.5%
나 1892
 
2.4%
Other values (128) 51986
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60079
74.7%
Decimal Number 8297
 
10.3%
Space Separator 6216
 
7.7%
Uppercase Letter 3308
 
4.1%
Open Punctuation 1490
 
1.9%
Close Punctuation 548
 
0.7%
Dash Punctuation 462
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3178
 
5.3%
사 3072
 
5.1%
동 2842
 
4.7%
빛 2397
 
4.0%
람 2366
 
3.9%
가 2366
 
3.9%
리 2072
 
3.4%
나 1892
 
3.1%
터 1774
 
3.0%
거 1733
 
2.9%
Other values (110) 36387
60.6%
Decimal Number
ValueCountFrequency (%)
0 2013
24.3%
2 1688
20.3%
1 1561
18.8%
3 747
 
9.0%
4 614
 
7.4%
9 521
 
6.3%
6 509
 
6.1%
8 251
 
3.0%
7 207
 
2.5%
5 186
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
K 855
25.8%
D 855
25.8%
N 855
25.8%
M 743
22.5%
Space Separator
ValueCountFrequency (%)
6216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1490
100.0%
Close Punctuation
ValueCountFrequency (%)
) 548
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 462
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60079
74.7%
Common 17013
 
21.2%
Latin 3308
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3178
 
5.3%
사 3072
 
5.1%
동 2842
 
4.7%
빛 2397
 
4.0%
람 2366
 
3.9%
가 2366
 
3.9%
리 2072
 
3.4%
나 1892
 
3.1%
터 1774
 
3.0%
거 1733
 
2.9%
Other values (110) 36387
60.6%
Common
ValueCountFrequency (%)
6216
36.5%
0 2013
 
11.8%
2 1688
 
9.9%
1 1561
 
9.2%
( 1490
 
8.8%
3 747
 
4.4%
4 614
 
3.6%
) 548
 
3.2%
9 521
 
3.1%
6 509
 
3.0%
Other values (4) 1106
 
6.5%
Latin
ValueCountFrequency (%)
K 855
25.8%
D 855
25.8%
N 855
25.8%
M 743
22.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60079
74.7%
ASCII 20321
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6216
30.6%
0 2013
 
9.9%
2 1688
 
8.3%
1 1561
 
7.7%
( 1490
 
7.3%
K 855
 
4.2%
D 855
 
4.2%
N 855
 
4.2%
3 747
 
3.7%
M 743
 
3.7%
Other values (8) 3298
16.2%
Hangul
ValueCountFrequency (%)
주 3178
 
5.3%
사 3072
 
5.1%
동 2842
 
4.7%
빛 2397
 
4.0%
람 2366
 
3.9%
가 2366
 
3.9%
리 2072
 
3.4%
나 1892
 
3.1%
터 1774
 
3.0%
거 1733
 
2.9%
Other values (110) 36387
60.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-11-01 00:00:00
Maximum2021-11-01 00:00:00
2023-12-12T11:20:35.793960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:20:35.907820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2023-12-12T11:20:34.473842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:20:34.566953image/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

위반일자위반장소명데이터기준일자
191572021-10-16영산한의원2021-11-01
158922021-08-30나주터미널2021-11-01
198572021-10-28KDN사거리2021-11-01
198392021-10-27KDN사거리2021-11-01
51952021-04-10금성관2021-11-01
112952021-07-04중앙로 사거리2021-11-01
150602021-08-18나주터미널2021-11-01
63182021-04-27빛가람동 우정로2021-11-01
41392021-03-26나주터미널2021-11-01
8582021-01-23KDN사거리 (사방 200M이2021-11-01
위반일자위반장소명데이터기준일자
17352021-02-14남평읍 동사리414 황색실선2021-11-01
131902021-07-27(구)광주은행2021-11-01
74522021-05-13중앙로 사거리2021-11-01
185832021-10-07나주터미널2021-11-01
75952021-05-15나주터미널2021-11-01
71972021-05-10삼영동 미니스톱2021-11-01
110202021-07-01영산한의원2021-11-01
76182021-05-16영산한의원2021-11-01
30232021-03-10빛가람동220 황색실선2021-11-01
167052021-09-09남평읍 동사리412 횡단보도2021-11-01

Duplicate rows

Most frequently occurring

위반일자위반장소명데이터기준일자# duplicates
1222021-01-27빛가람동 중야2길2021-11-0121
6272021-04-19빛가람동 중야2길2021-11-0120
9202021-06-01빛가람동 중야2길2021-11-0118
18642021-09-24빛가람동 전력로2021-11-0116
11792021-07-01나주터미널2021-11-0115
15362021-08-10나주터미널2021-11-0114
19482021-10-05나주터미널2021-11-0114
9292021-06-02빛가람동 상야1길2021-11-0113
10632021-06-18나주터미널2021-11-0113
12872021-07-13나주터미널2021-11-0113