Overview

Dataset statistics

Number of variables3
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows136
Duplicate rows (%)1.4%
Total size in memory312.5 KiB
Average record size in memory32.0 B

Variable types

DateTime2
Text1

Dataset

Description파일 다운로드
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-21795/F/1/datasetView.do

Alerts

Dataset has 136 (1.4%) duplicate rowsDuplicates

Reproduction

Analysis started2024-04-20 15:45:11.325399
Analysis finished2024-04-20 15:45:13.539727
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속일
Date

Distinct208
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-01-02 00:00:00
Maximum2021-07-28 00:00:00
2024-04-21T00:45:13.741662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:45:14.075432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속시간
Date

Distinct1064
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-04-21 00:00:00
Maximum2024-04-21 23:57:00
2024-04-21T00:45:14.328759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T00:45:14.564476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속장소
Text

Distinct2484
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T00:45:15.363806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.6693
Min length3

Characters and Unicode

Total characters96693
Distinct characters383
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1886 ?
Unique (%)18.9%

Sample

1st row공진초교 주변
2nd row정곡초등학교
3rd row곰달래로33길 4
4th row힐스테이트에코주변
5th row국내선1층
ValueCountFrequency (%)
부근 1278
 
7.8%
주변 838
 
5.1%
강서구 416
 
2.5%
서울 380
 
2.3%
1373 311
 
1.9%
행사전용주차장 232
 
1.4%
공공건축연구원주변 193
 
1.2%
국내선1층 188
 
1.1%
좋은책신사고주변 187
 
1.1%
국내선2층 185
 
1.1%
Other values (1858) 12146
74.3%
2024-04-21T00:45:16.446252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6441
 
6.7%
6366
 
6.6%
변 5783
 
6.0%
1 3369
 
3.5%
로 3340
 
3.5%
길 2332
 
2.4%
3 2317
 
2.4%
서 1834
 
1.9%
2 1718
 
1.8%
7 1653
 
1.7%
Other values (373) 61540
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72387
74.9%
Decimal Number 15999
 
16.5%
Space Separator 6366
 
6.6%
Dash Punctuation 781
 
0.8%
Uppercase Letter 661
 
0.7%
Open Punctuation 254
 
0.3%
Close Punctuation 192
 
0.2%
Lowercase Letter 32
 
< 0.1%
Other Punctuation 14
 
< 0.1%
Math Symbol 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6441
 
8.9%
변 5783
 
8.0%
로 3340
 
4.6%
길 2332
 
3.2%
서 1834
 
2.5%
화 1644
 
2.3%
구 1615
 
2.2%
곡 1550
 
2.1%
부 1398
 
1.9%
공 1373
 
1.9%
Other values (323) 45077
62.3%
Lowercase Letter
ValueCountFrequency (%)
e 5
15.6%
k 3
9.4%
s 3
9.4%
m 3
9.4%
t 2
 
6.2%
l 2
 
6.2%
d 2
 
6.2%
i 2
 
6.2%
a 2
 
6.2%
n 1
 
3.1%
Other values (7) 7
21.9%
Uppercase Letter
ValueCountFrequency (%)
T 171
25.9%
K 166
25.1%
I 128
19.4%
S 112
16.9%
F 63
 
9.5%
M 4
 
0.6%
L 4
 
0.6%
J 2
 
0.3%
G 2
 
0.3%
A 2
 
0.3%
Other values (5) 7
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 3369
21.1%
3 2317
14.5%
2 1718
10.7%
7 1653
10.3%
4 1549
9.7%
6 1516
9.5%
5 1350
8.4%
8 1264
 
7.9%
0 668
 
4.2%
9 595
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 9
64.3%
. 4
28.6%
! 1
 
7.1%
Space Separator
ValueCountFrequency (%)
6366
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 781
100.0%
Open Punctuation
ValueCountFrequency (%)
( 254
100.0%
Close Punctuation
ValueCountFrequency (%)
) 192
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72387
74.9%
Common 23613
 
24.4%
Latin 693
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6441
 
8.9%
변 5783
 
8.0%
로 3340
 
4.6%
길 2332
 
3.2%
서 1834
 
2.5%
화 1644
 
2.3%
구 1615
 
2.2%
곡 1550
 
2.1%
부 1398
 
1.9%
공 1373
 
1.9%
Other values (323) 45077
62.3%
Latin
ValueCountFrequency (%)
T 171
24.7%
K 166
24.0%
I 128
18.5%
S 112
16.2%
F 63
 
9.1%
e 5
 
0.7%
M 4
 
0.6%
L 4
 
0.6%
k 3
 
0.4%
s 3
 
0.4%
Other values (22) 34
 
4.9%
Common
ValueCountFrequency (%)
6366
27.0%
1 3369
14.3%
3 2317
 
9.8%
2 1718
 
7.3%
7 1653
 
7.0%
4 1549
 
6.6%
6 1516
 
6.4%
5 1350
 
5.7%
8 1264
 
5.4%
- 781
 
3.3%
Other values (8) 1730
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72386
74.9%
ASCII 24306
 
25.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6441
 
8.9%
변 5783
 
8.0%
로 3340
 
4.6%
길 2332
 
3.2%
서 1834
 
2.5%
화 1644
 
2.3%
구 1615
 
2.2%
곡 1550
 
2.1%
부 1398
 
1.9%
공 1373
 
1.9%
Other values (322) 45076
62.3%
ASCII
ValueCountFrequency (%)
6366
26.2%
1 3369
13.9%
3 2317
 
9.5%
2 1718
 
7.1%
7 1653
 
6.8%
4 1549
 
6.4%
6 1516
 
6.2%
5 1350
 
5.6%
8 1264
 
5.2%
- 781
 
3.2%
Other values (40) 2423
 
10.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

Missing values

2024-04-21T00:45:13.181010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T00:45:13.431753image/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

단속일단속시간단속장소
972922021-07-2213:54공진초교 주변
204482021-02-2210:47정곡초등학교
580102021-05-0710:03곰달래로33길 4
987102021-07-2512:06힐스테이트에코주변
463172021-04-1314:58국내선1층
814822021-06-2220:22공항대로46길 강서경찰서 뒷편
672322021-05-2613:15761 부근
504282021-04-2112:01행사전용주차장
755932021-06-1021:58886 부근
147672021-02-0621:16이대병원정문주변
단속일단속시간단속장소
718272021-06-0319:35마곡서로 부근
801662021-06-2011:271373 부근
865062021-07-0210:46화곡로 123
875702021-07-0419:44공항대로46길 40
804712021-06-2107:31등촌로39가길 28-3
293632021-03-1120:18월정로 176주변
590122021-05-0916:17공항동 하늘길
325132021-03-1719:48초록마을로 25-6
396462021-03-3114:21783-2 부근
289462021-03-1109:34공항대로81길 15앞

Duplicate rows

Most frequently occurring

단속일단속시간단속장소# duplicates
1072021-06-2718:39마곡서로 부근4
32021-01-1310:49마곡서로 부근3
132021-02-2019:16마곡중앙로 부근3
182021-03-0718:37886 부근3
242021-03-2114:29812 부근3
322021-03-2911:30886 부근3
432021-04-1212:18마곡중앙8로3길 부근3
522021-04-2319:14812 부근3
632021-05-1010:08785 부근3
812021-05-3113:24763-15 부근3