Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows242
Duplicate rows (%)2.4%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

DateTime1
Categorical3
Text1
Numeric1

Dataset

Description서울특별시 용산구 불법주정차단속현황(단속일시, 단속구분, 단속동, 서울특별시 용산구 단속장소, 단속원금, 위반내용)에 대한 데이터를 제공합니다
Author서울특별시 용산구
URLhttps://www.data.go.kr/data/15084175/fileData.do

Alerts

Dataset has 242 (2.4%) duplicate rowsDuplicates
단속구분 is highly overall correlated with 단속동 and 1 other fieldsHigh correlation
단속동 is highly overall correlated with 단속구분High correlation
위반내용 is highly overall correlated with 단속구분High correlation

Reproduction

Analysis started2023-12-12 12:24:10.497574
Analysis finished2023-12-12 12:24:11.559065
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속일시
Date

Distinct9476
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-01-01 00:00:00
Maximum2016-01-05 19:55:00
2023-12-12T21:24:11.668652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:24:11.831253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
PDA
4659 
CCTV
3085 
주행형CCTV
1783 
고정형CCTV
 
414
일반
 
50

Length

Max length7
Median length6
Mean length4.185
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPDA
2nd rowPDA
3rd rowPDA
4th rowPDA
5th rowPDA

Common Values

ValueCountFrequency (%)
PDA 4659
46.6%
CCTV 3085
30.9%
주행형CCTV 1783
 
17.8%
고정형CCTV 414
 
4.1%
일반 50
 
0.5%
시민신고제웹 9
 
0.1%

Length

2023-12-12T21:24:11.975951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:24:12.095713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pda 4659
46.6%
cctv 3085
30.9%
주행형cctv 1783
 
17.8%
고정형cctv 414
 
4.1%
일반 50
 
0.5%
시민신고제웹 9
 
0.1%

단속동
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
한남동
2084 
한강로동
1379 
이태원1동
933 
이촌동
749 
이태원2동
674 
Other values (45)
4181 

Length

Max length9
Median length7
Mean length3.8239
Min length3

Unique

Unique8 ?
Unique (%)0.1%

Sample

1st row남영동
2nd row원효로1동
3rd row이태원2동
4th row이태원1동
5th row한남동

Common Values

ValueCountFrequency (%)
한남동 2084
20.8%
한강로동 1379
13.8%
이태원1동 933
 
9.3%
이촌동 749
 
7.5%
이태원2동 674
 
6.7%
이태원동 613
 
6.1%
후암동 381
 
3.8%
남영동 310
 
3.1%
보광동 270
 
2.7%
효창동 238
 
2.4%
Other values (40) 2369
23.7%

Length

2023-12-12T21:24:12.237222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한남동 2084
20.8%
한강로동 1379
13.8%
이태원1동 933
 
9.3%
이촌동 749
 
7.5%
이태원2동 674
 
6.7%
이태원동 613
 
6.1%
후암동 381
 
3.8%
남영동 310
 
3.1%
보광동 270
 
2.7%
효창동 238
 
2.4%
Other values (40) 2369
23.7%

단속장소
Text

Distinct2661
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T21:24:12.541603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length37
Mean length21.7913
Min length16

Characters and Unicode

Total characters217913
Distinct characters378
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1661 ?
Unique (%)16.6%

Sample

1st row서울특별시 용산구 남영동 후암로57길
2nd row서울특별시 용산구 원효로1동 원효로84길 9
3rd row서울특별시 용산구 이태원2동 회나무로13길
4th row서울특별시 용산구 이태원1동 이태원로
5th row서울특별시 용산구 한남동 이태원로 240제일기획
ValueCountFrequency (%)
용산구 10001
22.4%
서울특별시 10000
22.4%
한남동 2423
 
5.4%
한강로동 1379
 
3.1%
이태원1동 933
 
2.1%
이촌동 749
 
1.7%
이태원동 677
 
1.5%
이태원2동 675
 
1.5%
앞 452
 
1.0%
후암동 381
 
0.9%
Other values (1779) 17024
38.1%
2023-12-12T21:24:13.060503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34701
 
15.9%
용 10766
 
4.9%
산 10702
 
4.9%
서 10485
 
4.8%
동 10412
 
4.8%
구 10399
 
4.8%
시 10161
 
4.7%
울 10003
 
4.6%
특 10000
 
4.6%
별 10000
 
4.6%
Other values (368) 90284
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159209
73.1%
Space Separator 34701
 
15.9%
Decimal Number 21832
 
10.0%
Dash Punctuation 1834
 
0.8%
Uppercase Letter 143
 
0.1%
Lowercase Letter 74
 
< 0.1%
Math Symbol 52
 
< 0.1%
Close Punctuation 34
 
< 0.1%
Open Punctuation 34
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 10766
 
6.8%
산 10702
 
6.7%
서 10485
 
6.6%
동 10412
 
6.5%
구 10399
 
6.5%
시 10161
 
6.4%
울 10003
 
6.3%
특 10000
 
6.3%
별 10000
 
6.3%
로 8024
 
5.0%
Other values (331) 58257
36.6%
Lowercase Letter
ValueCountFrequency (%)
s 11
14.9%
l 10
13.5%
c 10
13.5%
t 8
10.8%
a 7
9.5%
g 7
9.5%
v 4
 
5.4%
b 3
 
4.1%
p 3
 
4.1%
k 2
 
2.7%
Other values (6) 9
12.2%
Decimal Number
ValueCountFrequency (%)
1 5546
25.4%
2 3656
16.7%
3 2508
11.5%
4 2121
 
9.7%
0 1793
 
8.2%
5 1784
 
8.2%
6 1275
 
5.8%
7 1184
 
5.4%
9 1095
 
5.0%
8 870
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
G 61
42.7%
L 60
42.0%
S 9
 
6.3%
A 6
 
4.2%
K 6
 
4.2%
X 1
 
0.7%
Space Separator
ValueCountFrequency (%)
34701
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1834
100.0%
Math Symbol
ValueCountFrequency (%)
~ 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159209
73.1%
Common 58487
 
26.8%
Latin 217
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 10766
 
6.8%
산 10702
 
6.7%
서 10485
 
6.6%
동 10412
 
6.5%
구 10399
 
6.5%
시 10161
 
6.4%
울 10003
 
6.3%
특 10000
 
6.3%
별 10000
 
6.3%
로 8024
 
5.0%
Other values (331) 58257
36.6%
Latin
ValueCountFrequency (%)
G 61
28.1%
L 60
27.6%
s 11
 
5.1%
l 10
 
4.6%
c 10
 
4.6%
S 9
 
4.1%
t 8
 
3.7%
a 7
 
3.2%
g 7
 
3.2%
A 6
 
2.8%
Other values (12) 28
12.9%
Common
ValueCountFrequency (%)
34701
59.3%
1 5546
 
9.5%
2 3656
 
6.3%
3 2508
 
4.3%
4 2121
 
3.6%
- 1834
 
3.1%
0 1793
 
3.1%
5 1784
 
3.1%
6 1275
 
2.2%
7 1184
 
2.0%
Other values (5) 2085
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159188
73.1%
ASCII 58704
 
26.9%
Compat Jamo 21
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34701
59.1%
1 5546
 
9.4%
2 3656
 
6.2%
3 2508
 
4.3%
4 2121
 
3.6%
- 1834
 
3.1%
0 1793
 
3.1%
5 1784
 
3.0%
6 1275
 
2.2%
7 1184
 
2.0%
Other values (27) 2302
 
3.9%
Hangul
ValueCountFrequency (%)
용 10766
 
6.8%
산 10702
 
6.7%
서 10485
 
6.6%
동 10412
 
6.5%
구 10399
 
6.5%
시 10161
 
6.4%
울 10003
 
6.3%
특 10000
 
6.3%
별 10000
 
6.3%
로 8024
 
5.0%
Other values (328) 58236
36.6%
Compat Jamo
ValueCountFrequency (%)
ㅡ 19
90.5%
ㄴ 1
 
4.8%
ㅔ 1
 
4.8%

단속원금
Real number (ℝ)

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41806.5
Minimum10000
Maximum100000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T21:24:13.194002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile40000
Q140000
median40000
Q340000
95-th percentile50000
Maximum100000
Range90000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7229.4041
Coefficient of variation (CV)0.17292536
Kurtosis22.341578
Mean41806.5
Median Absolute Deviation (MAD)0
Skewness4.607964
Sum4.18065 × 108
Variance52264284
MonotonicityNot monotonic
2023-12-12T21:24:13.315335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
40000 9039
90.4%
50000 649
 
6.5%
80000 270
 
2.7%
90000 18
 
0.2%
20000 12
 
0.1%
60000 7
 
0.1%
10000 2
 
< 0.1%
100000 1
 
< 0.1%
25000 1
 
< 0.1%
30000 1
 
< 0.1%
ValueCountFrequency (%)
10000 2
 
< 0.1%
20000 12
 
0.1%
25000 1
 
< 0.1%
30000 1
 
< 0.1%
40000 9039
90.4%
50000 649
 
6.5%
60000 7
 
0.1%
80000 270
 
2.7%
90000 18
 
0.2%
100000 1
 
< 0.1%
ValueCountFrequency (%)
100000 1
 
< 0.1%
90000 18
 
0.2%
80000 270
 
2.7%
60000 7
 
0.1%
50000 649
 
6.5%
40000 9039
90.4%
30000 1
 
< 0.1%
25000 1
 
< 0.1%
20000 12
 
0.1%
10000 2
 
< 0.1%

위반내용
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
도로교통법 제32조
2341 
32조내지 34조위반
1828 
교통장애
1708 
도로교통법 제33조
1257 
황색점선
660 
Other values (15)
2206 

Length

Max length11
Median length10
Mean length7.6107
Min length3

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row황색점선
2nd row교통장애
3rd row교통장애
4th row황색점선
5th row교통장애

Common Values

ValueCountFrequency (%)
도로교통법 제32조 2341
23.4%
32조내지 34조위반 1828
18.3%
교통장애 1708
17.1%
도로교통법 제33조 1257
12.6%
황색점선 660
 
6.6%
주정차위반 588
 
5.9%
황색실선 418
 
4.2%
주정차금지 352
 
3.5%
보도주차 266
 
2.7%
횡단보도 205
 
2.1%
Other values (10) 377
 
3.8%

Length

2023-12-12T21:24:13.480452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도로교통법 3598
23.3%
제32조 2341
15.2%
34조위반 1829
11.9%
32조내지 1828
11.9%
교통장애 1708
11.1%
제33조 1257
 
8.1%
황색점선 660
 
4.3%
주정차위반 588
 
3.8%
황색실선 418
 
2.7%
주정차금지 352
 
2.3%
Other values (11) 847
 
5.5%

Interactions

2023-12-12T21:24:11.163223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:24:13.613077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속구분단속동단속원금위반내용
단속구분1.0000.8130.1100.933
단속동0.8131.0000.2390.778
단속원금0.1100.2391.0000.147
위반내용0.9330.7780.1471.000
2023-12-12T21:24:13.729442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위반내용단속구분단속동
위반내용1.0000.7750.291
단속구분0.7751.0000.511
단속동0.2910.5111.000
2023-12-12T21:24:13.858588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속원금단속구분단속동위반내용
단속원금1.0000.0600.0870.053
단속구분0.0601.0000.5110.775
단속동0.0870.5111.0000.291
위반내용0.0530.7750.2911.000

Missing values

2023-12-12T21:24:11.316647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:24:11.491493image/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

단속일시단속구분단속동단속장소단속원금위반내용
250042015-04-01 09:53PDA남영동서울특별시 용산구 남영동 후암로57길40000황색점선
928082015-12-23 19:51PDA원효로1동서울특별시 용산구 원효로1동 원효로84길 940000교통장애
624922015-08-11 22:57PDA이태원2동서울특별시 용산구 이태원2동 회나무로13길40000교통장애
630512015-08-14 01:28PDA이태원1동서울특별시 용산구 이태원1동 이태원로40000황색점선
679822015-09-04 23:47PDA한남동서울특별시 용산구 한남동 이태원로 240제일기획40000교통장애
405732015-05-23 19:48PDA이태원1동서울특별시 용산구 이태원1동 우사단로80000황색실선
702532015-09-14 09:40CCTV한강로1가서울특별시 용산구 한강로1가 백범로99길40000도로교통법 제33조
431182015-06-01 09:24주행형CCTV한남동서울특별시 용산구 한남동 742-150000도로교통법 제32조
140812015-02-19 15:28CCTV이태원1동서울특별시 용산구 이태원1동 해롯앤틱갤러리4000032조내지 34조위반
677842015-09-04 15:50CCTV한남동서울특별시 용산구 한남동 한남동 유엔빌리지 입구4000032조내지 34조위반
단속일시단속구분단속동단속장소단속원금위반내용
574542015-07-22 09:50CCTV이촌동서울특별시 용산구 이촌동 이촌로40000도로교통법 제33조
697892015-09-12 19:17PDA한남동서울특별시 용산구 한남동 이태원로 22240000황색점선
151542015-02-25 09:00주행형CCTV이촌동서울특별시 용산구 이촌동 301-16040000도로교통법 제32조
846082015-11-16 16:10PDA한남동서울특별시 용산구 한남동 이태원로45길 3340000교통장애
185672015-03-10 10:31주행형CCTV남영동서울특별시 용산구 남영동 43-1040000도로교통법 제32조
184592015-03-09 18:56PDA원효로1동서울특별시 용산구 원효로1동 원효로90길40000보도주차
478452015-06-19 09:17PDA이태원2동서울특별시 용산구 이태원2동 소월로38길40000황색점선
787312015-10-23 20:12주행형CCTV한강로동서울특별시 용산구 한강로동 16-940000도로교통법 제32조
711452015-09-17 15:16주행형CCTV한강로동서울특별시 용산구 한강로동 15-1940000도로교통법 제32조
825012015-11-08 13:47주행형CCTV청파동1가서울특별시 용산구 청파동1가 180-2440000도로교통법 제32조

Duplicate rows

Most frequently occurring

단속일시단속구분단속동단속장소단속원금위반내용# duplicates
02015-01-02 10:20CCTV이촌동서울특별시 용산구 이촌동 이촌로40000도로교통법 제33조3
12015-01-02 10:21CCTV이촌동서울특별시 용산구 이촌동 이촌로2가길40000도로교통법 제33조3
122015-01-12 20:20CCTV한남동서울특별시 용산구 한남동 이태원로40000도로교통법 제33조3
952015-05-17 15:04주행형CCTV이촌동서울특별시 용산구 이촌동 301-16040000도로교통법 제32조3
1052015-06-01 14:50CCTV이촌동서울특별시 용산구 이촌동 이촌로40000도로교통법 제33조3
1092015-06-07 16:58CCTV이태원동서울특별시 용산구 이태원동 보광로40000도로교통법 제33조3
1402015-07-15 21:23CCTV한남동서울특별시 용산구 한남동 대사관로40000도로교통법 제33조3
2082015-11-09 09:48CCTV용산동5가서울특별시 용산구 용산동5가 한강대로3040000도로교통법 제33조3
2112015-11-09 14:32CCTV용문동서울특별시 용산구 용문동 효창원로40000도로교통법 제33조3
2392015-12-26 23:58PDA이태원1동서울특별시 용산구 이태원1동 우사단로10길40000황색점선3