Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory566.4 KiB
Average record size in memory58.0 B

Variable types

Numeric2
DateTime1
Categorical2
Text1

Dataset

Description서울특별시 양천구 주정차 위반 단속 현황(단속일시, 단속원금, 단속동, 단속장소, 위반내용, 견인지시)등을 제공합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15083930/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2024-01-14 13:29:05.847050
Analysis finished2024-01-14 13:29:07.516030
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32255.513
Minimum9
Maximum64418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T22:29:07.614979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile3119.8
Q116317.25
median31968
Q348481.25
95-th percentile61274.25
Maximum64418
Range64409
Interquartile range (IQR)32164

Descriptive statistics

Standard deviation18650.914
Coefficient of variation (CV)0.57822406
Kurtosis-1.2036507
Mean32255.513
Median Absolute Deviation (MAD)16082.5
Skewness-0.00097966667
Sum3.2255513 × 108
Variance3.4785658 × 108
MonotonicityNot monotonic
2024-01-14T22:29:07.772211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
524 1
 
< 0.1%
15295 1
 
< 0.1%
22642 1
 
< 0.1%
24383 1
 
< 0.1%
19122 1
 
< 0.1%
53432 1
 
< 0.1%
49822 1
 
< 0.1%
40991 1
 
< 0.1%
56352 1
 
< 0.1%
57016 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
9 1
< 0.1%
18 1
< 0.1%
20 1
< 0.1%
26 1
< 0.1%
28 1
< 0.1%
55 1
< 0.1%
62 1
< 0.1%
63 1
< 0.1%
66 1
< 0.1%
83 1
< 0.1%
ValueCountFrequency (%)
64418 1
< 0.1%
64412 1
< 0.1%
64404 1
< 0.1%
64403 1
< 0.1%
64400 1
< 0.1%
64381 1
< 0.1%
64373 1
< 0.1%
64372 1
< 0.1%
64362 1
< 0.1%
64347 1
< 0.1%

단속일시
Date

Distinct9793
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 01:33:00
Maximum2023-12-26 20:47:00
2024-01-14T22:29:07.958572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:08.203208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

단속원금
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46462
Minimum10000
Maximum130000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-14T22:29:08.563942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile40000
Q140000
median40000
Q340000
95-th percentile120000
Maximum130000
Range120000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22537.377
Coefficient of variation (CV)0.48507117
Kurtosis6.5457422
Mean46462
Median Absolute Deviation (MAD)0
Skewness2.778033
Sum4.6462 × 108
Variance5.0793335 × 108
MonotonicityNot monotonic
2024-01-14T22:29:08.762722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
40000 8569
85.7%
120000 801
 
8.0%
50000 404
 
4.0%
10000 177
 
1.8%
130000 17
 
0.2%
20000 17
 
0.2%
80000 13
 
0.1%
90000 2
 
< 0.1%
ValueCountFrequency (%)
10000 177
 
1.8%
20000 17
 
0.2%
40000 8569
85.7%
50000 404
 
4.0%
80000 13
 
0.1%
90000 2
 
< 0.1%
120000 801
 
8.0%
130000 17
 
0.2%
ValueCountFrequency (%)
130000 17
 
0.2%
120000 801
 
8.0%
90000 2
 
< 0.1%
80000 13
 
0.1%
50000 404
 
4.0%
40000 8569
85.7%
20000 17
 
0.2%
10000 177
 
1.8%

단속동
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신정동
3720 
목동
3161 
신월동
2953 
목 동
 
149
양천구
 
13

Length

Max length5
Median length3
Mean length2.6996
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신정동
2nd row신월동
3rd row신월동
4th row목동
5th row신월동

Common Values

ValueCountFrequency (%)
신정동 3720
37.2%
목동 3161
31.6%
신월동 2953
29.5%
목 동 149
 
1.5%
양천구 13
 
0.1%
시민신고웹 4
 
< 0.1%

Length

2024-01-14T22:29:08.959356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-14T22:29:09.213966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신정동 3720
36.7%
목동 3161
31.1%
신월동 2953
29.1%
목 149
 
1.5%
동 149
 
1.5%
양천구 13
 
0.1%
시민신고웹 4
 
< 0.1%

단속장소
Text

Distinct3238
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-14T22:29:09.668796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length14.4413
Min length2

Characters and Unicode

Total characters144413
Distinct characters347
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2095 ?
Unique (%)20.9%

Sample

1st row목동신시가지 14단지 앞 삼거리
2nd row796 부근
3rd row신월7동 우리은행 주변
4th row목5동 이대목동병원 주변
5th row서울특별시 양천구 오목로15길 7
ValueCountFrequency (%)
양천구 5695
 
16.7%
서울 4020
 
11.8%
주변 1913
 
5.6%
서울특별시 1675
 
4.9%
목동 1426
 
4.2%
신월동 1339
 
3.9%
신정동 1304
 
3.8%
부근 686
 
2.0%
목1동 366
 
1.1%
후문 255
 
0.7%
Other values (2424) 15415
45.2%
2024-01-14T22:29:10.318795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24098
 
16.7%
동 7752
 
5.4%
서 6442
 
4.5%
1 6020
 
4.2%
양 5995
 
4.2%
구 5965
 
4.1%
울 5788
 
4.0%
천 5783
 
4.0%
목 4082
 
2.8%
2 3876
 
2.7%
Other values (337) 68612
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86512
59.9%
Decimal Number 29029
 
20.1%
Space Separator 24098
 
16.7%
Dash Punctuation 2854
 
2.0%
Open Punctuation 767
 
0.5%
Close Punctuation 666
 
0.5%
Uppercase Letter 235
 
0.2%
Other Punctuation 215
 
0.1%
Lowercase Letter 33
 
< 0.1%
Letter Number 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7752
 
9.0%
서 6442
 
7.4%
양 5995
 
6.9%
구 5965
 
6.9%
울 5788
 
6.7%
천 5783
 
6.7%
목 4082
 
4.7%
신 3861
 
4.5%
로 2576
 
3.0%
정 2362
 
2.7%
Other values (301) 35906
41.5%
Uppercase Letter
ValueCountFrequency (%)
S 115
48.9%
B 57
24.3%
H 11
 
4.7%
D 11
 
4.7%
C 10
 
4.3%
I 8
 
3.4%
T 5
 
2.1%
P 4
 
1.7%
A 4
 
1.7%
K 3
 
1.3%
Other values (4) 7
 
3.0%
Decimal Number
ValueCountFrequency (%)
1 6020
20.7%
2 3876
13.4%
3 3410
11.7%
0 2888
9.9%
4 2244
 
7.7%
9 2212
 
7.6%
5 2184
 
7.5%
6 2160
 
7.4%
7 2040
 
7.0%
8 1995
 
6.9%
Other Punctuation
ValueCountFrequency (%)
, 192
89.3%
; 11
 
5.1%
& 11
 
5.1%
. 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
p 11
33.3%
m 11
33.3%
a 11
33.3%
Space Separator
ValueCountFrequency (%)
24098
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2854
100.0%
Open Punctuation
ValueCountFrequency (%)
( 767
100.0%
Close Punctuation
ValueCountFrequency (%)
) 666
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86512
59.9%
Common 57629
39.9%
Latin 272
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7752
 
9.0%
서 6442
 
7.4%
양 5995
 
6.9%
구 5965
 
6.9%
울 5788
 
6.7%
천 5783
 
6.7%
목 4082
 
4.7%
신 3861
 
4.5%
로 2576
 
3.0%
정 2362
 
2.7%
Other values (301) 35906
41.5%
Common
ValueCountFrequency (%)
24098
41.8%
1 6020
 
10.4%
2 3876
 
6.7%
3 3410
 
5.9%
0 2888
 
5.0%
- 2854
 
5.0%
4 2244
 
3.9%
9 2212
 
3.8%
5 2184
 
3.8%
6 2160
 
3.7%
Other values (8) 5683
 
9.9%
Latin
ValueCountFrequency (%)
S 115
42.3%
B 57
21.0%
p 11
 
4.0%
H 11
 
4.0%
m 11
 
4.0%
a 11
 
4.0%
D 11
 
4.0%
C 10
 
3.7%
I 8
 
2.9%
T 5
 
1.8%
Other values (8) 22
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86510
59.9%
ASCII 57897
40.1%
Number Forms 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24098
41.6%
1 6020
 
10.4%
2 3876
 
6.7%
3 3410
 
5.9%
0 2888
 
5.0%
- 2854
 
4.9%
4 2244
 
3.9%
9 2212
 
3.8%
5 2184
 
3.8%
6 2160
 
3.7%
Other values (25) 5951
 
10.3%
Hangul
ValueCountFrequency (%)
동 7752
 
9.0%
서 6442
 
7.4%
양 5995
 
6.9%
구 5965
 
6.9%
울 5788
 
6.7%
천 5783
 
6.7%
목 4082
 
4.7%
신 3861
 
4.5%
로 2576
 
3.0%
정 2362
 
2.7%
Other values (300) 35904
41.5%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 2
100.0%

위반내용
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주차금지(황색점선)구역
2460 
교통소통장애
1476 
보도
1184 
주정차금지(황색실선)구역
1115 
횡단보도
1057 
Other values (14)
2708 

Length

Max length13
Median length12
Mean length7.4163
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row주정차금지(황색실선)구역
2nd row횡단보도
3rd row주차금지(황색점선)구역
4th row주차방법위반
5th row주정차금지(황색실선)구역

Common Values

ValueCountFrequency (%)
주차금지(황색점선)구역 2460
24.6%
교통소통장애 1476
14.8%
보도 1184
11.8%
주정차금지(황색실선)구역 1115
11.2%
횡단보도 1057
10.6%
도로 모퉁이 990
9.9%
주차방법위반 557
 
5.6%
소화전 464
 
4.6%
안전지대 297
 
3.0%
주차구획선외 주차 153
 
1.5%
Other values (9) 247
 
2.5%

Length

2024-01-14T22:29:10.486035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주차금지(황색점선)구역 2460
22.0%
교통소통장애 1476
13.2%
보도 1184
10.6%
주정차금지(황색실선)구역 1115
10.0%
횡단보도 1057
9.5%
도로 990
8.9%
모퉁이 990
8.9%
주차방법위반 557
 
5.0%
소화전 464
 
4.1%
안전지대 297
 
2.7%
Other values (12) 594
 
5.3%

Interactions

2024-01-14T22:29:06.953959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:06.673611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:07.084580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-14T22:29:06.812793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-14T22:29:10.592242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속원금단속동위반내용
연번1.0000.0580.0930.134
단속원금0.0581.0000.1540.548
단속동0.0930.1541.0000.359
위반내용0.1340.5480.3591.000
2024-01-14T22:29:10.756761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속동위반내용
단속동1.0000.175
위반내용0.1751.000
2024-01-14T22:29:10.908426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속원금단속동위반내용
연번1.000-0.0220.0490.050
단속원금-0.0221.0000.0560.290
단속동0.0490.0561.0000.175
위반내용0.0500.2900.1751.000

Missing values

2024-01-14T22:29:07.282094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-14T22:29:07.439232image/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

연번단속일시단속원금단속동단속장소위반내용
5235242023-01-04 08:44120000신정동목동신시가지 14단지 앞 삼거리주정차금지(황색실선)구역
25889258902023-06-11 15:3740000신월동796 부근횡단보도
36946369472023-08-11 20:2440000신월동신월7동 우리은행 주변주차금지(황색점선)구역
40440404412023-08-29 20:4710000목동목5동 이대목동병원 주변주차방법위반
18697186982023-04-29 11:1240000신월동서울특별시 양천구 오목로15길 7주정차금지(황색실선)구역
22041220422023-05-17 18:59120000목동서울특별시 양천구 목동동로 202주차방법위반
37776377772023-08-16 10:0340000신정동홍익병원앞 부근주차금지(황색점선)구역
39658396592023-08-25 18:4040000신월동강서초교 후문 주변주차금지(황색점선)구역
13351133522023-03-28 14:2040000신월동서울특별시 양천구 가로공원로 128교통소통장애
50462504632023-10-16 15:3940000신정동서울 양천구 신정동 1121교통소통장애
연번단속일시단속원금단속동단속장소위반내용
848584862023-02-24 16:2040000목동서울 양천구 목동서로 61 (목동)교통소통장애
54758547592023-11-05 19:1340000신월동서울특별시 양천구 남부순환로29길 35교통소통장애
38689386902023-08-20 21:0240000신월동서울특별시 양천구 남부순환로58길 32소방차(긴급차량)통행장애
10962109632023-03-13 20:1240000신정동서부식자재마트 맞은편 정류장 주변주정차금지(황색실선)구역
243224332023-01-16 14:4740000신월동서울특별시 양천구 남부순환로70길 19-10도로 모퉁이
35042350432023-08-01 18:4540000목동서울 양천구 목동 907-19교통소통장애
34108341092023-07-27 05:0440000신정동서울 양천구 신정동 1096도로 모퉁이
34263342642023-07-27 23:3540000신월동서울 양천구 남부순환로40길 65-20 (신월동)도로 모퉁이
51213512142023-10-20 07:4240000목동서울 양천구 목동 901-8교통소통장애
38623386242023-08-20 14:1640000신월동서울 양천구 신월동 783소화전