Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows53
Duplicate rows (%)0.5%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

DateTime1
Numeric1
Categorical3
Text1

Dataset

Description서울특별시 광진구 주정차단속현황에 대한 데이터로, 단속일시, 과태료, 단속지역, 단속장소, 위반내용, 단속구분에 대한 내용을 제공합니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15034487/fileData.do

Alerts

Dataset has 53 (0.5%) duplicate rowsDuplicates
위반내용 is highly overall correlated with 단속구분High correlation
단속구분 is highly overall correlated with 위반내용High correlation

Reproduction

Analysis started2024-04-06 08:11:05.497095
Analysis finished2024-04-06 08:11:07.133621
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속일시
Date

Distinct9673
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-01-01 11:38:00
Maximum2016-07-18 20:12:00
2024-04-06T17:11:07.658556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:11:07.958506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

과태료
Real number (ℝ)

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36335
Minimum8000
Maximum90000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:11:08.167708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8000
5-th percentile32000
Q132000
median40000
Q340000
95-th percentile40000
Maximum90000
Range82000
Interquartile range (IQR)8000

Descriptive statistics

Standard deviation6611.7885
Coefficient of variation (CV)0.18196748
Kurtosis10.407731
Mean36335
Median Absolute Deviation (MAD)8000
Skewness0.32791982
Sum3.6335 × 108
Variance43715747
MonotonicityNot monotonic
2024-04-06T17:11:08.362505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
40000 4756
47.6%
32000 4659
46.6%
50000 340
 
3.4%
8000 117
 
1.2%
64000 44
 
0.4%
10000 38
 
0.4%
80000 29
 
0.3%
16000 12
 
0.1%
72000 4
 
< 0.1%
90000 1
 
< 0.1%
ValueCountFrequency (%)
8000 117
 
1.2%
10000 38
 
0.4%
16000 12
 
0.1%
32000 4659
46.6%
40000 4756
47.6%
50000 340
 
3.4%
64000 44
 
0.4%
72000 4
 
< 0.1%
80000 29
 
0.3%
90000 1
 
< 0.1%
ValueCountFrequency (%)
90000 1
 
< 0.1%
80000 29
 
0.3%
72000 4
 
< 0.1%
64000 44
 
0.4%
50000 340
 
3.4%
40000 4756
47.6%
32000 4659
46.6%
16000 12
 
0.1%
10000 38
 
0.4%
8000 117
 
1.2%

단속지역
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
구의동
2800 
자양동
1989 
화양동
1640 
중곡동
1254 
광장동
1048 
Other values (3)
1269 

Length

Max length4
Median length3
Mean length2.9889
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자양동
2nd row자양동
3rd row화양동
4th row구의동
5th row중곡동

Common Values

ValueCountFrequency (%)
구의동 2800
28.0%
자양동 1989
19.9%
화양동 1640
16.4%
중곡동 1254
12.5%
광장동 1048
 
10.5%
군자동 874
 
8.7%
능동 253
 
2.5%
능 동 142
 
1.4%

Length

2024-04-06T17:11:08.615062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:11:08.872541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구의동 2800
27.6%
자양동 1989
19.6%
화양동 1640
16.2%
중곡동 1254
12.4%
광장동 1048
 
10.3%
군자동 874
 
8.6%
능동 253
 
2.5%
능 142
 
1.4%
동 142
 
1.4%

단속장소
Text

Distinct6237
Distinct (%)62.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:11:09.425704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length5.6069
Min length3

Characters and Unicode

Total characters56069
Distinct characters62
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5896 ?
Unique (%)59.0%

Sample

1st row21398
2nd row508298
3rd row21398
4th row53418
5th row41974
ValueCountFrequency (%)
21398 3414
34.1%
건대역약국앞 9
 
0.1%
강변역1번출구 5
 
< 0.1%
838690 2
 
< 0.1%
198023 2
 
< 0.1%
484404 2
 
< 0.1%
511797 2
 
< 0.1%
353192 2
 
< 0.1%
797478 2
 
< 0.1%
312740 2
 
< 0.1%
Other values (6230) 6561
65.6%
2024-04-06T17:11:10.373078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7579
13.5%
9 7387
13.2%
2 7322
13.1%
8 7315
13.0%
3 7225
12.9%
4 3979
7.1%
7 3957
7.1%
5 3911
7.0%
6 3900
7.0%
0 3343
6.0%
Other values (52) 151
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55918
99.7%
Other Letter 146
 
0.3%
Space Separator 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 16
 
11.0%
앞 14
 
9.6%
대 12
 
8.2%
건 10
 
6.8%
국 10
 
6.8%
약 9
 
6.2%
번 6
 
4.1%
변 6
 
4.1%
강 6
 
4.1%
구 5
 
3.4%
Other values (40) 52
35.6%
Decimal Number
ValueCountFrequency (%)
1 7579
13.6%
9 7387
13.2%
2 7322
13.1%
8 7315
13.1%
3 7225
12.9%
4 3979
7.1%
7 3957
7.1%
5 3911
7.0%
6 3900
7.0%
0 3343
6.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 55923
99.7%
Hangul 146
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 16
 
11.0%
앞 14
 
9.6%
대 12
 
8.2%
건 10
 
6.8%
국 10
 
6.8%
약 9
 
6.2%
번 6
 
4.1%
변 6
 
4.1%
강 6
 
4.1%
구 5
 
3.4%
Other values (40) 52
35.6%
Common
ValueCountFrequency (%)
1 7579
13.6%
9 7387
13.2%
2 7322
13.1%
8 7315
13.1%
3 7225
12.9%
4 3979
7.1%
7 3957
7.1%
5 3911
7.0%
6 3900
7.0%
0 3343
6.0%
Other values (2) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55923
99.7%
Hangul 146
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7579
13.6%
9 7387
13.2%
2 7322
13.1%
8 7315
13.1%
3 7225
12.9%
4 3979
7.1%
7 3957
7.1%
5 3911
7.0%
6 3900
7.0%
0 3343
6.0%
Other values (2) 5
 
< 0.1%
Hangul
ValueCountFrequency (%)
역 16
 
11.0%
앞 14
 
9.6%
대 12
 
8.2%
건 10
 
6.8%
국 10
 
6.8%
약 9
 
6.2%
번 6
 
4.1%
변 6
 
4.1%
강 6
 
4.1%
구 5
 
3.4%
Other values (40) 52
35.6%

위반내용
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주정차위반
3213 
32조내지 34조위반
3174 
주정차금지
1623 
도로교통법 제32조
836 
보도주차
492 
Other values (21)
662 

Length

Max length11
Median length10
Mean length7.2686
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row주정차위반
2nd row주정차위반
3rd row주정차금지
4th row32조내지 34조위반
5th row주정차금지

Common Values

ValueCountFrequency (%)
주정차위반 3213
32.1%
32조내지 34조위반 3174
31.7%
주정차금지 1623
16.2%
도로교통법 제32조 836
 
8.4%
보도주차 492
 
4.9%
버스정류장 111
 
1.1%
안전지대사방 101
 
1.0%
횡단보도 96
 
1.0%
어린이보호구역 79
 
0.8%
소통장해 58
 
0.6%
Other values (16) 217
 
2.2%

Length

2024-04-06T17:11:10.645555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주정차위반 3213
22.9%
32조내지 3174
22.6%
34조위반 3174
22.6%
주정차금지 1623
11.6%
도로교통법 844
 
6.0%
제32조 836
 
6.0%
보도주차 492
 
3.5%
버스정류장 111
 
0.8%
안전지대사방 101
 
0.7%
횡단보도 96
 
0.7%
Other values (18) 354
 
2.5%

단속구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
PDA
4035 
CCTV
3174 
주행형CCTV
2527 
고정형CCTV
 
258
버스장착형CCTV
 
6

Length

Max length9
Median length7
Mean length4.435
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
PDA 4035
40.4%
CCTV 3174
31.7%
주행형CCTV 2527
25.3%
고정형CCTV 258
 
2.6%
버스장착형CCTV 6
 
0.1%

Length

2024-04-06T17:11:10.910053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:11:11.208319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pda 4035
40.4%
cctv 3174
31.7%
주행형cctv 2527
25.3%
고정형cctv 258
 
2.6%
버스장착형cctv 6
 
0.1%

Interactions

2024-04-06T17:11:06.564001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:11:11.413618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과태료단속지역위반내용단속구분
과태료1.0000.1780.7030.101
단속지역0.1781.0000.5080.426
위반내용0.7030.5081.0000.883
단속구분0.1010.4260.8831.000
2024-04-06T17:11:11.595568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단속지역위반내용단속구분
단속지역1.0000.2300.278
위반내용0.2301.0000.665
단속구분0.2780.6651.000
2024-04-06T17:11:11.782795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과태료단속지역위반내용단속구분
과태료1.0000.0660.3710.061
단속지역0.0661.0000.2300.278
위반내용0.3710.2301.0000.665
단속구분0.0610.2780.6651.000

Missing values

2024-04-06T17:11:06.780165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:11:07.040801image/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

단속일시과태료단속지역단속장소위반내용단속구분
638902015-12-09 19:18:0032000자양동21398주정차위반주행형CCTV
817892016-04-12 08:16:0040000자양동508298주정차위반주행형CCTV
421322015-07-26 11:09:0032000화양동21398주정차금지PDA
13082015-01-07 23:13:0032000구의동5341832조내지 34조위반CCTV
664682015-12-26 22:04:0040000중곡동41974주정차금지PDA
332592015-06-05 12:24:0040000군자동2139832조내지 34조위반CCTV
210252015-04-08 15:25:0032000구의동653542주정차위반고정형CCTV
566692015-10-31 21:16:0040000구의동2139832조내지 34조위반CCTV
464162015-08-24 20:03:0040000자양동21398주정차위반주행형CCTV
601392015-11-18 12:37:0040000구의동21398주정차위반주행형CCTV
단속일시과태료단속지역단속장소위반내용단속구분
456192015-08-19 20:53:0040000구의동21398주정차위반고정형CCTV
625482015-12-01 17:13:0032000구의동21398주정차금지PDA
899772016-05-28 14:38:0040000군자동757515주정차위반PDA
32782015-01-15 18:59:0040000자양동113378주정차금지PDA
783892016-03-23 09:27:0032000광장동40481132조내지 34조위반CCTV
775702016-03-18 18:49:0040000중곡동37988532조내지 34조위반CCTV
769902016-03-15 21:18:0032000구의동36223132조내지 34조위반CCTV
836642016-04-22 19:24:0032000광장동565366주정차금지PDA
324992015-05-31 12:24:0040000구의동1002774주정차금지PDA
519362015-10-05 00:55:0040000구의동21398도로교통법 제32조PDA

Duplicate rows

Most frequently occurring

단속일시과태료단속지역단속장소위반내용단속구분# duplicates
232015-08-22 23:50:0032000화양동21398도로교통법 제32조PDA3
282015-09-16 14:13:0040000중곡동2139832조내지 34조위반CCTV3
02015-06-05 15:02:0032000광장동2139832조내지 34조위반CCTV2
12015-06-06 13:35:0040000광장동21398주정차위반주행형CCTV2
22015-06-07 23:50:0040000구의동21398도로교통법 제32조PDA2
32015-06-11 23:40:0040000구의동21398도로교통법 제32조PDA2
42015-06-16 16:17:0032000광장동21398주정차위반주행형CCTV2
52015-06-18 11:12:0032000광장동21398주정차위반주행형CCTV2
62015-06-18 14:18:0040000중곡동2139832조내지 34조위반CCTV2
72015-06-19 14:14:0040000중곡동2139832조내지 34조위반CCTV2