Overview

Dataset statistics

Number of variables5
Number of observations2835
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory116.4 KiB
Average record size in memory42.0 B

Variable types

Numeric1
DateTime1
Text1
Categorical2

Dataset

Description대전광역시 서구 거주자우선주차시스템 단속현황(단속일자, 단속시간, 단속장소, 금액, 최종처리상태)을 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15088577/fileData.do

Alerts

원금 has constant value ""Constant
순번 is highly overall correlated with 최종처리상태High correlation
최종처리상태 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:37:18.635994
Analysis finished2023-12-12 20:37:19.162941
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2835
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1418
Minimum1
Maximum2835
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.0 KiB
2023-12-13T05:37:19.233755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile142.7
Q1709.5
median1418
Q32126.5
95-th percentile2693.3
Maximum2835
Range2834
Interquartile range (IQR)1417

Descriptive statistics

Standard deviation818.53833
Coefficient of variation (CV)0.57724847
Kurtosis-1.2
Mean1418
Median Absolute Deviation (MAD)709
Skewness0
Sum4020030
Variance670005
MonotonicityStrictly increasing
2023-12-13T05:37:19.399156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1863 1
 
< 0.1%
1887 1
 
< 0.1%
1888 1
 
< 0.1%
1889 1
 
< 0.1%
1890 1
 
< 0.1%
1891 1
 
< 0.1%
1892 1
 
< 0.1%
1893 1
 
< 0.1%
1894 1
 
< 0.1%
Other values (2825) 2825
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2835 1
< 0.1%
2834 1
< 0.1%
2833 1
< 0.1%
2832 1
< 0.1%
2831 1
< 0.1%
2830 1
< 0.1%
2829 1
< 0.1%
2828 1
< 0.1%
2827 1
< 0.1%
2826 1
< 0.1%

단속일자
Date

Distinct2741
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size22.3 KiB
Minimum2022-09-01 22:00:00
Maximum2023-09-01 22:32:00
2023-12-13T05:37:19.598731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:37:19.774837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

위반장소
Text

Distinct745
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Memory size22.3 KiB
2023-12-13T05:37:20.195071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.6183422
Min length4

Characters and Unicode

Total characters15928
Distinct characters24
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

Unique314 ?
Unique (%)11.1%

Sample

1st row갈마 139
2nd row괴정 공영
3rd row내동 38
4th row내동 216
5th row도마 75
ValueCountFrequency (%)
변동 1069
18.9%
공영 690
 
12.2%
갈마 604
 
10.7%
내동 459
 
8.1%
괴정 423
 
7.5%
가장 207
 
3.7%
582 73
 
1.3%
도마 72
 
1.3%
581 50
 
0.9%
584 32
 
0.6%
Other values (479) 1990
35.1%
2023-12-13T05:37:20.862951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2834
17.8%
동 1529
 
9.6%
변 1070
 
6.7%
2 914
 
5.7%
3 839
 
5.3%
5 836
 
5.2%
1 732
 
4.6%
영 690
 
4.3%
공 690
 
4.3%
마 676
 
4.2%
Other values (14) 5118
32.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7050
44.3%
Decimal Number 6001
37.7%
Space Separator 2834
17.8%
Dash Punctuation 43
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1529
21.7%
변 1070
15.2%
영 690
9.8%
공 690
9.8%
마 676
9.6%
갈 604
 
8.6%
내 459
 
6.5%
괴 423
 
6.0%
정 423
 
6.0%
장 207
 
2.9%
Other values (2) 279
 
4.0%
Decimal Number
ValueCountFrequency (%)
2 914
15.2%
3 839
14.0%
5 836
13.9%
1 732
12.2%
4 585
9.7%
8 500
8.3%
6 494
8.2%
7 398
6.6%
0 353
 
5.9%
9 350
 
5.8%
Space Separator
ValueCountFrequency (%)
2834
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8878
55.7%
Hangul 7050
44.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2834
31.9%
2 914
 
10.3%
3 839
 
9.5%
5 836
 
9.4%
1 732
 
8.2%
4 585
 
6.6%
8 500
 
5.6%
6 494
 
5.6%
7 398
 
4.5%
0 353
 
4.0%
Other values (2) 393
 
4.4%
Hangul
ValueCountFrequency (%)
동 1529
21.7%
변 1070
15.2%
영 690
9.8%
공 690
9.8%
마 676
9.6%
갈 604
 
8.6%
내 459
 
6.5%
괴 423
 
6.0%
정 423
 
6.0%
장 207
 
2.9%
Other values (2) 279
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8878
55.7%
Hangul 7050
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2834
31.9%
2 914
 
10.3%
3 839
 
9.5%
5 836
 
9.4%
1 732
 
8.2%
4 585
 
6.6%
8 500
 
5.6%
6 494
 
5.6%
7 398
 
4.5%
0 353
 
4.0%
Other values (2) 393
 
4.4%
Hangul
ValueCountFrequency (%)
동 1529
21.7%
변 1070
15.2%
영 690
9.8%
공 690
9.8%
마 676
9.6%
갈 604
 
8.6%
내 459
 
6.5%
괴 423
 
6.0%
정 423
 
6.0%
장 207
 
2.9%
Other values (2) 279
 
4.0%

원금
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.3 KiB
7200
2835 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7200
2nd row7200
3rd row7200
4th row7200
5th row7200

Common Values

ValueCountFrequency (%)
7200 2835
100.0%

Length

2023-12-13T05:37:21.020671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:37:21.124777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7200 2835
100.0%

최종처리상태
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size22.3 KiB
수납
1522 
압류예정
642 
압류예정수납
354 
고지서발송
303 
결손
 
12
Other values (2)
 
2

Length

Max length6
Median length2
Mean length3.2751323
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
수납 1522
53.7%
압류예정 642
22.6%
압류예정수납 354
 
12.5%
고지서발송 303
 
10.7%
결손 12
 
0.4%
부과취소 1
 
< 0.1%
압류예정결손 1
 
< 0.1%

Length

2023-12-13T05:37:21.270175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:37:21.415420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수납 1522
53.7%
압류예정 642
22.6%
압류예정수납 354
 
12.5%
고지서발송 303
 
10.7%
결손 12
 
0.4%
부과취소 1
 
< 0.1%
압류예정결손 1
 
< 0.1%

Interactions

2023-12-13T05:37:18.845525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:37:21.517627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번최종처리상태
순번1.0000.786
최종처리상태0.7861.000
2023-12-13T05:37:21.635456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번최종처리상태
순번1.0000.555
최종처리상태0.5551.000

Missing values

2023-12-13T05:37:19.001651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:37:19.118802image/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

순번단속일자위반장소원금최종처리상태
012023-06-01 20:45갈마 1397200고지서발송
122023-06-01 20:08괴정 공영7200고지서발송
232023-06-01 22:10내동 387200고지서발송
342023-06-01 22:30내동 2167200고지서발송
452023-06-01 21:00도마 757200고지서발송
562023-06-01 21:39변동 공영7200고지서발송
672023-08-31 22:37변동 공영7200고지서발송
782023-08-31 21:29변동 5827200고지서발송
892023-08-31 22:52변동 5827200고지서발송
9102023-08-30 21:30변동 5487200고지서발송
순번단속일자위반장소원금최종처리상태
282528262023-02-24 20:12가장 2347200압류예정
282628272023-02-24 21:41괴정 2687200압류예정수납
282728282023-02-13 22:05갈마 4157200압류예정
282828292023-02-13 21:51괴정 3097200압류예정
282928302023-02-14 19:53갈마 5347200압류예정
283028312023-02-14 20:05갈마 4157200압류예정
283128322023-02-14 19:16변동 5877200압류예정수납
283228332023-02-15 21:32가장 1157200압류예정
283328342023-02-15 21:31내동 2907200압류예정
283428352023-02-15 21:50도마 287200압류예정