Overview

Dataset statistics

Number of variables7
Number of observations1700
Missing cells123
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory98.1 KiB
Average record size in memory59.1 B

Variable types

Numeric3
DateTime2
Text2

Dataset

Description부천시 관내의 자동차세 체납차량 번호판 영치 내역 현황 정보로 영치날짜, 차량번호, 체납건수, 체납금액, 영치장소, 반환일자 등에 대한 자료를 제공하고 있습니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/15064261/fileData.do

Alerts

체납건수 is highly overall correlated with 체납금액(원)High correlation
체납금액(원) is highly overall correlated with 체납건수High correlation
반환일자 has 123 (7.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:25:46.258849
Analysis finished2023-12-12 01:25:47.812713
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1700
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean850.5
Minimum1
Maximum1700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2023-12-12T10:25:47.896740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile85.95
Q1425.75
median850.5
Q31275.25
95-th percentile1615.05
Maximum1700
Range1699
Interquartile range (IQR)849.5

Descriptive statistics

Standard deviation490.89205
Coefficient of variation (CV)0.57718054
Kurtosis-1.2
Mean850.5
Median Absolute Deviation (MAD)425
Skewness0
Sum1445850
Variance240975
MonotonicityStrictly increasing
2023-12-12T10:25:48.069833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1144 1
 
0.1%
1142 1
 
0.1%
1141 1
 
0.1%
1140 1
 
0.1%
1139 1
 
0.1%
1138 1
 
0.1%
1137 1
 
0.1%
1136 1
 
0.1%
1135 1
 
0.1%
Other values (1690) 1690
99.4%
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 (%)
1700 1
0.1%
1699 1
0.1%
1698 1
0.1%
1697 1
0.1%
1696 1
0.1%
1695 1
0.1%
1694 1
0.1%
1693 1
0.1%
1692 1
0.1%
1691 1
0.1%

영치날짜
Date

Distinct145
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
Minimum2022-01-04 00:00:00
Maximum2022-09-15 00:00:00
2023-12-12T10:25:48.259020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:48.386624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차량번호
Text

Distinct1236
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2023-12-12T10:25:48.802558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.991765
Min length9

Characters and Unicode

Total characters18686
Distinct characters45
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

Unique890 ?
Unique (%)52.4%

Sample

1st row5*부3***
2nd row3*저5***
3rd row5*나0***
4th row6*가0***
5th row1*루3***
ValueCountFrequency (%)
2*도6 5
 
0.3%
1*어6 5
 
0.3%
2*모4 5
 
0.3%
6*너5 5
 
0.3%
1*버0 5
 
0.3%
6*거1 5
 
0.3%
0*누6 5
 
0.3%
2*보2 4
 
0.2%
6*루3 4
 
0.2%
1*조4 4
 
0.2%
Other values (1226) 1653
97.2%
2023-12-12T10:25:49.353677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 6800
36.4%
6565
35.1%
3 492
 
2.6%
2 481
 
2.6%
1 478
 
2.6%
6 417
 
2.2%
5 400
 
2.1%
4 385
 
2.1%
0 362
 
1.9%
8 207
 
1.1%
Other values (35) 2099
 
11.2%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 6800
36.4%
Space Separator 6565
35.1%
Decimal Number 3621
19.4%
Other Letter 1700
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 66
 
3.9%
수 66
 
3.9%
도 64
 
3.8%
루 62
 
3.6%
라 62
 
3.6%
어 62
 
3.6%
주 62
 
3.6%
모 58
 
3.4%
고 58
 
3.4%
마 58
 
3.4%
Other values (23) 1082
63.6%
Decimal Number
ValueCountFrequency (%)
3 492
13.6%
2 481
13.3%
1 478
13.2%
6 417
11.5%
5 400
11.0%
4 385
10.6%
0 362
10.0%
8 207
5.7%
7 206
5.7%
9 193
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 6800
100.0%
Space Separator
ValueCountFrequency (%)
6565
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16986
90.9%
Hangul 1700
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 66
 
3.9%
수 66
 
3.9%
도 64
 
3.8%
루 62
 
3.6%
라 62
 
3.6%
어 62
 
3.6%
주 62
 
3.6%
모 58
 
3.4%
고 58
 
3.4%
마 58
 
3.4%
Other values (23) 1082
63.6%
Common
ValueCountFrequency (%)
* 6800
40.0%
6565
38.6%
3 492
 
2.9%
2 481
 
2.8%
1 478
 
2.8%
6 417
 
2.5%
5 400
 
2.4%
4 385
 
2.3%
0 362
 
2.1%
8 207
 
1.2%
Other values (2) 399
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16986
90.9%
Hangul 1700
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 6800
40.0%
6565
38.6%
3 492
 
2.9%
2 481
 
2.8%
1 478
 
2.8%
6 417
 
2.5%
5 400
 
2.4%
4 385
 
2.3%
0 362
 
2.1%
8 207
 
1.2%
Other values (2) 399
 
2.3%
Hangul
ValueCountFrequency (%)
가 66
 
3.9%
수 66
 
3.9%
도 64
 
3.8%
루 62
 
3.6%
라 62
 
3.6%
어 62
 
3.6%
주 62
 
3.6%
모 58
 
3.4%
고 58
 
3.4%
마 58
 
3.4%
Other values (23) 1082
63.6%

체납건수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4870588
Minimum0
Maximum37
Zeros8
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2023-12-12T10:25:49.485933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile7
Maximum37
Range37
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3374419
Coefficient of variation (CV)0.93984183
Kurtosis41.962849
Mean2.4870588
Median Absolute Deviation (MAD)1
Skewness4.5784702
Sum4228
Variance5.4636347
MonotonicityNot monotonic
2023-12-12T10:25:49.618084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 683
40.2%
2 464
27.3%
3 223
 
13.1%
4 122
 
7.2%
5 64
 
3.8%
6 50
 
2.9%
7 27
 
1.6%
8 15
 
0.9%
9 14
 
0.8%
11 9
 
0.5%
Other values (10) 29
 
1.7%
ValueCountFrequency (%)
0 8
 
0.5%
1 683
40.2%
2 464
27.3%
3 223
 
13.1%
4 122
 
7.2%
5 64
 
3.8%
6 50
 
2.9%
7 27
 
1.6%
8 15
 
0.9%
9 14
 
0.8%
ValueCountFrequency (%)
37 1
 
0.1%
27 1
 
0.1%
20 1
 
0.1%
19 2
 
0.1%
16 1
 
0.1%
14 2
 
0.1%
13 2
 
0.1%
12 2
 
0.1%
11 9
0.5%
10 9
0.5%

체납금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct1086
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean388101.55
Minimum0
Maximum4151740
Zeros8
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2023-12-12T10:25:49.754094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile133750
Q1203925
median278805
Q3451080
95-th percentile988293.5
Maximum4151740
Range4151740
Interquartile range (IQR)247155

Descriptive statistics

Standard deviation324801.84
Coefficient of variation (CV)0.8368991
Kurtosis21.137886
Mean388101.55
Median Absolute Deviation (MAD)102195
Skewness3.524629
Sum6.5977264 × 108
Variance1.0549624 × 1011
MonotonicityNot monotonic
2023-12-12T10:25:50.177621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
133750 27
 
1.6%
267500 26
 
1.5%
173620 20
 
1.2%
266560 18
 
1.1%
186970 18
 
1.1%
177810 16
 
0.9%
227040 15
 
0.9%
220810 15
 
0.9%
213690 13
 
0.8%
223740 13
 
0.8%
Other values (1076) 1519
89.4%
ValueCountFrequency (%)
0 8
0.5%
18890 1
 
0.1%
27880 4
0.2%
28420 1
 
0.1%
31190 1
 
0.1%
55760 1
 
0.1%
63590 1
 
0.1%
63600 1
 
0.1%
66620 1
 
0.1%
76730 1
 
0.1%
ValueCountFrequency (%)
4151740 1
0.1%
2993510 1
0.1%
2707430 1
0.1%
2649440 1
0.1%
2516260 1
0.1%
2412950 1
0.1%
2200800 1
0.1%
2000120 1
0.1%
1943200 1
0.1%
1929720 1
0.1%

영치장소
Text

Distinct1360
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size13.4 KiB
2023-12-12T10:25:50.486386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length13.803529
Min length3

Characters and Unicode

Total characters23466
Distinct characters242
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1228 ?
Unique (%)72.2%

Sample

1st row부천시 중동 592-7
2nd row부천종합운동장
3rd row부천시 중동 593-13
4th row부천시 심곡동 142-14
5th row부천시 부일로356번길 11
ValueCountFrequency (%)
부천시 1534
31.2%
원종1동 110
 
2.2%
중동 109
 
2.2%
상동 50
 
1.0%
도당동 49
 
1.0%
송내동 47
 
1.0%
심곡동 45
 
0.9%
성곡동 45
 
0.9%
심곡본동 44
 
0.9%
원종동 43
 
0.9%
Other values (1571) 2834
57.7%
2023-12-12T10:25:50.966844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4574
19.5%
부 1636
 
7.0%
천 1593
 
6.8%
시 1547
 
6.6%
1 1545
 
6.6%
동 1330
 
5.7%
- 984
 
4.2%
2 912
 
3.9%
3 909
 
3.9%
4 584
 
2.5%
Other values (232) 7852
33.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11036
47.0%
Decimal Number 6751
28.8%
Space Separator 4574
19.5%
Dash Punctuation 984
 
4.2%
Close Punctuation 58
 
0.2%
Open Punctuation 58
 
0.2%
Uppercase Letter 3
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 1636
14.8%
천 1593
14.4%
시 1547
14.0%
동 1330
12.1%
로 409
 
3.7%
길 313
 
2.8%
곡 302
 
2.7%
번 294
 
2.7%
원 249
 
2.3%
중 215
 
1.9%
Other values (214) 3148
28.5%
Decimal Number
ValueCountFrequency (%)
1 1545
22.9%
2 912
13.5%
3 909
13.5%
4 584
 
8.7%
5 561
 
8.3%
6 539
 
8.0%
7 457
 
6.8%
0 447
 
6.6%
9 432
 
6.4%
8 365
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
R 1
33.3%
K 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
4574
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 984
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12427
53.0%
Hangul 11036
47.0%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 1636
14.8%
천 1593
14.4%
시 1547
14.0%
동 1330
12.1%
로 409
 
3.7%
길 313
 
2.8%
곡 302
 
2.7%
번 294
 
2.7%
원 249
 
2.3%
중 215
 
1.9%
Other values (214) 3148
28.5%
Common
ValueCountFrequency (%)
4574
36.8%
1 1545
 
12.4%
- 984
 
7.9%
2 912
 
7.3%
3 909
 
7.3%
4 584
 
4.7%
5 561
 
4.5%
6 539
 
4.3%
7 457
 
3.7%
0 447
 
3.6%
Other values (5) 915
 
7.4%
Latin
ValueCountFrequency (%)
R 1
33.3%
K 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12430
53.0%
Hangul 11036
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4574
36.8%
1 1545
 
12.4%
- 984
 
7.9%
2 912
 
7.3%
3 909
 
7.3%
4 584
 
4.7%
5 561
 
4.5%
6 539
 
4.3%
7 457
 
3.7%
0 447
 
3.6%
Other values (8) 918
 
7.4%
Hangul
ValueCountFrequency (%)
부 1636
14.8%
천 1593
14.4%
시 1547
14.0%
동 1330
12.1%
로 409
 
3.7%
길 313
 
2.8%
곡 302
 
2.7%
번 294
 
2.7%
원 249
 
2.3%
중 215
 
1.9%
Other values (214) 3148
28.5%

반환일자
Date

MISSING 

Distinct191
Distinct (%)12.1%
Missing123
Missing (%)7.2%
Memory size13.4 KiB
Minimum2021-06-23 00:00:00
Maximum2022-09-19 00:00:00
2023-12-12T10:25:51.134928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:51.292809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T10:25:47.257916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:46.610250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:46.923747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:47.382285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:46.709537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:47.048786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:47.501712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:46.817613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:25:47.153537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:25:51.531777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번체납건수체납금액(원)
연번1.0000.0890.111
체납건수0.0891.0000.870
체납금액(원)0.1110.8701.000
2023-12-12T10:25:51.668496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번체납건수체납금액(원)
연번1.000-0.020-0.091
체납건수-0.0201.0000.728
체납금액(원)-0.0910.7281.000

Missing values

2023-12-12T10:25:47.637796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:25:47.761704image/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

연번영치날짜차량번호체납건수체납금액(원)영치장소반환일자
012022-01-045*부3***3447940부천시 중동 592-72022-01-04
122022-01-043*저5***9757240부천종합운동장2022-01-14
232022-01-045*나0***1236880부천시 중동 593-132022-01-04
342022-01-056*가0***2414830부천시 심곡동 142-142022-01-06
452022-01-051*루3***5509660부천시 부일로356번길 11<NA>
562022-01-052*러1***5846660부천시 중동 8992022-01-05
672022-01-056*무2***3667770부천시 부일로356번길 112022-01-05
782022-01-066*도4***3399840성곡로97번길80 부근2022-02-10
892022-01-074*우9***6641100원미도서관 주차장2022-01-12
9102022-01-101*서3***2467910양지로152번길 15-482022-04-22
연번영치날짜차량번호체납건수체납금액(원)영치장소반환일자
169016912022-09-153*도1***2149740도당 장미공원 주차장<NA>
169116922022-09-153*8오***02181750부천시 성곡동 347-152022-09-15
169216932022-09-158*서6***127880도당 장미공원 주차장2022-09-16
169316942022-09-151*9마***11198800부천시 성곡동 4352022-09-15
169416952022-09-155*수5***3647710부천시 까치로124번길 7-82022-09-16
169516962022-09-152*9마***21334340부천시 고강1동 303-112022-09-15
169616972022-09-153*가2***3765510수도로206번길53-6 앞2022-09-15
169716982022-09-156*부1***2471080부천시 성곡동 69-13<NA>
169816992022-09-154*고4***2515020부천시 고강동 295-1<NA>
169917002022-09-155*어5***1198090부천시 고강1동 4422022-09-15