Overview

Dataset statistics

Number of variables6
Number of observations455
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.9 KiB
Average record size in memory49.3 B

Variable types

Categorical2
DateTime2
Text1
Numeric1

Dataset

Description전북특별자치도 익산시 1톤 트럭 폐차 정보로 최초등록일, 폐차일, 차 이름, 주행거리, 폐차사유가 기재되어 있는 데이터파일입니다.
Author전북특별자치도 익산시
URLhttps://www.data.go.kr/data/15124428/fileData.do

Alerts

사용본거지시군구명 has constant value ""Constant
폐차사유 has constant value ""Constant

Reproduction

Analysis started2024-03-14 08:46:47.580718
Analysis finished2024-03-14 08:46:48.467359
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용본거지시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
전북특별자치도 익산시
455 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도 익산시
2nd row전북특별자치도 익산시
3rd row전북특별자치도 익산시
4th row전북특별자치도 익산시
5th row전북특별자치도 익산시

Common Values

ValueCountFrequency (%)
전북특별자치도 익산시 455
100.0%

Length

2024-03-14T17:46:48.583520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:48.737106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 455
50.0%
익산시 455
50.0%

최초등록일
Date

Distinct427
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1993-08-07 00:00:00
Maximum2023-02-20 00:00:00
2024-03-14T17:46:48.920526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:46:49.404078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐차일
Date

Distinct140
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2023-01-02 00:00:00
Maximum2023-09-25 00:00:00
2024-03-14T17:46:49.788824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:46:50.206481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차명
Text

Distinct56
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2024-03-14T17:46:50.960429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.465934
Min length2

Characters and Unicode

Total characters4762
Distinct characters76
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)6.2%

Sample

1st row와이드봉고1톤
2nd row와이드봉고킹캡
3rd row포터장축슈퍼캡
4th row포터초장축슈퍼캡
5th row와이드봉고킹캡
ValueCountFrequency (%)
포터ⅱ(porterⅱ 199
31.6%
봉고ⅲ 106
16.9%
1톤 79
 
12.6%
porterⅱ 43
 
6.8%
포터ⅱ 37
 
5.9%
포터초장축슈퍼캡 15
 
2.4%
포터초장축더블캡 13
 
2.1%
봉고프런티어 12
 
1.9%
냉동차 10
 
1.6%
포터ⅱ내장탑차 9
 
1.4%
Other values (48) 106
16.9%
2024-03-14T17:46:51.857852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 537
 
11.3%
Ⅱ 502
 
10.5%
포 306
 
6.4%
터 306
 
6.4%
E 274
 
5.8%
) 274
 
5.8%
( 274
 
5.8%
O 270
 
5.7%
T 269
 
5.6%
P 264
 
5.5%
Other values (66) 1486
31.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1677
35.2%
Uppercase Letter 1662
34.9%
Letter Number 611
 
12.8%
Close Punctuation 274
 
5.8%
Open Punctuation 274
 
5.8%
Space Separator 175
 
3.7%
Decimal Number 89
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 306
18.2%
터 306
18.2%
봉 131
 
7.8%
고 131
 
7.8%
톤 80
 
4.8%
장 79
 
4.7%
캡 63
 
3.8%
축 59
 
3.5%
차 46
 
2.7%
초 44
 
2.6%
Other values (47) 432
25.8%
Uppercase Letter
ValueCountFrequency (%)
R 537
32.3%
E 274
16.5%
O 270
16.2%
T 269
16.2%
P 264
15.9%
I 15
 
0.9%
L 8
 
0.5%
S 7
 
0.4%
B 6
 
0.4%
A 5
 
0.3%
Other values (2) 7
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 502
82.2%
Ⅲ 109
 
17.8%
Decimal Number
ValueCountFrequency (%)
1 80
89.9%
4 9
 
10.1%
Close Punctuation
ValueCountFrequency (%)
) 274
100.0%
Open Punctuation
ValueCountFrequency (%)
( 274
100.0%
Space Separator
ValueCountFrequency (%)
175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2273
47.7%
Hangul 1677
35.2%
Common 812
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 306
18.2%
터 306
18.2%
봉 131
 
7.8%
고 131
 
7.8%
톤 80
 
4.8%
장 79
 
4.7%
캡 63
 
3.8%
축 59
 
3.5%
차 46
 
2.7%
초 44
 
2.6%
Other values (47) 432
25.8%
Latin
ValueCountFrequency (%)
R 537
23.6%
Ⅱ 502
22.1%
E 274
12.1%
O 270
11.9%
T 269
11.8%
P 264
11.6%
Ⅲ 109
 
4.8%
I 15
 
0.7%
L 8
 
0.4%
S 7
 
0.3%
Other values (4) 18
 
0.8%
Common
ValueCountFrequency (%)
) 274
33.7%
( 274
33.7%
175
21.6%
1 80
 
9.9%
4 9
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2474
52.0%
Hangul 1677
35.2%
Number Forms 611
 
12.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 537
21.7%
E 274
11.1%
) 274
11.1%
( 274
11.1%
O 270
10.9%
T 269
10.9%
P 264
10.7%
175
 
7.1%
1 80
 
3.2%
I 15
 
0.6%
Other values (7) 42
 
1.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 502
82.2%
Ⅲ 109
 
17.8%
Hangul
ValueCountFrequency (%)
포 306
18.2%
터 306
18.2%
봉 131
 
7.8%
고 131
 
7.8%
톤 80
 
4.8%
장 79
 
4.7%
캡 63
 
3.8%
축 59
 
3.5%
차 46
 
2.7%
초 44
 
2.6%
Other values (47) 432
25.8%

주행거리
Real number (ℝ)

Distinct452
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247870.04
Minimum4300
Maximum781009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-03-14T17:46:52.101001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4300
5-th percentile91051.4
Q1177726.5
median235855
Q3307798
95-th percentile463825
Maximum781009
Range776709
Interquartile range (IQR)130071.5

Descriptive statistics

Standard deviation111533.99
Coefficient of variation (CV)0.44996964
Kurtosis1.960311
Mean247870.04
Median Absolute Deviation (MAD)62164
Skewness0.91596307
Sum1.1278087 × 108
Variance1.2439831 × 1010
MonotonicityNot monotonic
2024-03-14T17:46:52.363275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
260000 3
 
0.7%
150000 2
 
0.4%
273944 1
 
0.2%
249383 1
 
0.2%
216863 1
 
0.2%
501200 1
 
0.2%
216624 1
 
0.2%
388380 1
 
0.2%
213731 1
 
0.2%
153774 1
 
0.2%
Other values (442) 442
97.1%
ValueCountFrequency (%)
4300 1
0.2%
5891 1
0.2%
16985 1
0.2%
23000 1
0.2%
27328 1
0.2%
40000 1
0.2%
41724 1
0.2%
42441 1
0.2%
43893 1
0.2%
46234 1
0.2%
ValueCountFrequency (%)
781009 1
0.2%
688256 1
0.2%
679294 1
0.2%
622540 1
0.2%
593090 1
0.2%
542580 1
0.2%
539020 1
0.2%
533994 1
0.2%
531294 1
0.2%
526857 1
0.2%

폐차사유
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
자진말소(폐차)
455 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자진말소(폐차)
2nd row자진말소(폐차)
3rd row자진말소(폐차)
4th row자진말소(폐차)
5th row자진말소(폐차)

Common Values

ValueCountFrequency (%)
자진말소(폐차) 455
100.0%

Length

2024-03-14T17:46:52.614129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:46:52.901375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자진말소(폐차 455
100.0%

Interactions

2024-03-14T17:46:47.791510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:46:53.067472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차명주행거리
차명1.0000.000
주행거리0.0001.000

Missing values

2024-03-14T17:46:48.158532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:46:48.388752image/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

사용본거지시군구명최초등록일폐차일차명주행거리폐차사유
0전북특별자치도 익산시1993-08-072023-05-25와이드봉고1톤101200자진말소(폐차)
1전북특별자치도 익산시1993-09-252023-05-01와이드봉고킹캡91133자진말소(폐차)
2전북특별자치도 익산시1996-04-022023-05-04포터장축슈퍼캡264284자진말소(폐차)
3전북특별자치도 익산시1996-04-022023-04-28포터초장축슈퍼캡229715자진말소(폐차)
4전북특별자치도 익산시1996-07-012023-05-01와이드봉고킹캡159876자진말소(폐차)
5전북특별자치도 익산시1998-01-132023-02-13세레스4륜구동차69625자진말소(폐차)
6전북특별자치도 익산시1998-03-062023-06-22봉고프런티어263921자진말소(폐차)
7전북특별자치도 익산시1998-06-242023-05-03봉고프런티어340000자진말소(폐차)
8전북특별자치도 익산시1998-06-302023-05-02포터장축슈퍼캡222660자진말소(폐차)
9전북특별자치도 익산시1998-11-282023-04-28포터초장축슈퍼캡315982자진말소(폐차)
사용본거지시군구명최초등록일폐차일차명주행거리폐차사유
445전북특별자치도 익산시2016-06-292023-07-10포터Ⅱ (PORTERⅡ)145413자진말소(폐차)
446전북특별자치도 익산시2017-04-042023-07-11봉고Ⅲ 1톤66305자진말소(폐차)
447전북특별자치도 익산시2017-08-032023-09-21봉고Ⅲ 일반덤프118300자진말소(폐차)
448전북특별자치도 익산시2018-03-212023-03-22포터Ⅱ (PORTERⅡ)124818자진말소(폐차)
449전북특별자치도 익산시2018-11-062023-01-03포터Ⅱ (PORTERⅡ)121654자진말소(폐차)
450전북특별자치도 익산시2020-06-292023-04-18포터Ⅱ (PORTERⅡ)128196자진말소(폐차)
451전북특별자치도 익산시2020-09-042023-06-09포터Ⅱ (PORTERⅡ)40000자진말소(폐차)
452전북특별자치도 익산시2020-09-172023-08-17봉고Ⅲ 1톤43893자진말소(폐차)
453전북특별자치도 익산시2021-11-152023-08-09포터Ⅱ윙바디 (PORTER Ⅱ)23000자진말소(폐차)
454전북특별자치도 익산시2023-02-202023-07-24봉고Ⅲ 1톤4300자진말소(폐차)