Overview

Dataset statistics

Number of variables5
Number of observations326
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 KiB
Average record size in memory42.4 B

Variable types

Numeric2
DateTime2
Categorical1

Dataset

Description1톤 트럭 전체 폐차 정보 요청에 따라 폐차 대상 자동차 최초 등록일, 폐차 날짜(말소 날짜), 폐차 시 자동차 주행거리를 제공합니다.
Author경상남도 진주시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15124200

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:16:32.038431
Analysis finished2023-12-10 23:16:32.648677
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct326
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.5
Minimum1
Maximum326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-11T08:16:32.713119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.25
Q182.25
median163.5
Q3244.75
95-th percentile309.75
Maximum326
Range325
Interquartile range (IQR)162.5

Descriptive statistics

Standard deviation94.252321
Coefficient of variation (CV)0.57646679
Kurtosis-1.2
Mean163.5
Median Absolute Deviation (MAD)81.5
Skewness0
Sum53301
Variance8883.5
MonotonicityStrictly increasing
2023-12-11T08:16:32.843838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
206 1
 
0.3%
224 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
Other values (316) 316
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
326 1
0.3%
325 1
0.3%
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%

최초등록일
Date

Distinct308
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum1991-02-27 00:00:00
Maximum2023-04-03 00:00:00
2023-12-11T08:16:32.991627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:16:33.122866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

말소일자
Date

Distinct141
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2023-01-02 00:00:00
Maximum2023-09-22 00:00:00
2023-12-11T08:16:33.265388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:16:33.391766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주행거리
Real number (ℝ)

Distinct320
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237252.21
Minimum0
Maximum822550
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-11T08:16:33.511390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile79273.75
Q1162234.75
median232347.5
Q3303945.5
95-th percentile433455.25
Maximum822550
Range822550
Interquartile range (IQR)141710.75

Descriptive statistics

Standard deviation113101.78
Coefficient of variation (CV)0.47671539
Kurtosis2.8633738
Mean237252.21
Median Absolute Deviation (MAD)70625.5
Skewness0.94237214
Sum77344221
Variance1.2792013 × 1010
MonotonicityNot monotonic
2023-12-11T08:16:33.920842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
130000 2
 
0.6%
362527 2
 
0.6%
188600 2
 
0.6%
180000 2
 
0.6%
156114 2
 
0.6%
200000 2
 
0.6%
95196 1
 
0.3%
280085 1
 
0.3%
335474 1
 
0.3%
131833 1
 
0.3%
Other values (310) 310
95.1%
ValueCountFrequency (%)
0 1
0.3%
64 1
0.3%
1274 1
0.3%
1500 1
0.3%
23000 1
0.3%
26510 1
0.3%
37657 1
0.3%
38082 1
0.3%
46203 1
0.3%
52300 1
0.3%
ValueCountFrequency (%)
822550 1
0.3%
720385 1
0.3%
617375 1
0.3%
596000 1
0.3%
532720 1
0.3%
500000 1
0.3%
493220 1
0.3%
484000 1
0.3%
482343 1
0.3%
472343 1
0.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-09-27
326 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-27
2nd row2023-09-27
3rd row2023-09-27
4th row2023-09-27
5th row2023-09-27

Common Values

ValueCountFrequency (%)
2023-09-27 326
100.0%

Length

2023-12-11T08:16:34.046479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:16:34.176004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-27 326
100.0%

Interactions

2023-12-11T08:16:32.303966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:16:32.126435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:16:32.400766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:16:32.229626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:16:34.231349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주행거리
연번1.0000.286
주행거리0.2861.000
2023-12-11T08:16:34.321565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주행거리
연번1.000-0.111
주행거리-0.1111.000

Missing values

2023-12-11T08:16:32.507423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:16:32.607133image/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

연번최초등록일말소일자주행거리데이터기준일자
012004-07-272023-09-132544522023-09-27
122007-03-152023-05-092553772023-09-27
232009-10-132023-09-071334522023-09-27
342000-09-252023-07-12757762023-09-27
452009-04-282023-09-222064472023-09-27
562006-07-102023-07-191886002023-09-27
672006-07-102023-07-191886002023-09-27
782007-01-102023-04-141053852023-09-27
892001-01-272023-03-272197162023-09-27
9102002-04-252023-05-232715962023-09-27
연번최초등록일말소일자주행거리데이터기준일자
3163172002-03-232023-04-11376572023-09-27
3173182002-04-022023-09-082156002023-09-27
3183192003-09-162023-02-231000602023-09-27
3193201999-11-242023-01-113152292023-09-27
3203212000-03-142023-03-29716032023-09-27
3213222003-12-182023-05-232533522023-09-27
3223232014-07-112023-04-062787742023-09-27
3233242007-09-102023-09-192841672023-09-27
3243251997-05-292023-03-301195892023-09-27
3253262002-02-022023-01-272680002023-09-27