Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows7
Duplicate rows (%)0.1%
Total size in memory400.4 KiB
Average record size in memory41.0 B

Variable types

DateTime2
Categorical1
Numeric1

Dataset

Description도시철도 벡스코역과 동래역을 구간을 경유하는 차종별 진입시간, 진출시간, 통행시간(초), 통행속도(km/h) 자료입니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15042253/fileData.do

Alerts

Dataset has 7 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 09:17:17.026509
Analysis finished2023-12-12 09:17:17.567913
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진입시간(원본)
Date

Distinct7716
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-11-12 01:03:00
Maximum2019-11-30 23:38:00
2023-12-12T18:17:17.635170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:17:17.808836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

진출시간(원본)
Date

Distinct7447
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2019-11-12 01:05:00
Maximum2019-11-30 23:50:00
2023-12-12T18:17:18.195025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:17:18.342929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

차종
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
승용차
7840 
화물차
955 
미분류
 
768
승합차
 
437

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화물차
2nd row미분류
3rd row승용차
4th row승용차
5th row승용차

Common Values

ValueCountFrequency (%)
승용차 7840
78.4%
화물차 955
 
9.6%
미분류 768
 
7.7%
승합차 437
 
4.4%

Length

2023-12-12T18:17:18.494348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:17:18.604221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
승용차 7840
78.4%
화물차 955
 
9.6%
미분류 768
 
7.7%
승합차 437
 
4.4%

통행시간(초)
Real number (ℝ)

Distinct1664
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1141.8435
Minimum309
Maximum2083
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T18:17:18.721957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum309
5-th percentile542
Q1805
median1102
Q31449
95-th percentile1854
Maximum2083
Range1774
Interquartile range (IQR)644

Descriptive statistics

Standard deviation409.00227
Coefficient of variation (CV)0.35819468
Kurtosis-0.90050144
Mean1141.8435
Median Absolute Deviation (MAD)317
Skewness0.23810139
Sum11418435
Variance167282.86
MonotonicityNot monotonic
2023-12-12T18:17:18.889677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1225 19
 
0.2%
1227 18
 
0.2%
1129 18
 
0.2%
1090 17
 
0.2%
787 17
 
0.2%
895 17
 
0.2%
906 16
 
0.2%
666 16
 
0.2%
803 16
 
0.2%
758 16
 
0.2%
Other values (1654) 9830
98.3%
ValueCountFrequency (%)
309 1
 
< 0.1%
313 1
 
< 0.1%
314 1
 
< 0.1%
315 1
 
< 0.1%
318 1
 
< 0.1%
321 1
 
< 0.1%
322 1
 
< 0.1%
325 1
 
< 0.1%
326 3
< 0.1%
330 1
 
< 0.1%
ValueCountFrequency (%)
2083 1
< 0.1%
2075 1
< 0.1%
2074 2
< 0.1%
2071 2
< 0.1%
2070 1
< 0.1%
2066 1
< 0.1%
2063 1
< 0.1%
2062 1
< 0.1%
2061 1
< 0.1%
2059 2
< 0.1%

Interactions

2023-12-12T18:17:17.265152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:17:19.015316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차종통행시간(초)
차종1.0000.128
통행시간(초)0.1281.000
2023-12-12T18:17:19.123002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
통행시간(초)차종
통행시간(초)1.0000.077
차종0.0771.000

Missing values

2023-12-12T18:17:17.409878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:17:17.516593image/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

진입시간(원본)진출시간(원본)차종통행시간(초)
260022019-11-30 10:482019-11-30 11:09화물차1275
203942019-11-25 18:152019-11-25 18:30미분류892
146522019-11-21 16:062019-11-21 16:38승용차1894
139852019-11-21 07:482019-11-21 08:00승용차755
234282019-11-28 08:242019-11-28 08:46승용차1300
138382019-11-21 03:182019-11-21 03:27승용차573
54542019-11-15 11:102019-11-15 11:36승용차1575
223722019-11-27 13:112019-11-27 13:37승용차1540
207382019-11-26 02:052019-11-26 02:20승용차908
200182019-11-25 11:152019-11-25 11:45화물차1850
진입시간(원본)진출시간(원본)차종통행시간(초)
15182019-11-13 02:002019-11-13 02:34승합차2063
92362019-11-17 21:012019-11-17 21:16승용차900
10722019-11-12 17:382019-11-12 18:01승용차1385
163422019-11-22 20:142019-11-22 20:28승용차836
237562019-11-28 11:262019-11-28 11:39승용차765
99732019-11-18 11:412019-11-18 12:03승용차1332
183102019-11-24 07:342019-11-24 07:48승용차850
68622019-11-16 08:062019-11-16 08:19승용차728
230252019-11-27 22:112019-11-27 22:28승용차1006
180122019-11-24 12:052019-11-24 12:19승용차809

Duplicate rows

Most frequently occurring

진입시간(원본)진출시간(원본)차종통행시간(초)# duplicates
02019-11-13 08:592019-11-13 09:25승용차15692
12019-11-17 07:452019-11-17 07:57승용차7182
22019-11-17 13:522019-11-17 14:00승용차4772
32019-11-21 12:142019-11-21 12:20승용차3262
42019-11-21 12:232019-11-21 12:42미분류11942
52019-11-23 12:132019-11-23 12:31승합차10672
62019-11-24 15:282019-11-24 15:52승용차14132