Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows10
Duplicate rows (%)0.1%
Total size in memory478.5 KiB
Average record size in memory49.0 B

Variable types

DateTime1
Categorical1
Text2
Numeric1

Dataset

Description부산광역시 교통정보서비스센터에서 운영중인 교통정보수집장치(DSRC)를 통해 수집한 정보를 세부구간별 가공한 교통정보(가공일시, 구간명, 시점, 종점, 속도)를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15041721/fileData.do

Alerts

Dataset has 10 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-04-21 01:08:53.115517
Analysis finished2024-04-21 01:08:54.744374
Duration1.63 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가공일시
Date

Distinct129
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-31 06:00:00
Maximum2024-03-31 08:08:00
2024-04-21T10:08:54.820625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:54.934978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구간명
Categorical

Distinct43
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
중앙대로
1407 
가락대로
714 
기장대로
 
566
가야대로
 
559
해운대로
 
550
Other values (38)
6204 

Length

Max length6
Median length4
Mean length4.048
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동평로
2nd row가락대로
3rd row중앙대로
4th row가야대로
5th row기장대로

Common Values

ValueCountFrequency (%)
중앙대로 1407
 
14.1%
가락대로 714
 
7.1%
기장대로 566
 
5.7%
가야대로 559
 
5.6%
해운대로 550
 
5.5%
충렬대로 511
 
5.1%
낙동대로 426
 
4.3%
충장대로 392
 
3.9%
번영로 355
 
3.5%
대영로 348
 
3.5%
Other values (33) 4172
41.7%

Length

2024-04-21T10:08:55.060095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중앙대로 1407
 
14.1%
가락대로 714
 
7.1%
기장대로 566
 
5.7%
가야대로 559
 
5.6%
해운대로 550
 
5.5%
충렬대로 511
 
5.1%
낙동대로 426
 
4.3%
충장대로 392
 
3.9%
번영로 355
 
3.5%
대영로 348
 
3.5%
Other values (33) 4172
41.7%

시점
Text

Distinct394
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:08:55.239583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.6887
Min length3

Characters and Unicode

Total characters66887
Distinct characters322
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row한국가수협회부산지회
2nd row구랑동1265
3rd row교대사거리
4th row가야성당
5th row교리삼거리
ValueCountFrequency (%)
속성변화점 152
 
1.5%
충장고가교 114
 
1.1%
시랑리706 111
 
1.1%
연화육교 75
 
0.8%
연화리507 70
 
0.7%
범방동314-1 69
 
0.7%
범방동1925 67
 
0.7%
화엄정사괴정포교당 63
 
0.6%
안락지하차도 61
 
0.6%
부산터널삼거리 59
 
0.6%
Other values (384) 9159
91.6%
2024-04-21T10:08:55.530378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 2587
 
3.9%
동 2415
 
3.6%
리 2254
 
3.4%
1 1842
 
2.8%
거 1469
 
2.2%
부 1334
 
2.0%
산 1307
 
2.0%
차 1301
 
1.9%
측 1216
 
1.8%
사 1179
 
1.8%
Other values (312) 49983
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56912
85.1%
Decimal Number 7577
 
11.3%
Uppercase Letter 1183
 
1.8%
Dash Punctuation 1049
 
1.6%
Close Punctuation 63
 
0.1%
Open Punctuation 63
 
0.1%
Lowercase Letter 40
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2587
 
4.5%
동 2415
 
4.2%
리 2254
 
4.0%
거 1469
 
2.6%
부 1334
 
2.3%
산 1307
 
2.3%
차 1301
 
2.3%
측 1216
 
2.1%
사 1179
 
2.1%
로 1178
 
2.1%
Other values (282) 40672
71.5%
Uppercase Letter
ValueCountFrequency (%)
C 323
27.3%
I 229
19.4%
S 152
12.8%
G 106
 
9.0%
T 88
 
7.4%
U 65
 
5.5%
A 35
 
3.0%
P 31
 
2.6%
D 27
 
2.3%
M 23
 
1.9%
Other values (5) 104
 
8.8%
Decimal Number
ValueCountFrequency (%)
1 1842
24.3%
2 879
11.6%
4 836
11.0%
5 830
11.0%
3 642
 
8.5%
9 598
 
7.9%
7 593
 
7.8%
8 514
 
6.8%
6 508
 
6.7%
0 335
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
l 20
50.0%
i 20
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1049
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56912
85.1%
Common 8752
 
13.1%
Latin 1223
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2587
 
4.5%
동 2415
 
4.2%
리 2254
 
4.0%
거 1469
 
2.6%
부 1334
 
2.3%
산 1307
 
2.3%
차 1301
 
2.3%
측 1216
 
2.1%
사 1179
 
2.1%
로 1178
 
2.1%
Other values (282) 40672
71.5%
Latin
ValueCountFrequency (%)
C 323
26.4%
I 229
18.7%
S 152
12.4%
G 106
 
8.7%
T 88
 
7.2%
U 65
 
5.3%
A 35
 
2.9%
P 31
 
2.5%
D 27
 
2.2%
M 23
 
1.9%
Other values (7) 144
11.8%
Common
ValueCountFrequency (%)
1 1842
21.0%
- 1049
12.0%
2 879
10.0%
4 836
9.6%
5 830
9.5%
3 642
 
7.3%
9 598
 
6.8%
7 593
 
6.8%
8 514
 
5.9%
6 508
 
5.8%
Other values (3) 461
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56912
85.1%
ASCII 9975
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 2587
 
4.5%
동 2415
 
4.2%
리 2254
 
4.0%
거 1469
 
2.6%
부 1334
 
2.3%
산 1307
 
2.3%
차 1301
 
2.3%
측 1216
 
2.1%
사 1179
 
2.1%
로 1178
 
2.1%
Other values (282) 40672
71.5%
ASCII
ValueCountFrequency (%)
1 1842
18.5%
- 1049
10.5%
2 879
8.8%
4 836
8.4%
5 830
8.3%
3 642
 
6.4%
9 598
 
6.0%
7 593
 
5.9%
8 514
 
5.2%
6 508
 
5.1%
Other values (20) 1684
16.9%

종점
Text

Distinct393
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:08:55.747798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length6.6649
Min length3

Characters and Unicode

Total characters66649
Distinct characters322
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row부암교차로
2nd row구랑주유소앞
3rd row소피아커피
4th row동의대어귀사거리
5th row청강리5-2
ValueCountFrequency (%)
속성변화점 177
 
1.8%
시랑리706 108
 
1.1%
충장고가교 105
 
1.1%
연화리507 72
 
0.7%
범방동314-1 68
 
0.7%
부암교차로 60
 
0.6%
연화육교 60
 
0.6%
범방동1925 59
 
0.6%
안락지하차도 58
 
0.6%
구랑동1265 56
 
0.6%
Other values (383) 9177
91.8%
2024-04-21T10:08:56.084784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 2594
 
3.9%
동 2370
 
3.6%
리 2296
 
3.4%
1 1863
 
2.8%
거 1485
 
2.2%
차 1348
 
2.0%
부 1290
 
1.9%
로 1258
 
1.9%
측 1237
 
1.9%
산 1235
 
1.9%
Other values (312) 49673
74.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56589
84.9%
Decimal Number 7621
 
11.4%
Uppercase Letter 1218
 
1.8%
Dash Punctuation 1073
 
1.6%
Lowercase Letter 52
 
0.1%
Open Punctuation 48
 
0.1%
Close Punctuation 48
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2594
 
4.6%
동 2370
 
4.2%
리 2296
 
4.1%
거 1485
 
2.6%
차 1348
 
2.4%
부 1290
 
2.3%
로 1258
 
2.2%
측 1237
 
2.2%
산 1235
 
2.2%
사 1152
 
2.0%
Other values (282) 40324
71.3%
Uppercase Letter
ValueCountFrequency (%)
C 321
26.4%
I 239
19.6%
S 139
11.4%
T 95
 
7.8%
G 83
 
6.8%
U 60
 
4.9%
P 44
 
3.6%
A 42
 
3.4%
L 33
 
2.7%
M 31
 
2.5%
Other values (5) 131
10.8%
Decimal Number
ValueCountFrequency (%)
1 1863
24.4%
2 921
12.1%
4 841
11.0%
5 834
10.9%
7 638
 
8.4%
3 629
 
8.3%
9 536
 
7.0%
6 505
 
6.6%
8 502
 
6.6%
0 352
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
i 26
50.0%
l 26
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1073
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56589
84.9%
Common 8790
 
13.2%
Latin 1270
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2594
 
4.6%
동 2370
 
4.2%
리 2296
 
4.1%
거 1485
 
2.6%
차 1348
 
2.4%
부 1290
 
2.3%
로 1258
 
2.2%
측 1237
 
2.2%
산 1235
 
2.2%
사 1152
 
2.0%
Other values (282) 40324
71.3%
Latin
ValueCountFrequency (%)
C 321
25.3%
I 239
18.8%
S 139
10.9%
T 95
 
7.5%
G 83
 
6.5%
U 60
 
4.7%
P 44
 
3.5%
A 42
 
3.3%
L 33
 
2.6%
M 31
 
2.4%
Other values (7) 183
14.4%
Common
ValueCountFrequency (%)
1 1863
21.2%
- 1073
12.2%
2 921
10.5%
4 841
9.6%
5 834
9.5%
7 638
 
7.3%
3 629
 
7.2%
9 536
 
6.1%
6 505
 
5.7%
8 502
 
5.7%
Other values (3) 448
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56589
84.9%
ASCII 10060
 
15.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 2594
 
4.6%
동 2370
 
4.2%
리 2296
 
4.1%
거 1485
 
2.6%
차 1348
 
2.4%
부 1290
 
2.3%
로 1258
 
2.2%
측 1237
 
2.2%
산 1235
 
2.2%
사 1152
 
2.0%
Other values (282) 40324
71.3%
ASCII
ValueCountFrequency (%)
1 1863
18.5%
- 1073
10.7%
2 921
9.2%
4 841
8.4%
5 834
8.3%
7 638
 
6.3%
3 629
 
6.3%
9 536
 
5.3%
6 505
 
5.0%
8 502
 
5.0%
Other values (20) 1718
17.1%

속도
Real number (ℝ)

Distinct103
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.5034
Minimum3
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:08:56.240524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile19
Q128
median37
Q352
95-th percentile78
Maximum106
Range103
Interquartile range (IQR)24

Descriptive statistics

Standard deviation18.242869
Coefficient of variation (CV)0.43955119
Kurtosis0.26255093
Mean41.5034
Median Absolute Deviation (MAD)11
Skewness0.79472782
Sum415034
Variance332.80227
MonotonicityNot monotonic
2024-04-21T10:08:56.363760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34 337
 
3.4%
36 326
 
3.3%
35 317
 
3.2%
25 310
 
3.1%
32 305
 
3.0%
29 300
 
3.0%
33 297
 
3.0%
26 271
 
2.7%
37 260
 
2.6%
30 256
 
2.6%
Other values (93) 7021
70.2%
ValueCountFrequency (%)
3 2
 
< 0.1%
4 44
0.4%
5 10
 
0.1%
6 27
0.3%
7 35
0.4%
8 11
 
0.1%
9 13
 
0.1%
10 24
0.2%
11 2
 
< 0.1%
12 16
 
0.2%
ValueCountFrequency (%)
106 1
 
< 0.1%
105 1
 
< 0.1%
104 3
 
< 0.1%
102 4
 
< 0.1%
101 1
 
< 0.1%
100 5
 
0.1%
99 6
 
0.1%
98 16
0.2%
97 3
 
< 0.1%
96 13
0.1%

Interactions

2024-04-21T10:08:54.423929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:08:56.440035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구간명속도
구간명1.0000.825
속도0.8251.000
2024-04-21T10:08:56.515568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
속도구간명
속도1.0000.457
구간명0.4571.000

Missing values

2024-04-21T10:08:54.586529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:08:54.692511image/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

가공일시구간명시점종점속도
665982024-03-31 07:26:00동평로한국가수협회부산지회부암교차로59
724842024-03-31 07:33:00가락대로구랑동1265구랑주유소앞54
781222024-03-31 07:40:00중앙대로교대사거리소피아커피24
595362024-03-31 07:17:00가야대로가야성당동의대어귀사거리26
130222024-03-31 06:16:00기장대로교리삼거리청강리5-240
436722024-03-31 06:56:00기장대로내리교(북측)기장교차로40
591882024-03-31 07:16:00중앙대로교대역3번출구교대사거리25
197662024-03-31 06:25:00중앙대로연산교차로연산동1340-421
544312024-03-31 07:10:00낙동대로당리역1번출구당리역31
173922024-03-31 06:22:00가락대로범방동82-1범방동36-252
가공일시구간명시점종점속도
101702024-03-31 06:13:00중앙대로광무교북측부전동573-125
134102024-03-31 06:17:00신선로핸즈커피메트로점퍼피인39
563012024-03-31 07:12:00신정관로산막2교북측두명터널남측89
579882024-03-31 07:15:00중앙대로부전동573-1부전동573-126
753672024-03-31 07:37:00가야대로동남석면환경연구소개금사거리32
284022024-03-31 06:37:00충장대로제1지하차도교차로초량동45-3850
85922024-03-31 06:11:00중앙대로범천동948-4범내골교차로29
663352024-03-31 07:25:00동부산관광로시랑리729당사리29638
282992024-03-31 06:36:00동부산관광로시랑리729당사리29626
292382024-03-31 06:38:00황령대로덕명여자정보고앞문전교차로25

Duplicate rows

Most frequently occurring

가공일시구간명시점종점속도# duplicates
02024-03-31 06:12:00기장해안로연화리507연화리507222
12024-03-31 06:14:00기장해안로시랑리706시랑리706292
22024-03-31 06:30:00기장해안로연화리507연화리507282
32024-03-31 06:40:00충장대로부두사거리충장고가교552
42024-03-31 07:20:00기장해안로연화리507연화리507372
52024-03-31 07:25:00가락대로범방동314-1범방동314-1532
62024-03-31 07:26:00가락대로범방동314-1범방동314-1522
72024-03-31 07:47:00기장해안로시랑리706시랑리706272
82024-03-31 07:54:00기장해안로시랑리706시랑리706472
92024-03-31 07:55:00기장해안로시랑리706시랑리706232