Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows10
Duplicate rows (%)0.1%
Total size in memory556.6 KiB
Average record size in memory57.0 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description부산광역시 교통정보서비스센터에서 수집한 교통정보와 유관기관 교통정보를 통해 도로구간별(1-4레벨) 소통정보를 분석하여 요일별 시간별 형태(요일, 시분, 구간명, 시점, 종점, 속도)로 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15041722/fileData.do

Alerts

Dataset has 10 (0.1%) duplicate rowsDuplicates
요일 is highly overall correlated with 시분High correlation
시분 is highly overall correlated with 요일High correlation
요일 is highly imbalanced (66.4%)Imbalance

Reproduction

Analysis started2024-03-14 16:44:27.329339
Analysis finished2024-03-14 16:44:29.617763
Duration2.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일요일
9379 
월요일
 
621

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일요일
2nd row일요일
3rd row일요일
4th row일요일
5th row일요일

Common Values

ValueCountFrequency (%)
일요일 9379
93.8%
월요일 621
 
6.2%

Length

2024-03-15T01:44:29.894620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:44:30.193287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일요일 9379
93.8%
월요일 621
 
6.2%

시분
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
18:00
1410 
18:10
822 
18:45
814 
18:20
791 
18:35
785 
Other values (7)
5378 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18:55
2nd row18:15
3rd row18:00
4th row18:00
5th row18:00

Common Values

ValueCountFrequency (%)
18:00 1410
14.1%
18:10 822
8.2%
18:45 814
8.1%
18:20 791
7.9%
18:35 785
7.8%
18:15 779
7.8%
18:55 776
7.8%
18:50 775
7.8%
18:40 773
7.7%
18:05 764
7.6%
Other values (2) 1511
15.1%

Length

2024-03-15T01:44:30.522138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
18:00 1410
14.1%
18:10 822
8.2%
18:45 814
8.1%
18:20 791
7.9%
18:35 785
7.8%
18:15 779
7.8%
18:55 776
7.8%
18:50 775
7.8%
18:40 773
7.7%
18:05 764
7.6%
Other values (2) 1511
15.1%

구간명
Text

Distinct848
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T01:44:31.635182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.9008
Min length3

Characters and Unicode

Total characters49008
Distinct characters252
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)0.7%

Sample

1st row충렬대로
2nd row녹산산단381로
3rd row다대낙조2길
4th row효열로
5th row식물원로
ValueCountFrequency (%)
중앙대로 297
 
3.0%
해운대로 170
 
1.7%
낙동대로 157
 
1.6%
낙동남로 148
 
1.5%
기장대로 145
 
1.5%
반송로 144
 
1.4%
번영로 142
 
1.4%
가락대로 138
 
1.4%
다대로 109
 
1.1%
동서고가로 93
 
0.9%
Other values (838) 8457
84.6%
2024-03-15T01:44:33.197042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 9729
 
19.9%
대 3195
 
6.5%
산 1930
 
3.9%
길 1893
 
3.9%
번 1819
 
3.7%
1 1226
 
2.5%
동 1146
 
2.3%
2 1050
 
2.1%
3 801
 
1.6%
녹 791
 
1.6%
Other values (242) 25428
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42955
87.6%
Decimal Number 6021
 
12.3%
Uppercase Letter 32
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 9729
22.6%
대 3195
 
7.4%
산 1930
 
4.5%
길 1893
 
4.4%
번 1819
 
4.2%
동 1146
 
2.7%
녹 791
 
1.8%
중 744
 
1.7%
해 721
 
1.7%
단 602
 
1.4%
Other values (228) 20385
47.5%
Decimal Number
ValueCountFrequency (%)
1 1226
20.4%
2 1050
17.4%
3 801
13.3%
6 520
8.6%
4 500
8.3%
7 469
 
7.8%
8 404
 
6.7%
0 376
 
6.2%
5 375
 
6.2%
9 300
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
E 8
25.0%
C 8
25.0%
P 8
25.0%
A 8
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42955
87.6%
Common 6021
 
12.3%
Latin 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 9729
22.6%
대 3195
 
7.4%
산 1930
 
4.5%
길 1893
 
4.4%
번 1819
 
4.2%
동 1146
 
2.7%
녹 791
 
1.8%
중 744
 
1.7%
해 721
 
1.7%
단 602
 
1.4%
Other values (228) 20385
47.5%
Common
ValueCountFrequency (%)
1 1226
20.4%
2 1050
17.4%
3 801
13.3%
6 520
8.6%
4 500
8.3%
7 469
 
7.8%
8 404
 
6.7%
0 376
 
6.2%
5 375
 
6.2%
9 300
 
5.0%
Latin
ValueCountFrequency (%)
E 8
25.0%
C 8
25.0%
P 8
25.0%
A 8
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42955
87.6%
ASCII 6053
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 9729
22.6%
대 3195
 
7.4%
산 1930
 
4.5%
길 1893
 
4.4%
번 1819
 
4.2%
동 1146
 
2.7%
녹 791
 
1.8%
중 744
 
1.7%
해 721
 
1.7%
단 602
 
1.4%
Other values (228) 20385
47.5%
ASCII
ValueCountFrequency (%)
1 1226
20.3%
2 1050
17.3%
3 801
13.2%
6 520
8.6%
4 500
8.3%
7 469
 
7.7%
8 404
 
6.7%
0 376
 
6.2%
5 375
 
6.2%
9 300
 
5.0%
Other values (4) 32
 
0.5%

시점
Text

Distinct2488
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T01:44:34.189037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.7039
Min length2

Characters and Unicode

Total characters67039
Distinct characters605
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

Unique316 ?
Unique (%)3.2%

Sample

1st row한국전력공사동래지점
2nd row삼우기계
3rd row성원뽀로로어린이집
4th row동산교회
5th row금정교당
ValueCountFrequency (%)
속성변화점 106
 
1.1%
명지ic 34
 
0.3%
제1지하차도 25
 
0.2%
대동화명대교ic 25
 
0.2%
거제역10번출구 22
 
0.2%
회동교차로 22
 
0.2%
버스정류장 20
 
0.2%
북구청삼거리 19
 
0.2%
청강교 19
 
0.2%
내성교차로 19
 
0.2%
Other values (2478) 9689
96.9%
2024-03-15T01:44:35.542734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 2876
 
4.3%
동 2254
 
3.4%
리 1598
 
2.4%
산 1326
 
2.0%
차 1302
 
1.9%
1 1261
 
1.9%
대 1235
 
1.8%
로 1143
 
1.7%
사 1135
 
1.7%
부 1082
 
1.6%
Other values (595) 51827
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59484
88.7%
Decimal Number 5184
 
7.7%
Uppercase Letter 1454
 
2.2%
Dash Punctuation 768
 
1.1%
Close Punctuation 56
 
0.1%
Open Punctuation 56
 
0.1%
Lowercase Letter 20
 
< 0.1%
Other Punctuation 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2876
 
4.8%
동 2254
 
3.8%
리 1598
 
2.7%
산 1326
 
2.2%
차 1302
 
2.2%
대 1235
 
2.1%
로 1143
 
1.9%
사 1135
 
1.9%
부 1082
 
1.8%
거 1069
 
1.8%
Other values (553) 44464
74.7%
Uppercase Letter
ValueCountFrequency (%)
C 376
25.9%
I 295
20.3%
G 134
 
9.2%
S 123
 
8.5%
K 97
 
6.7%
T 90
 
6.2%
B 55
 
3.8%
E 40
 
2.8%
J 37
 
2.5%
N 35
 
2.4%
Other values (13) 172
11.8%
Decimal Number
ValueCountFrequency (%)
1 1261
24.3%
2 847
16.3%
3 531
10.2%
4 507
9.8%
5 480
 
9.3%
7 364
 
7.0%
6 330
 
6.4%
9 327
 
6.3%
8 272
 
5.2%
0 265
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
i 7
35.0%
l 7
35.0%
k 3
15.0%
s 3
15.0%
Other Punctuation
ValueCountFrequency (%)
& 10
58.8%
, 7
41.2%
Dash Punctuation
ValueCountFrequency (%)
- 768
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59484
88.7%
Common 6081
 
9.1%
Latin 1474
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2876
 
4.8%
동 2254
 
3.8%
리 1598
 
2.7%
산 1326
 
2.2%
차 1302
 
2.2%
대 1235
 
2.1%
로 1143
 
1.9%
사 1135
 
1.9%
부 1082
 
1.8%
거 1069
 
1.8%
Other values (553) 44464
74.7%
Latin
ValueCountFrequency (%)
C 376
25.5%
I 295
20.0%
G 134
 
9.1%
S 123
 
8.3%
K 97
 
6.6%
T 90
 
6.1%
B 55
 
3.7%
E 40
 
2.7%
J 37
 
2.5%
N 35
 
2.4%
Other values (17) 192
13.0%
Common
ValueCountFrequency (%)
1 1261
20.7%
2 847
13.9%
- 768
12.6%
3 531
8.7%
4 507
8.3%
5 480
 
7.9%
7 364
 
6.0%
6 330
 
5.4%
9 327
 
5.4%
8 272
 
4.5%
Other values (5) 394
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59484
88.7%
ASCII 7555
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 2876
 
4.8%
동 2254
 
3.8%
리 1598
 
2.7%
산 1326
 
2.2%
차 1302
 
2.2%
대 1235
 
2.1%
로 1143
 
1.9%
사 1135
 
1.9%
부 1082
 
1.8%
거 1069
 
1.8%
Other values (553) 44464
74.7%
ASCII
ValueCountFrequency (%)
1 1261
16.7%
2 847
11.2%
- 768
10.2%
3 531
 
7.0%
4 507
 
6.7%
5 480
 
6.4%
C 376
 
5.0%
7 364
 
4.8%
6 330
 
4.4%
9 327
 
4.3%
Other values (32) 1764
23.3%

종점
Text

Distinct2473
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-15T01:44:36.547336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length6.7106
Min length2

Characters and Unicode

Total characters67106
Distinct characters605
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

Unique338 ?
Unique (%)3.4%

Sample

1st row우리들어린이집
2nd row신원금속
3rd row몰운대어린이집
4th row해바라기숲어린이집
5th row금강교차로
ValueCountFrequency (%)
속성변화점 105
 
1.1%
명지ic 34
 
0.3%
제1지하차도 27
 
0.3%
대동화명대교ic 22
 
0.2%
좌천삼거리 22
 
0.2%
내성교차로 21
 
0.2%
환경생태공학연구원 21
 
0.2%
삼락ic 21
 
0.2%
거제역10번출구 19
 
0.2%
회동교차로 18
 
0.2%
Other values (2463) 9690
96.9%
2024-03-15T01:44:38.217844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 2889
 
4.3%
동 2221
 
3.3%
리 1652
 
2.5%
산 1394
 
2.1%
1 1271
 
1.9%
차 1268
 
1.9%
대 1203
 
1.8%
부 1165
 
1.7%
로 1160
 
1.7%
거 1131
 
1.7%
Other values (595) 51752
77.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 59779
89.1%
Decimal Number 5088
 
7.6%
Uppercase Letter 1390
 
2.1%
Dash Punctuation 715
 
1.1%
Open Punctuation 53
 
0.1%
Close Punctuation 53
 
0.1%
Lowercase Letter 16
 
< 0.1%
Other Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 2889
 
4.8%
동 2221
 
3.7%
리 1652
 
2.8%
산 1394
 
2.3%
차 1268
 
2.1%
대 1203
 
2.0%
부 1165
 
1.9%
로 1160
 
1.9%
거 1131
 
1.9%
사 1098
 
1.8%
Other values (553) 44598
74.6%
Uppercase Letter
ValueCountFrequency (%)
C 361
26.0%
I 285
20.5%
G 133
 
9.6%
S 114
 
8.2%
K 86
 
6.2%
T 85
 
6.1%
B 54
 
3.9%
U 39
 
2.8%
E 37
 
2.7%
N 35
 
2.5%
Other values (13) 161
11.6%
Decimal Number
ValueCountFrequency (%)
1 1271
25.0%
2 852
16.7%
3 517
10.2%
4 515
10.1%
5 466
 
9.2%
7 358
 
7.0%
6 349
 
6.9%
9 282
 
5.5%
0 254
 
5.0%
8 224
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
i 6
37.5%
l 6
37.5%
s 2
 
12.5%
k 2
 
12.5%
Other Punctuation
ValueCountFrequency (%)
& 8
66.7%
, 4
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 715
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 59779
89.1%
Common 5921
 
8.8%
Latin 1406
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 2889
 
4.8%
동 2221
 
3.7%
리 1652
 
2.8%
산 1394
 
2.3%
차 1268
 
2.1%
대 1203
 
2.0%
부 1165
 
1.9%
로 1160
 
1.9%
거 1131
 
1.9%
사 1098
 
1.8%
Other values (553) 44598
74.6%
Latin
ValueCountFrequency (%)
C 361
25.7%
I 285
20.3%
G 133
 
9.5%
S 114
 
8.1%
K 86
 
6.1%
T 85
 
6.0%
B 54
 
3.8%
U 39
 
2.8%
E 37
 
2.6%
N 35
 
2.5%
Other values (17) 177
12.6%
Common
ValueCountFrequency (%)
1 1271
21.5%
2 852
14.4%
- 715
12.1%
3 517
8.7%
4 515
8.7%
5 466
 
7.9%
7 358
 
6.0%
6 349
 
5.9%
9 282
 
4.8%
0 254
 
4.3%
Other values (5) 342
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 59779
89.1%
ASCII 7327
 
10.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 2889
 
4.8%
동 2221
 
3.7%
리 1652
 
2.8%
산 1394
 
2.3%
차 1268
 
2.1%
대 1203
 
2.0%
부 1165
 
1.9%
로 1160
 
1.9%
거 1131
 
1.9%
사 1098
 
1.8%
Other values (553) 44598
74.6%
ASCII
ValueCountFrequency (%)
1 1271
17.3%
2 852
11.6%
- 715
9.8%
3 517
 
7.1%
4 515
 
7.0%
5 466
 
6.4%
C 361
 
4.9%
7 358
 
4.9%
6 349
 
4.8%
I 285
 
3.9%
Other values (32) 1638
22.4%

속도
Real number (ℝ)

Distinct100
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.9554
Minimum4
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T01:44:38.671204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile11
Q119
median26
Q336
95-th percentile67
Maximum105
Range101
Interquartile range (IQR)17

Descriptive statistics

Standard deviation16.407539
Coefficient of variation (CV)0.54773226
Kurtosis2.3140456
Mean29.9554
Median Absolute Deviation (MAD)8
Skewness1.4550743
Sum299554
Variance269.20733
MonotonicityNot monotonic
2024-03-15T01:44:39.157636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22 415
 
4.2%
23 415
 
4.2%
19 387
 
3.9%
20 380
 
3.8%
25 377
 
3.8%
26 371
 
3.7%
24 359
 
3.6%
21 358
 
3.6%
27 354
 
3.5%
18 328
 
3.3%
Other values (90) 6256
62.6%
ValueCountFrequency (%)
4 42
 
0.4%
5 30
 
0.3%
6 45
 
0.4%
7 64
0.6%
8 90
0.9%
9 70
0.7%
10 117
1.2%
11 127
1.3%
12 141
1.4%
13 156
1.6%
ValueCountFrequency (%)
105 3
 
< 0.1%
103 1
 
< 0.1%
102 2
 
< 0.1%
100 2
 
< 0.1%
99 2
 
< 0.1%
98 1
 
< 0.1%
97 6
0.1%
96 9
0.1%
95 6
0.1%
94 7
0.1%

Interactions

2024-03-15T01:44:28.750610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:44:39.423948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요일시분속도
요일1.0000.7910.052
시분0.7911.0000.026
속도0.0520.0261.000
2024-03-15T01:44:39.675523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요일시분
요일1.0000.634
시분0.6341.000
2024-03-15T01:44:39.948901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
속도요일시분
속도1.0000.0400.011
요일0.0401.0000.634
시분0.0110.6341.000

Missing values

2024-03-15T01:44:29.099195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:44:29.459000image/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

요일시분구간명시점종점속도
88643일요일18:55충렬대로한국전력공사동래지점우리들어린이집34
27794일요일18:15녹산산단381로삼우기계신원금속30
6789일요일18:00다대낙조2길성원뽀로로어린이집몰운대어린이집20
6420일요일18:00효열로동산교회해바라기숲어린이집19
5839일요일18:00식물원로금정교당금강교차로11
21123일요일18:10새벽시장로현진산업럭키메가마트24
23316일요일18:10토곡로튼튼어린이집극락사16
45092일요일18:25부곡로부곡교차로부곡2동주민센터19
48003일요일18:30강변대로532번길섬김의교회다솔유통33
214일요일18:00번영로S-Oil사랑드림셀프대연터널북측68
요일시분구간명시점종점속도
72441일요일18:45전포대로전포동부산은행앞사거리동성중고앞교차로26
84613일요일18:50덕천로신만덕교차로동원아파트앞교차로30
17837일요일18:10백양관문로윤선생영어교실백양터널어귀삼거리22
75620일요일18:45법원북로거제동1499-1부산지방법원가정지원25
95567월요일18:00범일로90번길부산은행범일동지점코리아시티관광호텔16
91280일요일18:55장림번영로장림1동행정복지센터조흥은행9
14865일요일18:05중앙대로260번길제1지하차도초량역6번출구7
27865일요일18:15녹산산단289로비투나인성골슈퍼28
65253일요일18:40괴정로괴정동삼거리부산은행사하지점18
18425일요일18:10경부고속도로노포IC노포JC89

Duplicate rows

Most frequently occurring

요일시분구간명시점종점속도# duplicates
0일요일18:00광안해변로358번길해마수산해마수산142
1일요일18:00광안해변로378번길환경생태공학연구원환경생태공학연구원182
2일요일18:00중앙대로부전사거리부전사거리262
3일요일18:05경부고속도로구서IC구서IC602
4일요일18:15기장해안로연화리507연화리507232
5일요일18:20광안해변로378번길환경생태공학연구원환경생태공학연구원182
6일요일18:30사리로튼튼어린이집튼튼어린이집182
7일요일18:30일광로일광삼거리이천교동측212
8일요일18:45기장해안로연화리507연화리507232
9일요일18:55번영로회동교차로회동교차로432