Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

DateTime3
Text2
Numeric2

Dataset

Description부산광역시 교통정보서비스센터에서 운영중인 교통정보수집장치(RSE)를 통해 수집한 RSE구간별 가공된 교통정보(가공일시, 시점, 시점통과시간, 종점, 속도, 통과시간)를 제공합니다.
Author부산광역시
URLhttps://www.data.go.kr/data/15041718/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
속도 is highly overall correlated with 통과시간(초)High correlation
통과시간(초) is highly overall correlated with 속도 High correlation

Reproduction

Analysis started2024-04-21 01:08:31.487868
Analysis finished2024-04-21 01:08:33.963764
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가공일시
Date

Distinct2543
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-31 00:00:00
Maximum2024-03-31 07:27:50
2024-04-21T10:08:34.040691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:34.165100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시점
Text

Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:08:34.364534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.7802
Min length3

Characters and Unicode

Total characters57802
Distinct characters158
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

Unique0 ?
Unique (%)0.0%

Sample

1st row부곡사거리
2nd row세산교차로
3rd row문현램프
4th row세산교차로
5th row개성중사거리
ValueCountFrequency (%)
덕천낙동강교 509
 
4.6%
동측 487
 
4.4%
개성중사거리 472
 
4.3%
진양사거리 368
 
3.3%
대연램프 359
 
3.3%
안락교차로 356
 
3.2%
연산교차로 350
 
3.2%
서면교차로 335
 
3.0%
범냇골램프 309
 
2.8%
양정교차로 302
 
2.7%
Other values (72) 7183
65.1%
2024-04-21T10:08:34.662437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 3982
 
6.9%
로 3271
 
5.7%
리 3082
 
5.3%
거 3008
 
5.2%
차 2991
 
5.2%
동 1959
 
3.4%
사 1743
 
3.0%
삼 1422
 
2.5%
측 1093
 
1.9%
프 1063
 
1.8%
Other values (148) 34188
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55133
95.4%
Space Separator 1030
 
1.8%
Uppercase Letter 540
 
0.9%
Close Punctuation 372
 
0.6%
Open Punctuation 372
 
0.6%
Decimal Number 206
 
0.4%
Dash Punctuation 149
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 3982
 
7.2%
로 3271
 
5.9%
리 3082
 
5.6%
거 3008
 
5.5%
차 2991
 
5.4%
동 1959
 
3.6%
사 1743
 
3.2%
삼 1422
 
2.6%
측 1093
 
2.0%
프 1063
 
1.9%
Other values (136) 31519
57.2%
Uppercase Letter
ValueCountFrequency (%)
I 162
30.0%
C 162
30.0%
P 72
13.3%
T 72
13.3%
A 72
13.3%
Decimal Number
ValueCountFrequency (%)
3 162
78.6%
4 22
 
10.7%
9 22
 
10.7%
Space Separator
ValueCountFrequency (%)
1030
100.0%
Close Punctuation
ValueCountFrequency (%)
) 372
100.0%
Open Punctuation
ValueCountFrequency (%)
( 372
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55133
95.4%
Common 2129
 
3.7%
Latin 540
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 3982
 
7.2%
로 3271
 
5.9%
리 3082
 
5.6%
거 3008
 
5.5%
차 2991
 
5.4%
동 1959
 
3.6%
사 1743
 
3.2%
삼 1422
 
2.6%
측 1093
 
2.0%
프 1063
 
1.9%
Other values (136) 31519
57.2%
Common
ValueCountFrequency (%)
1030
48.4%
) 372
 
17.5%
( 372
 
17.5%
3 162
 
7.6%
- 149
 
7.0%
4 22
 
1.0%
9 22
 
1.0%
Latin
ValueCountFrequency (%)
I 162
30.0%
C 162
30.0%
P 72
13.3%
T 72
13.3%
A 72
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55133
95.4%
ASCII 2669
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 3982
 
7.2%
로 3271
 
5.9%
리 3082
 
5.6%
거 3008
 
5.5%
차 2991
 
5.4%
동 1959
 
3.6%
사 1743
 
3.2%
삼 1422
 
2.6%
측 1093
 
2.0%
프 1063
 
1.9%
Other values (136) 31519
57.2%
ASCII
ValueCountFrequency (%)
1030
38.6%
) 372
 
13.9%
( 372
 
13.9%
3 162
 
6.1%
I 162
 
6.1%
C 162
 
6.1%
- 149
 
5.6%
P 72
 
2.7%
T 72
 
2.7%
A 72
 
2.7%
Other values (2) 44
 
1.6%

시점통과시간
Date

Distinct8143
Distinct (%)81.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-30 23:26:43
Maximum2024-03-31 07:26:58
2024-04-21T10:08:34.775072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:34.898619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종점
Text

Distinct78
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-21T10:08:35.118593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.8631
Min length3

Characters and Unicode

Total characters58631
Distinct characters158
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

Unique0 ?
Unique (%)0.0%

Sample

1st row금정경찰서교차로
2nd row마음소류지 삼거리
3rd row대연램프
4th row조만교
5th row동의대어귀사거리
ValueCountFrequency (%)
덕천낙동강교 581
 
5.2%
동측 458
 
4.1%
개성중사거리 446
 
4.0%
안락교차로 361
 
3.2%
범냇골램프 352
 
3.2%
진양사거리 344
 
3.1%
대연램프 324
 
2.9%
연산교차로 321
 
2.9%
서면교차로 295
 
2.6%
양정교차로 268
 
2.4%
Other values (72) 7407
66.4%
2024-04-21T10:08:35.430716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 4056
 
6.9%
로 3289
 
5.6%
리 3069
 
5.2%
차 3052
 
5.2%
거 2955
 
5.0%
동 1993
 
3.4%
사 1709
 
2.9%
삼 1530
 
2.6%
1157
 
2.0%
프 1110
 
1.9%
Other values (148) 34711
59.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55643
94.9%
Space Separator 1157
 
2.0%
Uppercase Letter 780
 
1.3%
Open Punctuation 342
 
0.6%
Close Punctuation 342
 
0.6%
Decimal Number 229
 
0.4%
Dash Punctuation 138
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 4056
 
7.3%
로 3289
 
5.9%
리 3069
 
5.5%
차 3052
 
5.5%
거 2955
 
5.3%
동 1993
 
3.6%
사 1709
 
3.1%
삼 1530
 
2.7%
프 1110
 
2.0%
측 1107
 
2.0%
Other values (136) 31773
57.1%
Uppercase Letter
ValueCountFrequency (%)
C 249
31.9%
I 249
31.9%
A 94
 
12.1%
T 94
 
12.1%
P 94
 
12.1%
Decimal Number
ValueCountFrequency (%)
3 185
80.8%
4 22
 
9.6%
9 22
 
9.6%
Space Separator
ValueCountFrequency (%)
1157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 342
100.0%
Close Punctuation
ValueCountFrequency (%)
) 342
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 138
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55643
94.9%
Common 2208
 
3.8%
Latin 780
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 4056
 
7.3%
로 3289
 
5.9%
리 3069
 
5.5%
차 3052
 
5.5%
거 2955
 
5.3%
동 1993
 
3.6%
사 1709
 
3.1%
삼 1530
 
2.7%
프 1110
 
2.0%
측 1107
 
2.0%
Other values (136) 31773
57.1%
Common
ValueCountFrequency (%)
1157
52.4%
( 342
 
15.5%
) 342
 
15.5%
3 185
 
8.4%
- 138
 
6.2%
4 22
 
1.0%
9 22
 
1.0%
Latin
ValueCountFrequency (%)
C 249
31.9%
I 249
31.9%
A 94
 
12.1%
T 94
 
12.1%
P 94
 
12.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55643
94.9%
ASCII 2988
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 4056
 
7.3%
로 3289
 
5.9%
리 3069
 
5.5%
차 3052
 
5.5%
거 2955
 
5.3%
동 1993
 
3.6%
사 1709
 
3.1%
삼 1530
 
2.7%
프 1110
 
2.0%
측 1107
 
2.0%
Other values (136) 31773
57.1%
ASCII
ValueCountFrequency (%)
1157
38.7%
( 342
 
11.4%
) 342
 
11.4%
C 249
 
8.3%
I 249
 
8.3%
3 185
 
6.2%
- 138
 
4.6%
A 94
 
3.1%
T 94
 
3.1%
P 94
 
3.1%
Other values (2) 44
 
1.5%

종점통과시간
Date

Distinct8167
Distinct (%)81.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-03-30 23:59:56
Maximum2024-03-31 07:27:49
2024-04-21T10:08:35.548711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:35.660052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

속도
Real number (ℝ)

HIGH CORRELATION 

Distinct130
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.2871
Minimum1
Maximum142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:08:35.763830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12
Q127
median42
Q365
95-th percentile88
Maximum142
Range141
Interquartile range (IQR)38

Descriptive statistics

Standard deviation24.288369
Coefficient of variation (CV)0.524733
Kurtosis-0.41999981
Mean46.2871
Median Absolute Deviation (MAD)18
Skewness0.45694032
Sum462871
Variance589.92487
MonotonicityNot monotonic
2024-04-21T10:08:35.898452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26 208
 
2.1%
31 203
 
2.0%
29 192
 
1.9%
32 182
 
1.8%
27 182
 
1.8%
30 180
 
1.8%
33 179
 
1.8%
34 171
 
1.7%
28 171
 
1.7%
35 168
 
1.7%
Other values (120) 8164
81.6%
ValueCountFrequency (%)
1 15
 
0.1%
2 35
0.4%
3 45
0.4%
4 28
0.3%
5 52
0.5%
6 60
0.6%
7 37
0.4%
8 56
0.6%
9 51
0.5%
10 49
0.5%
ValueCountFrequency (%)
142 1
 
< 0.1%
139 1
 
< 0.1%
137 1
 
< 0.1%
136 1
 
< 0.1%
129 1
 
< 0.1%
128 1
 
< 0.1%
126 4
< 0.1%
125 3
< 0.1%
124 3
< 0.1%
123 3
< 0.1%

통과시간(초)
Real number (ℝ)

HIGH CORRELATION 

Distinct814
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203.4545
Minimum21
Maximum3443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-21T10:08:36.011942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile52
Q1103
median155
Q3220
95-th percentile449.05
Maximum3443
Range3422
Interquartile range (IQR)117

Descriptive statistics

Standard deviation258.90447
Coefficient of variation (CV)1.2725424
Kurtosis59.587788
Mean203.4545
Median Absolute Deviation (MAD)58
Skewness6.7950506
Sum2034545
Variance67031.525
MonotonicityNot monotonic
2024-04-21T10:08:36.124951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
117 63
 
0.6%
174 63
 
0.6%
157 62
 
0.6%
144 62
 
0.6%
119 59
 
0.6%
141 58
 
0.6%
134 57
 
0.6%
149 57
 
0.6%
158 57
 
0.6%
133 56
 
0.6%
Other values (804) 9406
94.1%
ValueCountFrequency (%)
21 6
0.1%
22 1
 
< 0.1%
23 4
 
< 0.1%
24 7
0.1%
25 6
0.1%
26 10
0.1%
27 5
0.1%
28 10
0.1%
29 5
0.1%
30 11
0.1%
ValueCountFrequency (%)
3443 1
< 0.1%
3415 1
< 0.1%
3380 1
< 0.1%
3373 1
< 0.1%
3335 1
< 0.1%
3320 1
< 0.1%
3277 1
< 0.1%
3226 2
< 0.1%
3221 1
< 0.1%
3158 1
< 0.1%

Interactions

2024-04-21T10:08:33.615960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:33.399538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:33.697098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:08:33.535117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:08:36.209455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시점종점속도통과시간(초)
시점1.0000.9990.7530.309
종점0.9991.0000.7490.307
속도0.7530.7491.0000.627
통과시간(초)0.3090.3070.6271.000
2024-04-21T10:08:36.283519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
속도통과시간(초)
속도1.000-0.522
통과시간(초)-0.5221.000

Missing values

2024-04-21T10:08:33.815761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:08:33.913194image/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

가공일시시점시점통과시간종점종점통과시간속도통과시간(초)
900392024-03-31 07:03:10부곡사거리2024-03-31 07:00:16금정경찰서교차로2024-03-31 07:03:0437168
765822024-03-31 06:26:00세산교차로2024-03-31 06:24:34마음소류지 삼거리2024-03-31 06:25:586584
827082024-03-31 06:43:00문현램프2024-03-31 06:41:15대연램프2024-03-31 06:42:5881103
554362024-03-31 04:55:50세산교차로2024-03-31 04:52:01조만교2024-03-31 04:55:4945228
219502024-03-31 01:16:10개성중사거리2024-03-31 01:13:29동의대어귀사거리2024-03-31 01:16:0640157
971082024-03-31 07:21:00동대신교차로2024-03-31 07:16:403부두2024-03-31 07:20:5545255
6522024-03-31 00:01:50황령터널(서측)2024-03-30 23:57:49부전동2024-03-31 00:01:4920240
38092024-03-31 00:11:10동대신교차로2024-03-31 00:06:163부두2024-03-31 00:11:0739291
500792024-03-31 04:14:50개좌터널 북측2024-03-31 04:09:59곰내터널 남측2024-03-31 04:14:4756288
95122024-03-31 00:28:40장산역사거리2024-03-31 00:24:29해운대역2024-03-31 00:28:3825249
가공일시시점시점통과시간종점종점통과시간속도통과시간(초)
325392024-03-31 02:08:50정관중앙로-산단로2024-03-31 02:07:07곰내터널 남측2024-03-31 02:08:4793100
377082024-03-31 02:38:50서면교차로2024-03-31 02:34:04범내골교차로2024-03-31 02:38:4215278
412062024-03-31 03:03:20개성중사거리2024-03-31 03:00:52동의대어귀사거리2024-03-31 03:03:2042148
79402024-03-31 00:23:30범내골교차로2024-03-31 00:18:42서면교차로2024-03-31 00:23:2515283
165382024-03-31 00:53:40진양램프2024-03-31 00:51:42범냇골램프2024-03-31 00:53:3470112
950922024-03-31 07:16:20양정교차로2024-03-31 07:13:17신리삼거리2024-03-31 07:16:1230175
281952024-03-31 01:45:00좌천삼거리2024-03-31 01:41:37범내골교차로2024-03-31 01:44:5333196
242162024-03-31 01:26:30문현램프2024-03-31 01:24:30범냇골램프2024-03-31 01:26:2441114
285722024-03-31 01:47:20남문구사거리2024-03-31 01:45:42교대교차로2024-03-31 01:47:173795
833592024-03-31 06:44:50연화육교2024-03-31 06:40:22동부산IC2024-03-31 06:44:4230260

Duplicate rows

Most frequently occurring

가공일시시점시점통과시간종점종점통과시간속도통과시간(초)# duplicates
02024-03-31 07:11:30만덕교차로2024-03-31 07:08:13덕천낙동강교 동측2024-03-31 07:11:27561942