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_지능형교통정보_RSE정보_20240131
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15041718

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-13 13:19:12.564987
Analysis finished2024-03-13 13:19:13.979632
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가공일시
Date

Distinct2216
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-31 00:00:00
Maximum2024-01-31 06:47:40
2024-03-13T22:19:14.067463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:14.273233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시점
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:19:14.509881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.8851
Min length3

Characters and Unicode

Total characters58851
Distinct characters153
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 row세산교차로
2nd row안락뜨란채삼거리
3rd row황령터널(서측)
4th row조만교
5th row만덕교차로
ValueCountFrequency (%)
덕천낙동강교 494
 
4.5%
동측 474
 
4.3%
범냇골램프 421
 
3.8%
대연램프 383
 
3.5%
황령터널(서측 377
 
3.4%
개성중사거리 354
 
3.2%
만덕교차로 335
 
3.0%
황령터널(동측 319
 
2.9%
안락교차로 296
 
2.7%
진양사거리 277
 
2.5%
Other values (71) 7319
66.2%
2024-03-13T22:19:14.919460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 3505
 
6.0%
로 2892
 
4.9%
리 2755
 
4.7%
거 2681
 
4.6%
차 2590
 
4.4%
동 2149
 
3.7%
측 1594
 
2.7%
사 1473
 
2.5%
삼 1379
 
2.3%
터 1321
 
2.2%
Other values (143) 36512
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54965
93.4%
Space Separator 1049
 
1.8%
Open Punctuation 919
 
1.6%
Close Punctuation 919
 
1.6%
Uppercase Letter 503
 
0.9%
Decimal Number 328
 
0.6%
Dash Punctuation 168
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 3505
 
6.4%
로 2892
 
5.3%
리 2755
 
5.0%
거 2681
 
4.9%
차 2590
 
4.7%
동 2149
 
3.9%
측 1594
 
2.9%
사 1473
 
2.7%
삼 1379
 
2.5%
터 1321
 
2.4%
Other values (131) 32626
59.4%
Uppercase Letter
ValueCountFrequency (%)
C 157
31.2%
I 157
31.2%
A 63
12.5%
P 63
12.5%
T 63
12.5%
Decimal Number
ValueCountFrequency (%)
3 164
50.0%
4 82
25.0%
9 82
25.0%
Space Separator
ValueCountFrequency (%)
1049
100.0%
Open Punctuation
ValueCountFrequency (%)
( 919
100.0%
Close Punctuation
ValueCountFrequency (%)
) 919
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54965
93.4%
Common 3383
 
5.7%
Latin 503
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 3505
 
6.4%
로 2892
 
5.3%
리 2755
 
5.0%
거 2681
 
4.9%
차 2590
 
4.7%
동 2149
 
3.9%
측 1594
 
2.9%
사 1473
 
2.7%
삼 1379
 
2.5%
터 1321
 
2.4%
Other values (131) 32626
59.4%
Common
ValueCountFrequency (%)
1049
31.0%
( 919
27.2%
) 919
27.2%
- 168
 
5.0%
3 164
 
4.8%
4 82
 
2.4%
9 82
 
2.4%
Latin
ValueCountFrequency (%)
C 157
31.2%
I 157
31.2%
A 63
12.5%
P 63
12.5%
T 63
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54965
93.4%
ASCII 3886
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 3505
 
6.4%
로 2892
 
5.3%
리 2755
 
5.0%
거 2681
 
4.9%
차 2590
 
4.7%
동 2149
 
3.9%
측 1594
 
2.9%
사 1473
 
2.7%
삼 1379
 
2.5%
터 1321
 
2.4%
Other values (131) 32626
59.4%
ASCII
ValueCountFrequency (%)
1049
27.0%
( 919
23.6%
) 919
23.6%
- 168
 
4.3%
3 164
 
4.2%
C 157
 
4.0%
I 157
 
4.0%
4 82
 
2.1%
9 82
 
2.1%
A 63
 
1.6%
Other values (2) 126
 
3.2%

시점통과시간
Date

Distinct7453
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-30 23:18:20
Maximum2024-01-31 06:46:14
2024-03-13T22:19:15.053085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:15.195375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

종점
Text

Distinct77
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-13T22:19:15.491613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.9825
Min length3

Characters and Unicode

Total characters59825
Distinct characters153
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 row조만교
2nd row재송삼익아파트
3rd row황령터널(동측)
4th row세산교차로
5th row덕천낙동강교 동측
ValueCountFrequency (%)
덕천낙동강교 696
 
6.1%
동측 554
 
4.9%
범냇골램프 413
 
3.6%
황령터널(서측 330
 
2.9%
대연램프 327
 
2.9%
개성중사거리 318
 
2.8%
세산교차로 293
 
2.6%
진양사거리 292
 
2.6%
문현램프 288
 
2.5%
안락교차로 279
 
2.5%
Other values (71) 7532
66.5%
2024-03-13T22:19:15.851157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 3653
 
6.1%
로 2810
 
4.7%
차 2561
 
4.3%
리 2496
 
4.2%
동 2452
 
4.1%
거 2419
 
4.0%
측 1757
 
2.9%
삼 1412
 
2.4%
사 1368
 
2.3%
1322
 
2.2%
Other values (143) 37575
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55410
92.6%
Space Separator 1322
 
2.2%
Uppercase Letter 863
 
1.4%
Close Punctuation 845
 
1.4%
Open Punctuation 845
 
1.4%
Decimal Number 398
 
0.7%
Dash Punctuation 142
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 3653
 
6.6%
로 2810
 
5.1%
차 2561
 
4.6%
리 2496
 
4.5%
동 2452
 
4.4%
거 2419
 
4.4%
측 1757
 
3.2%
삼 1412
 
2.5%
사 1368
 
2.5%
프 1304
 
2.4%
Other values (131) 33178
59.9%
Uppercase Letter
ValueCountFrequency (%)
C 307
35.6%
I 307
35.6%
P 83
 
9.6%
A 83
 
9.6%
T 83
 
9.6%
Decimal Number
ValueCountFrequency (%)
3 196
49.2%
4 101
25.4%
9 101
25.4%
Space Separator
ValueCountFrequency (%)
1322
100.0%
Close Punctuation
ValueCountFrequency (%)
) 845
100.0%
Open Punctuation
ValueCountFrequency (%)
( 845
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55410
92.6%
Common 3552
 
5.9%
Latin 863
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 3653
 
6.6%
로 2810
 
5.1%
차 2561
 
4.6%
리 2496
 
4.5%
동 2452
 
4.4%
거 2419
 
4.4%
측 1757
 
3.2%
삼 1412
 
2.5%
사 1368
 
2.5%
프 1304
 
2.4%
Other values (131) 33178
59.9%
Common
ValueCountFrequency (%)
1322
37.2%
) 845
23.8%
( 845
23.8%
3 196
 
5.5%
- 142
 
4.0%
4 101
 
2.8%
9 101
 
2.8%
Latin
ValueCountFrequency (%)
C 307
35.6%
I 307
35.6%
P 83
 
9.6%
A 83
 
9.6%
T 83
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55410
92.6%
ASCII 4415
 
7.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 3653
 
6.6%
로 2810
 
5.1%
차 2561
 
4.6%
리 2496
 
4.5%
동 2452
 
4.4%
거 2419
 
4.4%
측 1757
 
3.2%
삼 1412
 
2.5%
사 1368
 
2.5%
프 1304
 
2.4%
Other values (131) 33178
59.9%
ASCII
ValueCountFrequency (%)
1322
29.9%
) 845
19.1%
( 845
19.1%
C 307
 
7.0%
I 307
 
7.0%
3 196
 
4.4%
- 142
 
3.2%
4 101
 
2.3%
9 101
 
2.3%
P 83
 
1.9%
Other values (2) 166
 
3.8%

종점통과시간
Date

Distinct7357
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2024-01-30 23:59:57
Maximum2024-01-31 06:47:40
2024-03-13T22:19:15.984530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:16.151360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

속도
Real number (ℝ)

Distinct124
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.2208
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:19:16.352337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14
Q129
median44
Q362
95-th percentile84
Maximum132
Range131
Interquartile range (IQR)33

Descriptive statistics

Standard deviation22.159972
Coefficient of variation (CV)0.47943722
Kurtosis-0.2881689
Mean46.2208
Median Absolute Deviation (MAD)16
Skewness0.38904414
Sum462208
Variance491.06435
MonotonicityNot monotonic
2024-03-13T22:19:16.533582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 234
 
2.3%
27 191
 
1.9%
50 187
 
1.9%
25 185
 
1.8%
44 182
 
1.8%
33 176
 
1.8%
48 173
 
1.7%
34 172
 
1.7%
28 172
 
1.7%
29 172
 
1.7%
Other values (114) 8156
81.6%
ValueCountFrequency (%)
1 12
 
0.1%
2 33
0.3%
3 42
0.4%
4 31
0.3%
5 34
0.3%
6 21
0.2%
7 33
0.3%
8 46
0.5%
9 48
0.5%
10 37
0.4%
ValueCountFrequency (%)
132 1
 
< 0.1%
126 2
< 0.1%
125 1
 
< 0.1%
124 1
 
< 0.1%
123 3
< 0.1%
122 2
< 0.1%
121 1
 
< 0.1%
120 4
< 0.1%
119 2
< 0.1%
117 2
< 0.1%

통과시간(초)
Real number (ℝ)

Distinct766
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean205.5017
Minimum20
Maximum3600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-13T22:19:16.696489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile57
Q1109
median158
Q3228
95-th percentile415.05
Maximum3600
Range3580
Interquartile range (IQR)119

Descriptive statistics

Standard deviation248.48052
Coefficient of variation (CV)1.2091409
Kurtosis69.256086
Mean205.5017
Median Absolute Deviation (MAD)57
Skewness7.2639728
Sum2055017
Variance61742.569
MonotonicityNot monotonic
2024-03-13T22:19:16.850224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126 70
 
0.7%
125 69
 
0.7%
145 65
 
0.7%
122 63
 
0.6%
131 60
 
0.6%
133 60
 
0.6%
117 60
 
0.6%
141 60
 
0.6%
155 59
 
0.6%
129 58
 
0.6%
Other values (756) 9376
93.8%
ValueCountFrequency (%)
20 1
 
< 0.1%
21 2
 
< 0.1%
22 2
 
< 0.1%
23 3
 
< 0.1%
24 2
 
< 0.1%
26 2
 
< 0.1%
27 7
0.1%
28 1
 
< 0.1%
29 4
 
< 0.1%
30 12
0.1%
ValueCountFrequency (%)
3600 1
< 0.1%
3575 1
< 0.1%
3505 1
< 0.1%
3495 1
< 0.1%
3472 1
< 0.1%
3466 1
< 0.1%
3343 1
< 0.1%
3331 1
< 0.1%
3312 1
< 0.1%
3138 1
< 0.1%

Interactions

2024-03-13T22:19:13.534460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:13.353432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:13.670051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:19:13.445789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:19:16.966686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시점종점속도통과시간(초)
시점1.0000.9990.7190.317
종점0.9991.0000.7220.343
속도0.7190.7221.0000.661
통과시간(초)0.3170.3430.6611.000
2024-03-13T22:19:17.352188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
속도통과시간(초)
속도1.000-0.486
통과시간(초)-0.4861.000

Missing values

2024-03-13T22:19:13.801606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:19:13.917694image/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)
771482024-01-31 06:17:50세산교차로2024-01-31 06:15:35조만교2024-01-31 06:17:4976134
185192024-01-31 01:31:10안락뜨란채삼거리2024-01-31 01:28:13재송삼익아파트2024-01-31 01:31:0223169
345922024-01-31 04:11:50황령터널(서측)2024-01-31 04:09:16황령터널(동측)2024-01-31 04:11:4647150
273182024-01-31 02:55:00조만교2024-01-31 02:51:42세산교차로2024-01-31 02:54:5354191
688922024-01-31 06:05:20만덕교차로2024-01-31 06:01:55덕천낙동강교 동측2024-01-31 06:05:1454199
944722024-01-31 06:40:40침례병원입구2024-01-31 06:36:39금정경찰서교차로2024-01-31 06:40:3136232
82922024-01-31 00:33:203부두2024-01-31 00:27:27문현램프2024-01-31 00:33:2038353
468532024-01-31 05:14:40세산교차로2024-01-31 05:12:09마음소류지 삼거리2024-01-31 05:14:4036151
907632024-01-31 06:36:10진양사거리2024-01-31 06:34:17당감삼익APT삼거리2024-01-31 06:36:0331106
465002024-01-31 05:13:30신리삼거리2024-01-31 05:11:18양정교차로2024-01-31 05:13:2242124
가공일시시점시점통과시간종점종점통과시간속도통과시간(초)
311952024-01-31 03:37:50범냇골램프2024-01-31 03:35:49진양램프2024-01-31 03:37:4965120
539672024-01-31 05:36:00당감사거리2024-01-31 05:32:51당감주공2024-01-31 05:35:5733186
45602024-01-31 00:17:40당감주공2024-01-31 00:13:18당감사거리2024-01-31 00:17:3324255
70482024-01-31 00:27:40안락교차로2024-01-30 23:54:40안락뜨란채삼거리2024-01-31 00:27:3321973
318702024-01-31 03:45:00덕천낙동강교 동측2024-01-31 03:43:54덕천낙동강교 서측2024-01-31 03:44:528558
939302024-01-31 06:40:00하단교차로2024-01-31 06:38:12낙동강하구둑 동측2024-01-31 06:39:5639104
223162024-01-31 02:03:40연산교차로2024-01-31 02:00:27양정교차로2024-01-31 02:03:3134184
843562024-01-31 06:27:40하단교차로2024-01-31 06:25:10낙동강하구둑 동측2024-01-31 06:27:3727147
736322024-01-31 06:12:40곰내터널 남측2024-01-31 06:10:33정관중앙로-산단로2024-01-31 06:12:4073127
449742024-01-31 05:07:50안락교차로2024-01-31 05:04:22안락뜨란채삼거리2024-01-31 05:07:4821206

Duplicate rows

Most frequently occurring

가공일시시점시점통과시간종점종점통과시간속도통과시간(초)# duplicates
02024-01-31 06:43:50대연램프2024-01-31 06:41:53문현램프2024-01-31 06:43:50721172