Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows1579
Duplicate rows (%)15.8%
Total size in memory644.5 KiB
Average record size in memory66.0 B

Variable types

DateTime1
Numeric2
Categorical1
Text3

Dataset

Description인천광역시 지능형교통시스템(UTIS)의 교통 소통정보(구간id, 구간명, 시점, 종점, 통행속도(km/h), 통행시간(초))와 관련된 데이터 입니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15089377

Alerts

Dataset has 1579 (15.8%) duplicate rowsDuplicates
구간아이디 is highly overall correlated with 구간명High correlation
구간명 is highly overall correlated with 구간아이디High correlation

Reproduction

Analysis started2024-01-28 15:19:13.707778
Analysis finished2024-01-28 15:19:14.648775
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가공일시
Date

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-08-01 00:00:00
Maximum2021-08-04 00:00:00
2024-01-29T00:19:14.684235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:19:14.757632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

구간아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct222
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6569018 × 109
Minimum1.6100086 × 109
Maximum1.6900242 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T00:19:14.850174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6100086 × 109
5-th percentile1.6300198 × 109
Q11.6400502 × 109
median1.6500546 × 109
Q31.6800095 × 109
95-th percentile1.6800635 × 109
Maximum1.6900242 × 109
Range80015600
Interquartile range (IQR)39959302

Descriptive statistics

Standard deviation19579603
Coefficient of variation (CV)0.011816997
Kurtosis-1.0106452
Mean1.6569018 × 109
Median Absolute Deviation (MAD)10052900
Skewness0.019896389
Sum1.6569018 × 1013
Variance3.8336085 × 1014
MonotonicityNot monotonic
2024-01-29T00:19:14.971471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1630023200 94
 
0.9%
1690003701 89
 
0.9%
1630031800 88
 
0.9%
1650062500 85
 
0.9%
1680057202 83
 
0.8%
1650008900 83
 
0.8%
1650039400 82
 
0.8%
1660004800 82
 
0.8%
1680000402 81
 
0.8%
1670029700 79
 
0.8%
Other values (212) 9154
91.5%
ValueCountFrequency (%)
1610008600 23
0.2%
1610008800 10
0.1%
1610069700 8
 
0.1%
1610070100 5
 
0.1%
1610071700 5
 
0.1%
1610071800 7
 
0.1%
1610082000 7
 
0.1%
1610082100 4
 
< 0.1%
1610082200 8
 
0.1%
1610082400 8
 
0.1%
ValueCountFrequency (%)
1690024200 32
 
0.3%
1690024100 34
 
0.3%
1690012600 21
 
0.2%
1690012500 20
 
0.2%
1690011600 28
 
0.3%
1690011500 40
0.4%
1690003802 18
 
0.2%
1690003801 62
0.6%
1690003702 17
 
0.2%
1690003701 89
0.9%

구간명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경원로
1343 
남동로
1218 
지방도305호선
1103 
인주로
660 
앵고개길
565 
Other values (27)
5111 

Length

Max length11
Median length8
Mean length4.5713
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경명로
2nd row한들로
3rd row경원로
4th row원정로10번길
5th row지방도305호선

Common Values

ValueCountFrequency (%)
경원로 1343
13.4%
남동로 1218
 
12.2%
지방도305호선 1103
 
11.0%
인주로 660
 
6.6%
앵고개길 565
 
5.7%
봉수대로 447
 
4.5%
청릉로 443
 
4.4%
국가지원지방도84호선 393
 
3.9%
미추홀길 369
 
3.7%
호구포길 342
 
3.4%
Other values (22) 3117
31.2%

Length

2024-01-29T00:19:15.088094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경원로 1343
13.4%
남동로 1218
 
12.2%
지방도305호선 1103
 
11.0%
인주로 660
 
6.6%
앵고개길 565
 
5.7%
봉수대로 447
 
4.5%
청릉로 443
 
4.4%
국가지원지방도84호선 393
 
3.9%
미추홀길 369
 
3.7%
호구포길 342
 
3.4%
Other values (22) 3117
31.2%

시점
Text

Distinct149
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:19:15.272529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.7464
Min length1

Characters and Unicode

Total characters57464
Distinct characters220
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

Unique0 ?
Unique (%)0.0%

Sample

1st row계산삼거리
2nd row백석초교삼거리
3rd row105호고가교
4th row취락진출입
5th row-
ValueCountFrequency (%)
545
 
5.3%
옹밀고가교 267
 
2.6%
왕길지하차도 217
 
2.1%
사리골사거리 199
 
1.9%
동춘역사거리 184
 
1.8%
안동포사거리 179
 
1.8%
무명신호3거리 153
 
1.5%
취락진출입 149
 
1.5%
길병원사거리 148
 
1.5%
십정사거리 148
 
1.5%
Other values (142) 8017
78.6%
2024-01-29T00:19:15.573272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 5709
 
9.9%
거 5344
 
9.3%
사 4381
 
7.6%
동 1247
 
2.2%
교 1146
 
2.0%
구 893
 
1.6%
고 820
 
1.4%
삼 735
 
1.3%
원 722
 
1.3%
가 694
 
1.2%
Other values (210) 35773
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54064
94.1%
Decimal Number 1944
 
3.4%
Dash Punctuation 545
 
0.9%
Uppercase Letter 432
 
0.8%
Space Separator 206
 
0.4%
Open Punctuation 123
 
0.2%
Close Punctuation 123
 
0.2%
Connector Punctuation 27
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 5709
 
10.6%
거 5344
 
9.9%
사 4381
 
8.1%
동 1247
 
2.3%
교 1146
 
2.1%
구 893
 
1.7%
고 820
 
1.5%
삼 735
 
1.4%
원 722
 
1.3%
가 694
 
1.3%
Other values (191) 32373
59.9%
Decimal Number
ValueCountFrequency (%)
3 651
33.5%
1 383
19.7%
4 301
15.5%
0 243
 
12.5%
5 156
 
8.0%
2 138
 
7.1%
6 67
 
3.4%
7 5
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
I 94
21.8%
C 94
21.8%
A 75
17.4%
Q 67
15.5%
G 51
11.8%
L 51
11.8%
Dash Punctuation
ValueCountFrequency (%)
- 545
100.0%
Space Separator
ValueCountFrequency (%)
206
100.0%
Open Punctuation
ValueCountFrequency (%)
( 123
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54064
94.1%
Common 2968
 
5.2%
Latin 432
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 5709
 
10.6%
거 5344
 
9.9%
사 4381
 
8.1%
동 1247
 
2.3%
교 1146
 
2.1%
구 893
 
1.7%
고 820
 
1.5%
삼 735
 
1.4%
원 722
 
1.3%
가 694
 
1.3%
Other values (191) 32373
59.9%
Common
ValueCountFrequency (%)
3 651
21.9%
- 545
18.4%
1 383
12.9%
4 301
10.1%
0 243
 
8.2%
206
 
6.9%
5 156
 
5.3%
2 138
 
4.6%
( 123
 
4.1%
) 123
 
4.1%
Other values (3) 99
 
3.3%
Latin
ValueCountFrequency (%)
I 94
21.8%
C 94
21.8%
A 75
17.4%
Q 67
15.5%
G 51
11.8%
L 51
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54064
94.1%
ASCII 3400
 
5.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 5709
 
10.6%
거 5344
 
9.9%
사 4381
 
8.1%
동 1247
 
2.3%
교 1146
 
2.1%
구 893
 
1.7%
고 820
 
1.5%
삼 735
 
1.4%
원 722
 
1.3%
가 694
 
1.3%
Other values (191) 32373
59.9%
ASCII
ValueCountFrequency (%)
3 651
19.1%
- 545
16.0%
1 383
11.3%
4 301
8.9%
0 243
 
7.1%
206
 
6.1%
5 156
 
4.6%
2 138
 
4.1%
( 123
 
3.6%
) 123
 
3.6%
Other values (9) 531
15.6%

종점
Text

Distinct147
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:19:15.745357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length5.766
Min length1

Characters and Unicode

Total characters57660
Distinct characters218
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

Unique1 ?
Unique (%)< 0.1%

Sample

1st row용종사거리
2nd row한들3거리
3rd row원인제역삼거리
4th row무명비신호3거리
5th row백석초교삼거리
ValueCountFrequency (%)
601
 
5.9%
옹밀고가교 278
 
2.7%
왕길지하차도 224
 
2.2%
동춘역사거리 191
 
1.9%
안동포사거리 172
 
1.7%
사리골사거리 172
 
1.7%
취락진출입 168
 
1.7%
열우물사거리 154
 
1.5%
석천사거리 147
 
1.4%
백석초교삼거리 137
 
1.3%
Other values (140) 7928
77.9%
2024-01-29T00:19:16.016189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 5547
 
9.6%
거 5250
 
9.1%
사 4206
 
7.3%
교 1239
 
2.1%
동 1167
 
2.0%
고 914
 
1.6%
가 869
 
1.5%
구 837
 
1.5%
삼 805
 
1.4%
장 768
 
1.3%
Other values (208) 36058
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54118
93.9%
Decimal Number 1981
 
3.4%
Dash Punctuation 601
 
1.0%
Uppercase Letter 499
 
0.9%
Space Separator 172
 
0.3%
Open Punctuation 124
 
0.2%
Close Punctuation 124
 
0.2%
Connector Punctuation 41
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 5547
 
10.2%
거 5250
 
9.7%
사 4206
 
7.8%
교 1239
 
2.3%
동 1167
 
2.2%
고 914
 
1.7%
가 869
 
1.6%
구 837
 
1.5%
삼 805
 
1.5%
장 768
 
1.4%
Other values (189) 32516
60.1%
Decimal Number
ValueCountFrequency (%)
3 601
30.3%
1 362
18.3%
4 358
18.1%
0 227
 
11.5%
2 197
 
9.9%
5 184
 
9.3%
6 45
 
2.3%
7 7
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 146
29.3%
I 146
29.3%
Q 59
11.8%
G 52
 
10.4%
L 52
 
10.4%
A 44
 
8.8%
Dash Punctuation
ValueCountFrequency (%)
- 601
100.0%
Space Separator
ValueCountFrequency (%)
172
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54118
93.9%
Common 3043
 
5.3%
Latin 499
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 5547
 
10.2%
거 5250
 
9.7%
사 4206
 
7.8%
교 1239
 
2.3%
동 1167
 
2.2%
고 914
 
1.7%
가 869
 
1.6%
구 837
 
1.5%
삼 805
 
1.5%
장 768
 
1.4%
Other values (189) 32516
60.1%
Common
ValueCountFrequency (%)
3 601
19.8%
- 601
19.8%
1 362
11.9%
4 358
11.8%
0 227
 
7.5%
2 197
 
6.5%
5 184
 
6.0%
172
 
5.7%
( 124
 
4.1%
) 124
 
4.1%
Other values (3) 93
 
3.1%
Latin
ValueCountFrequency (%)
C 146
29.3%
I 146
29.3%
Q 59
11.8%
G 52
 
10.4%
L 52
 
10.4%
A 44
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54118
93.9%
ASCII 3542
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 5547
 
10.2%
거 5250
 
9.7%
사 4206
 
7.8%
교 1239
 
2.3%
동 1167
 
2.2%
고 914
 
1.7%
가 869
 
1.6%
구 837
 
1.5%
삼 805
 
1.5%
장 768
 
1.4%
Other values (189) 32516
60.1%
ASCII
ValueCountFrequency (%)
3 601
17.0%
- 601
17.0%
1 362
10.2%
4 358
10.1%
0 227
 
6.4%
2 197
 
5.6%
5 184
 
5.2%
172
 
4.9%
C 146
 
4.1%
I 146
 
4.1%
Other values (9) 548
15.5%

통행속도(킬로미터 퍼 아워)
Real number (ℝ)

Distinct160
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.7517
Minimum1
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-29T00:19:16.127914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q134
median46
Q356
95-th percentile80
Maximum193
Range192
Interquartile range (IQR)22

Descriptive statistics

Standard deviation19.688952
Coefficient of variation (CV)0.42113873
Kurtosis5.0043486
Mean46.7517
Median Absolute Deviation (MAD)11
Skewness1.3454956
Sum467517
Variance387.65481
MonotonicityNot monotonic
2024-01-29T00:19:16.246698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48 275
 
2.8%
44 265
 
2.6%
50 263
 
2.6%
46 261
 
2.6%
42 251
 
2.5%
47 250
 
2.5%
49 249
 
2.5%
52 241
 
2.4%
51 235
 
2.4%
43 234
 
2.3%
Other values (150) 7476
74.8%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 7
0.1%
3 4
 
< 0.1%
4 9
0.1%
5 8
0.1%
6 7
0.1%
7 6
 
0.1%
8 6
 
0.1%
9 4
 
< 0.1%
10 17
0.2%
ValueCountFrequency (%)
193 1
 
< 0.1%
190 1
 
< 0.1%
188 1
 
< 0.1%
186 1
 
< 0.1%
184 2
< 0.1%
173 1
 
< 0.1%
170 1
 
< 0.1%
169 3
< 0.1%
164 1
 
< 0.1%
159 1
 
< 0.1%

통행시간(초)
Text

Distinct299
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-01-29T00:19:16.596663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0562
Min length1

Characters and Unicode

Total characters20562
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)0.5%

Sample

1st row20
2nd row149
3rd row16
4th row18
5th row104
ValueCountFrequency (%)
23 275
 
2.8%
26 273
 
2.7%
21 271
 
2.7%
27 270
 
2.7%
24 262
 
2.6%
30 257
 
2.6%
28 253
 
2.5%
29 245
 
2.5%
19 243
 
2.4%
18 241
 
2.4%
Other values (289) 7410
74.1%
2024-01-29T00:19:17.055741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3786
18.4%
1 3426
16.7%
3 2902
14.1%
4 2000
9.7%
5 1659
8.1%
6 1498
 
7.3%
7 1448
 
7.0%
8 1404
 
6.8%
9 1227
 
6.0%
0 1211
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20561
> 99.9%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3786
18.4%
1 3426
16.7%
3 2902
14.1%
4 2000
9.7%
5 1659
8.1%
6 1498
 
7.3%
7 1448
 
7.0%
8 1404
 
6.8%
9 1227
 
6.0%
0 1211
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20562
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3786
18.4%
1 3426
16.7%
3 2902
14.1%
4 2000
9.7%
5 1659
8.1%
6 1498
 
7.3%
7 1448
 
7.0%
8 1404
 
6.8%
9 1227
 
6.0%
0 1211
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20562
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3786
18.4%
1 3426
16.7%
3 2902
14.1%
4 2000
9.7%
5 1659
8.1%
6 1498
 
7.3%
7 1448
 
7.0%
8 1404
 
6.8%
9 1227
 
6.0%
0 1211
 
5.9%

Interactions

2024-01-29T00:19:14.313613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:19:14.133288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:19:14.403105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:19:14.220644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:19:17.136860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가공일시구간아이디구간명통행속도(킬로미터 퍼 아워)
가공일시1.0000.0770.1010.068
구간아이디0.0771.0000.9760.425
구간명0.1010.9761.0000.554
통행속도(킬로미터 퍼 아워)0.0680.4250.5541.000
2024-01-29T00:19:17.212781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구간아이디통행속도(킬로미터 퍼 아워)구간명
구간아이디1.000-0.1640.843
통행속도(킬로미터 퍼 아워)-0.1641.0000.230
구간명0.8430.2301.000

Missing values

2024-01-29T00:19:14.514259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:19:14.603677image/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

가공일시구간아이디구간명시점종점통행속도(킬로미터 퍼 아워)통행시간(초)
80002021-08-011670029600경명로계산삼거리용종사거리4820
320922021-08-021680019900한들로백석초교삼거리한들3거리27149
387422021-08-021640015700경원로105호고가교원인제역삼거리7016
322472021-08-021680010000원정로10번길취락진출입무명비신호3거리2018
388162021-08-021680008405지방도305호선-백석초교삼거리31104
208222021-08-011660004800경원로십정사거리열우물사거리6028
253902021-08-021680057202봉수대로안동포사거리옹밀고가교5851
732342021-08-031630001700인천대로도화IC북측(법원고가교사거리)인하대병원거리80174
869212021-08-041680009900원정로10번길무명비신호3거리취락진출입3311
405112021-08-021660004900경원로열우물사거리십정사거리5133
가공일시구간아이디구간명시점종점통행속도(킬로미터 퍼 아워)통행시간(초)
453012021-08-021630027500인주로용일사거리정현빌딩5135
593552021-08-031650015703논현고잔로--4520
532682021-08-021630037700경원로용하약국법원사거리5328
921342021-08-041650012200인주로올림픽공원사거리승기사거리3395
103602021-08-011650062600남동로석천사거리구월중학교2241
615342021-08-031630031700미추홀길시민회관사거리계몽사2850
49172021-08-011680009502지방도305호선기아자동차Q써비스(당하점)부일철강2230
634052021-08-031690003200국가지원지방도84호선선원면만남의광장찬우물고개3445
233882021-08-011680055800봉수대길옹밀고가교옹밀고가교7832
189312021-08-011650015703논현고잔로--5217

Duplicate rows

Most frequently occurring

가공일시구간아이디구간명시점종점통행속도(킬로미터 퍼 아워)통행시간(초)# duplicates
2182021-08-011650057300남동로길병원사거리구월주공사거리30437
6782021-08-021650054500인주로독곡사거리장승백이사거리56276
10482021-08-031640012100경원로동춘역사거리105호고가교60186
4172021-08-021630001800인천대로인하대병원거리도화IC북측(법원고가교사거리)731925
5062021-08-021640012100경원로동춘역사거리105호고가교58195
5272021-08-021640014000앵고개길서울미치과동춘사거리44215
6602021-08-021650045100남동로남동로진입남동공단입구사거리73205
7062021-08-021650063900호구포길모래마을사거리평안장로교회42465
7372021-08-021660004800경원로십정사거리열우물사거리53325
8532021-08-021680010000원정로10번길취락진출입무명비신호3거리20185