Overview

Dataset statistics

Number of variables13
Number of observations90
Missing cells175
Missing cells (%)15.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory112.5 B

Variable types

DateTime1
Numeric3
Unsupported1
Categorical7
Text1

Dataset

DescriptionSample
Author(재)인천테크노파크
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ICTREPTCNGSHI0000001

Alerts

첨두시종료시간 is highly overall correlated with 첨두시그룹번호 and 1 other fieldsHigh correlation
도로등급명 is highly overall correlated with 도로구간ID and 5 other fieldsHigh correlation
첨두시시작시간 is highly overall correlated with 첨두시그룹번호 and 1 other fieldsHigh correlation
도로시작지점명 is highly overall correlated with 도로구간ID and 4 other fieldsHigh correlation
첨두시그룹번호 is highly overall correlated with 첨두시시작시간 and 1 other fieldsHigh correlation
도로구간지역명 is highly overall correlated with 도로구간ID and 4 other fieldsHigh correlation
도로종료지점명 is highly overall correlated with 도로구간ID and 4 other fieldsHigh correlation
도로구간ID is highly overall correlated with 차량평균속도값 and 5 other fieldsHigh correlation
차량평균속도값 is highly overall correlated with 도로구간ID and 5 other fieldsHigh correlation
도로정체율 is highly overall correlated with 도로구간ID and 2 other fieldsHigh correlation
도로구간유형명 has 90 (100.0%) missing valuesMissing
도로전광표지판표출명 has 85 (94.4%) missing valuesMissing
도로구간유형명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 06:39:06.761456
Analysis finished2023-12-10 06:39:10.312468
Duration3.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

생성일시
Date

Distinct8
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2019-12-09 15:00:00
Maximum2019-12-23 15:00:00
2023-12-10T15:39:10.390846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:10.586026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

도로구간ID
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2683548 × 109
Minimum1.6310006 × 109
Maximum9.6800726 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T15:39:10.799242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6310006 × 109
5-th percentile1.6310012 × 109
Q11.6310026 × 109
median1.651001 × 109
Q39.6800725 × 109
95-th percentile9.6800725 × 109
Maximum9.6800726 × 109
Range8.049072 × 109
Interquartile range (IQR)8.0490699 × 109

Descriptive statistics

Standard deviation3.9965406 × 109
Coefficient of variation (CV)0.75859367
Kurtosis-2.00403
Mean5.2683548 × 109
Median Absolute Deviation (MAD)19999800
Skewness0.18675976
Sum4.7415193 × 1011
Variance1.5972337 × 1019
MonotonicityNot monotonic
2023-12-10T15:39:11.026256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1631002600 24
26.7%
9680072528 23
25.6%
9680072529 12
13.3%
1631001200 6
 
6.7%
1641000403 5
 
5.6%
1641000402 4
 
4.4%
1651000500 3
 
3.3%
1651004800 3
 
3.3%
1651001000 2
 
2.2%
8710086500 2
 
2.2%
Other values (5) 6
 
6.7%
ValueCountFrequency (%)
1631000600 1
 
1.1%
1631001200 6
 
6.7%
1631002600 24
26.7%
1641000200 1
 
1.1%
1641000402 4
 
4.4%
1641000403 5
 
5.6%
1651000500 3
 
3.3%
1651001000 2
 
2.2%
1651004800 3
 
3.3%
8710045603 1
 
1.1%
ValueCountFrequency (%)
9680072591 1
 
1.1%
9680072529 12
13.3%
9680072528 23
25.6%
9680004500 2
 
2.2%
8710086500 2
 
2.2%
8710045603 1
 
1.1%
1651004800 3
 
3.3%
1651001000 2
 
2.2%
1651000500 3
 
3.3%
1641000403 5
 
5.6%

도로구간유형명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing90
Missing (%)100.0%
Memory size942.0 B

도로등급명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
일반국도
45 
특별/광역시도
39 
고속국도
6 

Length

Max length7
Median length4
Mean length5.3
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반국도 45
50.0%
특별/광역시도 39
43.3%
고속국도 6
 
6.7%

Length

2023-12-10T15:39:11.314590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:11.537938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반국도 45
50.0%
특별/광역시도 39
43.3%
고속국도 6
 
6.7%

도로구간지역명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
송도
49 
영종
35 
청라
5 
미단
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
송도 49
54.4%
영종 35
38.9%
청라 5
 
5.6%
미단 1
 
1.1%

Length

2023-12-10T15:39:11.762332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:11.971878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송도 49
54.4%
영종 35
38.9%
청라 5
 
5.6%
미단 1
 
1.1%

첨두시그룹번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
3
37 
1
30 
2
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row1
4th row2
5th row3

Common Values

ValueCountFrequency (%)
3 37
41.1%
1 30
33.3%
2 23
25.6%

Length

2023-12-10T15:39:12.174324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:12.341761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 37
41.1%
1 30
33.3%
2 23
25.6%

첨두시시작시간
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
18
37 
7
30 
12
23 

Length

Max length2
Median length2
Mean length1.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row18
3rd row7
4th row12
5th row18

Common Values

ValueCountFrequency (%)
18 37
41.1%
7 30
33.3%
12 23
25.6%

Length

2023-12-10T15:39:12.548138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:12.747273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
18 37
41.1%
7 30
33.3%
12 23
25.6%

첨두시종료시간
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size852.0 B
20
37 
9
30 
14
23 

Length

Max length2
Median length2
Mean length1.6666667
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row20
3rd row9
4th row14
5th row20

Common Values

ValueCountFrequency (%)
20 37
41.1%
9 30
33.3%
14 23
25.6%

Length

2023-12-10T15:39:12.959136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:39:13.152000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20 37
41.1%
9 30
33.3%
14 23
25.6%

차량평균속도값
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.577778
Minimum4
Maximum38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T15:39:13.327168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q17
median26.5
Q336
95-th percentile37.55
Maximum38
Range34
Interquartile range (IQR)29

Descriptive statistics

Standard deviation13.894448
Coefficient of variation (CV)0.64392395
Kurtosis-1.8816781
Mean21.577778
Median Absolute Deviation (MAD)10.5
Skewness-0.099599691
Sum1942
Variance193.05568
MonotonicityNot monotonic
2023-12-10T15:39:13.515773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
36 15
16.7%
5 10
11.1%
7 9
10.0%
6 9
10.0%
35 7
 
7.8%
8 5
 
5.6%
37 5
 
5.6%
38 5
 
5.6%
32 4
 
4.4%
33 3
 
3.3%
Other values (10) 18
20.0%
ValueCountFrequency (%)
4 2
 
2.2%
5 10
11.1%
6 9
10.0%
7 9
10.0%
8 5
5.6%
9 2
 
2.2%
10 2
 
2.2%
16 1
 
1.1%
19 2
 
2.2%
21 1
 
1.1%
ValueCountFrequency (%)
38 5
 
5.6%
37 5
 
5.6%
36 15
16.7%
35 7
7.8%
33 3
 
3.3%
32 4
 
4.4%
31 1
 
1.1%
30 3
 
3.3%
29 2
 
2.2%
24 2
 
2.2%

도로정체율
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.555556
Minimum50
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-10T15:39:13.718448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile50
Q163
median79
Q3100
95-th percentile100
Maximum100
Range50
Interquartile range (IQR)37

Descriptive statistics

Standard deviation18.854923
Coefficient of variation (CV)0.24002023
Kurtosis-1.5200138
Mean78.555556
Median Absolute Deviation (MAD)21
Skewness-0.1279393
Sum7070
Variance355.50811
MonotonicityNot monotonic
2023-12-10T15:39:13.913079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
100 30
33.3%
50 9
 
10.0%
63 8
 
8.9%
79 7
 
7.8%
71 7
 
7.8%
54 7
 
7.8%
75 6
 
6.7%
58 5
 
5.6%
96 3
 
3.3%
83 2
 
2.2%
Other values (3) 6
 
6.7%
ValueCountFrequency (%)
50 9
10.0%
54 7
7.8%
58 5
5.6%
63 8
8.9%
67 2
 
2.2%
71 7
7.8%
75 6
6.7%
79 7
7.8%
83 2
 
2.2%
88 2
 
2.2%
ValueCountFrequency (%)
100 30
33.3%
96 3
 
3.3%
92 2
 
2.2%
88 2
 
2.2%
83 2
 
2.2%
79 7
 
7.8%
75 6
 
6.7%
71 7
 
7.8%
67 2
 
2.2%
63 8
 
8.9%

도로시작지점명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size852.0 B
인하대병원거리
24 
하늘대로종점
23 
하늘대로11
12 
제2경인고속도로시점
7 
송도3교교차로
5 
Other values (8)
19 

Length

Max length11
Median length10
Mean length6.6888889
Min length2

Unique

Unique3 ?
Unique (%)3.3%

Sample

1st row송도3교교차로
2nd row송도3교교차로
3rd row제2경인고속도로시점
4th row제2경인고속도로시점
5th row제2경인고속도로시점

Common Values

ValueCountFrequency (%)
인하대병원거리 24
26.7%
하늘대로종점 23
25.6%
하늘대로11 12
13.3%
제2경인고속도로시점 7
 
7.8%
송도3교교차로 5
 
5.6%
외암삼삼거리 5
 
5.6%
없음 4
 
4.4%
문학IC동측(본선) 3
 
3.3%
담지로종점 2
 
2.2%
서인천IC남측(본선) 2
 
2.2%
Other values (3) 3
 
3.3%

Length

2023-12-10T15:39:14.121984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인하대병원거리 24
26.7%
하늘대로종점 23
25.6%
하늘대로11 12
13.3%
제2경인고속도로시점 7
 
7.8%
송도3교교차로 5
 
5.6%
외암삼삼거리 5
 
5.6%
없음 4
 
4.4%
문학ic동측(본선 3
 
3.3%
담지로종점 2
 
2.2%
서인천ic남측(본선 2
 
2.2%
Other values (3) 3
 
3.3%

도로종료지점명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size852.0 B
제2경인고속도로시점
24 
하늘대로11
23 
하늘대로종점
12 
인하대병원거리
6 
옹암사거리
5 
Other values (9)
20 

Length

Max length11
Median length10
Mean length7.3
Min length2

Unique

Unique3 ?
Unique (%)3.3%

Sample

1st row옹암사거리
2nd row옹암사거리
3rd row인하대병원거리
4th row인하대병원거리
5th row인하대병원거리

Common Values

ValueCountFrequency (%)
제2경인고속도로시점 24
26.7%
하늘대로11 23
25.6%
하늘대로종점 12
13.3%
인하대병원거리 6
 
6.7%
옹암사거리 5
 
5.6%
없음 4
 
4.4%
송도3교교차로 4
 
4.4%
남동IC서측(본선) 3
 
3.3%
외암도사거리 2
 
2.2%
중흥S클래스13블록 2
 
2.2%
Other values (4) 5
 
5.6%

Length

2023-12-10T15:39:14.332125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2경인고속도로시점 24
26.7%
하늘대로11 23
25.6%
하늘대로종점 12
13.3%
인하대병원거리 6
 
6.7%
옹암사거리 5
 
5.6%
없음 4
 
4.4%
송도3교교차로 4
 
4.4%
남동ic서측(본선 3
 
3.3%
외암도사거리 2
 
2.2%
중흥s클래스13블록 2
 
2.2%
Other values (4) 5
 
5.6%

도로전광표지판표출명
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing85
Missing (%)94.4%
Memory size852.0 B
2023-12-10T15:39:14.553509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.6
Min length6

Characters and Unicode

Total characters33
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row중봉대로 하2
2nd row국제대로 하1
3rd row국제대로 하1
4th row경인고속도로
5th row경인고속도로
ValueCountFrequency (%)
국제대로 2
25.0%
하1 2
25.0%
경인고속도로 2
25.0%
중봉대로 1
12.5%
하2 1
12.5%
2023-12-10T15:39:15.014688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 5
15.2%
대 3
9.1%
3
9.1%
하 3
9.1%
국 2
 
6.1%
제 2
 
6.1%
1 2
 
6.1%
경 2
 
6.1%
인 2
 
6.1%
고 2
 
6.1%
Other values (5) 7
21.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27
81.8%
Space Separator 3
 
9.1%
Decimal Number 3
 
9.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 5
18.5%
대 3
11.1%
하 3
11.1%
국 2
 
7.4%
제 2
 
7.4%
경 2
 
7.4%
인 2
 
7.4%
고 2
 
7.4%
속 2
 
7.4%
도 2
 
7.4%
Other values (2) 2
 
7.4%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27
81.8%
Common 6
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 5
18.5%
대 3
11.1%
하 3
11.1%
국 2
 
7.4%
제 2
 
7.4%
경 2
 
7.4%
인 2
 
7.4%
고 2
 
7.4%
속 2
 
7.4%
도 2
 
7.4%
Other values (2) 2
 
7.4%
Common
ValueCountFrequency (%)
3
50.0%
1 2
33.3%
2 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27
81.8%
ASCII 6
 
18.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 5
18.5%
대 3
11.1%
하 3
11.1%
국 2
 
7.4%
제 2
 
7.4%
경 2
 
7.4%
인 2
 
7.4%
고 2
 
7.4%
속 2
 
7.4%
도 2
 
7.4%
Other values (2) 2
 
7.4%
ASCII
ValueCountFrequency (%)
3
50.0%
1 2
33.3%
2 1
 
16.7%

Interactions

2023-12-10T15:39:08.905210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:07.949715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:08.438493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:09.074935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:08.145250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:08.621672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:09.220087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:08.294660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:39:08.761885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:39:15.195772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생성일시도로구간ID도로등급명도로구간지역명첨두시그룹번호첨두시시작시간첨두시종료시간차량평균속도값도로정체율도로시작지점명도로종료지점명도로전광표지판표출명
생성일시1.0000.4420.3240.3360.0000.0000.0000.2220.0000.2550.4040.751
도로구간ID0.4421.0000.9310.8160.0000.0000.0000.7600.6591.0001.0001.000
도로등급명0.3240.9311.0000.6890.4730.4730.4731.0000.7140.9661.0001.000
도로구간지역명0.3360.8160.6891.0000.0920.0920.0920.9010.6051.0001.000NaN
첨두시그룹번호0.0000.0000.4730.0921.0001.0001.0000.2410.4620.0000.0000.000
첨두시시작시간0.0000.0000.4730.0921.0001.0001.0000.2410.4620.0000.0000.000
첨두시종료시간0.0000.0000.4730.0921.0001.0001.0000.2410.4620.0000.0000.000
차량평균속도값0.2220.7601.0000.9010.2410.2410.2411.0000.7190.8620.8981.000
도로정체율0.0000.6590.7140.6050.4620.4620.4620.7191.0000.7610.8010.598
도로시작지점명0.2551.0000.9661.0000.0000.0000.0000.8620.7611.0000.9931.000
도로종료지점명0.4041.0001.0001.0000.0000.0000.0000.8980.8010.9931.0001.000
도로전광표지판표출명0.7511.0001.000NaN0.0000.0000.0001.0000.5981.0001.0001.000
2023-12-10T15:39:15.450862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
첨두시종료시간도로등급명첨두시시작시간도로시작지점명첨두시그룹번호도로구간지역명도로종료지점명
첨두시종료시간1.0000.1861.0000.0001.0000.0840.000
도로등급명0.1861.0000.1860.8960.1860.7180.935
첨두시시작시간1.0000.1861.0000.0001.0000.0840.000
도로시작지점명0.0000.8960.0001.0000.0000.9460.949
첨두시그룹번호1.0000.1861.0000.0001.0000.0840.000
도로구간지역명0.0840.7180.0840.9460.0841.0000.940
도로종료지점명0.0000.9350.0000.9490.0000.9401.000
2023-12-10T15:39:15.659361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로구간ID차량평균속도값도로정체율도로등급명도로구간지역명첨두시그룹번호첨두시시작시간첨두시종료시간도로시작지점명도로종료지점명
도로구간ID1.000-0.798-0.6410.6770.8760.0000.0000.0000.9410.935
차량평균속도값-0.7981.0000.5580.9710.5530.1500.1500.1500.5720.609
도로정체율-0.6410.5581.0000.5510.3930.2990.2990.2990.4360.472
도로등급명0.6770.9710.5511.0000.7180.1860.1860.1860.8960.935
도로구간지역명0.8760.5530.3930.7181.0000.0840.0840.0840.9460.940
첨두시그룹번호0.0000.1500.2990.1860.0841.0001.0001.0000.0000.000
첨두시시작시간0.0000.1500.2990.1860.0841.0001.0001.0000.0000.000
첨두시종료시간0.0000.1500.2990.1860.0841.0001.0001.0000.0000.000
도로시작지점명0.9410.5720.4360.8960.9460.0000.0000.0001.0000.949
도로종료지점명0.9350.6090.4720.9350.9400.0000.0000.0000.9491.000

Missing values

2023-12-10T15:39:09.442481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:39:09.766536image/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

생성일시도로구간ID도로구간유형명도로등급명도로구간지역명첨두시그룹번호첨두시시작시간첨두시종료시간차량평균속도값도로정체율도로시작지점명도로종료지점명도로전광표지판표출명
02019-12-23 15:00:001641000403<NA>일반국도송도1793679송도3교교차로옹암사거리<NA>
12019-12-23 15:00:001641000403<NA>일반국도송도318203871송도3교교차로옹암사거리<NA>
22019-12-23 15:00:001631001200<NA>일반국도송도17936100제2경인고속도로시점인하대병원거리<NA>
32019-12-23 15:00:001631001200<NA>일반국도송도2121435100제2경인고속도로시점인하대병원거리<NA>
42019-12-23 15:00:001631001200<NA>일반국도송도3182038100제2경인고속도로시점인하대병원거리<NA>
52019-12-23 15:00:001631002600<NA>일반국도송도17933100인하대병원거리제2경인고속도로시점<NA>
62019-12-23 15:00:001631002600<NA>일반국도송도2121433100인하대병원거리제2경인고속도로시점<NA>
72019-12-23 15:00:001631002600<NA>일반국도송도3182032100인하대병원거리제2경인고속도로시점<NA>
82019-12-23 15:00:001641000200<NA>일반국도송도1793575외암도사거리없음<NA>
92019-12-23 15:00:001651000500<NA>일반국도송도1793375외암삼삼거리없음<NA>
생성일시도로구간ID도로구간유형명도로등급명도로구간지역명첨두시그룹번호첨두시시작시간첨두시종료시간차량평균속도값도로정체율도로시작지점명도로종료지점명도로전광표지판표출명
802019-12-13 15:00:009680072529<NA>특별/광역시도영종179758하늘대로11하늘대로종점<NA>
812019-12-11 15:00:009680004500<NA>고속국도청라318202158서인천IC남측(본선)서인천IC동측(본선)경인고속도로
822019-12-11 15:00:001631002600<NA>일반국도송도17936100인하대병원거리제2경인고속도로시점<NA>
832019-12-11 15:00:001631002600<NA>일반국도송도2121435100인하대병원거리제2경인고속도로시점<NA>
842019-12-11 15:00:001631002600<NA>일반국도송도3182036100인하대병원거리제2경인고속도로시점<NA>
852019-12-11 15:00:009680072528<NA>특별/광역시도영종179563하늘대로종점하늘대로11<NA>
862019-12-11 15:00:009680072528<NA>특별/광역시도영종21214554하늘대로종점하늘대로11<NA>
872019-12-11 15:00:009680072528<NA>특별/광역시도영종31820975하늘대로종점하늘대로11<NA>
882019-12-11 15:00:009680072529<NA>특별/광역시도영종21214671하늘대로11하늘대로종점<NA>
892019-12-11 15:00:009680072529<NA>특별/광역시도영종31820554하늘대로11하늘대로종점<NA>