Overview

Dataset statistics

Number of variables13
Number of observations200
Missing cells200
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.6 KiB
Average record size in memory110.7 B

Variable types

DateTime1
Numeric5
Categorical6
Unsupported1

Dataset

DescriptionSample
Author(재)인천테크노파크
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=ICTLINK5MMCMT0000001

Alerts

도로등급명 is highly overall correlated with 도로제한속도값 and 4 other fieldsHigh correlation
도로링크지역명 is highly overall correlated with 도로링크ID and 3 other fieldsHigh correlation
도로번호 is highly overall correlated with 도로링크통과제한차량명 and 3 other fieldsHigh correlation
도로링크통과제한차량명 is highly overall correlated with 차량평균속도값 and 3 other fieldsHigh correlation
도로명 is highly overall correlated with 도로링크ID and 8 other fieldsHigh correlation
도로링크ID is highly overall correlated with 도로링크지역명 and 1 other fieldsHigh correlation
도로제한속도값 is highly overall correlated with 평균교통량값 and 5 other fieldsHigh correlation
평균교통량값 is highly overall correlated with 도로제한속도값 and 1 other fieldsHigh correlation
차량평균속도값 is highly overall correlated with 도로링크통과제한차량명 and 1 other fieldsHigh correlation
평균도로점유율 is highly overall correlated with 도로제한속도값 and 2 other fieldsHigh correlation
도로유형명 is highly overall correlated with 도로제한속도값 and 2 other fieldsHigh correlation
도로등급명 is highly imbalanced (56.3%)Imbalance
도로번호 is highly imbalanced (51.0%)Imbalance
도로파티션구분자여부 has 200 (100.0%) missing valuesMissing
도로파티션구분자여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
도로제한속도값 has 91 (45.5%) zerosZeros
평균교통량값 has 115 (57.5%) zerosZeros
평균도로점유율 has 117 (58.5%) zerosZeros

Reproduction

Analysis started2023-12-10 06:14:30.658140
Analysis finished2023-12-10 06:14:35.945463
Duration5.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

생성일시
Date

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2019-12-22 15:05:00
Maximum2019-12-22 16:00:00
2023-12-10T15:14:36.011717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:36.175510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)

도로링크ID
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6484263 × 109
Minimum1.6100066 × 109
Maximum1.6800948 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:36.365396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.6100066 × 109
5-th percentile1.6101313 × 109
Q11.6400258 × 109
median1.640194 × 109
Q31.6800029 × 109
95-th percentile1.6800936 × 109
Maximum1.6800948 × 109
Range70088200
Interquartile range (IQR)39977125

Descriptive statistics

Standard deviation21940017
Coefficient of variation (CV)0.013309674
Kurtosis-0.66062167
Mean1.6484263 × 109
Median Absolute Deviation (MAD)9841850
Skewness0.081224327
Sum3.2968527 × 1011
Variance4.8136436 × 1014
MonotonicityNot monotonic
2023-12-10T15:14:36.564632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1640088800 2
 
1.0%
1640007800 2
 
1.0%
1680002900 2
 
1.0%
1650004700 2
 
1.0%
1640090700 2
 
1.0%
1610176400 2
 
1.0%
1680084600 2
 
1.0%
1650000900 2
 
1.0%
1650037100 2
 
1.0%
1640141100 2
 
1.0%
Other values (108) 180
90.0%
ValueCountFrequency (%)
1610006600 2
1.0%
1610050900 1
0.5%
1610051300 2
1.0%
1610111600 1
0.5%
1610111700 1
0.5%
1610112400 1
0.5%
1610116000 2
1.0%
1610132100 2
1.0%
1610133200 2
1.0%
1610135700 1
0.5%
ValueCountFrequency (%)
1680094800 2
1.0%
1680094700 2
1.0%
1680094600 2
1.0%
1680094200 2
1.0%
1680094000 2
1.0%
1680093600 1
0.5%
1680093500 2
1.0%
1680091200 1
0.5%
1680088200 2
1.0%
1680087400 2
1.0%

도로제한속도값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.15
Minimum0
Maximum90
Zeros91
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:36.737504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50
Q360
95-th percentile60
Maximum90
Range90
Interquartile range (IQR)60

Descriptive statistics

Standard deviation30.056521
Coefficient of variation (CV)0.93488402
Kurtosis-1.8631739
Mean32.15
Median Absolute Deviation (MAD)20
Skewness-0.067772124
Sum6430
Variance903.39447
MonotonicityNot monotonic
2023-12-10T15:14:36.893851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 91
45.5%
60 86
43.0%
70 7
 
3.5%
50 6
 
3.0%
40 6
 
3.0%
90 2
 
1.0%
30 2
 
1.0%
ValueCountFrequency (%)
0 91
45.5%
30 2
 
1.0%
40 6
 
3.0%
50 6
 
3.0%
60 86
43.0%
70 7
 
3.5%
90 2
 
1.0%
ValueCountFrequency (%)
90 2
 
1.0%
70 7
 
3.5%
60 86
43.0%
50 6
 
3.0%
40 6
 
3.0%
30 2
 
1.0%
0 91
45.5%

도로링크통과제한차량명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
모두통행가능
100 
<NA>
95 
이륜차
 
5

Length

Max length6
Median length5
Mean length4.975
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row모두통행가능
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row모두통행가능

Common Values

ValueCountFrequency (%)
모두통행가능 100
50.0%
<NA> 95
47.5%
이륜차 5
 
2.5%

Length

2023-12-10T15:14:37.101140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:37.265670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
모두통행가능 100
50.0%
na 95
47.5%
이륜차 5
 
2.5%

도로링크지역명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
송도
108 
청라
54 
<NA>
18 
영종
 
10
미단
 
10

Length

Max length4
Median length2
Mean length2.18
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
송도 108
54.0%
청라 54
27.0%
<NA> 18
 
9.0%
영종 10
 
5.0%
미단 10
 
5.0%

Length

2023-12-10T15:14:37.469636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:37.656193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송도 108
54.0%
청라 54
27.0%
na 18
 
9.0%
영종 10
 
5.0%
미단 10
 
5.0%

평균교통량값
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.69
Minimum0
Maximum63
Zeros115
Zeros (%)57.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:37.884577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile22.1
Maximum63
Range63
Interquartile range (IQR)4

Descriptive statistics

Standard deviation12.039879
Coefficient of variation (CV)2.5671384
Kurtosis16.116479
Mean4.69
Median Absolute Deviation (MAD)0
Skewness3.9841581
Sum938
Variance144.95869
MonotonicityNot monotonic
2023-12-10T15:14:38.065530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 115
57.5%
1 20
 
10.0%
8 10
 
5.0%
6 9
 
4.5%
4 9
 
4.5%
12 8
 
4.0%
63 5
 
2.5%
3 4
 
2.0%
2 4
 
2.0%
5 3
 
1.5%
Other values (10) 13
 
6.5%
ValueCountFrequency (%)
0 115
57.5%
1 20
 
10.0%
2 4
 
2.0%
3 4
 
2.0%
4 9
 
4.5%
5 3
 
1.5%
6 9
 
4.5%
7 2
 
1.0%
8 10
 
5.0%
9 1
 
0.5%
ValueCountFrequency (%)
63 5
2.5%
60 2
 
1.0%
31 1
 
0.5%
30 1
 
0.5%
24 1
 
0.5%
22 1
 
0.5%
16 1
 
0.5%
14 1
 
0.5%
12 8
4.0%
11 2
 
1.0%

차량평균속도값
Real number (ℝ)

HIGH CORRELATION 

Distinct50
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.215
Minimum12
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:38.273476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile22
Q139
median48
Q356
95-th percentile78.15
Maximum120
Range108
Interquartile range (IQR)17

Descriptive statistics

Standard deviation16.203132
Coefficient of variation (CV)0.32923157
Kurtosis2.8970364
Mean49.215
Median Absolute Deviation (MAD)9
Skewness0.96530292
Sum9843
Variance262.54148
MonotonicityNot monotonic
2023-12-10T15:14:38.492588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48 14
 
7.0%
60 14
 
7.0%
53 12
 
6.0%
31 11
 
5.5%
39 10
 
5.0%
55 10
 
5.0%
38 9
 
4.5%
40 9
 
4.5%
45 8
 
4.0%
56 7
 
3.5%
Other values (40) 96
48.0%
ValueCountFrequency (%)
12 1
 
0.5%
15 1
 
0.5%
18 4
 
2.0%
20 3
 
1.5%
22 2
 
1.0%
28 1
 
0.5%
29 1
 
0.5%
30 1
 
0.5%
31 11
5.5%
32 1
 
0.5%
ValueCountFrequency (%)
120 1
0.5%
111 1
0.5%
99 2
1.0%
90 1
0.5%
88 1
0.5%
86 1
0.5%
85 2
1.0%
81 1
0.5%
78 1
0.5%
74 2
1.0%

평균도로점유율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.805
Minimum0
Maximum5
Zeros117
Zeros (%)58.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:14:38.754166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile3
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.1104687
Coefficient of variation (CV)1.3794642
Kurtosis0.74348701
Mean0.805
Median Absolute Deviation (MAD)0
Skewness1.2159573
Sum161
Variance1.2331407
MonotonicityNot monotonic
2023-12-10T15:14:38.942725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 117
58.5%
2 40
 
20.0%
1 27
 
13.5%
3 11
 
5.5%
4 4
 
2.0%
5 1
 
0.5%
ValueCountFrequency (%)
0 117
58.5%
1 27
 
13.5%
2 40
 
20.0%
3 11
 
5.5%
4 4
 
2.0%
5 1
 
0.5%
ValueCountFrequency (%)
5 1
 
0.5%
4 4
 
2.0%
3 11
 
5.5%
2 40
 
20.0%
1 27
 
13.5%
0 117
58.5%

도로파티션구분자여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

도로명
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
경원로
23 
남동로
19 
일반국도77호선
14 
경명로
 
10
컨벤시아대로
 
10
Other values (30)
124 

Length

Max length15
Median length13
Mean length4.995
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row영종대로
2nd row인천타워대로
3rd row중봉대로 상1
4th row인천타워대로
5th row남동로

Common Values

ValueCountFrequency (%)
경원로 23
 
11.5%
남동로 19
 
9.5%
일반국도77호선 14
 
7.0%
경명로 10
 
5.0%
컨벤시아대로 10
 
5.0%
인천타워대로 9
 
4.5%
중봉대로 상1 8
 
4.0%
테크노파크로 8
 
4.0%
아트센터대로 8
 
4.0%
청릉로 7
 
3.5%
Other values (25) 84
42.0%

Length

2023-12-10T15:14:39.145517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경원로 23
 
10.8%
남동로 19
 
8.9%
일반국도77호선 14
 
6.6%
중봉대로 12
 
5.6%
경명로 10
 
4.7%
컨벤시아대로 10
 
4.7%
인천타워대로 9
 
4.2%
아트센터대로 8
 
3.8%
테크노파크로 8
 
3.8%
상1 8
 
3.8%
Other values (25) 92
43.2%

도로등급명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
특별/광역시도
159 
고속국도
 
15
일반국도
 
14
<NA>
 
8
지방도
 
2

Length

Max length7
Median length7
Mean length6.375
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row특별/광역시도
2nd row특별/광역시도
3rd row<NA>
4th row특별/광역시도
5th row특별/광역시도

Common Values

ValueCountFrequency (%)
특별/광역시도 159
79.5%
고속국도 15
 
7.5%
일반국도 14
 
7.0%
<NA> 8
 
4.0%
지방도 2
 
1.0%
시/군도 2
 
1.0%

Length

2023-12-10T15:14:39.348456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:39.533215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특별/광역시도 159
79.5%
고속국도 15
 
7.5%
일반국도 14
 
7.0%
na 8
 
4.0%
지방도 2
 
1.0%
시/군도 2
 
1.0%

도로유형명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
일반도로
132 
<NA>
62 
교량
 
4
고가차도
 
2

Length

Max length4
Median length4
Mean length3.96
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반도로
2nd row일반도로
3rd row<NA>
4th row일반도로
5th row일반도로

Common Values

ValueCountFrequency (%)
일반도로 132
66.0%
<NA> 62
31.0%
교량 4
 
2.0%
고가차도 2
 
1.0%

Length

2023-12-10T15:14:39.723951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:39.919661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반도로 132
66.0%
na 62
31.0%
교량 4
 
2.0%
고가차도 2
 
1.0%

도로번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
162 
-
35 
77
 
3

Length

Max length4
Median length4
Mean length3.445
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 162
81.0%
- 35
 
17.5%
77 3
 
1.5%

Length

2023-12-10T15:14:40.117929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:14:40.292110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 162
81.0%
35
 
17.5%
77 3
 
1.5%

Interactions

2023-12-10T15:14:34.867460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:31.692614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.619238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.264823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.970065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:35.014831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:31.880877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.756635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.425899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:34.105182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:35.136342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.055438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.865803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.559378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:34.215040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:35.258748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.285485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.011178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.710545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:34.623588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:35.389629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:32.441998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.127511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:33.835450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:14:34.736633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:14:40.438320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생성일시도로링크ID도로제한속도값도로링크통과제한차량명도로링크지역명평균교통량값차량평균속도값평균도로점유율도로명도로등급명도로유형명도로번호
생성일시1.0000.0000.0000.0000.0000.2830.0000.0000.0000.0000.0000.000
도로링크ID0.0001.0000.5340.2570.8140.1820.4280.4040.9730.6750.0880.159
도로제한속도값0.0000.5341.0000.0000.7710.2600.4740.5230.9960.6700.9370.021
도로링크통과제한차량명0.0000.2570.0001.0000.0000.0000.9670.0001.0001.0000.074NaN
도로링크지역명0.0000.8140.7710.0001.0000.0000.3530.4531.0000.3830.000NaN
평균교통량값0.2830.1820.2600.0000.0001.0000.0000.7800.7610.0000.0000.000
차량평균속도값0.0000.4280.4740.9670.3530.0001.0000.1750.9360.6780.3860.446
평균도로점유율0.0000.4040.5230.0000.4530.7800.1751.0000.8330.1800.0000.357
도로명0.0000.9730.9961.0001.0000.7610.9360.8331.0001.0000.8831.000
도로등급명0.0000.6750.6701.0000.3830.0000.6780.1801.0001.0000.7211.000
도로유형명0.0000.0880.9370.0740.0000.0000.3860.0000.8830.7211.0000.000
도로번호0.0000.1590.021NaNNaN0.0000.4460.3571.0001.0000.0001.000
2023-12-10T15:14:40.656812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로등급명도로유형명도로링크지역명도로번호도로링크통과제한차량명도로명
도로등급명1.0000.7060.1570.9860.9850.919
도로유형명0.7061.0000.0000.0000.1220.695
도로링크지역명0.1570.0001.0001.0000.0000.918
도로번호0.9860.0001.0001.0001.0000.866
도로링크통과제한차량명0.9850.1220.0001.0001.0000.924
도로명0.9190.6950.9180.8660.9241.000
2023-12-10T15:14:40.828436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로링크ID도로제한속도값평균교통량값차량평균속도값평균도로점유율도로링크통과제한차량명도로링크지역명도로명도로등급명도로유형명도로번호
도로링크ID1.0000.0770.031-0.075-0.0240.1680.7540.8010.3160.0820.256
도로제한속도값0.0771.0000.712-0.1070.6670.0000.6510.8400.5110.6890.000
평균교통량값0.0310.7121.000-0.0040.9290.0000.0000.4200.0000.0000.000
차량평균속도값-0.075-0.107-0.0041.000-0.0880.8220.2000.6340.3140.0890.342
평균도로점유율-0.0240.6670.929-0.0881.0000.0000.3050.5050.1210.0000.227
도로링크통과제한차량명0.1680.0000.0000.8220.0001.0000.0000.9240.9850.1221.000
도로링크지역명0.7540.6510.0000.2000.3050.0001.0000.9180.1570.0001.000
도로명0.8010.8400.4200.6340.5050.9240.9181.0000.9190.6950.866
도로등급명0.3160.5110.0000.3140.1210.9850.1570.9191.0000.7060.986
도로유형명0.0820.6890.0000.0890.0000.1220.0000.6950.7061.0000.000
도로번호0.2560.0000.0000.3420.2271.0001.0000.8660.9860.0001.000

Missing values

2023-12-10T15:14:35.579808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:14:35.839614image/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

생성일시도로링크ID도로제한속도값도로링크통과제한차량명도로링크지역명평균교통량값차량평균속도값평균도로점유율도로파티션구분자여부도로명도로등급명도로유형명도로번호
02019-12-22 15:05:00161011170060모두통행가능영종6421<NA>영종대로특별/광역시도일반도로-
12019-12-22 15:05:00164009070060<NA>송도12584<NA>인천타워대로특별/광역시도일반도로<NA>
22019-12-22 15:05:00168008450060<NA>청라7451<NA>중봉대로 상1<NA><NA><NA>
32019-12-22 15:05:00164010810060<NA>송도8512<NA>인천타워대로특별/광역시도일반도로<NA>
42019-12-22 15:05:0016500328000모두통행가능송도0530<NA>남동로특별/광역시도일반도로<NA>
52019-12-22 15:05:0016100513000이륜차송도0850<NA>제2경인고속도로 인천대교고속국도일반도로<NA>
62019-12-22 15:05:00168009420060<NA>청라8442<NA>청중로특별/광역시도<NA><NA>
72019-12-22 15:05:0016400338000모두통행가능송도0470<NA>경원로특별/광역시도일반도로<NA>
82019-12-22 15:05:00168008820060<NA>청라1372<NA>사파이어로특별/광역시도<NA><NA>
92019-12-22 15:05:00164012020060<NA>송도8662<NA>테크노파크로특별/광역시도일반도로<NA>
생성일시도로링크ID도로제한속도값도로링크통과제한차량명도로링크지역명평균교통량값차량평균속도값평균도로점유율도로파티션구분자여부도로명도로등급명도로유형명도로번호
1902019-12-22 16:00:0016400258000모두통행가능송도0490<NA>경원로특별/광역시도일반도로<NA>
1912019-12-22 16:00:00161011600070모두통행가능영종5901<NA>하늘대로특별/광역시도일반도로-
1922019-12-22 16:00:00168009460060<NA>청라6382<NA>청중로특별/광역시도<NA><NA>
1932019-12-22 16:00:00164024720060모두통행가능<NA>0310<NA>미추홀대로특별/광역시도일반도로-
1942019-12-22 16:00:0016500372000모두통행가능송도0400<NA>남동로특별/광역시도일반도로<NA>
1952019-12-22 16:00:00164012770060<NA>송도4692<NA>아트센터대로특별/광역시도일반도로<NA>
1962019-12-22 16:00:0016800030000<NA>청라0740<NA>경인고속도로고속국도<NA><NA>
1972019-12-22 16:00:00164024690040모두통행가능<NA>0310<NA>미추홀대로특별/광역시도일반도로-
1982019-12-22 16:00:00161013210030모두통행가능영종1431<NA>은하수로특별/광역시도일반도로-
1992019-12-22 16:00:0016400358000모두통행가능송도0470<NA>경원로특별/광역시도일반도로<NA>