Overview

Dataset statistics

Number of variables17
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.6 KiB
Average record size in memory149.3 B

Variable types

Numeric10
Categorical7

Alerts

도로종류 has constant value ""Constant
측정일 has constant value ""Constant
측정시간 has constant value ""Constant
지점 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
기본키 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
차선 is highly overall correlated with 평균 속도(km/hr)High correlation
장비이정(km) is highly overall correlated with 지점 and 2 other fieldsHigh correlation
차량통과수(대) is highly overall correlated with TSP(g/km) and 1 other fieldsHigh correlation
평균 속도(km/hr) is highly overall correlated with 차선High correlation
위도(°) is highly overall correlated with 지점 and 2 other fieldsHigh correlation
경도(°) is highly overall correlated with 지점 and 2 other fieldsHigh correlation
기울기(°) is highly overall correlated with 지점 and 2 other fieldsHigh correlation
TSP(g/km) is highly overall correlated with 차량통과수(대) and 1 other fieldsHigh correlation
PM10(g/km) is highly overall correlated with 차량통과수(대) and 1 other fieldsHigh correlation
방향 is highly overall correlated with 측정구간High correlation
측정구간 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
기본키 has unique valuesUnique
차량통과수(대) has 21 (21.0%) zerosZeros
평균 속도(km/hr) has 21 (21.0%) zerosZeros
TSP(g/km) has 21 (21.0%) zerosZeros
PM10(g/km) has 21 (21.0%) zerosZeros

Reproduction

Analysis started2023-12-10 11:13:20.367785
Analysis finished2023-12-10 11:13:35.467629
Duration15.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:35.585925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T20:13:35.834120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

도로종류
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
도로공사
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도로공사 100
100.0%

Length

2023-12-10T20:13:36.042191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:13:36.191458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로공사 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-0500-0763E-8
12 
A-0400-0568S-6
 
6
A-0400-1082S-4
 
4
A-0500-0844S-8
 
4
A-0400-0834S-4
 
4
Other values (18)
70 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0400-0708S-4
2nd rowA-0400-0708S-4
3rd rowA-0400-0708S-4
4th rowA-0400-0708S-4
5th rowA-0400-1082S-4

Common Values

ValueCountFrequency (%)
A-0500-0763E-8 12
 
12.0%
A-0400-0568S-6 6
 
6.0%
A-0400-1082S-4 4
 
4.0%
A-0500-0844S-8 4
 
4.0%
A-0400-0834S-4 4
 
4.0%
A-0450-2107S-4 4
 
4.0%
A-0400-0862S-4 4
 
4.0%
A-0400-1025S-4 4
 
4.0%
A-0352-2643E-4 4
 
4.0%
A-0450-2601E-4 4
 
4.0%
Other values (13) 50
50.0%

Length

2023-12-10T20:13:36.339908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a-0500-0763e-8 12
 
12.0%
a-0400-0568s-6 6
 
6.0%
a-0300-0040s-4 4
 
4.0%
a-0400-0708s-4 4
 
4.0%
a-0300-0245s-4 4
 
4.0%
a-0550-3119s-4 4
 
4.0%
a-0550-2644e-4 4
 
4.0%
a-0450-2483e-4 4
 
4.0%
a-0450-1719e-4 4
 
4.0%
a-0450-1398e-4 4
 
4.0%
Other values (13) 50
50.0%

방향
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
S
50 
E
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS
2nd rowS
3rd rowE
4th rowE
5th rowS

Common Values

ValueCountFrequency (%)
S 50
50.0%
E 50
50.0%

Length

2023-12-10T20:13:36.490221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:13:36.613888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 50
50.0%
e 50
50.0%

차선
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.86
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:36.719427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2228465
Coefficient of variation (CV)0.65744435
Kurtosis9.505553
Mean1.86
Median Absolute Deviation (MAD)1
Skewness2.7419668
Sum186
Variance1.4953535
MonotonicityNot monotonic
2023-12-10T20:13:36.883722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 44
44.0%
2 44
44.0%
3 4
 
4.0%
4 4
 
4.0%
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%
8 1
 
1.0%
ValueCountFrequency (%)
1 44
44.0%
2 44
44.0%
3 4
 
4.0%
4 4
 
4.0%
5 1
 
1.0%
6 1
 
1.0%
7 1
 
1.0%
8 1
 
1.0%
ValueCountFrequency (%)
8 1
 
1.0%
7 1
 
1.0%
6 1
 
1.0%
5 1
 
1.0%
4 4
 
4.0%
3 4
 
4.0%
2 44
44.0%
1 44
44.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
호법JC-이천IC
북진천IC-대소JC
 
4
여주JC-이천IC
 
4
이천IC-호법JC
 
4
금왕꽃동네IC-대소JC
 
2
Other values (39)
78 

Length

Max length13
Median length9
Mean length9.8
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음성IC-금왕꽃동네IC
2nd row음성IC-금왕꽃동네IC
3rd row금왕꽃동네IC-음성IC
4th row금왕꽃동네IC-음성IC
5th row제천JC-동충주IC

Common Values

ValueCountFrequency (%)
호법JC-이천IC 8
 
8.0%
북진천IC-대소JC 4
 
4.0%
여주JC-이천IC 4
 
4.0%
이천IC-호법JC 4
 
4.0%
금왕꽃동네IC-대소JC 2
 
2.0%
제천JC-동충주IC 2
 
2.0%
동충주IC-제천JC 2
 
2.0%
충주JC-서충주IC 2
 
2.0%
서충주IC-충주JC 2
 
2.0%
충주IC-괴산IC 2
 
2.0%
Other values (34) 68
68.0%

Length

2023-12-10T20:13:37.102175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
호법jc-이천ic 8
 
8.0%
이천ic-호법jc 4
 
4.0%
북진천ic-대소jc 4
 
4.0%
여주jc-이천ic 4
 
4.0%
신림ic-남원주ic 2
 
2.0%
보은ic-회인ic 2
 
2.0%
낙동jc-상주ic 2
 
2.0%
회인ic-보은ic 2
 
2.0%
화서ic-구병산hi 2
 
2.0%
낙동jc-남상주ic 2
 
2.0%
Other values (34) 68
68.0%

장비이정(km)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140.5704
Minimum4
Maximum320.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:37.274046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile24.5
Q176.3
median86.28
Q3248.33
95-th percentile311.9
Maximum320.5
Range316.5
Interquartile range (IQR)172.03

Descriptive statistics

Standard deviation96.832161
Coefficient of variation (CV)0.68885171
Kurtosis-1.1434071
Mean140.5704
Median Absolute Deviation (MAD)35.63
Skewness0.59205781
Sum14057.04
Variance9376.4673
MonotonicityNot monotonic
2023-12-10T20:13:37.464298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
76.3 16
 
16.0%
56.8 6
 
6.0%
70.8 4
 
4.0%
24.5 4
 
4.0%
84.43 4
 
4.0%
311.9 4
 
4.0%
264.4 4
 
4.0%
248.33 4
 
4.0%
171.91 4
 
4.0%
139.85 4
 
4.0%
Other values (12) 46
46.0%
ValueCountFrequency (%)
4.0 4
 
4.0%
24.5 4
 
4.0%
44.5 2
 
2.0%
56.8 6
 
6.0%
60.2 4
 
4.0%
70.8 4
 
4.0%
76.3 16
16.0%
83.4 4
 
4.0%
84.43 4
 
4.0%
86.28 4
 
4.0%
ValueCountFrequency (%)
320.5 4
4.0%
311.9 4
4.0%
285.2 4
4.0%
264.4 4
4.0%
264.3 4
4.0%
260.1 4
4.0%
248.33 4
4.0%
210.73 4
4.0%
171.91 4
4.0%
139.85 4
4.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20200801
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200801
2nd row20200801
3rd row20200801
4th row20200801
5th row20200801

Common Values

ValueCountFrequency (%)
20200801 100
100.0%

Length

2023-12-10T20:13:37.674019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:13:37.870841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200801 100
100.0%

측정시간
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 100
100.0%

Length

2023-12-10T20:13:38.109560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:13:38.346525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

차량통과수(대)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)62.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.85
Minimum0
Maximum313
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:38.628135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114.5
median44
Q383.25
95-th percentile181.65
Maximum313
Range313
Interquartile range (IQR)68.75

Descriptive statistics

Standard deviation60.46426
Coefficient of variation (CV)1.0274301
Kurtosis3.8352763
Mean58.85
Median Absolute Deviation (MAD)37.5
Skewness1.6988757
Sum5885
Variance3655.9268
MonotonicityNot monotonic
2023-12-10T20:13:38.886223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21
 
21.0%
72 3
 
3.0%
39 3
 
3.0%
20 2
 
2.0%
86 2
 
2.0%
101 2
 
2.0%
34 2
 
2.0%
124 2
 
2.0%
112 2
 
2.0%
80 2
 
2.0%
Other values (52) 59
59.0%
ValueCountFrequency (%)
0 21
21.0%
3 1
 
1.0%
4 1
 
1.0%
5 1
 
1.0%
13 1
 
1.0%
15 1
 
1.0%
17 1
 
1.0%
18 1
 
1.0%
20 2
 
2.0%
21 1
 
1.0%
ValueCountFrequency (%)
313 1
1.0%
277 1
1.0%
213 1
1.0%
201 1
1.0%
194 1
1.0%
181 1
1.0%
166 1
1.0%
153 1
1.0%
134 1
1.0%
125 1
1.0%

평균 속도(km/hr)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct71
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.0428
Minimum0
Maximum134
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:39.163144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q178.74
median89.125
Q3101.525
95-th percentile120.1115
Maximum134
Range134
Interquartile range (IQR)22.785

Descriptive statistics

Standard deviation41.285658
Coefficient of variation (CV)0.54292659
Kurtosis-0.23436611
Mean76.0428
Median Absolute Deviation (MAD)11.225
Skewness-1.0990087
Sum7604.28
Variance1704.5056
MonotonicityNot monotonic
2023-12-10T20:13:39.477206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
21.0%
86.5 3
 
3.0%
128.0 2
 
2.0%
91.5 2
 
2.0%
100.5 2
 
2.0%
106.0 2
 
2.0%
111.0 2
 
2.0%
116.0 2
 
2.0%
94.8 2
 
2.0%
83.62 1
 
1.0%
Other values (61) 61
61.0%
ValueCountFrequency (%)
0.0 21
21.0%
76.25 1
 
1.0%
78.17 1
 
1.0%
78.5 1
 
1.0%
78.71 1
 
1.0%
78.75 1
 
1.0%
80.57 1
 
1.0%
80.74 1
 
1.0%
81.25 1
 
1.0%
81.62 1
 
1.0%
ValueCountFrequency (%)
134.0 1
1.0%
129.0 1
1.0%
128.0 2
2.0%
122.23 1
1.0%
120.0 1
1.0%
117.5 1
1.0%
116.5 1
1.0%
116.0 2
2.0%
114.0 1
1.0%
111.5 1
1.0%

위도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.933785
Minimum36.368358
Maximum37.410278
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:39.743724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.368358
5-th percentile36.374167
Q136.741389
median37.003333
Q337.112222
95-th percentile37.234167
Maximum37.410278
Range1.0419195
Interquartile range (IQR)0.37083333

Descriptive statistics

Standard deviation0.28347815
Coefficient of variation (CV)0.0076753072
Kurtosis-0.47929357
Mean36.933785
Median Absolute Deviation (MAD)0.15111111
Skewness-0.67249399
Sum3693.3785
Variance0.080359862
MonotonicityNot monotonic
2023-12-10T20:13:39.987495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
37.23416667 12
 
12.0%
36.86916667 6
 
6.0%
36.9425 6
 
6.0%
37.11222222 6
 
6.0%
36.98055556 4
 
4.0%
36.46971667 4
 
4.0%
37.41027778 4
 
4.0%
37.03138889 4
 
4.0%
36.62861111 4
 
4.0%
36.37416667 4
 
4.0%
Other values (12) 46
46.0%
ValueCountFrequency (%)
36.36835833 4
4.0%
36.37416667 4
4.0%
36.444525 2
 
2.0%
36.46971667 4
4.0%
36.548875 4
4.0%
36.62861111 4
4.0%
36.74138889 4
4.0%
36.86916667 6
6.0%
36.9425 6
6.0%
36.94388889 4
4.0%
ValueCountFrequency (%)
37.41027778 4
 
4.0%
37.23416667 12
12.0%
37.1885605 4
 
4.0%
37.17138889 4
 
4.0%
37.11222222 6
6.0%
37.07186389 4
 
4.0%
37.065 4
 
4.0%
37.03944444 4
 
4.0%
37.03138889 4
 
4.0%
37.02611111 4
 
4.0%

경도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73052
Minimum127.44083
Maximum128.2625
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:40.207329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.44083
5-th percentile127.44806
Q1127.46389
median127.68551
Q3127.91361
95-th percentile128.23944
Maximum128.2625
Range0.8216667
Interquartile range (IQR)0.4497222

Descriptive statistics

Standard deviation0.27376387
Coefficient of variation (CV)0.0021432926
Kurtosis-0.90927999
Mean127.73052
Median Absolute Deviation (MAD)0.22402775
Skewness0.6139353
Sum12773.052
Variance0.074946658
MonotonicityNot monotonic
2023-12-10T20:13:40.450721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
127.4480556 12
 
12.0%
127.9094444 6
 
6.0%
127.4613889 6
 
6.0%
127.7019444 6
 
6.0%
127.6047222 4
 
4.0%
127.6690722 4
 
4.0%
127.9258333 4
 
4.0%
128.2625 4
 
4.0%
128.1472222 4
 
4.0%
128.2394444 4
 
4.0%
Other values (12) 46
46.0%
ValueCountFrequency (%)
127.4408333 4
 
4.0%
127.4480556 12
12.0%
127.4613889 6
6.0%
127.4638889 4
 
4.0%
127.4675 4
 
4.0%
127.4731028 4
 
4.0%
127.4988889 4
 
4.0%
127.6047222 4
 
4.0%
127.6126927 4
 
4.0%
127.6690722 4
 
4.0%
ValueCountFrequency (%)
128.2625 4
4.0%
128.2394444 4
4.0%
128.2008222 4
4.0%
128.1472222 4
4.0%
127.9739528 4
4.0%
127.9258333 4
4.0%
127.9136111 4
4.0%
127.9094444 6
6.0%
127.8848333 2
 
2.0%
127.7497222 4
4.0%

기울기(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.30097746
Minimum-6.688
Maximum4.25421
Zeros0
Zeros (%)0.0%
Negative58
Negative (%)58.0%
Memory size1.0 KiB
2023-12-10T20:13:40.671339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6.688
5-th percentile-2.72685
Q1-0.785921
median-0.4315305
Q30.5068
95-th percentile1.99427
Maximum4.25421
Range10.94221
Interquartile range (IQR)1.292721

Descriptive statistics

Standard deviation1.8811455
Coefficient of variation (CV)-6.2501208
Kurtosis4.3993061
Mean-0.30097746
Median Absolute Deviation (MAD)0.742774
Skewness-0.97674872
Sum-30.097746
Variance3.5387083
MonotonicityNot monotonic
2023-12-10T20:13:40.877834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
-0.785921 12
 
12.0%
-0.7189909999999999 6
 
6.0%
1.99427 4
 
4.0%
4.25421 4
 
4.0%
-0.489801 4
 
4.0%
0.21004 4
 
4.0%
-0.37326 4
 
4.0%
-0.14187 4
 
4.0%
-6.688 4
 
4.0%
-1.203288 4
 
4.0%
Other values (13) 50
50.0%
ValueCountFrequency (%)
-6.688 4
 
4.0%
-2.72685 4
 
4.0%
-1.391058 4
 
4.0%
-1.344974 4
 
4.0%
-1.203288 4
 
4.0%
-1.13121 4
 
4.0%
-0.785921 12
12.0%
-0.7189909999999999 6
6.0%
-0.522334 4
 
4.0%
-0.489801 4
 
4.0%
ValueCountFrequency (%)
4.25421 4
4.0%
1.99427 4
4.0%
1.73409 4
4.0%
1.10171 4
4.0%
1.04309 2
2.0%
0.647992 4
4.0%
0.5068 4
4.0%
0.484469 4
4.0%
0.28226 4
4.0%
0.21004 4
4.0%

TSP(g/km)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1218
Minimum0
Maximum21.8
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:41.126369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1975
median1.935
Q34.775
95-th percentile10.3355
Maximum21.8
Range21.8
Interquartile range (IQR)4.5775

Descriptive statistics

Standard deviation3.9302282
Coefficient of variation (CV)1.2589622
Kurtosis5.5389008
Mean3.1218
Median Absolute Deviation (MAD)1.935
Skewness2.078842
Sum312.18
Variance15.446694
MonotonicityNot monotonic
2023-12-10T20:13:41.395972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
21.0%
0.44 2
 
2.0%
1.48 2
 
2.0%
0.39 1
 
1.0%
5.0 1
 
1.0%
3.07 1
 
1.0%
5.09 1
 
1.0%
6.77 1
 
1.0%
3.44 1
 
1.0%
7.46 1
 
1.0%
Other values (68) 68
68.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.03 1
 
1.0%
0.04 1
 
1.0%
0.17 1
 
1.0%
0.19 1
 
1.0%
0.2 1
 
1.0%
0.28 1
 
1.0%
0.3 1
 
1.0%
0.33 1
 
1.0%
0.34 1
 
1.0%
ValueCountFrequency (%)
21.8 1
1.0%
15.79 1
1.0%
14.54 1
1.0%
13.52 1
1.0%
10.63 1
1.0%
10.32 1
1.0%
9.15 1
1.0%
9.11 1
1.0%
8.86 1
1.0%
8.47 1
1.0%

PM10(g/km)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)74.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3735
Minimum0
Maximum9.59
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:13:42.053201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0875
median0.85
Q32.1
95-th percentile4.547
Maximum9.59
Range9.59
Interquartile range (IQR)2.0125

Descriptive statistics

Standard deviation1.7297173
Coefficient of variation (CV)1.2593501
Kurtosis5.5306363
Mean1.3735
Median Absolute Deviation (MAD)0.85
Skewness2.0777765
Sum137.35
Variance2.991922
MonotonicityNot monotonic
2023-12-10T20:13:42.354329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
 
21.0%
2.57 2
 
2.0%
0.23 2
 
2.0%
0.89 2
 
2.0%
0.19 2
 
2.0%
0.65 2
 
2.0%
2.38 2
 
2.0%
3.28 1
 
1.0%
2.24 1
 
1.0%
2.98 1
 
1.0%
Other values (64) 64
64.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.01 1
 
1.0%
0.02 1
 
1.0%
0.07 1
 
1.0%
0.08 1
 
1.0%
0.09 1
 
1.0%
0.12 1
 
1.0%
0.13 1
 
1.0%
0.14 1
 
1.0%
0.15 1
 
1.0%
ValueCountFrequency (%)
9.59 1
1.0%
6.95 1
1.0%
6.4 1
1.0%
5.95 1
1.0%
4.68 1
1.0%
4.54 1
1.0%
4.02 1
1.0%
4.01 1
1.0%
3.9 1
1.0%
3.73 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
경기 이천시 호법면
12 
충북 진천군 이월면 미잠리
 
6
충북 충주시 산척면 영덕리
 
4
경기 여주시 가남읍 정단리
 
4
충북 충주시 신니면 화석리
 
4
Other values (18)
70 

Length

Max length14
Median length14
Mean length12.6
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충북 음성군 금왕읍 금석리
2nd row충북 음성군 금왕읍 금석리
3rd row충북 음성군 금왕읍 금석리
4th row충북 음성군 금왕읍 금석리
5th row충북 충주시 산척면 영덕리

Common Values

ValueCountFrequency (%)
경기 이천시 호법면 12
 
12.0%
충북 진천군 이월면 미잠리 6
 
6.0%
충북 충주시 산척면 영덕리 4
 
4.0%
경기 여주시 가남읍 정단리 4
 
4.0%
충북 충주시 신니면 화석리 4
 
4.0%
충북 괴산군 장연면 상리 4
 
4.0%
충북 충주시 노은면 문성리 4
 
4.0%
충북 충주시 엄정면 율릉리 4
 
4.0%
충북 청원군 오창읍 학소리 4
 
4.0%
경기 여주시 가남읍 4
 
4.0%
Other values (13) 50
50.0%

Length

2023-12-10T20:13:42.645531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 58
 
15.8%
경기 24
 
6.6%
충주시 16
 
4.4%
음성군 16
 
4.4%
경북 14
 
3.8%
호법면 12
 
3.3%
이천시 12
 
3.3%
상주시 10
 
2.7%
청원군 8
 
2.2%
낙동면 8
 
2.2%
Other values (43) 188
51.4%

Interactions

2023-12-10T20:13:33.424484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.259775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.250158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.365526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.780205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.021339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.134357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.424021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.688139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:31.536433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:33.584143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.346078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.369434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.469487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.907375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.146773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.228018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.545430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.819324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:31.730276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:33.749335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.445311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.484192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.591630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.022493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.259029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.339729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.669159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.027223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:31.885271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:33.894502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.537211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.597059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.963924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.138649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.355442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.460185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.794011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.168209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:32.033866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.039638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.627740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.703256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.073944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.268871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.463759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.566414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.911875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.299828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:32.182547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.197905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.746691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.808068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.188972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.402312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.550487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.704473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.062620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.464580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:32.353356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.353905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.839174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.921925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.320658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.544658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.649487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.830973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.198494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.679073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:32.851357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.497797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:21.938376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.029384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.446999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.658675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.751848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:27.944837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.322983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:30.932851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:32.990211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.635525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.035137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.138422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.556290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.776354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.869167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.060633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.447956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:31.107399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:33.139984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:34.769826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:22.150175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:23.242586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:24.670537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:25.898555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:26.989909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:28.177817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:29.559682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:31.323885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:13:33.275189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:13:42.829901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향차선측정구간장비이정(km)차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)주소
기본키1.0000.9810.0000.1030.9950.9140.4650.5260.9360.7470.7540.2780.2780.981
지점0.9811.0000.0000.0001.0001.0000.6510.7140.9970.9981.0000.4220.4221.000
방향0.0000.0001.0000.0001.0000.0000.0930.0000.0000.0000.0000.0000.0000.000
차선0.1030.0000.0001.0000.0000.0000.0000.3980.0000.0000.0000.0000.0000.000
측정구간0.9951.0001.0000.0001.0001.0000.8050.6451.0001.0001.0000.5850.5851.000
장비이정(km)0.9141.0000.0000.0001.0001.0000.6030.4960.9610.8270.8730.3770.3771.000
차량통과수(대)0.4650.6510.0930.0000.8050.6031.0000.5560.5900.3890.5130.6890.6890.651
평균 속도(km/hr)0.5260.7140.0000.3980.6450.4960.5561.0000.5810.2990.3630.4750.4750.714
위도(°)0.9360.9970.0000.0001.0000.9610.5900.5811.0000.8470.8550.5430.5430.997
경도(°)0.7470.9980.0000.0001.0000.8270.3890.2990.8471.0000.8440.0000.0000.998
기울기(°)0.7541.0000.0000.0001.0000.8730.5130.3630.8550.8441.0000.1930.1931.000
TSP(g/km)0.2780.4220.0000.0000.5850.3770.6890.4750.5430.0000.1931.0001.0000.422
PM10(g/km)0.2780.4220.0000.0000.5850.3770.6890.4750.5430.0000.1931.0001.0000.422
주소0.9811.0000.0000.0001.0001.0000.6510.7140.9970.9981.0000.4220.4221.000
2023-12-10T20:13:43.097758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점주소방향측정구간
지점1.0001.0000.0000.853
주소1.0001.0000.0000.853
방향0.0000.0001.0000.756
측정구간0.8530.8530.7561.000
2023-12-10T20:13:43.284719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키차선장비이정(km)차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)지점방향측정구간주소
기본키1.0000.2620.114-0.046-0.3400.293-0.020-0.270-0.077-0.0770.8220.0000.7490.822
차선0.2621.000-0.149-0.250-0.5900.257-0.219-0.1240.0500.0500.0000.0000.0000.000
장비이정(km)0.114-0.1491.0000.4020.1800.2430.1990.1060.3130.3130.9250.0000.7890.925
차량통과수(대)-0.046-0.2500.4021.0000.332-0.3760.2590.0670.8490.8490.2880.0850.3420.288
평균 속도(km/hr)-0.340-0.5900.1800.3321.000-0.2120.2130.3100.1610.1610.3790.0000.2560.379
위도(°)0.2930.2570.243-0.376-0.2121.000-0.339-0.096-0.391-0.3910.9090.0000.7890.909
경도(°)-0.020-0.2190.1990.2590.213-0.3391.0000.0790.2080.2080.9040.0000.7800.904
기울기(°)-0.270-0.1240.1060.0670.310-0.0960.0791.0000.0770.0770.9100.0000.7760.910
TSP(g/km)-0.0770.0500.3130.8490.161-0.3910.2080.0771.0001.0000.1610.0000.1940.161
PM10(g/km)-0.0770.0500.3130.8490.161-0.3910.2080.0771.0001.0000.1610.0000.1940.161
지점0.8220.0000.9250.2880.3790.9090.9040.9100.1610.1611.0000.0000.8531.000
방향0.0000.0000.0000.0850.0000.0000.0000.0000.0000.0000.0001.0000.7560.000
측정구간0.7490.0000.7890.3420.2560.7890.7800.7760.1940.1940.8530.7561.0000.853
주소0.8220.0000.9250.2880.3790.9090.9040.9100.1610.1611.0000.0000.8531.000

Missing values

2023-12-10T20:13:34.987766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:13:35.334483image/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

기본키도로종류지점방향차선측정구간장비이정(km)측정일측정시간차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)주소
01도로공사A-0400-0708S-4S1음성IC-금왕꽃동네IC70.820200801020134.036.980556127.6047221.994270.390.17충북 음성군 금왕읍 금석리
12도로공사A-0400-0708S-4S2음성IC-금왕꽃동네IC70.82020080103492.7536.980556127.6047221.994271.180.52충북 음성군 금왕읍 금석리
23도로공사A-0400-0708S-4E1금왕꽃동네IC-음성IC70.820200801029120.036.980556127.6047221.994270.330.14충북 음성군 금왕읍 금석리
34도로공사A-0400-0708S-4E2금왕꽃동네IC-음성IC70.82020080104689.536.980556127.6047221.994272.331.02충북 음성군 금왕읍 금석리
45도로공사A-0400-1082S-4S1제천JC-동충주IC108.242020080103110.037.071864127.9739534.254210.030.01충북 충주시 산척면 영덕리
56도로공사A-0400-1082S-4S2제천JC-동충주IC108.2420200801013100.037.071864127.9739534.254211.960.86충북 충주시 산척면 영덕리
67도로공사A-0400-1082S-4E1동충주IC-제천JC108.2420200801039111.037.071864127.9739534.254210.440.19충북 충주시 산척면 영덕리
78도로공사A-0400-1082S-4E2동충주IC-제천JC108.242020080104193.2537.071864127.9739534.254211.740.76충북 충주시 산척면 영덕리
89도로공사A-0400-0834S-4S1충주JC-서충주IC83.420200801000.037.026111127.723333-1.131210.00.0충북 충주시 신니면 화석리
910도로공사A-0400-0834S-4S2충주JC-서충주IC83.420200801000.037.026111127.723333-1.131210.00.0충북 충주시 신니면 화석리
기본키도로종류지점방향차선측정구간장비이정(km)측정일측정시간차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)주소
9091도로공사A-0500-0763E-8E3호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9192도로공사A-0500-0763E-8E4호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9293도로공사A-0500-0763E-8E5호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9394도로공사A-0500-0763E-8E6호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9495도로공사A-0500-0763E-8E7호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9596도로공사A-0500-0763E-8E8호법JC-이천IC76.320200801000.037.234167127.448056-0.7859210.00.0경기 이천시 호법면
9697도로공사A-0500-0844S-8S1여주JC-이천IC84.4320200801000.037.410278127.925833-0.4898010.00.0경기 여주시 가남읍 정단리
9798도로공사A-0500-0844S-8S2여주JC-이천IC84.4320200801011694.837.410278127.925833-0.4898012.51.1경기 여주시 가남읍 정단리
9899도로공사A-0500-0844S-8S3여주JC-이천IC84.432020080107978.7137.410278127.925833-0.4898015.22.29경기 여주시 가남읍 정단리
99100도로공사A-0500-0844S-8S4여주JC-이천IC84.432020080102180.5737.410278127.925833-0.4898012.841.25경기 여주시 가남읍 정단리