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

Numeric9
Categorical8

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
측정구간 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
기본키 is highly overall correlated with 장비이정(km) and 5 other fieldsHigh correlation
장비이정(km) is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
차량통과수(대) is highly overall correlated with 평균 속도(km/hr) and 2 other fieldsHigh correlation
평균 속도(km/hr) is highly overall correlated with 차량통과수(대) and 2 other fieldsHigh correlation
위도(°) is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
경도(°) is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
기울기(°) is highly overall correlated with 지점 and 3 other fieldsHigh correlation
TSP(g/km) is highly overall correlated with 차량통과수(대) and 2 other fieldsHigh correlation
PM10(g/km) is highly overall correlated with 차량통과수(대) and 2 other fieldsHigh correlation
방향 is highly overall correlated with 기울기(°) and 1 other fieldsHigh correlation
기본키 has unique valuesUnique
차량통과수(대) has 30 (30.0%) zerosZeros
평균 속도(km/hr) has 30 (30.0%) zerosZeros
TSP(g/km) has 30 (30.0%) zerosZeros
PM10(g/km) has 32 (32.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:57:51.173716
Analysis finished2023-12-10 10:58:09.046034
Duration17.87 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
2023-12-10T19:58:09.201605image/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
2023-12-10T19:58:09.470728image/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

2023-12-10T19:58:09.814379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:58:10.071764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로공사 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A-0010-3452S-10
10 
A-0010-3613E-10
10 
A-0010-3801E-10
10 
A-0010-3932E-10
10 
A-0010-4105E-10
10 
Other values (9)
50 

Length

Max length15
Median length14.5
Mean length14.5
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA-0010-0538E-6
2nd rowA-0010-0538E-6
3rd rowA-0010-0538E-6
4th rowA-0010-0538E-6
5th rowA-0010-0538E-6

Common Values

ValueCountFrequency (%)
A-0010-3452S-10 10
10.0%
A-0010-3613E-10 10
10.0%
A-0010-3801E-10 10
10.0%
A-0010-3932E-10 10
10.0%
A-0010-4105E-10 10
10.0%
A-0010-2583E-7 7
 
7.0%
A-0010-0538E-6 6
 
6.0%
A-0010-2761E-6 6
 
6.0%
A-0010-3019E-6 6
 
6.0%
A-0010-3068E-6 6
 
6.0%
Other values (4) 19
19.0%

Length

2023-12-10T19:58:10.252387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a-0010-3452s-10 10
10.0%
a-0010-3613e-10 10
10.0%
a-0010-3801e-10 10
10.0%
a-0010-3932e-10 10
10.0%
a-0010-4105e-10 10
10.0%
a-0010-2583e-7 7
 
7.0%
a-0010-0538e-6 6
 
6.0%
a-0010-2761e-6 6
 
6.0%
a-0010-3019e-6 6
 
6.0%
a-0010-3068e-6 6
 
6.0%
Other values (4) 19
19.0%

방향
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
E
52 
S
48 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
E 52
52.0%
S 48
48.0%

Length

2023-12-10T19:58:10.464350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:58:10.679372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
e 52
52.0%
s 48
48.0%

차선
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
25 
2
25 
3
25 
4
14 
5
11 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 25
25.0%
2 25
25.0%
3 25
25.0%
4 14
14.0%
5 11
11.0%

Length

2023-12-10T19:58:10.963969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:58:11.173970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 25
25.0%
2 25
25.0%
3 25
25.0%
4 14
14.0%
5 11
11.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
안성JC-안성IC
 
5
양재IC-금토JC
 
5
금토JC-양재IC
 
5
청주JC-남이JC
 
5
신갈JC-수원신갈IC
 
5
Other values (20)
75 

Length

Max length11
Median length9
Mean length9.38
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row언양JC-활천IC
2nd row언양JC-활천IC
3rd row언양JC-활천IC
4th row활천IC-언양JC
5th row활천IC-언양JC

Common Values

ValueCountFrequency (%)
안성JC-안성IC 5
 
5.0%
양재IC-금토JC 5
 
5.0%
금토JC-양재IC 5
 
5.0%
청주JC-남이JC 5
 
5.0%
신갈JC-수원신갈IC 5
 
5.0%
수원신갈IC-신갈JC 5
 
5.0%
동탄JC-오산IC 5
 
5.0%
오산IC-동탄JC 5
 
5.0%
천안IC-북천안IC 5
 
5.0%
북천안IC-천안IC 5
 
5.0%
Other values (15) 50
50.0%

Length

2023-12-10T19:58:11.854346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
안성jc-안성ic 5
 
5.0%
양재ic-금토jc 5
 
5.0%
금토jc-양재ic 5
 
5.0%
청주jc-남이jc 5
 
5.0%
신갈jc-수원신갈ic 5
 
5.0%
수원신갈ic-신갈jc 5
 
5.0%
동탄jc-오산ic 5
 
5.0%
오산ic-동탄jc 5
 
5.0%
천안ic-북천안ic 5
 
5.0%
북천안ic-천안ic 5
 
5.0%
Other values (15) 50
50.0%

장비이정(km)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.681
Minimum53.4
Maximum410.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:12.065216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum53.4
5-th percentile53.4
Q1290.5
median326
Q3380.1
95-th percentile410.41
Maximum410.41
Range357.01
Interquartile range (IQR)89.6

Descriptive statistics

Standard deviation83.425408
Coefficient of variation (CV)0.26260748
Kurtosis3.7069037
Mean317.681
Median Absolute Deviation (MAD)49.9
Skewness-1.7407177
Sum31768.1
Variance6959.7986
MonotonicityNot monotonic
2023-12-10T19:58:12.308986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
345.2 10
10.0%
361.3 10
10.0%
380.1 10
10.0%
393.2 10
10.0%
410.41 10
10.0%
258.3 7
 
7.0%
53.4 6
 
6.0%
276.1 6
 
6.0%
301.9 6
 
6.0%
306.8 6
 
6.0%
Other values (4) 19
19.0%
ValueCountFrequency (%)
53.4 6
6.0%
258.3 7
7.0%
262.6 6
6.0%
276.1 6
6.0%
295.3 4
 
4.0%
295.6 4
 
4.0%
297.9 5
5.0%
301.9 6
6.0%
306.8 6
6.0%
345.2 10
10.0%
ValueCountFrequency (%)
410.41 10
10.0%
393.2 10
10.0%
380.1 10
10.0%
361.3 10
10.0%
345.2 10
10.0%
306.8 6
6.0%
301.9 6
6.0%
297.9 5
5.0%
295.6 4
 
4.0%
295.3 4
 
4.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20221201
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20221201
2nd row20221201
3rd row20221201
4th row20221201
5th row20221201

Common Values

ValueCountFrequency (%)
20221201 100
100.0%

Length

2023-12-10T19:58:12.556644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:58:12.752135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20221201 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

2023-12-10T19:58:12.923675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:58:13.107071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

차량통과수(대)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.5
Minimum0
Maximum196
Zeros30
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:13.303097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median26
Q372.25
95-th percentile152.05
Maximum196
Range196
Interquartile range (IQR)72.25

Descriptive statistics

Standard deviation51.934788
Coefficient of variation (CV)1.1414239
Kurtosis0.19751451
Mean45.5
Median Absolute Deviation (MAD)26
Skewness1.1081829
Sum4550
Variance2697.2222
MonotonicityNot monotonic
2023-12-10T19:58:13.644776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30
30.0%
18 3
 
3.0%
26 3
 
3.0%
35 2
 
2.0%
73 2
 
2.0%
65 2
 
2.0%
25 2
 
2.0%
22 2
 
2.0%
37 2
 
2.0%
39 2
 
2.0%
Other values (47) 50
50.0%
ValueCountFrequency (%)
0 30
30.0%
1 2
 
2.0%
3 1
 
1.0%
7 2
 
2.0%
8 2
 
2.0%
9 1
 
1.0%
11 1
 
1.0%
16 1
 
1.0%
18 3
 
3.0%
22 2
 
2.0%
ValueCountFrequency (%)
196 1
1.0%
176 1
1.0%
172 1
1.0%
162 1
1.0%
153 1
1.0%
152 1
1.0%
146 1
1.0%
144 1
1.0%
134 1
1.0%
130 1
1.0%

평균 속도(km/hr)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.7111
Minimum0
Maximum119.5
Zeros30
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:13.938931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median79.665
Q391.1275
95-th percentile110.0335
Maximum119.5
Range119.5
Interquartile range (IQR)91.1275

Descriptive statistics

Standard deviation42.084959
Coefficient of variation (CV)0.68196741
Kurtosis-1.2755346
Mean61.7111
Median Absolute Deviation (MAD)15.335
Skewness-0.65622868
Sum6171.11
Variance1771.1438
MonotonicityNot monotonic
2023-12-10T19:58:14.282798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 30
30.0%
75.0 3
 
3.0%
95.0 2
 
2.0%
79.0 2
 
2.0%
92.5 2
 
2.0%
81.0 2
 
2.0%
93.0 2
 
2.0%
90.67 1
 
1.0%
90.6 1
 
1.0%
94.25 1
 
1.0%
Other values (54) 54
54.0%
ValueCountFrequency (%)
0.0 30
30.0%
52.0 1
 
1.0%
64.14 1
 
1.0%
68.0 1
 
1.0%
72.29 1
 
1.0%
73.5 1
 
1.0%
75.0 3
 
3.0%
75.25 1
 
1.0%
75.62 1
 
1.0%
76.5 1
 
1.0%
ValueCountFrequency (%)
119.5 1
1.0%
113.5 1
1.0%
113.0 1
1.0%
111.0 1
1.0%
110.67 1
1.0%
110.0 1
1.0%
109.5 1
1.0%
107.5 1
1.0%
107.33 1
1.0%
107.0 1
1.0%

위도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.76714
Minimum35.681944
Maximum37.42325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:14.561311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.681944
5-th percentile35.681944
Q136.502403
median36.75455
Q337.158778
95-th percentile37.42325
Maximum37.42325
Range1.7413056
Interquartile range (IQR)0.65637528

Descriptive statistics

Standard deviation0.45510551
Coefficient of variation (CV)0.01237805
Kurtosis-0.13755208
Mean36.76714
Median Absolute Deviation (MAD)0.36494
Skewness-0.48110413
Sum3676.714
Variance0.20712102
MonotonicityNot monotonic
2023-12-10T19:58:14.821210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
36.86890278 10
10.0%
37.00888889 10
10.0%
37.15877778 10
10.0%
37.27944444 10
10.0%
37.42325 10
10.0%
36.30722222 7
 
7.0%
35.68194444 6
 
6.0%
36.38961 6
 
6.0%
36.60611111 6
 
6.0%
36.64019722 6
 
6.0%
Other values (4) 19
19.0%
ValueCountFrequency (%)
35.68194444 6
6.0%
36.30722222 7
7.0%
36.33222222 6
6.0%
36.38961 6
6.0%
36.54 4
 
4.0%
36.55638889 4
 
4.0%
36.57694444 5
5.0%
36.60611111 6
6.0%
36.64019722 6
6.0%
36.86890278 10
10.0%
ValueCountFrequency (%)
37.42325 10
10.0%
37.27944444 10
10.0%
37.15877778 10
10.0%
37.00888889 10
10.0%
36.86890278 10
10.0%
36.64019722 6
6.0%
36.60611111 6
6.0%
36.57694444 5
5.0%
36.55638889 4
 
4.0%
36.54 4
 
4.0%

경도(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.3925
Minimum127.07728
Maximum129.18111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:15.060840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.07728
5-th percentile127.07728
Q1127.10583
median127.28243
Q3127.4325
95-th percentile129.18111
Maximum129.18111
Range2.1038333
Interquartile range (IQR)0.3266667

Descriptive statistics

Standard deviation0.4854558
Coefficient of variation (CV)0.0038107093
Kurtosis8.8336749
Mean127.3925
Median Absolute Deviation (MAD)0.1514639
Skewness3.002833
Sum12739.25
Variance0.23566734
MonotonicityNot monotonic
2023-12-10T19:58:15.306574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
127.1867222 10
10.0%
127.1491667 10
10.0%
127.0883333 10
10.0%
127.1058333 10
10.0%
127.0772778 10
10.0%
127.5744444 7
 
7.0%
129.1811111 6
 
6.0%
127.423508 6
 
6.0%
127.4083333 6
 
6.0%
127.3781278 6
 
6.0%
Other values (4) 19
19.0%
ValueCountFrequency (%)
127.0772778 10
10.0%
127.0883333 10
10.0%
127.1058333 10
10.0%
127.1491667 10
10.0%
127.1867222 10
10.0%
127.3781278 6
6.0%
127.4083333 6
6.0%
127.423508 6
6.0%
127.4277778 5
5.0%
127.4325 4
 
4.0%
ValueCountFrequency (%)
129.1811111 6
6.0%
127.5744444 7
7.0%
127.5341667 6
6.0%
127.4338889 4
 
4.0%
127.4325 4
 
4.0%
127.4277778 5
5.0%
127.423508 6
6.0%
127.4083333 6
6.0%
127.3781278 6
6.0%
127.1867222 10
10.0%

기울기(°)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.06120791
Minimum-2.788625
Maximum2.703849
Zeros0
Zeros (%)0.0%
Negative49
Negative (%)49.0%
Memory size1.0 KiB
2023-12-10T19:58:15.653879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.788625
5-th percentile-1.758683
Q1-0.73138
median0.151187
Q30.688696
95-th percentile1.717451
Maximum2.703849
Range5.492474
Interquartile range (IQR)1.420076

Descriptive statistics

Standard deviation1.1367817
Coefficient of variation (CV)-18.572463
Kurtosis0.076483695
Mean-0.06120791
Median Absolute Deviation (MAD)0.811191
Skewness-0.050420664
Sum-6.120791
Variance1.2922726
MonotonicityNot monotonic
2023-12-10T19:58:15.993603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
-0.624001 5
 
5.0%
-1.30142 5
 
5.0%
-0.73138 5
 
5.0%
-1.758683 5
 
5.0%
0.69298 5
 
5.0%
-0.139436 5
 
5.0%
0.151187 5
 
5.0%
0.671977 5
 
5.0%
-0.660004 5
 
5.0%
0.61369 5
 
5.0%
Other values (15) 50
50.0%
ValueCountFrequency (%)
-2.788625 3
3.0%
-1.758683 5
5.0%
-1.717451 3
3.0%
-1.30142 5
5.0%
-1.22799 3
3.0%
-0.807188 4
4.0%
-0.73138 5
5.0%
-0.688696 3
3.0%
-0.660004 5
5.0%
-0.624001 5
5.0%
ValueCountFrequency (%)
2.703849 3
3.0%
1.717451 3
3.0%
1.293015 5
5.0%
1.22799 3
3.0%
1.056036 4
4.0%
0.69298 5
5.0%
0.688696 3
3.0%
0.671977 5
5.0%
0.61369 5
5.0%
0.2594 4
4.0%

TSP(g/km)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.87
Minimum0
Maximum16.34
Zeros30
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:16.324295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.34
Q34.8375
95-th percentile9.647
Maximum16.34
Range16.34
Interquartile range (IQR)4.8375

Descriptive statistics

Standard deviation3.5653413
Coefficient of variation (CV)1.2422792
Kurtosis1.3196103
Mean2.87
Median Absolute Deviation (MAD)1.34
Skewness1.3227082
Sum287
Variance12.711659
MonotonicityNot monotonic
2023-12-10T19:58:16.651722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 30
30.0%
2.32 3
 
3.0%
0.08 2
 
2.0%
0.01 2
 
2.0%
5.11 1
 
1.0%
11.58 1
 
1.0%
1.39 1
 
1.0%
8.72 1
 
1.0%
1.76 1
 
1.0%
2.2 1
 
1.0%
Other values (57) 57
57.0%
ValueCountFrequency (%)
0.0 30
30.0%
0.01 2
 
2.0%
0.04 1
 
1.0%
0.07 1
 
1.0%
0.08 2
 
2.0%
0.1 1
 
1.0%
0.21 1
 
1.0%
0.22 1
 
1.0%
0.25 1
 
1.0%
0.29 1
 
1.0%
ValueCountFrequency (%)
16.34 1
1.0%
11.7 1
1.0%
11.58 1
1.0%
11.39 1
1.0%
10.16 1
1.0%
9.62 1
1.0%
8.72 1
1.0%
8.67 1
1.0%
8.51 1
1.0%
8.22 1
1.0%

PM10(g/km)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2623
Minimum0
Maximum7.19
Zeros32
Zeros (%)32.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:58:17.016966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.59
Q32.125
95-th percentile4.242
Maximum7.19
Range7.19
Interquartile range (IQR)2.125

Descriptive statistics

Standard deviation1.5687748
Coefficient of variation (CV)1.2427907
Kurtosis1.3197102
Mean1.2623
Median Absolute Deviation (MAD)0.59
Skewness1.3227437
Sum126.23
Variance2.4610543
MonotonicityNot monotonic
2023-12-10T19:58:17.293442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 32
32.0%
0.03 3
 
3.0%
1.02 3
 
3.0%
1.85 2
 
2.0%
1.78 2
 
2.0%
0.57 1
 
1.0%
0.36 1
 
1.0%
1.33 1
 
1.0%
3.74 1
 
1.0%
7.19 1
 
1.0%
Other values (53) 53
53.0%
ValueCountFrequency (%)
0.0 32
32.0%
0.02 1
 
1.0%
0.03 3
 
3.0%
0.04 1
 
1.0%
0.09 1
 
1.0%
0.1 1
 
1.0%
0.11 1
 
1.0%
0.13 1
 
1.0%
0.2 1
 
1.0%
0.21 1
 
1.0%
ValueCountFrequency (%)
7.19 1
1.0%
5.15 1
1.0%
5.09 1
1.0%
5.01 1
1.0%
4.47 1
1.0%
4.23 1
1.0%
3.84 1
1.0%
3.82 1
1.0%
3.74 1
1.0%
3.61 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 청원군 남이면
13 
충남 천안시 서북구 성거읍 송남리
10 
경기 안성시 원곡면
10 
경기 화성시 동탄면 송리
10 
경기 용인시 기흥구 신갈동
10 
Other values (7)
47 

Length

Max length18
Median length15
Mean length12.96
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산 울주군 두서면 활천리
2nd row울산 울주군 두서면 활천리
3rd row울산 울주군 두서면 활천리
4th row울산 울주군 두서면 활천리
5th row울산 울주군 두서면 활천리

Common Values

ValueCountFrequency (%)
충북 청원군 남이면 13
13.0%
충남 천안시 서북구 성거읍 송남리 10
10.0%
경기 안성시 원곡면 10
10.0%
경기 화성시 동탄면 송리 10
10.0%
경기 용인시 기흥구 신갈동 10
10.0%
경기 성남시 수정구 금토동 10
10.0%
충북 옥천군 옥천읍 삼양리 7
7.0%
울산 울주군 두서면 활천리 6
6.0%
대전 대덕구 연축동 6
6.0%
충북 청주시 흥덕구 강서1동 6
6.0%
Other values (2) 12
12.0%

Length

2023-12-10T19:58:17.570631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 40
 
10.7%
충북 38
 
10.1%
청원군 19
 
5.1%
남이면 13
 
3.5%
옥천군 13
 
3.5%
동탄면 10
 
2.7%
금토동 10
 
2.7%
성남시 10
 
2.7%
신갈동 10
 
2.7%
기흥구 10
 
2.7%
Other values (26) 202
53.9%

Interactions

2023-12-10T19:58:06.569551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:52.587796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:54.167922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:55.902722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:57.815725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:59.483517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.652680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.260982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:04.796848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:06.736487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:52.736192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:54.334074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:56.079088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:57.999930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:59.682615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.812449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.407470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.015918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:06.927884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:52.962394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:54.569625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:56.316994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:58.192943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:59.890623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.991019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.572745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.208796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:07.125381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.155713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:54.804713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:56.588044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:58.381512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:00.087903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:02.168301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.750387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.409983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:07.437409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.320940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:54.973539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:56.769729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:58.599253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:00.266180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:02.353541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.925440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.586213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:07.632086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.489399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:55.163647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:56.963784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:58.784037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:00.822842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:02.516562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:04.090750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.778199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:07.777699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.641035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:55.316206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:57.171276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:58.948176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.112131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:02.682941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:04.257918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:05.958802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:08.020599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.810675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:55.486175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:57.390168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:59.109924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.278825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:02.873312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:04.407125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:06.158261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:08.215112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:53.993335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:55.723738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:57.593774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:57:59.296772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:01.458005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:03.096680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:04.599035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:58:06.340317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:58:17.808436image/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
기본키1.0000.9360.0000.0000.9860.8850.6270.3420.8880.8850.8950.0000.0000.930
지점0.9361.0000.0080.0001.0001.0000.3340.4821.0001.0000.9050.2060.2061.000
방향0.0000.0081.0000.0001.0000.0000.0000.0000.0000.0000.6850.0000.0000.000
차선0.0000.0000.0001.0000.0000.0000.0000.4510.0000.0890.0000.4910.4910.000
측정구간0.9861.0001.0000.0001.0001.0000.2110.4131.0001.0001.0000.0000.0001.000
장비이정(km)0.8851.0000.0000.0001.0001.0000.4010.1930.9601.0000.7160.1570.1571.000
차량통과수(대)0.6270.3340.0000.0000.2110.4011.0000.5340.3380.3610.0000.6300.6300.292
평균 속도(km/hr)0.3420.4820.0000.4510.4130.1930.5341.0000.2410.0000.0000.4980.4980.217
위도(°)0.8881.0000.0000.0001.0000.9600.3380.2411.0001.0000.7940.1790.1790.999
경도(°)0.8851.0000.0000.0891.0001.0000.3610.0001.0001.0000.7330.0000.0001.000
기울기(°)0.8950.9050.6850.0001.0000.7160.0000.0000.7940.7331.0000.0000.0000.873
TSP(g/km)0.0000.2060.0000.4910.0000.1570.6300.4980.1790.0000.0001.0001.0000.146
PM10(g/km)0.0000.2060.0000.4910.0000.1570.6300.4980.1790.0000.0001.0001.0000.146
주소0.9301.0000.0000.0001.0001.0000.2920.2170.9991.0000.8730.1460.1461.000
2023-12-10T19:58:18.071307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점차선측정구간방향주소
지점1.0000.0000.9340.0000.989
차선0.0001.0000.0000.0000.000
측정구간0.9340.0001.0000.8750.923
방향0.0000.0000.8751.0000.000
주소0.9890.0000.9230.0001.000
2023-12-10T19:58:18.356067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키장비이정(km)차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)지점방향차선측정구간주소
기본키1.0000.7420.3130.0170.742-0.7210.0250.0930.0850.7350.0000.0000.8080.741
장비이정(km)0.7421.0000.336-0.0971.000-0.9790.0050.0410.0340.9570.0000.0000.8930.968
차량통과수(대)0.3130.3361.0000.6060.336-0.3140.0420.8510.8470.1330.0000.0000.0460.120
평균 속도(km/hr)0.017-0.0970.6061.000-0.0970.097-0.0410.5480.5330.1870.0000.3050.1630.098
위도(°)0.7421.0000.336-0.0971.000-0.9790.0050.0410.0340.9670.0000.0000.9030.945
경도(°)-0.721-0.979-0.3140.097-0.9791.000-0.025-0.012-0.0010.9460.0000.0690.8840.957
기울기(°)0.0250.0050.042-0.0410.005-0.0251.000-0.049-0.0510.6540.5110.0000.9130.611
TSP(g/km)0.0930.0410.8510.5480.041-0.012-0.0491.0000.9970.0770.0000.3030.0000.050
PM10(g/km)0.0850.0340.8470.5330.034-0.001-0.0510.9971.0000.0770.0000.3030.0000.050
지점0.7350.9570.1330.1870.9670.9460.6540.0770.0771.0000.0000.0000.9340.989
방향0.0000.0000.0000.0000.0000.0000.5110.0000.0000.0001.0000.0000.8750.000
차선0.0000.0000.0000.3050.0000.0690.0000.3030.3030.0000.0001.0000.0000.000
측정구간0.8080.8930.0460.1630.9030.8840.9130.0000.0000.9340.8750.0001.0000.923
주소0.7410.9680.1200.0980.9450.9570.6110.0500.0500.9890.0000.0000.9231.000

Missing values

2023-12-10T19:58:08.468714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:58:08.892567image/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-0010-0538E-6E1언양JC-활천IC53.4202212010395.035.681944129.1811110.225450.210.09울산 울주군 두서면 활천리
12도로공사A-0010-0538E-6E2언양JC-활천IC53.42022120101883.6735.681944129.1811110.225450.460.2울산 울주군 두서면 활천리
23도로공사A-0010-0538E-6E3언양JC-활천IC53.42022120101681.7535.681944129.1811110.225452.521.11울산 울주군 두서면 활천리
34도로공사A-0010-0538E-6S1활천IC-언양JC53.42022120109101.035.681944129.1811110.191580.10.04울산 울주군 두서면 활천리
45도로공사A-0010-0538E-6S2활천IC-언양JC53.42022120103392.635.681944129.1811110.191582.321.02울산 울주군 두서면 활천리
56도로공사A-0010-0538E-6S3활천IC-언양JC53.42022120102680.7535.681944129.1811110.191584.021.77울산 울주군 두서면 활천리
67도로공사A-0010-2583E-7E1금강IC-옥천IC258.3202212010875.036.307222127.574444-0.063390.040.02충북 옥천군 옥천읍 삼양리
78도로공사A-0010-2583E-7E2금강IC-옥천IC258.32022120101890.6736.307222127.574444-0.063390.470.21충북 옥천군 옥천읍 삼양리
89도로공사A-0010-2583E-7E3금강IC-옥천IC258.32022120103482.036.307222127.574444-0.063398.053.54충북 옥천군 옥천읍 삼양리
910도로공사A-0010-2583E-7S1옥천IC-금강IC258.32022120107113.036.307222127.5744440.25940.080.03충북 옥천군 옥천읍 삼양리
기본키도로종류지점방향차선측정구간장비이정(km)측정일측정시간차량통과수(대)평균 속도(km/hr)위도(°)경도(°)기울기(°)TSP(g/km)PM10(g/km)주소
9091도로공사A-0010-4105E-10S2양재IC-금토JC410.4120221201000.037.42325127.077278-0.731380.00.0경기 성남시 수정구 금토동
9192도로공사A-0010-4105E-10S3양재IC-금토JC410.4120221201000.037.42325127.077278-0.731380.00.0경기 성남시 수정구 금토동
9293도로공사A-0010-4105E-10S4양재IC-금토JC410.4120221201017681.1737.42325127.077278-0.731387.773.42경기 성남시 수정구 금토동
9394도로공사A-0010-4105E-10S5양재IC-금토JC410.4120221201000.037.42325127.077278-0.731380.00.0경기 성남시 수정구 금토동
9495도로공사A-0010-2626S-6E1옥천IC-비룡JC262.62022120107111.036.332222127.5341671.227990.080.03충북 옥천군 군북면 이백리
9596도로공사A-0010-2626S-6E2옥천IC-비룡JC262.62022120102588.3336.332222127.5341671.227992.321.02충북 옥천군 군북면 이백리
9697도로공사A-0010-2626S-6E3옥천IC-비룡JC262.62022120104275.6236.332222127.5341671.227997.323.22충북 옥천군 군북면 이백리
9798도로공사A-0010-2626S-6S1비룡JC-옥천IC262.620221201011107.536.332222127.534167-1.227990.290.13충북 옥천군 군북면 이백리
9899도로공사A-0010-2626S-6S2비룡JC-옥천IC262.62022120102987.7136.332222127.534167-1.227991.980.87충북 옥천군 군북면 이백리
99100도로공사A-0010-2626S-6S3비룡JC-옥천IC262.62022120103978.6236.332222127.534167-1.227994.782.1충북 옥천군 군북면 이백리