Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.8 KiB
Average record size in memory141.3 B

Variable types

Numeric9
Categorical7

Alerts

도로종류 has constant value ""Constant
측정일 has constant value ""Constant
주소 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
측정구간 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
기본키 is highly overall correlated with 지점 and 3 other fieldsHigh correlation
연장 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치위도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치경도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
co is highly overall correlated with nox and 3 other fieldsHigh correlation
nox is highly overall correlated with co and 6 other fieldsHigh correlation
hc is highly overall correlated with co and 3 other fieldsHigh correlation
pm is highly overall correlated with co and 6 other fieldsHigh correlation
co2 is highly overall correlated with co and 3 other fieldsHigh correlation
측정시분 is highly overall correlated with 기본키High correlation
측정시분 is highly imbalanced (67.3%)Imbalance
기본키 has unique valuesUnique
pm has 2 (2.0%) zerosZeros

Reproduction

Analysis started2024-04-16 21:37:25.781404
Analysis finished2024-04-16 21:37:32.370754
Duration6.59 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
2024-04-17T06:37:32.430138image/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
2024-04-17T06:37:32.537293image/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
건기연
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건기연 100
100.0%

Length

2024-04-17T06:37:32.648723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:32.726445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
[0324-1]
 
4
[0325-3]
 
4
[0325-4]
 
4
[2517-0]
 
2
[1914-2]
 
2
Other values (42)
84 

Length

Max length9
Median length8
Mean length7.84
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row[0324-1]
2nd row[0324-1]
3rd row[0325-3]
4th row[0325-3]
5th row[0325-4]

Common Values

ValueCountFrequency (%)
[0324-1] 4
 
4.0%
[0325-3] 4
 
4.0%
[0325-4] 4
 
4.0%
[2517-0] 2
 
2.0%
[1914-2] 2
 
2.0%
[2518-2] 2
 
2.0%
[0326-2] 2
 
2.0%
[2114-0] 2
 
2.0%
[0406-1] 2
 
2.0%
[0408-1] 2
 
2.0%
Other values (37) 74
74.0%

Length

2024-04-17T06:37:32.807992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0324-1 4
 
4.0%
0325-4 4
 
4.0%
0325-3 4
 
4.0%
04011 2
 
2.0%
3709-2 2
 
2.0%
04012 2
 
2.0%
04510-1 2
 
2.0%
3808-1 2
 
2.0%
3412-1 2
 
2.0%
3609-0 2
 
2.0%
Other values (37) 74
74.0%

방향
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
50 
2
50 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

Length

2024-04-17T06:37:32.935238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:33.015388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수안보-충주
 
4
주덕-충주
 
4
오생-장호원
 
4
신니-신양
 
4
삼승-보은
 
2
Other values (41)
82 

Length

Max length13
Median length5
Mean length6.42
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수안보-충주
2nd row수안보-충주
3rd row신니-신양
4th row신니-신양
5th row주덕-충주

Common Values

ValueCountFrequency (%)
수안보-충주 4
 
4.0%
주덕-충주 4
 
4.0%
오생-장호원 4
 
4.0%
신니-신양 4
 
4.0%
삼승-보은 2
 
2.0%
내북-구방 2
 
2.0%
대전-옥천 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
청주-진천 2
 
2.0%
Other values (36) 72
72.0%

Length

2024-04-17T06:37:33.107228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수안보-충주 4
 
4.0%
신니-신양 4
 
4.0%
주덕-충주 4
 
4.0%
오생-장호원 4
 
4.0%
일죽-감곡ic 2
 
2.0%
목계-산척 2
 
2.0%
장락-쌍용 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 2
 
2.0%
내사-덕산 2
 
2.0%
Other values (36) 72
72.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.994
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:33.207140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.6
median7.3
Q311.1
95-th percentile15.2
Maximum22.4
Range20.9
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.3751553
Coefficient of variation (CV)0.54730489
Kurtosis0.72249877
Mean7.994
Median Absolute Deviation (MAD)3.55
Skewness0.81894601
Sum799.4
Variance19.141984
MonotonicityNot monotonic
2024-04-17T06:37:33.304786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7.3 10
 
10.0%
3.4 4
 
4.0%
8.8 4
 
4.0%
11.1 4
 
4.0%
12.3 4
 
4.0%
5.0 4
 
4.0%
5.4 4
 
4.0%
3.6 4
 
4.0%
14.5 2
 
2.0%
7.5 2
 
2.0%
Other values (29) 58
58.0%
ValueCountFrequency (%)
1.5 2
2.0%
2.0 2
2.0%
2.1 2
2.0%
2.7 2
2.0%
2.8 2
2.0%
3.1 2
2.0%
3.4 4
4.0%
3.6 4
4.0%
3.7 2
2.0%
4.3 2
2.0%
ValueCountFrequency (%)
22.4 2
2.0%
15.5 2
2.0%
15.2 2
2.0%
14.5 2
2.0%
14.4 2
2.0%
13.9 2
2.0%
13.6 2
2.0%
12.3 4
4.0%
12.1 2
2.0%
11.2 2
2.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210601
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210601
2nd row20210601
3rd row20210601
4th row20210601
5th row20210601

Common Values

ValueCountFrequency (%)
20210601 100
100.0%

Length

2024-04-17T06:37:33.417169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:33.493318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210601 100
100.0%

측정시분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
94 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 94
94.0%
2 6
 
6.0%

Length

2024-04-17T06:37:33.564857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:33.634795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 94
94.0%
2 6
 
6.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.81504
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:33.735069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.64694
median36.90117
Q337.02646
95-th percentile37.11937
Maximum37.19998
Range1.09471
Interquartile range (IQR)0.37952

Descriptive statistics

Standard deviation0.27582674
Coefficient of variation (CV)0.0074922298
Kurtosis-0.085228913
Mean36.81504
Median Absolute Deviation (MAD)0.13493
Skewness-0.95227598
Sum3681.504
Variance0.076080392
MonotonicityNot monotonic
2024-04-17T06:37:33.837159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
36.88774 4
 
4.0%
36.96342 4
 
4.0%
36.9979 4
 
4.0%
37.19998 2
 
2.0%
37.05389 2
 
2.0%
36.80475 2
 
2.0%
36.7235 2
 
2.0%
36.83418 2
 
2.0%
36.91571 2
 
2.0%
36.9327 2
 
2.0%
Other values (37) 74
74.0%
ValueCountFrequency (%)
36.10527 2
2.0%
36.20366 2
2.0%
36.24756 2
2.0%
36.32083 2
2.0%
36.3326 2
2.0%
36.35443 2
2.0%
36.44592 2
2.0%
36.45034 2
2.0%
36.47999 2
2.0%
36.51373 2
2.0%
ValueCountFrequency (%)
37.19998 2
2.0%
37.18469 2
2.0%
37.11937 2
2.0%
37.1091 2
2.0%
37.07857 2
2.0%
37.06589 2
2.0%
37.05585 2
2.0%
37.05389 2
2.0%
37.04502 2
2.0%
37.03807 2
2.0%

좌표위치경도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73323
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:33.944994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.44767
Q1127.57716
median127.692
Q3127.86686
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.2897

Descriptive statistics

Standard deviation0.22514955
Coefficient of variation (CV)0.0017626544
Kurtosis1.0780535
Mean127.73323
Median Absolute Deviation (MAD)0.13033
Skewness1.0210323
Sum12773.323
Variance0.050692318
MonotonicityNot monotonic
2024-04-17T06:37:34.073152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.86686 4
 
4.0%
127.72238 4
 
4.0%
127.61191 2
 
2.0%
127.72826 2
 
2.0%
127.64739 2
 
2.0%
127.55372 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
127.66697 2
 
2.0%
Other values (37) 74
74.0%
ValueCountFrequency (%)
127.37509 2
2.0%
127.38986 2
2.0%
127.44767 2
2.0%
127.46142 2
2.0%
127.47145 2
2.0%
127.48385 2
2.0%
127.52268 2
2.0%
127.53139 2
2.0%
127.53503 2
2.0%
127.5518 2
2.0%
ValueCountFrequency (%)
128.39227 2
2.0%
128.33167 2
2.0%
128.27212 2
2.0%
128.10947 2
2.0%
127.98484 4
4.0%
127.95441 2
2.0%
127.95118 2
2.0%
127.92804 2
2.0%
127.91705 2
2.0%
127.8901 2
2.0%

co
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.075
Minimum1.05
Maximum663.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:34.176015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.05
5-th percentile2.3075
Q110.125
median28.7
Q384.4575
95-th percentile463.3915
Maximum663.12
Range662.07
Interquartile range (IQR)74.3325

Descriptive statistics

Standard deviation132.94012
Coefficient of variation (CV)1.7248151
Kurtosis9.0555656
Mean77.075
Median Absolute Deviation (MAD)24.01
Skewness3.0481685
Sum7707.5
Variance17673.076
MonotonicityNot monotonic
2024-04-17T06:37:34.279487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.26 3
 
3.0%
2.78 2
 
2.0%
38.8 2
 
2.0%
3.93 2
 
2.0%
21.58 1
 
1.0%
210.19 1
 
1.0%
311.05 1
 
1.0%
3.31 1
 
1.0%
107.44 1
 
1.0%
89.52 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
1.05 1
 
1.0%
1.73 1
 
1.0%
2.26 3
3.0%
2.31 1
 
1.0%
2.6 1
 
1.0%
2.78 2
2.0%
2.83 1
 
1.0%
3.31 1
 
1.0%
3.88 1
 
1.0%
3.93 2
2.0%
ValueCountFrequency (%)
663.12 1
1.0%
587.24 1
1.0%
569.1 1
1.0%
554.8 1
1.0%
495.91 1
1.0%
461.68 1
1.0%
311.05 1
1.0%
210.19 1
1.0%
170.82 1
1.0%
148.96 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean144.454
Minimum0.55
Maximum1432.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:34.386175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.55
5-th percentile1.51
Q19.26
median31.45
Q392.315
95-th percentile943.99
Maximum1432.4
Range1431.85
Interquartile range (IQR)83.055

Descriptive statistics

Standard deviation285.15627
Coefficient of variation (CV)1.9740282
Kurtosis8.508182
Mean144.454
Median Absolute Deviation (MAD)28.455
Skewness2.9431955
Sum14445.4
Variance81314.101
MonotonicityNot monotonic
2024-04-17T06:37:34.491304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.51 3
 
3.0%
2.28 2
 
2.0%
1.79 2
 
2.0%
24.28 1
 
1.0%
3.48 1
 
1.0%
740.95 1
 
1.0%
2.06 1
 
1.0%
262.3 1
 
1.0%
125.8 1
 
1.0%
74.56 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
0.55 1
 
1.0%
1.23 1
 
1.0%
1.28 1
 
1.0%
1.51 3
3.0%
1.6 1
 
1.0%
1.79 2
2.0%
1.88 1
 
1.0%
2.06 1
 
1.0%
2.28 2
2.0%
2.43 1
 
1.0%
ValueCountFrequency (%)
1432.4 1
1.0%
1289.19 1
1.0%
1121.38 1
1.0%
1064.79 1
1.0%
969.83 1
1.0%
942.63 1
1.0%
740.95 1
1.0%
515.47 1
1.0%
422.86 1
1.0%
399.43 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct93
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.3783
Minimum0.09
Maximum143.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:34.612276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile0.2295
Q11.4075
median4.36
Q313.1425
95-th percentile97.2965
Maximum143.77
Range143.68
Interquartile range (IQR)11.735

Descriptive statistics

Standard deviation28.781204
Coefficient of variation (CV)1.8715465
Kurtosis8.6668057
Mean15.3783
Median Absolute Deviation (MAD)3.85
Skewness2.9785325
Sum1537.83
Variance828.35772
MonotonicityNot monotonic
2024-04-17T06:37:34.760724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.22 3
 
3.0%
0.44 2
 
2.0%
0.23 2
 
2.0%
0.51 2
 
2.0%
0.38 2
 
2.0%
0.26 2
 
2.0%
3.79 1
 
1.0%
49.96 1
 
1.0%
72.69 1
 
1.0%
0.31 1
 
1.0%
Other values (83) 83
83.0%
ValueCountFrequency (%)
0.09 1
 
1.0%
0.18 1
 
1.0%
0.22 3
3.0%
0.23 2
2.0%
0.26 2
2.0%
0.27 1
 
1.0%
0.31 1
 
1.0%
0.36 1
 
1.0%
0.38 2
2.0%
0.44 2
2.0%
ValueCountFrequency (%)
143.77 1
1.0%
129.36 1
1.0%
117.29 1
1.0%
113.07 1
1.0%
100.46 1
1.0%
97.13 1
1.0%
72.69 1
1.0%
49.96 1
1.0%
41.52 1
1.0%
36.5 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8802
Minimum0
Maximum88.11
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:34.872108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13
Q10.69
median2.17
Q36.065
95-th percentile56.489
Maximum88.11
Range88.11
Interquartile range (IQR)5.375

Descriptive statistics

Standard deviation17.293491
Coefficient of variation (CV)1.9474213
Kurtosis8.667879
Mean8.8802
Median Absolute Deviation (MAD)1.9
Skewness2.9541864
Sum888.02
Variance299.06483
MonotonicityNot monotonic
2024-04-17T06:37:34.973055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.13 9
 
9.0%
0.14 4
 
4.0%
0.72 2
 
2.0%
1.36 2
 
2.0%
0.4 2
 
2.0%
1.33 2
 
2.0%
0.27 2
 
2.0%
0.41 2
 
2.0%
0.97 2
 
2.0%
0.0 2
 
2.0%
Other values (69) 71
71.0%
ValueCountFrequency (%)
0.0 2
 
2.0%
0.13 9
9.0%
0.14 4
4.0%
0.26 1
 
1.0%
0.27 2
 
2.0%
0.28 1
 
1.0%
0.4 2
 
2.0%
0.41 2
 
2.0%
0.54 1
 
1.0%
0.66 1
 
1.0%
ValueCountFrequency (%)
88.11 1
1.0%
78.87 1
1.0%
67.85 1
1.0%
64.14 1
1.0%
57.61 1
1.0%
56.43 1
1.0%
44.95 1
1.0%
31.58 1
1.0%
26.29 1
1.0%
24.19 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20526.208
Minimum277.37
Maximum185421.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:35.075421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum277.37
5-th percentile601.3185
Q12331.2375
median6927.31
Q320438.408
95-th percentile128032.6
Maximum185421.81
Range185144.44
Interquartile range (IQR)18107.17

Descriptive statistics

Standard deviation36690.024
Coefficient of variation (CV)1.7874721
Kurtosis8.9624814
Mean20526.208
Median Absolute Deviation (MAD)5686.765
Skewness3.025631
Sum2052620.8
Variance1.3461579 × 109
MonotonicityNot monotonic
2024-04-17T06:37:35.183938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
595.97 3
 
3.0%
948.33 2
 
2.0%
734.66 2
 
2.0%
4549.57 1
 
1.0%
1341.9 1
 
1.0%
89967.47 1
 
1.0%
873.34 1
 
1.0%
33735.49 1
 
1.0%
20902.12 1
 
1.0%
10975.65 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
277.37 1
 
1.0%
457.29 1
 
1.0%
595.97 3
3.0%
601.6 1
 
1.0%
614.73 1
 
1.0%
734.66 2
2.0%
740.29 1
 
1.0%
873.34 1
 
1.0%
948.33 2
2.0%
1017.66 1
 
1.0%
ValueCountFrequency (%)
185421.81 1
1.0%
164505.85 1
1.0%
152170.42 1
1.0%
146813.16 1
1.0%
130311.08 1
1.0%
127912.68 1
1.0%
89967.47 1
1.0%
62164.96 1
1.0%
50209.33 1
1.0%
44555.35 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 충주 수안보 중산
 
4
충북 충주 신니 원평
 
4
충북 충주 대소원 만정
 
4
충북 보은 수한 후평
 
2
충북 영동 학산 범화
 
2
Other values (42)
84 

Length

Max length12
Median length11
Mean length11.1
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충북 충주 수안보 중산
2nd row충북 충주 수안보 중산
3rd row충북 충주 신니 원평
4th row충북 충주 신니 원평
5th row충북 충주 대소원 만정

Common Values

ValueCountFrequency (%)
충북 충주 수안보 중산 4
 
4.0%
충북 충주 신니 원평 4
 
4.0%
충북 충주 대소원 만정 4
 
4.0%
충북 보은 수한 후평 2
 
2.0%
충북 영동 학산 범화 2
 
2.0%
충북 청주 남일 두산 2
 
2.0%
충북 음성 생극 송곡 2
 
2.0%
충북 음성 생극 병암 2
 
2.0%
충북 옥천 군북 이백 2
 
2.0%
충북 영동 심천 약목 2
 
2.0%
Other values (37) 74
74.0%

Length

2024-04-17T06:37:35.293363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 30
 
7.5%
음성 16
 
4.0%
증평 10
 
2.5%
청주 10
 
2.5%
보은 10
 
2.5%
진천 8
 
2.0%
옥천 8
 
2.0%
영동 6
 
1.5%
노은 6
 
1.5%
Other values (79) 196
49.0%

Interactions

2024-04-17T06:37:31.308295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.383096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.943987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.729267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.325089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.947941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.530915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.122243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.735634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.372291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.443153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.001618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.811276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.387665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.009064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.595892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.190510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.795875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.429519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.497623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.052441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.871151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.455122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.064520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.653373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.252481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.848512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.496251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.563299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.115760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.932356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.536435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.127823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.719994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.319547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.909421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.563817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.625460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.186178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.998527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.600053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.193262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.787185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.383204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.969378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.630038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.688547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.254330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.063470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.665482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.261024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.854111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.450270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.032958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.696691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.753386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.553577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.131603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.732989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.330953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.921233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.525322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.114541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:32.001288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.820838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.613735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.198448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.800022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.401749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.993078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.602143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.187810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:32.061496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:26.878654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:27.668154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.258863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:28.862638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:29.462826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.053400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:30.662158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:31.242045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T06:37:35.620570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9930.0000.9940.5650.8930.7640.6780.5230.6350.5820.6240.5500.993
지점0.9931.0000.0001.0001.0000.1471.0001.0000.8730.9250.9010.9250.7771.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0380.000
측정구간0.9941.0000.0001.0001.0000.2281.0001.0000.8810.9290.9070.9290.7951.000
연장0.5651.0000.0001.0001.0000.0960.6840.5510.3430.4020.3170.4030.2711.000
측정시분0.8930.1470.0000.2280.0961.0000.0000.0760.0000.0000.0000.0000.0000.147
좌표위치위도0.7641.0000.0001.0000.6840.0001.0000.6200.4810.5210.5080.5480.4421.000
좌표위치경도0.6781.0000.0001.0000.5510.0760.6201.0000.3150.2890.4690.3030.2491.000
co0.5230.8730.0000.8810.3430.0000.4810.3151.0000.9910.9950.9930.9980.873
nox0.6350.9250.0000.9290.4020.0000.5210.2890.9911.0000.9951.0000.9910.925
hc0.5820.9010.0000.9070.3170.0000.5080.4690.9950.9951.0000.9970.9960.901
pm0.6240.9250.0000.9290.4030.0000.5480.3030.9931.0000.9971.0000.9910.925
co20.5500.7770.0380.7950.2710.0000.4420.2490.9980.9910.9960.9911.0000.777
주소0.9931.0000.0001.0001.0000.1471.0001.0000.8730.9250.9010.9250.7771.000
2024-04-17T06:37:35.726212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소방향측정구간지점측정시분
주소1.0000.0000.9911.0000.059
방향0.0001.0000.0000.0000.000
측정구간0.9910.0001.0000.9910.117
지점1.0000.0000.9911.0000.059
측정시분0.0590.0000.1170.0591.000
2024-04-17T06:37:35.810254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정시분주소
기본키1.0000.1570.294-0.0130.3460.3550.3520.3520.3620.7180.0000.7260.6990.718
연장0.1571.0000.2190.081-0.022-0.027-0.022-0.030-0.0200.7590.0000.7660.0640.759
좌표위치위도0.2940.2191.0000.3320.3890.4470.4370.4550.3890.7670.0000.7750.0000.767
좌표위치경도-0.0130.0810.3321.000-0.352-0.317-0.325-0.311-0.3470.7630.0000.7700.0680.763
co0.346-0.0220.389-0.3521.0000.9890.9950.9850.9980.4140.0000.4270.0000.414
nox0.355-0.0270.447-0.3170.9891.0000.9970.9980.9900.5020.0000.5130.0000.502
hc0.352-0.0220.437-0.3250.9950.9971.0000.9940.9930.4580.0000.4700.0000.458
pm0.352-0.0300.455-0.3110.9850.9980.9941.0000.9860.5020.0000.5130.0000.502
co20.362-0.0200.389-0.3470.9980.9900.9930.9861.0000.3140.0140.3310.0000.314
지점0.7180.7590.7670.7630.4140.5020.4580.5020.3141.0000.0000.9910.0591.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0140.0001.0000.0000.0000.000
측정구간0.7260.7660.7750.7700.4270.5130.4700.5130.3310.9910.0001.0000.1170.991
측정시분0.6990.0640.0000.0680.0000.0000.0000.0000.0000.0590.0000.1171.0000.059
주소0.7180.7590.7670.7630.4140.5020.4580.5020.3141.0000.0000.9910.0591.000

Missing values

2024-04-17T06:37:32.163150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T06:37:32.314419image/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

기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
01건기연[0324-1]1수안보-충주7.320210601136.88774127.9848421.5824.283.761.514549.57충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210601136.88774127.9848413.7416.182.41.083106.29충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210601136.9979127.7223838.843.296.062.729073.5충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210601136.9979127.7223846.0660.248.564.0210122.71충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210601136.96342127.8668677.5381.2310.745.618775.65충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210601136.96342127.86686110.2115.3615.347.1826456.42충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210601137.06589127.6041637.8443.176.242.748109.68충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210601137.06589127.6041622.1431.084.082.265084.74충북 음성 생극 송곡
89건기연[2114-0]1오생-장호원3.620210601137.02646127.6046222.3430.314.072.24973.42충북 음성 생극 병암
910건기연[2114-0]2오생-장호원3.620210601137.02646127.6046219.8524.373.261.674285.66충북 음성 생극 병암
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04510-1]1충주JCT-감곡IC12.120210601137.05389127.72826461.68969.8397.1357.61127912.68충북 충주 노은 연하
9192건기연[04510-1]2충주JCT-감곡IC12.120210601137.05389127.72826495.91942.63100.4656.43130311.08충북 충주 노은 연하
9293건기연[04511]1감곡IC-여주JCT14.520210601137.19998127.61191569.11121.38117.2967.85152170.42충북 음성 감곡 상우
9394건기연[04511]2감곡IC-여주JCT14.520210601137.19998127.61191554.81064.79113.0764.14146813.16충북 음성 감곡 상우
9495건기연[0324-1]1수안보-충주7.320210601236.88774127.9848410.6910.791.610.722524.54충북 충주 수안보 중산
9596건기연[0324-1]2수안보-충주7.320210601236.88774127.9848412.4815.162.261.052791.45충북 충주 수안보 중산
9697건기연[0325-3]1신니-신양8.820210601236.9979127.7223821.4420.943.141.365129.05충북 충주 신니 원평
9798건기연[0325-3]2신니-신양8.820210601236.9979127.7223823.9430.554.572.085220.49충북 충주 신니 원평
9899건기연[0325-4]1주덕-충주5.020210601236.96342127.8668652.9451.337.173.3412198.27충북 충주 대소원 만정
99100건기연[0325-4]2주덕-충주5.020210601236.96342127.8668648.1851.686.73.2711552.53충북 충주 대소원 만정