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
지점 is highly overall correlated with 기본키 and 8 other fieldsHigh correlation
측정구간 is highly overall correlated with 기본키 and 8 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 8 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 6 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
co has unique valuesUnique
co2 has unique valuesUnique
pm has 5 (5.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:37:55.264429
Analysis finished2023-12-10 10:38:12.663012
Duration17.4 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
2023-12-10T19:38:12.867357image/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
2023-12-10T19:38:13.666010image/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

2023-12-10T19:38:13.945157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:38:14.120881image/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
[2516-3]
 
2
[1724-4]
 
2
Other values (42)
84 

Length

Max length8
Median length8
Mean length7.8
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%
[2516-3] 2
 
2.0%
[1724-4] 2
 
2.0%
[2517-0] 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

2023-12-10T19:38:14.303874image/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%
04009 2
 
2.0%
3709-2 2
 
2.0%
04011 2
 
2.0%
04013 2
 
2.0%
3808-1 2
 
2.0%
3409-1 2
 
2.0%
3412-1 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

2023-12-10T19:38:14.527770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:38:14.708682image/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
영동-영동IC
 
2
Other values (41)
82 

Length

Max length13
Median length5
Mean length6.4
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%
영동-영동IC 2
 
2.0%
삼승-보은 2
 
2.0%
대전-옥천 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
제천-신림 2
 
2.0%
Other values (36) 72
72.0%

Length

2023-12-10T19:38:14.923102image/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%
증평-대사 2
 
2.0%
초정-증평 2
 
2.0%
내사-덕산 2
 
2.0%
Other values (36) 72
72.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:15.136338image/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 deviation4.3796591
Coefficient of variation (CV)0.54745739
Kurtosis0.70458968
Mean8
Median Absolute Deviation (MAD)3.55
Skewness0.81457129
Sum800
Variance19.181414
MonotonicityNot monotonic
2023-12-10T19:38:15.344525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7.3 10
 
10.0%
5.0 4
 
4.0%
5.4 4
 
4.0%
3.6 4
 
4.0%
12.3 4
 
4.0%
8.8 4
 
4.0%
3.4 4
 
4.0%
11.0 2
 
2.0%
6.4 2
 
2.0%
11.1 2
 
2.0%
Other values (30) 60
60.0%
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%
11.4 2
2.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210401
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210401
2nd row20210401
3rd row20210401
4th row20210401
5th row20210401

Common Values

ValueCountFrequency (%)
20210401 100
100.0%

Length

2023-12-10T19:38:15.593776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:38:15.746555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210401 100
100.0%

측정시분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
94 
15
 
6

Length

Max length2
Median length1
Mean length1.06
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 94
94.0%
15 6
 
6.0%

Length

2023-12-10T19:38:16.028158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:38:16.225225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 94
94.0%
15 6
 
6.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.806053
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:16.448078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.62606
median36.90117
Q337.02646
95-th percentile37.15606
Maximum37.19998
Range1.09471
Interquartile range (IQR)0.4004

Descriptive statistics

Standard deviation0.28794885
Coefficient of variation (CV)0.0078234103
Kurtosis-0.39433435
Mean36.806053
Median Absolute Deviation (MAD)0.140375
Skewness-0.84925023
Sum3680.6053
Variance0.082914542
MonotonicityNot monotonic
2023-12-10T19:38:16.741133image/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%
37.05585 2
 
2.0%
36.7919 2
 
2.0%
36.80475 2
 
2.0%
36.7235 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%
36.28264 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%
ValueCountFrequency (%)
37.19998 2
2.0%
37.18469 2
2.0%
37.15606 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%
37.04502 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%
Mean127.74166
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:17.024204image/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 deviation0.23121984
Coefficient of variation (CV)0.0018100582
Kurtosis0.66968115
Mean127.74166
Median Absolute Deviation (MAD)0.139235
Skewness0.9270489
Sum12774.166
Variance0.053462614
MonotonicityNot monotonic
2023-12-10T19:38:17.285078image/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%
127.84924 2
 
2.0%
127.6034 2
 
2.0%
127.64739 2
 
2.0%
127.55372 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%
128.11702 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%

co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.1177
Minimum0
Maximum939.62
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:17.556766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.7695
Q19.79
median36.865
Q3103.1
95-th percentile457.71
Maximum939.62
Range939.62
Interquartile range (IQR)93.31

Descriptive statistics

Standard deviation164.91293
Coefficient of variation (CV)1.7521989
Kurtosis12.966677
Mean94.1177
Median Absolute Deviation (MAD)32.575
Skewness3.4421417
Sum9411.77
Variance27196.273
MonotonicityNot monotonic
2023-12-10T19:38:17.938804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.09 1
 
1.0%
6.53 1
 
1.0%
468.73 1
 
1.0%
0.65 1
 
1.0%
5.56 1
 
1.0%
101.88 1
 
1.0%
122.6 1
 
1.0%
36.81 1
 
1.0%
34.12 1
 
1.0%
26.67 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
0.0 1
1.0%
0.52 1
1.0%
0.65 1
1.0%
1.3 1
1.0%
1.57 1
1.0%
1.78 1
1.0%
2.03 1
1.0%
3.28 1
1.0%
3.31 1
1.0%
3.36 1
1.0%
ValueCountFrequency (%)
939.62 1
1.0%
900.29 1
1.0%
605.72 1
1.0%
552.9 1
1.0%
468.73 1
1.0%
457.13 1
1.0%
445.33 1
1.0%
370.16 1
1.0%
193.72 1
1.0%
161.62 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean191.0132
Minimum0
Maximum2041.7
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:18.205463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.305
Q16.1675
median38.595
Q3119.855
95-th percentile1257.9505
Maximum2041.7
Range2041.7
Interquartile range (IQR)113.6875

Descriptive statistics

Standard deviation413.58883
Coefficient of variation (CV)2.1652369
Kurtosis9.2136112
Mean191.0132
Median Absolute Deviation (MAD)35.905
Skewness3.1173713
Sum19101.32
Variance171055.72
MonotonicityNot monotonic
2023-12-10T19:38:18.546936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.57 2
 
2.0%
97.48 2
 
2.0%
2.64 2
 
2.0%
0.83 1
 
1.0%
1244.12 1
 
1.0%
1574.1 1
 
1.0%
0.32 1
 
1.0%
274.42 1
 
1.0%
163.69 1
 
1.0%
67.91 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
0.0 1
1.0%
0.28 1
1.0%
0.32 1
1.0%
0.64 1
1.0%
0.83 1
1.0%
1.33 1
1.0%
1.41 1
1.0%
1.96 1
1.0%
2.06 1
1.0%
2.16 1
1.0%
ValueCountFrequency (%)
2041.7 1
1.0%
1976.23 1
1.0%
1574.1 1
1.0%
1451.24 1
1.0%
1340.8 1
1.0%
1253.59 1
1.0%
1244.12 1
1.0%
1229.34 1
1.0%
493.67 1
1.0%
377.34 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.5958
Minimum0
Maximum211.36
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:18.906701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1775
Q10.915
median5.485
Q315.5725
95-th percentile117.111
Maximum211.36
Range211.36
Interquartile range (IQR)14.6575

Descriptive statistics

Standard deviation39.082871
Coefficient of variation (CV)1.9944514
Kurtosis11.141395
Mean19.5958
Median Absolute Deviation (MAD)5.06
Skewness3.2873514
Sum1959.58
Variance1527.4708
MonotonicityNot monotonic
2023-12-10T19:38:19.337123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 2
 
2.0%
0.32 2
 
2.0%
6.95 2
 
2.0%
2.6 1
 
1.0%
7.29 1
 
1.0%
92.15 1
 
1.0%
116.78 1
 
1.0%
0.06 1
 
1.0%
0.53 1
 
1.0%
23.83 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
0.0 1
1.0%
0.04 1
1.0%
0.06 1
1.0%
0.12 1
1.0%
0.13 1
1.0%
0.18 1
1.0%
0.21 1
1.0%
0.31 1
1.0%
0.32 2
2.0%
0.36 1
1.0%
ValueCountFrequency (%)
211.36 1
1.0%
199.98 1
1.0%
142.21 1
1.0%
127.59 1
1.0%
123.4 1
1.0%
116.78 1
1.0%
114.66 1
1.0%
92.15 1
1.0%
50.65 1
1.0%
41.03 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct82
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.9355
Minimum0
Maximum124.34
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:19.614918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1235
Q10.52
median2.67
Q37.2625
95-th percentile78.0705
Maximum124.34
Range124.34
Interquartile range (IQR)6.7425

Descriptive statistics

Standard deviation25.523183
Coefficient of variation (CV)2.138426
Kurtosis9.0161776
Mean11.9355
Median Absolute Deviation (MAD)2.4
Skewness3.0901752
Sum1193.55
Variance651.4329
MonotonicityNot monotonic
2023-12-10T19:38:19.920734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5
 
5.0%
0.13 5
 
5.0%
0.14 4
 
4.0%
0.27 4
 
4.0%
0.4 3
 
3.0%
6.38 2
 
2.0%
0.52 2
 
2.0%
17.02 1
 
1.0%
124.34 1
 
1.0%
83.4 1
 
1.0%
Other values (72) 72
72.0%
ValueCountFrequency (%)
0.0 5
5.0%
0.13 5
5.0%
0.14 4
4.0%
0.27 4
4.0%
0.28 1
 
1.0%
0.4 3
3.0%
0.41 1
 
1.0%
0.42 1
 
1.0%
0.52 2
 
2.0%
0.54 1
 
1.0%
ValueCountFrequency (%)
124.34 1
1.0%
122.23 1
1.0%
96.86 1
1.0%
90.72 1
1.0%
83.4 1
1.0%
77.79 1
1.0%
77.57 1
1.0%
75.33 1
1.0%
31.01 1
1.0%
24.65 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25540.484
Minimum0
Maximum248961.46
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:38:20.217157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile460.577
Q12599.275
median8996.71
Q325760.135
95-th percentile140430.23
Maximum248961.46
Range248961.46
Interquartile range (IQR)23160.86

Descriptive statistics

Standard deviation47287.026
Coefficient of variation (CV)1.8514538
Kurtosis10.762256
Mean25540.484
Median Absolute Deviation (MAD)7732.83
Skewness3.2463868
Sum2554048.4
Variance2.2360628 × 109
MonotonicityNot monotonic
2023-12-10T19:38:20.619210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4614.06 1
 
1.0%
1563.06 1
 
1.0%
158331.96 1
 
1.0%
153.68 1
 
1.0%
1469.32 1
 
1.0%
33347.13 1
 
1.0%
26665.5 1
 
1.0%
10214.65 1
 
1.0%
7476.66 1
 
1.0%
7066.05 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
0.0 1
1.0%
138.68 1
1.0%
153.68 1
1.0%
307.36 1
1.0%
416.06 1
1.0%
462.92 1
1.0%
492.91 1
1.0%
794.65 1
1.0%
873.34 1
1.0%
878.97 1
1.0%
ValueCountFrequency (%)
248961.46 1
1.0%
247631.97 1
1.0%
175411.32 1
1.0%
158331.96 1
1.0%
152493.59 1
1.0%
139795.32 1
1.0%
136991.64 1
1.0%
129335.86 1
1.0%
55642.3 1
1.0%
42570.55 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 탄부 상장
 
2
충북 진천 이월 중산
 
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 탄부 상장 2
 
2.0%
충북 진천 이월 중산 2
 
2.0%
충북 보은 수한 후평 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

2023-12-10T19:38:20.931669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 28
 
7.0%
음성 16
 
4.0%
보은 10
 
2.5%
청주 10
 
2.5%
옥천 10
 
2.5%
진천 8
 
2.0%
증평 8
 
2.0%
영동 6
 
1.5%
신니 6
 
1.5%
Other values (80) 198
49.5%

Interactions

2023-12-10T19:38:09.907645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:56.783713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.673464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:00.085008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:02.003841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.860314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.268605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:06.849296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.266785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:10.128989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:56.938411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.849262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:00.253026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:02.610333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.018275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.439125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.010629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.432032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:10.351167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:57.094638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.986360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:00.414221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:02.771936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.154439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.586296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.149689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.594368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:10.579029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:57.458126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.126373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:00.638651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:02.927565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.322795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.758940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.299167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.758473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:10.733349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:57.648884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.283331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:00.930970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.077047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.476626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.923685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.438428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.919658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:10.910746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:57.958838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.421915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:01.075063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.236888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.622575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:06.074329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.590341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:09.083878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:11.072069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.179842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.594998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:01.304431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.417330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.805050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:06.254913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.804866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:09.272397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:11.214994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.333787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.768284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:01.584043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.562140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:04.957243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:06.421522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:07.947204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:09.461255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:11.434702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:58.511162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:59.908832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:01.778389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:03.711885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:05.121626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:06.681578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:08.118161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:38:09.706057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:38:21.211015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9930.0000.9940.5710.8930.8030.6260.5800.6440.6750.6710.5670.993
지점0.9931.0000.0001.0001.0000.1471.0001.0000.9000.9190.9590.9260.9061.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9941.0000.0001.0001.0000.2281.0001.0000.9030.9210.9600.9270.9091.000
연장0.5711.0000.0001.0001.0000.0960.6600.5590.4780.1440.3270.1130.3141.000
측정시분0.8930.1470.0000.2280.0961.0000.0000.1060.0000.0000.0000.0000.0000.147
좌표위치위도0.8031.0000.0001.0000.6600.0001.0000.6040.6030.5500.6110.5510.5951.000
좌표위치경도0.6261.0000.0001.0000.5590.1060.6041.0000.2390.2260.2790.2340.3071.000
co0.5800.9000.0000.9030.4780.0000.6030.2391.0000.9490.9800.9520.9710.900
nox0.6440.9190.0000.9210.1440.0000.5500.2260.9491.0000.9411.0000.9530.919
hc0.6750.9590.0000.9600.3270.0000.6110.2790.9800.9411.0000.9460.9880.959
pm0.6710.9260.0000.9270.1130.0000.5510.2340.9521.0000.9461.0000.9500.926
co20.5670.9060.0000.9090.3140.0000.5950.3070.9710.9530.9880.9501.0000.906
주소0.9931.0000.0001.0001.0000.1471.0001.0000.9000.9190.9590.9260.9061.000
2023-12-10T19:38:21.539611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점측정구간방향주소측정시분
지점1.0000.9910.0001.0000.059
측정구간0.9911.0000.0000.9910.117
방향0.0000.0001.0000.0000.000
주소1.0000.9910.0001.0000.059
측정시분0.0590.1170.0000.0591.000
2023-12-10T19:38:21.805436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정시분주소
기본키1.0000.1040.186-0.0720.3550.3820.3770.3800.3660.7180.0000.7260.6990.718
연장0.1041.0000.2010.109-0.032-0.017-0.032-0.015-0.0190.7590.0000.7660.0640.759
좌표위치위도0.1860.2011.0000.3620.2150.2930.2860.3000.2240.7670.0000.7750.0000.767
좌표위치경도-0.0720.1090.3621.000-0.420-0.370-0.383-0.371-0.4080.7630.0000.7700.0980.763
co0.355-0.0320.215-0.4201.0000.9810.9860.9740.9970.4650.0000.4760.0000.465
nox0.382-0.0170.293-0.3700.9811.0000.9970.9960.9860.5190.0000.5290.0000.519
hc0.377-0.0320.286-0.3830.9860.9971.0000.9930.9870.5970.0000.6060.0000.597
pm0.380-0.0150.300-0.3710.9740.9960.9931.0000.9800.5310.0000.5410.0000.531
co20.366-0.0190.224-0.4080.9970.9860.9870.9801.0000.4880.0000.4990.0000.488
지점0.7180.7590.7670.7630.4650.5190.5970.5310.4881.0000.0000.9910.0591.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.7260.7660.7750.7700.4760.5290.6060.5410.4990.9910.0001.0000.1170.991
측정시분0.6990.0640.0000.0980.0000.0000.0000.0000.0000.0590.0000.1171.0000.059
주소0.7180.7590.7670.7630.4650.5190.5970.5310.4881.0000.0000.9910.0591.000

Missing values

2023-12-10T19:38:11.732806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:38:12.419281image/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-충주7.320210401036.88774127.9848419.0920.582.61.44614.06충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210401036.88774127.9848412.6911.91.790.823123.68충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210401036.9979127.7223867.5993.9812.646.3815334.92충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210401036.9979127.7223874.1290.1813.396.2716467.4충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210401036.96342127.8668699.0697.4813.736.5222403.99충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210401036.96342127.86686134.94119.316.487.2731146.16충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210401037.06589127.6041641.1548.876.953.388838.3충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210401037.06589127.6041642.7752.017.773.969588.46충북 음성 생극 송곡
89건기연[2114-0]1오생-장호원3.620210401037.02646127.6046228.237.245.02.736456.15충북 음성 생극 병암
910건기연[2114-0]2오생-장호원3.620210401037.02646127.6046235.4347.836.093.568029.89충북 음성 생극 병암
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04013]1노은JCT-동충주IC12.320210401037.05585127.8492489.73241.3423.9214.8825911.53충북 충주 노은 신효
9192건기연[04013]2노은JCT-동충주IC12.320210401037.05585127.84924109.0318.7629.8519.4932834.03충북 충주 노은 신효
9293건기연[04511]1감곡IC-여주JCT14.520210401037.19998127.61191605.721451.24142.2190.72175411.32충북 음성 감곡 상우
9394건기연[04511]2감곡IC-여주JCT14.520210401037.19998127.61191552.91253.59127.5977.57152493.59충북 음성 감곡 상우
9495건기연[0324-1]1수안보-충주7.3202104011536.88774127.9848413.8513.051.480.833523.24충북 충주 수안보 중산
9596건기연[0324-1]2수안보-충주7.3202104011536.88774127.984849.46.10.90.522537.01충북 충주 수안보 중산
9697건기연[0325-3]1신니-신양8.8202104011536.9979127.7223869.5494.9412.816.3815795.97충북 충주 신니 원평
9798건기연[0325-3]2신니-신양8.8202104011536.9979127.7223879.581.7512.625.3817297.92충북 충주 신니 원평
9899건기연[0325-4]1주덕-충주5.0202104011536.96342127.8668684.9676.8711.225.0619728.99충북 충주 대소원 만정
99100건기연[0325-4]2주덕-충주5.0202104011536.96342127.86686139.25121.5216.657.2632156.81충북 충주 대소원 만정