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
측정시분 has constant value ""Constant
측정구간 is highly overall correlated with 기본키 and 10 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 10 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 10 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 6 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 6 other fieldsHigh correlation
측정일 is highly overall correlated with 기본키High correlation
측정일 is highly imbalanced (59.8%)Imbalance
기본키 has unique valuesUnique
co has unique valuesUnique
nox has unique valuesUnique
hc has unique valuesUnique
co2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:37:09.516134
Analysis finished2023-12-10 12:37:24.474772
Duration14.96 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
2023-12-10T21:37:24.628016image/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
2023-12-10T21:37:24.844287image/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

2023-12-10T21:37:25.041336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:25.206458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
[0324-1]
 
4
[0325-4]
 
4
[0326-2]
 
4
[0325-3]
 
4
[1916-5]
 
2
Other values (41)
82 

Length

Max length8
Median length8
Mean length7.82
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%
[0325-4] 4
 
4.0%
[0326-2] 4
 
4.0%
[0325-3] 4
 
4.0%
[1916-5] 2
 
2.0%
[1917-3] 2
 
2.0%
[0406-1] 2
 
2.0%
[0408-1] 2
 
2.0%
[0521-1] 2
 
2.0%
[0524-4] 2
 
2.0%
Other values (36) 72
72.0%

Length

2023-12-10T21:37:25.339409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0324-1 4
 
4.0%
0325-3 4
 
4.0%
0325-4 4
 
4.0%
0326-2 4
 
4.0%
3713-1 2
 
2.0%
3806-0 2
 
2.0%
3808-1 2
 
2.0%
3412-1 2
 
2.0%
3609-0 2
 
2.0%
3609-1 2
 
2.0%
Other values (36) 72
72.0%

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

2023-12-10T21:37:25.507838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:25.663250image/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 length6.3
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

2023-12-10T21:37:25.848096image/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%
괴산-음성 2
 
2.0%
일죽-감곡ic 2
 
2.0%
목계-산척 2
 
2.0%
증평-대사 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 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%
Mean7.874
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:26.051199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.8
median7.3
Q311
95-th percentile15.2
Maximum22.4
Range20.9
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation4.1993174
Coefficient of variation (CV)0.53331438
Kurtosis1.3017875
Mean7.874
Median Absolute Deviation (MAD)3.2
Skewness0.91794878
Sum787.4
Variance17.634267
MonotonicityNot monotonic
2023-12-10T21:37:26.233778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7.3 10
 
10.0%
5.4 6
 
6.0%
5.0 4
 
4.0%
8.8 4
 
4.0%
12.3 4
 
4.0%
11.1 4
 
4.0%
3.4 4
 
4.0%
11.0 2
 
2.0%
6.4 2
 
2.0%
13.9 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 2
2.0%
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%
14.4 2
2.0%
13.9 2
2.0%
12.3 4
4.0%
12.1 2
2.0%
11.4 2
2.0%
11.2 2
2.0%
11.1 4
4.0%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210201
92 
20210202
 
8

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210201
2nd row20210201
3rd row20210201
4th row20210201
5th row20210201

Common Values

ValueCountFrequency (%)
20210201 92
92.0%
20210202 8
 
8.0%

Length

2023-12-10T21:37:26.416922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:26.575289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210201 92
92.0%
20210202 8
 
8.0%

측정시분
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

2023-12-10T21:37:26.858121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:26.977871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.797774
Minimum36.10527
Maximum37.18469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:27.124315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.62606
median36.88855
Q337.01554
95-th percentile37.11937
Maximum37.18469
Range1.07942
Interquartile range (IQR)0.38948

Descriptive statistics

Standard deviation0.28251673
Coefficient of variation (CV)0.0076775494
Kurtosis-0.36583983
Mean36.797774
Median Absolute Deviation (MAD)0.152995
Skewness-0.86086626
Sum3679.7774
Variance0.079815701
MonotonicityNot monotonic
2023-12-10T21:37:27.323727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
36.88774 4
 
4.0%
36.96342 4
 
4.0%
37.06589 4
 
4.0%
36.9979 4
 
4.0%
37.18469 2
 
2.0%
36.7235 2
 
2.0%
36.83418 2
 
2.0%
36.91571 2
 
2.0%
36.35443 2
 
2.0%
36.51373 2
 
2.0%
Other values (36) 72
72.0%
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 (%)
37.18469 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 4
4.0%
37.05585 2
2.0%
37.04502 2
2.0%
37.03807 2
2.0%
37.03413 2
2.0%

좌표위치경도
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.74337
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:27.532504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.44767
Q1127.57716
median127.7073
Q3127.86686
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.2897

Descriptive statistics

Standard deviation0.23093445
Coefficient of variation (CV)0.0018077999
Kurtosis0.65946069
Mean127.74337
Median Absolute Deviation (MAD)0.14776
Skewness0.90876431
Sum12774.337
Variance0.05333072
MonotonicityNot monotonic
2023-12-10T21:37:27.770278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.86686 4
 
4.0%
127.60416 4
 
4.0%
127.72238 4
 
4.0%
128.27212 2
 
2.0%
127.55372 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
127.59919 2
 
2.0%
127.79015 2
 
2.0%
Other values (36) 72
72.0%
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%
Mean5229.3038
Minimum466.1
Maximum30179.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:27.993893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum466.1
5-th percentile615.229
Q11739.24
median4018.705
Q37243.97
95-th percentile12941.041
Maximum30179.59
Range29713.49
Interquartile range (IQR)5504.73

Descriptive statistics

Standard deviation4978.5634
Coefficient of variation (CV)0.9520509
Kurtosis9.3414741
Mean5229.3038
Median Absolute Deviation (MAD)2834.48
Skewness2.4954792
Sum522930.38
Variance24786093
MonotonicityNot monotonic
2023-12-10T21:37:28.226290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2585.62 1
 
1.0%
1334.72 1
 
1.0%
12934.86 1
 
1.0%
852.2 1
 
1.0%
874.75 1
 
1.0%
11022.41 1
 
1.0%
12017.85 1
 
1.0%
4090.15 1
 
1.0%
4311.38 1
 
1.0%
3033.34 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
466.1 1
1.0%
499.61 1
1.0%
532.94 1
1.0%
538.15 1
1.0%
603.05 1
1.0%
615.87 1
1.0%
735.53 1
1.0%
798.73 1
1.0%
843.64 1
1.0%
852.2 1
1.0%
ValueCountFrequency (%)
30179.59 1
1.0%
28253.82 1
1.0%
15094.23 1
1.0%
13846.33 1
1.0%
13058.48 1
1.0%
12934.86 1
1.0%
12321.8 1
1.0%
12017.85 1
1.0%
11692.12 1
1.0%
11022.41 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7057.2325
Minimum368.06
Maximum49921.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:28.438023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum368.06
5-th percentile543.139
Q11697.4125
median4013.11
Q39062.365
95-th percentile27695.55
Maximum49921.54
Range49553.48
Interquartile range (IQR)7364.9525

Descriptive statistics

Standard deviation8971.6007
Coefficient of variation (CV)1.2712633
Kurtosis9.5227427
Mean7057.2325
Median Absolute Deviation (MAD)2861.73
Skewness2.7867449
Sum705723.25
Variance80489619
MonotonicityNot monotonic
2023-12-10T21:37:28.640513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2365.34 1
 
1.0%
1619.77 1
 
1.0%
27829.88 1
 
1.0%
845.88 1
 
1.0%
750.2 1
 
1.0%
17128.93 1
 
1.0%
14548.65 1
 
1.0%
6647.02 1
 
1.0%
5316.26 1
 
1.0%
4043.35 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
368.06 1
1.0%
393.56 1
1.0%
453.66 1
1.0%
481.31 1
1.0%
539.89 1
1.0%
543.31 1
1.0%
611.24 1
1.0%
659.91 1
1.0%
750.2 1
1.0%
752.6 1
1.0%
ValueCountFrequency (%)
49921.54 1
1.0%
49676.89 1
1.0%
28823.37 1
1.0%
28131.84 1
1.0%
27829.88 1
1.0%
27688.48 1
1.0%
20983.59 1
1.0%
19383.39 1
1.0%
17128.93 1
1.0%
17089.44 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean789.3309
Minimum49.01
Maximum4956.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:28.869229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49.01
5-th percentile68.167
Q1230.77
median528.8
Q31129.115
95-th percentile2309.504
Maximum4956.08
Range4907.07
Interquartile range (IQR)898.345

Descriptive statistics

Standard deviation866.96772
Coefficient of variation (CV)1.0983578
Kurtosis8.7169719
Mean789.3309
Median Absolute Deviation (MAD)357.17
Skewness2.5406017
Sum78933.09
Variance751633.03
MonotonicityNot monotonic
2023-12-10T21:37:29.079669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
314.57 1
 
1.0%
180.57 1
 
1.0%
2323.83 1
 
1.0%
113.73 1
 
1.0%
99.44 1
 
1.0%
1831.41 1
 
1.0%
1808.1 1
 
1.0%
660.07 1
 
1.0%
669.87 1
 
1.0%
490.06 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
49.01 1
1.0%
54.27 1
1.0%
59.2 1
1.0%
64.59 1
1.0%
64.88 1
1.0%
68.34 1
1.0%
73.18 1
1.0%
80.3 1
1.0%
99.44 1
1.0%
103.89 1
1.0%
ValueCountFrequency (%)
4956.08 1
1.0%
4818.37 1
1.0%
2817.04 1
1.0%
2599.26 1
1.0%
2323.83 1
1.0%
2308.75 1
1.0%
2180.32 1
1.0%
2027.75 1
1.0%
1831.41 1
1.0%
1808.1 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean422.7534
Minimum24.18
Maximum2969.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:29.283977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.18
5-th percentile30.008
Q1112.845
median234.855
Q3494.745
95-th percentile1567.4995
Maximum2969.69
Range2945.51
Interquartile range (IQR)381.9

Descriptive statistics

Standard deviation544.56462
Coefficient of variation (CV)1.2881378
Kurtosis8.765663
Mean422.7534
Median Absolute Deviation (MAD)161.615
Skewness2.7110957
Sum42275.34
Variance296550.62
MonotonicityNot monotonic
2023-12-10T21:37:29.505280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
233.75 2
 
2.0%
131.83 1
 
1.0%
114.15 1
 
1.0%
1884.74 1
 
1.0%
58.32 1
 
1.0%
38.93 1
 
1.0%
964.86 1
 
1.0%
760.94 1
 
1.0%
403.89 1
 
1.0%
324.43 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
24.18 1
1.0%
25.0 1
1.0%
25.84 1
1.0%
28.2 1
1.0%
29.21 1
1.0%
30.05 1
1.0%
38.93 1
1.0%
43.72 1
1.0%
44.26 1
1.0%
45.29 1
1.0%
ValueCountFrequency (%)
2969.69 1
1.0%
2937.87 1
1.0%
1898.58 1
1.0%
1884.74 1
1.0%
1614.23 1
1.0%
1565.04 1
1.0%
1221.33 1
1.0%
1130.41 1
1.0%
1035.68 1
1.0%
1022.15 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1376765.5
Minimum120242.64
Maximum8001907.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:29.727165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120242.64
5-th percentile157902.27
Q1406886.26
median1009149.3
Q31826940.2
95-th percentile3893821.1
Maximum8001907.9
Range7881665.3
Interquartile range (IQR)1420054

Descriptive statistics

Standard deviation1368893.4
Coefficient of variation (CV)0.99428214
Kurtosis8.8914614
Mean1376765.5
Median Absolute Deviation (MAD)701037.58
Skewness2.4997161
Sum1.3767655 × 108
Variance1.873869 × 1012
MonotonicityNot monotonic
2023-12-10T21:37:29.977896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
643400.95 1
 
1.0%
324196.99 1
 
1.0%
3890375.26 1
 
1.0%
208866.84 1
 
1.0%
220899.12 1
 
1.0%
2944657.58 1
 
1.0%
2988642.09 1
 
1.0%
1164255.48 1
 
1.0%
1076105.36 1
 
1.0%
763531.36 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
120242.64 1
1.0%
128412.59 1
1.0%
134114.79 1
1.0%
135455.84 1
1.0%
155689.9 1
1.0%
158018.71 1
1.0%
189931.93 1
1.0%
205716.09 1
1.0%
207768.03 1
1.0%
208866.84 1
1.0%
ValueCountFrequency (%)
8001907.93 1
1.0%
7775238.42 1
1.0%
4271757.4 1
1.0%
4159757.32 1
1.0%
3959292.49 1
1.0%
3890375.26 1
1.0%
3421209.07 1
1.0%
3066439.38 1
1.0%
2988642.09 1
1.0%
2944657.58 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 충주 수안보 중산
 
4
충북 충주 대소원 만정
 
4
충북 음성 생극 송곡
 
4
충북 충주 신니 원평
 
4
충북 영동 용산 율
 
2
Other values (41)
82 

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 대소원 만정 4
 
4.0%
충북 음성 생극 송곡 4
 
4.0%
충북 충주 신니 원평 4
 
4.0%
충북 영동 용산 율 2
 
2.0%
충북 보은 보은 금굴 2
 
2.0%
충북 옥천 군북 이백 2
 
2.0%
충북 영동 심천 약목 2
 
2.0%
충북 단양 매포 매포 2
 
2.0%
충북 제천 봉양 구학 2
 
2.0%
Other values (36) 72
72.0%

Length

2023-12-10T21:37:30.213593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 28
 
7.0%
보은 10
 
2.5%
증평 10
 
2.5%
청주 10
 
2.5%
옥천 10
 
2.5%
음성 10
 
2.5%
진천 8
 
2.0%
영동 6
 
1.5%
괴산 6
 
1.5%
Other values (81) 202
50.5%

Interactions

2023-12-10T21:37:22.178197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:11.034135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.714528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.933624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.636748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.997399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.318936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.536620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.900848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.322921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:11.213246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.849087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:14.074725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.799975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.164548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.438997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.701015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.027370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.465301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:11.475025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.985898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:14.252986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.955986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.338156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.562034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.815912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.153735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.666424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:11.661115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.111449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:14.393245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.107454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.513958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.697630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.949182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.289402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.824748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:11.822163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.238702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:14.551214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.241614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.646790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.830394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.172739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.423118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.997776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.041969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.374682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.044665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.379676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.791480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.954258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.300089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.576439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:23.137468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.184192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.515873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.184705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.520378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:17.911845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.082810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.429410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.702441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:23.284533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.438368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.647066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.338124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.682217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.040555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.214736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.618058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:21.872777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:23.426120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:12.568380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:13.785797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:15.473429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:16.820546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:18.169811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:19.363583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:20.759840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:22.022898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:37:30.361826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정일좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9910.0000.9910.5400.9780.8050.6470.6510.6970.6220.6440.5730.991
지점0.9911.0000.0001.0001.0000.1371.0001.0000.9930.9680.9910.9730.9851.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9911.0000.0001.0001.0000.1371.0001.0000.9930.9680.9910.9730.9851.000
연장0.5401.0000.0001.0001.0000.2040.6030.5790.5110.2890.3910.4570.5031.000
측정일0.9780.1370.0000.1370.2041.0000.1530.0000.0000.0000.0000.0000.0000.137
좌표위치위도0.8051.0000.0001.0000.6030.1531.0000.6540.7270.6310.5860.5870.6471.000
좌표위치경도0.6471.0000.0001.0000.5790.0000.6541.0000.6290.3660.5600.4280.5381.000
co0.6510.9930.0000.9930.5110.0000.7270.6291.0000.8730.8910.8830.9620.993
nox0.6970.9680.0000.9680.2890.0000.6310.3660.8731.0000.9700.9550.9580.968
hc0.6220.9910.0000.9910.3910.0000.5860.5600.8910.9701.0000.9300.9860.991
pm0.6440.9730.0000.9730.4570.0000.5870.4280.8830.9550.9301.0000.9110.973
co20.5730.9850.0000.9850.5030.0000.6470.5380.9620.9580.9860.9111.0000.985
주소0.9911.0000.0001.0001.0000.1371.0001.0000.9930.9680.9910.9730.9851.000
2023-12-10T21:37:30.894987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일측정구간지점주소방향
측정일1.0000.0450.0450.0450.000
측정구간0.0451.0001.0001.0000.000
지점0.0451.0001.0001.0000.000
주소0.0451.0001.0001.0000.000
방향0.0000.0000.0000.0001.000
2023-12-10T21:37:31.028745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정일주소
기본키1.0000.0190.213-0.0910.2770.2900.2860.2830.2970.7090.0000.7090.8360.709
연장0.0191.0000.1460.124-0.087-0.123-0.110-0.134-0.1000.7660.0000.7660.1460.766
좌표위치위도0.2130.1461.0000.3890.2150.2750.2640.2720.2190.7750.0000.7750.1080.775
좌표위치경도-0.0910.1240.3891.000-0.415-0.364-0.384-0.375-0.4090.7700.0000.7700.0000.770
co0.277-0.0870.215-0.4151.0000.9750.9840.9620.9980.7180.0000.7180.0000.718
nox0.290-0.1230.275-0.3640.9751.0000.9960.9920.9780.6280.0000.6280.0000.628
hc0.286-0.1100.264-0.3840.9840.9961.0000.9880.9840.7090.0000.7090.0000.709
pm0.283-0.1340.272-0.3750.9620.9920.9881.0000.9650.6370.0000.6370.0000.637
co20.297-0.1000.219-0.4090.9980.9780.9840.9651.0000.6850.0000.6850.0000.685
지점0.7090.7660.7750.7700.7180.6280.7090.6370.6851.0000.0001.0000.0451.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.7090.7660.7750.7700.7180.6280.7090.6370.6851.0000.0001.0000.0451.000
측정일0.8360.1460.1080.0000.0000.0000.0000.0000.0000.0450.0000.0451.0000.045
주소0.7090.7660.7750.7700.7180.6280.7090.6370.6851.0000.0001.0000.0451.000

Missing values

2023-12-10T21:37:24.054886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:37:24.364231image/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-충주7.320210201036.88774127.984842585.622365.34314.57131.83643400.95충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210201036.88774127.984842748.422627.65332.94153.31699035.72충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210201036.9979127.722384526.857034.35828.85383.271154865.61충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210201036.9979127.722384751.375974.65798.95342.441131054.53충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210201036.96342127.866869189.068592.721084.42569.232322840.21충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210201036.96342127.866869365.889092.141139.51509.732351040.24충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210201037.06589127.604166846.889278.011139.15625.491678684.74충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210201037.06589127.604167494.139808.761222.24629.341806704.68충북 음성 생극 송곡
89건기연[0406-1]1대전-옥천15.520210201036.3326127.531394061.143296.71427.87168.251057296.9충북 옥천 군북 이백
910건기연[0406-1]2대전-옥천15.520210201036.3326127.531395036.153500.67523.98155.511186881.81충북 옥천 군북 이백
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04013]1노은JCT-동충주IC12.320210201037.05585127.849247818.9913126.421431.1876.372141566.97충북 충주 노은 신효
9192건기연[04013]2노은JCT-동충주IC12.320210201037.05585127.849248111.713243.891454.981035.682250032.79충북 충주 노은 신효
9293건기연[0324-1]1수안보-충주7.320210202036.88774127.984842530.882029.53264.9890.87648121.35충북 충주 수안보 중산
9394건기연[0324-1]2수안보-충주7.320210202036.88774127.984842297.811850.39234.52100.58592945.89충북 충주 수안보 중산
9495건기연[0325-3]1신니-신양8.820210202036.9979127.722383010.752650.58359.49123.48772697.14충북 충주 신니 원평
9596건기연[0325-3]2신니-신양8.820210202036.9979127.722382867.052699.22356.93138.94723602.38충북 충주 신니 원평
9697건기연[0325-4]1주덕-충주5.020210202036.96342127.866867343.336421.5795.09396.291867010.89충북 충주 대소원 만정
9798건기연[0325-4]2주덕-충주5.020210202036.96342127.866866421.785416.42666.27255.051645750.94충북 충주 대소원 만정
9899건기연[0326-2]1오생-장호원5.420210202037.06589127.604164536.14314.81533.62282.311174686.71충북 음성 생극 송곡
99100건기연[0326-2]2오생-장호원5.420210202037.06589127.604164503.683727.47496.84217.11147618.45충북 음성 생극 송곡