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 (53.1%)Imbalance
기본키 has unique valuesUnique
co has unique valuesUnique
nox has unique valuesUnique
hc has unique valuesUnique
pm has unique valuesUnique
co2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:36:22.635085
Analysis finished2023-12-10 12:36:36.874563
Duration14.24 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
2023-12-10T21:36:37.075413image/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
2023-12-10T21:36:37.296636image/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

2023-12-10T21:36:37.576583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:37.880607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
[0324-1]
 
4
[0326-2]
 
4
[0406-1]
 
4
[0325-3]
 
4
[0325-4]
 
4
Other values (40)
80 

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%
[0326-2] 4
 
4.0%
[0406-1] 4
 
4.0%
[0325-3] 4
 
4.0%
[0325-4] 4
 
4.0%
[1917-3] 2
 
2.0%
[0408-1] 2
 
2.0%
[0521-1] 2
 
2.0%
[0524-4] 2
 
2.0%
[1721-0] 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:36:38.042443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0324-1 4
 
4.0%
0406-1 4
 
4.0%
0325-3 4
 
4.0%
0325-4 4
 
4.0%
0326-2 4
 
4.0%
3810-1 2
 
2.0%
5913-1 2
 
2.0%
3609-0 2
 
2.0%
3613-0 2
 
2.0%
3709-2 2
 
2.0%
Other values (35) 70
70.0%

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

2023-12-10T21:36:38.229605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:38.375604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수안보-충주
 
4
오생-장호원
 
4
대전-옥천
 
4
신니-신양
 
4
주덕-충주
 
4
Other values (40)
80 

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%
오생-장호원 4
 
4.0%
대전-옥천 4
 
4.0%
신니-신양 4
 
4.0%
주덕-충주 4
 
4.0%
삼승-보은 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
제천-신림 2
 
2.0%
청주-진천 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:36:38.577329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수안보-충주 4
 
4.0%
대전-옥천 4
 
4.0%
신니-신양 4
 
4.0%
주덕-충주 4
 
4.0%
오생-장호원 4
 
4.0%
장락-쌍용 2
 
2.0%
대대-향산 2
 
2.0%
초정-증평 2
 
2.0%
내사-덕산 2
 
2.0%
군서-안내 2
 
2.0%
Other values (35) 70
70.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.074
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:38.819274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.8
median7.3
Q311.1
95-th percentile15.5
Maximum22.4
Range20.9
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation4.4072855
Coefficient of variation (CV)0.54586147
Kurtosis0.6562045
Mean8.074
Median Absolute Deviation (MAD)3.45
Skewness0.82352401
Sum807.4
Variance19.424166
MonotonicityNot monotonic
2023-12-10T21:36:39.046694image/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%
3.4 4
 
4.0%
8.8 4
 
4.0%
12.3 4
 
4.0%
5.0 4
 
4.0%
15.5 4
 
4.0%
14.5 2
 
2.0%
11.0 2
 
2.0%
6.4 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 4
4.0%
15.2 2
2.0%
14.5 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%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210401
90 
20210402
10 

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 90
90.0%
20210402 10
 
10.0%

Length

2023-12-10T21:36:39.262607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:39.447201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210401 90
90.0%
20210402 10
 
10.0%

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

2023-12-10T21:36:39.705593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:39.901637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.79484
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:40.160978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.56286
median36.89448
Q337.03359
95-th percentile37.15606
Maximum37.19998
Range1.09471
Interquartile range (IQR)0.47073

Descriptive statistics

Standard deviation0.29559176
Coefficient of variation (CV)0.0080335112
Kurtosis-0.64372102
Mean36.79484
Median Absolute Deviation (MAD)0.166175
Skewness-0.74975124
Sum3679.484
Variance0.087374487
MonotonicityNot monotonic
2023-12-10T21:36:40.394701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
36.88774 4
 
4.0%
36.96342 4
 
4.0%
37.06589 4
 
4.0%
36.3326 4
 
4.0%
36.9979 4
 
4.0%
36.28264 2
 
2.0%
36.7235 2
 
2.0%
36.91571 2
 
2.0%
36.35443 2
 
2.0%
36.51373 2
 
2.0%
Other values (35) 70
70.0%
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 4
4.0%
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 4
4.0%
37.05585 2
2.0%
37.04502 2
2.0%
37.03807 2
2.0%

좌표위치경도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73894
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:40.624341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.44767
Q1127.56961
median127.692
Q3127.86686
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.29725

Descriptive statistics

Standard deviation0.23289092
Coefficient of variation (CV)0.0018231788
Kurtosis0.62121818
Mean127.73894
Median Absolute Deviation (MAD)0.14858
Skewness0.92846699
Sum12773.894
Variance0.054238179
MonotonicityNot monotonic
2023-12-10T21:36:40.852375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.86686 4
 
4.0%
127.60416 4
 
4.0%
127.53139 4
 
4.0%
127.72238 4
 
4.0%
127.64833 2
 
2.0%
127.55372 2
 
2.0%
128.10947 2
 
2.0%
127.59919 2
 
2.0%
127.79015 2
 
2.0%
Other values (35) 70
70.0%
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 4
4.0%
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%
Mean7277.0567
Minimum573.63
Maximum36084.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:41.076379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum573.63
5-th percentile883.064
Q12409.905
median5280.4
Q310608.017
95-th percentile20817.927
Maximum36084.47
Range35510.84
Interquartile range (IQR)8198.1125

Descriptive statistics

Standard deviation6641.53
Coefficient of variation (CV)0.91266706
Kurtosis5.3609471
Mean7277.0567
Median Absolute Deviation (MAD)3835
Skewness1.9499477
Sum727705.67
Variance44109920
MonotonicityNot monotonic
2023-12-10T21:36:41.357185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2766.84 1
 
1.0%
5925.43 1
 
1.0%
35004.53 1
 
1.0%
21058.9 1
 
1.0%
20836.68 1
 
1.0%
17854.96 1
 
1.0%
17538.32 1
 
1.0%
1172.94 1
 
1.0%
1086.88 1
 
1.0%
11072.77 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
573.63 1
1.0%
602.85 1
1.0%
762.65 1
1.0%
847.85 1
1.0%
860.15 1
1.0%
884.27 1
1.0%
971.4 1
1.0%
1031.85 1
1.0%
1075.21 1
1.0%
1085.97 1
1.0%
ValueCountFrequency (%)
36084.47 1
1.0%
35004.53 1
1.0%
23407.56 1
1.0%
21058.9 1
1.0%
20836.68 1
1.0%
20816.94 1
1.0%
17854.96 1
1.0%
17538.32 1
1.0%
16671.72 1
1.0%
16015.18 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13875.368
Minimum448.89
Maximum88145.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:41.642613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448.89
5-th percentile879.1355
Q13095.685
median6872.175
Q316236.385
95-th percentile57864.611
Maximum88145.06
Range87696.17
Interquartile range (IQR)13140.7

Descriptive statistics

Standard deviation17939.854
Coefficient of variation (CV)1.2929282
Kurtosis5.3739689
Mean13875.368
Median Absolute Deviation (MAD)5428.75
Skewness2.2803209
Sum1387536.8
Variance3.2183837 × 108
MonotonicityNot monotonic
2023-12-10T21:36:41.880395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3063.24 1
 
1.0%
10769.34 1
 
1.0%
85671.82 1
 
1.0%
62822.85 1
 
1.0%
59603.12 1
 
1.0%
57803.7 1
 
1.0%
59021.92 1
 
1.0%
1414.36 1
 
1.0%
1258.81 1
 
1.0%
27849.99 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
448.89 1
1.0%
620.75 1
1.0%
788.31 1
1.0%
807.52 1
1.0%
810.46 1
1.0%
882.75 1
1.0%
905.23 1
1.0%
986.21 1
1.0%
1016.5 1
1.0%
1027.89 1
1.0%
ValueCountFrequency (%)
88145.06 1
1.0%
85671.82 1
1.0%
62822.85 1
1.0%
59603.12 1
1.0%
59021.92 1
1.0%
57803.7 1
1.0%
55062.57 1
1.0%
48843.55 1
1.0%
42922.54 1
1.0%
39980.94 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1454.2536
Minimum61.02
Maximum8489.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:42.187490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum61.02
5-th percentile115.4125
Q1406.7775
median838.695
Q31939.075
95-th percentile4947.428
Maximum8489.87
Range8428.85
Interquartile range (IQR)1532.2975

Descriptive statistics

Standard deviation1647.4832
Coefficient of variation (CV)1.132872
Kurtosis5.491247
Mean1454.2536
Median Absolute Deviation (MAD)632.435
Skewness2.1732692
Sum145425.36
Variance2714201
MonotonicityNot monotonic
2023-12-10T21:36:42.539462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
410.9 1
 
1.0%
1286.98 1
 
1.0%
8246.99 1
 
1.0%
5612.51 1
 
1.0%
5425.62 1
 
1.0%
4339.5 1
 
1.0%
4360.43 1
 
1.0%
199.61 1
 
1.0%
173.37 1
 
1.0%
2488.98 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
61.02 1
1.0%
86.31 1
1.0%
100.65 1
1.0%
110.58 1
1.0%
112.42 1
1.0%
115.57 1
1.0%
125.88 1
1.0%
128.74 1
1.0%
137.36 1
1.0%
138.59 1
1.0%
ValueCountFrequency (%)
8489.87 1
1.0%
8246.99 1
1.0%
5612.51 1
1.0%
5463.11 1
1.0%
5425.62 1
1.0%
4922.26 1
1.0%
4360.43 1
1.0%
4339.5 1
1.0%
4294.87 1
1.0%
4055.3 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean884.809
Minimum38.74
Maximum5483.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:42.882427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.74
5-th percentile58.3165
Q1207.5025
median414.75
Q31095.7675
95-th percentile3601.328
Maximum5483.89
Range5445.15
Interquartile range (IQR)888.265

Descriptive statistics

Standard deviation1113.8948
Coefficient of variation (CV)1.2589099
Kurtosis5.224937
Mean884.809
Median Absolute Deviation (MAD)328.56
Skewness2.2359383
Sum88480.9
Variance1240761.7
MonotonicityNot monotonic
2023-12-10T21:36:43.142384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201.57 1
 
1.0%
707.68 1
 
1.0%
5339.74 1
 
1.0%
3863.57 1
 
1.0%
3652.59 1
 
1.0%
3598.63 1
 
1.0%
3672.92 1
 
1.0%
91.77 1
 
1.0%
88.68 1
 
1.0%
1719.36 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
38.74 1
1.0%
45.41 1
1.0%
47.93 1
1.0%
50.59 1
1.0%
52.36 1
1.0%
58.63 1
1.0%
66.59 1
1.0%
71.16 1
1.0%
71.6 1
1.0%
75.25 1
1.0%
ValueCountFrequency (%)
5483.89 1
1.0%
5339.74 1
1.0%
3863.57 1
1.0%
3672.92 1
1.0%
3652.59 1
1.0%
3598.63 1
1.0%
3421.88 1
1.0%
3034.95 1
1.0%
2714.05 1
1.0%
2548.35 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1966286
Minimum145773.73
Maximum10565448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:43.412185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum145773.73
5-th percentile218705.17
Q1609784.24
median1328100.8
Q32661255.7
95-th percentile6127451.5
Maximum10565448
Range10419675
Interquartile range (IQR)2051471.4

Descriptive statistics

Standard deviation1969762.1
Coefficient of variation (CV)1.0017679
Kurtosis5.7449194
Mean1966286
Median Absolute Deviation (MAD)1003396
Skewness2.1418122
Sum1.966286 × 108
Variance3.8799629 × 1012
MonotonicityNot monotonic
2023-12-10T21:36:43.649704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
663301.79 1
 
1.0%
1440995.2 1
 
1.0%
10099541.98 1
 
1.0%
6691180.59 1
 
1.0%
6443560.37 1
 
1.0%
6110814.16 1
 
1.0%
5989367.18 1
 
1.0%
267163.18 1
 
1.0%
251642.89 1
 
1.0%
3418640.25 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
145773.73 1
1.0%
150285.04 1
1.0%
191580.13 1
1.0%
211316.41 1
1.0%
214795.86 1
1.0%
218910.92 1
1.0%
246195.16 1
1.0%
251642.89 1
1.0%
252219.22 1
1.0%
261757.02 1
1.0%
ValueCountFrequency (%)
10565448.27 1
1.0%
10099541.98 1
1.0%
6721791.53 1
1.0%
6691180.59 1
1.0%
6443560.37 1
1.0%
6110814.16 1
1.0%
5989367.18 1
1.0%
5891706.76 1
1.0%
4705340.17 1
1.0%
4488573.32 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 충주 수안보 중산
 
4
충북 음성 생극 송곡
 
4
충북 옥천 군북 이백
 
4
충북 충주 신니 원평
 
4
충북 충주 대소원 만정
 
4
Other values (40)
80 

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 음성 생극 송곡 4
 
4.0%
충북 옥천 군북 이백 4
 
4.0%
충북 충주 신니 원평 4
 
4.0%
충북 충주 대소원 만정 4
 
4.0%
충북 보은 보은 금굴 2
 
2.0%
충북 영동 심천 약목 2
 
2.0%
충북 단양 매포 매포 2
 
2.0%
충북 제천 봉양 구학 2
 
2.0%
충북 청주 오창 가곡 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:36:43.873756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 28
 
7.0%
음성 12
 
3.0%
옥천 12
 
3.0%
청주 10
 
2.5%
보은 10
 
2.5%
증평 8
 
2.0%
진천 8
 
2.0%
신니 6
 
1.5%
영동 6
 
1.5%
Other values (78) 200
50.0%

Interactions

2023-12-10T21:36:34.454385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.006059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.175670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.300945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:27.900875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.308169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.618075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.945171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.077607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:34.598273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.148887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.290460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.430743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.049850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.490049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.735200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.070466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.200753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:34.743613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.267734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.394719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.545197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.180808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.623397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.851925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.174700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.317689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:34.878418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.417760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.511493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.674890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.313716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.784189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.994747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.351969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.449394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:35.027834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.550892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.633979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.803763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.513654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.945193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.165190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.478147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.607761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:35.226498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.688500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.790488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:27.335582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.711900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.085649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.319996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.607108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.747564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:35.493105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.801109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.928480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:27.478322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.834501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.223589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.446605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.721067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:33.875616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:35.630660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:24.931232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.059337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:27.601216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:28.978460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.343643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.644213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.830605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:34.011830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:35.746375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:25.056313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:26.175735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:27.739382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:29.101922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:30.479465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:31.802733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:32.962306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:34.174620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:36:44.065769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정일좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9900.0000.9900.5321.0000.7780.6520.6080.6590.6400.6460.6030.990
지점0.9901.0000.0001.0001.0000.1071.0001.0000.9770.9710.9780.9820.9871.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9901.0000.0001.0001.0000.1071.0001.0000.9770.9710.9780.9820.9871.000
연장0.5321.0000.0001.0001.0000.1790.6840.5510.6610.4110.5630.4110.6451.000
측정일1.0000.1070.0000.1070.1791.0000.1990.0000.0000.0000.0000.0000.0390.107
좌표위치위도0.7781.0000.0001.0000.6840.1991.0000.6290.6470.5850.5980.5900.6061.000
좌표위치경도0.6521.0000.0001.0000.5510.0000.6291.0000.4480.4250.3970.5290.5431.000
co0.6080.9770.0000.9770.6610.0000.6470.4481.0000.8740.9630.8790.9760.977
nox0.6590.9710.0000.9710.4110.0000.5850.4250.8741.0000.9160.9990.9240.971
hc0.6400.9780.0000.9780.5630.0000.5980.3970.9630.9161.0000.9180.9850.978
pm0.6460.9820.0000.9820.4110.0000.5900.5290.8790.9990.9181.0000.9390.982
co20.6030.9870.0000.9870.6450.0390.6060.5430.9760.9240.9850.9391.0000.987
주소0.9901.0000.0001.0001.0000.1071.0001.0000.9770.9710.9780.9820.9871.000
2023-12-10T21:36:44.736943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일측정구간지점주소방향
측정일1.0000.0000.0000.0000.000
측정구간0.0001.0001.0001.0000.000
지점0.0001.0001.0001.0000.000
주소0.0001.0001.0001.0000.000
방향0.0000.0000.0000.0001.000
2023-12-10T21:36:44.917214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정일주소
기본키1.0000.0920.192-0.1430.3440.4060.4080.4020.3750.6990.0000.6990.9580.699
연장0.0921.0000.1510.065-0.051-0.038-0.036-0.057-0.0460.7730.0000.7730.1280.773
좌표위치위도0.1920.1511.0000.3700.2540.3470.3440.3540.2560.7820.0000.7820.1430.782
좌표위치경도-0.1430.0650.3701.000-0.463-0.383-0.400-0.375-0.4470.7770.0000.7770.0000.777
co0.344-0.0510.254-0.4631.0000.9640.9730.9570.9930.6590.0000.6590.0000.659
nox0.406-0.0380.347-0.3830.9641.0000.9960.9970.9760.5930.0000.5930.0000.593
hc0.408-0.0360.344-0.4000.9730.9961.0000.9930.9790.6630.0000.6630.0000.663
pm0.402-0.0570.354-0.3750.9570.9970.9931.0000.9690.6290.0000.6290.0000.629
co20.375-0.0460.256-0.4470.9930.9760.9790.9691.0000.6980.0000.6980.0400.698
지점0.6990.7730.7820.7770.6590.5930.6630.6290.6981.0000.0001.0000.0001.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.6990.7730.7820.7770.6590.5930.6630.6290.6981.0000.0001.0000.0001.000
측정일0.9580.1280.1430.0000.0000.0000.0000.0000.0400.0000.0000.0001.0000.000
주소0.6990.7730.7820.7770.6590.5930.6630.6290.6981.0000.0001.0000.0001.000

Missing values

2023-12-10T21:36:36.015417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:36.744937image/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-충주7.320210401036.88774127.984842766.843063.24410.9201.57663301.79충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210401036.88774127.984842987.884004.4486.47270.54741216.41충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210401036.9979127.722386745.6210632.581322.86720.761612949.88충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210401036.9979127.722386960.011443.761405.58759.61679053.4충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210401036.96342127.8668611570.5713455.481697.07937.542822289.76충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210401036.96342127.8668610612.611259.931416.07688.692640755.56충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210401037.06589127.604169933.6815789.551917.881106.532360891.52충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210401037.06589127.6041611118.4117380.662154.281226.332607448.34충북 음성 생극 송곡
89건기연[0406-1]1대전-옥천15.520210401036.3326127.531395049.94550.47604.53276.81279113.95충북 옥천 군북 이백
910건기연[0406-1]2대전-옥천15.520210401036.3326127.531395222.064517.42612.73270.171317438.01충북 옥천 군북 이백
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[0324-1]1수안보-충주7.320210402036.88774127.984842741.363106.5394.41209.48678615.61충북 충주 수안보 중산
9192건기연[0324-1]2수안보-충주7.320210402036.88774127.984842832.793754.22437.65259.35720358.36충북 충주 수안보 중산
9293건기연[0325-3]1신니-신양8.820210402036.9979127.722386830.1811132.931336.99745.81673733.89충북 충주 신니 원평
9394건기연[0325-3]2신니-신양8.820210402036.9979127.722387221.6212289.011464.48816.361779501.8충북 충주 신니 원평
9495건기연[0325-4]1주덕-충주5.020210402036.96342127.8668611709.7413923.211727.92964.462871574.41충북 충주 대소원 만정
9596건기연[0325-4]2주덕-충주5.020210402036.96342127.8668610606.4911122.081386.66664.32648384.87충북 충주 대소원 만정
9697건기연[0326-2]1오생-장호원5.420210402037.06589127.6041610162.3816115.881978.751128.332403603.88충북 음성 생극 송곡
9798건기연[0326-2]2오생-장호원5.420210402037.06589127.6041611444.6318488.652263.461290.282705147.41충북 음성 생극 송곡
9899건기연[0406-1]1대전-옥천15.520210402036.3326127.531395183.04761.82636.48282.11304085.88충북 옥천 군북 이백
99100건기연[0406-1]2대전-옥천15.520210402036.3326127.531395338.744680.42641.48270.11336162.59충북 옥천 군북 이백