Overview

Dataset statistics

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

Variable types

Numeric9
Categorical7

Alerts

도로종류 has constant value ""Constant
측정일 has constant value ""Constant
주소 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
측정구간 is highly overall correlated with 기본키 and 8 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 6 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 4 other fieldsHigh correlation
nox is highly overall correlated with co and 6 other fieldsHigh correlation
hc is highly overall correlated with co and 3 other fieldsHigh correlation
pm is highly overall correlated with co and 4 other fieldsHigh correlation
co2 is highly overall correlated with co and 3 other fieldsHigh correlation
측정시분 is highly overall correlated with 기본키High correlation
측정시분 is highly imbalanced (67.3%)Imbalance
기본키 has unique valuesUnique
pm has 4 (4.0%) zerosZeros

Reproduction

Analysis started2024-04-16 21:37:47.941151
Analysis finished2024-04-16 21:37:54.937381
Duration7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:54.996203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2024-04-17T06:37:55.101549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

도로종류
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건기연 100
100.0%

Length

2024-04-17T06:37:55.198552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:55.266085image/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

2024-04-17T06:37:55.342322image/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

2024-04-17T06:37:55.447968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:55.521135image/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

2024-04-17T06:37:55.609602image/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
2024-04-17T06:37:55.708074image/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
2024-04-17T06:37:55.803819image/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

2024-04-17T06:37:55.895637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:55.964680image/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
1
94 
2
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2024-04-17T06:37:56.036200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:37:56.106456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 94
94.0%
2 6
 
6.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.806053
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:56.197132image/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
2024-04-17T06:37:56.306212image/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
2024-04-17T06:37:56.412550image/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
2024-04-17T06:37:56.522201image/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 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.6706
Minimum0.65
Maximum617.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:56.630159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.65
5-th percentile1.722
Q17.0725
median28
Q370.225
95-th percentile357.548
Maximum617.74
Range617.09
Interquartile range (IQR)63.1525

Descriptive statistics

Standard deviation121.07415
Coefficient of variation (CV)1.7891692
Kurtosis10.28446
Mean67.6706
Median Absolute Deviation (MAD)23.375
Skewness3.2075907
Sum6767.06
Variance14658.95
MonotonicityNot monotonic
2024-04-17T06:37:56.741689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.65 3
 
3.0%
2.68 2
 
2.0%
11.93 1
 
1.0%
3.28 1
 
1.0%
392.28 1
 
1.0%
3.36 1
 
1.0%
98.18 1
 
1.0%
65.53 1
 
1.0%
29.91 1
 
1.0%
26.72 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
0.65 3
3.0%
1.38 1
 
1.0%
1.57 1
 
1.0%
1.73 1
 
1.0%
2.31 1
 
1.0%
2.63 1
 
1.0%
2.68 2
2.0%
2.78 1
 
1.0%
3.04 1
 
1.0%
3.27 1
 
1.0%
ValueCountFrequency (%)
617.74 1
1.0%
613.48 1
1.0%
527.57 1
1.0%
419.45 1
1.0%
392.28 1
1.0%
355.72 1
1.0%
335.82 1
1.0%
314.36 1
1.0%
133.96 1
1.0%
109.65 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.1828
Minimum0.32
Maximum1494.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:56.861933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.32
5-th percentile1.223
Q14.2075
median34.175
Q391.1075
95-th percentile981.27
Maximum1494.01
Range1493.69
Interquartile range (IQR)86.9

Descriptive statistics

Standard deviation316.13232
Coefficient of variation (CV)2.1774778
Kurtosis8.6305885
Mean145.1828
Median Absolute Deviation (MAD)31.455
Skewness3.0699162
Sum14518.28
Variance99939.646
MonotonicityNot monotonic
2024-04-17T06:37:56.996011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.32 3
 
3.0%
1.73 2
 
2.0%
10.77 1
 
1.0%
1.96 1
 
1.0%
1310.88 1
 
1.0%
2.16 1
 
1.0%
263.88 1
 
1.0%
94.34 1
 
1.0%
62.03 1
 
1.0%
48.78 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
0.32 3
3.0%
0.83 1
 
1.0%
1.09 1
 
1.0%
1.23 1
 
1.0%
1.6 1
 
1.0%
1.64 1
 
1.0%
1.73 2
2.0%
1.79 1
 
1.0%
1.96 1
 
1.0%
2.01 1
 
1.0%
ValueCountFrequency (%)
1494.01 1
1.0%
1420.06 1
1.0%
1310.88 1
1.0%
1164.98 1
1.0%
1076.08 1
1.0%
976.28 1
1.0%
940.88 1
1.0%
930.96 1
1.0%
305.57 1
1.0%
286.76 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5595
Minimum0.06
Maximum145.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:57.102653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile0.179
Q10.69
median4.665
Q311.5225
95-th percentile90.28
Maximum145.16
Range145.1
Interquartile range (IQR)10.8325

Descriptive statistics

Standard deviation29.253749
Coefficient of variation (CV)2.009255
Kurtosis9.6132184
Mean14.5595
Median Absolute Deviation (MAD)4.245
Skewness3.1526261
Sum1455.95
Variance855.78182
MonotonicityNot monotonic
2024-04-17T06:37:57.206943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.06 3
 
3.0%
0.32 2
 
2.0%
0.27 2
 
2.0%
0.26 2
 
2.0%
0.3 1
 
1.0%
82.29 1
 
1.0%
97.11 1
 
1.0%
22.46 1
 
1.0%
12.34 1
 
1.0%
5.81 1
 
1.0%
Other values (85) 85
85.0%
ValueCountFrequency (%)
0.06 3
3.0%
0.13 1
 
1.0%
0.16 1
 
1.0%
0.18 1
 
1.0%
0.23 1
 
1.0%
0.26 2
2.0%
0.27 2
2.0%
0.3 1
 
1.0%
0.32 2
2.0%
0.33 1
 
1.0%
ValueCountFrequency (%)
145.16 1
1.0%
143.64 1
1.0%
121.05 1
1.0%
97.11 1
1.0%
96.74 1
1.0%
89.94 1
1.0%
83.61 1
1.0%
82.29 1
1.0%
32.99 1
1.0%
27.04 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.1038
Minimum0
Maximum93.67
Zeros4
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:57.312477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13
Q10.3775
median2.18
Q35.5725
95-th percentile59.624
Maximum93.67
Range93.67
Interquartile range (IQR)5.195

Descriptive statistics

Standard deviation19.586025
Coefficient of variation (CV)2.151412
Kurtosis8.714188
Mean9.1038
Median Absolute Deviation (MAD)1.985
Skewness3.0749313
Sum910.38
Variance383.61237
MonotonicityNot monotonic
2024-04-17T06:37:57.418720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.13 7
 
7.0%
0.14 6
 
6.0%
0.0 4
 
4.0%
0.27 4
 
4.0%
0.28 4
 
4.0%
0.84 2
 
2.0%
0.79 2
 
2.0%
66.92 1
 
1.0%
88.17 1
 
1.0%
93.67 1
 
1.0%
Other values (68) 68
68.0%
ValueCountFrequency (%)
0.0 4
4.0%
0.13 7
7.0%
0.14 6
6.0%
0.27 4
4.0%
0.28 4
4.0%
0.41 1
 
1.0%
0.54 1
 
1.0%
0.55 1
 
1.0%
0.67 1
 
1.0%
0.79 2
 
2.0%
ValueCountFrequency (%)
93.67 1
1.0%
88.17 1
1.0%
81.12 1
1.0%
72.04 1
1.0%
66.92 1
1.0%
59.24 1
1.0%
58.01 1
1.0%
57.66 1
1.0%
19.52 1
1.0%
17.77 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18550.81
Minimum153.68
Maximum175700.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:37:57.542978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum153.68
5-th percentile455.2285
Q11709.2275
median6694.105
Q317342.595
95-th percentile110788.44
Maximum175700.82
Range175547.14
Interquartile range (IQR)15633.368

Descriptive statistics

Standard deviation35235.863
Coefficient of variation (CV)1.8994245
Kurtosis9.2757027
Mean18550.81
Median Absolute Deviation (MAD)5661.46
Skewness3.1180718
Sum1855081
Variance1.241566 × 109
MonotonicityNot monotonic
2024-04-17T06:37:57.892556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
153.68 3
 
3.0%
646.6 2
 
2.0%
2668.32 1
 
1.0%
794.65 1
 
1.0%
130598.62 1
 
1.0%
878.97 1
 
1.0%
32007.7 1
 
1.0%
14729.33 1
 
1.0%
8656.96 1
 
1.0%
6706.9 1
 
1.0%
Other values (87) 87
87.0%
ValueCountFrequency (%)
153.68 3
3.0%
339.23 1
 
1.0%
416.06 1
 
1.0%
457.29 1
 
1.0%
601.6 1
 
1.0%
640.96 1
 
1.0%
646.6 2
2.0%
734.66 1
 
1.0%
787.16 1
 
1.0%
794.65 1
 
1.0%
ValueCountFrequency (%)
175700.82 1
1.0%
169002.2 1
1.0%
142342.2 1
1.0%
130598.62 1
1.0%
112935.33 1
1.0%
110675.45 1
1.0%
107811.5 1
1.0%
99543.97 1
1.0%
34712.69 1
1.0%
32007.7 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

2024-04-17T06:37:57.999650image/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

2024-04-17T06:37:53.864009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.527731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.352994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.225495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.841519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.449616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.070919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.662672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.293143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.926885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.589921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.438867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.303488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.904139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.513874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.137511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.723620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.354655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.985943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.651592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.508108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.377481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.962765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.571407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.200075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.781818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.420732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.051953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.734883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.584541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.451409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.025496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.634651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.265732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.853320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.483647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.359411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.826560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.650267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.515134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.088516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.704671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.332895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.931120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.546134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.424097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:48.935360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.709047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.580767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.159466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.766252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.397341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.995657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.607526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.493633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.059915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.788378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.646894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.228199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.849338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.466102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.064675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.677405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.560689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.177241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.106210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.714076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.303351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.925387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.533246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.141248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.741920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:54.624111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:49.260597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.162936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:50.773131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.361713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:51.985061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:52.594320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.212790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:37:53.799132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T06:37:58.076451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9930.0000.9940.5710.8930.8030.6260.5760.5650.6510.5960.5060.993
지점0.9931.0000.0001.0001.0000.1471.0001.0000.9100.9150.8780.9110.8631.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9941.0000.0001.0001.0000.2281.0001.0000.9130.9180.8830.9140.8691.000
연장0.5711.0000.0001.0001.0000.0960.6600.5590.2790.2350.0850.2010.3461.000
측정시분0.8930.1470.0000.2280.0961.0000.0000.1060.0000.0000.0000.0000.0000.147
좌표위치위도0.8031.0000.0001.0000.6600.0001.0000.6040.5890.4970.5530.4960.5471.000
좌표위치경도0.6261.0000.0001.0000.5590.1060.6041.0000.3320.1440.0000.1020.0001.000
co0.5760.9100.0000.9130.2790.0000.5890.3321.0000.9880.9960.9880.9860.910
nox0.5650.9150.0000.9180.2350.0000.4970.1440.9881.0000.9921.0000.9860.915
hc0.6510.8780.0000.8830.0850.0000.5530.0000.9960.9921.0000.9930.9840.878
pm0.5960.9110.0000.9140.2010.0000.4960.1020.9881.0000.9931.0000.9850.911
co20.5060.8630.0000.8690.3460.0000.5470.0000.9860.9860.9840.9851.0000.863
주소0.9931.0000.0001.0001.0000.1471.0001.0000.9100.9150.8780.9110.8631.000
2024-04-17T06:37:58.187008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소방향측정구간지점측정시분
주소1.0000.0000.9911.0000.059
방향0.0001.0000.0000.0000.000
측정구간0.9910.0001.0000.9910.117
지점1.0000.0000.9911.0000.059
측정시분0.0590.0000.1170.0591.000
2024-04-17T06:37:58.299948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정시분주소
기본키1.0000.1040.186-0.0720.3050.3360.3360.3260.3280.7180.0000.7260.6990.718
연장0.1041.0000.2010.109-0.024-0.018-0.015-0.020-0.0240.7590.0000.7660.0640.759
좌표위치위도0.1860.2011.0000.3620.2610.3310.3290.3460.2710.7670.0000.7750.0000.767
좌표위치경도-0.0720.1090.3621.000-0.403-0.352-0.359-0.353-0.3940.7630.0000.7700.0980.763
co0.305-0.0240.261-0.4031.0000.9820.9870.9730.9970.4950.0000.5060.0000.495
nox0.336-0.0180.331-0.3520.9821.0000.9970.9950.9880.5050.0000.5160.0000.505
hc0.336-0.0150.329-0.3590.9870.9971.0000.9910.9890.4460.0000.4580.0000.446
pm0.326-0.0200.346-0.3530.9730.9950.9911.0000.9780.4980.0000.5080.0000.498
co20.328-0.0240.271-0.3940.9970.9880.9890.9781.0000.4300.0000.4420.0000.430
지점0.7180.7590.7670.7630.4950.5050.4460.4980.4301.0000.0000.9910.0591.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.7260.7660.7750.7700.5060.5160.4580.5080.4420.9910.0001.0000.1170.991
측정시분0.6990.0640.0000.0980.0000.0000.0000.0000.0000.0590.0000.1171.0000.059
주소0.7180.7590.7670.7630.4950.5050.4460.4980.4301.0000.0000.9910.0591.000

Missing values

2024-04-17T06:37:54.727311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T06:37:54.879241image/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-충주7.320210401136.88774127.9848411.9310.771.690.672668.32충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210401136.88774127.9848412.2811.771.820.862736.37충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210401136.9979127.7223837.7653.097.443.638076.44충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210401136.9979127.7223864.81100.3413.066.5514322.72충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210401136.96342127.8668669.076.959.995.416406.37충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210401136.96342127.8668688.7880.5911.254.6520275.61충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210401137.06589127.6041631.8340.425.642.826720.28충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210401137.06589127.6041634.2951.097.063.717500.85충북 음성 생극 송곡
89건기연[2114-0]1오생-장호원3.620210401137.02646127.6046221.4130.174.052.234765.14충북 음성 생극 병암
910건기연[2114-0]2오생-장호원3.620210401137.02646127.6046228.1434.264.72.56086.72충북 음성 생극 병암
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04013]1노은JCT-동충주IC12.320210401137.05585127.8492481.94247.1923.2515.2425109.8충북 충주 노은 신효
9192건기연[04013]2노은JCT-동충주IC12.320210401137.05585127.8492493.55286.7625.717.7729442.8충북 충주 노은 신효
9293건기연[04511]1감곡IC-여주JCT14.520210401137.19998127.61191527.571164.98121.0572.04142342.2충북 음성 감곡 상우
9394건기연[04511]2감곡IC-여주JCT14.520210401137.19998127.61191419.45930.9696.7457.66112935.33충북 음성 감곡 상우
9495건기연[0324-1]1수안보-충주7.320210401236.88774127.984844.632.70.440.141107.64충북 충주 수안보 중산
9596건기연[0324-1]2수안보-충주7.320210401236.88774127.984843.932.280.380.13948.33충북 충주 수안보 중산
9697건기연[0325-3]1신니-신양8.820210401236.9979127.7223823.9129.774.442.15305.52충북 충주 신니 원평
9798건기연[0325-3]2신니-신양8.820210401236.9979127.7223831.3842.426.352.866681.31충북 충주 신니 원평
9899건기연[0325-4]1주덕-충주5.020210401236.96342127.8668649.2855.697.273.9111723.22충북 충주 대소원 만정
99100건기연[0325-4]2주덕-충주5.020210401236.96342127.8668642.944.065.572.6910456.08충북 충주 대소원 만정