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 5 other fieldsHigh correlation
측정구간 is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
기본키 is highly overall correlated with 지점 and 3 other fieldsHigh correlation
연장 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치위도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치경도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
co is highly overall correlated with nox and 3 other fieldsHigh correlation
nox is highly overall correlated with co and 3 other fieldsHigh correlation
hc is highly overall correlated with co and 3 other fieldsHigh correlation
pm is highly overall correlated with co and 3 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 (75.8%)Imbalance
기본키 has unique valuesUnique
pm has 5 (5.0%) zerosZeros

Reproduction

Analysis started2024-04-16 21:38:10.295936
Analysis finished2024-04-16 21:38:16.722318
Duration6.43 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
2024-04-17T06:38:17.050847image/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
2024-04-17T06:38:17.160290image/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

2024-04-17T06:38:17.256228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:38:17.325542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
[0324-1]
 
4
[0325-3]
 
4
[1914-2]
 
2
[0325-4]
 
2
[0326-2]
 
2
Other values (43)
86 

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%
[0325-3] 4
 
4.0%
[1914-2] 2
 
2.0%
[0325-4] 2
 
2.0%
[0326-2] 2
 
2.0%
[2114-0] 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 (38) 76
76.0%

Length

2024-04-17T06:38:17.398864image/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%
3806-0 2
 
2.0%
3409-1 2
 
2.0%
3412-1 2
 
2.0%
3609-0 2
 
2.0%
3609-1 2
 
2.0%
3613-0 2
 
2.0%
3716-0 2
 
2.0%
3709-2 2
 
2.0%
Other values (38) 76
76.0%

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

2024-04-17T06:38:17.483214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:38:17.556280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수안보-충주
 
4
신니-신양
 
4
오생-장호원
 
4
보은-회북
 
2
황산-묵정
 
2
Other values (42)
84 

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%
신니-신양 4
 
4.0%
오생-장호원 4
 
4.0%
보은-회북 2
 
2.0%
황산-묵정 2
 
2.0%
남일-가덕 2
 
2.0%
주덕-충주 2
 
2.0%
대전-옥천 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
Other values (37) 74
74.0%

Length

2024-04-17T06:38:17.644327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수안보-충주 4
 
4.0%
오생-장호원 4
 
4.0%
신니-신양 4
 
4.0%
대소jct-금왕꽃동네ic 2
 
2.0%
군서-안내 2
 
2.0%
금왕꽃동네ic-음성ic 2
 
2.0%
충주jct-노은jct 2
 
2.0%
일죽-감곡ic 2
 
2.0%
증평-대사 2
 
2.0%
초정-증평 2
 
2.0%
Other values (37) 74
74.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.01
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:17.742383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.6
median7.35
Q311.1
95-th percentile15.2
Maximum22.4
Range20.9
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.2844445
Coefficient of variation (CV)0.53488695
Kurtosis0.93278595
Mean8.01
Median Absolute Deviation (MAD)3.55
Skewness0.80604401
Sum801
Variance18.356465
MonotonicityNot monotonic
2024-04-17T06:38:17.836391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7.3 10
 
10.0%
8.8 4
 
4.0%
5.4 4
 
4.0%
3.6 4
 
4.0%
12.3 4
 
4.0%
11.1 4
 
4.0%
3.4 4
 
4.0%
8.9 2
 
2.0%
6.4 2
 
2.0%
13.6 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%
14.4 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%
11.2 2
2.0%

측정일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210201
100 

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 100
100.0%

Length

2024-04-17T06:38:17.927958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:38:17.999780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210201 100
100.0%

측정시분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
96 
2
 
4

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 96
96.0%
2 4
 
4.0%

Length

2024-04-17T06:38:18.072403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T06:38:18.151948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 96
96.0%
2 4
 
4.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.796371
Minimum36.10527
Maximum37.18469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:18.256224image/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 deviation0.2814808
Coefficient of variation (CV)0.0076496892
Kurtosis-0.35331928
Mean36.796371
Median Absolute Deviation (MAD)0.14755
Skewness-0.86383897
Sum3679.6371
Variance0.07923144
MonotonicityNot monotonic
2024-04-17T06:38:18.370876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
36.88774 4
 
4.0%
36.9979 4
 
4.0%
37.05585 2
 
2.0%
37.11937 2
 
2.0%
36.7919 2
 
2.0%
36.80475 2
 
2.0%
36.7235 2
 
2.0%
36.83418 2
 
2.0%
36.91571 2
 
2.0%
36.9327 2
 
2.0%
Other values (38) 76
76.0%
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 2
2.0%
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 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73938
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:18.477947image/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 deviation0.23048191
Coefficient of variation (CV)0.0018043136
Kurtosis0.75498924
Mean127.73938
Median Absolute Deviation (MAD)0.13033
Skewness0.96323244
Sum12773.938
Variance0.053121911
MonotonicityNot monotonic
2024-04-17T06:38:18.587125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.72238 4
 
4.0%
127.84924 2
 
2.0%
127.65518 2
 
2.0%
127.6034 2
 
2.0%
127.64739 2
 
2.0%
127.55372 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
127.66697 2
 
2.0%
Other values (38) 76
76.0%
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 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.2699
Minimum0.52
Maximum671.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:18.693220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.52
5-th percentile2.2445
Q19.835
median28.345
Q373.2275
95-th percentile239.2255
Maximum671.43
Range670.91
Interquartile range (IQR)63.3925

Descriptive statistics

Standard deviation100.64341
Coefficient of variation (CV)1.642624
Kurtosis19.120314
Mean61.2699
Median Absolute Deviation (MAD)21.42
Skewness3.9751088
Sum6126.99
Variance10129.096
MonotonicityNot monotonic
2024-04-17T06:38:18.813540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.56 2
 
2.0%
1.3 2
 
2.0%
17.63 1
 
1.0%
52.0 1
 
1.0%
165.3 1
 
1.0%
38.63 1
 
1.0%
36.21 1
 
1.0%
23.77 1
 
1.0%
21.07 1
 
1.0%
9.37 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
0.52 1
1.0%
1.05 1
1.0%
1.3 2
2.0%
1.95 1
1.0%
2.26 1
1.0%
2.59 1
1.0%
3.31 1
1.0%
3.83 1
1.0%
5.14 1
1.0%
5.23 1
1.0%
ValueCountFrequency (%)
671.43 1
1.0%
563.19 1
1.0%
323.67 1
1.0%
286.96 1
1.0%
245.41 1
1.0%
238.9 1
1.0%
185.31 1
1.0%
165.3 1
1.0%
146.09 1
1.0%
119.85 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.1454
Minimum0.28
Maximum1066.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:18.925974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.28
5-th percentile1.4825
Q16.6275
median26.8
Q375.3575
95-th percentile496.171
Maximum1066.61
Range1066.33
Interquartile range (IQR)68.73

Descriptive statistics

Standard deviation176.10825
Coefficient of variation (CV)2.0208554
Kurtosis15.981216
Mean87.1454
Median Absolute Deviation (MAD)22.915
Skewness3.8192559
Sum8714.54
Variance31014.116
MonotonicityNot monotonic
2024-04-17T06:38:19.052184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.92 2
 
2.0%
0.64 2
 
2.0%
15.48 1
 
1.0%
51.1 1
 
1.0%
191.78 1
 
1.0%
55.61 1
 
1.0%
38.83 1
 
1.0%
27.0 1
 
1.0%
19.89 1
 
1.0%
9.91 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
0.28 1
1.0%
0.55 1
1.0%
0.64 2
2.0%
0.96 1
1.0%
1.51 1
1.0%
1.59 1
1.0%
2.06 1
1.0%
2.34 1
1.0%
2.92 1
1.0%
3.26 1
1.0%
ValueCountFrequency (%)
1066.61 1
1.0%
954.05 1
1.0%
624.24 1
1.0%
614.17 1
1.0%
512.53 1
1.0%
495.31 1
1.0%
261.89 1
1.0%
202.87 1
1.0%
194.9 1
1.0%
194.85 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.5915
Minimum0.04
Maximum111.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:19.168781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.2175
Q11.005
median3.76
Q39.8375
95-th percentile42.8405
Maximum111.08
Range111.04
Interquartile range (IQR)8.8325

Descriptive statistics

Standard deviation17.207558
Coefficient of variation (CV)1.7940425
Kurtosis17.594567
Mean9.5915
Median Absolute Deviation (MAD)3.145
Skewness3.878596
Sum959.15
Variance296.10007
MonotonicityNot monotonic
2024-04-17T06:38:19.276661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.64 2
 
2.0%
0.12 2
 
2.0%
0.49 2
 
2.0%
3.28 2
 
2.0%
1.82 1
 
1.0%
1.11 1
 
1.0%
29.71 1
 
1.0%
25.07 1
 
1.0%
6.24 1
 
1.0%
5.36 1
 
1.0%
Other values (86) 86
86.0%
ValueCountFrequency (%)
0.04 1
1.0%
0.09 1
1.0%
0.12 2
2.0%
0.17 1
1.0%
0.22 1
1.0%
0.26 1
1.0%
0.31 1
1.0%
0.35 1
1.0%
0.49 2
2.0%
0.5 1
1.0%
ValueCountFrequency (%)
111.08 1
1.0%
93.44 1
1.0%
60.5 1
1.0%
51.63 1
1.0%
46.84 1
1.0%
42.63 1
1.0%
29.71 1
1.0%
25.07 1
1.0%
21.56 1
1.0%
19.95 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)77.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2106
Minimum0
Maximum63.1
Zeros5
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:19.382859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1235
Q10.415
median1.705
Q34.36
95-th percentile28.4185
Maximum63.1
Range63.1
Interquartile range (IQR)3.945

Descriptive statistics

Standard deviation10.606362
Coefficient of variation (CV)2.0355357
Kurtosis15.067226
Mean5.2106
Median Absolute Deviation (MAD)1.43
Skewness3.7431339
Sum521.06
Variance112.49492
MonotonicityNot monotonic
2024-04-17T06:38:19.487301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.27 9
 
9.0%
0.13 5
 
5.0%
0.0 5
 
5.0%
0.28 4
 
4.0%
1.32 2
 
2.0%
0.42 2
 
2.0%
3.08 2
 
2.0%
1.73 2
 
2.0%
0.85 1
 
1.0%
3.34 1
 
1.0%
Other values (67) 67
67.0%
ValueCountFrequency (%)
0.0 5
5.0%
0.13 5
5.0%
0.14 1
 
1.0%
0.27 9
9.0%
0.28 4
4.0%
0.4 1
 
1.0%
0.42 2
 
2.0%
0.54 1
 
1.0%
0.67 1
 
1.0%
0.68 1
 
1.0%
ValueCountFrequency (%)
63.1 1
1.0%
55.57 1
1.0%
42.59 1
1.0%
34.65 1
1.0%
34.47 1
1.0%
28.1 1
1.0%
14.42 1
1.0%
12.06 1
1.0%
11.74 1
1.0%
11.11 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15963.079
Minimum138.68
Maximum176054.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-17T06:38:19.589359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum138.68
5-th percentile589.224
Q12533.4
median6963.105
Q320031.285
95-th percentile71693.962
Maximum176054.04
Range175915.36
Interquartile range (IQR)17497.885

Descriptive statistics

Standard deviation27237.609
Coefficient of variation (CV)1.7062879
Kurtosis17.383889
Mean15963.079
Median Absolute Deviation (MAD)4925.905
Skewness3.8495268
Sum1596307.9
Variance7.4188736 × 108
MonotonicityNot monotonic
2024-04-17T06:38:19.696554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1589.29 2
 
2.0%
307.36 2
 
2.0%
4511.37 1
 
1.0%
11679.2 1
 
1.0%
38417.31 1
 
1.0%
9670.31 1
 
1.0%
8557.38 1
 
1.0%
5634.91 1
 
1.0%
4699.39 1
 
1.0%
2207.6 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
138.68 1
1.0%
277.37 1
1.0%
307.36 2
2.0%
461.05 1
1.0%
595.97 1
1.0%
644.57 1
1.0%
873.34 1
1.0%
1012.03 1
1.0%
1255.69 1
1.0%
1293.19 1
1.0%
ValueCountFrequency (%)
176054.04 1
1.0%
148711.07 1
1.0%
91384.13 1
1.0%
88289.6 1
1.0%
72541.22 1
1.0%
71649.37 1
1.0%
46079.64 1
1.0%
38417.31 1
1.0%
36803.61 1
1.0%
32150.26 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 충주 수안보 중산
 
4
충북 충주 신니 원평
 
4
충북 영동 학산 범화
 
2
충북 충주 대소원 만정
 
2
충북 음성 생극 송곡
 
2
Other values (43)
86 

Length

Max length12
Median length11
Mean length11.08
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 영동 학산 범화 2
 
2.0%
충북 충주 대소원 만정 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%
충북 단양 매포 매포 2
 
2.0%
충북 제천 봉양 구학 2
 
2.0%
Other values (38) 76
76.0%

Length

2024-04-17T06:38:19.808533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 26
 
6.5%
음성 14
 
3.5%
증평 10
 
2.5%
보은 10
 
2.5%
청주 10
 
2.5%
옥천 10
 
2.5%
진천 8
 
2.0%
신니 6
 
1.5%
영동 6
 
1.5%
Other values (83) 200
50.0%

Interactions

2024-04-17T06:38:15.815869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:10.917004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.480752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.051033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.867946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.482986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.104893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.669240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.240901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.878985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:10.975832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.538145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.112413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.928940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.544903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.170628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.728799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.301620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.942002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.028776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.590062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.170923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.987317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.604672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.225486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.789907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.359892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.008652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.101664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.649837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.231305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.049971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.671991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.286591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.859957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.422767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.079241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.170504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.716522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.293761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.112683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.741010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.349343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.924001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.498770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.150035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.235221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.787123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.611538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.194581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.808102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.414584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.990318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.564003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.218262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.293962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.850100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.671709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.276015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.876533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.475994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.052379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.625846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.281431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.352784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.923482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.735960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.351801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.941254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.537577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.110802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.687053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:16.365832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.416185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:11.985203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:12.799688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:13.414373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.024078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:14.603371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.174103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T06:38:15.748637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T06:38:19.882889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9960.0000.9960.5950.7160.8540.6680.3650.4210.4660.4200.3710.996
지점0.9961.0000.0001.0001.0000.1651.0001.0000.8520.7270.8850.7490.8411.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0730.1020.0000.0000.0610.000
측정구간0.9961.0000.0001.0001.0000.2261.0001.0000.8570.7430.8740.7470.8461.000
연장0.5951.0000.0001.0001.0000.2070.5960.5740.3670.0000.4040.0000.3541.000
측정시분0.7160.1650.0000.2260.2071.0000.0000.1080.0000.0000.0000.0000.0000.165
좌표위치위도0.8541.0000.0001.0000.5960.0001.0000.6500.6380.5830.5890.5420.6321.000
좌표위치경도0.6681.0000.0001.0000.5740.1080.6501.0000.5730.4690.6340.4530.5681.000
co0.3650.8520.0730.8570.3670.0000.6380.5731.0000.9960.9560.9381.0000.852
nox0.4210.7270.1020.7430.0000.0000.5830.4690.9961.0000.9560.9790.9960.727
hc0.4660.8850.0000.8740.4040.0000.5890.6340.9560.9561.0000.9930.9570.885
pm0.4200.7490.0000.7470.0000.0000.5420.4530.9380.9790.9931.0000.9400.749
co20.3710.8410.0610.8460.3540.0000.6320.5681.0000.9960.9570.9401.0000.841
주소0.9961.0000.0001.0001.0000.1651.0001.0000.8520.7270.8850.7490.8411.000
2024-04-17T06:38:19.989946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소방향측정구간지점측정시분
주소1.0000.0000.9911.0000.067
방향0.0001.0000.0000.0000.000
측정구간0.9910.0001.0000.9910.121
지점1.0000.0000.9911.0000.067
측정시분0.0670.0000.1210.0671.000
2024-04-17T06:38:20.323915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정시분주소
기본키1.0000.1080.133-0.0830.2390.2780.2800.2740.2470.7270.0000.7350.5360.727
연장0.1081.0000.1490.134-0.100-0.118-0.116-0.123-0.0990.7520.0000.7590.1480.752
좌표위치위도0.1330.1491.0000.3780.1700.2180.2210.2260.1650.7600.0000.7670.0000.760
좌표위치경도-0.0830.1340.3781.000-0.392-0.365-0.373-0.376-0.3930.7560.0000.7630.1000.756
co0.239-0.1000.170-0.3921.0000.9830.9890.9750.9980.4050.0720.4180.0000.405
nox0.278-0.1180.218-0.3650.9831.0000.9970.9950.9850.2850.1030.3040.0000.285
hc0.280-0.1160.221-0.3730.9890.9971.0000.9910.9880.4110.0000.4240.0000.411
pm0.274-0.1230.226-0.3760.9750.9950.9911.0000.9770.2730.0000.2920.0000.273
co20.247-0.0990.165-0.3930.9980.9850.9880.9771.0000.3960.0580.4090.0000.396
지점0.7270.7520.7600.7560.4050.2850.4110.2730.3961.0000.0000.9910.0671.000
방향0.0000.0000.0000.0000.0720.1030.0000.0000.0580.0001.0000.0000.0000.000
측정구간0.7350.7590.7670.7630.4180.3040.4240.2920.4090.9910.0001.0000.1210.991
측정시분0.5360.1480.0000.1000.0000.0000.0000.0000.0000.0670.0000.1211.0000.067
주소0.7270.7520.7600.7560.4050.2850.4110.2730.3961.0000.0000.9910.0671.000

Missing values

2024-04-17T06:38:16.494028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T06:38:16.659760image/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-충주7.320210201136.88774127.9848417.6315.481.820.854511.37충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210201136.88774127.9848415.4213.881.610.833939.29충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210201136.9979127.7223830.448.545.532.657974.22충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210201136.9979127.7223849.1551.877.72.9310634.96충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210201136.96342127.86686112.23108.6713.547.1927831.15충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210201136.96342127.86686113.396.313.395.0426056.35충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210201137.06589127.6041623.626.63.531.765593.68충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210201137.06589127.6041631.0829.914.231.737060.47충북 음성 생극 송곡
89건기연[2114-0]1오생-장호원3.620210201137.02646127.6046226.133.444.432.385895.5충북 음성 생극 병암
910건기연[2114-0]2오생-장호원3.620210201137.02646127.6046227.6735.084.72.476245.23충북 음성 생극 병암
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04011]1서충주IC-충주JCT7.720210201137.00933127.6790285.45132.4516.126.8621193.19충북 충주 신니 모남
9192건기연[04011]2서충주IC-충주JCT7.720210201137.00933127.6790275.44123.614.336.5719946.6충북 충주 신니 모남
9293건기연[04012]1충주JCT-노은JCT5.420210201137.03807127.7654998.65194.918.9911.7427700.32충북 충주 노은 문성
9394건기연[04012]2충주JCT-노은JCT5.420210201137.03807127.7654972.49156.2114.569.2821467.79충북 충주 노은 문성
9495건기연[04013]1노은JCT-동충주IC12.320210201137.05585127.8492493.32159.6217.110.7125987.72충북 충주 노은 신효
9596건기연[04013]2노은JCT-동충주IC12.320210201137.05585127.8492490.04139.2516.1310.5623398.01충북 충주 노은 신효
9697건기연[0324-1]1수안보-충주7.320210201236.88774127.984849.765.790.880.272578.8충북 충주 수안보 중산
9798건기연[0324-1]2수안보-충주7.320210201236.88774127.984849.235.510.840.272440.11충북 충주 수안보 중산
9899건기연[0325-3]1신니-신양8.820210201236.9979127.7223820.5823.63.61.264621.23충북 충주 신니 원평
99100건기연[0325-3]2신니-신양8.820210201236.9979127.7223835.1535.965.712.017541.9충북 충주 신니 원평