Overview

Dataset statistics

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

Variable types

Numeric9
Categorical7

Alerts

도로종류 has constant value ""Constant
측정일 has constant value ""Constant
지점 is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
측정구간 is highly overall correlated with 기본키 and 5 other fieldsHigh correlation
주소 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
co has unique valuesUnique
nox has unique valuesUnique
co2 has unique valuesUnique
pm has 2 (2.0%) zerosZeros

Reproduction

Analysis started2023-12-10 10:37:25.971991
Analysis finished2023-12-10 10:37:43.824891
Duration17.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:43.991902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T19:37:44.301720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

도로종류
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건기연 100
100.0%

Length

2023-12-10T19:37:44.551045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:37:44.711775image/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
[1916-5]
 
2
[0325-4]
 
2
[0326-2]
 
2
Other values (43)
86 

Length

Max length9
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%
[1916-5] 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%
[1721-0] 2
 
2.0%
Other values (38) 76
76.0%

Length

2023-12-10T19:37:44.886952image/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%
3810-1 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%
3711-1 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

2023-12-10T19:37:45.154020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:37:45.335160image/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
남일-가덕
 
2
영동-영동IC
 
2
Other values (42)
84 

Length

Max length13
Median length5
Mean length6.5
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%
남일-가덕 2
 
2.0%
영동-영동IC 2
 
2.0%
입장-진천 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

2023-12-10T19:37:45.560789image/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%
서충주ic-충주jct 2
 
2.0%
보은-장갑 2
 
2.0%
충주jct-노은jct 2
 
2.0%
충주jct-감곡ic 2
 
2.0%
장락-쌍용 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 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%
Mean8.122
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:45.818267image/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 deviation4.3793496
Coefficient of variation (CV)0.53919596
Kurtosis0.61512548
Mean8.122
Median Absolute Deviation (MAD)3.65
Skewness0.7433807
Sum812.2
Variance19.178703
MonotonicityNot monotonic
2023-12-10T19:37:46.052629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7.3 10
 
10.0%
3.4 4
 
4.0%
8.8 4
 
4.0%
11.1 4
 
4.0%
12.3 4
 
4.0%
5.4 4
 
4.0%
3.6 4
 
4.0%
12.1 2
 
2.0%
7.5 2
 
2.0%
14.5 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
20210501
100 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210501
2nd row20210501
3rd row20210501
4th row20210501
5th row20210501

Common Values

ValueCountFrequency (%)
20210501 100
100.0%

Length

2023-12-10T19:37:46.317111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:37:46.524157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210501 100
100.0%

측정시분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
96 
15
 
4

Length

Max length2
Median length1
Mean length1.04
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 96
96.0%
15 4
 
4.0%

Length

2023-12-10T19:37:46.744774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:37:46.928871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 96
96.0%
15 4
 
4.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.801425
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:47.134061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.62606
median36.89448
Q337.02646
95-th percentile37.11937
Maximum37.19998
Range1.09471
Interquartile range (IQR)0.4004

Descriptive statistics

Standard deviation0.28491161
Coefficient of variation (CV)0.0077418635
Kurtosis-0.37552805
Mean36.801425
Median Absolute Deviation (MAD)0.147065
Skewness-0.85507179
Sum3680.1425
Variance0.081174623
MonotonicityNot monotonic
2023-12-10T19:37:47.413235image/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%
37.19998 2
 
2.0%
37.18469 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%
36.35443 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 (%)
37.19998 2
2.0%
37.18469 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%
37.05389 2
2.0%
37.04502 2
2.0%
37.03807 2
2.0%

좌표위치경도
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.72886
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:47.680462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.44767
Q1127.57716
median127.68539
Q3127.84924
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.27208

Descriptive statistics

Standard deviation0.22462837
Coefficient of variation (CV)0.0017586344
Kurtosis1.1999403
Mean127.72886
Median Absolute Deviation (MAD)0.12342
Skewness1.0822727
Sum12772.886
Variance0.050457906
MonotonicityNot monotonic
2023-12-10T19:37:47.959362image/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%
127.61191 2
 
2.0%
128.27212 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%
127.59919 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%
128.10947 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%
127.8901 2
2.0%

co
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.7963
Minimum2.6
Maximum1078.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:48.247774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile4.6255
Q118.185
median59.59
Q3118.575
95-th percentile492.117
Maximum1078.46
Range1075.86
Interquartile range (IQR)100.39

Descriptive statistics

Standard deviation180.35702
Coefficient of variation (CV)1.5711048
Kurtosis12.097662
Mean114.7963
Median Absolute Deviation (MAD)44.005
Skewness3.2903255
Sum11479.63
Variance32528.655
MonotonicityNot monotonic
2023-12-10T19:37:48.524891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.65 1
 
1.0%
9.17 1
 
1.0%
314.83 1
 
1.0%
10.47 1
 
1.0%
15.62 1
 
1.0%
127.02 1
 
1.0%
66.15 1
 
1.0%
41.58 1
 
1.0%
63.11 1
 
1.0%
28.78 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
2.6 1
1.0%
2.63 1
1.0%
2.92 1
1.0%
3.31 1
1.0%
4.54 1
1.0%
4.63 1
1.0%
6.45 1
1.0%
6.93 1
1.0%
7.82 1
1.0%
8.61 1
1.0%
ValueCountFrequency (%)
1078.46 1
1.0%
820.89 1
1.0%
791.81 1
1.0%
701.18 1
1.0%
523.03 1
1.0%
490.49 1
1.0%
320.68 1
1.0%
319.89 1
1.0%
314.83 1
1.0%
279.18 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.2926
Minimum1.28
Maximum1914.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:49.215366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.28
5-th percentile2.6775
Q112.335
median47.525
Q3121.0775
95-th percentile592.804
Maximum1914.44
Range1913.16
Interquartile range (IQR)108.7425

Descriptive statistics

Standard deviation293.32854
Coefficient of variation (CV)1.978039
Kurtosis17.848558
Mean148.2926
Median Absolute Deviation (MAD)38.89
Skewness3.8651814
Sum14829.26
Variance86041.635
MonotonicityNot monotonic
2023-12-10T19:37:49.492378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.42 1
 
1.0%
4.94 1
 
1.0%
624.99 1
 
1.0%
5.59 1
 
1.0%
9.02 1
 
1.0%
157.62 1
 
1.0%
54.18 1
 
1.0%
28.46 1
 
1.0%
46.72 1
 
1.0%
22.71 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1.28 1
1.0%
1.64 1
1.0%
2.0 1
1.0%
2.06 1
1.0%
2.25 1
1.0%
2.7 1
1.0%
3.72 1
1.0%
3.95 1
1.0%
4.21 1
1.0%
4.94 1
1.0%
ValueCountFrequency (%)
1914.44 1
1.0%
1548.09 1
1.0%
949.98 1
1.0%
870.68 1
1.0%
624.99 1
1.0%
591.11 1
1.0%
531.66 1
1.0%
526.32 1
1.0%
494.74 1
1.0%
447.15 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.3722
Minimum0.23
Maximum201.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:49.763631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.23
5-th percentile0.4385
Q11.97
median7.365
Q314.93
95-th percentile67.973
Maximum201.13
Range200.9
Interquartile range (IQR)12.96

Descriptive statistics

Standard deviation31.126829
Coefficient of variation (CV)1.7917609
Kurtosis15.83035
Mean17.3722
Median Absolute Deviation (MAD)6.13
Skewness3.6493471
Sum1737.22
Variance968.87951
MonotonicityNot monotonic
2023-12-10T19:37:50.149140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.0 2
 
2.0%
1.14 2
 
2.0%
0.73 1
 
1.0%
62.83 1
 
1.0%
0.97 1
 
1.0%
1.38 1
 
1.0%
17.93 1
 
1.0%
7.77 1
 
1.0%
4.29 1
 
1.0%
7.59 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
0.23 1
1.0%
0.26 1
1.0%
0.27 1
1.0%
0.31 1
1.0%
0.41 1
1.0%
0.44 1
1.0%
0.57 1
1.0%
0.61 1
1.0%
0.73 1
1.0%
0.83 1
1.0%
ValueCountFrequency (%)
201.13 1
1.0%
153.51 1
1.0%
112.96 1
1.0%
105.53 1
1.0%
69.74 1
1.0%
67.88 1
1.0%
62.83 1
1.0%
55.38 1
1.0%
51.6 1
1.0%
49.78 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct83
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.105
Minimum0
Maximum111.88
Zeros2
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:50.486640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13
Q10.6675
median2.465
Q36.8675
95-th percentile32.7175
Maximum111.88
Range111.88
Interquartile range (IQR)6.2

Descriptive statistics

Standard deviation16.528755
Coefficient of variation (CV)2.0393282
Kurtosis21.114864
Mean8.105
Median Absolute Deviation (MAD)2.11
Skewness4.1859549
Sum810.5
Variance273.19974
MonotonicityNot monotonic
2023-12-10T19:37:50.756551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.13 5
 
5.0%
0.14 5
 
5.0%
0.27 3
 
3.0%
0.42 2
 
2.0%
0.28 2
 
2.0%
1.2 2
 
2.0%
1.91 2
 
2.0%
1.56 2
 
2.0%
0.0 2
 
2.0%
0.54 2
 
2.0%
Other values (73) 73
73.0%
ValueCountFrequency (%)
0.0 2
 
2.0%
0.13 5
5.0%
0.14 5
5.0%
0.27 3
3.0%
0.28 2
 
2.0%
0.4 1
 
1.0%
0.42 2
 
2.0%
0.52 1
 
1.0%
0.54 2
 
2.0%
0.56 1
 
1.0%
ValueCountFrequency (%)
111.88 1
1.0%
90.98 1
1.0%
45.03 1
1.0%
41.87 1
1.0%
39.51 1
1.0%
32.36 1
1.0%
27.33 1
1.0%
26.09 1
1.0%
25.38 1
1.0%
23.79 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30298.626
Minimum614.73
Maximum291242
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:37:51.039929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum614.73
5-th percentile1106.0465
Q14838.685
median13807.995
Q329804.085
95-th percentile126887.41
Maximum291242
Range290627.27
Interquartile range (IQR)24965.4

Descriptive statistics

Standard deviation49590.209
Coefficient of variation (CV)1.6367148
Kurtosis12.179827
Mean30298.626
Median Absolute Deviation (MAD)10417.98
Skewness3.3146041
Sum3029862.6
Variance2.4591888 × 109
MonotonicityNot monotonic
2023-12-10T19:37:51.390920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3740.84 1
 
1.0%
2183.42 1
 
1.0%
92106.56 1
 
1.0%
2490.78 1
 
1.0%
4115.6 1
 
1.0%
34204.75 1
 
1.0%
16617.85 1
 
1.0%
10801.07 1
 
1.0%
14753.98 1
 
1.0%
7249.28 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
614.73 1
1.0%
640.96 1
1.0%
821.31 1
1.0%
873.34 1
1.0%
1075.77 1
1.0%
1107.64 1
1.0%
1705.45 1
1.0%
1847.75 1
1.0%
1870.42 1
1.0%
2061.6 1
1.0%
ValueCountFrequency (%)
291242.0 1
1.0%
243724.6 1
1.0%
210490.86 1
1.0%
180421.88 1
1.0%
145849.85 1
1.0%
125889.39 1
1.0%
92962.4 1
1.0%
92106.56 1
1.0%
87614.72 1
1.0%
77118.66 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 용산 율
 
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 용산 율 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 청주 오창 가곡 2
 
2.0%
Other values (38) 76
76.0%

Length

2023-12-10T19:37:51.692814image/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%
증평 10
 
2.5%
청주 10
 
2.5%
옥천 10
 
2.5%
보은 10
 
2.5%
진천 8
 
2.0%
노은 6
 
1.5%
중산 6
 
1.5%
Other values (81) 196
49.0%

Interactions

2023-12-10T19:37:41.743813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:27.710988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:29.759216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:31.662779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.261435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:34.996533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:36.811254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.420066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.957960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:41.891031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:27.857104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:29.902726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:31.835176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.444159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:35.152916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:36.979022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.585613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:40.504243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.061535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:28.025408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:30.031618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:31.984092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.623061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:35.308452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:37.147637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.739129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:40.649046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.262143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:28.210787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:30.213868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:32.153384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.776863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:35.482249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:37.312469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.910481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:40.800332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.427987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:28.392603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:30.418222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:32.332049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.978315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:35.721095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:37.489119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.095020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:40.941161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.583534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:28.564146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:30.573381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:32.555117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:34.166661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:35.881387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:37.678773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.244534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:41.086691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.754437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:28.750116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:30.739722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:32.728060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:34.343057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:36.083157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:37.866920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.429221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:41.240538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:42.951486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:29.404102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:31.085882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:32.907624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:34.642257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:36.427424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.053343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.624322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:41.406796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:43.101359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:29.581831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:31.393126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:33.100203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:34.818799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:36.636653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:38.227132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:39.791588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:37:41.581022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:37:51.930207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9960.0000.9960.6100.7160.7980.6580.5290.4670.4770.4010.4820.996
지점0.9961.0000.0001.0001.0000.1651.0001.0000.8340.8000.8310.7730.7831.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0660.0000.0000.1120.1080.000
측정구간0.9961.0000.0001.0001.0000.2261.0001.0000.8400.8080.8370.7850.7961.000
연장0.6101.0000.0001.0001.0000.2760.6810.5300.3180.0000.3800.1790.2771.000
측정시분0.7160.1650.0000.2260.2761.0000.0000.1080.0000.0000.0000.0000.0000.165
좌표위치위도0.7981.0000.0001.0000.6810.0001.0000.6190.5880.3770.4500.3820.5131.000
좌표위치경도0.6581.0000.0001.0000.5300.1080.6191.0000.1960.0000.0000.0000.0001.000
co0.5290.8340.0660.8400.3180.0000.5880.1961.0000.9700.9820.9750.9810.834
nox0.4670.8000.0000.8080.0000.0000.3770.0000.9701.0000.9980.9940.9360.800
hc0.4770.8310.0000.8370.3800.0000.4500.0000.9820.9981.0000.9940.9580.831
pm0.4010.7730.1120.7850.1790.0000.3820.0000.9750.9940.9941.0000.9540.773
co20.4820.7830.1080.7960.2770.0000.5130.0000.9810.9360.9580.9541.0000.783
주소0.9961.0000.0001.0001.0000.1651.0001.0000.8340.8000.8310.7730.7831.000
2023-12-10T19:37:52.270846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지점측정구간방향주소측정시분
지점1.0000.9910.0001.0000.067
측정구간0.9911.0000.0000.9910.121
방향0.0000.0001.0000.0000.000
주소1.0000.9910.0001.0000.067
측정시분0.0670.1210.0000.0671.000
2023-12-10T19:37:52.471798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정시분주소
기본키1.0000.2000.257-0.0540.3600.3670.3730.3570.3750.7270.0000.7350.5360.727
연장0.2001.0000.1900.0850.0850.0810.0820.0480.0910.7520.0000.7590.1990.752
좌표위치위도0.2570.1901.0000.3120.2790.3200.3190.3070.2830.7600.0000.7670.0000.760
좌표위치경도-0.0540.0850.3121.000-0.416-0.411-0.400-0.440-0.4090.7560.0000.7630.1000.756
co0.3600.0850.279-0.4161.0000.9870.9920.9650.9990.3840.0640.3970.0000.384
nox0.3670.0810.320-0.4110.9871.0000.9970.9890.9870.3480.0000.3630.0000.348
hc0.3730.0820.319-0.4000.9920.9971.0000.9810.9910.3800.0000.3930.0000.380
pm0.3570.0480.307-0.4400.9650.9890.9811.0000.9660.3230.1140.3400.0000.323
co20.3750.0910.283-0.4090.9990.9870.9910.9661.0000.3140.1010.3310.0000.314
지점0.7270.7520.7600.7560.3840.3480.3800.3230.3141.0000.0000.9910.0671.000
방향0.0000.0000.0000.0000.0640.0000.0000.1140.1010.0001.0000.0000.0000.000
측정구간0.7350.7590.7670.7630.3970.3630.3930.3400.3310.9910.0001.0000.1210.991
측정시분0.5360.1990.0000.1000.0000.0000.0000.0000.0000.0670.0000.1211.0000.067
주소0.7270.7520.7600.7560.3840.3480.3800.3230.3141.0000.0000.9910.0671.000

Missing values

2023-12-10T19:37:43.338178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:37:43.693452image/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-충주7.320210501036.88774127.9848415.658.421.450.273740.84충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210501036.88774127.9848422.6613.242.020.545989.7충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210501036.9979127.7223864.9657.379.172.9314482.44충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210501036.9979127.7223873.8453.258.712.7417088.27충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210501036.96342127.86686128.2698.7114.186.5430339.0충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210501036.96342127.86686160.51141.4717.928.3640553.65충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210501037.06589127.6041647.1752.377.333.3710996.71충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210501037.06589127.6041648.4460.48.624.1611007.15충북 음성 생극 송곡
89건기연[2114-0]1오생-장호원3.620210501037.02646127.6046226.5125.743.282.036599.51충북 음성 생극 병암
910건기연[2114-0]2오생-장호원3.620210501037.02646127.6046242.5243.445.942.9210226.62충북 음성 생극 병암
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04013]1노은JCT-동충주IC12.320210501037.05585127.84924214.07447.1548.7825.3856634.4충북 충주 노은 신효
9192건기연[04013]2노은JCT-동충주IC12.320210501037.05585127.84924131.63276.3628.2415.8438998.33충북 충주 노은 신효
9293건기연[04510-1]1충주JCT-감곡IC12.120210501037.05389127.72826701.18870.68105.5341.87180421.88충북 충주 노은 연하
9394건기연[04510-1]2충주JCT-감곡IC12.120210501037.05389127.72826490.49526.3267.8823.79125889.39충북 충주 노은 연하
9495건기연[04511]1감곡IC-여주JCT14.520210501037.19998127.61191791.81949.98112.9645.03210490.86충북 음성 감곡 상우
9596건기연[04511]2감곡IC-여주JCT14.520210501037.19998127.61191523.03591.1169.7427.33145849.85충북 음성 감곡 상우
9697건기연[0324-1]1수안보-충주7.3202105011536.88774127.9848412.97.451.140.273410.91충북 충주 수안보 중산
9798건기연[0324-1]2수안보-충주7.3202105011536.88774127.9848416.9210.361.420.44862.92충북 충주 수안보 중산
9899건기연[0325-3]1신니-신양8.8202105011536.9979127.7223858.4350.428.052.6713133.55충북 충주 신니 원평
99100건기연[0325-3]2신니-신양8.8202105011536.9979127.7223886.0752.339.82.3517944.07충북 충주 신니 원평