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 5 other fieldsHigh correlation
지점 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 pm and 4 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 4 other fieldsHigh correlation
hc is highly overall correlated with co and 4 other fieldsHigh correlation
pm is highly overall correlated with 기본키 and 4 other fieldsHigh correlation
co2 is highly overall correlated with co and 3 other fieldsHigh correlation
측정일 is highly overall correlated with 기본키 and 3 other fieldsHigh correlation
측정일 is highly imbalanced (53.1%)Imbalance
기본키 has unique valuesUnique
co has unique valuesUnique
nox has unique valuesUnique
pm has unique valuesUnique
co2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:36:47.276171
Analysis finished2023-12-10 12:36:59.982967
Duration12.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기본키
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:00.116074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2023-12-10T21:37:00.466758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

도로종류
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건기연 100
100.0%

Length

2023-12-10T21:37:00.746506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:00.922220image/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 length7.82
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%
[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

2023-12-10T21:37:01.117234image/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%
3808-1 2
 
2.0%
3810-1 2
 
2.0%
3609-0 2
 
2.0%
3609-1 2
 
2.0%
3613-0 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

2023-12-10T21:37:01.361258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:01.529057image/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 length6.3
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%
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

2023-12-10T21:37:01.697483image/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%
목계-산척 2
 
2.0%
장락-쌍용 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 2
 
2.0%
내사-덕산 2
 
2.0%
Other values (35) 70
70.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.006
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:01.899335image/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 deviation4.3324666
Coefficient of variation (CV)0.54115246
Kurtosis0.8775139
Mean8.006
Median Absolute Deviation (MAD)3.45
Skewness0.8547409
Sum800.6
Variance18.770267
MonotonicityNot monotonic
2023-12-10T21:37:02.121386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
7.3 10
 
10.0%
5.4 6
 
6.0%
5.0 4
 
4.0%
15.5 4
 
4.0%
12.3 4
 
4.0%
8.8 4
 
4.0%
11.1 4
 
4.0%
3.4 4
 
4.0%
11.0 2
 
2.0%
6.4 2
 
2.0%
Other values (28) 56
56.0%
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%
14.4 2
2.0%
13.9 2
2.0%
12.3 4
4.0%
12.1 2
2.0%
11.4 2
2.0%
11.2 2
2.0%
11.1 4
4.0%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210301
90 
20210302
10 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210301
2nd row20210301
3rd row20210301
4th row20210301
5th row20210301

Common Values

ValueCountFrequency (%)
20210301 90
90.0%
20210302 10
 
10.0%

Length

2023-12-10T21:37:02.307031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:02.441058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210301 90
90.0%
20210302 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

2023-12-10T21:37:02.596943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:02.724500image/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%
Mean36.787524
Minimum36.10527
Maximum37.18469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:02.902953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.56286
median36.88855
Q337.01554
95-th percentile37.11937
Maximum37.18469
Range1.07942
Interquartile range (IQR)0.45268

Descriptive statistics

Standard deviation0.28988921
Coefficient of variation (CV)0.0078800958
Kurtosis-0.61250519
Mean36.787524
Median Absolute Deviation (MAD)0.16076
Skewness-0.77382015
Sum3678.7524
Variance0.084035754
MonotonicityNot monotonic
2023-12-10T21:37:03.133402image/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%
37.03359 2
 
2.0%
36.7235 2
 
2.0%
36.83418 2
 
2.0%
36.91571 2
 
2.0%
36.35443 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 (%)
37.18469 2
2.0%
37.15606 2
2.0%
37.11937 2
2.0%
37.1091 2
2.0%
37.07857 2
2.0%
37.06589 4
4.0%
37.05585 2
2.0%
37.04502 2
2.0%
37.03807 2
2.0%
37.03413 2
2.0%

좌표위치경도
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73901
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:03.374859image/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 deviation0.23284901
Coefficient of variation (CV)0.0018228496
Kurtosis0.62238937
Mean127.73901
Median Absolute Deviation (MAD)0.14858
Skewness0.92824934
Sum12773.901
Variance0.054218663
MonotonicityNot monotonic
2023-12-10T21:37:03.585099image/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%
128.39227 2
 
2.0%
127.55372 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
127.59919 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%
Mean3835.0601
Minimum454.62
Maximum23507.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:03.795094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum454.62
5-th percentile514.0875
Q11521.76
median2914.605
Q35433.2625
95-th percentile9693.3475
Maximum23507.31
Range23052.69
Interquartile range (IQR)3911.5025

Descriptive statistics

Standard deviation3537.4009
Coefficient of variation (CV)0.92238473
Kurtosis10.541861
Mean3835.0601
Median Absolute Deviation (MAD)1921.17
Skewness2.5772945
Sum383506.01
Variance12513205
MonotonicityNot monotonic
2023-12-10T21:37:04.373263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1659.96 1
 
1.0%
2180.13 1
 
1.0%
8593.26 1
 
1.0%
8274.58 1
 
1.0%
7645.55 1
 
1.0%
607.41 1
 
1.0%
526.36 1
 
1.0%
7623.62 1
 
1.0%
5399.85 1
 
1.0%
3080.54 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
454.62 1
1.0%
455.61 1
1.0%
460.72 1
1.0%
475.68 1
1.0%
482.88 1
1.0%
515.73 1
1.0%
526.36 1
1.0%
607.41 1
1.0%
635.33 1
1.0%
641.79 1
1.0%
ValueCountFrequency (%)
23507.31 1
1.0%
17737.49 1
1.0%
10712.41 1
1.0%
10628.73 1
1.0%
9993.69 1
1.0%
9677.54 1
1.0%
8593.26 1
1.0%
8325.61 1
1.0%
8274.58 1
1.0%
7645.55 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4346.1526
Minimum340.28
Maximum31158.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:04.644692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum340.28
5-th percentile413.6595
Q11090.9725
median2516.325
Q35414.8625
95-th percentile13771.823
Maximum31158.64
Range30818.36
Interquartile range (IQR)4323.89

Descriptive statistics

Standard deviation5250.7964
Coefficient of variation (CV)1.2081482
Kurtosis9.9447441
Mean4346.1526
Median Absolute Deviation (MAD)1818.09
Skewness2.7738953
Sum434615.26
Variance27570863
MonotonicityNot monotonic
2023-12-10T21:37:04.869547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1347.18 1
 
1.0%
1957.14 1
 
1.0%
12968.83 1
 
1.0%
13750.86 1
 
1.0%
14170.12 1
 
1.0%
548.4 1
 
1.0%
476.33 1
 
1.0%
7984.18 1
 
1.0%
5672.79 1
 
1.0%
3024.64 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
340.28 1
1.0%
360.04 1
1.0%
382.52 1
1.0%
399.86 1
1.0%
407.38 1
1.0%
413.99 1
1.0%
476.33 1
1.0%
531.49 1
1.0%
548.4 1
1.0%
553.42 1
1.0%
ValueCountFrequency (%)
31158.64 1
1.0%
28227.64 1
1.0%
16195.99 1
1.0%
15679.93 1
1.0%
14170.12 1
1.0%
13750.86 1
1.0%
13346.49 1
1.0%
12968.83 1
1.0%
12297.63 1
1.0%
11048.83 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean508.7137
Minimum44.54
Maximum3176.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:05.121664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44.54
5-th percentile56.798
Q1151.895
median335.27
Q3685.605
95-th percentile1360.255
Maximum3176.69
Range3132.15
Interquartile range (IQR)533.71

Descriptive statistics

Standard deviation544.80745
Coefficient of variation (CV)1.070951
Kurtosis7.4468805
Mean508.7137
Median Absolute Deviation (MAD)233.78
Skewness2.3935878
Sum50871.37
Variance296815.16
MonotonicityNot monotonic
2023-12-10T21:37:05.312354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57.01 2
 
2.0%
171.4 1
 
1.0%
71.91 1
 
1.0%
1354.39 1
 
1.0%
1247.78 1
 
1.0%
1190.45 1
 
1.0%
64.88 1
 
1.0%
952.55 1
 
1.0%
711.36 1
 
1.0%
357.72 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
44.54 1
1.0%
48.28 1
1.0%
48.91 1
1.0%
52.0 1
1.0%
52.77 1
1.0%
57.01 2
2.0%
64.88 1
1.0%
65.2 1
1.0%
71.91 1
1.0%
74.29 1
1.0%
ValueCountFrequency (%)
3176.69 1
1.0%
2674.6 1
1.0%
2026.46 1
1.0%
1914.59 1
1.0%
1471.69 1
1.0%
1354.39 1
1.0%
1352.56 1
1.0%
1330.91 1
1.0%
1318.37 1
1.0%
1247.78 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean253.4833
Minimum11.93
Maximum1662.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:05.508442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.93
5-th percentile26.323
Q158.5425
median128.78
Q3282.415
95-th percentile993.8355
Maximum1662.94
Range1651.01
Interquartile range (IQR)223.8725

Descriptive statistics

Standard deviation319.91996
Coefficient of variation (CV)1.2620948
Kurtosis6.8803858
Mean253.4833
Median Absolute Deviation (MAD)88.355
Skewness2.4810853
Sum25348.33
Variance102348.78
MonotonicityNot monotonic
2023-12-10T21:37:05.680763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
66.92 1
 
1.0%
101.25 1
 
1.0%
671.24 1
 
1.0%
992.49 1
 
1.0%
1019.4 1
 
1.0%
40.58 1
 
1.0%
27.8 1
 
1.0%
404.56 1
 
1.0%
306.43 1
 
1.0%
168.31 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
11.93 1
1.0%
20.54 1
1.0%
22.78 1
1.0%
23.32 1
1.0%
24.1 1
1.0%
26.44 1
1.0%
26.73 1
1.0%
27.8 1
1.0%
28.93 1
1.0%
29.87 1
1.0%
ValueCountFrequency (%)
1662.94 1
1.0%
1632.08 1
1.0%
1158.49 1
1.0%
1086.34 1
1.0%
1019.4 1
1.0%
992.49 1
1.0%
845.53 1
1.0%
728.81 1
1.0%
701.16 1
1.0%
671.24 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean999727.68
Minimum113274.36
Maximum6246718.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:05.881858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113274.36
5-th percentile133385.41
Q1396884.53
median764607.3
Q31414892.7
95-th percentile2373558.9
Maximum6246718.9
Range6133444.6
Interquartile range (IQR)1018008.2

Descriptive statistics

Standard deviation939334.01
Coefficient of variation (CV)0.93958988
Kurtosis11.323422
Mean999727.68
Median Absolute Deviation (MAD)509007.98
Skewness2.6858564
Sum99972768
Variance8.8234838 × 1011
MonotonicityNot monotonic
2023-12-10T21:37:06.154512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
426691.49 1
 
1.0%
513068.26 1
 
1.0%
2368011.56 1
 
1.0%
2280705.2 1
 
1.0%
2190697.63 1
 
1.0%
155878.37 1
 
1.0%
134213.04 1
 
1.0%
1923878.0 1
 
1.0%
1376686.34 1
 
1.0%
831540.59 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
113274.36 1
1.0%
117014.33 1
1.0%
118498.16 1
1.0%
124019.29 1
1.0%
124160.37 1
1.0%
133870.94 1
1.0%
134213.04 1
1.0%
155878.37 1
1.0%
157766.53 1
1.0%
163939.84 1
1.0%
ValueCountFrequency (%)
6246718.92 1
1.0%
4940350.34 1
1.0%
2650397.21 1
1.0%
2489316.2 1
1.0%
2478958.14 1
1.0%
2368011.56 1
1.0%
2287659.56 1
1.0%
2281427.96 1
1.0%
2280705.2 1
1.0%
2190697.63 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

2023-12-10T21:37:06.344591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 28
 
7.0%
옥천 12
 
3.0%
음성 10
 
2.5%
증평 10
 
2.5%
청주 10
 
2.5%
보은 10
 
2.5%
진천 8
 
2.0%
신니 6
 
1.5%
영동 6
 
1.5%
Other values (79) 200
50.0%

Interactions

2023-12-10T21:36:58.200091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:48.444494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.558988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.711826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.988429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.229490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.271204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:55.490267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.994132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.337055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:48.565426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.696103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.868316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.113034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.341610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.390787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:55.601719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.117175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.470784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:48.678838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.808021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.014430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.245743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.443080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.493667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:55.713223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.233624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.598381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:48.797962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.954343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.159655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.389419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.567588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.593745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.165618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.375136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.738218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:48.922906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.082877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.298969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.533589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.683447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.746232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.317159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.518548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.856292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.041537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.205360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.430805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.662278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.801514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.864477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.435709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.640275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.979224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.169510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.325965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.582646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.815262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.906673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.988800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.580073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.778589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:59.102836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.301769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.453158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.703456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:52.972591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.026764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:55.165274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.707851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:57.906807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:59.239649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:49.424463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:50.586252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:51.842002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:53.101193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:54.150166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:55.364809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:56.848567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:58.041131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:37:06.504775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정일좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9900.0000.9900.5401.0000.8250.6520.6370.6690.5440.5750.5460.990
지점0.9901.0000.0001.0001.0000.1071.0001.0000.9030.8960.7970.8400.8551.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9901.0000.0001.0001.0000.1071.0001.0000.9030.8960.7970.8400.8551.000
연장0.5401.0000.0001.0001.0000.2310.6440.5690.3850.2210.0850.4320.1901.000
측정일1.0000.1070.0000.1070.2311.0000.2280.0000.5500.5500.5830.6620.3550.107
좌표위치위도0.8251.0000.0001.0000.6440.2281.0000.6700.6020.5900.3850.4280.5381.000
좌표위치경도0.6521.0000.0001.0000.5690.0000.6701.0000.4610.3550.3130.3270.4581.000
co0.6370.9030.0000.9030.3850.5500.6020.4611.0000.9600.9220.8250.9960.903
nox0.6690.8960.0000.8960.2210.5500.5900.3550.9601.0000.9240.9000.9610.896
hc0.5440.7970.0000.7970.0850.5830.3850.3130.9220.9241.0000.8960.9160.797
pm0.5750.8400.0000.8400.4320.6620.4280.3270.8250.9000.8961.0000.8600.840
co20.5460.8550.0000.8550.1900.3550.5380.4580.9960.9610.9160.8601.0000.855
주소0.9901.0000.0001.0001.0000.1071.0001.0000.9030.8960.7970.8400.8551.000
2023-12-10T21:37:06.774373image/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
2023-12-10T21:37:06.976144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정일주소
기본키1.0000.0650.155-0.1330.4520.4950.4920.5240.4580.6990.0000.6990.9580.699
연장0.0651.0000.0980.075-0.087-0.100-0.103-0.121-0.0880.7730.0000.7730.1660.773
좌표위치위도0.1550.0981.0000.4010.1820.2280.2260.2450.1790.7820.0000.7820.1650.782
좌표위치경도-0.1330.0750.4011.000-0.440-0.369-0.387-0.350-0.4440.7770.0000.7770.0000.777
co0.452-0.0870.182-0.4401.0000.9790.9860.9540.9980.4980.0000.4980.5760.498
nox0.495-0.1000.228-0.3690.9791.0000.9960.9870.9790.4860.0000.4860.5760.486
hc0.492-0.1030.226-0.3870.9860.9961.0000.9800.9850.3100.0000.3100.5650.310
pm0.524-0.1210.245-0.3500.9540.9870.9801.0000.9540.3920.0000.3920.4870.392
co20.458-0.0880.179-0.4440.9980.9790.9850.9541.0000.4290.0000.4290.3710.429
지점0.6990.7730.7820.7770.4980.4860.3100.3920.4291.0000.0001.0000.0001.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.6990.7730.7820.7770.4980.4860.3100.3920.4291.0000.0001.0000.0001.000
측정일0.9580.1660.1650.0000.5760.5760.5650.4870.3710.0000.0000.0001.0000.000
주소0.6990.7730.7820.7770.4980.4860.3100.3920.4291.0000.0001.0000.0001.000

Missing values

2023-12-10T21:36:59.471822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:59.815102image/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-충주7.320210301036.88774127.984841659.961347.18171.466.92426691.49충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210301036.88774127.984841579.771365.38169.580.96404185.28충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210301036.9979127.722382596.462044.2287.24113.93664364.42충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210301036.9979127.722382622.452505.28345.27127.91641582.87충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210301036.96342127.866866406.675896.2721.5376.011631972.86충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210301036.96342127.866865533.54861.12609.26216.41396956.07충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210301037.06589127.604164046.483774.87492.1245.921026718.57충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210301037.06589127.604164370.584155.95529.28268.041106346.35충북 음성 생극 송곡
89건기연[0406-1]1대전-옥천15.520210301036.3326127.531393244.972420.09316.82109.71842487.64충북 옥천 군북 이백
910건기연[0406-1]2대전-옥천15.520210301036.3326127.531393574.12554.23344.58108.04927124.12충북 옥천 군북 이백
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[0324-1]1수안보-충주7.320210302036.88774127.984842320.862575.24336.6171.36558897.45충북 충주 수안보 중산
9192건기연[0324-1]2수안보-충주7.320210302036.88774127.984842540.243591.72402.42241.64652266.99충북 충주 수안보 중산
9293건기연[0325-3]1신니-신양8.820210302036.9979127.722385932.648570.71054.22596.041468702.67충북 충주 신니 원평
9394건기연[0325-3]2신니-신양8.820210302036.9979127.722386600.4911048.831318.37728.811617964.38충북 충주 신니 원평
9495건기연[0325-4]1주덕-충주5.020210302036.96342127.8668610712.4112297.631471.69845.532650397.21충북 충주 대소원 만정
9596건기연[0325-4]2주덕-충주5.020210302036.96342127.866869993.6910716.041330.91646.872478958.14충북 충주 대소원 만정
9697건기연[0326-2]1오생-장호원5.420210302037.06589127.604169677.5415679.931914.591086.342281427.96충북 음성 생극 송곡
9798건기연[0326-2]2오생-장호원5.420210302037.06589127.6041610628.7316195.992026.461158.492489316.2충북 음성 생극 송곡
9899건기연[0406-1]1대전-옥천15.520210302036.3326127.531394123.143352.7441.31204.061057794.4충북 옥천 군북 이백
99100건기연[0406-1]2대전-옥천15.520210302036.3326127.531394257.893378.5452.72201.051093777.42충북 옥천 군북 이백