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 6 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 6 other fieldsHigh correlation
기본키 is highly overall correlated with 지점 and 3 other fieldsHigh correlation
연장 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치위도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
좌표위치경도 is highly overall correlated with 지점 and 2 other fieldsHigh correlation
co is highly overall correlated with nox and 6 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
측정일 is highly overall correlated with 기본키High correlation
측정일 is highly imbalanced (53.1%)Imbalance
기본키 has unique valuesUnique
co has unique valuesUnique
nox has unique valuesUnique
hc has unique valuesUnique
pm has unique valuesUnique
co2 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:37:33.091862
Analysis finished2023-12-10 12:37:45.951384
Duration12.86 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
2023-12-10T21:37:46.082046image/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
2023-12-10T21:37:46.303320image/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

2023-12-10T21:37:46.490187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:46.599463image/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 length7.86
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%
[1916-5] 2
 
2.0%
[0408-1] 2
 
2.0%
[0521-1] 2
 
2.0%
[0524-4] 2
 
2.0%
[1720-1] 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:37:46.723835image/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%
3713-1 2
 
2.0%
3806-0 2
 
2.0%
3412-1 2
 
2.0%
3609-0 2
 
2.0%
3609-1 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

2023-12-10T21:37:46.872252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:47.008313image/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 length6.12
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%
영동-영동IC 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
제천-신림 2
 
2.0%
현도-남이 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:37:47.159442image/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%
괴산-음성 2
 
2.0%
일죽-감곡ic 2
 
2.0%
증평-대사 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 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%
Mean7.848
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:47.326189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.6
median7.3
Q311
95-th percentile15.5
Maximum22.4
Range20.9
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation4.3550152
Coefficient of variation (CV)0.55492039
Kurtosis0.94745506
Mean7.848
Median Absolute Deviation (MAD)3.45
Skewness0.91696999
Sum784.8
Variance18.966158
MonotonicityNot monotonic
2023-12-10T21:37:47.502003image/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%
8.8 4
 
4.0%
12.3 4
 
4.0%
3.4 4
 
4.0%
11.1 4
 
4.0%
7.5 2
 
2.0%
2.7 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%
3.3 2
2.0%
3.4 4
4.0%
3.6 2
2.0%
3.7 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%
11.2 2
2.0%
11.1 4
4.0%
11.0 2
2.0%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210101
90 
20210102
10 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210101
2nd row20210101
3rd row20210101
4th row20210101
5th row20210101

Common Values

ValueCountFrequency (%)
20210101 90
90.0%
20210102 10
 
10.0%

Length

2023-12-10T21:37:47.667776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:47.806259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210101 90
90.0%
20210102 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

2023-12-10T21:37:47.968330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:37:48.096826image/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%
Mean36.80325
Minimum36.10527
Maximum37.18469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:48.260524image/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 deviation0.27476319
Coefficient of variation (CV)0.0074657317
Kurtosis-0.24336834
Mean36.80325
Median Absolute Deviation (MAD)0.152995
Skewness-0.8693168
Sum3680.325
Variance0.075494809
MonotonicityNot monotonic
2023-12-10T21:37:48.470444image/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%
37.07857 2
 
2.0%
36.80475 2
 
2.0%
36.7235 2
 
2.0%
36.83418 2
 
2.0%
36.91571 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%
36.3326 4
4.0%
36.35443 2
2.0%
36.44592 2
2.0%
36.45034 2
2.0%
36.47999 2
2.0%
36.51373 2
2.0%
36.54466 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%
Mean127.7386
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:48.647457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.43014
Q1127.56961
median127.7073
Q3127.86686
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.29725

Descriptive statistics

Standard deviation0.23510363
Coefficient of variation (CV)0.0018405058
Kurtosis0.54315162
Mean127.7386
Median Absolute Deviation (MAD)0.15657
Skewness0.87206696
Sum12773.86
Variance0.055273717
MonotonicityNot monotonic
2023-12-10T21:37:49.097563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.86686 4
 
4.0%
127.60416 4
 
4.0%
127.53139 4
 
4.0%
127.72238 4
 
4.0%
127.95118 2
 
2.0%
127.64739 2
 
2.0%
127.55372 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
Other values (35) 70
70.0%
ValueCountFrequency (%)
127.37509 2
2.0%
127.38986 2
2.0%
127.43014 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%
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%
Mean4792.6407
Minimum396.02
Maximum30847.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:49.271704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum396.02
5-th percentile512.1755
Q11559.0025
median3297.32
Q35976.34
95-th percentile11261.165
Maximum30847.2
Range30451.18
Interquartile range (IQR)4417.3375

Descriptive statistics

Standard deviation4894.7306
Coefficient of variation (CV)1.0213014
Kurtosis11.371498
Mean4792.6407
Median Absolute Deviation (MAD)2342.2
Skewness2.7912211
Sum479264.07
Variance23958388
MonotonicityNot monotonic
2023-12-10T21:37:49.415175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2946.24 1
 
1.0%
962.37 1
 
1.0%
702.07 1
 
1.0%
11103.56 1
 
1.0%
5910.02 1
 
1.0%
4646.08 1
 
1.0%
2790.26 1
 
1.0%
2745.7 1
 
1.0%
2035.77 1
 
1.0%
1154.55 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
396.02 1
1.0%
423.58 1
1.0%
471.6 1
1.0%
476.96 1
1.0%
490.43 1
1.0%
513.32 1
1.0%
622.08 1
1.0%
650.74 1
1.0%
702.07 1
1.0%
775.71 1
1.0%
ValueCountFrequency (%)
30847.2 1
1.0%
27802.74 1
1.0%
13279.31 1
1.0%
12775.58 1
1.0%
12016.7 1
1.0%
11221.4 1
1.0%
11103.56 1
1.0%
11033.07 1
1.0%
10977.63 1
1.0%
10783.64 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5944.6603
Minimum278.51
Maximum59808.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:49.593396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum278.51
5-th percentile407.263
Q11249.665
median2711.42
Q35681.57
95-th percentile22661.166
Maximum59808.42
Range59529.91
Interquartile range (IQR)4431.905

Descriptive statistics

Standard deviation9194.6777
Coefficient of variation (CV)1.546712
Kurtosis16.366705
Mean5944.6603
Median Absolute Deviation (MAD)1859.105
Skewness3.6202251
Sum594466.03
Variance84542098
MonotonicityNot monotonic
2023-12-10T21:37:49.768380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2190.53 1
 
1.0%
686.37 1
 
1.0%
520.29 1
 
1.0%
11265.81 1
 
1.0%
5603.5 1
 
1.0%
4177.18 1
 
1.0%
2445.67 1
 
1.0%
2264.15 1
 
1.0%
1678.74 1
 
1.0%
1700.29 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
278.51 1
1.0%
290.57 1
1.0%
293.67 1
1.0%
359.76 1
1.0%
370.27 1
1.0%
409.21 1
1.0%
414.43 1
1.0%
441.96 1
1.0%
520.29 1
1.0%
601.89 1
1.0%
ValueCountFrequency (%)
59808.42 1
1.0%
50696.79 1
1.0%
24895.02 1
1.0%
23160.67 1
1.0%
23086.5 1
1.0%
22638.78 1
1.0%
18934.12 1
1.0%
18692.78 1
1.0%
18656.42 1
1.0%
17208.84 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean698.1756
Minimum36.89
Maximum5881.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:49.967992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.89
5-th percentile53.9285
Q1168.2275
median364.67
Q3705.445
95-th percentile2433.428
Maximum5881.19
Range5844.3
Interquartile range (IQR)537.2175

Descriptive statistics

Standard deviation942.04581
Coefficient of variation (CV)1.3492964
Kurtosis12.152108
Mean698.1756
Median Absolute Deviation (MAD)238.28
Skewness3.0823883
Sum69817.56
Variance887450.31
MonotonicityNot monotonic
2023-12-10T21:37:50.143416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
294.01 1
 
1.0%
90.01 1
 
1.0%
67.04 1
 
1.0%
1329.43 1
 
1.0%
698.28 1
 
1.0%
542.75 1
 
1.0%
325.51 1
 
1.0%
302.69 1
 
1.0%
228.89 1
 
1.0%
198.16 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
36.89 1
1.0%
40.23 1
1.0%
45.02 1
1.0%
48.6 1
1.0%
49.91 1
1.0%
54.14 1
1.0%
55.98 1
1.0%
59.8 1
1.0%
67.04 1
1.0%
81.17 1
1.0%
ValueCountFrequency (%)
5881.19 1
1.0%
4943.98 1
1.0%
2605.68 1
1.0%
2512.89 1
1.0%
2500.27 1
1.0%
2429.91 1
1.0%
2294.59 1
1.0%
2209.64 1
1.0%
2079.66 1
1.0%
1970.47 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean359.875
Minimum8.21
Maximum3464.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:50.323738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.21
5-th percentile19.226
Q160.95
median138.295
Q3273.2725
95-th percentile1500.7315
Maximum3464.02
Range3455.81
Interquartile range (IQR)212.3225

Descriptive statistics

Standard deviation585.69492
Coefficient of variation (CV)1.6274954
Kurtosis10.541307
Mean359.875
Median Absolute Deviation (MAD)92.62
Skewness2.9984013
Sum35987.5
Variance343038.54
MonotonicityNot monotonic
2023-12-10T21:37:50.519644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82.65 1
 
1.0%
23.85 1
 
1.0%
22.38 1
 
1.0%
515.22 1
 
1.0%
270.85 1
 
1.0%
186.16 1
 
1.0%
128.6 1
 
1.0%
149.85 1
 
1.0%
120.37 1
 
1.0%
107.59 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
8.21 1
1.0%
9.65 1
1.0%
15.85 1
1.0%
16.07 1
1.0%
17.82 1
1.0%
19.3 1
1.0%
22.38 1
1.0%
22.51 1
1.0%
23.17 1
1.0%
23.85 1
1.0%
ValueCountFrequency (%)
3464.02 1
1.0%
2855.72 1
1.0%
1812.22 1
1.0%
1778.17 1
1.0%
1547.12 1
1.0%
1498.29 1
1.0%
1471.6 1
1.0%
1458.66 1
1.0%
1456.42 1
1.0%
1091.56 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1243014.1
Minimum103370.83
Maximum8465401.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:37:50.808345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum103370.83
5-th percentile133834.85
Q1407574.85
median835820.03
Q31502850.2
95-th percentile3097983.5
Maximum8465401.9
Range8362031.1
Interquartile range (IQR)1095275.3

Descriptive statistics

Standard deviation1317477.1
Coefficient of variation (CV)1.0599052
Kurtosis12.843996
Mean1243014.1
Median Absolute Deviation (MAD)581756.85
Skewness3.0042984
Sum1.2430141 × 108
Variance1.7357459 × 1012
MonotonicityNot monotonic
2023-12-10T21:37:51.005182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
760407.95 1
 
1.0%
250950.96 1
 
1.0%
182790.28 1
 
1.0%
2950504.5 1
 
1.0%
1539857.27 1
 
1.0%
1138530.73 1
 
1.0%
713428.98 1
 
1.0%
715665.33 1
 
1.0%
525170.39 1
 
1.0%
288324.48 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
103370.83 1
1.0%
110950.62 1
1.0%
111612.49 1
1.0%
121957.79 1
1.0%
124683.99 1
1.0%
134316.47 1
1.0%
164312.35 1
1.0%
171278.91 1
1.0%
182790.28 1
1.0%
193599.09 1
1.0%
ValueCountFrequency (%)
8465401.94 1
1.0%
7556459.35 1
1.0%
3655330.8 1
1.0%
3331472.3 1
1.0%
3268197.46 1
1.0%
3089024.84 1
1.0%
2950504.5 1
1.0%
2864981.25 1
1.0%
2810393.93 1
1.0%
2794603.86 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 length13
Median length11
Mean length11.14
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 영동 용산 율 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 남이 부용외천 2
 
2.0%
Other values (35) 70
70.0%

Length

2023-12-10T21:37:51.199548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 28
 
7.0%
청주 12
 
3.0%
보은 10
 
2.5%
음성 10
 
2.5%
증평 10
 
2.5%
진천 8
 
2.0%
옥천 6
 
1.5%
영동 6
 
1.5%
중산 6
 
1.5%
Other values (80) 204
51.0%

Interactions

2023-12-10T21:37:44.460481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.350241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.593445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.760211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.085502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.300594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.539746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.688424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.244933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.578814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.463680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.757452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.889765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.230360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.434248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.672568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.108674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.398186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.691745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.567024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.899789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.005820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.339822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.549413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.797894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.230793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.518785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.811624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.692583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.021081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.163841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.460535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.677008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.934716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.390702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.647628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.929268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.849957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.150505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.307435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.584086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.801444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.071986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.519351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.768527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:45.047442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:34.976313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.265579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.486870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.723358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.940186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.209694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.648378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.906021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:45.158134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.104816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.402513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.636985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.863524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.110869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.330221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.886722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.035145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:45.295741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.243494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.519173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.780205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:38.992370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.262167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.441159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:42.998412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.180427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:45.424236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:35.408070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:36.644225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:37.938526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:39.137249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:40.419268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:41.578749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:43.118383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:37:44.324844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:37:51.358137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정일좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9900.0000.9900.5371.0000.8050.6400.5990.5300.5350.5410.4950.990
지점0.9901.0000.0001.0001.0000.1071.0001.0000.9290.8240.8630.6520.8811.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
측정구간0.9901.0000.0001.0001.0000.1071.0001.0000.9290.8240.8630.6520.8811.000
연장0.5371.0000.0001.0001.0000.2310.6510.5940.4640.2320.3770.0000.3251.000
측정일1.0000.1070.0000.1070.2311.0000.2280.0000.2110.3640.2770.5890.0910.107
좌표위치위도0.8051.0000.0001.0000.6510.2281.0000.6760.4910.2970.2720.1470.4121.000
좌표위치경도0.6401.0000.0001.0000.5940.0000.6761.0000.5080.2830.3530.1270.3361.000
co0.5990.9290.0000.9290.4640.2110.4910.5081.0000.8080.8530.8200.9380.929
nox0.5300.8240.0000.8240.2320.3640.2970.2830.8081.0000.9840.9570.9660.824
hc0.5350.8630.0000.8630.3770.2770.2720.3530.8530.9841.0000.9180.9730.863
pm0.5410.6520.0000.6520.0000.5890.1470.1270.8200.9570.9181.0000.8970.652
co20.4950.8810.0000.8810.3250.0910.4120.3360.9380.9660.9730.8971.0000.881
주소0.9901.0000.0001.0001.0000.1071.0001.0000.9290.8240.8630.6520.8811.000
2023-12-10T21:37:51.560845image/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
2023-12-10T21:37:51.702370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정일주소
기본키1.0000.0790.227-0.0610.3720.3870.4000.4440.3650.6990.0000.6990.9580.699
연장0.0791.0000.1620.139-0.162-0.183-0.168-0.183-0.1640.7730.0000.7730.1660.773
좌표위치위도0.2270.1621.0000.4070.3130.3390.3480.3450.3110.7820.0000.7820.1650.782
좌표위치경도-0.0610.1390.4071.000-0.390-0.361-0.369-0.357-0.3920.7770.0000.7770.0000.777
co0.372-0.1620.313-0.3901.0000.9780.9860.9390.9990.5470.0000.5470.1520.547
nox0.387-0.1830.339-0.3610.9781.0000.9960.9770.9770.3920.0000.3920.3800.392
hc0.400-0.1680.348-0.3690.9860.9961.0000.9690.9830.4360.0000.4360.2880.436
pm0.444-0.1830.345-0.3570.9390.9770.9691.0000.9370.2330.0000.2330.4310.233
co20.365-0.1640.311-0.3920.9990.9770.9830.9371.0000.4640.0000.4640.0990.464
지점0.6990.7730.7820.7770.5470.3920.4360.2330.4641.0000.0001.0000.0001.000
방향0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.6990.7730.7820.7770.5470.3920.4360.2330.4641.0000.0001.0000.0001.000
측정일0.9580.1660.1650.0000.1520.3800.2880.4310.0990.0000.0000.0001.0000.000
주소0.6990.7730.7820.7770.5470.3920.4360.2330.4641.0000.0001.0000.0001.000

Missing values

2023-12-10T21:37:45.585032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:37:45.842945image/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-충주7.320210101036.88774127.984842946.242190.53294.0182.65760407.95충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210101036.88774127.984842875.082301.25298.76107.84736267.72충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210101036.9979127.722383281.912722.73389.49116.05826766.07충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210101036.9979127.722382935.022778.32372.71133.38735034.5충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210101036.96342127.866867890.686551.21823.77379.152029484.03충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210101036.96342127.866866959.685915.78726.94274.031781972.14충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210101037.06589127.604164662.574143.32558.6273.021179823.6충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210101037.06589127.604165108.554939.68651.99313.081262010.99충북 음성 생극 송곡
89건기연[0406-1]1대전-옥천15.520210101036.3326127.531393483.762398.38323.3787.77910973.47충북 옥천 군북 이백
910건기연[0406-1]2대전-옥천15.520210101036.3326127.531393845.822658.38358.189.181004108.76충북 옥천 군북 이백
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[0324-1]1수안보-충주7.320210102036.88774127.984842688.822636.32337.8159.53669690.17충북 충주 수안보 중산
9192건기연[0324-1]2수안보-충주7.320210102036.88774127.984843292.023225.09421.49194.86774603.79충북 충주 수안보 중산
9293건기연[0325-3]1신니-신양8.820210102036.9979127.722385718.538193.211010.11500.471410515.66충북 충주 신니 원평
9394건기연[0325-3]2신니-신양8.820210102036.9979127.722385933.628569.381070.91567.181438498.08충북 충주 신니 원평
9495건기연[0325-4]1주덕-충주5.020210102036.96342127.8668610783.6411702.741438.81786.172674322.84충북 충주 대소원 만정
9596건기연[0325-4]2주덕-충주5.020210102036.96342127.8668610977.6312612.381529.63782.242729892.08충북 충주 대소원 만정
9697건기연[0326-2]1오생-장호원5.420210102037.06589127.604168988.4714041.331702.64991.342153453.11충북 음성 생극 송곡
9798건기연[0326-2]2오생-장호원5.420210102037.06589127.6041610019.0215736.421970.471091.562323341.57충북 음성 생극 송곡
9899건기연[0406-1]1대전-옥천15.520210102036.3326127.531394915.733861.89561.15205.141145897.39충북 옥천 군북 이백
99100건기연[0406-1]2대전-옥천15.520210102036.3326127.531394290.553663.9488.92207.581079020.93충북 옥천 군북 이백