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 7 other fieldsHigh correlation
지점 is highly overall correlated with 기본키 and 7 other fieldsHigh correlation
주소 is highly overall correlated with 기본키 and 7 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 6 other fieldsHigh correlation
측정일 is highly overall correlated with 기본키High correlation
측정일 is highly imbalanced (59.8%)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 12:35:58.662944
Analysis finished2023-12-10 12:36:12.517999
Duration13.86 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
2023-12-10T21:36:12.654147image/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
2023-12-10T21:36:12.879875image/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

2023-12-10T21:36:13.074039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:13.223278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건기연 100
100.0%

지점
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
[0324-1]
 
4
[0325-4]
 
4
[0326-2]
 
4
[0325-3]
 
4
[1917-3]
 
2
Other values (41)
82 

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%
[0325-4] 4
 
4.0%
[0326-2] 4
 
4.0%
[0325-3] 4
 
4.0%
[1917-3] 2
 
2.0%
[1919-1] 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 (36) 72
72.0%

Length

2023-12-10T21:36:13.399344image/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%
0325-4 4
 
4.0%
0326-2 4
 
4.0%
3808-1 2
 
2.0%
3810-1 2
 
2.0%
5913-1 2
 
2.0%
3609-0 2
 
2.0%
3609-1 2
 
2.0%
3613-0 2
 
2.0%
Other values (36) 72
72.0%

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

2023-12-10T21:36:13.669133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:13.806236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 50
50.0%
2 50
50.0%

측정구간
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
수안보-충주
 
4
주덕-충주
 
4
오생-장호원
 
4
신니-신양
 
4
삼승-보은
 
2
Other values (41)
82 

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%
주덕-충주 4
 
4.0%
오생-장호원 4
 
4.0%
신니-신양 4
 
4.0%
삼승-보은 2
 
2.0%
내북-구방 2
 
2.0%
대전-옥천 2
 
2.0%
약목-황간 2
 
2.0%
단양-하시 2
 
2.0%
청주-진천 2
 
2.0%
Other values (36) 72
72.0%

Length

2023-12-10T21:36:14.020325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수안보-충주 4
 
4.0%
신니-신양 4
 
4.0%
주덕-충주 4
 
4.0%
오생-장호원 4
 
4.0%
목계-산척 2
 
2.0%
장락-쌍용 2
 
2.0%
대대-향산 2
 
2.0%
초정-증평 2
 
2.0%
노암-중흥 2
 
2.0%
내사-덕산 2
 
2.0%
Other values (36) 72
72.0%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.986
Minimum1.5
Maximum22.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:14.264437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.5
5-th percentile2.1
Q14.8
median7.3
Q311.1
95-th percentile15.2
Maximum22.4
Range20.9
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation4.2996833
Coefficient of variation (CV)0.53840262
Kurtosis0.92996101
Mean7.986
Median Absolute Deviation (MAD)3.45
Skewness0.85055926
Sum798.6
Variance18.487277
MonotonicityNot monotonic
2023-12-10T21:36:14.450109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
7.3 10
 
10.0%
5.4 6
 
6.0%
3.4 4
 
4.0%
8.8 4
 
4.0%
11.1 4
 
4.0%
12.3 4
 
4.0%
5.0 4
 
4.0%
7.7 2
 
2.0%
2.1 2
 
2.0%
3.6 2
 
2.0%
Other values (29) 58
58.0%
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 2
2.0%
15.2 2
2.0%
14.5 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%

측정일
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20210501
92 
20210502
 
8

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 92
92.0%
20210502 8
 
8.0%

Length

2023-12-10T21:36:14.756086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:14.929495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210501 92
92.0%
20210502 8
 
8.0%

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

2023-12-10T21:36:15.217148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:36:15.443215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

좌표위치위도
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.802828
Minimum36.10527
Maximum37.19998
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:15.636585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.10527
5-th percentile36.24756
Q136.62606
median36.89448
Q337.03359
95-th percentile37.11937
Maximum37.19998
Range1.09471
Interquartile range (IQR)0.40753

Descriptive statistics

Standard deviation0.28591005
Coefficient of variation (CV)0.007768698
Kurtosis-0.38727341
Mean36.802828
Median Absolute Deviation (MAD)0.154975
Skewness-0.85314916
Sum3680.2828
Variance0.081744559
MonotonicityNot monotonic
2023-12-10T21:36:15.874892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
36.88774 4
 
4.0%
36.96342 4
 
4.0%
37.06589 4
 
4.0%
36.9979 4
 
4.0%
36.28264 2
 
2.0%
36.83418 2
 
2.0%
36.91571 2
 
2.0%
36.35443 2
 
2.0%
36.51373 2
 
2.0%
37.11937 2
 
2.0%
Other values (36) 72
72.0%
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 4
4.0%
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 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.73285
Minimum127.37509
Maximum128.39227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:16.122714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37509
5-th percentile127.44767
Q1127.57716
median127.692
Q3127.86686
95-th percentile128.27212
Maximum128.39227
Range1.01718
Interquartile range (IQR)0.2897

Descriptive statistics

Standard deviation0.22528091
Coefficient of variation (CV)0.0017636881
Kurtosis1.0758504
Mean127.73285
Median Absolute Deviation (MAD)0.13033
Skewness1.0238178
Sum12773.285
Variance0.050751488
MonotonicityNot monotonic
2023-12-10T21:36:16.378736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
127.98484 4
 
4.0%
127.86686 4
 
4.0%
127.60416 4
 
4.0%
127.72238 4
 
4.0%
127.64833 2
 
2.0%
127.61577 2
 
2.0%
128.10947 2
 
2.0%
127.59919 2
 
2.0%
127.79015 2
 
2.0%
127.65518 2
 
2.0%
Other values (36) 72
72.0%
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%
Mean8399.522
Minimum966.32
Maximum47983.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:16.990244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum966.32
5-th percentile1162.502
Q13224.94
median6160.82
Q311273.272
95-th percentile20874.914
Maximum47983.24
Range47016.92
Interquartile range (IQR)8048.3325

Descriptive statistics

Standard deviation7705.3663
Coefficient of variation (CV)0.91735771
Kurtosis8.7024278
Mean8399.522
Median Absolute Deviation (MAD)3882.765
Skewness2.4100986
Sum839952.2
Variance59372670
MonotonicityNot monotonic
2023-12-10T21:36:17.317940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3085.82 1
 
1.0%
5884.44 1
 
1.0%
41115.84 1
 
1.0%
17937.41 1
 
1.0%
19281.59 1
 
1.0%
16449.9 1
 
1.0%
16007.72 1
 
1.0%
2257.29 1
 
1.0%
2303.51 1
 
1.0%
11407.32 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
966.32 1
1.0%
991.1 1
1.0%
994.9 1
1.0%
1032.53 1
1.0%
1106.3 1
1.0%
1165.46 1
1.0%
1222.94 1
1.0%
1348.38 1
1.0%
1384.3 1
1.0%
1419.27 1
1.0%
ValueCountFrequency (%)
47983.24 1
1.0%
41115.84 1
1.0%
22638.9 1
1.0%
21761.13 1
1.0%
21699.6 1
1.0%
20831.51 1
1.0%
20067.82 1
1.0%
19281.59 1
1.0%
18632.7 1
1.0%
18491.18 1
1.0%

nox
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11112.619
Minimum734.75
Maximum88793.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:17.552256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum734.75
5-th percentile895.7955
Q12459.9
median6276.165
Q312487.57
95-th percentile33854.11
Maximum88793.81
Range88059.06
Interquartile range (IQR)10027.67

Descriptive statistics

Standard deviation14306.502
Coefficient of variation (CV)1.2874105
Kurtosis11.497247
Mean11112.619
Median Absolute Deviation (MAD)4417.96
Skewness2.9650607
Sum1111261.9
Variance2.04676 × 108
MonotonicityNot monotonic
2023-12-10T21:36:17.872721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2275.96 1
 
1.0%
5881.02 1
 
1.0%
75146.93 1
 
1.0%
29215.86 1
 
1.0%
29579.1 1
 
1.0%
35988.39 1
 
1.0%
32654.24 1
 
1.0%
1625.81 1
 
1.0%
1656.46 1
 
1.0%
14673.96 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
734.75 1
1.0%
771.94 1
1.0%
772.21 1
1.0%
784.16 1
1.0%
795.96 1
1.0%
901.05 1
1.0%
917.63 1
1.0%
970.81 1
1.0%
1000.55 1
1.0%
1134.24 1
1.0%
ValueCountFrequency (%)
88793.81 1
1.0%
75146.93 1
1.0%
43132.78 1
1.0%
39708.23 1
1.0%
35988.39 1
1.0%
33741.78 1
1.0%
32654.24 1
1.0%
30861.34 1
1.0%
29756.76 1
1.0%
29579.1 1
1.0%

hc
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1276.7768
Minimum104.77
Maximum9264.59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:18.169456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum104.77
5-th percentile123.889
Q1345.8775
median828.47
Q31543.7325
95-th percentile3452.181
Maximum9264.59
Range9159.82
Interquartile range (IQR)1197.855

Descriptive statistics

Standard deviation1453.6467
Coefficient of variation (CV)1.1385285
Kurtosis11.230737
Mean1276.7768
Median Absolute Deviation (MAD)554.6
Skewness2.8499507
Sum127677.68
Variance2113088.8
MonotonicityNot monotonic
2023-12-10T21:36:18.384571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
318.87 1
 
1.0%
798.76 1
 
1.0%
7536.29 1
 
1.0%
3014.3 1
 
1.0%
3102.19 1
 
1.0%
3449.98 1
 
1.0%
3229.71 1
 
1.0%
230.16 1
 
1.0%
232.11 1
 
1.0%
1662.41 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
104.77 1
1.0%
106.19 1
1.0%
112.8 1
1.0%
115.42 1
1.0%
119.69 1
1.0%
124.11 1
1.0%
126.79 1
1.0%
136.8 1
1.0%
145.48 1
1.0%
146.38 1
1.0%
ValueCountFrequency (%)
9264.59 1
1.0%
7536.29 1
1.0%
4377.66 1
1.0%
3982.38 1
1.0%
3494.0 1
1.0%
3449.98 1
1.0%
3337.29 1
1.0%
3263.94 1
1.0%
3256.1 1
1.0%
3229.71 1
1.0%

pm
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean627.0093
Minimum33.11
Maximum5242.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:18.679771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.11
5-th percentile49.5555
Q1151.07
median345.08
Q3755.51
95-th percentile2055.393
Maximum5242.84
Range5209.73
Interquartile range (IQR)604.44

Descriptive statistics

Standard deviation821.37261
Coefficient of variation (CV)1.3099847
Kurtosis13.279523
Mean627.0093
Median Absolute Deviation (MAD)232.82
Skewness3.1879731
Sum62700.93
Variance674652.97
MonotonicityNot monotonic
2023-12-10T21:36:18.960132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112.01 1
 
1.0%
359.13 1
 
1.0%
4390.89 1
 
1.0%
1589.73 1
 
1.0%
1567.04 1
 
1.0%
2196.24 1
 
1.0%
2047.98 1
 
1.0%
79.57 1
 
1.0%
72.17 1
 
1.0%
795.8 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
33.11 1
1.0%
39.42 1
1.0%
39.66 1
1.0%
39.88 1
1.0%
46.62 1
1.0%
49.71 1
1.0%
51.19 1
1.0%
58.74 1
1.0%
69.47 1
1.0%
70.03 1
1.0%
ValueCountFrequency (%)
5242.84 1
1.0%
4390.89 1
1.0%
2462.89 1
1.0%
2280.09 1
1.0%
2196.24 1
1.0%
2047.98 1
1.0%
1925.99 1
1.0%
1595.17 1
1.0%
1589.73 1
1.0%
1567.04 1
1.0%

co2
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2239589.8
Minimum243536.86
Maximum13029958
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:36:19.252396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum243536.86
5-th percentile301365.36
Q1833144.12
median1550974.5
Q32939519.7
95-th percentile5859061
Maximum13029958
Range12786421
Interquartile range (IQR)2106375.5

Descriptive statistics

Standard deviation2167764.6
Coefficient of variation (CV)0.9679293
Kurtosis8.3257911
Mean2239589.8
Median Absolute Deviation (MAD)969577.55
Skewness2.4265279
Sum2.2395898 × 108
Variance4.6992034 × 1012
MonotonicityNot monotonic
2023-12-10T21:36:19.472628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
795217.09 1
 
1.0%
1483874.67 1
 
1.0%
11707130.61 1
 
1.0%
5260363.77 1
 
1.0%
5412892.18 1
 
1.0%
4889770.64 1
 
1.0%
4605017.43 1
 
1.0%
581182.47 1
 
1.0%
595198.03 1
 
1.0%
3082760.63 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
243536.86 1
1.0%
247193.7 1
1.0%
255169.81 1
1.0%
260464.88 1
1.0%
286456.21 1
1.0%
302150.05 1
1.0%
322089.91 1
1.0%
353041.92 1
1.0%
356279.27 1
1.0%
356580.37 1
1.0%
ValueCountFrequency (%)
13029958.25 1
1.0%
11707130.61 1
1.0%
6473740.03 1
1.0%
6192450.18 1
1.0%
6043358.64 1
1.0%
5849361.15 1
1.0%
5575566.55 1
1.0%
5412892.18 1
1.0%
5356881.55 1
1.0%
5260363.77 1
1.0%

주소
Categorical

HIGH CORRELATION 

Distinct46
Distinct (%)46.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
충북 충주 수안보 중산
 
4
충북 충주 대소원 만정
 
4
충북 음성 생극 송곡
 
4
충북 충주 신니 원평
 
4
충북 보은 보은 금굴
 
2
Other values (41)
82 

Length

Max length12
Median length11
Mean length11.1
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충북 충주 수안보 중산
2nd row충북 충주 수안보 중산
3rd row충북 충주 신니 원평
4th row충북 충주 신니 원평
5th row충북 충주 대소원 만정

Common Values

ValueCountFrequency (%)
충북 충주 수안보 중산 4
 
4.0%
충북 충주 대소원 만정 4
 
4.0%
충북 음성 생극 송곡 4
 
4.0%
충북 충주 신니 원평 4
 
4.0%
충북 보은 보은 금굴 2
 
2.0%
충북 청주 미원 미원 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 (36) 72
72.0%

Length

2023-12-10T21:36:19.692332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충북 100
25.0%
충주 30
 
7.5%
음성 12
 
3.0%
증평 10
 
2.5%
청주 10
 
2.5%
보은 10
 
2.5%
옥천 10
 
2.5%
진천 8
 
2.0%
영동 6
 
1.5%
신니 6
 
1.5%
Other values (79) 198
49.5%

Interactions

2023-12-10T21:36:10.642257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.052407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.415333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.540239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.806818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.032975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.266690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:07.928013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.298025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.778003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.277630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.541670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.707710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.946967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.172057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.402451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.122100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.409984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.924569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.413652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.644924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.867711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.079506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.286889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.517387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.255362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.514971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.082557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.589391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.783427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.034860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.210930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.428333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.644179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.402607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.645818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.220902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.738058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.912068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.159748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.349755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.554955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.778251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.548522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.786795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.354890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:00.903186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.036988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.283254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.510925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.678846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.902434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.674037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.082803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.497231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.045066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.185811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.411263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.642259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.793327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:07.029190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.833450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.269384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.625567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.161731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.298178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.542264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.755752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:05.917400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:07.558000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:08.998407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.389990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:11.759072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:01.284501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:02.413250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:03.664551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:04.890464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:06.120228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:07.752332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:09.156771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:36:10.506485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:36:19.840113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키지점방향측정구간연장측정일좌표위치위도좌표위치경도conoxhcpmco2주소
기본키1.0000.9910.0000.9910.5860.9780.8160.6060.5490.5630.5330.5710.5160.991
지점0.9911.0000.0001.0001.0000.1371.0001.0000.9420.8210.8720.8590.9331.000
방향0.0000.0001.0000.0000.0000.0000.0000.0000.0000.1480.0000.0000.0000.000
측정구간0.9911.0000.0001.0001.0000.1371.0001.0000.9420.8210.8720.8590.9331.000
연장0.5861.0000.0001.0001.0000.2420.6860.5310.4030.2400.2130.2390.3371.000
측정일0.9780.1370.0000.1370.2421.0000.0000.0000.0000.0770.0000.0000.0000.137
좌표위치위도0.8161.0000.0001.0000.6860.0001.0000.6240.5240.3700.4000.3590.4491.000
좌표위치경도0.6061.0000.0001.0000.5310.0000.6241.0000.4420.3280.3480.2880.4201.000
co0.5490.9420.0000.9420.4030.0000.5240.4421.0000.9800.9780.9770.9970.942
nox0.5630.8210.1480.8210.2400.0770.3700.3280.9801.0000.9930.9960.9760.821
hc0.5330.8720.0000.8720.2130.0000.4000.3480.9780.9931.0000.9910.9780.872
pm0.5710.8590.0000.8590.2390.0000.3590.2880.9770.9960.9911.0000.9760.859
co20.5160.9330.0000.9330.3370.0000.4490.4200.9970.9760.9780.9761.0000.933
주소0.9911.0000.0001.0001.0000.1371.0001.0000.9420.8210.8720.8590.9331.000
2023-12-10T21:36:20.072614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
측정일측정구간지점주소방향
측정일1.0000.0450.0450.0450.000
측정구간0.0451.0001.0001.0000.000
지점0.0451.0001.0001.0000.000
주소0.0451.0001.0001.0000.000
방향0.0000.0000.0000.0001.000
2023-12-10T21:36:20.253054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기본키연장좌표위치위도좌표위치경도conoxhcpmco2지점방향측정구간측정일주소
기본키1.0000.1120.329-0.0600.4580.4500.4590.4450.4630.7090.0000.7090.8360.709
연장0.1121.0000.1860.0700.0490.0410.0460.0220.0450.7660.0000.7660.1740.766
좌표위치위도0.3290.1861.0000.3190.3670.3920.3970.3700.3700.7750.0000.7750.0000.775
좌표위치경도-0.0600.0700.3191.000-0.380-0.374-0.380-0.400-0.3770.7700.0000.7700.0000.770
co0.4580.0490.367-0.3801.0000.9710.9800.9580.9970.5650.0000.5650.0000.565
nox0.4500.0410.392-0.3740.9711.0000.9960.9930.9740.3850.1520.3850.0820.385
hc0.4590.0460.397-0.3800.9800.9961.0000.9880.9800.4420.0000.4420.0000.442
pm0.4450.0220.370-0.4000.9580.9930.9881.0000.9610.4260.0000.4260.0000.426
co20.4630.0450.370-0.3770.9970.9740.9800.9611.0000.5470.0000.5470.0000.547
지점0.7090.7660.7750.7700.5650.3850.4420.4260.5471.0000.0001.0000.0451.000
방향0.0000.0000.0000.0000.0000.1520.0000.0000.0000.0001.0000.0000.0000.000
측정구간0.7090.7660.7750.7700.5650.3850.4420.4260.5471.0000.0001.0000.0451.000
측정일0.8360.1740.0000.0000.0000.0820.0000.0000.0000.0450.0000.0451.0000.045
주소0.7090.7660.7750.7700.5650.3850.4420.4260.5471.0000.0001.0000.0451.000

Missing values

2023-12-10T21:36:12.059129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:36:12.403414image/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-충주7.320210501036.88774127.984843085.822275.96318.87112.01795217.09충북 충주 수안보 중산
12건기연[0324-1]2수안보-충주7.320210501036.88774127.984843265.122939.4365.23164.88862093.24충북 충주 수안보 중산
23건기연[0325-3]1신니-신양8.820210501036.9979127.722385493.496727.05862.18381.321368369.65충북 충주 신니 원평
34건기연[0325-3]2신니-신양8.820210501036.9979127.722385728.295925.36764.91327.581472536.27충북 충주 신니 원평
45건기연[0325-4]1주덕-충주5.020210501036.96342127.8668610903.269623.491255.77643.752778943.91충북 충주 대소원 만정
56건기연[0325-4]2주덕-충주5.020210501036.96342127.8668611476.4811265.791379.53624.262931134.99충북 충주 대소원 만정
67건기연[0326-2]1오생-장호원5.420210501037.06589127.604168955.3211251.311455.86766.282168628.28충북 음성 생극 송곡
78건기연[0326-2]2오생-장호원5.420210501037.06589127.6041610425.6813540.81723.2918.532520337.56충북 음성 생극 송곡
89건기연[0406-1]1대전-옥천15.520210501036.3326127.531395892.784043.04565.07199.871539739.65충북 옥천 군북 이백
910건기연[0406-1]2대전-옥천15.520210501036.3326127.531395763.063929.98549.47184.51500948.68충북 옥천 군북 이백
기본키도로종류지점방향측정구간연장측정일측정시분좌표위치위도좌표위치경도conoxhcpmco2주소
9091건기연[04511]1감곡IC-여주JCT14.520210501037.19998127.6119122638.930861.343337.291542.776473740.03충북 음성 감곡 상우
9192건기연[04511]2감곡IC-여주JCT14.520210501037.19998127.6119121699.626982.753099.331299.56043358.64충북 음성 감곡 상우
9293건기연[0324-1]1수안보-충주7.320210502036.88774127.984843933.953519.88498.46179.19975522.81충북 충주 수안보 중산
9394건기연[0324-1]2수안보-충주7.320210502036.88774127.984843469.853211.6447.22182.04862283.28충북 충주 수안보 중산
9495건기연[0325-3]1신니-신양8.820210502036.9979127.722386744.556697.43899.41332.911697740.91충북 충주 신니 원평
9596건기연[0325-3]2신니-신양8.820210502036.9979127.722385970.286199.79858.93319.641464567.35충북 충주 신니 원평
9697건기연[0325-4]1주덕-충주5.020210502036.96342127.8668611802.310345.571368.46653.383013112.7충북 충주 대소원 만정
9798건기연[0325-4]2주덕-충주5.020210502036.96342127.8668611702.6510734.481386.61512.492966417.07충북 충주 대소원 만정
9899건기연[0326-2]1오생-장호원5.420210502037.06589127.6041610807.2311958.481557.48768.52686437.87충북 음성 생극 송곡
99100건기연[0326-2]2오생-장호원5.420210502037.06589127.604169908.9411051.651440.58691.662432423.72충북 음성 생극 송곡