Overview

Dataset statistics

Number of variables15
Number of observations4121
Missing cells16484
Missing cells (%)26.7%
Duplicate rows194
Duplicate rows (%)4.7%
Total size in memory531.4 KiB
Average record size in memory132.0 B

Variable types

Numeric8
Categorical3
Unsupported4

Dataset

Description경기도_도로대장 전산화 시스템_도로 성토면
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=6NPOO5LOW1AC4R0GUXU733879511&infSeq=1

Alerts

Dataset has 194 (4.7%) duplicate rowsDuplicates
노선번호 is highly overall correlated with 비고High correlation
구간번호 is highly overall correlated with 비고High correlation
위치?시점 is highly overall correlated with 위치?종점High correlation
위치?종점 is highly overall correlated with 위치?시점 and 1 other fieldsHigh correlation
연장 is highly overall correlated with 비고High correlation
높이?최대 is highly overall correlated with 종류 and 1 other fieldsHigh correlation
높이?최소 is highly overall correlated with 비고High correlation
종류 is highly overall correlated with 높이?최대 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 노선번호 and 6 other fieldsHigh correlation
비고 is highly imbalanced (95.4%)Imbalance
공간경도시점 has 4121 (100.0%) missing valuesMissing
공간위도시점 has 4121 (100.0%) missing valuesMissing
공간경도종점 has 4121 (100.0%) missing valuesMissing
공간위도종점 has 4121 (100.0%) missing valuesMissing
높이?최대 is highly skewed (γ1 = 61.50453042)Skewed
공간경도시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공간위도시점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공간경도종점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
공간위도종점 is an unsupported type, check if it needs cleaning or further analysisUnsupported
높이?최대 has 1742 (42.3%) zerosZeros
높이?최소 has 3449 (83.7%) zerosZeros
경사 has 1762 (42.8%) zerosZeros

Reproduction

Analysis started2023-12-10 22:49:39.706325
Analysis finished2023-12-10 22:49:48.662516
Duration8.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277.55399
Minimum23
Maximum391
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:48.720143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile56
Q1302
median314
Q3341
95-th percentile375
Maximum391
Range368
Interquartile range (IQR)39

Descriptive statistics

Standard deviation108.3166
Coefficient of variation (CV)0.39025415
Kurtosis-0.031366029
Mean277.55399
Median Absolute Deviation (MAD)19
Skewness-1.2768473
Sum1143800
Variance11732.485
MonotonicityNot monotonic
2023-12-11T07:49:48.830409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
309 377
 
9.1%
78 276
 
6.7%
318 274
 
6.6%
333 274
 
6.6%
364 244
 
5.9%
313 205
 
5.0%
306 160
 
3.9%
56 145
 
3.5%
341 116
 
2.8%
342 116
 
2.8%
Other values (34) 1934
46.9%
ValueCountFrequency (%)
23 65
 
1.6%
56 145
3.5%
57 16
 
0.4%
70 64
 
1.6%
78 276
6.7%
82 90
 
2.2%
86 88
 
2.1%
88 49
 
1.2%
98 69
 
1.7%
301 93
 
2.3%
ValueCountFrequency (%)
391 23
 
0.6%
387 81
 
2.0%
383 95
 
2.3%
379 3
 
0.1%
375 110
2.7%
372 110
2.7%
371 85
 
2.1%
368 4
 
0.1%
367 12
 
0.3%
364 244
5.9%

구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.90876
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:48.931872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile14
Maximum99
Range98
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.7089901
Coefficient of variation (CV)1.4053159
Kurtosis69.888403
Mean6.90876
Median Absolute Deviation (MAD)3
Skewness7.6825161
Sum28471
Variance94.264489
MonotonicityNot monotonic
2023-12-11T07:49:49.026837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 610
14.8%
4 536
13.0%
3 386
9.4%
7 352
8.5%
9 318
7.7%
2 309
7.5%
6 304
7.4%
5 297
7.2%
14 273
6.6%
8 216
 
5.2%
Other values (8) 520
12.6%
ValueCountFrequency (%)
1 610
14.8%
2 309
7.5%
3 386
9.4%
4 536
13.0%
5 297
7.2%
6 304
7.4%
7 352
8.5%
8 216
 
5.2%
9 318
7.7%
10 65
 
1.6%
ValueCountFrequency (%)
99 37
 
0.9%
24 10
 
0.2%
18 19
 
0.5%
15 57
 
1.4%
14 273
6.6%
13 137
3.3%
12 80
 
1.9%
11 115
 
2.8%
10 65
 
1.6%
9 318
7.7%

위치?시점
Real number (ℝ)

HIGH CORRELATION 

Distinct3066
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3537137
Minimum0
Maximum17.48
Zeros30
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:49.122504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.245
Q12.22
median4.755
Q37.803
95-th percentile13.058
Maximum17.48
Range17.48
Interquartile range (IQR)5.583

Descriptive statistics

Standard deviation3.9050296
Coefficient of variation (CV)0.72940576
Kurtosis-0.13291271
Mean5.3537137
Median Absolute Deviation (MAD)2.712
Skewness0.7185414
Sum22062.654
Variance15.249256
MonotonicityNot monotonic
2023-12-11T07:49:49.247331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 30
 
0.7%
0.05 7
 
0.2%
0.08 6
 
0.1%
5.0 6
 
0.1%
2.58 6
 
0.1%
4.57 6
 
0.1%
4.78 5
 
0.1%
14.692 5
 
0.1%
14.972 5
 
0.1%
14.873 5
 
0.1%
Other values (3056) 4040
98.0%
ValueCountFrequency (%)
0.0 30
0.7%
0.005 1
 
< 0.1%
0.006 2
 
< 0.1%
0.007 2
 
< 0.1%
0.008 2
 
< 0.1%
0.009 4
 
0.1%
0.01 5
 
0.1%
0.012 1
 
< 0.1%
0.015 1
 
< 0.1%
0.016 2
 
< 0.1%
ValueCountFrequency (%)
17.48 1
< 0.1%
17.181 1
< 0.1%
17.028 1
< 0.1%
16.902 1
< 0.1%
16.88 1
< 0.1%
16.87 1
< 0.1%
16.692 1
< 0.1%
16.69 1
< 0.1%
16.689 1
< 0.1%
16.677 1
< 0.1%

위치?종점
Real number (ℝ)

HIGH CORRELATION 

Distinct3110
Distinct (%)75.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5303227
Minimum0.003
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:49.369037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.003
5-th percentile0.418
Q12.405
median4.9
Q37.94
95-th percentile13.189
Maximum71
Range70.997
Interquartile range (IQR)5.535

Descriptive statistics

Standard deviation4.030286
Coefficient of variation (CV)0.72876144
Kurtosis16.429558
Mean5.5303227
Median Absolute Deviation (MAD)2.709
Skewness1.6792284
Sum22790.46
Variance16.243205
MonotonicityNot monotonic
2023-12-11T07:49:49.479307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.772 6
 
0.1%
5.084 5
 
0.1%
14.479 5
 
0.1%
15.132 5
 
0.1%
15.057 5
 
0.1%
14.972 5
 
0.1%
14.869 5
 
0.1%
15.133 5
 
0.1%
2.31 5
 
0.1%
14.842 5
 
0.1%
Other values (3100) 4070
98.8%
ValueCountFrequency (%)
0.003 1
< 0.1%
0.005 1
< 0.1%
0.012 1
< 0.1%
0.013 1
< 0.1%
0.019 1
< 0.1%
0.026 1
< 0.1%
0.034 1
< 0.1%
0.037 1
< 0.1%
0.048 1
< 0.1%
0.05 2
< 0.1%
ValueCountFrequency (%)
71.0 1
< 0.1%
17.72 1
< 0.1%
17.21 1
< 0.1%
17.18 1
< 0.1%
17.07 1
< 0.1%
16.959 1
< 0.1%
16.957 1
< 0.1%
16.82 1
< 0.1%
16.81 1
< 0.1%
16.76 1
< 0.1%

위치?방향
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
상행
2089 
하행
2029 
중앙
 
2
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0004853
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row상행
2nd row상행
3rd row상행
4th row상행
5th row하행

Common Values

ValueCountFrequency (%)
상행 2089
50.7%
하행 2029
49.2%
중앙 2
 
< 0.1%
<NA> 1
 
< 0.1%

Length

2023-12-11T07:49:49.587693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:49:49.674826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상행 2089
50.7%
하행 2029
49.2%
중앙 2
 
< 0.1%
na 1
 
< 0.1%

연장
Real number (ℝ)

HIGH CORRELATION 

Distinct1168
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean194.11311
Minimum-5
Maximum6730
Zeros12
Zeros (%)0.3%
Negative1
Negative (%)< 0.1%
Memory size36.3 KiB
2023-12-11T07:49:49.765367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5
5-th percentile19
Q153
median108.85
Q3210
95-th percentile580
Maximum6730
Range6735
Interquartile range (IQR)157

Descriptive statistics

Standard deviation343.23141
Coefficient of variation (CV)1.7682032
Kurtosis128.81581
Mean194.11311
Median Absolute Deviation (MAD)68.15
Skewness8.7224921
Sum799940.11
Variance117807.8
MonotonicityNot monotonic
2023-12-11T07:49:49.871621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1613.0 71
 
1.7%
40.0 50
 
1.2%
60.0 39
 
0.9%
30.0 38
 
0.9%
80.0 36
 
0.9%
100.0 35
 
0.8%
34.0 34
 
0.8%
20.0 33
 
0.8%
55.0 33
 
0.8%
200.0 30
 
0.7%
Other values (1158) 3722
90.3%
ValueCountFrequency (%)
-5.0 1
 
< 0.1%
0.0 12
0.3%
2.0 3
 
0.1%
3.0 1
 
< 0.1%
4.0 3
 
0.1%
5.0 2
 
< 0.1%
5.6 1
 
< 0.1%
6.0 6
0.1%
7.0 5
0.1%
7.75 1
 
< 0.1%
ValueCountFrequency (%)
6730.0 1
< 0.1%
6600.0 1
< 0.1%
6576.0 2
< 0.1%
3446.0 1
< 0.1%
3008.0 1
< 0.1%
2690.0 1
< 0.1%
2664.0 1
< 0.1%
2564.0 1
< 0.1%
2470.0 1
< 0.1%
2417.0 1
< 0.1%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
흙사면
2008 
혼합사면
1513 
<NA>
553 
암사면
 
47

Length

Max length4
Median length4
Mean length3.5013346
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
흙사면 2008
48.7%
혼합사면 1513
36.7%
<NA> 553
 
13.4%
암사면 47
 
1.1%

Length

2023-12-11T07:49:49.975006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:49:50.055786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
흙사면 2008
48.7%
혼합사면 1513
36.7%
na 553
 
13.4%
암사면 47
 
1.1%

높이?최대
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct861
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9810827
Minimum0
Maximum4202
Zeros1742
Zeros (%)42.3%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:50.157030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.2
Q34.2
95-th percentile14.4
Maximum4202
Range4202
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation66.349546
Coefficient of variation (CV)13.320306
Kurtosis3888.8456
Mean4.9810827
Median Absolute Deviation (MAD)1.2
Skewness61.50453
Sum20527.042
Variance4402.2622
MonotonicityNot monotonic
2023-12-11T07:49:50.266901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1742
42.3%
2.0 36
 
0.9%
3.0 36
 
0.9%
1.7 35
 
0.8%
1.0 31
 
0.8%
5.0 30
 
0.7%
2.5 29
 
0.7%
4.0 29
 
0.7%
3.5 27
 
0.7%
1.2 26
 
0.6%
Other values (851) 2100
51.0%
ValueCountFrequency (%)
0.0 1742
42.3%
0.01 1
 
< 0.1%
0.03 2
 
< 0.1%
0.11 1
 
< 0.1%
0.15 1
 
< 0.1%
0.17 1
 
< 0.1%
0.19 1
 
< 0.1%
0.2 7
 
0.2%
0.23 1
 
< 0.1%
0.24 1
 
< 0.1%
ValueCountFrequency (%)
4202.0 1
< 0.1%
188.0 1
< 0.1%
180.7 1
< 0.1%
174.0 1
< 0.1%
154.0 1
< 0.1%
144.0 1
< 0.1%
138.0 1
< 0.1%
130.0 1
< 0.1%
122.0 1
< 0.1%
112.0 1
< 0.1%

높이?최소
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct285
Distinct (%)6.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2299345
Minimum0
Maximum174
Zeros3449
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-11T07:49:50.410815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1.89
Maximum174
Range174
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.6000613
Coefficient of variation (CV)7.8053437
Kurtosis131.87504
Mean1.2299345
Median Absolute Deviation (MAD)0
Skewness10.887169
Sum5068.56
Variance92.161178
MonotonicityNot monotonic
2023-12-11T07:49:50.528149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3449
83.7%
1.0 95
 
2.3%
0.1 14
 
0.3%
1.7 12
 
0.3%
2.0 10
 
0.2%
0.7 8
 
0.2%
1.2 8
 
0.2%
0.8 7
 
0.2%
0.46 7
 
0.2%
0.3 7
 
0.2%
Other values (275) 504
 
12.2%
ValueCountFrequency (%)
0.0 3449
83.7%
0.01 3
 
0.1%
0.03 1
 
< 0.1%
0.04 2
 
< 0.1%
0.05 1
 
< 0.1%
0.06 2
 
< 0.1%
0.07 1
 
< 0.1%
0.1 14
 
0.3%
0.11 2
 
< 0.1%
0.12 3
 
0.1%
ValueCountFrequency (%)
174.0 1
< 0.1%
163.0 1
< 0.1%
148.0 1
< 0.1%
142.0 1
< 0.1%
130.0 1
< 0.1%
128.0 1
< 0.1%
109.0 1
< 0.1%
104.0 1
< 0.1%
99.0 2
< 0.1%
98.89 2
< 0.1%

경사
Real number (ℝ)

ZEROS 

Distinct438
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.127991
Minimum-7
Maximum73.077
Zeros1762
Zeros (%)42.8%
Negative26
Negative (%)0.6%
Memory size36.3 KiB
2023-12-11T07:49:50.650832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7
5-th percentile0
Q10
median17.4
Q366.7
95-th percentile66.7
Maximum73.077
Range80.077
Interquartile range (IQR)66.7

Descriptive statistics

Standard deviation32.141426
Coefficient of variation (CV)1.0004181
Kurtosis-1.9404838
Mean32.127991
Median Absolute Deviation (MAD)17.4
Skewness0.076629101
Sum132399.45
Variance1033.0712
MonotonicityNot monotonic
2023-12-11T07:49:50.799575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1762
42.8%
66.7 1336
32.4%
66.6 300
 
7.3%
66.67 89
 
2.2%
66.0 23
 
0.6%
45.0 23
 
0.6%
50.0 14
 
0.3%
60.0 13
 
0.3%
66.66 12
 
0.3%
55.0 11
 
0.3%
Other values (428) 538
 
13.1%
ValueCountFrequency (%)
-7.0 1
< 0.1%
-6.89 1
< 0.1%
-6.16 2
< 0.1%
-5.99 1
< 0.1%
-5.9 2
< 0.1%
-5.84 1
< 0.1%
-5.6 1
< 0.1%
-3.4 1
< 0.1%
-3.18 1
< 0.1%
-2.51 1
< 0.1%
ValueCountFrequency (%)
73.077 1
 
< 0.1%
69.444 1
 
< 0.1%
68.75 1
 
< 0.1%
67.7 5
 
0.1%
66.96 1
 
< 0.1%
66.78 1
 
< 0.1%
66.76 1
 
< 0.1%
66.7 1336
32.4%
66.69 1
 
< 0.1%
66.68 1
 
< 0.1%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct29
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
<NA>
4036 
분리(좌측)
 
19
분리(우측)
 
19
2단
 
10
하부도로1
 
4
Other values (24)
 
33

Length

Max length13
Median length4
Mean length4.0383402
Min length2

Unique

Unique19 ?
Unique (%)0.5%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 4036
97.9%
분리(좌측) 19
 
0.5%
분리(우측) 19
 
0.5%
2단 10
 
0.2%
하부도로1 4
 
0.1%
부체도로 4
 
0.1%
본선 4
 
0.1%
램프구간 2
 
< 0.1%
분리(하행) 2
 
< 0.1%
군도64호선 2
 
< 0.1%
Other values (19) 19
 
0.5%

Length

2023-12-11T07:49:50.973758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4036
97.9%
분리(우측 19
 
0.5%
분리(좌측 19
 
0.5%
2단 10
 
0.2%
하부도로1 4
 
0.1%
부체도로 4
 
0.1%
본선 4
 
0.1%
분리(하행 2
 
< 0.1%
군도64호선 2
 
< 0.1%
램프구간 2
 
< 0.1%
Other values (19) 19
 
0.5%

공간경도시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4121
Missing (%)100.0%
Memory size36.3 KiB

공간위도시점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4121
Missing (%)100.0%
Memory size36.3 KiB

공간경도종점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4121
Missing (%)100.0%
Memory size36.3 KiB

공간위도종점
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4121
Missing (%)100.0%
Memory size36.3 KiB

Interactions

2023-12-11T07:49:47.307665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:40.969098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.202935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.087309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.001580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.862657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.657371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.386370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:47.423203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.086481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.307279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.203621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.143104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.954673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.754243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.498021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:47.552872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.198187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.407690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.332129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.235101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.057376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.847694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.611747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:47.690888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.325206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.527303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.442734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.354142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.176334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.930416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.726955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:48.044982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.440880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.646456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.572800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.474588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.288257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.016864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.845541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:48.139312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.580783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.800299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.670586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.565750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.381317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.099318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.939027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:48.218198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.693725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.883545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.755826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.654273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.472350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.173724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:47.052742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:48.318336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:41.820377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:42.975793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:43.864573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:44.752789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:45.557187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:46.271102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:49:47.190882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:49:51.058944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호구간번호위치?시점위치?종점위치?방향연장종류높이?최대높이?최소경사비고
노선번호1.0000.5180.3240.2880.1470.2280.4490.0000.1140.2940.993
구간번호0.5181.0000.2620.3520.0000.2530.1780.0000.0710.3020.955
위치?시점0.3240.2621.0000.9070.0000.2580.2190.0640.1520.2210.742
위치?종점0.2880.3520.9071.0000.0000.2520.1030.0000.2190.1180.964
위치?방향0.1470.0000.0000.0001.0000.0000.0450.0000.0650.0000.576
연장0.2280.2530.2580.2520.0001.0000.1640.0000.0000.1221.000
종류0.4490.1780.2190.1030.0450.1641.000NaN0.1260.3590.865
높이?최대0.0000.0000.0640.0000.0000.000NaN1.0000.0000.0001.000
높이?최소0.1140.0710.1520.2190.0650.0000.1260.0001.0000.2421.000
경사0.2940.3020.2210.1180.0000.1220.3590.0000.2421.0000.617
비고0.9930.9550.7420.9640.5761.0000.8651.0001.0000.6171.000
2023-12-11T07:49:51.185795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종류위치?방향비고
종류1.0000.0130.656
위치?방향0.0131.0000.378
비고0.6560.3781.000
2023-12-11T07:49:51.293227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호구간번호위치?시점위치?종점연장높이?최대높이?최소경사위치?방향종류비고
노선번호1.0000.0850.1370.131-0.131-0.231-0.0530.0590.0610.2080.822
구간번호0.0851.0000.0470.0460.015-0.183-0.1260.2400.0000.1690.700
위치?시점0.1370.0471.0000.996-0.032-0.0150.0340.1120.0000.1330.373
위치?종점0.1310.0460.9961.0000.008-0.0110.0430.1060.0000.0970.740
연장-0.1310.015-0.0320.0081.0000.1910.150-0.0800.0000.1250.829
높이?최대-0.231-0.183-0.015-0.0110.1911.0000.4570.2990.0001.0000.829
높이?최소-0.053-0.1260.0340.0430.1500.4571.000-0.2430.0280.0800.829
경사0.0590.2400.1120.106-0.0800.299-0.2431.0000.0000.2310.229
위치?방향0.0610.0000.0000.0000.0000.0000.0280.0001.0000.0130.378
종류0.2080.1690.1330.0970.1251.0000.0800.2310.0131.0000.656
비고0.8220.7000.3730.7400.8290.8290.8290.2290.3780.6561.000

Missing values

2023-12-11T07:49:48.449603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:49:48.601172image/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

노선번호구간번호위치?시점위치?종점위치?방향연장종류높이?최대높이?최소경사비고공간경도시점공간위도시점공간경도종점공간위도종점
0391816.6316.81상행180.0혼합사면28.21.5454.81<NA><NA><NA><NA><NA>
1391816.8817.07상행190.0혼합사면5.730.610.33<NA><NA><NA><NA><NA>
2391817.4817.72상행240.0혼합사면8.460.1115.25<NA><NA><NA><NA><NA>
339169.0539.065상행12.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
439169.0669.21하행144.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
539169.0699.223상행154.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
639169.2259.31상행85.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
7391610.04810.143하행95.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
839169.09.036하행36.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
939169.09.039상행39.0혼합사면0.00.00.0<NA><NA><NA><NA><NA>
노선번호구간번호위치?시점위치?종점위치?방향연장종류높이?최대높이?최소경사비고공간경도시점공간위도시점공간경도종점공간위도종점
411132514.1844.37상행186.0혼합사면1.281.232.3<NA><NA><NA><NA><NA>
411232514.684.745상행65.0혼합사면5.650.7810.19<NA><NA><NA><NA><NA>
411332514.684.8하행120.0혼합사면6.311.0311.38<NA><NA><NA><NA><NA>
411432516.0546.124상행70.0혼합사면0.990.871.78<NA><NA><NA><NA><NA>
411532516.0546.254하행200.0혼합사면4.320.997.79<NA><NA><NA><NA><NA>
411632516.6746.756하행80.53흙사면6.40.066.6<NA><NA><NA><NA><NA>
411732516.7646.914하행144.27흙사면8.60.066.6<NA><NA><NA><NA><NA>
411832516.7766.914상행143.33흙사면8.50.066.6<NA><NA><NA><NA><NA>
411932516.9687.089하행119.48흙사면4.80.066.6<NA><NA><NA><NA><NA>
412032516.9697.068상행103.55흙사면5.20.066.6<NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

노선번호구간번호위치?시점위치?종점위치?방향연장종류높이?최대높이?최소경사비고# duplicates
3330512.9673.258하행288.0흙사면11.70.00.0<NA>3
3430513.5753.781상행206.0흙사면7.50.00.0<NA>3
3530513.5853.779하행194.0흙사면4.70.00.0<NA>3
3630513.7854.081상행295.0흙사면7.50.00.0<NA>3
3730513.7874.093하행306.0흙사면5.20.00.0<NA>3
3830514.0934.215상행122.0흙사면4.00.00.0<NA>3
3930514.1054.22하행115.0흙사면4.90.00.0<NA>3
4030514.2284.313하행85.0흙사면5.90.00.0<NA>3
4130514.2624.457상행195.0흙사면1.10.00.0<NA>3
4230514.3594.428하행69.0흙사면4.70.00.0<NA>3