Overview

Dataset statistics

Number of variables13
Number of observations389
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.6 KiB
Average record size in memory117.3 B

Variable types

Numeric8
Categorical5

Dataset

Description경상남도 도로대장전산화 시스템 데이터의 중장기개방계획에 따른 데이터입니다. 시스템 상에서의 우회도로 및 구간정보를 가지고 있으며, 도로대장의 오르막차로 데이터를 포함하고있습니다.
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15091956

Alerts

관리기관 has constant value ""Constant
이력코드 has constant value ""Constant
식별번호 is highly overall correlated with 구간번호High correlation
노선번호 is highly overall correlated with 도로종류 and 1 other fieldsHigh correlation
구간번호 is highly overall correlated with 식별번호High correlation
위치_시점 is highly overall correlated with 위치_종점High correlation
위치_종점 is highly overall correlated with 위치_시점High correlation
오르막차로의 폭원 is highly overall correlated with 경사 and 3 other fieldsHigh correlation
경사 is highly overall correlated with 오르막차로의 폭원 and 3 other fieldsHigh correlation
도로종류 is highly overall correlated with 노선번호 and 3 other fieldsHigh correlation
위치_방향 is highly overall correlated with 오르막차로의 폭원 and 1 other fieldsHigh correlation
차로수 is highly overall correlated with 노선번호 and 3 other fieldsHigh correlation
도로종류 is highly imbalanced (90.1%)Imbalance
차로수 is highly imbalanced (79.3%)Imbalance
식별번호 has unique valuesUnique
위치_시점 has 11 (2.8%) zerosZeros
연장 has 111 (28.5%) zerosZeros
오르막차로의 폭원 has 378 (97.2%) zerosZeros
경사 has 381 (97.9%) zerosZeros

Reproduction

Analysis started2023-12-11 00:45:56.946668
Analysis finished2023-12-11 00:46:04.086612
Duration7.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

식별번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct389
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean195
Minimum1
Maximum389
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:04.191916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.4
Q198
median195
Q3292
95-th percentile369.6
Maximum389
Range388
Interquartile range (IQR)194

Descriptive statistics

Standard deviation112.43887
Coefficient of variation (CV)0.5766096
Kurtosis-1.2
Mean195
Median Absolute Deviation (MAD)97
Skewness0
Sum75855
Variance12642.5
MonotonicityStrictly increasing
2023-12-11T09:46:04.335089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
245 1
 
0.3%
267 1
 
0.3%
266 1
 
0.3%
265 1
 
0.3%
264 1
 
0.3%
263 1
 
0.3%
262 1
 
0.3%
261 1
 
0.3%
260 1
 
0.3%
Other values (379) 379
97.4%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
389 1
0.3%
388 1
0.3%
387 1
0.3%
386 1
0.3%
385 1
0.3%
384 1
0.3%
383 1
0.3%
382 1
0.3%
381 1
0.3%
380 1
0.3%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
1683
389 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1683
2nd row1683
3rd row1683
4th row1683
5th row1683

Common Values

ValueCountFrequency (%)
1683 389
100.0%

Length

2023-12-11T09:46:04.465218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:46:04.576302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1683 389
100.0%

도로종류
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
1504
384 
1507
 
5

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1504
2nd row1504
3rd row1504
4th row1504
5th row1504

Common Values

ValueCountFrequency (%)
1504 384
98.7%
1507 5
 
1.3%

Length

2023-12-11T09:46:04.662431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:46:04.747557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1504 384
98.7%
1507 5
 
1.3%

노선번호
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1015.8355
Minimum37
Maximum1077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:04.824509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile1004.4
Q11020
median1041
Q31041
95-th percentile1041
Maximum1077
Range1040
Interquartile range (IQR)21

Descriptive statistics

Standard deviation111.54163
Coefficient of variation (CV)0.10980285
Kurtosis71.25228
Mean1015.8355
Median Absolute Deviation (MAD)0
Skewness-8.460915
Sum395160
Variance12441.535
MonotonicityNot monotonic
2023-12-11T09:46:04.922766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1041 197
50.6%
1005 63
 
16.2%
1020 51
 
13.1%
1023 37
 
9.5%
1026 20
 
5.1%
1004 15
 
3.9%
37 3
 
0.8%
60 1
 
0.3%
69 1
 
0.3%
1077 1
 
0.3%
ValueCountFrequency (%)
37 3
 
0.8%
60 1
 
0.3%
69 1
 
0.3%
1004 15
 
3.9%
1005 63
 
16.2%
1020 51
 
13.1%
1023 37
 
9.5%
1026 20
 
5.1%
1041 197
50.6%
1077 1
 
0.3%
ValueCountFrequency (%)
1077 1
 
0.3%
1041 197
50.6%
1026 20
 
5.1%
1023 37
 
9.5%
1020 51
 
13.1%
1005 63
 
16.2%
1004 15
 
3.9%
69 1
 
0.3%
60 1
 
0.3%
37 3
 
0.8%

구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8329049
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:05.022537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.3342689
Coefficient of variation (CV)0.48299501
Kurtosis-1.1506926
Mean4.8329049
Median Absolute Deviation (MAD)2
Skewness-0.23207579
Sum1880
Variance5.4488114
MonotonicityNot monotonic
2023-12-11T09:46:05.127572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3 70
18.0%
8 66
17.0%
6 63
16.2%
1 56
14.4%
5 52
13.4%
7 46
11.8%
4 27
 
6.9%
2 9
 
2.3%
ValueCountFrequency (%)
1 56
14.4%
2 9
 
2.3%
3 70
18.0%
4 27
 
6.9%
5 52
13.4%
6 63
16.2%
7 46
11.8%
8 66
17.0%
ValueCountFrequency (%)
8 66
17.0%
7 46
11.8%
6 63
16.2%
5 52
13.4%
4 27
 
6.9%
3 70
18.0%
2 9
 
2.3%
1 56
14.4%

이력코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
389 

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 (%)
0 389
100.0%

Length

2023-12-11T09:46:05.244347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:46:05.347749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 389
100.0%

위치_시점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct295
Distinct (%)75.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0774781
Minimum0
Maximum16.16
Zeros11
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:05.457709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.108
Q11.74
median4.46
Q38.04
95-th percentile12.8172
Maximum16.16
Range16.16
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation4.0110835
Coefficient of variation (CV)0.78997553
Kurtosis-0.15051223
Mean5.0774781
Median Absolute Deviation (MAD)3.06
Skewness0.7156624
Sum1975.139
Variance16.088791
MonotonicityNot monotonic
2023-12-11T09:46:05.585044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 11
 
2.8%
0.28 4
 
1.0%
2.1 3
 
0.8%
0.02 3
 
0.8%
0.9 3
 
0.8%
0.08 3
 
0.8%
2.78 3
 
0.8%
5.2 3
 
0.8%
4.74 3
 
0.8%
4.08 3
 
0.8%
Other values (285) 350
90.0%
ValueCountFrequency (%)
0.0 11
2.8%
0.02 3
 
0.8%
0.04 1
 
0.3%
0.05 1
 
0.3%
0.08 3
 
0.8%
0.1 1
 
0.3%
0.12 2
 
0.5%
0.14 3
 
0.8%
0.16 3
 
0.8%
0.18 1
 
0.3%
ValueCountFrequency (%)
16.16 1
0.3%
16.08 1
0.3%
16.04 1
0.3%
15.98 1
0.3%
15.74 1
0.3%
15.6 1
0.3%
15.33 1
0.3%
15.08 2
0.5%
14.94 1
0.3%
14.86 1
0.3%

위치_종점
Real number (ℝ)

HIGH CORRELATION 

Distinct308
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2523702
Minimum0.02
Maximum16.18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:05.707548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.188
Q11.9
median4.6
Q38.22
95-th percentile13.712
Maximum16.18
Range16.16
Interquartile range (IQR)6.32

Descriptive statistics

Standard deviation4.0314888
Coefficient of variation (CV)0.76755611
Kurtosis-0.15911534
Mean5.2523702
Median Absolute Deviation (MAD)3
Skewness0.71103505
Sum2043.172
Variance16.252902
MonotonicityNot monotonic
2023-12-11T09:46:05.833633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.28 4
 
1.0%
4.6 3
 
0.8%
0.08 3
 
0.8%
0.2 3
 
0.8%
0.14 3
 
0.8%
2.78 3
 
0.8%
0.9 3
 
0.8%
0.16 3
 
0.8%
2.1 3
 
0.8%
9.3 3
 
0.8%
Other values (298) 358
92.0%
ValueCountFrequency (%)
0.02 2
0.5%
0.04 1
 
0.3%
0.05 1
 
0.3%
0.06 1
 
0.3%
0.08 3
0.8%
0.1 2
0.5%
0.12 2
0.5%
0.14 3
0.8%
0.15 1
 
0.3%
0.16 3
0.8%
ValueCountFrequency (%)
16.18 1
0.3%
16.16 1
0.3%
16.08 1
0.3%
16.04 1
0.3%
15.98 1
0.3%
15.74 1
0.3%
15.6 1
0.3%
15.33 1
0.3%
15.122 1
0.3%
15.08 2
0.5%

위치_방향
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
<NA>
197 
0
188 
1
 
4

Length

Max length4
Median length4
Mean length2.5192802
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 197
50.6%
0 188
48.3%
1 4
 
1.0%

Length

2023-12-11T09:46:05.962873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:46:06.073569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 197
50.6%
0 188
48.3%
1 4
 
1.0%

연장
Real number (ℝ)

ZEROS 

Distinct50
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.43702
Minimum0
Maximum1840
Zeros111
Zeros (%)28.5%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:06.199222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median80
Q3160
95-th percentile352
Maximum1840
Range1840
Interquartile range (IQR)160

Descriptive statistics

Standard deviation179.16924
Coefficient of variation (CV)1.4754088
Kurtosis32.599581
Mean121.43702
Median Absolute Deviation (MAD)80
Skewness4.7278076
Sum47239
Variance32101.618
MonotonicityNot monotonic
2023-12-11T09:46:06.321974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 111
28.5%
80 32
 
8.2%
140 32
 
8.2%
100 30
 
7.7%
60 23
 
5.9%
120 22
 
5.7%
160 17
 
4.4%
200 13
 
3.3%
40 12
 
3.1%
180 11
 
2.8%
Other values (40) 86
22.1%
ValueCountFrequency (%)
0 111
28.5%
20 7
 
1.8%
32 1
 
0.3%
40 12
 
3.1%
42 1
 
0.3%
50 5
 
1.3%
60 23
 
5.9%
70 2
 
0.5%
76 1
 
0.3%
80 32
 
8.2%
ValueCountFrequency (%)
1840 1
0.3%
1350 1
0.3%
1100 2
0.5%
1004 1
0.3%
722 1
0.3%
693 1
0.3%
675 1
0.3%
600 1
0.3%
560 1
0.3%
540 1
0.3%

차로수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
0
365 
2
 
15
1
 
6
3
 
3

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 (%)
0 365
93.8%
2 15
 
3.9%
1 6
 
1.5%
3 3
 
0.8%

Length

2023-12-11T09:46:06.441541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:46:06.539642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 365
93.8%
2 15
 
3.9%
1 6
 
1.5%
3 3
 
0.8%

오르막차로의 폭원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct8
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1092545
Minimum0
Maximum8
Zeros378
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:06.621618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.69070912
Coefficient of variation (CV)6.3220199
Kurtosis61.4496
Mean0.1092545
Median Absolute Deviation (MAD)0
Skewness7.3326624
Sum42.5
Variance0.47707908
MonotonicityNot monotonic
2023-12-11T09:46:06.719489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 378
97.2%
3.0 4
 
1.0%
3.5 2
 
0.5%
8.0 1
 
0.3%
4.0 1
 
0.3%
2.0 1
 
0.3%
5.0 1
 
0.3%
4.5 1
 
0.3%
ValueCountFrequency (%)
0.0 378
97.2%
2.0 1
 
0.3%
3.0 4
 
1.0%
3.5 2
 
0.5%
4.0 1
 
0.3%
4.5 1
 
0.3%
5.0 1
 
0.3%
8.0 1
 
0.3%
ValueCountFrequency (%)
8.0 1
 
0.3%
5.0 1
 
0.3%
4.5 1
 
0.3%
4.0 1
 
0.3%
3.5 2
 
0.5%
3.0 4
 
1.0%
2.0 1
 
0.3%
0.0 378
97.2%

경사
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1722365
Minimum0
Maximum15.4
Zeros381
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-11T09:46:06.810578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15.4
Range15.4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2788729
Coefficient of variation (CV)7.4250978
Kurtosis77.104921
Mean0.1722365
Median Absolute Deviation (MAD)0
Skewness8.382028
Sum67
Variance1.6355159
MonotonicityNot monotonic
2023-12-11T09:46:06.896693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 381
97.9%
5.0 2
 
0.5%
10.0 2
 
0.5%
8.6 1
 
0.3%
15.4 1
 
0.3%
7.0 1
 
0.3%
6.0 1
 
0.3%
ValueCountFrequency (%)
0.0 381
97.9%
5.0 2
 
0.5%
6.0 1
 
0.3%
7.0 1
 
0.3%
8.6 1
 
0.3%
10.0 2
 
0.5%
15.4 1
 
0.3%
ValueCountFrequency (%)
15.4 1
 
0.3%
10.0 2
 
0.5%
8.6 1
 
0.3%
7.0 1
 
0.3%
6.0 1
 
0.3%
5.0 2
 
0.5%
0.0 381
97.9%

Interactions

2023-12-11T09:46:02.962507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.401330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.531492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.204079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.988265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.722821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.406256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.158703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.067745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.504394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.628462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.313851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.099985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.807190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.511946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.245498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.149322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.614321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.705939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.394923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.183268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.881882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.606112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.327315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.460477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.738138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.789231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.480123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.292538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.965701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.690219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.415299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.537041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.848924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.873921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.579090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.382551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.051526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.775997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.527269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.613717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:57.966684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.951145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.710350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.470003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.134579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.864237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.639912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.690909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.060468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.030919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.792467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.554291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.217732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.962132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.736016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:03.772166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:58.152694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.114415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:45:59.889945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:00.639874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:01.309320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.070924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:46:02.874336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:46:06.984872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식별번호도로종류노선번호구간번호위치_시점위치_종점위치_방향연장차로수오르막차로의 폭원경사
식별번호1.0000.4110.4110.8870.7540.7550.2220.2790.5840.2490.095
도로종류0.4111.0000.9870.5990.2830.2540.4710.1910.9071.0000.885
노선번호0.4110.9871.0000.5990.2830.2540.4710.1910.9071.0000.885
구간번호0.8870.5990.5991.0000.5640.5530.0700.2800.6230.3430.371
위치_시점0.7540.2830.2830.5641.0000.9960.6450.2630.2200.1510.341
위치_종점0.7550.2540.2540.5530.9961.0000.4280.3570.2080.0880.307
위치_방향0.2220.4710.4710.0700.6450.4281.0000.6540.6720.6380.922
연장0.2790.1910.1910.2800.2630.3570.6541.0000.6030.8160.646
차로수0.5840.9070.9070.6230.2200.2080.6720.6031.0000.8320.755
오르막차로의 폭원0.2491.0001.0000.3430.1510.0880.6380.8160.8321.0000.892
경사0.0950.8850.8850.3710.3410.3070.9220.6460.7550.8921.000
2023-12-11T09:46:07.104398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로종류차로수위치_방향
도로종류1.0000.7220.312
차로수0.7221.0000.470
위치_방향0.3120.4701.000
2023-12-11T09:46:07.211517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
식별번호노선번호구간번호위치_시점위치_종점연장오르막차로의 폭원경사도로종류위치_방향차로수
식별번호1.0000.4120.7420.1720.1640.216-0.013-0.0280.3120.1580.387
노선번호0.4121.0000.4240.0370.0230.454-0.192-0.1290.8980.3120.722
구간번호0.7420.4241.0000.0950.083-0.062-0.141-0.1230.4500.0840.317
위치_시점0.1720.0370.0951.0000.9980.1090.0660.0150.2150.4820.132
위치_종점0.1640.0230.0830.9981.0000.1130.0860.0380.1930.3170.126
연장0.2160.454-0.0620.1090.1131.0000.2140.2040.2030.4730.460
오르막차로의 폭원-0.013-0.192-0.1410.0660.0860.2141.0000.8550.9940.7390.797
경사-0.028-0.129-0.1230.0150.0380.2040.8551.0000.6960.7430.591
도로종류0.3120.8980.4500.2150.1930.2030.9940.6961.0000.3120.722
위치_방향0.1580.3120.0840.4820.3170.4730.7390.7430.3121.0000.470
차로수0.3870.7220.3170.1320.1260.4600.7970.5910.7220.4701.000

Missing values

2023-12-11T09:46:03.882213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:46:04.024876image/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

식별번호관리기관도로종류노선번호구간번호이력코드위치_시점위치_종점위치_방향연장차로수오르막차로의 폭원경사
01168315041041301.141.26<NA>12000.00.0
12168315041041300.70.78<NA>8000.00.0
23168315041041309.849.94<NA>10000.00.0
34168315041041300.50.7<NA>20000.00.0
45168315041041302.92.98<NA>8000.00.0
56168315041041300.780.88<NA>10000.00.0
67168315041041300.240.4<NA>16000.00.0
78168315041041301.31.7<NA>40000.00.0
89168315041041301.741.9<NA>16000.00.0
910168315041041301.90.06<NA>184000.00.0
식별번호관리기관도로종류노선번호구간번호이력코드위치_시점위치_종점위치_방향연장차로수오르막차로의 폭원경사
3793801683150410418014.5614.86<NA>30000.00.0
3803811683150410418014.8614.94<NA>8000.00.0
3813821683150410418014.9415.08<NA>14000.00.0
3823831683150410418015.0815.33<NA>25000.00.0
3833841683150410418015.3315.6<NA>27000.00.0
3843851683150410418015.615.74<NA>14000.00.0
3853861683150410418015.7415.98<NA>24000.00.0
3863871683150410418015.9816.04<NA>6000.00.0
3873881683150410418016.0416.08<NA>4000.00.0
3883891683150410418014.0814.18<NA>10000.00.0