Overview

Dataset statistics

Number of variables16
Number of observations8910
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory138.0 B

Variable types

Numeric6
Categorical9
Text1

Dataset

Description도시정보시스템 도로에 대한 중심선의 지형지물부호, 도로구간번호, 행정읍면동, 도엽번호, 관리기관, 구간구분, 중용여부, 도로연장, 도로면적, 도로폭원, 구간연결 등에 관한 정보
Author경상남도 통영시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15063179

Alerts

지형지물부호 has constant value ""Constant
관리기관 has constant value ""Constant
오르막차로관리번호 has constant value ""Constant
우회도로관리번호 has constant value ""Constant
구간구분 is highly overall correlated with 대장초기화여부High correlation
대장초기화여부 is highly overall correlated with 구간구분High correlation
도로연장 is highly overall correlated with 도로면적 and 1 other fieldsHigh correlation
도로면적 is highly overall correlated with 도로연장High correlation
구간연결 is highly overall correlated with 도로연장High correlation
구간구분 is highly imbalanced (96.6%)Imbalance
도로중심선교점관리번호 is highly imbalanced (97.8%)Imbalance
대장초기화여부 is highly imbalanced (99.8%)Imbalance
아이디 has unique valuesUnique
도로폭원 has 121 (1.4%) zerosZeros
구간연결 has 3722 (41.8%) zerosZeros

Reproduction

Analysis started2023-12-11 00:36:07.687238
Analysis finished2023-12-11 00:36:14.472473
Duration6.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

UNIQUE 

Distinct8910
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4455.5
Minimum1
Maximum8910
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:14.550230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile446.45
Q12228.25
median4455.5
Q36682.75
95-th percentile8464.55
Maximum8910
Range8909
Interquartile range (IQR)4454.5

Descriptive statistics

Standard deviation2572.2398
Coefficient of variation (CV)0.57731787
Kurtosis-1.2
Mean4455.5
Median Absolute Deviation (MAD)2227.5
Skewness0
Sum39698505
Variance6616417.5
MonotonicityStrictly increasing
2023-12-11T09:36:14.684278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5944 1
 
< 0.1%
5938 1
 
< 0.1%
5939 1
 
< 0.1%
5940 1
 
< 0.1%
5941 1
 
< 0.1%
5942 1
 
< 0.1%
5943 1
 
< 0.1%
5945 1
 
< 0.1%
5953 1
 
< 0.1%
Other values (8900) 8900
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8910 1
< 0.1%
8909 1
< 0.1%
8908 1
< 0.1%
8907 1
< 0.1%
8906 1
< 0.1%
8905 1
< 0.1%
8904 1
< 0.1%
8903 1
< 0.1%
8902 1
< 0.1%
8901 1
< 0.1%

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
도로중심선
8910 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
도로중심선 8910
100.0%

Length

2023-12-11T09:36:14.826862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:14.916145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도로중심선 8910
100.0%

도로구간번호
Real number (ℝ)

Distinct8773
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5455296.9
Minimum0
Maximum2.02301 × 109
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:15.025720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile478.45
Q12465.25
median6291.5
Q38835.75
95-th percentile11085.55
Maximum2.02301 × 109
Range2.02301 × 109
Interquartile range (IQR)6370.5

Descriptive statistics

Standard deviation1.0476906 × 108
Coefficient of variation (CV)19.205016
Kurtosis366.45902
Mean5455296.9
Median Absolute Deviation (MAD)3152
Skewness19.193142
Sum4.8606695 × 1010
Variance1.0976556 × 1016
MonotonicityNot monotonic
2023-12-11T09:36:15.178715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
0.1%
13507 3
 
< 0.1%
10114 2
 
< 0.1%
10014 2
 
< 0.1%
10121 2
 
< 0.1%
10032 2
 
< 0.1%
10035 2
 
< 0.1%
10036 2
 
< 0.1%
10037 2
 
< 0.1%
10048 2
 
< 0.1%
Other values (8763) 8885
99.7%
ValueCountFrequency (%)
0 6
0.1%
1 1
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
2023010002 1
< 0.1%
2023010001 1
< 0.1%
2022080001 1
< 0.1%
2021120008 1
< 0.1%
2021120007 1
< 0.1%
2021120006 1
< 0.1%
2021120005 1
< 0.1%
2021120004 1
< 0.1%
2021120003 1
< 0.1%
2021120002 1
< 0.1%

행정읍면동
Categorical

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
사량면
4305 
광도면
1677 
용남면
1114 
도산면
697 
한산면
 
374
Other values (11)
743 

Length

Max length4
Median length3
Mean length3.0016835
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
사량면 4305
48.3%
광도면 1677
 
18.8%
용남면 1114
 
12.5%
도산면 697
 
7.8%
한산면 374
 
4.2%
산양읍 369
 
4.1%
욕지면 326
 
3.7%
북신동 19
 
0.2%
<NA> 18
 
0.2%
당동 3
 
< 0.1%
Other values (6) 8
 
0.1%

Length

2023-12-11T09:36:15.342235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사량면 4305
48.3%
광도면 1677
 
18.8%
용남면 1114
 
12.5%
도산면 697
 
7.8%
한산면 374
 
4.2%
산양읍 369
 
4.1%
욕지면 326
 
3.7%
북신동 19
 
0.2%
na 18
 
0.2%
당동 3
 
< 0.1%
Other values (6) 8
 
0.1%

도엽번호
Text

Distinct1030
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
2023-12-11T09:36:15.595503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters89100
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)3.4%

Sample

1st row348021424D
2nd row348021424C
3rd row348021424C
4th row348021425C
5th row348021425C
ValueCountFrequency (%)
348021915d 123
 
1.4%
348021915c 117
 
1.3%
348021917a 96
 
1.1%
348021935c 84
 
0.9%
348021934d 83
 
0.9%
348021487c 73
 
0.8%
348021444d 73
 
0.8%
348021485b 73
 
0.8%
348021476c 72
 
0.8%
348021486d 72
 
0.8%
Other values (1020) 8044
90.3%
2023-12-11T09:36:15.936462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 14234
16.0%
0 11721
13.2%
3 11600
13.0%
8 11437
12.8%
2 10916
12.3%
1 9856
11.1%
9 4348
 
4.9%
5 2858
 
3.2%
D 2345
 
2.6%
B 2270
 
2.5%
Other values (4) 7515
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80190
90.0%
Uppercase Letter 8910
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 14234
17.8%
0 11721
14.6%
3 11600
14.5%
8 11437
14.3%
2 10916
13.6%
1 9856
12.3%
9 4348
 
5.4%
5 2858
 
3.6%
7 1645
 
2.1%
6 1575
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
D 2345
26.3%
B 2270
25.5%
C 2190
24.6%
A 2105
23.6%

Most occurring scripts

ValueCountFrequency (%)
Common 80190
90.0%
Latin 8910
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 14234
17.8%
0 11721
14.6%
3 11600
14.5%
8 11437
14.3%
2 10916
13.6%
1 9856
12.3%
9 4348
 
5.4%
5 2858
 
3.6%
7 1645
 
2.1%
6 1575
 
2.0%
Latin
ValueCountFrequency (%)
D 2345
26.3%
B 2270
25.5%
C 2190
24.6%
A 2105
23.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 89100
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 14234
16.0%
0 11721
13.2%
3 11600
13.0%
8 11437
12.8%
2 10916
12.3%
1 9856
11.1%
9 4348
 
4.9%
5 2858
 
3.2%
D 2345
 
2.6%
B 2270
 
2.5%
Other values (4) 7515
8.4%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
통영시
8910 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
통영시 8910
100.0%

Length

2023-12-11T09:36:16.057767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:16.161797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
통영시 8910
100.0%

구간구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
차도구간
8831 
교량구간
 
42
지하차도
 
23
<NA>
 
11
터널구간
 
2

Length

Max length4
Median length4
Mean length3.9998878
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
차도구간 8831
99.1%
교량구간 42
 
0.5%
지하차도 23
 
0.3%
<NA> 11
 
0.1%
터널구간 2
 
< 0.1%
미분류 1
 
< 0.1%

Length

2023-12-11T09:36:16.249407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:16.352487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
차도구간 8831
99.1%
교량구간 42
 
0.5%
지하차도 23
 
0.3%
na 11
 
0.1%
터널구간 2
 
< 0.1%
미분류 1
 
< 0.1%

중용여부
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
미분류
3534 
연결선(가노선)
1723 
일반도로(구간속성)
1514 
일반도로(구간속성아님)
1507 
우선도로(구간속성아님)
 
158
Other values (4)
474 

Length

Max length12
Median length10
Mean length7.243771
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미분류
2nd row일반도로(구간속성)
3rd row미분류
4th row부속도로(구간속성아님)
5th row우선도로(구간속성아님)

Common Values

ValueCountFrequency (%)
미분류 3534
39.7%
연결선(가노선) 1723
19.3%
일반도로(구간속성) 1514
17.0%
일반도로(구간속성아님) 1507
16.9%
우선도로(구간속성아님) 158
 
1.8%
우선도로(구간속성) 158
 
1.8%
부속도로(구간속성아님) 157
 
1.8%
부속도로(구간속성) 156
 
1.8%
중용도로 3
 
< 0.1%

Length

2023-12-11T09:36:16.514449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:16.911408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미분류 3534
39.7%
연결선(가노선 1723
19.3%
일반도로(구간속성 1514
17.0%
일반도로(구간속성아님 1507
16.9%
우선도로(구간속성아님 158
 
1.8%
우선도로(구간속성 158
 
1.8%
부속도로(구간속성아님 157
 
1.8%
부속도로(구간속성 156
 
1.8%
중용도로 3
 
< 0.1%

도로연장
Real number (ℝ)

HIGH CORRELATION 

Distinct4437
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.264131
Minimum0
Maximum3836.93
Zeros86
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:17.050827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.44
Q15.34
median10.555
Q345.665
95-th percentile257.4755
Maximum3836.93
Range3836.93
Interquartile range (IQR)40.325

Descriptive statistics

Standard deviation176.44728
Coefficient of variation (CV)2.8801074
Kurtosis110.50244
Mean61.264131
Median Absolute Deviation (MAD)6.975
Skewness8.6476813
Sum545863.41
Variance31133.641
MonotonicityNot monotonic
2023-12-11T09:36:17.250736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 86
 
1.0%
4.0 18
 
0.2%
6.01 15
 
0.2%
4.07 14
 
0.2%
5.01 14
 
0.2%
2.59 14
 
0.2%
5.05 14
 
0.2%
7.5 14
 
0.2%
3.81 14
 
0.2%
3.94 14
 
0.2%
Other values (4427) 8693
97.6%
ValueCountFrequency (%)
0.0 86
1.0%
0.77 1
 
< 0.1%
0.87 1
 
< 0.1%
0.95 1
 
< 0.1%
0.98 1
 
< 0.1%
1.03 2
 
< 0.1%
1.05 1
 
< 0.1%
1.08 1
 
< 0.1%
1.16 1
 
< 0.1%
1.19 3
 
< 0.1%
ValueCountFrequency (%)
3836.93 1
< 0.1%
3319.25 1
< 0.1%
3238.39 1
< 0.1%
3186.05 1
< 0.1%
2922.01 1
< 0.1%
2729.49 1
< 0.1%
2454.52 1
< 0.1%
2394.25 1
< 0.1%
2332.98 1
< 0.1%
2101.59 1
< 0.1%

도로면적
Real number (ℝ)

HIGH CORRELATION 

Distinct5110
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean719.84307
Minimum0
Maximum42023.48
Zeros43
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:17.401264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile34.2115
Q1105.06
median228.4
Q3591.1125
95-th percentile2979.916
Maximum42023.48
Range42023.48
Interquartile range (IQR)486.0525

Descriptive statistics

Standard deviation1763.1266
Coefficient of variation (CV)2.4493208
Kurtosis104.22649
Mean719.84307
Median Absolute Deviation (MAD)159.365
Skewness8.0680707
Sum6413801.7
Variance3108615.4
MonotonicityNot monotonic
2023-12-11T09:36:17.548465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 43
 
0.5%
29.22 7
 
0.1%
104.39 7
 
0.1%
329.6 7
 
0.1%
61.8 7
 
0.1%
197.65 7
 
0.1%
42.29 7
 
0.1%
171.98 7
 
0.1%
113.4 7
 
0.1%
319.89 7
 
0.1%
Other values (5100) 8804
98.8%
ValueCountFrequency (%)
0.0 43
0.5%
3.01 3
 
< 0.1%
3.62 3
 
< 0.1%
4.71 2
 
< 0.1%
6.19 1
 
< 0.1%
9.14 3
 
< 0.1%
9.63 2
 
< 0.1%
11.21 1
 
< 0.1%
11.32 1
 
< 0.1%
11.49 3
 
< 0.1%
ValueCountFrequency (%)
42023.48 1
< 0.1%
37074.44 1
< 0.1%
29601.26 1
< 0.1%
26489.14 1
< 0.1%
24793.1 1
< 0.1%
23985.55 1
< 0.1%
23711.27 1
< 0.1%
21624.49 1
< 0.1%
21577.32 1
< 0.1%
20226.21 1
< 0.1%

도로폭원
Real number (ℝ)

ZEROS 

Distinct2674
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.741146
Minimum0
Maximum79.71
Zeros121
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:17.691389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.0945
Q17.29
median10.21
Q317.4775
95-th percentile35.823
Maximum79.71
Range79.71
Interquartile range (IQR)10.1875

Descriptive statistics

Standard deviation10.414969
Coefficient of variation (CV)0.75794032
Kurtosis5.9811448
Mean13.741146
Median Absolute Deviation (MAD)4.33
Skewness2.1160811
Sum122433.61
Variance108.47157
MonotonicityNot monotonic
2023-12-11T09:36:17.857348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 121
 
1.4%
8.0 74
 
0.8%
10.0 38
 
0.4%
4.0 36
 
0.4%
7.98 29
 
0.3%
8.21 27
 
0.3%
7.0 25
 
0.3%
4.5 25
 
0.3%
8.3 25
 
0.3%
6.0 24
 
0.3%
Other values (2664) 8486
95.2%
ValueCountFrequency (%)
0.0 121
1.4%
1.2 1
 
< 0.1%
1.91 1
 
< 0.1%
2.18 1
 
< 0.1%
2.21 5
 
0.1%
2.38 1
 
< 0.1%
2.42 1
 
< 0.1%
2.47 2
 
< 0.1%
2.51 1
 
< 0.1%
2.54 1
 
< 0.1%
ValueCountFrequency (%)
79.71 1
< 0.1%
79.5 1
< 0.1%
79.2 1
< 0.1%
78.29 1
< 0.1%
78.24 1
< 0.1%
77.81 1
< 0.1%
77.45 1
< 0.1%
77.14 1
< 0.1%
74.67 1
< 0.1%
72.88 1
< 0.1%

구간연결
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1674
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4022.396
Minimum0
Maximum160052
Zeros3722
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size78.4 KiB
2023-12-11T09:36:18.011668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1263
Q36563.75
95-th percentile10185
Maximum160052
Range160052
Interquartile range (IQR)6563.75

Descriptive statistics

Standard deviation12400.437
Coefficient of variation (CV)3.0828485
Kurtosis140.51189
Mean4022.396
Median Absolute Deviation (MAD)1263
Skewness11.401997
Sum35839548
Variance1.5377085 × 108
MonotonicityNot monotonic
2023-12-11T09:36:18.163001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3722
41.8%
5299 5
 
0.1%
160034 5
 
0.1%
1964 5
 
0.1%
692 5
 
0.1%
6954 5
 
0.1%
5310 5
 
0.1%
5569 5
 
0.1%
7882 5
 
0.1%
2556 5
 
0.1%
Other values (1664) 5143
57.7%
ValueCountFrequency (%)
0 3722
41.8%
1 3
 
< 0.1%
4 3
 
< 0.1%
7 3
 
< 0.1%
9 3
 
< 0.1%
13 4
 
< 0.1%
22 4
 
< 0.1%
26 3
 
< 0.1%
28 3
 
< 0.1%
33 3
 
< 0.1%
ValueCountFrequency (%)
160052 1
< 0.1%
160051 1
< 0.1%
160050 1
< 0.1%
160048 1
< 0.1%
160047 1
< 0.1%
160046 1
< 0.1%
160045 1
< 0.1%
160043 1
< 0.1%
160042 1
< 0.1%
160041 1
< 0.1%

도로중심선교점관리번호
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
0
8891 
2
 
19

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 8891
99.8%
2 19
 
0.2%

Length

2023-12-11T09:36:18.306375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:18.424832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8891
99.8%
2 19
 
0.2%

오르막차로관리번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
0
8910 

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 8910
100.0%

Length

2023-12-11T09:36:18.519216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:18.639127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8910
100.0%

우회도로관리번호
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
0
8910 

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 8910
100.0%

Length

2023-12-11T09:36:18.730743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:18.814070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8910
100.0%

대장초기화여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size69.7 KiB
1
8909 
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 8909
> 99.9%
0 1
 
< 0.1%

Length

2023-12-11T09:36:18.916158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:36:19.004472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8909
> 99.9%
0 1
 
< 0.1%

Interactions

2023-12-11T09:36:12.722203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.344537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.937678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.853349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.500341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.075645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.919200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.433354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.290564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.973803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.575385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.180892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:13.204885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.533610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.394152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.101616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.665724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.313092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:13.504354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.665742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.490011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.200004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.775979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.422374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:13.776117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.744364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.571903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.291345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.883533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.509355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:13.967087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:09.834674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:10.725884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.397030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:11.977853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:36:12.610994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:36:19.069451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디도로구간번호행정읍면동구간구분중용여부도로연장도로면적도로폭원구간연결도로중심선교점관리번호대장초기화여부
아이디1.0000.1270.5410.0350.0610.0860.0790.1720.1110.0830.000
도로구간번호0.1271.0000.3860.0000.0230.0000.0000.0000.0000.0000.000
행정읍면동0.5410.3861.0000.0930.1050.1610.1030.2840.2740.0000.000
구간구분0.0350.0000.0931.0000.1230.0000.1040.0000.1640.0001.000
중용여부0.0610.0230.1050.1231.0000.1540.1330.2860.0090.0000.000
도로연장0.0860.0000.1610.0000.1541.0000.9400.0390.0000.0940.000
도로면적0.0790.0000.1030.1040.1330.9401.0000.0000.1970.0670.000
도로폭원0.1720.0000.2840.0000.2860.0390.0001.0000.1420.0260.000
구간연결0.1110.0000.2740.1640.0090.0000.1970.1421.0000.0000.000
도로중심선교점관리번호0.0830.0000.0000.0000.0000.0940.0670.0260.0001.0000.000
대장초기화여부0.0000.0000.0001.0000.0000.0000.0000.0000.0000.0001.000
2023-12-11T09:36:19.200155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구간구분중용여부대장초기화여부도로중심선교점관리번호행정읍면동
구간구분1.0000.0711.0000.0000.039
중용여부0.0711.0000.0000.0000.043
대장초기화여부1.0000.0001.0000.0000.000
도로중심선교점관리번호0.0000.0000.0001.0000.000
행정읍면동0.0390.0430.0000.0001.000
2023-12-11T09:36:19.292688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디도로구간번호도로연장도로면적도로폭원구간연결행정읍면동구간구분중용여부도로중심선교점관리번호대장초기화여부
아이디1.000-0.064-0.003-0.009-0.063-0.0510.2340.0140.0280.0630.000
도로구간번호-0.0641.0000.0630.062-0.1040.2220.3520.0000.0230.0000.000
도로연장-0.0030.0631.0000.808-0.174-0.6730.0600.0000.0700.0720.000
도로면적-0.0090.0620.8081.0000.172-0.4330.0390.0430.0610.0510.000
도로폭원-0.063-0.104-0.1740.1721.0000.3120.1090.0000.1340.0200.000
구간연결-0.0510.222-0.673-0.4330.3121.0000.2500.2000.0090.0000.000
행정읍면동0.2340.3520.0600.0390.1090.2501.0000.0390.0430.0000.000
구간구분0.0140.0000.0000.0430.0000.2000.0391.0000.0710.0001.000
중용여부0.0280.0230.0700.0610.1340.0090.0430.0711.0000.0000.000
도로중심선교점관리번호0.0630.0000.0720.0510.0200.0000.0000.0000.0001.0000.000
대장초기화여부0.0000.0000.0000.0000.0000.0000.0001.0000.0000.0001.000

Missing values

2023-12-11T09:36:14.134587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:36:14.370023image/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

아이디지형지물부호도로구간번호행정읍면동도엽번호관리기관구간구분중용여부도로연장도로면적도로폭원구간연결도로중심선교점관리번호오르막차로관리번호우회도로관리번호대장초기화여부
01도로중심선7038광도면348021424D통영시차도구간미분류53.48803.118.9900001
12도로중심선7612광도면348021424C통영시차도구간일반도로(구간속성)19.64934.647.1576120001
23도로중심선7069광도면348021424C통영시차도구간미분류76.741873.1122.3600001
34도로중심선7465광도면348021425C통영시차도구간부속도로(구간속성아님)7.52286.2434.1575810001
45도로중심선7037광도면348021425C통영시차도구간우선도로(구간속성아님)9.85286.2426.7875810001
56도로중심선7581광도면348021425C통영시차도구간우선도로(구간속성)9.23286.2427.8375810001
67도로중심선6796광도면348020991B통영시차도구간미분류202.661694.578.3600001
78도로중심선6848광도면348020992C통영시차도구간연결선(가노선)4.5190.1542.2668800001
89도로중심선1835사량면348021914D통영시차도구간연결선(가노선)9.75198.7218.6417720001
910도로중심선3417사량면348021914D통영시차도구간일반도로(구간속성아님)6.44198.7217.5917720001
아이디지형지물부호도로구간번호행정읍면동도엽번호관리기관구간구분중용여부도로연장도로면적도로폭원구간연결도로중심선교점관리번호오르막차로관리번호우회도로관리번호대장초기화여부
89008901도로중심선5693용남면348021531A통영시차도구간일반도로(구간속성아님)8.89158.9517.8858000001
89018902도로중심선7024광도면348021435B통영시차도구간미분류314.26287.37.4400001
89028903도로중심선7403광도면348021435D통영시차도구간연결선(가노선)14.12289.4516.9475610001
89038904도로중심선7159광도면348021435D통영시차도구간미분류19.93218.8510.1200001
89048905도로중심선7269광도면348021435D통영시차도구간연결선(가노선)18.33704.4831.4175600001
89058906도로중심선7561광도면348021435D통영시차도구간일반도로(구간속성)6.06289.4539.4175610001
89068907도로중심선7313광도면348021435D통영시차도구간일반도로(구간속성아님)5.96289.4540.1375610001
89078908도로중심선5876용남면348021437C통영시차도구간미분류24.98388.2815.5500001
89088909도로중심선5884용남면348021437C통영시차도구간미분류43.34176.94.7900001
89098910도로중심선5862용남면348021447B통영시차도구간미분류173.181228.27.9200001